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Case Study – Methods, Examples and Guide

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A case study is a research method that involves an in-depth examination and analysis of a particular phenomenon or case, such as an individual, organization, community, event, or situation.

It is a qualitative research approach that aims to provide a detailed and comprehensive understanding of the case being studied. Case studies typically involve multiple sources of data, including interviews, observations, documents, and artifacts, which are analyzed using various techniques, such as content analysis, thematic analysis, and grounded theory. The findings of a case study are often used to develop theories, inform policy or practice, or generate new research questions.

Types of Case Study

Types and Methods of Case Study are as follows:

Single-Case Study

A single-case study is an in-depth analysis of a single case. This type of case study is useful when the researcher wants to understand a specific phenomenon in detail.

For Example , A researcher might conduct a single-case study on a particular individual to understand their experiences with a particular health condition or a specific organization to explore their management practices. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of a single-case study are often used to generate new research questions, develop theories, or inform policy or practice.

Multiple-Case Study

A multiple-case study involves the analysis of several cases that are similar in nature. This type of case study is useful when the researcher wants to identify similarities and differences between the cases.

For Example, a researcher might conduct a multiple-case study on several companies to explore the factors that contribute to their success or failure. The researcher collects data from each case, compares and contrasts the findings, and uses various techniques to analyze the data, such as comparative analysis or pattern-matching. The findings of a multiple-case study can be used to develop theories, inform policy or practice, or generate new research questions.

Exploratory Case Study

An exploratory case study is used to explore a new or understudied phenomenon. This type of case study is useful when the researcher wants to generate hypotheses or theories about the phenomenon.

For Example, a researcher might conduct an exploratory case study on a new technology to understand its potential impact on society. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as grounded theory or content analysis. The findings of an exploratory case study can be used to generate new research questions, develop theories, or inform policy or practice.

Descriptive Case Study

A descriptive case study is used to describe a particular phenomenon in detail. This type of case study is useful when the researcher wants to provide a comprehensive account of the phenomenon.

For Example, a researcher might conduct a descriptive case study on a particular community to understand its social and economic characteristics. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of a descriptive case study can be used to inform policy or practice or generate new research questions.

Instrumental Case Study

An instrumental case study is used to understand a particular phenomenon that is instrumental in achieving a particular goal. This type of case study is useful when the researcher wants to understand the role of the phenomenon in achieving the goal.

For Example, a researcher might conduct an instrumental case study on a particular policy to understand its impact on achieving a particular goal, such as reducing poverty. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of an instrumental case study can be used to inform policy or practice or generate new research questions.

Case Study Data Collection Methods

Here are some common data collection methods for case studies:

Interviews involve asking questions to individuals who have knowledge or experience relevant to the case study. Interviews can be structured (where the same questions are asked to all participants) or unstructured (where the interviewer follows up on the responses with further questions). Interviews can be conducted in person, over the phone, or through video conferencing.

Observations

Observations involve watching and recording the behavior and activities of individuals or groups relevant to the case study. Observations can be participant (where the researcher actively participates in the activities) or non-participant (where the researcher observes from a distance). Observations can be recorded using notes, audio or video recordings, or photographs.

Documents can be used as a source of information for case studies. Documents can include reports, memos, emails, letters, and other written materials related to the case study. Documents can be collected from the case study participants or from public sources.

Surveys involve asking a set of questions to a sample of individuals relevant to the case study. Surveys can be administered in person, over the phone, through mail or email, or online. Surveys can be used to gather information on attitudes, opinions, or behaviors related to the case study.

Artifacts are physical objects relevant to the case study. Artifacts can include tools, equipment, products, or other objects that provide insights into the case study phenomenon.

How to conduct Case Study Research

Conducting a case study research involves several steps that need to be followed to ensure the quality and rigor of the study. Here are the steps to conduct case study research:

• Define the research questions: The first step in conducting a case study research is to define the research questions. The research questions should be specific, measurable, and relevant to the case study phenomenon under investigation.
• Select the case: The next step is to select the case or cases to be studied. The case should be relevant to the research questions and should provide rich and diverse data that can be used to answer the research questions.
• Collect data: Data can be collected using various methods, such as interviews, observations, documents, surveys, and artifacts. The data collection method should be selected based on the research questions and the nature of the case study phenomenon.
• Analyze the data: The data collected from the case study should be analyzed using various techniques, such as content analysis, thematic analysis, or grounded theory. The analysis should be guided by the research questions and should aim to provide insights and conclusions relevant to the research questions.
• Draw conclusions: The conclusions drawn from the case study should be based on the data analysis and should be relevant to the research questions. The conclusions should be supported by evidence and should be clearly stated.
• Validate the findings: The findings of the case study should be validated by reviewing the data and the analysis with participants or other experts in the field. This helps to ensure the validity and reliability of the findings.
• Write the report: The final step is to write the report of the case study research. The report should provide a clear description of the case study phenomenon, the research questions, the data collection methods, the data analysis, the findings, and the conclusions. The report should be written in a clear and concise manner and should follow the guidelines for academic writing.

Examples of Case Study

Here are some examples of case study research:

• The Hawthorne Studies : Conducted between 1924 and 1932, the Hawthorne Studies were a series of case studies conducted by Elton Mayo and his colleagues to examine the impact of work environment on employee productivity. The studies were conducted at the Hawthorne Works plant of the Western Electric Company in Chicago and included interviews, observations, and experiments.
• The Stanford Prison Experiment: Conducted in 1971, the Stanford Prison Experiment was a case study conducted by Philip Zimbardo to examine the psychological effects of power and authority. The study involved simulating a prison environment and assigning participants to the role of guards or prisoners. The study was controversial due to the ethical issues it raised.
• The Challenger Disaster: The Challenger Disaster was a case study conducted to examine the causes of the Space Shuttle Challenger explosion in 1986. The study included interviews, observations, and analysis of data to identify the technical, organizational, and cultural factors that contributed to the disaster.
• The Enron Scandal: The Enron Scandal was a case study conducted to examine the causes of the Enron Corporation’s bankruptcy in 2001. The study included interviews, analysis of financial data, and review of documents to identify the accounting practices, corporate culture, and ethical issues that led to the company’s downfall.
• The Fukushima Nuclear Disaster : The Fukushima Nuclear Disaster was a case study conducted to examine the causes of the nuclear accident that occurred at the Fukushima Daiichi Nuclear Power Plant in Japan in 2011. The study included interviews, analysis of data, and review of documents to identify the technical, organizational, and cultural factors that contributed to the disaster.

Application of Case Study

Case studies have a wide range of applications across various fields and industries. Here are some examples:

Business and Management

Case studies are widely used in business and management to examine real-life situations and develop problem-solving skills. Case studies can help students and professionals to develop a deep understanding of business concepts, theories, and best practices.

Case studies are used in healthcare to examine patient care, treatment options, and outcomes. Case studies can help healthcare professionals to develop critical thinking skills, diagnose complex medical conditions, and develop effective treatment plans.

Case studies are used in education to examine teaching and learning practices. Case studies can help educators to develop effective teaching strategies, evaluate student progress, and identify areas for improvement.

Social Sciences

Case studies are widely used in social sciences to examine human behavior, social phenomena, and cultural practices. Case studies can help researchers to develop theories, test hypotheses, and gain insights into complex social issues.

Law and Ethics

Case studies are used in law and ethics to examine legal and ethical dilemmas. Case studies can help lawyers, policymakers, and ethical professionals to develop critical thinking skills, analyze complex cases, and make informed decisions.

Purpose of Case Study

The purpose of a case study is to provide a detailed analysis of a specific phenomenon, issue, or problem in its real-life context. A case study is a qualitative research method that involves the in-depth exploration and analysis of a particular case, which can be an individual, group, organization, event, or community.

The primary purpose of a case study is to generate a comprehensive and nuanced understanding of the case, including its history, context, and dynamics. Case studies can help researchers to identify and examine the underlying factors, processes, and mechanisms that contribute to the case and its outcomes. This can help to develop a more accurate and detailed understanding of the case, which can inform future research, practice, or policy.

Case studies can also serve other purposes, including:

• Illustrating a theory or concept: Case studies can be used to illustrate and explain theoretical concepts and frameworks, providing concrete examples of how they can be applied in real-life situations.
• Developing hypotheses: Case studies can help to generate hypotheses about the causal relationships between different factors and outcomes, which can be tested through further research.
• Providing insight into complex issues: Case studies can provide insights into complex and multifaceted issues, which may be difficult to understand through other research methods.
• Informing practice or policy: Case studies can be used to inform practice or policy by identifying best practices, lessons learned, or areas for improvement.

Advantages of Case Study Research

There are several advantages of case study research, including:

• In-depth exploration: Case study research allows for a detailed exploration and analysis of a specific phenomenon, issue, or problem in its real-life context. This can provide a comprehensive understanding of the case and its dynamics, which may not be possible through other research methods.
• Rich data: Case study research can generate rich and detailed data, including qualitative data such as interviews, observations, and documents. This can provide a nuanced understanding of the case and its complexity.
• Holistic perspective: Case study research allows for a holistic perspective of the case, taking into account the various factors, processes, and mechanisms that contribute to the case and its outcomes. This can help to develop a more accurate and comprehensive understanding of the case.
• Theory development: Case study research can help to develop and refine theories and concepts by providing empirical evidence and concrete examples of how they can be applied in real-life situations.
• Practical application: Case study research can inform practice or policy by identifying best practices, lessons learned, or areas for improvement.
• Contextualization: Case study research takes into account the specific context in which the case is situated, which can help to understand how the case is influenced by the social, cultural, and historical factors of its environment.

Limitations of Case Study Research

There are several limitations of case study research, including:

• Limited generalizability : Case studies are typically focused on a single case or a small number of cases, which limits the generalizability of the findings. The unique characteristics of the case may not be applicable to other contexts or populations, which may limit the external validity of the research.
• Biased sampling: Case studies may rely on purposive or convenience sampling, which can introduce bias into the sample selection process. This may limit the representativeness of the sample and the generalizability of the findings.
• Subjectivity: Case studies rely on the interpretation of the researcher, which can introduce subjectivity into the analysis. The researcher’s own biases, assumptions, and perspectives may influence the findings, which may limit the objectivity of the research.
• Limited control: Case studies are typically conducted in naturalistic settings, which limits the control that the researcher has over the environment and the variables being studied. This may limit the ability to establish causal relationships between variables.
• Time-consuming: Case studies can be time-consuming to conduct, as they typically involve a detailed exploration and analysis of a specific case. This may limit the feasibility of conducting multiple case studies or conducting case studies in a timely manner.
• Resource-intensive: Case studies may require significant resources, including time, funding, and expertise. This may limit the ability of researchers to conduct case studies in resource-constrained settings.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Please note you do not have access to teaching notes, integration in a mixed-method case study of construction phenomena: from data to theory.

Engineering, Construction and Architectural Management

ISSN : 0969-9988

Article publication date: 19 October 2021

Issue publication date: 27 February 2023

This study demonstrates integration within a mixed-methods case study of construction phenomena, whilst ensuring reliability and validity. This is in view of the established philosophical challenges in theory generation, whereby qualitative and quantitative methods are underpinned by divergent, almost incompatible, paradigmic assumptions.

Design/methodology/approach

The study uses a sample case study research on the phenomenon of cost overruns, supported by a coherent flow of well-articulated philosophical arguments to idealise the logic of integration. Issues of reliability and validity were resolved along these lines, by incorporating applicable criteria from both the qualitative and qualitative strands. A detailed outline and rationalisation of the stepwise approach to achieving integration are provided, from the point of design conceptualisation, data collection, analysis and further down to theory generation.

The study generated two level-1 theories by collecting numerical data on cost overruns, geotechnical index parameters and textual data on the geotechnical practices. Another level-1 theory was generated in reflexive adaptation to unanticipated social constructs emerging from the qualitative data. All level-1 theories from the quantitative and qualitative strands were triangulated to yield two “level-2 theories”: A log-regression model and a cognitive map. The approach to integration is thus explanatory sequential, and concurrent (at the second stage of transformation in the generation of level-2 theories).

Research limitations/implications

The study empirically reinforces that ontological flexibility, achievable through the use of thoughtfully designed integrated mixed-methods case studies, permits the investigation of multidimensional construction phenomena in innovative ways, relevant to provide holistic theoretical and practice-based contributions.

Originality/value

The study practically signposts a bespoke stepwise approach to integration, in a mixed-methods case study of construction phenomena, against the contextual backdrop of its relative novelty and lack of studies delving in-depth into the theoretical nitty-gritty.

• Construction
• Design conceptualisation
• Integration
• Mixed methods
• Qualitative
• Quantitative
• Reliability

Amadi, A. (2023), "Integration in a mixed-method case study of construction phenomena: from data to theory", Engineering, Construction and Architectural Management , Vol. 30 No. 1, pp. 210-237. https://doi.org/10.1108/ECAM-02-2021-0111

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• What Is a Case Study? | Definition, Examples & Methods

What Is a Case Study? | Definition, Examples & Methods

Published on May 8, 2019 by Shona McCombes . Revised on November 20, 2023.

A case study is a detailed study of a specific subject, such as a person, group, place, event, organization, or phenomenon. Case studies are commonly used in social, educational, clinical, and business research.

A case study research design usually involves qualitative methods , but quantitative methods are sometimes also used. Case studies are good for describing , comparing, evaluating and understanding different aspects of a research problem .

Table of contents

When to do a case study, step 1: select a case, step 2: build a theoretical framework, step 3: collect your data, step 4: describe and analyze the case, other interesting articles.

A case study is an appropriate research design when you want to gain concrete, contextual, in-depth knowledge about a specific real-world subject. It allows you to explore the key characteristics, meanings, and implications of the case.

Case studies are often a good choice in a thesis or dissertation . They keep your project focused and manageable when you don’t have the time or resources to do large-scale research.

You might use just one complex case study where you explore a single subject in depth, or conduct multiple case studies to compare and illuminate different aspects of your research problem.

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Once you have developed your problem statement and research questions , you should be ready to choose the specific case that you want to focus on. A good case study should have the potential to:

• Provide new or unexpected insights into the subject
• Challenge or complicate existing assumptions and theories
• Propose practical courses of action to resolve a problem
• Open up new directions for future research

TipIf your research is more practical in nature and aims to simultaneously investigate an issue as you solve it, consider conducting action research instead.

Unlike quantitative or experimental research , a strong case study does not require a random or representative sample. In fact, case studies often deliberately focus on unusual, neglected, or outlying cases which may shed new light on the research problem.

Example of an outlying case studyIn the 1960s the town of Roseto, Pennsylvania was discovered to have extremely low rates of heart disease compared to the US average. It became an important case study for understanding previously neglected causes of heart disease.

However, you can also choose a more common or representative case to exemplify a particular category, experience or phenomenon.

Example of a representative case studyIn the 1920s, two sociologists used Muncie, Indiana as a case study of a typical American city that supposedly exemplified the changing culture of the US at the time.

While case studies focus more on concrete details than general theories, they should usually have some connection with theory in the field. This way the case study is not just an isolated description, but is integrated into existing knowledge about the topic. It might aim to:

• Exemplify a theory by showing how it explains the case under investigation
• Expand on a theory by uncovering new concepts and ideas that need to be incorporated
• Challenge a theory by exploring an outlier case that doesn’t fit with established assumptions

To ensure that your analysis of the case has a solid academic grounding, you should conduct a literature review of sources related to the topic and develop a theoretical framework . This means identifying key concepts and theories to guide your analysis and interpretation.

There are many different research methods you can use to collect data on your subject. Case studies tend to focus on qualitative data using methods such as interviews , observations , and analysis of primary and secondary sources (e.g., newspaper articles, photographs, official records). Sometimes a case study will also collect quantitative data.

Example of a mixed methods case studyFor a case study of a wind farm development in a rural area, you could collect quantitative data on employment rates and business revenue, collect qualitative data on local people’s perceptions and experiences, and analyze local and national media coverage of the development.

The aim is to gain as thorough an understanding as possible of the case and its context.

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In writing up the case study, you need to bring together all the relevant aspects to give as complete a picture as possible of the subject.

How you report your findings depends on the type of research you are doing. Some case studies are structured like a standard scientific paper or thesis , with separate sections or chapters for the methods , results and discussion .

Others are written in a more narrative style, aiming to explore the case from various angles and analyze its meanings and implications (for example, by using textual analysis or discourse analysis ).

In all cases, though, make sure to give contextual details about the case, connect it back to the literature and theory, and discuss how it fits into wider patterns or debates.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Normal distribution
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Ecological validity

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

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Improving Mid-Term, Intermediate, and Long-Range Cost Forecasting for State Transportation Agencies (2020)

Chapter: 3 case study methodology.

Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

26 3 Case Study Methodology 3.1 Introduction Case studies are in-depth investigations of subjects, groups, or phenomena on their respective real- life contexts, providing researchers with a better view of the problem at hand and facilitating the detection of issues that could have passed unnoticed with other research instruments. The unique perspective of the research problem provided by a case study allows researchers to better fill intended and unintended knowledge gaps. Case studies in this research project were conducted with the state transportation agencies (STAs) of Minnesota (MnDOT), Colorado (CDOT), and Delaware (DelDOT). This chapter discusses the case study objectives and methodology, including a general description of the data collection, cleaning, and processing efforts undertaken by the research team. The chapter also introduces the different cost indexing approaches considered in the study, with a general description of the alternative Multilevel Construction Cost Index (MCCI) approach. The actual application of the case study methodology and its results are described in the following chapters. 3.2 Case Study Objective The case studies were mainly intended to contribute to the accomplishment of the second project objective stated in Section 1.1: conducting a qualitative and quantitative assessment of the current practices by comparing forecasted cost estimates with actual cost outcomes. Case study results were consolidated into the following outputs:  A protocol to perform a comparative suitability analysis of cost indexing alternatives (Chapter 4)  Guidelines to apply different cost forecasting approach (Chapter 5)  The Cost Forecasting Approach Selection Framework (Chapter 6)  Guidance to use the Cost Forecasting Toolkit (Chapter 6)  Other relevant findings and observations. 3.3 Case Study Methodology Figure 3.1 illustrates the methodology followed by the research team for each of the selected case study agencies. Each case study started with the collection and cleaning of 20 years of historical bid data, which was required to perform a long-range “forecasts vs. actual outcomes” analysis. Data gathering efforts also included historical index values from five external construction cost indexes (CCIs). Those indexes are also available to the case study agencies (and to all STAs) as possible inputs to cost forecasting processes. In the case of MnDOT and CDOT, their case studies also involved in-house CCIs. The comparative analysis in Figure 3.1 was divided into two parts. The first part consisted of a comparative suitability analysis among various cost indexing alternatives (i.e., multiple MCCI versions, external and in-house indexes), while the second part

27 was intended for the assessment and comparison of different cost forecasting methods. After completion of the three case studies, the team proceeded to synthesize all results and observations into the outputs listed above in Section 3.2. Calculations for MnDOT’s case study were repeated, assuming that only the most recent 10 years of data were available in an attempt to assess the implications of using a smaller amount of historical bid data. Figure 3.1 Case Study Methodology The historical bid data was used to develop different MCCI versions for each agency, served as a reference to assess the suitability of various cost indexing alternatives (as explained in Chapter 4), and to assess the level of accuracy and reliability of the forecasting methods under consideration (as explained in Chapter 5). The application of both parts of the comparative analysis to the three case studies allowed the research team to refine the procedures for the suitability analysis of cost indexes (first part) and for the implementation of each cost forecasting approach (second part). The refined procedures correspond to the first two outputs listed in Section 3.2. The following sections are related to the initial steps in the case study methodology shown in Figure 3.1. Those are the collection and cleaning of historical bid data, the collection of data from existing CCIs, and a general description of the MCCI system developed with the collected historical bid data. 3.4 Historical Bid Data Collection and Cleaning Table 3.1 summarizes the amount of historical bid data collected from each case study agency in terms of the number of years of data and the number of projects that provided that data. Considerable data collection efforts were required to gather 20 years of bid data from each agency. That amount of data was required to effectively assess the performance of the cost forecasting practices over long periods of time. Data from MnDOT and DelDOT was collected directly from bid tabulations posted on their websites for all projects awarded between 1999 and 2018. CDOT’s data was provided directly by the agency and comprises project awarded between 1994 and 2013. Appendix A summarizes a number of attributes from the dataset collected from each agency. Table 3.1 Summary of Collected Historical Bid Data per Agency Agency Years of Bid Data Number of Projects Minnesota DOT 1999 – 2018 (20 years) 4,299 Colorado DOT 1994 – 2013 (20 years) 2,653 Delaware DOT 1999 – 2018 (20 years) 1,530

28 The original format of the collected data was not ideal for data analysis and processing, especially to handle the large amounts of data used in this study. Part of the data cleaning efforts undertaken by the research team aimed to reformat the data into a tidy format while merging the data from all projects into a single dataset. Figure 3.2 shows a screen capture of a small portion of the tidy dataset created for MnDOT. Figure 3.2 Example of Tidy Dataset – MnDOT’s Tidy Dataset “Tidy datasets are easy to manipulate, model and visualize, and have a specific structure: each variable is a column, each observation is a row, and each type of observational unit is a table” (Wickham 2014). There is only one observational unit in this study: pay items included in the collected projects. Thus, there is only one table, with each row referring to a single pay item used in a given project. The columns correspond to all the available information associated with each pay item and its respective contract. Information provided for each pay item on each row includes, but is not limited to, item identification number, item description, awarded quantity, unit of measurement, contract identification number, project location (e.g., county, district), and unit price submitted by each bidder. 3.4.1 Outlier Detection and Removal Another critical part of the data cleaning process consisted of removing observations that do not belong with the rest of the data, generally called outliers. “Usually, the presence of an outlier indicates some sort of problem. This can be a case that does not fit the model under study, or an error in measurement” (Cho et al. 2010). In this study, the authors used two different outlier identification methods that were strategically selected and applied to serve different purposes. The first outlier detection approach used was the modified Z-score method. It was applied following the guidelines provided by Iglewicz and Hoaglin (1993), and at the Pay Item Level (to each row) in order to identify outliers among the unit prices received for the same item under the same contract. While some of those errors could correspond to typographical mistakes, or the misinterpretation of the scope contained within the unit price, a number of them are the result of unbalanced bids (Rueda 2016). “A bid is considered unbalanced if the unit rates are substantially higher or lower, in relation to the estimate and the rates quoted by other bidders” (JICA 2000). There are three main reasons that could lead a contractor to unbalance a bid: 1) to protect its intended profit or fixed cost which could be partially lost if actual quantities of work are less than the bid quantities; 2) to maximize profits by taking advantage of errors in the quantities of work

29 listed in the solicitation documents; or 3) to inflate prices for early activities to reduce financial costs (the cost of borrowing money) (FHWA 1988). Regardless of the possible ethical implications associated with unbalanced bids, this is a common practice among construction contractors, and could mislead STAs when tracking market changes over time. The second outlier detection approach was used as a secondary filter to remove outliers overlooked by the modified Z-score method. The missed outliers could have resulted from unusual project requirements that may have forced all contractors to bid outside the typical unit price ranges. Since the modified Z-score method compares unit prices for the same item under a given contract, it may find no outliers if all bidders are forced to submit unit prices substantially higher (or lower) than those typically paid by the agency for the same pay item in other projects. The second outlier detection approach used in this study was the Robust Regression and Outlier Removal method (ROUT). This method was developed by Motulsky and Brown in 2006 and combines robust regression and non-linear regression techniques to identify values that could be significantly apart from the regression equation. Detailed information about the application of the two outlier detection methods used in this study is provided in NCHRP Research Report 953: Improving Mid- Term, Intermediate, and Long-Range Cost Forecasting: Guidance for State Transportation Agencies. 3.5 Existing Cost Indexing Alternatives In addition to the different MCCI versions developed for each case study (see Section 3.6.4), the cost indexing alternatives considered by the research team included five external and two in-house CCIs. Three of those indexes, including the in-house CCIs, are classified as highway construction indexes, one is a building/vertical construction index, and two are macroeconomic indexes. Table 3.2 shows some general information about those indexes. It should be noted that MnDOT’s and CDOT’s in-house cost indexes were only used with their respective case studies. The five existing indexes include the national and the regional versions of the RSMeans CCI. Although RSMeans cost indexes are mainly intended for the vertical and commercial construction industry, this study found that RSMeans CCIs are an option considered by some STAs. Table 3.2 outlines the components (or inputs) used in the calculation of each index, as well as their applicability, which refers to their geographic scope (i.e., national, state, and regional). The final column in this table refers to the updating frequency of each index. This is how often a new index value is generated; on an annual, quarterly, or monthly basis.

30 Table 3.2 Existing Construction Cost Indexes Index Components Applicability Updating Frequency Highway Construction Federal Highway Administration: National Highway Construction Cost Index (NHCCI)  Bid data from highway construction contracts executed by STAs National Quarterly Minnesota Department of Transportation: Construction Composite Cost Index (CCI)  Excavation Index - Excavation  Structures Index - Reinforcing Steel - Structural Steel - Structural Concrete  Surfacing Index - Bituminous Pavement - Concrete Pavement Minnesota Quarterly &Annual Colorado Department of Transportation: Colorado Construction Cost Index (CCI)  Earthwork  Hot Mix Asphalt  Concrete Pavement  Structural Concrete  Reinforcing Steel Colorado Quarterly Building Construction RSMeans Construction Cost Index (CCI)  9 types of buildings - 66 construction materials - Wage rates for 21 different trades - 6 types of construction equipment National & Regional Annual Macroeconomic Indexes Bureau of Labor Statistics (BLS): Consumer Price Index (CPI)  80,000 items in a market basket of goods and services purchased by urban consumers National Monthly Bureau of Economic Analysis (BEA): Personal Consumption Expenditures (PCE) Price Index  Actual and imputed expenditures of households, including data pertaining to durable and non-durable goods and services National Quarterly 3.6 Multilevel Construction Cost Index This section presents a general description of the configuration and process to develop the different MCCI versions evaluated in this study. A more detailed and technical description of the MCCI development and updating process (i.e., mathematical and statistical procedures) is presented in the Transportation Cost Forecasting Guidebook. An MCCI consists of a group of indexes organized in a multilevel arrangement. Thus, each cost element in a program/project can be

31 individually represented by its closest matching MCCI index. After selecting the most relevant group of MCCI indexes for the scope of work under consideration, they are mathematically combined into a single scope-based CCI, which is then used to generate annual inflation rates. Costs for different programs/projects are forecasted with different sets of indexes, offering great flexibility to customize the forecasting process to the specifics of each program or project. MCCIs are built with a basket of relevant pay items selected according to the procedures described in the following section. 3.6.1 Defining Basket of Pay Items for MCCI The “basket of pay items” in the title of this section refers to the set of contract pay items used to create an MCCI. In an ideal world, an STA would be able to easily track the prices of all its contract pay items. However, most items are not frequently used, making it difficult to track their pricing variability over time. Likewise, some pay items with a low frequency of use and low impact on total project costs may not be worth monitoring. The research team performed the following steps to find the largest possible group of significant repetitive pay items to build the MCCIs for the case study agencies: 1. Discard those items whose units do not consistently refer to the same set of specifications or amounts work (e.g. each, lump sum), and keep those units that are comparable between projects (e.g. linear feet, cubic yards, tons). Pay items measured on an “each” or “lump sum” basis are usually not comparable between projects. Therefore, it is not appropriate to track price fluctuations for those items using historical unit prices. 2. Identify those pay items frequently used by the agency, ideally but not necessarily, at least once in the first and second halves of each year. For this study, the calendar year is divided into two periods as follows: Period 1 (P1) from January 1 to June 30 and Period 2 (P2) from July 1 to December 31. Although items used on a semi-annual frequency are preferred, that is not a strict requirement since that could lead to the dismissal of relevant items whose frequency of use could skip a few periods. As explained later in this chapter, the structure of the MCCI system facilitates an effective handling of missing values. 3. Discard those items that show no apparent correlation between their unit prices and their respective quantities of work. As explained in the following section, an ideal cost indexing system takes into consideration the quantity-unit price relationship to effectively quantify price fluctuations over time. Appendix B shows the final basket of pay items developed for each agency. A total of 61, 40, and 37 representative pay items remained for MnDOT, CDOT, and DelDOT, respectively, after following the three steps listed above. The number of items is less than 1% of the entire list of pay items used by those agencies. However, they could represent over 25% of their annual construction budgets. 3.6.2 MCCI Configuration and Calculation The basket of pay items selected for each agency was then used to develop several cost indexes organized in a multilevel arrangement like the one shown in Figure 3.3. This figure illustrates the

32 five-level arrangement with the 96 cost indexes developed with CDOT’s 40 representative pay items. The lowest level is the Pay Item Level, which contains one cost index for each of the selected 40 pay items. This level has the most specific cost indexes. Each of the 40 cost indexes at this level is only intended to be used on its respective pay item. Figure 3.3 Example of MCCI Configuration – CDOT MCCI Following a bottom-up calculation approach, CDOT’s indexes at the Pay Item Level were used to calculate the 28 indexes at the Sub-Division Level 1, which are less specific. Similarly, the indexes at the Sub-Division Level 1 were used to calculate 22 broader indexes at the Sub-Division Level 2, and so on until reaching the top level where a single general index was calculated at the Agency Level. All indexes were developed with a semi-annual updating frequency, with index values updated twice every year, once on June 30, and again on December 31. A semi-annual recalculation approach was selected in this study because an exploratory data analysis anticipated an inconsistent quarterly supply of data for some of the chosen pay items. Likewise, a semi-annual updating frequency was preferred over annual updates because shorter periods can better reflect the volatility of the construction market (Molenaar et al. 2013). As explained in the previous section, there are a number of factors that would prevent STAs from developing Pay Item Level indexes for all their pay items. However, if that were possible, the agency would always be able to fully meet the matching principle (see Section 1.4.1) at the project level since each pay item could be paired with an index calculated with its own historical data. On the other side of the spectrum, the worst possible matching would correspond to a situation where the Agency Level index is equally applied to all pay items. This would be the equivalent to the traditional use of a one-size-fits-all cost index, with zero flexibility to adapt to the intended scope of work. The use of an MCCI to model the fluctuation of prices for a typical project would be expected to include cost indexes from various, or all, MCCI levels. This means that MCCI users would usually be somewhere in-between the ends of the matching principle spectrum. The greater the use of indexes at lower MCCI levels, the better the matching, as well as the proportionality. As explained

33 in Section 1.4.1, the degree at which the matching principle is met would affect the ability of the cost index to meet the proportionality principle. Perfect proportionality could only be achieved after ensuing perfect matching. An appropriate identification of the maximum number of suitable MCCI pay items with the process proposed in the previous section, as well as a sound MCCI configuration would contribute to the maximization of the matching degree between the resulting cost indexes and the intended scopes of work. A sound configuration would be achieved by ensuring that all MCCI cost indexes at each level are appropriately and thoughtfully grouped to create upper level indexes. It should be noted that the discussion about the matching and proportionality principles presented in this section occurs at the project level. However, as discussed in the next section, scope-based CCIs at the program level are developed by combining project level CCIs from a selected group of sample projects. Therefore, a greater use of lower level indexes would have a similar impact at the program level, improving the degree of matching. Even though STAs execute hundreds of contracts per year, it is not possible to ensure that every item in a representative group of cost items will be used during each index period, which could result in missing index values. Unlike traditional CCIs, the multilevel arrangement of MCCIs facilitates a mechanism to avoid missing index values due to lack of data by allowing the use of corresponding upper indexes to fill the gaps. Calculations to develop MCCIs are divided into two major steps: 1) calculation of indexes at the Pay Item Level and 2) bottom-up calculation of indexes at upper levels. Step 1: Calculation of Indexes at the Pay Item Level The first step is the calculation of all indexes at the Pay Item Level. Since those are single- component indexes (calculated with a single pay item), there is no need to deal with the challenges associated with the combination of different types of index inputs. Nevertheless, to effectively track unit price fluctuations at the Pay Item Level, it is necessary to consider the economies of scale principle. “Economies of scale refers to a reduction in total cost per unit as output increases” (Betts 2007). The higher the quantities of work, the lower the unit price (Zhang and Sun 2007; Akintoye 2000). Figure 3.4 uses MnDOT’s Common Excavation pay item to illustrate the concept of economies of scale. This figure shows some awarded unit prices for that pay item (in dollars per cubic yard [CY]) paid by MnDOT during a 5-year period. As shown in this figure, the quantity-unit price relationship for this excavation activity can be modeled using a non-linear regression model. More specifically, Figure 3.4 shows a power regression curve, which is a regression approach commonly used to explain the reduction in unit prices as the quantities of work increase (Rueda 2016; Pakalapati 2018). Power regression functions were used to model unit prices for all items at the Pay Item Level.

34 Figure 3.4 MnDOT Unit Price Model for Common Excavation 2008-2012 Traditional cost indexing approaches have a limited capacity to consider the economies of scale principle. For example, a traditional indexing approach could indicate a reduction in the price of excavation if the unit price paid last year for 10,000 cubic yards of common excavation is compared against the price paid today for 200,000 cubic yards. However, the price difference could actually be due to the significant difference in the amount of excavation delivered under each contract. To address this problem, the two previous studies using the MCCI approach (Gransberg and Rueda 2014; Pakalapati and Rueda 2018) defined a number of quantity ranges for each pay item. Assuming that quantities of work within each range have comparable unit prices, they proceeded to track price changes for each quantity range. A single price change measure for each item was then estimated as a weighted average of all quantity ranges. Although the use of quantity ranges proved to be an effective approach, it required considerable quantitative efforts to establish quantity ranges, track price changes within each range, and combine measures from all quantity ranges into a single measure of change. This study has proposed an improvement to that approach by tracking the average movements of the power regression curve. For instance, if a curve for a given item moves up 10%, the index for that pay item is increased by 10%. More details about the calculation of the cost indexes at the Pay Item Level can be found in the Transportation Cost Forecasting Guidebook. Step 2: Bottom-Up Calculation of Indexes at Upper Levels The second major step in the development of an MCCI refers to bottom-up calculations to define indexes at the upper levels. To calculate the indexes on the Sub-Division Level 1, indexes at the Pay Item Level are grouped based on similar characteristics and aggregated to produce a single overall cost index per group. It means that, for CDOT’s MCCI in Figure 3.3, 28 groups were formed out of the 40 pay item cost indexes, resulting in the 28 indexes at Sub-Division Level 1. In a similar way, these 28 indexes were divided into 22 groups to produce the 22 indexes at Sub- Division Level 2, and so on until calculating a single Agency Level index with the 5 indexes from the Division Level. The combination of similar indexes into a higher-level index is just the

35 weighted average of the grouped items at the lower level. Weights for this calculation are proportional to the dollar amounts spent on the items under consideration during each indexing period. Indexes at all levels are grouped according to the coding scheme used by each STA to classify its pay items. Pay item identification numbers could communicate information about the scope, materials, and/or activities associated with each item. Thus, pay items with similar identification numbers can be assumed to be closely related. STAs’ pay item coding schemes, which usually align with their standard specification books, are also used in this study to label each of the cost indexes in the MCCI. Table 3.3 shows how some of the indexes were grouped and labeled across all CDOT’s MCCI versions. This table only shows identification labels for indexes across the bottom-up pathways of the 13 pay item indexes under Division 2. Divisions 3 to 5 also have downward ramifications, but those are not shown in Table 3.3. Table 3.3 CDOT’s MCCI Levels and Configuration Pay Item Level Sub-Division Level 1 Sub-Division Level 2 Division Level Agency Level 202-00035 202-000 202 2 1 202-00210 202-002 202-00220 202-00240 202-00250 203-00010 203-000 203 203-00060 203-00100 203-001 206-00000 206-000 206 206-00065 206-00100 206-001 206-00360 206-003 207-00205 207-002 207 - - - 3 - - - 4 - - - 5 The MCCIs developed for MnDOT and DelDOT have slightly different configurations than the one shown in Table 3.3, but those are also five-level MCCIs and the bottom-up calculation process and upward ramifications follow the same general principles. A complete version of Table 3.3, as well as the corresponding tables for MnDOT and DelDOT can be found in Appendix B. Each STA’s MCCI configuration should be adjusted according to its unique pay item classification system. Table 3.4 shows the number of cost indexes developed at each MCCI level for each agency.

