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The metro, renowned as an environmentally friendly mode of transportation due to its low energy consumption and minimal pollution, plays a crucial role in achieving sustainable urban growth. Due to the scarcity of information in the early stages of metro construction projects and the subjectivity of cost estimation (which relies heavily on the estimator's experience), it is always difficult to guarantee the accuracy of metro construction project cost estimation. Furthermore, the existing methodological models commonly used for cost estimation do not adequately consider the interpretability of the estimation results, making it difficult to promote their application in real-world scenarios. In this paper, an interpretable machine learning method is introduced into the study of cost estimation of metro construction projects, and a maximum relevance and minimum redundancy (mRMR)–light gradient boosting machine (LightGBM)–Shapley additive explanations (SHAP) interpretable assisted investment decision-making framework is proposed. The results show that the negative impact of variable multicollinearity on model prediction is avoided by quantitatively identifying the key driving variables of costing through mRMR based on the historical data of metro construction projects and macroeconomic data. LightGBM is employed to predict the cost of metro construction projects with a mean absolute percentage error of 13.00%, surpassing the accuracy of the five baseline models. The SHAP method's introduction explains the influence of key driving variables on the model prediction response at both global and local levels, which improves the decision trust of the cost estimation of metro construction projects. The study takes into account the impact of key driving variables on the model's prediction response in a real-world context and balances the needs for estimation accuracy and variable interpretability in real-world scenarios. Practical Applications: In this study, we propose a new interpretable machine learning method that helps improve the decision trust of cost estimation for metro construction projects. We use the mRMR module to identify the key driving variables for cost. Based on the LightGBM module, we accurately fit the nonlinear relationship between the cost of metro construction projects and the key variables. The SHAP algorithm is introduced to analyze the effects of the key driving variables on the prediction of the model at both global and local levels. The combined mRMR-LightGBM-SHAP model is proven to have better prediction accuracy than the traditional prediction model under the same conditions, and the SHAP response results prove the reliability of the model prediction. The study also found that the inclusion of economic environment variables plays a positive role in improving the accuracy of cost estimation for metro construction projects. The research results can be mainly used by metro investment units to quickly confirm or review the cost of metro construction projects, and they can also help government departments pay close attention to the impact of the external economic environment on the cost of metro construction. [ABSTRACT FROM AUTHOR]

With the digital transformation of the construction industry, the need to improve construction business process collaboration and automation is increasing. However, as construction projects usually involve many stakeholders with complex relationships and insufficient mutual trust, the existing technologies cannot fulfill the requirements of the construction industry. This paper explores the integration of blockchain, smart contracts, and process automation technologies into construction business processes, shedding light on both managerial and technical challenges. The study introduces a comprehensive technical framework meticulously designed to align with the intricate nature of construction practices while focusing on the resolution of legal complexities associated with smart contract applications and the facilitation of process collaboration and automation. The framework comprises three core modules: (1) action definition and extension to process models, (2) standardized mapping for automatic smart contract generation, and (3) smart contract visualization for reliable process collaboration and automation. This multifaceted approach caters to the specific needs of construction management, standardization, interoperability, and visualization. The framework's practicality is further evaluated through real-world testing within a construction payment case, effectively showcasing its efficacy and applicability in tangible business scenarios. While this paper represents a significant step forward in addressing construction business process collaboration and automation challenges, it acknowledges the necessity for ongoing research and development to refine and expand these innovative solutions to meet the evolving demands of construction management. Practical Applications: Currently, there is a significant escalation in the severity of disputes within the construction industry. The adoption of blockchain technology allows for the redistribution of trust within a construction project, shifting reliance from individuals to the system itself for better collaboration and fewer disputes. Although blockchain can help foster a more secure and transparent environment, at the process level, an efficient workflow engine is needed to activate processes in this environment. Therefore, this study proposed an approach to generating smart contract codes based on construction business processes in a standardized way and further visually executing these codes for the processes with historical transactions stored in blockchain. This approach can reduce the effort of smart contract programming and improve the standardization and credibility of smart contract generation. It can also streamline the procedure from construction business process design to final execution via predefined and visual modules. Meanwhile, the generation prototype is open sourced to provide transparency and further enhance the approach. To indicate practical implications in the real world, this study provided a case of construction payment, but the solution is not limited to the payment scenario. [ABSTRACT FROM AUTHOR]

Dynamic cone penetrometer (DCP) has been commonly used for the evaluation and quality control/assurance of soils before, during, and after construction in civil engineering projects. This test equipment has been increasingly used for geotechnical engineering applications but not yet been used to evaluate lightweight cellular concrete (LCC) as a backfill material. This technical note reports laboratory and field DCP tests to evaluate the properties of LCC. To establish the relationship between DCP data and other material properties, unconfined compressive strength and California bearing ratio (CBR) tests were conducted on this material. The test results showed that the measured unconfined compressive strength and CBR of LCC increased as its density increased. The DCP indices (DCPI) for the LCC specimens at different densities were almost constant with the penetration depth. This technical note proposes the correlations between the DCPI and the unconfined compressive strength and CBR, which may be used for future applications. [ABSTRACT FROM AUTHOR]

Effective quality management is essential for ensuring construction quality, adhering to schedules, and controlling costs. The application of Building Information Modeling (BIM) for quality control during the construction phase presents challenges, particularly with the real-time monitoring and tracing of onsite quality data. In response, we propose a framework that integrates Internet of Things (IoT)-based quality data with four-dimensional (4D) BIM for enhanced quality monitoring and acceptance. This framework includes (1) automatic segmentation of 4D BIM, (2) collection and mapping of quality data, and (3) real-time monitoring and assessment of quality. We validated our framework in a large-scale building project in Wuhan, China, focusing on concrete engineering quality acceptance. The results demonstrate that our integrated framework effectively captures and integrates live quality data in real-time into 4D BIM models for ongoing monitoring and assessment. The contribution of our research lays the foundation for the development of an integrated BIM-IoT framework for real-time quality monitoring, improving its efficiency and accuracy during quality acceptance in construction. Practical Applications: This study presents a practical solution for real-time quality monitoring and acceptance at construction sites through the integration of 4D Building Information Modeling with IoT technologies. By facilitating real-time quality monitoring and data capture, the framework significantly enhances decision-making processes. Construction managers can use this system to promptly detect and resolve quality issues, thereby reducing rework costs and likelihood. Additionally, this integrated framework ensures compliance with stringent quality standards, providing a reliable method to meet all construction project specifications. The capability to continuously update the 4D BIM model with live data enables dynamic resource management and optimizing workerpower. Consequently, this approach leads to improved project outcomes, higher-quality buildings, and greater client satisfaction. In a case study involving a large-scale high-rise building project, the framework demonstrated its effectiveness by integrating live quality data into 4D BIM for ongoing monitoring and acceptance. The results underscored the framework's potential to provide stakeholders with timely information and implement corrective actions, significantly enhancing the efficiency and reliability of construction quality acceptance. [ABSTRACT FROM AUTHOR]

This research presents a novel microlevel (i.e., project-level) construction productivity framework aimed at measuring and benchmarking productivity consistently within and between projects, work packages, and activities. Using a design science research approach, the framework was rigorously developed with data collected from UK-based construction projects and refined through several cycles of implementation and industry engagement. The framework is useful in providing new insights into project performance, helping understand process variability, setting benchmarks, and conducting data analytics for improved decision making. This framework can be used for industrywide measurement both within and across subsectors of construction in the UK and internationally. [ABSTRACT FROM AUTHOR]

Prefabrication is highly recognized in construction due to its inherent cost efficiency, quality control, and sustainability benefits. However, the presence of uncertainties in prefabrication processes hinders the realization of these advantages, necessitating addressing production time uncertainty. Mixed reality (MR) has demonstrated promising outcomes in mitigating time uncertainties as an immersive visualization and simulation technology in different domains. Therefore, this study investigates the impact of MR-based approaches in prefabrication to reduce time uncertainty. The methodology comprises Discrete event simulation (DES) modeling, correlation analysis, and the development of an MR-based immersive visualization and simulation tool. Following an initial work study to measure standard times, visualizations of 13 processes in the prefabricated panel production were developed in the Unity environment and deployed on the HoloLens 2. Through several work studies before and after MR implementations, the study demonstrated a 10.8% reduction in the total completion times (P99) in correlated production activities. Findings emphasize that MR reduces time uncertainty by providing an immersive, interactive, and dynamic approach, ultimately improving efficiency in prefabrication. The study contributes to existing knowledge by quantifying the impact of MR on completion times and underscores the importance of addressing time uncertainties for sustainable lean prefabrication. The sensitivity analysis results prioritized the reinforcement trade in managerial decision-making, emphasizing the need for MR-based approaches for targeted improvement opportunities. Minimizing scheduling uncertainty is of practical importance in realizing prefabrication benefits. Practical Applications: This study emphasizes the practical applications of MR technology in the construction industry, specifically in the prefabrication process. By utilizing the developed MR-based approach as an immersive visualization and simulation tool, construction stakeholders can streamline their operations, reduce uncertainties, and achieve significant benefits. The MR-based approach enables real-time monitoring, analysis, and collaboration among project teams, empowering them to make informed decisions and adapt to dynamic production processes. By quantifying the impact of uncertainties and delays, stakeholders can prioritize MR-based approaches, particularly for skilled trade teams, to optimize resource allocation and improve production efficiency. Further, MR contributes to achieving lean production targets of prefabrication by optimizing resource usage, enhancing values, and reducing waste. The findings emphasize the importance of MR in managerial decision-making, providing insights that enable informed choices to maximize efficiency and productivity. The study demonstrates how MR can revolutionize prefabrication practices, making construction projects more sustainable, cost-effective, and efficient. [ABSTRACT FROM AUTHOR]

The positive outcomes associated with the Last Planner System (LPS) of production control are usually interpreted as stemming from the application of LPS-as-theorized in the seminal publications about this method. However, the use of LPS in real settings is subjected to contextual influences and involvement of actors with varying perspectives of what counts as an effective implementation. This suggests that LPS-as-theorized may not be the only valid and sufficient representation to explain its success. This paper investigates how the different representations of LPS contribute to its effectiveness and adaptation to local conditions. It is based on a case study on the implementation of LPS in a refurbishment project. Four representations are compared: LPS-as-theorized (literature based), LPS-as-prescribed (handbook based), LPS-as-disclosed (interviews based), and LPS-as-done, i.e., what happened in reality, according to different sources of evidence. Findings set the basis for proposing a model that frames LPS-as-done as an emergent phenomenon unique to each construction project. This new perspective contributes to the recognition of the role of informal practices, the development of more accurate assessments of LPS implementation, the analysis of trade-offs when using LPS, and the alignment of expectations on the adoption of LPS. Practical Applications: The outcomes of this investigation can help practitioners to identify and appreciate the complementary roles of different representations of the LPS, which are not limited to LPS-as-theorized described in seminal academic papers. The use of LPS in real settings depends on contextual factors and is therefore always unique to some extent. Giving visibility to diverse representations (e.g., LPS-as-prescribed in companies' handbooks, LPS-as-disclosed by managers) supports a more accurate and shared understanding of how LPS is implemented, making it possible to align expectations among project stakeholders. This analysis also sheds light on the need to fill the gaps in the formal planning system, setting the basis for revising procedures and training programs. Furthermore, the findings suggest that the assessment methods of LPS implementation should be based on different sources of data in order to account for the multiple representations. Overall, the results are likely to resonate with practitioners because these will recognize that they are not merely strictly following predefined procedures but rather playing an active role that demands expertise for adjusting theory into practice on an everyday basis. [ABSTRACT FROM AUTHOR]

Nowadays a lot of organizations and project-oriented governmental and private companies have been leading their approach from project-oriented management to project-oriented basket management to answer to pointed problems, the necessity of having meaningful relation of approaches, themes, and projects and aim of them to more efficiency to themes and their projects. Project basket management is a new approach is grown from project management knowledge and the meaning was focused on the management of combining targeted projects and special situations it deemed to be a high level of project management and themes of them in organizations and offering the model of effective criterion models and optimal projects in selecting portfolios of constructions projects were studied in this survey. The results showed that five effective and basic indexes for optimal selecting of construction projects are: budget indexes and supply of resources, scheduling of management indexes, management indexes and risk reduction, detailed documental indexes, and parallel operation of indexes. The results showed that there is a meaningful and positive effect in surveys of hypothesis 1, budget indexes, and supplying resources in optimal management of construction project portfolios. The meaningful levels of hypothesis equals 0 and lower than 0.05 according to results and then the project hypothesis is approved by this meaning that budget and supplying resources have a positive and meaningful effect on optimal management of construction project portfolios. The amount of this effect is 0.513 By noticing this coefficient is positive and the effect of that is direct. In other words, changing a unit (increasing) budget index and supplying resources by the amount of 0.513% leads to increasing optimal management on construction project portfolios. The meaningful level of the hypothesis was equal to 0 and lower than 0.05 according to the results. The meaningful hypothesis of this hypothesis is approved by the meaning that parallel operation of them on construction projects of portfolio and optimal management have a meaningful and positive effect. The amount of this effect is 0.615 and the effect of that is direct by noticing that this coefficient is positive. In other words, changing a unit of parallel operation by the amount of 0.165 percent is increased in the optimal management of construction project portfolios. [ABSTRACT FROM AUTHOR]

ABSTRACT The socioeconomic prosperity of a region is intricately tied to its infrastructure development, particularly the connectivity provided by highways. Preserving the economic well‐being of an area demands meticulous planning and the execution of construction projects with minimal risk. Landslide hazard zonation (LHZ) is a crucial tool for assessing the likelihood of landslide occurrences in specific regions. This study delves into the LHZ of a 171.2 km2 area, focusing on critical causative factors such as slope inclination and aspect, slope mass material, Land Use/Land Cover (LULC), distance from fault lines, roads, and drainage systems. The classification resulted in four distinct zones along the National Highway (NH‐109) stretch from Bhowali to Almora. Notably, the moderate‐hazard zone encompasses 60.4% of the area, followed by the high‐hazard zone at 24.4%, the low‐hazard zone at 11.9%, and the very high‐hazard zone at 3.3%. To enhance the reliability of the study, 63 previously identified landslide locations were marked based on diverse sources, including field studies and landslide inventory data from the Geological Survey of India (GSI). In the validation process, 12 past landslide occurrences were situated within the very high‐hazard zone, 32 in the high‐hazard zone, 18 in the moderate‐hazard zone, and only one in the low‐hazard zone. The receiver operating characteristic (ROC) curve yielded a commendable quality with a % area under the curve (AUC) of 71.2%. In summary, this research underscores the importance of LHZ in assessing and mitigating landslide risks along a stretch of the NH‐109 corridor. The findings provide valuable insights for informed decision‐making in infrastructure development and risk management, contributing to the sustainable growth and protection of the region's livelihood. [ABSTRACT FROM AUTHOR]

Sustainability principles should be incorporated into all decision-making stages for residential construction projects to ensure maximum revenue while maintaining essential residential building services. This study identifies and analyzes the critical success factors (CSFs) necessary for implementing agile project management (APM) in residential construction projects. Data were collected from 120 professionals in the Nigerian construction industry through questionnaire surveys to understand the implementation of APM. The CSFs were obtained from previous research and analyzed within the specific context of the Nigerian construction industry through questionnaire surveys. The CSFs were grouped into two main categories using exploratory factor analysis: dynamic project optimization and agile project foundations. The model for the CSFs was developed using partial least squares structural equation modeling. The study found that the dynamic project optimization element had the most significant impact on the model, highlighting its importance as a key CSF in APM implementation. These results support the adoption of APM within Nigeria's construction industry as stakeholders and professionals seek effective strategies to reduce costs and improve sustainability. [ABSTRACT FROM AUTHOR]