36 Table 3.4 Number of Cost Indexes per Level per Case Study Agency Agency MnDOT CDOT DelDOT Agency Level 1 1 1 Division Level 12 5 7 Sub-Division Level 2 21 22 14 Sub-Division Level 1 28 28 21 Pay Item Level 61 40 37 Total No. of Cost Indexes 123 96 80 As moving from the Pay Item Level to the Agency Level, the number of digits used to identify the MCCI indexes is reduced, meaning that now the index represents a broader scope of work. In other words, the degree of detail of an index is given by its MCCI level, with the scope becoming increasingly broader at upper levels. For example, cost indexes 203-00010 and 203-00060 in Table 3.3 only represent these two specific pay items. Bid data from these two indexes was then used to calculate cost index 203-000 at Sub-Division Level 1, which is intended to represent all items that start with 203-000. In the same way, index 203 represents all pay items that start with 203 and index 2 represents all pay items starting with 2. The Division Level corresponds to the actual construction divisions from the STA’s standard specification book. All the construction divisions in CDOT Standard Specification Book are listed below (CDOT 2019). Thus, in the case of CDOT, index 2 represents the overall market behavior of earthwork activities, comprising all pay items starting with 2.  Division 2 – Earthwork  Division 3 – Bases  Division 4 – Pavements  Division 5 – Structures 3.6.3 Development of Scope-Based CCIs As mentioned before in this report, one of the most important benefits offered by MCCIs is the ability to customize the cost forecasting process to meet the specifics of each project or program through the use of scope-based CCIs. This section presents the process to generate scope-based CCIs from an MCCI at both the project and program level. Project-Specific Cost Indexes The process of generating a project-specific CCI is illustrated with the asphalt paving project shown in Table 3.5. This is a real project awarded by MnDOT. In summary, a project-specific cost index is developed by combining individual relevant MCCI indexes; one MCCI index for each anticipated pay item. Each pay item is paired with the MCCI index that best represents its scope, as indicated by its item identification number. The final project-specific CCI is just the weighted average of the selected MCCI indexes. The weight for each pay item is proportional to its contribution to the total estimated project cost. Weights are calculated using engineering estimates since actual awarded prices would not be known until awarding the project. Likewise, engineering estimates are calculated based on current prices observed at the moment of developing the project-

37 specific CCI. It should be noted that, at this point of the process, the relative relevance of each item is more important than predicting the actual prices to be submitted by the successful contractor at eh letting date. Table 3.5 Asphalt Paving Project – MnDOT Sample Project Item Number Description Units Weight MCCI Index 2021501/00010 Mobilization LS 2.3781% 2 2051501/00010 Maintenance and Restoration of Haul Roads LS 0.0001% 2 2104509/00055 Remove Twisted End Treatment EACH 0.1203% 2104 2104521/00220 Salvage Guard Rail-Plate Beam L F 0.1077% 2104521/00220 2104601/01011 Haul Salvaged Material LS 0.0595% 2104 2105501/00010 Common Excavation C Y 0.0773% 2105501/00010 2221501/00010 Aggregate Shouldering Class 1 TON 1.9326% 2 2221604/00010 Aggregate Shouldering S Y 0.1231% 2 2232501/00040 Mill Bituminous Surface (1.5\'') S Y 0.3325% 2232501/00040 2232602/00010 Milled Rumble Strips EACH 0.3266% 2232602/00010 2357606/00010 Bituminous Material for Shoulder Tack GAL 0.0195% 2357606/00010 2360501/22200 Type SP 12.5 Wearing Course Mixture (2,b) TON 82.7320% 2360501/22200 2411507/00060 Concrete End Post EACH 1.5658% 2411 2540602/00150 Mail Box Support EACH 0.1359% 2 2554501/00001 Traffic Barrier Design Special L F 0.6992% 2554501 2554501/02007 Traffic Barrier Design B8307 L F 0.3703% 2554501/02007 2554501/02038 Traffic Barrier Design B8338 L F 0.6268% 2554501/02038 2554521/00020 Anchorage Assembly-Plate Beam EACH 0.1364% 2554 2554523/00028 End Treatment-Tangent Terminal EACH 0.2610% 2554 2563601/00010 Traffic Control LS 4.1618% 2 2580603/00010 Interim Pavement Marking L F 0.5916% 2580603/00010 2582501/03008 Pavement Message (Stop Ahead) Epoxy EACH 0.1567% 258 2582502/41104 4\'' Solid Line White-Epoxy L F 2.4801% 258 2582502/41524 24\'' Stop Line White-Epoxy L F 0.0266% 258 2582502/42104 4\'' Solid Line Yellow-Epoxy L F 0.3017% 258 2582502/42204 4\'' Broken Line Yellow-Epoxy L F 0.2770% 258 TOTAL 100.00% Table 3.5 shows the weight and MCCI index selected for each item. The latter refers to the index identification labels in the last column of the table (see the configuration of MnDOT’s MCCI in Appendix B). Those labels are equivalent to the labels shown in Table 3.3 for CDOT. For example, an item like 2580606/00010 - Interim Pavement Marking in Table 3.5 has its own index at the Pay Item Level. On the other hand, item 2582502/41104 - 4\'' Solid Line White-Epoxy had to move up to the MCCI Division Level to find its best matching index. It should be noted that cost indexes at MnDOT’s Division Level are identified with three-digit labels (e.g., 258). Likewise, the identification number for all MnDOT’s pay items always start with 2; therefore, that is the single- digit label for the Agency Level index (see Appendix B). The weighted sum for the combination of the selected MCCI indexes is a simple process. It is exactly the same as the bottom-up calculation process explained in the previous section for the development of indexes at upper levels. A more detailed description of this process can be found in NCHRP Research Report 953. Table 3.6 and Figure 3.5 show an example of a project-specific CCI generated for the asphalt paving project in Table 3.5 using one of the MCCI versions

38 developed for MnDOT (see Section 3.6.4). All project- and program-specific CCIs developed with the proposed methodology are set to start with an index value of 100. Index values in the order of hundreds are commonly used in CCIs (Gransberg and Rueda, 2014). Table 3.6 Example of Project-Specific CCI – CCI for MnDOT’s Sample Asphalt Paving Project Date Index Date Index Date Index Date Index P1-1999 100.00 P1-2004 98.33 P1-2009 167.73 P1-2014 206.80 P2-1999 95.56 P2-2004 107.63 P2-2009 154.21 P2-2014 234.74 P1-2000 104.65 P1-2005 111.53 P1-2010 180.67 P1-2015 232.07 P2-2000 102.32 P2-2005 129.98 P2-2010 211.10 P2-2015 208.51 P1-2001 103.47 P1-2006 137.55 P1-2011 176.54 P1-2016 250.10 P2-2001 119.04 P2- 2006 160.08 P2-2011 135.62 P2-2016 174.95 P1-2002 114.94 P1-2007 146.38 P1-2012 202.39 P1-2017 223.16 P2-2002 100.77 P2-2007 170.48 P2-2012 168.01 P2-2017 236.04 P1-2003 100.13 P1-2008 158.46 P1-2013 205.13 P1-2018 245.06 P2-2003 104.46 P2-2008 162.91 P2-2013 224.80 P2-2018 278.82 Figure 3.5 Example of Project-Specific CCI – MnDOT’s Asphalt Paving Project Program-Specific Cost Indexes The first step in the creation of program-specific cost indexes is to understand the composition of the scope of work associated with the program. Some programs, like bridge or pavement management programs, are aimed to plan construction activities for a specific type of work. In those cases, the program-specific cost index could be a project-specific index for a carefully selected sample project intended to represent the scope of the intended program. For example, the asphalt paving project in Table 3.5 was originally identified as a good representative of MnDOT’s typical asphalt paving activities. Thus, a planning program focused only on asphalt paving could use the index shown in Table 3.6 and Figure 3.5 to determine a program-specific inflation rate.

39 The process to develop program-specific indexes for programs that involve various types of work (such as LRTPs) has a few additional steps, but it is still a simple four-step process: 1. Identify the different types of work contained in the program. 2. Approximate the percentage of the total program that corresponds to each type of work. These percentages will be used as weights in Step 4. 3. Identify a sample project that reasonably represents each type of work and develop project- specific CCIs for those projects. This step may not always be required since the agency could create and maintain a library of generic cost indexes for typical types of work. 4. Combine all project-specific indexes through a weighted average calculation using the weights defined at Step 2. The simplicity of this methodology also facilitates sensitivity analyses to evaluate multiple scenarios or to quantify the risk of having drastic changes in the anticipated distribution of work within the program. For example, Figure 3.6 shows three possible program-specific indexes that could be developed by MnDOT for a statewide pavement program that combines asphalt paving (AP) and concrete paving (CP) activities. Figure 3.6 Example of Program-Specific CCI – MnDOT Paving Program The three program-specific indexes in Figure 3.6 correspond to three different distributions of the amounts of work associated with each pavement material (50%/50%; 30%/70%; and 70%/30%). These hybrid indexes are the result of a weighted average calculation between an Asphalt Paving and a Concrete Paving CCI. The Asphalt Paving CCI is the same project-specific CCI shown in Figure 3.5, which is assumed to represent all asphalt paving activities. Similarly, the Concrete Paving CCI in Figure 3.6 is a project-specific CCI for a representative concrete paving project. All the examples of project- and program-specific CCIs presented in this chapter were developed with one of the 20 MCCI versions developed for MnDOT: a statewide MCCI calculated with all unit 80 100 120 140 160 180 200 220 240 260 280 6/ 30 /1 99 9 6/ 29 /2 00 0 6/ 29 /2 00 1 6/ 29 /2 00 2 6/ 30 /2 00 3 6/ 29 /2 00 4 6/ 29 /2 00 5 6/ 30 /2 00 6 6/ 30 /2 00 7 6/ 29 /2 00 8 6/ 30 /2 00 9 6/ 30 /2 01 0 6/ 30 /2 01 1 6/ 29 /2 01 2 6/ 30 /2 01 3 6/ 30 /2 01 4 6/ 30 /2 01 5 6/ 30 /2 01 6 6/ 30 /2 01 7 6/ 30 /2 01 8 In de x  Va lu e Date Aphalt Paving CCI Concret Paving CCI Program‐Specific CCI (50% AP; 50% CP) Program‐Specific CCI (30% AP; 70% CP) Program‐Specific CCI (70% AP; 30% CP)

40 prices submitted by both successful and unsuccessful contractors. The following section provides more information about all the MCCI versions developed for each of the three case study agencies. 3.6.4 MCCI Versions Under Consideration As mentioned before, various MCCI versions were developed for each agency in an attempt to identify the most effective one at representing the regional construction market. All MCCI versions for each agency follow the configurations in Appendix B. The difference between versions lies in their geographic scope (statewide and regional) and their type of price input: awarded unit prices (submitted by the selected contractors); average unit prices per project; median unit prices per project; and all unit prices received from both successful and unsuccessful contractors. Tables 3.7 to 3.9 outline the different MCCI versions developed for each agency. Table 3.7 MnDOT - Multilevel Construction Cost Index Classification Geographic Classification Description Statewide Multilevel Construction Cost Indexes Statewide MCCI with Awarded Unit Prices Statewide MCCI with Average Unit Prices per Project Statewide MCCI with Median of Unit Prices per Project Statewide MCCI with All Unit Prices Regional Multilevel Construction Cost Indexes Region Description North North MCCI with Awarded Unit Prices North MCCI with Average Unit Prices per Project North MCCI with Median of Unit Prices per Project North MCCI with All Unit Prices North Central North Central MCCI with Awarded Unit Prices North Central MCCI with Average Unit Prices per Project North Central MCCI with Median of Unit Prices per Project North Central MCCI with All Unit Prices South Central South Central MCCI with Awarded Unit Prices South Central MCCI with Average Unit Prices per Project South Central MCCI with Median of Unit Prices per Project South Central MCCI with All Unit Prices South South MCCI with Awarded Unit Prices South MCCI with Average Unit Prices per Project South MCCI with Median of Unit Prices per Project South MCCI with All Unit Prices

41 Table 3.8 CDOT - Multilevel Construction Cost Index Classification Geographic Classification Description Statewide Multilevel Construction Cost Indexes Statewide MCCI with Awarded Unit Prices Statewide MCCI with Average Unit Prices per Project Statewide MCCI with Median of Unit Prices per Project Statewide MCCI with All Unit Prices Regional Multilevel Construction Cost Indexes Region Description Northwest Northwest MCCI with Awarded Unit Prices Northwest MCCI with Average Unit Prices per Project Northwest MCCI with Median of Unit Prices per Project Northwest MCCI with All Unit Prices Northeast Northeast MCCI with Awarded Unit Prices Northeast MCCI with Average Unit Prices per Project Northeast MCCI with Median of Unit Prices per Project Northeast MCCI with All Unit Prices Southwest Southwest MCCI with Awarded Unit Prices Southwest MCCI with Average Unit Prices per Project Southwest MCCI with Median of Unit Prices per Project Southwest MCCI with All Unit Prices Southeast Southeast MCCI with Awarded Unit Prices Southeast MCCI with Average Unit Prices per Project Southeast MCCI with Median of Unit Prices per Project Southeast MCCI with All Unit Prices Table 3.9 DelDOT - Multilevel Construction Cost Index Classification Geographic Classification Description Statewide Multilevel Construction Cost Indexes Statewide MCCI with Awarded Unit Prices Statewide MCCI with Average Unit Prices per Project Statewide MCCI with Median of Unit Prices per Project Statewide MCCI with All Unit Prices Regional Multilevel Construction Cost Indexes Region Description North North MCCI with Awarded Unit Prices North MCCI with Average Unit Prices per Project North MCCI with Median of Unit Prices per Project North MCCI with All Unit Prices Central Central MCCI with Awarded Unit Prices Central MCCI with Average Unit Prices per Project Central MCCI with Median of Unit Prices per Project Central MCCI with All Unit Prices South South MCCI with Awarded Unit Prices South MCCI with Average Unit Prices per Project South MCCI with Median of Unit Prices per Project South MCCI with All Unit Prices The evaluation of the different MCCI versions outlined in Tables 3.7 to 3.9 was intended to determine if different geographic conditions could result in different inflationary trends in the construction industry, as well as to determine what index input would more effectively represent the local construction market. Different geographic conditions bring different challenges and

42 requirements at the program and project level. Therefore, different prices could be obtained for the same type of work or commodity in different locations. Price variability across the country or state depends on multiple factors including: the local climate and geological conditions; the availability of qualified local labor, suppliers, subcontractors, and general contractors; and the local applicable regulations (Akanni, Oke, and Akpomiemie 2015; Cuervo and Sui 2003; Kaming et al. 1997). Extensive research has been performed to investigate the factors that make current construction prices at Location A higher than those at Location B. However, little has been done to investigate if construction prices at Location A grow at higher/lower rate than those at Location B. There is a knowledge gap on how different geographic considerations affect inflation rates in the construction sector. In an attempt to address this gap, the research team developed separate MCCIs for the different geographic regions shown in Figures 3.7 to 3.9. Figure 3.7 MnDOT Geographic Regions

43 Figure 3.8 CDOT Geographic Regions Figure 3.9 DelDOT Geographic Regions The geographic classification of indexes is just an additional partition to the available data in an attempt to analyze price volatility at the regional level. Thus, DelDOT’s “Statewide MCCI with Awarded Unit Prices” was developed with historical data from all available projects across the state and using only unit prices submitted by the awarded contractors. On the other hand, DelDOT’s “North MCCI with Awarded Unit Prices” was also built with low-bid proposals, but only with bid data from Sussex County. Therefore, this MCCI and any findings from this data are only applicable to that region.

44 The regional classification done for each agency was intended to produce regions large enough to provide a constant stream of bid data, but at the same time, not too large to keep them relevant geographic-wise. The regional classification also tried to meet the apparent criteria followed by the selected agencies for the designation of their operational districts/regions. For example, each geographic region in Figure 3.5 is a combination of two of MnDOT’s operational districts. Each region in Figure 3.6 is associated with a given regional office, except for the Northeast Region, which combines CDOT’s Regions 1 and 4. On the other hand, having only three counties, DelDOT treats each county as a separate district. 3.6.5 Regional Levels of Competition in MCCIs Although little is known about the relationship between the level of competition and inflation rates in the construction industry, it does not prevent MCCIs from taking into consideration potential impacts associated with the numbers of contractors that might compete for the forecasted construction activities. A review of this issue revealed the following three main aspects influencing levels of competition in construction:  Local availability of general contractors, unions vs. right-to-work laws, and other geographic considerations.  Nature and complexity of the intended scope of work.  Seasonal changes in local construction industry. In general, impacts to the forecasting process associated with local geographic conditions, including level of competition, is accounted for, to some extent, by the geographic classification discussed in the previous section. If low levels of competition were affecting a given region, those would be reflected in the recorded unit prices from that region. Thus, any level-of-competition effects would indirectly considered in the forecasting process through the regional MCCIs, which were developed with local historical cost data. The level of competition for complex scopes of work can reasonably be expected to be considerably lower than the intensity of competition in simple projects. High technical and management requirements associated to some scopes of work could limit the letting process to a few number large construction companies with relevant experience. Likewise, some types of work could be more attractive to potential bidders due to the expectation of higher returns, increasing the number of competing contractors. Potential changes in levels of competition associated with different scopes of work can be factored into the cost forecasting process through the development of scope-based inflation rates, which is allowed by the MCCI methodology as explained in Section 3.6.5. If, for example, asphalt paving projects attract more contractors than other types of projects, and if that higher level of competition has an impact on inflation rates, that impact would be indirectly accounted for if the cost forecasting process is customized to asphalt paving projects. Finally, construction markets tend to have a seasonal behavior, which is more marked in northern states like Minnesota, where the majority of construction activities are performed during non- winter months. Although further research is required to better understand seasonal contractors’ and supplier’s pricing patterns, any possible seasonal effects on inflations rates can be considered

45 by MCCIs by matching index updating frequencies with in- and out-of-season months. Figure 3.10 clearly illustrates a seasonal pattern in MnDOT’s contracting activities with the vast majority of the annual construction program awarded during the first six months of every calendar year. Thus, any seasonal changes in levels of competition would be capture by an MCCI with a semi-annual updating frequency, as the one used in this study. Figure 3.10 Number of Contract Awarded by MnDOT per Period (2009-2018) After developing all the statewide and regional MCCIs for each agency, and after identifying the existing cost indexing alternatives to be considered in the case studies (those listed in Table 3.2), the research team proceeded to design and perform a comparative analysis to identify the most suitable cost indexing approach for each region under each case study. This comparative analysis process and the results of its application on the case study agencies are discussed in the next chapter.