Predicting rock tunnel squeezing in underground projects is challenging due to its intricate and unpredictable nature. This study proposes an innovative approach to enhance the accuracy and reliability of tunnel squeezing prediction. The proposed method combines ensemble learning techniques with Q-learning and online Markov chain integration. A deep learning model is trained on a comprehensive database comprising tunnel parameters including diameter (D), burial depth (H), support stiffness (K), and tunneling quality index (Q). Multiple deep learning models are trained concurrently, leveraging ensemble learning to capture diverse patterns and improve prediction performance. Integration of the Q-learning-Online Markov Chain further refines predictions. The online Markov chain analyzes historical sequences of tunnel parameters and squeezing class transitions, establishing transition probabilities between different squeezing classes. The Q-learning algorithm optimizes decision-making by learning the optimal policy for transitioning between tunnel states. The proposed model is evaluated using a dataset from various tunnel construction projects, assessing performance through metrics like accuracy, precision, recall, and F1-score. Results demonstrate the efficiency of the ensemble deep learning model combined with Q-learning-Online Markov Chain in predicting surrounding rock tunnel squeezing. This approach offers insights into parameter interrelationships and dynamic squeezing characteristics, enabling proactive planning and support measures implementation to mitigate tunnel squeezing hazards and ensure underground structure safety. Experimental results show the model achieves a prediction accuracy of 98.11%, surpassing individual CNN and RNN models, with an AUC value of 0.98. [ABSTRACT FROM AUTHOR]

This study proposed novel designs for achieving self-centering (SC) behavior using superelastic shape memory alloy (SMA) buckling-restrained plates (BRPs). Compared with previous studies relying on small-diameter SMA bars, this study employed large-dimensional SMA plates that could provide sufficient strength for real construction projects. The design concept and configurations of SMA-BRPs were first introduced. Corresponding tests were then conducted. Three specimens were tested, including one that was unsatisfactory and two that were acceptable. Based on the initial examination of the behavior and failure mode of the unsatisfactory trial specimen, the corresponding modifications were made to achieve the improved performance of two acceptable specimens. Subsequently, the hysteresis and SC behaviors, energy dissipation capacity, and yielding strength degradation of the two acceptable specimens were investigated. Both specimens exhibited high-quality flag-shaped behaviors in their tension–compression cycles, with their strengths reaching around 200 kN under tension and more than 310 kN under compression, representing one of the largest strength values shown by a single SMA element in the literature. Asymmetric behavior was observed under tensile and compressive loadings, primarily due to the asymmetric behavior of the SMA base material, high-mode inelastic buckling under compression and friction between the SMA core plate and buckling-restraining device. After the tests, finite element models were developed to obtain an in-depth understanding of the detailed behavior of SMA-BRPs. The studies showed that SMA-BRPs successfully achieved the SC buckling-restraining design target. The design incorporating end restrainers was preferred due to its flexibility, which reduces application restraints. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has struck the construction industry gravely. Accordingly, numerous studies reported the impact of COVID-19 on various aspects of the construction industry and projects. However, there exists no framework that can guide the evaluation of holistic impact of COVID-19 on a construction project specifically for developing countries. To fulfill this knowledge gap, this study conducted state-of-the-art review of recent related journal articles from developing countries and developed an eight-dimensional assessment framework to assess the impact of COVID-19 on construction projects. These eight dimensions include: (1) on-site safety measures, (2) productivity, (3) supply chain management, (4) transportation, (5) labor issues, (6) time and cost performances, (7) contractual implications, and (8) social impact. Additionally, to demonstrate the usefulness of the framework, the study utilized the framework to assess four projects in three developing countries: Saudi Arabia, Pakistan, and Bangladesh. Finally, the study presented the best practices to mitigate the impacts of any future wave of COVID-19 on construction projects. The developed framework holds potential applications ranging from policy planning to construction operations under COVID-19 and similar pandemics. It can be implemented to assess the impacts of COVID-19 on the construction industry, evaluating project performance across eight dimensions. Moreover, it aids in the development of COVID-19 impact management actions to control project performance. Additionally, the framework assists in building organizational resilience for managing construction projects under the challenges posed by COVID-19 or similar pandemic scenarios. [ABSTRACT FROM AUTHOR]

[Objective] This study aims to comprehend the spatial distribution patterns of arable soil nutrients in various geomorphic conditions of the Loess Plateau, to unveil the driving factors behind these changes, and to provide the critical insights for precision management in the regional agriculture and the construction of agricultural projects. [Methods] Based on the 2020 soil nutrient data from the Loess Plateau in Shaanxi, the Kriging interpolation method was employed to analyze the spatial patterns of soil nutrients across four different geomorphic types. The driving factors behind these nutrient spatial variations was explored by using the geodetector model. [Results] (1) In the Loess Plateau, spanning from the Great Wall's sandy lands, through the hilly and gully regions of northern Shaanxi, the loess table lands in northern of Weihe River, to the Guanzhong Plain, the average contents of soil organic matter (SOM), total nitrogen (TN), available phosphorus (AP), and available potassium (AK) exhibited a gradual increasing trend. Specifically, the SOM content averaged 10.20, 10.08, 15.28, and 18.78 g/kg, respectively, across these regions. TN averaged 0.63, 0.66, 0.98, and 1.19 g/kg. AP level averaged 12.99, 13.10, 16.97, and 27.24 mg/kg, and AK averaged 117.72, 149.94, 217.27, and 252.83 mg/kg, respectively. This trend indicated a consistent increase from the sandy lands to the plains. (2) In the loess area of Shaanxi, the duration of sunshine had most significant factor influencing overall nutrient contents, followed by annual temperature and fertilizer use. The distribution of nutrients in the windy area was predominantly affected by soil bulk density, whereas in the hilly and gully areas, plateau areas, and plains, fertilizer use was the primary influencing factor. The interaction of various factors provided a more comprehensive explanatory of nutrient dynamics than individual factor alone. [Conclusion] To optimize soil health, it is advisable to increase nutrient input and enhance soil fertility retention in sandy areas and hilly and gully areas. In contrast, the focus should be on improving nutrient utilization efficiency for plateau and plain areas. Additionally, in the process of farmland, it is crucial to tailor human activities to suit the environmental characteristics and specific conditions of different geomorphic regions. [ABSTRACT FROM AUTHOR]

The construction industry is characterized by its fragmented nature, which introduces numerous uncertainties and challenges for project management. Analyzing project impact factors is crucial for federal agencies to mitigate risks, make informed decisions, and ensure successful project outcomes. Although many previous studies explored critical project impact factors for various project types, this paper's primary objective is to identify and categorize the impact factors critical to projects' success in federal facilities. Additionally, the study ranked impact factors based on their significance and relevance to project management teams in federal facilities. The study surveyed federal agencies to identify the top-ranking factors within and across categories based on their impact. The research methodology encompassed a thorough literature review, data mapping, survey development, and analysis to identify, classify, and rank impact factors for federal projects. Spearman's rank-order correlations were computed for correlations between the impact factor categories. The impact factors were ranked based on their relevance and importance for the federal facilities based on frequency distributions of survey results—aligning with the data mapping and correlations exercises. The study's findings indicate that the top five factors with a maximum negative impact on the federal capital facility project belong to the early project life cycle phases, classified within the Governance and Stakeholders and Planning and Execution categories. The paper's findings aim to emphasize the optimization of stakeholder engagement and strategic planning to address critical risks for federal capital facilities projects early in the project life cycle—particularly the detailed engineering and procurement stages. The study's findings contribute to a better understanding of project management in the federal sector and offer beneficial guidance for future project planning and execution. [ABSTRACT FROM AUTHOR]

Modern slavery is an illegal and unethical phenomenon affecting more than 40 million victims worldwide, with many of them employed in construction. This article aims to investigate why modern slavery continues to exist on construction sites managed by companies that have pledged to fight it. Primary data were collected using semistructured interviews with 22 experts working in construction companies in three organization for economic co-operation and development (OECD) countries (UK, Australia, and Switzerland) and analyzed using inductive thematic analysis. The construction companies were the unit of analysis, and their managers were the primary source of information. The results present the mechanisms that explain the difference between the official antimodern slavery statements of construction companies and the empirical observations on construction sites. The primary mechanisms are a lack of awareness, training, response, and responsibility, as well as alternative priorities. The results further show the role and importance of reporting cases of modern slavery in addressing it. The risk areas of modern slavery in construction projects, which include the lower tiers of subcontracting and the supply chains of construction materials, are identified. Furthermore, the article discusses the reasons behind the trivialization of modern slavery in construction companies: the presence of alternative priorities, the fear of reputational damage, blame-shifting, and minimizing the problem. Finally, we propose recommendations for construction companies and managers to help address modern slavery and offer areas for future research. This article presents two key novel contributions. First, we discovered a disconnection between construction companies' official antimodern slavery statements and the reality on construction sites. Second, we identified the reasons behind this disconnection. Practical Applications: Due to its low profit margins and project time constraints, the construction sector is plagued by unethical and illegal practices, including modern slavery. Modern slavery can result in reputational damage, financial repercussions from legal penalties, and loss of trust and opportunities among stakeholders. Therefore, construction companies and employees must be better informed about the ethical, legal, and economic implications of modern slavery, and construction companies must implement stricter regulations to address modern slavery. They should provide continuous and mandatory training to all employees, conduct regular site audits for laborers, raise awareness through posters and social media, and educate employees about reporting. Modern slavery should be addressed not only for ethical reasons but also for the quality and sustainability of construction projects. Finally, addressing modern slavery protects the reputation of construction companies and professionals and, most importantly, safeguards laborers' dignity, health, safety, and well-being. [ABSTRACT FROM AUTHOR]

Contract flexibility is like a double-edged sword for contractor opportunistic behavior, and it may both inhibit and promote such opportunistic behavior. This study constructs a dual-path integration model in which contract flexibility affects contractor's opportunistic behavior through trust and conflict. Based on principal-agent theory, building information modeling (BIM) application degree was selected as a moderating variable for the double-edged sword effect of contract flexibility. A partial least-squares structural equation model (SEM) was used to verify hypothesis based on data collected from 271 questionnaires. The results show that contract flexibility has a positive effect on reducing the opportunistic behavior of contractors through trust, and at the same time, it induces the opportunistic behavior of contractors through payment conflicts. Additionally, the BIM application degree does not solve the double-edged sword effect dilemma of contract flexibility, but amplifies the negative effect of contract flexibility, and then induces the contractor's opportunistic behavior. The findings of this study contribute to the formation mechanism and governance strategy of contract flexibility. It also finds that the use of BIM technology has not achieved the desired effect because the technological development is not synchronized with the development of organizations and people, which provides a new research perspective for the integration of social and technological systems. [ABSTRACT FROM AUTHOR]

Since hydration heat generated during construction has been the cause of cracking and deformations in mass concrete structures, selecting appropriate thermal control plans is crucial in mass concrete construction. However, developing numerical models to predict the heat of hydration in mass concrete involves complex processes that demand extensive knowledge in thermodynamics and related fields, which can result in increased costs and extended timelines for construction methods and material selection. To address this problem, this research aims to develop a simple decision-making framework to select a cost-effective thermal control method using nomograms for materials and construction engineers. Several nomograms, including temperature and cost nomograms, were used to provide the most cost-effective thermal control plans while satisfying the maximum temperature limits of mass concrete. A case study of an actual construction project was used to validate and demonstrate the proposed framework. The effectiveness of this framework was demonstrated through a case study on a real construction project, which validated the approach and confirmed its potential to reduce the time required for developing thermal control plans in mass concrete construction projects. The findings from this study highlight the proposed framework's capability to streamline the thermal control method selection process, thereby facilitating a more intuitive understanding of thermal control options and markedly reducing both costs and time in mass concrete construction projects. [ABSTRACT FROM AUTHOR]

Recently published professional learning outcomes require future engineers to think of the impacts that engineering decisions have on society. History shows that construction and civil engineering projects can exacerbate inequality by ignoring community concerns and failing to consider the impacts on marginalized and vulnerable stakeholders, among other factors. How might construction engineering professors help students meet these standards, and how do construction and civil engineering students respond when construction engineering is framed as inextricably linked to these obligations? We designed and evaluated curriculum modules aimed at helping develop a critical consciousness with construction and civil engineering students (N=177) in three construction and civil engineering courses at two universities in the midwestern region between 2020 and 2021. The curriculum builds on a three-phase framework aimed at encouraging students to see social inequities and their impacts, finding social inequities unjust, and enhancing reflective self-awareness. Post-implementation responses to the case study designed to make clear the need for a critical consciousness in engineering found that students responded positively to both the instructional approach of a case study and the content connected to critical consciousness. We discuss implications for the development of further curriculum and the implementation of such an approach. [ABSTRACT FROM AUTHOR]

This research paper examines the heritage value of construction documentation and processes via Virtual Reality (VR), with a focus on the Sydney Opera House (SOH). It underscores the importance of comprehending and documenting transient construction techniques for heritage valuation. Utilising VR, the study offers an immersive portrayal of the SOH's construction, emphasising its innovative methods, craftsmanship, and environmental challenges. The paper draws from the Digital Heritage Construction project, showcased at the Heritage Exposition of the ICOMOS General Assembly 2023. This project featured two VR simulations, developed through analysing 200 original shop drawings, historical photographs, and site minutes and reports. The first simulation illustrates the formwork systems used for the SOH's iconic sails, while the second elucidates the assembly methods for the precast vaulted roofs, including the operation of the telescopic erection arch and the installation of concrete segments. The paper examines the novelty of this approach through a survey conducted at the Heritage Exposition. Analysis of the survey's result reveals VR's effectiveness in deepening the appreciation of architectural heritage's intangible qualities, providing new insights into the historical construction processes of the building and their cultural significance. [ABSTRACT FROM AUTHOR]

While contractors may experience financial failure if they bid on an inappropriate project, bidding on the right project may allow them to profit substantially. Therefore, understanding the various factors that influence the bid/no-bid decision is crucial for construction companies in determining whether to pursue a project. The present study aims to identify the critical factors influencing contractors' bid/no-bid decisions. A total of 112 responses were collected from a questionnaire survey to rate the relative importance of 22 factors, and these factors were then analyzed based on the type of project and the contractor's years of experience. The results indicate that the client's ability to pay, clarity of the scope of work, project cash flow, the need for work, and availability of qualified labor are the most critical factors influencing contractors when making bid/no-bid decisions. The factor "previous experience in similar projects" was statistically significant among building and infrastructure projects, while "project location" was statistically significant among contractors with different years of experience. Finally, factor analysis identifies the six major underlying groups: client-related factors, bidding-related factors, contractor-related factors, market-related factors, economy-related factors, and project-related factors. The study's findings can help contractors better understand the factors influencing their bidding-related decisions. [ABSTRACT FROM AUTHOR]

Cement-based composites (CBCs) are essential in the construction sector due to their cost-effectiveness, availability, and versatility, but they struggle with low tensile strength and poor heat resistance. Recent advancements have highlighted the potential of nanomaterials, particularly graphene oxide (GO), in enhancing the mechanical, thermal, and electrical properties of CBCs. This study aims to provide a comprehensive review of the incorporation of GO into cementitious composites, examining its impact on microstructure, mechanical properties, rheology, and durability; thus, a bibliometric review and scientometric analysis were conducted to thoroughly evaluate the existing literature. A total of 263 studies were selected for thorough study. It can be concluded that GO content acts as a pore filler, decreasing porosity by 23% and average pore size by 22%, while boosting compressive strength by up to 15% at a 0.05% concentration. It also enhances workability, stability, and resistance to chloride ingress, sulfate attack, alkali–silica reaction, and carbonation. Incorporating GO reduces cement consumption and carbon footprint, leading to more durable structures and supporting sustainable construction by efficiently utilizing waste materials. The optimal GO concentration for these benefits ranges from 0.03% to 0.1% by weight of cement, as higher concentrations may cause agglomeration. GO-modified cementitious materials are well suited for high-performance and durable applications, particularly in environments with chemical and mechanical stresses. [ABSTRACT FROM AUTHOR]