Predicting the future of the construction market is always a challenging task - regardless of whether it is over the next one or 20 years - since it involves several uncertainties.

The TRB National Cooperative Highway Research Program's NCHRP Web-Only Document 283: Improving Mid-Term, Intermediate, and Long-Range Cost Forecasting for State Transportation Agencies documents the research that led to the development of a Cost Forecasting Approach Selection Framework that can assist state transportation agencies to select and implement effective mid-term (3 to 5 years), intermediate-range (up to 15 years), and long-range (more than 15 years) cost forecasting procedures.

Supplemental information to the technical report includes NCHRP Research Report 953: Improving Mid-Term, Intermediate,and Long-Range Cost Forecasting: Guidebook for State Transportation Agencies , a presentation , and videos .

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The Prince2 Methodology In The Construction Industry: A Case Study

Table of contents.

• Use of PRINCE2 products and templates
• Techniques for managing project risks
• Tailoring PRINCE2 to suit different types of projects
• Roles and responsibilities in a PRINCE2 project
• Processes of PRINCE2
• Principles of PRINCE2 Themes of PRINCE2
• PRINCE2 terminology and concepts
• PRINCE2 Salary
• PRINCE2 Exam Study Guide
• PRINCE2 Exam History
• Overview of PRINCE2 methodology
• Management of project stakeholders and communication
• Examining the relationships between the themes
• Effective leadership and management of project teams
• Application of PRINCE2 principles

Norman J. Francisco

Imagine overseeing a construction project where every detail is meticulously planned, every task is assigned to the right team member, and every milestone is successfully achieved. This level of precision and efficiency is not just a dream, but a reality with the implementation of the PRINCE2 methodology in the construction industry.

In this article, we will explore how this project management approach has revolutionized construction projects, providing a practical and effective solution to the challenges faced by construction project managers. Through a detailed case study, we will delve into the key principles and processes of PRINCE2 and how they can be applied in the construction industry.

From the initial planning stages to the successful completion of a project, we will examine the benefits, challenges, and solutions in implementing PRINCE2. Join us on this journey as we uncover the secrets to achieving success in construction projects through the PRINCE2 methodology.

Key Takeaways

• PRINCE2 methodology provides a structured approach to project management in the construction industry.
• Implementation of PRINCE2 in construction projects leads to improved project execution, decision-making, and control.
• The key principles of PRINCE2, such as continued business justification and defined roles and responsibilities, are crucial for successful implementation in the construction industry.
• Challenges in implementing PRINCE2 in construction can be addressed through strategic approaches like change management, stakeholder engagement, and resource management.

Overview of the PRINCE2 Methodology

Let’s dive into the fascinating world of the PRINCE2 methodology, which provides a structured approach to project management in the construction industry. As a construction project manager or industry expert, you understand the importance of practicality and efficiency in delivering successful projects.

PRINCE2 offers a practical solution by providing best practices for project management in construction. It emphasizes the importance of attention to detail, ensuring accuracy and precision in every aspect of the project. By implementing PRINCE2, you can benefit from its systematic approach, which includes clear project objectives, defined roles and responsibilities, effective risk management, and efficient communication channels.

These best practices allow for smoother project execution, improved decision-making, and enhanced project control. In the next section, we will explore the benefits of implementing PRINCE2 in construction projects, highlighting how this methodology can positively impact your project outcomes.

Benefits of Implementing PRINCE2 in Construction Projects

You can experience numerous advantages when implementing PRINCE2 in your construction projects. This methodology provides a structured approach to project initiation, planning, execution, monitoring, and closing, ensuring improved project control throughout the entire lifecycle. By adopting PRINCE2, construction project managers gain a comprehensive framework that enhances project management practices. It emphasizes the importance of defining roles and responsibilities, setting clear objectives, and establishing effective communication channels.

Additionally, PRINCE2 promotes increased efficiency by enabling project managers to identify and address potential risks and issues proactively. This ensures that projects are delivered on time and within budget, minimizing disruptions and delays. Implementing PRINCE2 in construction projects can lead to smoother operations, better resource utilization, and enhanced overall project performance. Ultimately, this results in higher client satisfaction and a competitive edge in the construction industry.

In the following section, we will explore a case study that demonstrates the successful implementation of PRINCE2 in a construction project.

Case Study: Successful Implementation of PRINCE2 in a Construction Project

The successful implementation of PRINCE2 in a construction project showcased the significant improvements in project control, stakeholder satisfaction, and overall performance. By adopting PRINCE2, the project team was able to overcome various implementation challenges and achieve project management success. One of the key challenges was ensuring effective communication and coordination between different stakeholders, including contractors, architects, and suppliers. PRINCE2’s emphasis on clear roles and responsibilities, regular reporting, and structured decision-making processes helped streamline communication and enhance collaboration. Additionally, the use of PRINCE2’s stage-gate approach allowed for better project control and risk management, ensuring that potential issues were identified and addressed early on. The successful implementation of PRINCE2 in this construction project demonstrates its practicality and effectiveness in delivering successful outcomes. Moving forward, it is important to understand the key principles and processes of PRINCE2 in construction to further enhance project management efficiency and effectiveness.

Key Principles and Processes of PRINCE2 in Construction

By implementing PRINCE2 in a construction project, you’ll unlock a treasure trove of key principles and processes that will serve as the foundation for a successful and well-managed endeavor.

PRINCE2, an acronym for Projects IN Controlled Environments, is a widely recognized project management methodology specifically designed for the construction industry. It provides a structured and systematic approach to project management, ensuring that projects are delivered on time, within budget, and to the required quality standards.

The key principles of PRINCE2 include:

• Continued business justification
• Learning from experience
• Defined roles and responsibilities
• Managing by stages
• Managing by exception
• Focusing on products
• Tailoring to suit the project environment

These principles are complemented by a set of processes, such as:

• Starting up a project
• Initiating a project
• Directing a project
• Controlling a stage
• Managing product delivery
• Closing a project

By following these principles and processes, construction project managers can effectively control and manage their projects, mitigating risks and maximizing success.

Now, let’s explore the challenges and solutions in implementing PRINCE2 in the construction industry.

Challenges and Solutions in Implementing PRINCE2 in the Construction Industry

Overcoming hurdles in adopting PRINCE2 can be a challenging task, but with the right strategies, construction projects can flourish and achieve unprecedented success. Implementing PRINCE2 in the construction industry requires careful consideration of the unique challenges and finding practical solutions.

Here are three key challenges and their corresponding solutions:

Change management: The construction industry is constantly evolving, and managing changes effectively is crucial. Establishing a change control board can help monitor and assess changes, ensuring they align with project objectives. Regular communication and training sessions can also promote stakeholder buy-in and facilitate a smooth transition.

Stakeholder engagement: Engaging stakeholders throughout the construction project is vital for success. Creating a stakeholder engagement plan that identifies key stakeholders and defines their roles and responsibilities can foster collaboration and mitigate potential conflicts. Regular communication channels, such as meetings and progress reports, should be established to keep stakeholders informed and involved.

Resource management: Construction projects require efficient allocation and management of resources. Implementing resource management tools, such as resource leveling and critical path analysis, can help optimize resource utilization and ensure project deadlines are met. Regular monitoring and evaluation of resource usage can identify bottlenecks and allow for timely adjustments.

By addressing these challenges with strategic approaches, construction projects can successfully implement PRINCE2 and achieve their goals.

Frequently Asked Questions

How does the prince2 methodology compare to other project management methodologies commonly used in the construction industry.

When comparing the PRINCE2 methodology to other project management methodologies commonly used in the construction industry, one notable comparison is with Agile methodology.

While Agile focuses on adaptability and flexibility, PRINCE2 emphasizes a structured and controlled approach.

PRINCE2 offers several benefits for construction projects, such as clear project governance, defined roles and responsibilities, and efficient project monitoring.

Its practical approach ensures that construction projects are executed with precision, attention to detail, and a focus on delivering successful outcomes.

Can the PRINCE2 methodology be customized to fit the specific needs and requirements of different construction projects?

Yes, the PRINCE2 methodology can be customized to fit the specific needs and requirements of different construction projects.

For example, a construction project manager can tailor the methodology to accommodate the unique scope, timelines, and resources of a high-rise building project.

The customization options offered by PRINCE2 allow for flexibility in adapting the methodology to various project sizes and complexities.

However, it’s important to note that while customization offers benefits such as improved project control and stakeholder engagement, it also presents challenges in terms of maintaining consistency and ensuring effective communication across project teams.

Are there any specific training or certification requirements for individuals involved in implementing the PRINCE2 methodology in construction projects?

When implementing the PRINCE2 methodology in construction projects, there are specific training and certification requirements that individuals must meet.

Training requirements include attending PRINCE2 courses that provide a comprehensive understanding of the methodology’s principles, themes, and processes. These courses cover topics such as project initiation, planning, execution, and monitoring.

Certification requirements involve passing the PRINCE2 examination, which assesses the individual’s knowledge and application of the methodology.

By meeting these requirements, individuals can effectively implement PRINCE2 in construction projects, ensuring efficient and successful project management.

How does the PRINCE2 methodology address risk management in construction projects?

When it comes to risk management in construction projects, the PRINCE2 methodology takes a unique and ironic approach.

It starts by identifying and assessing risks, which is a novel concept in the construction industry.

Then, it moves on to the crucial step of risk response planning, where it actually plans how to respond to those risks.

This practical and detail-oriented approach ensures that construction project managers are well-prepared to handle any potential challenges that may arise.

What are some examples of construction projects that have successfully implemented the PRINCE2 methodology, and what were the key factors that contributed to their success?

Successfully implementing the PRINCE2 methodology in construction projects requires key factors for success. Examples of such projects include large-scale infrastructure developments and high-rise building construction.

Effective stakeholder engagement, thorough risk management, and clear project objectives were key factors that contributed to their success. By adopting a practical approach and utilizing PRINCE2 principles, these projects achieved efficient project delivery and effective communication among the project team.

Attention to detail was crucial in ensuring accurate project documentation, timely decision-making, and successful project outcomes.

In conclusion, implementing the PRINCE2 methodology in the construction industry offers numerous benefits.

The case study showcased the successful utilization of PRINCE2 in a construction project, highlighting its key principles and processes.

Despite challenges, such as adapting to industry-specific jargon and technical details, solutions can be found through a practical and detail-oriented approach.

Construction project managers must prioritize practicality, efficiency, and effectiveness to achieve successful project outcomes.

By paying close attention to detail and utilizing industry best practices, construction projects can be executed with precision and accuracy.

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• Published: 27 March 2024

Application and configuration analysis of electric muck transfer equipment in plateau railway tunnel: a case study in southwest China

• Xiaoxu Yang 1 ,
• Yuming Liu 1 ,
• Kai Liu 1 ,
• Jianying Wei 2 ,
• Guangzhong Hu 1 &
• Shifan Pei 1  

Scientific Reports volume  14 , Article number:  7222 ( 2024 ) Cite this article

Metrics details

• Environmental sciences
• Environmental social sciences

The burgeoning development of railway construction in plateau regions of southwest China necessitates innovative and environmentally sustainable approaches, particularly in the realm of tunnel construction, where the transfer of muck poses significant operational and environmental challenges. This research, pivoting around the application and configuration of electric muck transfer equipment in plateau railway tunnels, seeks to dissect the potentialities and impediments of transitioning from conventional diesel-powered machinery to electric alternatives, with a spotlight on mitigating environmental impacts and enhancing operational efficiency. Through an analytical lens, the study employs a case study methodology, leveraging data and insights from existing electric equipment models and their applications, provided by major manufacturers in China, to weave a comprehensive narrative around the practicalities, specifications, and challenges embedded in the adoption of electric machinery in plateau environments. The findings unveil a nuanced landscape, where the environmental and operational advantages of electric equipment are juxtaposed against a backdrop of technological, financial, and infrastructural hurdles, thereby crafting a complex tapestry of opportunities and challenges. The research further extrapolates policy recommendations and practical guidelines, advocating for a harmonized amalgamation of governmental policies, technological advancements, and strategic planning to navigate through the identified challenges and optimize the integration of electric equipment in tunnel construction practices. Envisaging future research pathways, the study underscores the criticality of perpetuating technological innovations, policy adaptations, and interdisciplinary research to further refine and enhance the application of electric muck transfer equipment in plateau railway tunnel projects, thereby contributing to the broader narrative of sustainable construction practices in challenging terrains.

Introduction

Railways, often regarded as the lifeblood of China's national economy, serve as crucial infrastructure and play a pivotal role in major livelihood projects. Their significance in shaping China's socio-economic landscape cannot be overstated 1 , 2 , 3 , 4 . Over the years, the methodologies employed in railway tunnel construction in China have witnessed a transformative evolution, culminating in a robust and mature technical system. A landmark in this journey was the construction of the Dayaoshan Tunnel of the Hengyang Guangzhou Double Track Railway in the 1980s. This era marked a paradigm shift from traditional manual tunneling methods, reminiscent of the "one man, one pick" approach, to a more sophisticated mechanized construction mode 5 . This transition paved the way for China to delve into innovative construction methods, blending drilling, blasting, and mechanized techniques, thereby enhancing the efficiency, quality, and safety of tunnel construction 6 , 7 , 8 , 9 , 10 , 11 .

However, as China's infrastructural ambitions expanded into its remote and challenging mountainous terrains, the challenges multiplied. The surge in high-altitude railway tunnels and blasting projects brought to light the limitations of conventional diesel-powered mechanical equipment. Their diminished dynamic and economic performance, leading to significant power losses, rendered them inadequate for high-standard construction, posing substantial technical challenges for mechanized drilling and blasting operations.

The essence of efficient tunnel construction lies in the judicious selection and configuration of machinery. Over the years, numerous scholars have ventured into this domain, aiming to devise optimal equipment configurations for plateau railway tunneling. Their endeavors have been directed towards harnessing established equipment systems and fine-tuning selection strategies in light of available technological advancements 12 , 13 , 14 , 15 . For instance, Xiang and Yuan's pioneering work laid down a comprehensive mechanical equipment coordination and operational blueprint tailored for large-scale passenger-only line tunnels, encompassing diverse processes from excavation to lining 16 . Song and Xia's innovative carbon emission model, rooted in life-cycle assessment and the carbon emission factor method, offers a nuanced perspective on the environmental footprint of tunneling mechanisms 17 . Sun et al.'s insights into tunnel slag discharge techniques, especially their proposal of a continuous band slag discharge method, underscore the potential benefits of modern slag extraction systems, especially in challenging terrains like frozen soils and plateaus 18 .

While past research has predominantly focused on optimizing conventional fuel oil equipment configurations or dissecting specific technologies tailored for plateau environments, there remains a conspicuous void in systematic research on electric construction equipment, especially in highly mechanized configurations 19 . Electric equipment, with its low energy costs, reduced maintenance overheads, and zero-emission capabilities, offers a promising alternative. Its advantages are particularly pronounced in plateau regions, where climatic constraints amplify the benefits of electric appliances in railway tunnels 20 . Furthermore, given the significant time and machinery resources consumed by tunneling muck transfer operations, coupled with their environmental implications, the modern development paradigm necessitates innovative approaches in the application and configuration of electric equipment for muck transfer in plateau railway tunnels.

Requirements of sustainable development concept

In the wake of China's commitment to peak its carbon emissions before 2030 and achieve carbon neutrality before 2060, known as the 'Dual Carbon' targets 21 , 22 , the nation has been steering its industries towards more sustainable practices. The Ministry of Industry and Information Technology, in 2020, initiated an action plan to expedite the electrification of public sector vehicles, including construction machinery and heavy trucks, thereby aligning with the national agenda to mitigate carbon emissions. Table 1 encapsulates a series of policies and regulations, reflecting China's strategic approach towards embracing green and low-carbon technologies across various sectors, including transport and manufacturing. These policies not only underscore the importance of adopting new energy and clean energy vehicles but also emphasize enhancing charging infrastructure and promoting green products and technologies 23 .

The transition to electric equipment in construction, especially in tunneling operations, is further necessitated by the changing demographics of the Chinese labor force 24 . With an aging population and increasing labor costs, there is a growing need for more efficient, less labor-intensive construction methods. Electric muck transfer equipment offers a solution to these challenges, providing a cleaner, safer, and more sustainable alternative to traditional diesel-powered machinery 25 . While acknowledging the significant strides made in electric vehicle technology and infrastructure, it's crucial to place electric construction equipment within a context that considers multiple alternatives, including hybrid and hydrogen fuel cells. This study examines electric equipment's viability against such alternatives, considering factors like energy efficiency, environmental impact, and adaptability to plateau conditions.

Plateau climate and environmental limitations

Tunnel construction, particularly in plateau regions, is inherently energy and resource-intensive, leading to significant greenhouse gas emissions 26 , 27 . A primary source of these emissions is the diesel-powered machinery commonly used in drilling and blasting methods, such as excavators, loaders, and dump trucks. These machines, while efficient at lower altitudes, face operational challenges in plateau environments due to the thin air and low oxygen levels.

At lower altitudes, the abundance of oxygen mitigates the concentration of harmful gases emitted by construction machinery, resulting in relatively lower pollution levels. However, in plateau regions, the situation is markedly different (see Table 2 ). The reduced oxygen content in the air leads to inefficient combustion in diesel engines, significantly increasing the emission of hazardous gases such as nitrogen oxides, oxygenated hydrocarbons, and particulates 28 , 29 . This not only poses serious health risks to the construction workforce but also complicates the ventilation requirements in tunnel construction, impacting overall efficiency and safety.

Sketch of variation of oxygen content in high-altitude tunnel with footage depth 31 .

At the same time, the problem of oil machinery and equipment competing for oxygen with front-line workers in the plateau area also cannot be ignored, due to the continuous oxygen consumption of construction personnel and mechanical equipment in the tunnel, the oxygen content in the tunnel at high altitude will gradually decrease with the increase of tunnel footage, as shown in Fig.  1 . Excessive hypoxia can lead to physical discomfort, fainting, and even death for workers 32 , 33 , adding to the strain of long-distance ventilation in the plateau tunnels.

Currently, electric equipment, primarily powered by lithium iron phosphate batteries, offers a sustainable alternative. By substituting internal combustion engines with electric motors, electric equipment reduces power losses unaffected by air pressure and oxygen fraction changes 34 , 36 . This advantage is particularly significant in tunnels above 3000 m altitude, where electric muck removal equipment surpasses traditional diesel-powered machinery in operational efficiency. Electric drive systems do not consume oxygen during operation, and with zero exhaust emissions, they address the issue of competing for oxygen with workers, alleviating ventilation and oxygenation pressures in high-altitude tunnel construction 35 , 37 . Moreover, field data indicate that electric equipment generates significantly lower external noise levels, 20–30 dB lower than comparable diesel machinery, effectively improving the work environment.

The plateau climate presents unique challenges that exacerbate the limitations of diesel-powered equipment. Electric equipment, with its inherent advantages in energy efficiency and lower emissions, offers a compelling alternative. This study aims to fill the research void by systematically comparing the performance, environmental impact, and practicality of electric versus diesel equipment in these demanding environments.

Equipment research and development status

Electric muck transfer equipment.

The vigorous development of electric vehicles has led to the development of power batteries and electric motors, and has also made it possible to electrify construction machinery. Compared with electric vehicles, electric construction machinery and equipment is still in its infancy 36 , 37 . Currently, tunnel equipment can be divided into three categories according to their power source: (1) Pure electric equipment: common in secondary lining equipment, such as invert trestle, waterproof board trolley, lining trolley, etc. Such equipment have no requirements on the oxygen content of the air in which they operate and do not pollute the tunnel environment. (2) Diesel-electric hybrid equipment: widely used in advance geological prediction, excavation operation, initial lining, the use of diesel power walking, electric power work. The walking time of such equipment takes up a small proportion compared to the working time, which has a slight effect on the pollution and oxygen consumption in the tunnel. (3) Pure diesel power equipment: common in muck transfer equipment, such as excavators, loaders, dumpers, etc. Such equipment is extra sensitive to oxygen and pressure changes in the working environment, and will produce additional toxic gas due to insufficient fuel combustion, causing serious pollution to the tunnel. In addition, the muck transfer line is still dominated by purely diesel power equipment. Muck transfer operations accounted for approximately half of the total cycle time throughout the drilling and blasting method. Therefore, plateau railway tunnel construction for electric equipment demand, mainly concentrated in muck transfer lines.

However, there is no complete set of electric muck transfer equipment for sale in China, and the research and development of related enterprises is concentrated in the small and medium-sized stage, which cannot cover all the working conditions of the plateau railway for the time being. According to the current status of electric equipment products of major manufacturers in China (see Table 3 ), it can be found that compared with traditional diesel power equipment, the specifications and models of electric excavators and loaders are relatively simple, while the specifications and models of electric dump trucks are relatively various.

Charging infrastructure

Charging pile

Charging infrastructure is an essential supporting guarantee for the efficiency of electric equipment. Currently, the construction technique of fixed charging piles is relatively mature. It is feasible to construct centralized charging stations for electric equipment outside the tunnels and configure high-power double-gun quick charging piles. China has also formulated a series of national, industrial and related corporate standards and norms for charging technology. In the short term, shortening charging times and improving endurance are undoubtedly the technological priorities for the market.

The charging pile has a low construction cost and can be distributed flexibly according to the distribution of vehicles. At the same time, one charging pile can satisfy 3–4 vehicles for a whole day's operation. Depending on the operation conditions of the vehicles at the project site, energy can be replenished by exploiting the waiting time for loading and unloading materials and the rest time of the drivers. Equipped with high-power charging piles, the energy can be replenished by 40–50% in half an hour and the driving endurance of vehicles can be increased by 50-70 km. When the tunneling distance is not lengthy, the charging pile can be fixed outside the tunnel. As the tunneling distance increases, it can be considered to fix the charging pile in the secondary lining area of the tunnel and push forward with the tunneling (see Fig.  2 ). However, it is necessary to further verify the reliability of the supporting charging piles in the humid, high temperature and relatively muddy environment of the tunnel and how the structural firmness meets the construction requirements under frequent movement.

Battery swap station

Layout of charging piles in the secondary lining area.

Compared with charging facilities, the construction of electricity exchange facilities is relatively in the early stages of development. In May 2020, the power station was included in the Government Work Report for the first time, as an vital part of the improved infrastructure. In July 2020, the Ministry of Industry and Information Technology made it clear that it supports electric switching services and encourages auto companies to develop electric switching models. Later that year, at the Huaneng Yimin coal and electricity open-pit mine, China's first set of electric heavy-duty trucks with intelligent power shift systems went through a 100-day high-intensity trial operation, which started the process of electric energy replacement for China's large construction vehicles (see Fig.  3 ).

The first intelligent electrical change system for electric heavy truck in China.

The one-time investment cost of the battery swap station is relatively costly (about five to six million CNY), and it covers a large area (about 150–200 square meters), which requires centralized operation. When the number of battery-swap mode machines exceeds 50, the size economy effect can be generated. The electric-changing mode can be considered in the operation scenarios that require high charging efficiency.

• Application and configuration analysis

Project overview

As a new product, electric muck transfer equipment is rarely used in the engineering construction sector, and is still in the trial phase in the railway tunnel construction sector 38 , 39 . The project under study is located in a challenging terrain in the plateau mountainous region of southwest China. This tunnel, a crucial part of the railway network expansion in the region, spans approximately 20 km in length. It features a maximum buried depth exceeding 1000 m and is situated at an average elevation of over 3500 m. These geographical and environmental conditions present unique challenges, including significant variations in temperature, reduced oxygen levels, and complex geological structures.

In this project, electric muck transfer equipment, a relatively new innovation in railway tunnel construction, was employed. The equipment, sourced from mainstream manufacturers, matches the traditional diesel-powered equipment in specifications, performance, safety, and reliability. The construction enterprise adopted electric excavators, loaders, dump trucks, and supporting charging infrastructure, creating a comprehensive demonstration of electric muck transfer in tunnel construction.

The operational cycle of the project typically involves three construction phases every two days. Each phase includes a muck transfer duration of approximately three hours, handling about 260 cubic meters of muck. This translates to an average daily working time of 4.5 h for the muck transfer equipment, with an average daily muck transfer volume of 390 cubic meters, or an hourly rate of 86.67 m 3 /h.

Preliminary observations indicate that the performance of the electric equipment aligns closely with that of traditional diesel-powered machinery. For the purpose of a subsequent economic analysis, we have made certain assumptions: excavators and loaders are considered over a depreciation period of ten years, dump trucks over five years, and battery life is also estimated at five years. These calculations do not take into account the salvage value of the equipment. These parameters are set to construct a framework for a detailed economic analysis, which will be elaborated in the following sections.

The relationship between indicators is shown in Fig.  4 .

Equipment input cost ( C ei )

The relationship between indicators.

C ei is calculated according to the following formula:

where q refers to the quantity of equipment purchased and U p refers to the unit price of equipment.

Total equipment input cost ( C tei )

Total equipment input cost includes equipment input cost ( C ei ), battery replacement cost ( C br ) and energy supplement facilities cost ( C esf ). Therefore, the total equipment input cost ( C tei ) can be expressed as follows:

Daily equipment depreciation ( DED )

DED is calculated according to the following formula:

where y represents the years of depreciation.

Amortization of total equipment input cost ( AC tei )

AC ei is calculated according to the following formula:

where m 1 represents the daily amount of muck transfer.

Working energy consumption cost ( C wec )

C wec is calculated according to the following formulas:

where P e represents the price of electricity per kilowatt-hour; P f represents the price of fuel per liter; B c represents battery capacity; T v represents tank volume; and E represents endurance.

Among them, formula 6 applies to electric equipment and formula 7 applies to diesel power equipment. According to the general situation of the project, the price of electricity per kilowatt-hour is CNY 0.85 and the price of fuel per liter is CNY 8.00.

Amortization of working energy consumption cost ( AC wec )

( AC wec ) is calculated according to the following formulas:

where m 2 represents the amount of muck transfer per hour.

Amortization of total cost ( AC t )

The amortization of total cost ( AC t ) includes amortization of equipment input cost ( AC tei ) and amortization of working energy consumption cost ( AC wec ). Because the trial period of the equipment is not long, the maintenance cost is not considered in this analysis. Therefore, the Amortization of total cost ( AC t ) can be expressed as follows:

Table 4 meticulously unfolds a comparative analysis between the electric excavator (XE215E) and its diesel-powered counterpart, each embodying distinct operational and economic characteristics that warrant an in-depth exploration within the context of tunnel construction.

Equipment parameters

The electric excavator, while showcasing a formidable maximum mechanical output power of 215 kW, significantly eclipses the 135 kW of its diesel equivalent, thereby ensuring a potent power delivery without compromising on the intrinsic excavation capabilities, as both models exhibit an identical bucket digging force of 149 kN. However, the electric excavator, with a length of 10,050 mm, surpasses its diesel counterpart by 425 mm, potentially introducing navigational complexities within the restricted confines of tunnel environments, thereby necessitating strategic operational planning to safeguard both efficiency and safety. Moreover, the endurance time of the electric excavator, approximately one-third of the diesel model, demands frequent and strategically planned charging sessions to mitigate potential workflow disruptions.

Economic considerations

While the electric excavator necessitates a considerably higher initial investment, approximately 1.55 times that of the diesel variant, its working energy consumption cost is less than 50%, heralding potential long-term operational savings. Despite the initial financial outlay, the electric excavator, over an extended period of use, emerges as a more economically prudent option, with cost amortization approximately 18% lower than the diesel power excavator, thereby presenting a compelling economic narrative for its adoption.

In-depth analysis

The electric excavator, despite its frequent charging requisites, operates with zero emissions, aligning seamlessly with global sustainability initiatives and potentially offering long-term economic and environmental dividends, especially in protracted projects. The frequent charging requirements necessitate astute strategic planning to seamlessly integrate charging sessions into the operational workflow, thereby minimizing disruptions and adhering to project timelines. Furthermore, the zero-emission operation of the electric excavator enhances the safety and health conditions within the tunnel, mitigating workers' exposure to harmful emissions and contributing to a healthier, more conducive working environment.

In summation, the electric excavator, despite presenting initial adaptation and investment challenges, aligns impeccably with sustainability, long-term economic viability, and enhanced health and safety conditions, thereby substantiating its potential as a formidable alternative to traditional diesel-powered excavators in tunnel construction projects amidst the global pivot towards sustainable practices.

Table 5 unfolds a comprehensive comparison between the electric loader (856E-MAX) and its diesel-powered equivalent (856H-MAX), each embodying distinct operational and economic characteristics that warrant a thorough exploration within the context of tunnel construction.

The electric loader, with a maximum mechanical output power of 180 kW, slightly outperforms the diesel-powered loader, which delivers 168 kW, thereby ensuring a potent power delivery without compromising on intrinsic loading capabilities. However, it's crucial to note that the electric loader exhibits smaller maximum breakout and tractive forces compared to its diesel counterpart, potentially influencing its performance in certain operational contexts. Additionally, the electric loader, extending to 8,980 mm, surpasses its diesel counterpart by 307 mm, potentially introducing navigational complexities within the restricted confines of tunnel environments, thereby necessitating strategic operational planning to safeguard both efficiency and safety. Moreover, the endurance time of the electric loader, approximately one-third of the diesel model, demands frequent and strategically planned charging sessions to mitigate potential workflow disruptions.

While the electric loader demands a notably higher initial investment, approximately 1.51 times that of the diesel variant, its working energy consumption cost is less than 40%, heralding potential long-term operational savings. Despite the initial financial outlay, the electric loader, over an extended period of use, emerges as a more economically prudent option, with cost amortization approximately 20% lower than the diesel power loader, thereby presenting a compelling economic narrative for its adoption.

The electric loader, despite its frequent charging requisites, operates with zero emissions, aligning seamlessly with global sustainability initiatives and potentially offering long-term economic and environmental dividends, especially in protracted projects. The frequent charging requirements necessitate astute strategic planning to seamlessly integrate charging sessions into the operational workflow, thereby minimizing disruptions and adhering to project timelines. Furthermore, the zero-emission operation of the electric loader enhances the safety and health conditions within the tunnel, mitigating workers’ exposure to harmful emissions and contributing to a healthier, more conducive working environment.

In summation, the electric loader, despite presenting initial adaptation and investment challenges, aligns impeccably with sustainability, long-term economic viability, and enhanced health and safety conditions, thereby substantiating its potential as a formidable alternative to traditional diesel-powered loaders in tunnel construction projects amidst the global pivot towards sustainable practices.

Table 6 provides a detailed comparison between the electric dump truck (SYM3251ZZX3BEV319) and its diesel-powered counterpart (SYM3257ZZX1E), each embodying distinct operational and economic characteristics that warrant a thorough exploration within the context of tunnel construction.

Power Dynamics: The electric dump truck, with a maximum mechanical output power of 400 kW, surpasses the 360 kW offered by the diesel-powered dump truck, ensuring a robust power delivery while navigating through the tunnel environments.

Weight and Load Capacity: The electric dump truck, with a curb weight of 16.80 t, is notably heavier than its diesel counterpart, which weighs 12.43 t. This additional weight, attributed to the batteries and other components, reduces the load capacity of the electric dump truck by approximately 4 tons (or about 2 cubic meters) of tunnel dregs per trip under the maximum allowable total mass constraint. Consequently, to achieve equivalent workload, the number of electric dump trucks needs to be augmented by 25%.

Initial Investment and Operational Costs: The electric dump truck demands a significantly higher initial investment, approximately 2.5 times that of the diesel variant, especially considering the need to increase the number of vehicles to achieve the same workload. Despite the electric dump truck presenting lower working energy consumption costs, the elevated initial investment and increased vehicle quantity result in a total cost amortization that is higher than the diesel power truck.

Environmental and Operational Efficiency: The electric dump truck, while operating with zero emissions and aligning with global sustainability initiatives, demands strategic operational planning to ensure that the reduced load capacity and increased vehicle requirements do not adversely impact the project timelines and workflow.

Strategic Planning: The reduced load capacity of the electric dump truck necessitates astute strategic planning to seamlessly integrate the increased vehicle requirements into the operational workflow, thereby minimizing disruptions and adhering to project timelines.

Long-term Economic Viability: The higher initial investment and operational complexities of the electric dump truck, when considered in the context of long-term projects, can potentially offset the initial investment, presenting a compelling case for its adoption in tunnel construction projects, especially considering the global shift towards sustainable practices.

In conclusion, the electric dump truck, while presenting initial challenges in terms of adaptation, investment, and operational planning, aligns impeccably with sustainability and presents a potential alternative to traditional diesel-powered dump trucks in tunnel construction projects amidst the global pivot towards sustainable practices. However, its adoption necessitates meticulous planning and strategic considerations to ensure that the operational and economic implications are navigated effectively to harness its potential benefits.

In summary, the exploration and analysis of electric equipment in the context of tunnel construction, especially within the challenging environments of plateau tunnels, reveal a nuanced tapestry of economic, environmental, and health-related considerations. The preceding sections, 4.1 through 4.4, have meticulously dissected the comparative attributes of electric and diesel-powered equipment, shedding light on their respective advantages and limitations in both operational and economic spectrums.

While the initial financial outlay for electric equipment is notably higher, attributed to the elevated equipment input costs and the financial commitment to energy replenishment infrastructures, it is imperative to recognize the long-term economic and non-economic benefits that unfold. The diminished working energy consumption costs and the significant carbon reduction impact of electric equipment underscore a commitment to sustainability and environmental stewardship, which is becoming increasingly pivotal in contemporary construction practices.

Moreover, the deployment of electric equipment heralds a marked improvement in the tunnel’s air quality by mitigating exhaust emissions from fuel equipment. This not only alleviates the operational necessity and associated costs of tunnel ventilation but also crafts a healthier and safer working environment for construction personnel. The safeguarding of worker health, while not directly quantifiable in a financial matrix, is of paramount importance and presents an ethical and regulatory consideration that is integral to sustainable construction practices.

The trials involving electric muck transfer equipment, as detailed in this chapter, have not only substantiated an enhancement in the working environment and operational efficiencies within the plateau tunnel construction but have also demonstrated a tangible alignment with energy-saving and emission reduction objectives. Thus, while the economic investment in electric equipment is palpable, the amalgamation of environmental, health, and potential long-term operational benefits presents a compelling narrative for its adoption. This exploration, therefore, transcends its immediate context, offering valuable insights and reference points for future projects that seek to navigate the intricate balance between economic viability, environmental sustainability, and occupational health in tunnel construction within challenging terrains.

Conclusions and perspectives

Research summary and limitations.