The transport sector emits 18% of global CO2. Industry and consumers must adopt green mobility to reduce emissions and climate change. This will help achieve sustainability by improving efficiency and reducing greenhouse gas emissions. Thus, smart electric vehicles (SEVs) have emerged. Digital twins concept and technology may help launch SEVs to the market by analysing and optimising supporting infrastructure. This work aims to fill in the gaps between different pieces of research by giving a full review from a technical and scientifically neutral point of view. The study looks at how digital twin technology can be used in smart car systems by looking at its promise and the hurdles faced. Based on a comprehensive literature survey, this is the first in-depth look at how digital twin technology can be used in smart electric cars. The review has been organised into specific areas of the smart vehicle system, such as drive train system battery management system, driver assistance system, vehicle health monitoring system, vehicle power electronics. This review goes into detail about each component of the car to provide an overall view of the smart vehicle system as a whole. This review makes it easier to understand how digital twin technology can be utilized into each area from a scientific point of view. Lastly, the work looks at the technological and economic impact of digital twin technology, which will make considerable changes in car manufacturing processes, as well as help address current obstacles in utilizing advanced technologies. [ABSTRACT FROM AUTHOR]

While pedestrian crashes on suburban roads have received more attention over recent years, the role of pedestrian crossing risk in areas adjacent to pedestrian crossing facilities, such as pedestrian overpasses, has been neglected. Most pedestrians in suburban areas tend to avoid pedestrian overpasses, exhibiting crossing behaviors that increase the likelihood of pedestrian-involving crashes. As a result of the presence of overpasses, drivers may think that there are no pedestrians in the surroundings, so they choose a speed based only on the prevailing traffic and road environment without accounting for potential interactions with pedestrians. Consequently, crashes will occur, with pedestrians typically being the most seriously affected casualties. In this study, using video recordings from a suburban road in Amol-Babol, Iran, the risk of pedestrian crossing behavior in areas near pedestrian overpasses is investigated. The speed selection behavior of drivers in these areas has also been examined using speedometer cameras. To quantify the level of risk for pedestrians when interacting with approaching vehicles during the crossing movements, the post encroachment time (PET) was used as a surrogate safety measure. Based on critical thresholds of PET, three different risk levels were identified using a K-means algorithm: high, medium, and low risk. To identify the elements affecting the risk of pedestrian crossing behavior, structural equation models were estimated for all three risk levels. The results showed that human factors, relating to both drivers and pedestrians, have a dominant impact on pedestrian safety, especially in high and medium risk contexts. Road and vehicle factors were also found to have statistically observable effects on pedestrian safety, but to a milder extent compared to human factors. The findings of this study highlight the need for intervening in several aspects of vehicle-pedestrian interactions with critical importance for pedestrian safety, including road users' performance and compliance, state of alertness, and interaction with road infrastructure. [ABSTRACT FROM AUTHOR]

To promote the improvement and development of China's automotive industry policy, this study conducts a systematic review and hierarchical analysis of both domestic and international automotive industry policies. First, the automotive industry policies of the United States, Germany, South Korea, and Japan are summarized in terms of their industrial structure adjustment, technological innovation, taxes and financial subsidies, and infrastructure construction. Benchmarking the policies of international automotive industry powers provides a reference and basis for integrating their experiences in the formulation of China's automotive industry policy. Second, beginning with China's "Automotive Industry Policy" issued in 1994, the key automotive industry policies at different points in history and under different strategies are analyzed. Through policy adjustment and target setting, the changing focus through the historical development of China's automotive industry is determined, along with the development of the industry and technological progress. Then, from the perspectives of strategic planning, promotion and application, credit management, infrastructure, management standards, and standard systems, the advantages and disadvantages of current development policies for new energy and intelligent connected vehicles are clarified. The challenges and limitations of China's automotive industry policy are summarized, including a lack of investment in technology research and development, low level of infrastructure support, and insufficient consumer protection. China's automotive industry policy is then into three different historical stages: i) 1994 to 2008, ii) 2009 to 2013, and iii) 2014 to present; and the characteristics of each stage are summarized. Finally, based on China's national conditions and considering the future development trends of the international automotive industry, the study concludes that under the strong drivers of carbon peak and neutrality goals, China's future automotive industry policy should feature energy saving and emission reduction as the main goals. Independent innovation should be the main enabler, strengthening and supplementing the supply chain through intelligent connectivity. [ABSTRACT FROM AUTHOR]

The years we are experiencing are often identified as those of the age of digital technologies, where "digital" is commonly associated with intelligence, efficiency, and convenience. The emergence of digital technologies has significantly impacted and transformed various aspects of our society compared to the past. In this panorama, some arising questions regard transportation infrastructure systems and, first of all, highway infrastructure. This research focuses on one central issue: how highways fit into this digital revolution. Actually, the work in this paper can be described as follows. Although there are many different theoretical model systems for the architecture of the digital twin, we have chosen to review the main body of research on the digital twin in highway infrastructure based on a relatively well-established modeling framework, the five-dimensional model of the digital twin. After discussing the components of the digital twin for highway infrastructure's five-dimensional model, the paper reviews some innovative technologies that make these items effective. In addition to this, the digital twin maturity level of highway infrastructure and the MBSE-based (model-based systems engineering) digital twin model for highway are also discussed in this paper. Therefore, the paper provides a bird's eye view of this extremely dynamic technology for a new system of intelligent highways and discusses some of their criticalities and strengths, allowing for the optimization and development of new transportation functions and services, improving the adaptability of highways to the digital revolution. [ABSTRACT FROM AUTHOR]

Major railway projects are large-scale, complex systems involving multiple stakeholders, and the risks during the construction process can be multifaceted and constantly evolving. To enhance the risk prevention and control capabilities in such projects, according to resilience theory, the study proposed a resilience management model based on risk prevention and control and outlined a framework for resilience construction management mode in major railway resilience construction projects. Using stakeholder theory, an integrated virtual organizational structure model for major railway construction was introduced. The resilience construction management mode combined organizational management and intelligent project management, embedding risk prevention and control into the organizational management system. This approach enhanced the resilience of organizational structure, strengthened its capacity to respond to risks and challenges, and leveraged intelligent technologies to boost collaborative capabilities. Additionally, the operational mechanism of resilience management was analyzed, which was governed by contractual, administrative, and trust-based relationships. The research results provide theoretical insights and decision-making strategies for risk prevention and control in major railway projects. [ABSTRACT FROM AUTHOR]

The architecture, engineering, and construction (AEC) industry faces ongoing challenges in enhancing safety performance. Despite the availability of advanced technologies for enhancing safety, there is limited understanding of the inter-relationships among safety factors and advanced technologies for enhancing safety performance. This study aims to investigate the inter-relationships among factors affecting safety performance and advanced technologies. A questionnaire survey was disseminated to construction professionals to assess the criticality of factors and strategies. The data were analyzed using descriptive statistics, correlation analysis, and exploratory factor analysis (EFA). The findings indicate that 16 factors and eight advanced technologies are critical for enhancing safety. The EFA grouped 11 critical factors into four underlying groupings: safety planning and hazard prevention, workplace environment and supervision, employee safety support, and medical readiness and site protection. Moreover, the EFA grouped the eight critical advanced technologies into two underlying groupings: advanced digital technologies and personal and site monitoring technologies. The correlation analysis demonstrates measurable but weak associations between the factors and advanced technologies, indicating the need for future research to explore additional variables that may impact these relationships. The findings help construction professionals prioritize resources to address the specific groupings of critical factors and advanced technologies. [ABSTRACT FROM AUTHOR]