The exploration into the application of electric equipment in plateau railway tunnel projects has unveiled a myriad of insights and potential pathways towards more sustainable, efficient, and environmentally responsible construction practices. The research underscored the pivotal role of electric equipment in mitigating the multifaceted challenges posed by conventional fuel-powered machinery, particularly in the context of plateau environments characterized by reduced oxygen levels, extreme temperatures, and sensitive ecological conditions.

Through a detailed examination of various policies, technological advancements, and practical applications, the research illuminated the potential of electric equipment to not only align with China's 'Dual Carbon' targets but also to navigate through the operational, environmental, and socio-economic challenges inherent in plateau railway tunnel construction. The adoption of electric equipment, particularly in muck transfer operations, was identified as a crucial strategy to reduce pollution, enhance worker safety and health, and improve operational efficiency amidst the challenging plateau conditions.

The implications of this research extend across multiple dimensions. For the research community, this study contributes to the burgeoning field of sustainable construction practices by providing empirical evidence on the efficacy of electric equipment in challenging environments. It lays the groundwork for further exploration into alternative energy solutions within the construction industry. For practice, the findings offer actionable insights for construction project managers and policymakers looking to reduce environmental impact and enhance efficiency in plateau railway tunnel projects. The adoption of electric muck transfer equipment, as demonstrated in our study, provides a tangible pathway towards achieving China's 'Dual Carbon' goals within the construction sector. For society, this research underscores the potential for significant environmental benefits, including reduced greenhouse gas emissions and lessened ecological disturbance, contributing to a more sustainable future.

While the research provides a comprehensive overview and analysis of the current situation, several limitations must be acknowledged:

Technological maturity：

The research is constrained by the current technological maturity and availability of electric construction machinery and equipment. The rapidly evolving nature of technology may introduce new solutions and challenges that are not addressed in the present study.

Data availability

The availability and accessibility of data, particularly pertaining to the real-world application, performance, and challenges of electric equipment in various tunneling projects, are limited. This restricts the depth and breadth of the analysis and findings.

Diverse Working Conditions: The research primarily focuses on the application of electric equipment in plateau railway tunnel projects, which may not fully encapsulate the diverse range of working conditions and challenges encountered in different geographical and environmental contexts.

Economic and Policy Dynamics: The economic and policy dynamics are subject to change, influenced by various factors like technological advancements, market conditions, and governmental policies, which might impact the feasibility and applicability of the findings in future contexts.

The aforementioned limitations necessitate a cautious and adaptive approach to applying the findings and recommendations of the research in practical scenarios. Future research and applications should consider the evolving technological landscape, emerging data, and changing economic and policy dynamics to ensure the relevance and efficacy of strategies and solutions in real-world contexts.

In light of these limitations, the findings and recommendations of the research serve as a foundational framework, providing valuable insights and directions for further exploration, development, and application of electric equipment in plateau railway tunnel projects. The continuous evolution of technologies, methodologies, and policies will invariably introduce new opportunities and challenges, warranting ongoing research and dialogue among stakeholders to navigate towards more sustainable, efficient, and responsible construction practices.

Policy recommendations and practical guidelines

Navigating through the complexities of adopting electric equipment in plateau railway tunnel projects necessitates a robust framework of policy recommendations and practical guidelines, wherein governmental support emerges as a linchpin, providing financial and infrastructural backing through policies, incentive programs, and a stringent regulatory framework that champions the use of environmentally congenial technologies in construction ventures, particularly within the ecologically delicate plateaus. In addition to the immediate operational and environmental benefits, the implementation of these policy recommendations and practical guidelines has profound implications for research, practice, and society. By fostering an ecosystem that encourages the use of electric equipment, we not only advance the research agenda in sustainable construction practices but also set a precedent for industry standards that prioritize environmental stewardship and worker safety. These guidelines serve as a model for other sectors, demonstrating the tangible benefits of integrating sustainable technologies into practical applications. On a societal level, these practices contribute to the realization of a greener, more sustainable future, aligning construction practices with global sustainability goals and enhancing public health through reduced emissions and pollution. The meticulous formulation and rigorous enforcement of standards for electric equipment become imperative, ensuring a steadfast adherence to safety, reliability, and efficiency across a spectrum of operational contexts, while on a practical note, the crafting of a phased strategy for the adoption of electric equipment, which prioritizes the foundational establishment of charging and battery-swap infrastructure, coupled with the implementation of comprehensive training programs for operators and maintenance personnel, becomes crucial to seamlessly navigate the operational and logistical challenges intertwined with the integration of novel technologies into extant workflows. Concurrently, the establishment of risk management protocols, designed to adeptly address potential challenges and disruptions related to the utilization of electric equipment in tunnel construction, acts as a safeguard, fortifying against operational and financial adversities.

Future research directions

Envisioning the future research directions in the domain of electric equipment utilization in plateau railway tunnel projects encompasses a multifaceted exploration into technological advancements, operational efficacy, socio-economic implications, and interdisciplinary research, with a pronounced focus on enhancing battery technology, delving into research that seeks to elevate energy density, expedite charging capabilities, and augment longevity, while also exploring the integration of automation and AI technologies to enhance efficiency and safety in tunnel construction activities. Beyond technological advancements, future research must emphasize the socio-economic and environmental impacts of electric equipment adoption. This includes studying the effects on worker health, community well-being, and contributing to sustainable development goals. Interdisciplinary research that bridges technology with policy analysis, social sciences, and environmental studies will be crucial for understanding the full spectrum of impacts and opportunities presented by electric equipment in construction. Investigative pursuits into innovative materials and technologies that can bolster the durability and performance of electric equipment, especially within the harsh environments of plateaus, emerge as a pivotal research avenue, while operational dynamics, environmental impact studies, and health and safety investigations will pave the way for data-driven insights and guidelines that optimize and safeguard tunnel construction practices. Furthermore, comprehensive economic analyses, social impact explorations, and investigations into the supply chain implications will illuminate the broader socio-economic ramifications and strategic considerations related to the adoption of electric equipment, and fostering intersectoral collaboration, engaging in international research collaborations, and exploring the broader sustainability implications of adopting electric equipment will ensure that practices are globally informed, technologically advanced, and holistically sustainable.

The datasets used and analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Equipment input cost

Battery replacement cost

Energy supplement facilities cost

Total equipment input cost

Working energy consumption cost

Daily equipment depreciation

Amortization of equipment input cost

Amortization of working energy consumption cost

Amortization of total cost

Quantity of equipment purchased

Years of depreciation

Daily amount of muck transfer

Amount of muck transfer per hour

Price of electricity per kilowatt-hour

Price of fuel per liter

Battery capacity

Tank volume

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Acknowledgements

This research was supported by the Fundamental Research Funds for the Railway Research Institute Group Limited Foundation of China (Grant No. 2021YJ111).

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Yang, X., Liu, Y., Liu, K. et al. Application and configuration analysis of electric muck transfer equipment in plateau railway tunnel: a case study in southwest China. Sci Rep 14 , 7222 (2024). https://doi.org/10.1038/s41598-024-57628-4

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Gangue grouting filling in subsequent space of coal green mining: methodology and case study

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• Published: 27 March 2024
• Volume 83 , article number  217 , ( 2024 )

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• Kunpeng Yu 1 ,
• Liqiang Ma 1 , 2 ,
• Ichhuy Ngo 1 ,
• Jiangtao Zhai 1 ,
• Yujun Xu 3 ,
• Zhiyang Zhao 1 ,
• Hui Wang 1 &
• Dangliang Wang 2  

Underground backfilling stands out as a crucial technological strategy for the eco-friendly and effective management of solid waste in mining operations. However, existing backfilling techniques have led to increased production processes at the working face, resulting in a reduction in coal extraction efficiency. Addressing the temporal and spatial interference between mine solid waste backfilling and coal mining is essential. To overcome this challenge, this study introduces a novel post-mining spatial gangue slurry backfilling method. Radar detection was employed to ascertain the typical characteristics of the subsequent space collapse roof shape. Stress monitoring and compaction experiments were conducted to establish the relationship between stress and the bulking coefficient of the overlying rock mass, identifying subsequent spatial void structure characteristics. The development of a CO 2 mineralized coal-based solid waste filling material, utilizing conventional low-calcium fly ash under normal temperature and pressure conditions, was presented. This paper provides a comprehensive understanding of the post-mining spatial gangue slurry backfilling method, outlines the spatial layout approach for the corresponding system, and analyzes research challenges associated with gangue slurry backfilling materials and the technology of slurry injection borehole layout. The research aims to innovate an efficient underground disposal model for gangue, contributing to the refinement of the technical system for the comprehensive disposal and utilization of gangue.

Avoid common mistakes on your manuscript.

Introduction

Coal is one of the primary sources of energy worldwide and plays a significant role in economic development (Zhang et al. 2019a , b , c ; Gao et al. 2018 ). The healthy development of the coal industry is crucial for energy security and sustainable economic growth (Chen et al. 2020a , b ; Xu et al. 2020 ). While coal has made tremendous contributions to industrial development, it has also brought a series of environmental damage issues, significantly impacting surface ecology and groundwater environments, particularly in ecologically vulnerable areas (Singh and Guha 2018 ; Li et al. 2019 ). The contradiction between large-scale coal extraction and environmental protection is particularly pronounced in areas characterized by coalfields with thick coal seams, shallow burial, limited water resources, and fragile ecosystems (Wang et al. 2018a , b , c ; Chen et al. 2020a , b , 2021 ; Zhong et al. 2019 ). In response to the ecological damage caused by large-scale mechanized mining methods, the current scientific development strategy for coal resources needs to shift from “passive restoration” to “active protection” and from “intensive mining” to “harmonious coordination” (Zeng et al. 2019 ; Liu et al. 2020 ).

Due to the limited conditions for coal occurrence, around 90% of coal in China is primarily extracted through underground mining (Wang et al. 2019 ; Huang et al. 2022 ; Qi et al. 2019 ). In accordance with the overall requirements of ecological civilization construction and prioritizing environmental protection, as well as emphasizing natural restoration, efforts should be made to minimize and control the ecological damage caused by mining operations underground. Currently, the main methods used to prevent ground ecosystem disruption resulting from coal mine strata collapse are pillar extraction and backfill mining (Zhu et al. 2018 ; Zhang et al. 2017a , b ; Wang et al. 2018a , b , c ). However, the pillar extraction method leads to resource wastage and reduces the service life of mines. It also affects production layout and efficient coal recovery (Bai et al. 2022b ; Li et al. 2016 ). On the other hand, traditional backfill mining incurs high costs and poor economic viability, making it unsuitable for large-scale promotion and implementation by coal mining enterprises (Wang et al. 2018a , b , c ; Yu et al. 2020a , b ; Shao et al. 2020 ). Therefore, it is crucial to explore a comprehensive, scientifically sound, and efficient coal mining technique that minimizes subsidence and ensures water preservation, which is a vital and practical requirement for green and efficient mining at the current stage (Meng et al. 2021 ; Hou et al. 2021 ; Yuan et al. 2021 ).

In underground mining, longwall mining method, compared to other mining methods, enables continuous coal extraction and possesses advantages such as high productivity, efficiency, recovery rate, and strong applicability (Zhang et al. 2017a , b ; Liu et al. 2023 ). Consequently, it has been widely applied and developed. However, the damage caused by longwall mining to the surface and groundwater in mining areas should not be underestimated (Doulati et al. 2022 ; Bai et al. 2022a ). Since most longwall mining methods primarily adopt the full caving method to manage the roof, the roof collapse area is extensive, resulting in significant displacement and deformation of overlying rock layers from the coal seam to the surface (He et al. 2015 ; Bai and Tu 2019 ). In cases where the coal seam is close to aquifers or surface water bodies, mining-induced fractures may penetrate the aquifer sealing layers, leading to water resource loss and sudden inrush of water in working areas, thereby triggering a series of ecological, environmental, and production safety issues (Gao et al. 2019 ; Yu et al. 2020a , b ; Hu et al. 2018 ). The various environmental and safety problems caused by underground coal mining essentially revolve around the loss of water resources induced by mining operations (Li et al. 2020 ; Xu et al. 2019 ).

Backfill mining is an effective method that limits the impact on water, soil resources, and infrastructure within the tolerable range of ecological tolerance for mining activities (Liu et al. 2018 ; Hu et al. 2017a , b ; Chen et al. 2019 ; Zhang et al. 2020a , b ). Promoting advanced technologies such as efficient backfill mining in an adaptable manner and conducting feasibility studies on coal mine backfill mining are among the key tasks for comprehensive management of mining subsidence areas (Zhao et al. 2019 ; Ma et al. 2018 ; Zhang et al. 2019a , b , c ; Wang et al. 2020 ). Backfilling the goaf is currently one of the most effective approaches to water conservation in coal mining (Liu et al. 2019 ; Zhang et al. 2020a , b ; Xie et al. 2016 ; Xu et al. 2017 ). However, traditional goaf backfilling encounters challenges such as insufficient time and space for timely backfilling before the roof collapses after coal extraction (Chen et al. 2018 ; Yang et al. 2017 ; Wu et al. 2016 ; Zhao et al. 2020 ). Additionally, mining and backfilling operations occur within the same limited space, making it difficult to coordinate parallel operations and causing backfilling to affect mining progress (Zhang et al. 2019a , b , c ; Shi et al. 2019 ; Hu et al. 2017a , b ; Wang et al. 2021a , b ). In coal mining environments characterized by complex geological conditions, a specialized approach to backfill mining has been implemented. This practice entails utilizing materials like gangue, sand, and crushed stone to fill the goaf, with the primary objective of minimizing subsidence associated with the mining process (Yang et al. 2019 ; Jiang et al. 2018 ; Liu et al. 2021 ). However, whether using coal gangue backfilling, cementitious backfilling, partial substitution of fly ash for cement in backfilling, or concrete backfilling, the unit cost is generally high. The relatively high investment cost significantly impacts the economic benefits of enterprises and objectively limits the widespread application of this method.

Regarding this particular situation, the authors propose a delayed backfilling approach for goaf filling. The backfilling operation is delayed compared to the mining operation, allowing for the natural collapse of the goaf roof. This results in a completely or nearly completely filled goaf area formed by the natural collapse of the goaf roof after coal mining. The authors utilize the fragmentation and expansion properties of the collapsed rocks. On the side close to the working face, a designated delayed filling zone is determined. Through directional drilling or upper-level roadways near the working face, the voids in the collapsed zone are grouted before compaction, consolidating the collapsed zone to form a load-bearing structure with certain strength, as depicted in Fig.  1 . Radar detection was utilized to characterize the typical shape of the roof collapse in the subsequent space. Stress monitoring and compaction experiments were carried out to establish the correlation between stress and the bulking coefficient of the overlying rock mass, revealing the characteristics of the subsequent spatial void structure. The paper introduced the development of a CO 2 mineralized coal-based solid waste filling material, employing conventional low-calcium fly ash under normal temperature and pressure conditions. It systematically elaborated on the concept of the subsequent space gangue grouting filling method and provided the spatial layout approach for the subsequent space gangue grouting filling system. The challenges in the development of gangue grouting filling materials and the technology for grouting borehole layout were thoroughly examined. The backfilling volume and range only cover a portion of the mined-out space. After reinforcing the collapsed rock mass with backfill material, it supports the overlying strata and achieves the objectives of controlling strata movement and water conservation while mining proceeds parallelly. The advantage of this method is that it separates the mining and backfilling processes, avoiding interference between them. Based on field investigations, the authors provide a detailed analysis of the characteristics of the collapsed goaf roof and the height of the collapsed zone, establishing the boundaries for grout filling. By monitoring the stress of the goaf in real-time, a stress distribution model for the delayed filling zone of the collapsed rock mass is established. This provides theoretical support for determining the timing of delayed grout filling in the collapsed goaf and understanding the development patterns of overlying strata fractures in the delayed filling zone.

Idea of subsequent space gangue grouting filling technology

Study area and hydrogeological conditions

The Yushen mining area is located in the arid inland region of central and western China, characterized by scarce water resources, making it a typical ecologically fragile mining area (Fig.  2 ). Groundwater in this region mainly relies on atmospheric precipitation, with an annual average precipitation ranging from 248.7 to 724.9 mm and a long-term average precipitation of 471.5 mm. Due to the terrain and landform, most of the precipitation forms surface runoff and is lost, with less than 15% infiltrating into the rock and soil layers. Moreover, the area experiences a high average annual evaporation of 1611 mm, leading to severe water shortage (Ma et al. 2022 ). In the early twenty-first century, the Yushen mining area began adopting modern coal mining technologies such as large working faces and one-time full-height mining. Due to the shallow burial of coal seams, thin overlying bedrock, and thick wind-blown sand cover on the surface, this high-intensity, integrated mining leads to deformation and fracture zones known as “double zones.” The structural damage to the aquifers results in the infiltration of water from the bedrock aquifer and the loose water-bearing layers of the Quaternary system into the goaf. This has caused a series of mining environmental geological effects, including leakage of underground water resources, sudden inrush of water and sand underground, groundwater level decline, and degradation of the ecological environment. The original fragile ecological environment of the mining area has become even more difficult to restore. For example, on July 13, 2003, when the 1310 working face in the Dalitata mine advanced to a position 16.7 m away from the cutting eye, the roof collapsed completely, leading to a geological disaster of water inrush and sand outburst, with a maximum water inflow of 510 m 3 /h (Ma et al. 2022 ). According to the statistics of water inflow in the Yushen mining area in recent years, the average water inflow of the Dalitata, Bulianta, and Shigetai mines exceeds 13,000 m 3 /d. The maximum water inflow is 16,853 m 3 /d (Shigetai). The average flow rate of the Mother River Spring Domain in the Dalitata mining field was 5961 m 3 /d before coal mining, with a maximum average flow rate of 106,273 m 3 /d (Fan et al. 2018 ). However, in recent years, due to the damage and drainage of the Quaternary water-bearing layer caused by coal mining, the flow rate of the Mother River Spring Domain has decreased to only 1680 m 3 /d, a reduction of 72% (Song et al. 2021 ). Protecting and utilizing groundwater resources in coal mining has become an urgent issue in the scientific development of coal resources in ecologically fragile areas of central and western China.

Location of Yu-Shen mining area

The project proposes the technique of delayed backfilling for low-carbon water-conserving mining in goaf areas. It determines the space for delayed backfilling in goaf areas, the layout of grouting holes for backfilling, and parameters for delayed grouting and backfilling. The main contents include the fragmentation characteristics of collapsed rock blocks in goaf areas, the initial distance for delayed backfilling, the ultimate distance for delayed backfilling, the stratigraphic position for delayed backfilling, the arrangement of surface grouting holes and underground grouting holes, hole spacing, hole structure, and grouting volume.

The typical comprehensive stratigraphic column of the Yu-Shen coal area and the lithological characteristics are shown in Fig.  3 . The surface is primarily covered by Quaternary strata, and bedrock outcrops are sporadically distributed in valleys. The mining area is defined within the coal field, and it comprises six mineable coal seams at various depths. The total estimated coal resources amount to 1.24 billion tons, with a remaining reserve of 1.19 billion tons. The designed production capacity of the mine is 8 million tons per year, and the expected mine service life is 67.9 years. As of October 2021, the mining operation has completed the extraction in the 301 panel area, including ten working faces (30,101–30,110), and the extraction is ongoing in the 302 panel area, specifically in the 30,201 working face. In the next three years, the mine plans to extract from the 30,201 and 30,202 working faces. The 301 panel area adopts a multi-slice longwall (MSL) method with a mining height of 5 m, while the 302 panel area plans to use a single pass longwall (SPL) method with a mining height of 7.2 m.

Comprehensive geological histogram of the Yu-Shen coal area

Based on the groundwater occurrence conditions and hydraulic characteristics, they are divided into two types: the Quaternary loose rock porous confined aquifer and the Jurassic Middle System Zhijialu Formation and Yan'an Formation sandstone fractured confined aquifer. From top to bottom, it can be divided into five aquifer layers (formations): the Quaternary Holocene alluvial layer porous confined aquifer, the Upper Pleistocene lacustrine layer porous confined aquifer, the Quaternary Middle Pleistocene loess layer porous fractured confined aquifer, the Jurassic clastic rock weathered crust fractured aquifer, and the clastic rock fractured confined aquifer. The aquitards mainly consist of Quaternary Middle Pleistocene relative aquitard and the mudstone and sandy mudstone aquitard between the Jurassic sandstone layers (Table  1 ).

Upon analyzing the distribution characteristics of aquifers in the mining area, two main types of aquifers were identified: the loose rock mass aquifer with pore and fissure water in the Quaternary system, and the fractured rock aquifer in the Jurassic clastic rocks. As for the distribution characteristics of aquitards in the mining area, two major aquitards were identified: the relative aquitard composed of middle-lower Quaternary loess in the Quaternary system and the interbedded aquitard in the Jurassic bedrock. Current research indicates that the focus of water hazard prevention and control lies in ensuring safe mining operations by minimizing the inflow of water from the roof during the mining process. Properly controlling the position of the interface between the water-conductive fractured zone and the aquifers based on the hydrogeological conditions of the mined coal seam and preventing damage to the aquitards caused by mining activities are essential approaches to achieve water-conserving mining practices.

Field detection of collapsed roof form

The detection area is the goaf of the No. 3 coal seam in the 301 panel area. The ZTR12 series geological radar (GR) utilizes shielded antennas to emit high-frequency electromagnetic waves ranging from 1 MHz to 2.5 GHz, while the receiving antennas collect the corresponding signals, which are then stored and displayed by a computer. The ZTR12 series GR has a central antenna frequency of 100 MHz, a length of less than 1 m for each individual antenna, a step size smaller than 2 × 10 –12  s, an output signal of 10 × 10 –9  s, and a voltage of 90 V. Additionally, when generating a 100 MHz transmission pulse, the amplitude ratio between the pulse and ripple increases significantly to over 30 dB, allowing the effective mapping depth of the GR to reach within a range of 30 m below the No. 3 coal seam, making it fully applicable in underground mining environments. The ZTR12 series GR was employed to detect the roof strata of the goaf in the No. 3 coal seam. The GR has a detection depth of 30 m and a detection distance of 70 m. The detection area is illustrated in Fig.  4 , and the GR system conducted tests at 1024 sampling points.

Location of GR detection

The GR detection data collected were processed through zero-point calibration, denoising, filtering, and gain adjustment to obtain the GR detection images. These images clearly reflect the collapse status of the roof strata after coal seam extraction in the detection area, as shown in Fig.  5 . From Fig.  5 , it can be observed that within a distance of 30 to 70 m from the detection starting point, there are four distinct alternating strong and weak reflection zones. Specifically, a weak reflection zone appears in the 60 to 70 m position, and its phase is generally consistent with the surrounding medium reflection image. Therefore, the black dashed-line area represents a mildly damaged region where the roof exhibits minor fragmentation and relatively high integrity. On the other hand, a strong reflection zone appears in the 50 to 60 m positions, and its phase differs from the surrounding medium reflection image. Hence, the white dashed-line area represents a severely damaged region where the roof exhibits significant fragmentation and poor integrity. This cyclic pattern of alternating reflection zones follows the advancing direction of the working face and is in basic agreement with the results obtained from on-site borehole observations. Based on the aforementioned detection results, the collapsed morphology of the roof in the goaf of the No. 3 coal seam was reconstructed, as shown in Fig.  6 .

Processed detection results of GR data

Inversion map of breaking structure form with GR of coal seam mining

From Fig.  6 , it can be observed that after the extraction of the No. 3 coal seam, the immediate roof (carbonaceous mudstone) and the overlying roof (siltstone) exhibit well-developed fractures, and the fracture development has extended into the mudstone layer. However, the upper portion of the siltstone layer is minimally affected by the extraction of the No. 3 coal seam, with a collapse zone height of 25 m.

Collapse rock mass expansion characteristics

Based on the theory of overlying stress in collapsed rock blocks within goaf areas, the stress variation and dilatancy coefficient of the collapsed rock blocks within the goaf are divided into different zones. By analyzing the stress variation patterns and dilatancy characteristics of the collapsed rock blocks within the goaf, the initial lag filling distance is determined.

Zoning of stress in collapsed rock blocks

After the collapse of the roof in the goaf area, the overlying load is transferred and redistributed, resulting in the formation of supporting pressure. Based on the principles of limit equilibrium and conservation of overlying load, the calculation methods for the range of coal wall support influence and stress recovery zone are studied. The deformation zoning of the lag filling zone is analyzed, and the corresponding stress paths during mining are determined based on the longitudinal and transverse stress variation patterns of the overlying strata. A stress-distance distribution model for the collapsed rock blocks in the lag-filling zone is established. Combining the theories of cantilever beams and elastic foundation beams, the stress variation patterns of collapsed rock blocks in the goaf area are analyzed. Based on the subsidence of the underlying rock layer in the 302 panel area, the stress zones of the collapsed rock blocks in the goaf area are classified as follows: low stress zone (LSZ), stress-increasing zone (SIZ), and stress-stable zone (SSZ), as shown in Fig.  7 .

Schematic diagram of stress distribution in goaf

The relationship between stress \(\sigma_{I}\) in low-stress zone of collapsed rock mass and the position l of coal wall in the working face satisfies:

In the equation: \(\sigma_{I}\) represents the stress in the low-stress zone of the collapsed rock mass in MPa; l represents the distance from the coal wall in meters; \(\Delta C\) represents the compensation parameter; a and b are coordination parameters determined through stress measurement experiments on the collapsed rock mass.

Distribution of fragmentation and swelling characteristics of collapsed rock blocks

Based on the relationship between rock swelling coefficient and axial pressure, the distribution characteristics of fragmentation and swelling of collapsed rock blocks are analyzed. Since the rock swelling coefficient is not a constant value but a function of stress variation, the rock swelling coefficient and the characteristics of swelling can only be obtained when the regression coefficients are determined. In the field of the 302 panel area, random samples of collapsed rock blocks were collected, crushed, and placed in rigid cylinders for compaction experiments. By using a Multi-functional Mechanical Test Loading System (MMTLS), as shown in Fig.  6 , the rock swelling coefficient under compression was calculated (Table  2 ), and the relationship curve between the swelling coefficient and stress was plotted (Fig.  8 ).

Collapse rock mass compaction experiment

At the initial filling stage, the fragmentation coefficient is relatively large, and at this time, the initial delayed filling position is located in the low-stress zone. According to Eq. ( 1 ), the relationship between the fragmentation coefficient ( k p ) of the collapsed rock block and the distance ( l ) from the working face to the coal wall is given by:

In the equation, \(\alpha\) and \(\beta\) represent the regression coefficients related to the overlying rock stress in the goaf area, while c and d are the coordinating parameters for overlying rock stress determination. ΔE represents the compensatory parameter. It should be noted that the distance between the coal mining face and the backfill body needs to be greater than the initial collapse step distance of the roof. The calculation formula for the roof's ultimate collapse step distance is as follows:

Here, L represents the collapse step distance of the roof. Q denotes the load borne by the strata beam of the overlying roof. R T is the ultimate tensile strength of the strata at that location. H represents the thickness of the overlying roof strata. k is the coefficient that accounts for the influence of the support stress generated by the mining face advancement and the production technical conditions.

Analyzing the stress distribution of the collapsed rock mass in the goaf, the stress in the collapsed rock mass is mainly derived from the overlying strata pressure. The overlying strata above the adjacent coal seam form a cantilever beam structure, which restricts the stress exerted by the overlying strata on the collapsed rock mass. According to the principle of limited stress distribution in the overlying strata near the coal seam (Wang et al. 2021a ; b ), the relationship between the stress in the collapsed rock mass ( σ ) and the position of the mining face relative to the coal seam ( l ) can be expressed as follows:

In the equation, σ represents the stress in the collapsed rock mass, MPa. l represents the distance from the coal seam, m. ΔC represents the compensation parameter. a and b are coordination parameters determined through experimental measurements of the stress in the collapsed rock mass.

After coal extraction, VSP530 vibrating wire rock stress meters were installed on the mining floor, along with the GT204A vibrating wire readout instrument, to measure the overburden stress of the collapsed rock blocks (Fig.  9 ). Based on the measured stress data of the collapsed rock mass in the goaf, an approximate exponential relationship curve was fitted, which showed good agreement with the established mathematical model (Fig.  10 ). It was observed that the closer the distance to the coal wall, the smaller the stress exerted by the overlying strata on the collapsed rock mass, with the corresponding parameters of ΔC  = − 0.02, a  = 7, and b  = 0.03.

Testing of overlying strata stress on the collapsed rock mass

Stress-position relationship of the collapsed rock mass

Determination of the delayed backfilling zone in the goaf area

Considering the natural caving state of the roof after coal mining operations in the 302-panel area, the technique of delayed backfilling with low-carbon water-retaining mining was proposed. A precise slurry system was established on the ground to produce a slurry of coal gangue, water, and additives with a certain mass fraction. Then, the gangue slurry was transported through a pipeline system and high-pressure injection to fill the space behind the working face, thereby achieving the disposal of coal gangue in an environmentally friendly manner without affecting normal production (Fig.  11 ).

Schematic diagram of delayed backfilling in the goaf area

To support the overlying strata and control the development of water-conducting fractures, delayed backfilling plays a crucial role in preventing the connection with aquifers. Therefore, before determining the backfilling area, it is necessary to identify the layers for groundwater protection. Based on the distances between the 3# coal roof and major aquifers within the scope of the 302-panel area, as shown in Table  1 , it is observed that the Zhenwu Cave Sandstone is located at a distance of 0.99 to 18.38 m from the coal seam, which is too close to be protected through goaf backfilling. On the other hand, the Qili Town Sandstone is situated at a distance of 40.97 to 99.05 m from the coal seam, which is sufficiently far to be protected through delayed backfilling. Consequently, the groundwater protection layers are identified as the Qili Town Sandstone aquifer and the overlying Fourth Series Sandstone aquifer.

The distance for delayed backfilling in the goaf

Based on the geological data of the 302-panel area, the initial collapse step distance of the roof is estimated to be 41.6 m. Through the rock fragmentation compaction experiments, the initial filling coefficient of the collapsed rock blocks in the 302-panel area is determined to be 1.5. By applying Eq.  3 , the distance from the mining face to the coal wall is calculated to be 46 m, which exceeds the roof collapse step distance. Combining surface observations in the Yushen mining area and surface subsidence monitoring of the 30,201 working faces in the Hanglaiwan coal mine, it is observed that the initiation phase of the surface movement for the 30,201 working face lasts for 6 days, with a starting distance of 59 m. With an average daily mining progress of 10.38 m, the underground mining distance during the initiation phase is determined to be 62 m. Therefore, the final determined distance for the initially delayed backfilling is 62 m.

The further the distance from the working face, the more compact the collapsed rock blocks in the goaf become, leading to a decrease in the void ratio between the rock blocks. When the residual fragmentation coefficient is less than 1.03, it is not feasible to carry out delayed backfilling work. Based on the fitted relationship between the fragmentation coefficient and the overlying rock stress, according to Eq.  3 , the distance to the mining face is calculated to be 706 m in this case. Combining surface observations in the Yushen mining area and surface subsidence monitoring of the 30,201 working faces in the Hanglaiwan coal mine, it is observed that the surface movement duration is 220 days, with an average active phase of 71 days. With an average daily mining progress of 10.38 m, the underground mining distance at this stage is determined to be 737 m. Therefore, the final determined distance for the maximum delayed backfilling is 737 m.

The stratigraphic position for delayed backfilling in the goaf

The stratigraphic position for delayed backfilling in the goaf is determined by the sum of the collapsed rock layer thickness and the coal seam extraction thickness. By analyzing the hydrogeological data of the 302-panel area and considering the occurrence conditions and physical–mechanical properties of the overlying rock layers in the mining area, along with empirical calculations based on mining height, collapsed zones, and fracture zones, the relative position relationship between the overlying aquifer and the collapsed zones/fracture zones is determined to ensure that the collapse and fracture zones do not extend into the aquifer. In the 302-panel area, the coal seam extraction thickness is 7.2 m, and empirical formulas yield a collapsed zone height of 30 m and a fracture zone height of 154.8 m.

The thickness of the collapsed rock layer and the position for delayed backfilling are determined based on the accumulated height of the collapsed zone on the immediate roof and the gap height between the immediate roof and the old roof. If the collapse thickness of the immediate roof layer is \(\Sigma h\) , then the accumulated height after the collapse is \(k_{p} \Sigma h\) , and the gap left between the immediate roof and the old roof is denoted as \(\Delta\) :

In the equation, M represents the thickness of the extracted coal seam, and \(\Sigma h\) represents the thickness of the collapsed rock layer.

When \(M = \Sigma h(k_{p} - 1)\) , \(\Delta = 0\) , the collapsed rock layer fills the goaf completely. At this point, the bending and sinking of the immediate roof are usually negligible and can be disregarded. Therefore, the thickness of the collapsed rock layer \(\Sigma h{ = }h^{\prime}\frac{M}{{k_{p} - 1}}\) , where h’ represents the safety factor for caving, \(h^{\prime}{ = }5\sim 5.5\) .

The position of the backfill layer in the goaf is determined by the sum of the thickness of the collapsed rock layer and the thickness of the coal seam being mined. Different backfill regions correspond to different coefficients of rock fragmentation for the collapsed rock in the goaf, resulting in different positions for the backfill layer. In the initial stage of backfilling, when the coefficient of rock fragmentation for the collapsed rock in the goaf is 1.5 and a safety factor of 5.5 is chosen, the calculation yields a rock collapse thickness of 97.2 m. With a coal seam thickness of 7.2 m in the 302-panel area, the position of the backfill layer in the goaf is determined to be 86.4 m. In the ultimate stage of backfilling, when the coefficient of rock fragmentation for the collapsed rock in the goaf is 1.35 and a safety factor of 5 is chosen, the calculation yields a rock collapse thickness of 102.9 m. With a coal seam thickness of 7.2 m in the 302-panel area, the position of the backfill layer in the goaf is determined to be 110 m. Therefore, the position of the backfill layer in the goaf ranges from 86.4 m to 110 m.

Preparation of CO 2 mineralized fly ash backfill material

During coal mining operations, a significant amount of solid waste and CO 2 is generated. In the context of the peak carbon and carbon neutrality goals, the comprehensive utilization of solid waste and CO 2 is an important approach for achieving green and low-carbon development in the coal industry. Traditional CO 2 mineralization of fly ash typically requires high-temperature, high-pressure, and high-calcium conditions to enhance the reaction rate, mineralization conversion rate, and strength of the backfill material. However, in engineering practice, it is difficult to meet the requirements of high-temperature and high-pressure mineralization conditions, and there are safety risks involved.

To address this challenge, the development of CO 2 -mineralized fly ash backfill material under conventional low-calcium conditions at ambient temperature and pressure is pursued. The main raw material for the backfill material is the fly ash from a power plant in Zhengzhou, Henan Province, China, with Ordinary Portland Cement (OPC) procured from Zhucheng Yangchun Co., Ltd. as an additive and CO 2 as the mineralization gas supplemented with alkaline activator SA. The experimental process is outlined in Fig.  12 . The chemical properties of fly ash, the characteristics of OPC and details about the mixing procedure of the negative carbon filling material (NCFM) are the same as previous studies (Ngo et al. 2023 ). Mortar samples were prepared in accordance with the Chinese standard GB/T17671-2021. The Unconfined Compressive Strength (UCS) tests for NCFM samples were conducted following the identical procedures, utilizing the same equipment, and maintaining consistent parameter settings as described in previous studies (Ngo et al. 2023 ). The CO 2 -mineralized fly ash backfill material is filled into the goaf, achieving both water retention during coal mining and sequestration of CO 2 and fly ash.