Various hydrogeological problems like groundwater inflow, water table drawdown, and water pressure redistribution may be encountered in the construction of hydraulic projects. How to accurately predict the occurrence of groundwater inflow and assess the drainage effect during construction are still challenging problems for engineering designers. Taking the Jinzhai pumped storage power station (JPSPS) of China as an example, this paper aims to use different methods to calculate the water inflow rates of an underground powerhouse and evaluate the drainage effect caused by tunnel inflow during construction. The methods consist of the analytical formulas, the site groundwater rating (SGR) method, and the Signorini type variational inequality formulation. The results show that the analytical methods considering stable water table may overestimate the water inflow rates of caverns in drained conditions, whereas the SGR method with available hydro-geological parameters obtains a qualitative hazard assessment in the preliminary phase. The numerical solutions provide more precise and reliable values of groundwater inflow considering complex geological structures and seepage control measures. Moreover, the drainage effects, including a seepage-free surface, pore water pressure redistribution, and hydraulic gradient, have been accurately evaluated using various numerical synthetic cases. Specifically, the faults intersecting on underground caverns and drainage structures significantly change the groundwater flow regime around caverns. This comparative study can not only exactly identify the capabilities of the methods for cavern inflow in drained conditions, but also can comprehensively evaluate the drainage effect during cavern construction. [ABSTRACT FROM AUTHOR]

Egypt's economy is unstable, marked by high unemployment, low incomes, and safety concerns, which impede its rapid development. One crucial sector that faces difficulties is construction, dealing with issues like funding shortages, payment disputes, and ineffective project management. Conventional project success criteria strongly emphasize efficient resource use and waste minimization. These criteria are symbolized by the iron triangle of cost, time, and quality. A key instrument for obtaining value for money in building projects is value engineering (VE). Even though VE is acknowledged in theory, its application is still limited in most developing countries, including the Egyptian construction industry. Therefore, to bridge the gap between theory and practice, this paper attempts to investigate the current state and application of VE in Egypt. The study further outlines strategies for integrating VE into construction practices and identifies obstacles to their implementation. This study employed both qualitative and quantitative research approaches to attain the research aim, beginning with a thorough literature review to assess the application of value engineering (VE) in both local and international construction industries. Then, a web-based survey was conducted to gather diverse perspectives on VE's role and its current practice in Egyptian construction projects. The gathered data were analyzed mainly using descriptive and thematic analysis approaches. The paper's findings revealed that there is a large gap between VE in theory and practice in Egypt. Reasons include lack of awareness and understanding, time and financial constraints, and resistance to change. Bridging the gap to enhance VE in Egypt includes a focus on the role of educational institutions and training, public awareness and recognition, and early project lifecycle integration. This research has gained insights about VE environment, process, duration, types of projects applied, and effectiveness, aiming to get a comprehensive overview of VE in Egypt. Furthermore, this research has identified a significant gap between VE theory and practice in Egypt. To bridge this gap and enhance the implementation of VE in Egypt, strategies such as focusing on the role of educational institutions, increasing public awareness and recognition, and integrating VE approach early in the project lifecycle are suggested. These findings will guide construction industry practitioners to deeply understand the current state of VE in Egypt and practically integrate VE in the construction industry to minimize unnecessary costs, enhance functionality requirements, and achieve value for client's money. [ABSTRACT FROM AUTHOR]

Although the design‐bid‐build (DBB) system has poor stakeholder collaboration due to the separation between architects, engineers, and contractors in its linear process, resulting in longer schedules and cost overruns, DBB remains the most widely used project delivery system due to its benefits, such as higher competition and the owner's absolute control over the project. Researchers and practitioners expect building information modeling (BIM) implementation to improve stakeholder collaboration due to its potential to bridge the collaboration gap between these stakeholders, ensuring better coordination and motivating cost reduction. However, the fragmented nature of DBB still poses significant challenges to effective stakeholder collaboration, impacting BIM implementation negatively. Therefore, the objective of this study is to identify and rank critical risk factors (CRFs) related to stakeholder collaboration impacting BIM implementation in the context of high‐rise residential building projects delivered by DBB. By adopting a Delphi procedure, this study identified such CRFs by triangulating the knowledge from the literature and the experience of an expert panel recruited from the construction industry. Seven CRFs were selected and ranked through three rounds of a Delphi survey. Analysis revealed that the rankings remained unchanged despite the increasing degree of consensus among experts. The highest‐ranking negative CRFs were "Inappropriate mindset of BIM collaboration process," "Awareness of additional roles and responsibilities," and "Disconnection in the information flow and BIM process." A matrix of nine recommended solutions that can be applied across different CRFs was collected from the expert panel to improve the productivity of BIM collaboration under DBB. This study provides an in‐depth understanding of the CRFs of BIM‐based collaboration between stakeholders under a nonintegrated delivery system like DBB. The findings of this study can ensure successful project completion by creating awareness and allowing professionals and researchers to develop practical strategies for delivering BIM‐based DBB projects. [ABSTRACT FROM AUTHOR]

With the rapid development of China's construction industry and the acceleration of urbanization, large‐scale public building projects are becoming increasingly important in urban development, and the risk management problems of them should be pay more attention to. Based on the integration of back propagation (BP) neural network and building information model (BIM) technology, this paper carries out the research on risk management process of the whole life cycle of large public buildings and identifies the risk factors of large public buildings from the application dimension and the management dimension. The risk management evaluation index system is constructed and identified, and assessment, early warning, prevention, and control of risk management are applied and analyzed throughout the process. The international large public sports center project is used as a case study to establish a BIM model, while the BP neural network risk management model is used for prediction and calculation. The results of this study show that, first, the maximum deviation rate of the output indicators of the BP neural network risk model is 3.57% in the design period (B2) and the minimum deviation rate is 0.00% in the commissioning period (B4), which verifies the reliability of the training results of the model. Second, the best effect of risk management in the whole life cycle of the building is in the investment period (B1) and the highest risk is in the construction period (B3). Last, this paper constructs a new risk management framework to realise the risk management of the whole cycle of construction projects from design to operation, which helps to improve the management level and risk response ability of construction projects and ensure the smooth and sustainable development of the whole life cycle of construction. [ABSTRACT FROM AUTHOR]

Introduction: Nepal has witnessed several instances of slope instability associated with Hydroelectric Projects in the recent decades. Despite this, slope instability tends to receive less attention compared to other hazards. Objectives: The objective of this study is to investigate fourteen hydroelectric projects with the aim of identifying the types and causes of slope failures. Additionally, it seeks to offer a comprehensive understanding of slope stability conditions and challenges encountered during construction at project sites. Methods: To accomplish this, the study employs Key Informant Interviews with Questionnaires to delve into the slope stability concerns within Nepal's hydropower projects. The findings are then validated through an extensive review of pertinent literature. To conduct a thorough assessment of slope stability, the study relies on on-site observations, measurements, investigations, and both in-situ and laboratory tests. Results: It becomes evident that the careful selection of study sites, the application of geotechnical methods, and the establishment of regular monitoring are pivotal for ensuring favorable slope stability outcomes. Conclusion: A majority of respondents concur that cutslope is the primary factor causing slope instability with 44.4% answering affirmatively. An independent t-test reveals there is no significant difference between the variables. Moreover, the correlation which is closed to 1 suggests that perception of respondents are interconnected and tend to vary in a synchronized manner. Participants in the study widely acknowledge numerical modeling methods as a means to overcome the limitations of slope stability studies. [ABSTRACT FROM AUTHOR]

Bio-based carbon dioxide removal encompasses a range of (1) natural sink enhancement concepts in agriculture and on organic soils including peatlands, and in forestry, (2) bio-based building materials, and (3) bioenergy production with CO2 capture and storage (BECCS). A common database on these concepts is crucial for their consideration in strategies and implementation. In this study, we analyse standardised factsheets on these concepts. We find different dynamics of deployment until 2045: for CO2 removal rates from the atmosphere, natural sink enhancement concepts are characterised by gradually increasing rates, followed by a saturation and potentially a decrease after few decades; forest-related measures ramp up slowly and for construction projects and bioenergy plants, annually constant removal rates are assumed during operation which drop to zero afterwards. The expenses for removing 1 t CO2 from the atmosphere were found to be between 8 and 520 € t CO2−1, which arises from high divergence both in capital and operational expenditures among the concepts. This high variability of expenses seems to suggest the more cost-effective concepts should be implemented first. However, aspects from economics, resource base and environmental impacts to social and political implications for Germany need to be considered for developing implementation strategies. All concepts investigated could be deployed on scales to significantly contribute to the German climate neutrality target. [ABSTRACT FROM AUTHOR]

Purpose: The construction industry has been observed to be one of the most dangerous sectors in which to work; thus, it has struggled to attract new employees and suffered from skill shortages. Another characteristic is adopting a reactive approach to preventing accidents instead of a proactive approach that implements safety-leading indicators. In contributing to achieving a safer construction industry, this study investigated the barriers to achieving a proactive approach to safety in the construction industry. Method: The study adopted a quantitative approach. Data was collected by randomly administering a well-structured questionnaire to industry professionals in South Africa. One hundred and two questionnaires were collected and used as the basis for data analysis and interpretation by the study. Result: The analysis of the collected data identified nineteen significant barriers which were clustered into two based on an exploratory factor analysis. The top three ranked significant barriers are Lack of Top management's commitment to safety, Lack of leadership training and Prioritising productivity over employee safety. The two clusters formed from the nineteen barriers through factor analysis are top management approaches to safety and Safety culture through employee-centric training and accountability. Originality: Considering the accident data from South Africa, and the inherent benefits of implementing SLI to overcome this, this study provides critical insights for industry stakeholders and policymakers. It fills a gap that has not been filled in the developing country context before now. [ABSTRACT FROM AUTHOR]

It is crucial to address uncertainties in the construction project scheduling to mitigate delays. Probabilistic simulation offers a viable alternative method. This study examined the relationship between project duration and delay risks, as well as identified the most influential activities for modest housing projects using Monte Carlo Simulation. The simulation analysis, which included 2547 iterations, found that, on average, it took 87.39 days to complete a 54-type modest house project, with the shortest and longest durations being 44 and 149 days, respectively. The sensitivity analysis revealed that finishing works, such as painting, doors/windows installation, and cleaning, had the highest uncertainty and significantly affected the project duration. Additionally, the severity analysis showed that wall work was the most impactful activity contributing to delays. Based on these analyses, both finishing works and wall work were identified as the most critical activities significantly influencing the project's completion duration. [ABSTRACT FROM AUTHOR]

Selecting an appropriate Project Delivery Method (PDM) is a crucial decision for owners that significantly influences the success of a construction project. Various criteria, such as the nature of construction projects and the specific characteristics of owners and projects, should be properly considered to make this decision. This paper first assesses and evaluates the key criteria for selecting a PDM for building projects in Surabaya. It then proposes a multi-criteria decision-making model for the selection of three PDMs, namely Single General Contractor, Multiple Primes, and Design and Build. A three-step questionnaire survey was conducted to achieve the objectives. The initial analysis revealed six important selection criteria, which were then modelled and used in the subsequent survey. Using the Analytical Hierarchy Process (AHP) procedures, the second analysis determined the weights of each criterion for the three PDMs. The paper discusses these weights, suggesting the relative strengths of each PDM. Finally, the paper tests the robustness of the model using three building projects in Surabaya. [ABSTRACT FROM AUTHOR]

The joint construction of subways and other public buildings is a relatively newer type of construction. There is little research experience in the vibration characteristics and track damping design for this type of structure. In this study, a field test was adopted to conduct site measurement analysis on the vibration response of the joint construction project consisting of a subway tunnel and a building with typical frame structures. Numerical simulation methods were also adopted to, respectively, assume the use of ordinary tracks and steel-spring floating slab tracks for the subway for the situation where the Cologne-egg high-elastic fasteners were used on the track for damping purposes. Comparisons were performed to analyze the difference in the system vibration response between three different types of track. The results showed that the high-elastic fastener track and floating slab track both have a certain degree of damping effect compared with an ordinary track. Specifically speaking, the former has a damping advantage for frequency bands below 20 Hz, while the latter has the advantage for frequency bands above 20 Hz under the impact of the structural vibration characteristics for this joint construction. For this jointly construction structure, affected by the natural vibration characteristics of the structure, the natural frequency of the floating slab track is within 4 ∼ 10 Hz, and the similar vibration reduction effect can be achieved. This indicates that the structural vibration characteristic of the jointly constructed structure is an important factor determining the appropriate natural frequency of the floating slab track. [ABSTRACT FROM AUTHOR]

Simple Summary: Mystus macropterus, a commercially significant Mystus fish species found in the Yangtze River and Pearl River, is currently experiencing a rapid decline attributed to the construction of hydraulic engineering projects, water pollution, and overfishing. Consequently, extensive artificial breeding efforts are being undertaken for large-scale commercial aquaculture purposes as well as for reintroducing this fish back into its natural habitat. Our aim was the evaluation of the effect of different opening diets on the growth, the structure of the digestive tract, and digestive enzyme activity of larval and juvenile M. macropterus. It is recommended to include Tubifex in the diet of M. macropterus larvae during the standardized farming process. One of the crucial factors influencing the growth and viability of larvae and juveniles is their opening diets. The objective of this study was to identify suitable initial feed options for M. macropterus larvae and juveniles. A total of 1200 newly hatched M. macropterus with an average weight of 18.3 mg and an average length of 11.58 mm were selected and randomly divided into four groups. The fish were fed with different opening diets, including rotifer, Artemia nauplii, Tubifex, and micro-diet from six days after hatching (dahs), respectively. Growth indices and activities of digestive enzymes were assessed at 10, 15, 20, 25, 30, 35, and 40 dahs. Histological examination of the structure of the digestive tract was performed at 40 dahs, while survival rates were also documented. The results demonstrated that different diets had no effect on the survival rate of larvae and juveniles of M. macropterus. The growth performance indices were ranked as follows: Tubifex group > Artemia nauplii group > micro-diet group > rotifer group. Remarkably, the Tubifex group exhibited superior growth performance, which was also reflected in the structure of the digestive tract and digestive enzyme activity. Therefore, it is recommended to include Tubifex in the diet of M. macropterus larvae and juvenile during the standardized farming process. [ABSTRACT FROM AUTHOR]

In urban metro construction, shield tunneling often needs to pass through building and bridge pile foundations, potentially affecting the stability of existing structures. Therefore, accurately assessing the impact of shield tunneling on bridges and buildings is crucial. This study presents a comprehensive prediction method combining numerical simulation and empirical formulas, taking the underpass project of the Shijiazhuang–Wuhan High-Speed Railway Bridge by Zhengzhou Metro Line 5 as a case study. Three-dimensional numerical model calculations were performed using finite element software to analyze the displacement and stress changes of buildings and tunnel structures at different construction stages, revealing the deformation patterns of buildings adjacent to the tunnel during shield tunneling. In particular, the ground settlement caused by twin-tunnel excavation was compared with Peck's empirical formula to verify the reliability of the numerical simulation. The results show that twin-tunnel excavation exacerbates the horizontal displacement, uplift, and settlement of the ground, with maximum deformation rates increasing by 7.10%, 20%, and 11.4%, respectively. Comparing the ground deformation results of Peck's empirical formulas with numerical calculations revealed similar trends in the settlement curves, with a maximum deviation of 6.67%. It can be concluded that using Peck's empirical formula to calculate ground deformation characteristics complements the limitations of numerical simulations, making the assessment results more reliable. The findings of this study demonstrate that integrating numerical simulation with empirical formulas significantly enhances the reliability of deformation predictions in complex tunneling scenarios. This research not only offers a comprehensive safety assessment method for shield tunneling construction but also provides valuable guidance for the design and construction of similar projects, serving as a theoretical reference for future engineering endeavors. [ABSTRACT FROM AUTHOR]

The water sensitivity and structural characteristics of collapsible loess are two typical factors that significantly influence its mechanical behaviors. This paper presents a simple and practical elastic-plastic model based on the modified Cam-Clay model to well capture the essential behavior of unsaturated intact loess. The model employs deviator stress and spheric stress as the stress variables, with the water content serving as the moisture variable. The critical state surface of the model can be determined by utilizing the shear strength parameters of unsaturated soil under axisymmetric stress conditions. An initial yield surface equation is established by incorporating structural strength into the elliptical yield surface equation, which is used to determine the starting point for elastic-plastic deformation calculations under different humidity and stress combinations. The model comprises several parameters, each of which has a clear physical interpretation and can be conveniently obtained through conventional triaxial tests. The validity of the model for unsaturated intact loess is confirmed through a comparison with the stress–strain relationship of unsaturated intact loess in the axisymmetric stress state. This work has the potential to significantly enhance our ability to predict and mitigate potential geotechnical disasters, such as foundation deformation under axisymmetric conditions and slope stability problems under non-axisymmetric conditions. Ultimately, the application of this model could contribute to the safety and stability of infrastructure and construction projects in loess regions. [ABSTRACT FROM AUTHOR]