Preparation of NCFM backfill material

The CO 2 mineralization reaction is conducted during the preparation of the backfill material, resulting in the development of mineralized backfill. The alkaline activator SA is added to tap water to prepare an activating agent solution, which is then added to the solid mixture at a water-to-ash ratio of 1:2. CO 2 is introduced into the mixture during the stirring process to initiate a mineralization reaction. The backfill slurry is prepared into cylindrical specimens measuring 50 mm × 100 mm and cured at constant temperature and humidity (humidity: 95 ± 1%, temperature: 20 ± 1 °C) for 3, 7, 14, 28, and 56 days. The composition ratios of the CO 2 mineralized fly ash backfill material are shown in Table  3 . The rheological parameters and fitting results of the slurry are presented in Table  4 . The influence of curing time and fly ash content on the unconfined compressive strength (UCS) of the negative carbon filling material (NCFM) specimens are illustrated in Fig.  13 .

UCS of NCFM backfill material

The yield stresses of FA50-FA80 are 36.01 Pa, 26.75 Pa, 16.76 Pa, and 15.99 Pa, respectively. The yield stress of the NCFM slurry decreases with an increase in the mass of fly ash. During the carbonation process, CO 2 reacts with the hydration products of cement to form C–S–H gel, consuming free water in the slurry and reducing its fluidity. Therefore, slurry with a lower fly ash content requires higher yield stress for pumping. However, when the fly ash content is increased to 90%, the yield stress increases to 17.09 Pa. This is due to the excessive fly ash content, which increases the specific surface area of particles in the slurry and adsorbs a large amount of free water.

To ensure the transportation of filling materials through pipelines, the yield stress of the slurry needs to be within 200 Pa, and thus the yield stress of NCFM meets the industrial application requirements. Regarding hydration and carbonation reactions, the adoption of ambient temperature and pressure CO 2 mineralization method produces silica-based gel and CaCO 3 , providing strength to high fly ash filling materials and overcoming the disadvantage of low strength in conventional low-calcium fly ash in filling applications. The flowability and UCS of NCFM filling materials meet the requirements for underground filling. The UCS at 3 days and 28 days are 2.70 MPa and 5.12 MPa, respectively. The silica-based gel generated from the reaction of CO 2 with alkali activators compensates for the low binding property of high fly ash filling materials, exhibiting early strength characteristics and subsequently promoting the reaction of volcanic ash, thereby increasing the long-term strength of NCFM. Based on market prices, the direct cost of NCFM filling materials is approximately 131 RMB per ton. Compared to conventional fly ash filling materials and traditional filling materials, NCFM filling materials can save direct costs of 28 RMB per ton and 59 RMB per ton, respectively. For detailed cost analysis, refer to Table  5 .

The arrangement of drilling and grouting parameters

The arrangement of drilling involves a combination of surface drilling and underground directional drilling. Due to being unaffected by factors such as the coal seam dip angle, priority is given to surface drilling and grouting filling (Fig.  14 ). If surface conditions do not permit drilling, directional drilling is conducted in the vicinity of the mining area (Figs.  15 and 16 ).

Schematic diagram of surface grouting drilling hole arrangement

Arrangement of directional drilling for grouting (Option 1)

Arrangement of directional drilling for grouting (Option 2)

Drilling spacing

Referring to experimental measurements and empirical data, the diffusion radius of the backfill slurry is determined to be 100–150 m (Shi et al. 2021 ). Applying a safety factor of 1.5, the grouting hole spacing is set at 66–100 m. For the 302 panel area with a working face length of 300 m, the surface grouting drilling arrangement is shown in Fig.  14 . Three holes are arranged along the inclined direction of the working face with a spacing of 75 m. The underground directional drilling arrangement is shown in Figs.  13 and 14 . Based on the determined distance and stratigraphic position of delayed filling, directional drilling is conducted from the filling drifts on both sides towards the fractured zone above the goaf. Two directional drilling holes are arranged on each side of the filling drifts, and four directional drilling holes are arranged along the inclined direction of the working face. Two options are considered: Option 1, where the two directional drilling holes are located in the same vertical cross-section with a spacing of 75 m (Fig.  15 ); Option 2, where the two directional drilling holes are located at the same horizontal stratigraphic position but staggered, with a spacing of 37.5 m (Fig.  16 ).

Drilling parameters

Both the vertical and inclined sections of the borehole require permanent cement grouting to ensure water sealing and meet the requirements for drilling and grouting construction, thereby ensuring construction safety.

The borehole structure is determined based on factors such as the comprehensive treatment approach, geological conditions, and equipment capabilities. The surface borehole has a diameter of Ф311 mm, and a surface casing of Ф244.5 mm × 8.94 mm is inserted down to the bedrock and cemented for wellbore integrity.

The underground directional drilling borehole has a diameter of Ф135 mm, and the horizontal section is left unlined.

Maximum grouting volume

There is a certain relationship between the grouting volume of the collapsed zone with fragmented gangue and the rock mass dilation characteristics. The dilation coefficient ( k p ) of the rock mass in the study area is generally between 1.12 and 1.5, and the grout cannot completely fill the voids in the collapsed zone. Depending on the block size of the fragmented rock mass, the filling capacity under grout pressure can only reach 60–90% of the dilation volume, i.e., the filling degree (the ratio of grouting volume to rock mass volume) γ is between 0.6 and 0.9. The maximum grouting volume ( V g _) of the entire collapsed zone with backfill slurry is given by:

where V g is the grouting volume of the slurry, V m is the volume of coal extraction, V r is the original volume of the roof that collapses during coal extraction, k p is the rock mass dilation coefficient. By definition, when γ  =  V g /( k p V r ), we can obtain:

The maximum grouting volume of the entire backfilling space is influenced by the mining volume, the original volume of the collapsed roof, and the rock mass dilation coefficient. Since the mining volume and the original volume of the collapsed roof are constant, the maximum grouting volume can be obtained by integrating the dilation coefficient equation along the length in the mining direction and substituting it into Eq. ( 7 ).

Following the principle of initial dilution, subsequent concentration, and final dilution, grouting filling is carried out. The maximum grouting pressure is determined to be 6 MPa based on the water inflow from the goaf to the working face, the horizontal thrust of the collapsed rock blocks on the support, and the maximum compressive strength of the grouting pipe during grouting. The filling degree ranges from 68 to 80%, and the filling degree after water leakage is ensured to be above 50%.

Mining volume of the grouting section at the working face is as follows:

where L is the length of the grouting section at the working face, m. D is the width of the working face, taken as 300 m. M is the mining thickness, taken as 7.2 m. η is the recovery rate, taken as 100% (without considering the gangue content).

Volume of post-mining collapse at the working face is as follows:

where q o is the settlement coefficient of full extraction at the working face.

Volume of injected backfill material required for subsidence reduction ( n /%) is as follows:

where A is the backfill coefficient.

Grouting volume is as follows:

where x is the water-to-cement ratio, taken as 0.5. For the 302 panel, the calculated unit grouting volume is 1400 kg/m 3 .

Conclusions

Underground backfilling was essential for environmentally friendly waste disposal in mines. However, addressing temporal and spatial interference between mine waste backfilling and coal mining was crucial to overcome technical challenges. This paper proposed a post-mining gangue grouting filling method for goaf collapse blocks, utilizing post-mining space efficiently. Collapse roof morphology in the post-mining space was determined using radar detection. The intrinsic relationship between roof stress in collapse blocks and the swelling coefficient was established through stress monitoring and compaction experiments, revealing structural characteristics and spatiotemporal evolution of post-mining space voids. NCFM was developed under normal temperature, pressure, and conventional low-calcium fly ash conditions. Key parameters for grouting filling were meticulously designed.

The study identified two main aquifer types: Quaternary loose rock porous and fractured confined aquifers, and Jurassic clastic rock fractured confined aquifers. Two main aquitards were also recognized: the Quaternary middle and lower Pleistocene loess relative aquitard and the Jurassic interbedded aquitard rock group.

The stress variation law of collapse blocks in the goaf, the distribution characteristics of block swelling, and the observation of surface (roof) subsidence in the mining area are analyzed, determining the initial lag filling distance of 62 m and the ultimate lag filling distance of 737 m. The thickness of the collapsed rock layer that fills the goaf is determined based on the accumulated height of the directly collapsed roof and the void between the directly collapsed roof and the old roof, and the final lag filling stratum is determined to be 86.4 m to 110 m.

Under standard temperature and pressure conditions, and employing conventional low-calcium fly ash, NCFM was synthesized. Demonstrating suitable flowability, setting time, and UCS, NCFM met the stringent requirements for underground filling, exhibiting UCS values of 2.70 MPa at 3 days and 5.12 MPa at 28 days. The silica gel produced from the reaction between CO 2 and alkali activators compensated for the low binding capacity inherent in high fly ash filling materials. This phenomenon facilitated the formation of a dense structure in the early stages and enhanced the long-term strength of NCFM through volcanic ash reactions. The financial benefits of employing NCFM, in comparison to conventional fly ash and traditional filling materials, amounted to 28 yuan/ton and 59 yuan/ton, respectively.

The innovative slurry injection method for backfilling coal mine gob post-mining improved the technical system for comprehensive gob disposal. This approach, reducing emissions at the source and promoting on-site disposal, holds significant promise for efficient solid waste disposal and ecological protection in coal mining.

Data availability

Data available on request from the authors.

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The authors would like to make an appreciation to the Fundamental Research Funds for the Central Universities (2022QN1004) for financial support.

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Kunpeng Yu, Liqiang Ma, Ichhuy Ngo, Jiangtao Zhai, Zhiyang Zhao & Hui Wang

Key Laboratory of Xinjiang Coal Resources Green Mining (Xinjiang Institute of Engineering), Ministry of Education, Urumqi, 830023, China

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State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mines, Anhui University of Science and Technology, Huainan, 232001, Anhui, China

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Yu, K., Ma, L., Ngo, I. et al. Gangue grouting filling in subsequent space of coal green mining: methodology and case study. Environ Earth Sci 83 , 217 (2024). https://doi.org/10.1007/s12665-024-11514-4

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March 27, 2024 - Baltimore Key Bridge collapse

By Kathleen Magramo , Antoinette Radford, Alisha Ebrahimji , Maureen Chowdhury , Elise Hammond , Tori B. Powell and Aditi Sangal , CNN

Here's what you should know about the Key Bridge collapse

From CNN staff

Officials recovered the bodies of two construction workers who were on Baltimore's Francis Scott Key Bridge when it collapsed early Tuesday morning after a 984-foot-long cargo ship collided into a pillar.

Maryland Gov. Wes Moore called the collapse Wednesday " a global crisis ."

"The national economy and the world's economy depends on the Port of Baltimore. The port handles more cars and more farm equipment than any other port in the country," Moore said.

Here's what you should know:

• The victims: The six people who are presumed dead were from Mexico Guatemala, El Salvador and Honduras, according to Col. Roland L. Butler Jr, the superintendent of Maryland State Police. Two bodies were recovered and have been identified as Alejandro Hernandez Fuentes from Mexico and Dorlian Ronial Castillo Cabrera from Guatemala. The two workers were filling potholes on the bridge and were later found trapped in a red pickup truck in about 25 feet of water, Butler said. The FBI is handling notifying the victims' families, Butler said.
• Recovery efforts: Authorities are pausing search efforts for the four other workers who are presumed dead, because additional vehicles are encased in concrete and other debris, making it unsafe for divers, Butler said. Once salvage operations clear the debris, divers will search for more remains, he said.
• The investigation: The National Transportation Safety Board is leading the investigation into the fatal incident, according to the agency's chair Jennifer Homendy. During a Wednesday news conference, Homendy said there were 21 crew members and two pilots on board the Dali cargo ship when it crashed into the bridge. She also said a senior NTSB hazmat investigator identified 56 containers of hazardous material, and that some containers are in the water. The agency received six hours of voyage data from the ship and the investigation could take 12 to 24 months to complete, Homendy said. She emphasized that NTSB will not analyze information collected or provide conclusions while on scene of the collapse.
• Looking forward: Department of Transportation Secretary Pete Buttigieg said rebuilding the bridge will not be "quick or easy" but that it will get done. He said there are four main focus points ahead: reopening the port, dealing with supply chain issues until its reopening, rebuilding the bridge and dealing with traffic issues until the bridge is rebuilt. Biden  pledged the full support  of the federal government in the response and recovery efforts. His administration has already conveyed a sense of urgency to open up federal funding to remove debris and ultimately rebuild the bridge. Maryland has submitted a request to the Biden administration for emergency relief funds "to assist in our work going forward," Moore said Wednesday.

It's almost impossible to place people on the bow of ship due to the unstable structure, fire official says

 From CNN's Sarah Engel

Baltimore City Fire Chief James Wallace said Wednesday that the cargo ship's bridge structure and containers at the bow remain unstable.

"It's going to be very difficult, if not impossible, and very dangerous, to place people on the bow of that boat right now," Wallace told CNN's Kaitlan Collins.

"Naturally, we're still very cognizant of the fact that there are hazardous materials on board the vessel itself," Wallace said, alluding to the National Transportation Safety Board saying earlier that 56 containers were carrying hazardous materials.

Wallace said his team is relying heavily on aerial recognizance, including drones. "That's the only way we're able to see in," he said.  

He added that the aerial surveillance has "been able to really assure us right now we have no [chemical] reactions on board." 

"It's just utter devastation," NTSB chief says of the bridge collapse site

From CNN's Aditi Sangal

Jennifer Homendy, chair of the National Transportation Safety Board, called the site of the Key Bridge collapse "devastating."

"It's pretty devastating, certainly, seeing not just what's going on with the cargo containers, but just looking at what was a bridge span — three bridge spans that is pretty much gone. It's just utter devastation," she said at Wednesday evening's news briefing.

She added that she is thinking of families who lost loved ones and those who are waiting to reunite with their lived ones.

NTSB interviewed the Dali's captain and some other crew members today, agency chief says

The National Transportation Safety Board has interviewed the ship's captain, his mate, the chief engineer and one other engineer today, according to Chair Jennifer Homendy.

The two pilots on board the Dali at the time of collision will be interviewed tomorrow, she added.

Cargo ship's voyage data recorder is basic when compared to an airplane's, NTSB chair says

From CNN's Tori B. Powell

The voyage data recorder on the cargo ship Dali was a "newer model" but is considered basic when compared to that on an airplane, according to National Transportation Safety Board Chair Jennifer Homendy.

"But it is very basic compared to say, a flight data recorder, where we would have 1,000 parameters," she said at a news conference on Wednesday.

The NTSB chief investigator Marcel Muise added:

"It's not a ship-wide system recorder, so most of the sensors that are being recorded are from the bridge. So things like GPS, the audio, rudder feedback, rudder commands are recorded on there. But not engineering, the temperature of each cylinder, power distribution sensors."

There were no tug boats with Dali at the time of the collision. That's normal, NTSB chief says

There were no tugs with Dali when the cargo vessel collided with Baltimore's Key Bridge, which is normal protocol, according to National Transportation Safety Board Chair Jennifer Homendy.

Remember: At 01:26:39 on Tuesday, Dali's pilot made a general very high frequency (VHF) radio call for tugs in the vicinity to assist, the NTSB investigator Marcel Muise had said.

"The tugs help the vessel leave the dock, leave the port and get into the main ship channel. And then they leave. Once it's on its way, it's a straight shot through the channel. So there are no tugs with the vessel at the time. So they were calling for tugs," she said.

NTSB chair says she saw some containers that were carrying hazardous materials in the water

National Transportation Safety Board Chair Jennifer Homendy said she did see some of the 56 containers that were carrying hazardous materials in the water.

When asked how many

When asked how many containers of hazardous materials were in the water, Homendy said:

"I did see some containers in the water, and some breached significantly on the vessel itself," she said. "I don't have an exact number, but it's something that we can provide in an update."

Homendy said that a preliminary report should be out in two to four weeks.

This post has been updated with more quotes from Homendy.

Bridge did not have any redundancy, unlike the preferred method for building bridges today, NTSB chair says

Baltimore's Key Bridge did not have any redundancy, which is included in the preferred method of building bridges in the present day, according to National Transportation Safety Board Chair Jennifer Homendy.

"The bridge is a fracture critical," she explained. "What that means is if a member fails that would likely cause a portion of, or the entire bridge, to collapse, there's no redundancy. The preferred method for building bridges today is that there is redundancy built in, whether that's transmitting loads to another member or some sort of structural redundancy. This bridge did not have redundancy," Homendy said.

There are 17,468 fracture critical bridges in the United States out of 615,000 bridges total, she said, citing the Federal Highway Administration.

The NTSB investigator in charge of the bridge collapse investigation provides a timeline of crash

Marcel Muise, the National Transportation Safety Board investigator in charge, provided the following timeline of events as provided by the recovered voyage data recorder (VDR).

• Approximately 12:39 a.m. ET: The ship departed from Seagirt Marine Terminal.
• By 1:07: The ship had entered the Fort McHenry Channel.
• 01:24:59:  Numerous audible alarms were recorded on the ship's bridge audio. About the same time, VDR sensor data ceased recording. The VDR audio continued to record using the redundant power source, Muise said.
• 01:26:02:  VDR resumed recording sensor data and during this time, steering commands and rudder orders were recorded on the audio.
• 01:26:39 : The ship's pilot made a general very high frequency (VHF) radio call for tugs in the vicinity to assist. About to this time, Muise said, the pilot association dispatcher phoned the Maryland Transportation Authority (MDTA) duty officer regarding the blackout.
• Around 01:27:04: The pilot ordered the Dali to drop the port anchor and ordered additional steering commands.
• Around 01:27:25: The pilot issued a radio call over the VHF radio, reporting that the Dali had lost all power and was approaching the bridge. Around this time, the MDTA data shows the following also occurred: Their duty officer radioed two of their units that were already on scene due to construction on the bridge — one on each side of the bridge — and ordered them to close traffic on the bridge. All lanes were then shut down by MDTA.
• Around 01:29: The ship's speed over ground was recorded at just under 8 miles per hour. From this moment on approximately 1:29:33, the VDR audio recorded sounds consistent with the collision of the bridge. Additionally, around this time, MDTA dash cameras show the bridge lights extinguishing.
• 01:29:39: The pilot reported the bridge down over the VFH radio to the Coast Guard.

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