Applying deep learning algorithms in the construction industry holds tremendous potential for enhancing site management, safety, and efficiency. The development of such algorithms necessitates a comprehensive and diverse image dataset. This study introduces the Aerial Image Dataset for Construction (AIDCON), a novel aerial image collection containing 9563 construction machines across nine categories annotated at the pixel level, carrying critical value for researchers and professionals seeking to develop and refine object detection and segmentation algorithms across various construction projects. The study highlights the benefits of utilizing UAV-captured images by evaluating the performance of five cutting-edge deep learning algorithms—Mask R-CNN, Cascade Mask R-CNN, Mask Scoring R-CNN, Hybrid Task Cascade, and Pointrend—on the AIDCON dataset. It underscores the significance of clustering strategies for generating reliable and robust outcomes. The AIDCON dataset's unique aerial perspective aids in reducing occlusions and provides comprehensive site overviews, facilitating better object positioning and segmentation. The findings presented in this paper have far-reaching implications for the construction industry, as they enhance construction site efficiency while setting the stage for future advancements in construction site monitoring and management utilizing remote sensing technologies. [ABSTRACT FROM AUTHOR]

The construction industry has witnessed unprecedented disruptions in the supply chain (SC) over the past four years due to the consecutive impacts of the 2018 steel and aluminum tariffs, the COVID-19 pandemic, and the Russian–Ukrainian war. SC disruptions have been linked to price escalations, the management of which varies across different construction contracts. Thus, there is a timely need to understand the contractual implications of price escalation clauses. This article fulfills this research requirement by following an interdependent research methodology. First, the authors analyzed and compared price escalation provisions under various US-based, international, and UK-based standard design–bid–build contracts. Second, the authors examined legal cases that have arisen due to disputes over price escalation-related matters. Third, based on the contractual and legal analysis, the authors formulated and proposed a set of contractual considerations that can be used to plan and manage the contractual implications arising from triggering price escalation clauses. The findings indicate substantial variability in contractual provisions addressing price escalation. A predominant approach entails specifying a fixed contract price, often with a general exception permitting adjustments related to legislative changes. Certain standard contracts afford flexibility through the incorporation of supplementary clauses or amendments during the contract formation stage to counteract escalation risks. Further, insights from the legal review show that judicial relief from contractual obligations is typically granted solely in instances of unforeseen and severe economic conditions. This research makes a significant academic contribution by advancing the understanding of contractual obligations concerning price escalation, especially in the context of ongoing market disruptions. Ultimately, the findings of this study will impact the construction industry by promoting more balanced contractual practices regarding price escalations in construction projects. [ABSTRACT FROM AUTHOR]

Task conflict is prevalent among construction project parties, however, how task conflict affects construction project performance still lacks a comprehensive investigation. Against this background, this study adopts an uncertainty management perspective to conduct an integrative model including both positive and negative mediators as well as one moderator to investigate the link between task conflict and construction project performance. Using 206 samples from the Chinese construction industry, the proposed hypotheses are empirically examined. Results suggest that project commitment (effect size = -0.046) negatively mediates the link between task conflict and project performance, whereas knowledge integration (effect size = 0.053) has a positive mediating effect. What's more, task reflexivity is found to mitigate the negative effects of task conflict on both project commitment (coefficient of interaction item = 0.12) and knowledge integration (coefficient of interaction item = 0.08). It is also found that task reflexivity changes the direction and strength of the link from task conflict to project performance by both project commitment (from -0.155 to 0.069) and knowledge integration (from -0.049 to 0.052). These findings provide a holistic understanding of the relationship between task conflict and construction project performance, thus contributing to construction project management theoretically and practically. [ABSTRACT FROM AUTHOR]

Due to the complex nature of mega construction projects (MCPs), technological innovation risks have signifi- cantly increased. Cooperation is widely accepted as a proactive approach to resolving these risks. An in-depth study of technological innovation cooperative behavior (TICB) helps understand the underlying reasons, but studies need to pay more attention to it. This study explored the factors affecting TICB for MCPs and developed a conceptual model based on the Theory of planned behavior (TPB). It established a structural equation model to verify the relationship between influencing factors. An example verified the feasibility of the model. The results show that cooperative attitude, subjective cooperative norm, perceived cooperative behavior control, and cooperative scenarios positively affect cooperative behavior through cooperative intention. Cooperative attitude plays a mediating role between cooperative scenarios and cooperative intention. Perceived cooperative behavior control has no direct effect on cooperative behavior. This study provides a theoretical reference to guide future empirical studies and enriches the knowledge of TICB for MCPs. [ABSTRACT FROM AUTHOR]

The paper presents the model resilience measurement based on the complex network theory and analyzes the resilience of project portfolio network considering risk propagation. The model can be used to evaluate the resilience and improve its success probability of projects in the portfolio network. Firstly, the research analyzes the dynamic changes of the portfolio network derived from the construction of the project portfolio matrix, as well as the main factors to be taken into consideration in measuring the resilience of the project portfolio. Further, the research measures the resilience of the project portfolio network according to the node attributes (project) and the relationship attributes (the relationship that one project will impact another in the portfolio network) respectively. Then, to integrate the resilience of the projects and influence relationship between projects, the research proposes the dynamic PageRank algorithm to analyze the resilience of the project portfolio based on the analysis of traditional PageRank algorithm. In addition, resilience is not only affected by the projects and its influence relationship between them, but is also affected by risk propagation. Therefore, the research presents a model for analyzing the portfolio network resilience considering multiple risk propagation. Finally, a research and development project portfolio are taken as an example to demonstrate the effectiveness of the method presented in this research. Our approach can be used by managers to identify the scores of project resilience capacity in portfolio network. Our method explicitly allows to uncover the most resilient projects considering the resilience of project (node) and their influence relationship (network structure), and the risk propagation. Utilizing the outcomes of this research can enhance the capacity of the whole project portfolio to manage risks and improve the success probability of the whole project portfolio by enhancing network resilience. [ABSTRACT FROM AUTHOR]

In order to meet the monitoring needs of the roadbed in the station renovation project, grasp the changes in roadbed settlement during the construction of the station renovation project, relying on a certain station renovation construction project and combining with the characteristics of the station renovation project, the traditional manual monitoring and four commonly used automated monitoring methods were compared. It was found that the static level automation monitoring technology had a lower cost and could overcome the limitations of station renovation construction while taking into account the preferences of equipment management units. By analyzing the principle of static level automation monitoring technology, a static level automation monitoring system based on the station renovation project was built, and multiple static level gauges were connected in series to form a connected pipe, which collected the liquid level height in real time and transmitted it to the static level automation monitoring cloud platform. Research has shown that the system can obtain real-time settlement changes of station renovation construction line foundations according to monitoring frequency requirements. After a rainy season, the maximum cumulative settlement change is 2.43 mm, which does not exceed the warning value ± 6 mm, indicating that the station renovation project did not have a significant impact on the roadbed. [ABSTRACT FROM AUTHOR]

This paper analyzed the technical principle and advantages of GB-SAR, and combined engineering practices to study the site selection, data acquisition scheme and data processing of GB-SAR station, and made a complete emergency monitoring scheme. Taking the construction blasting scene of an engineering construction as an example, the blasting point was located in the central position where the whole reinforced slope needs to be monitored. The emergency monitoring was carried out by using GB-SAR and the deformation information was obtained by using time-series data processing method, which verified the feasibility of the proposed emergency monitoring scheme and the reliability of data processing. The results show that, the blasting has little influence on the well-supported structure, and the shape variable is less than 1. 5 mm. After the explosion, the position shape variable near the center increases sharply, and the maximum value can reach 103 mm during the monitoring period. It is further confirmed that the GB-SAR can effectively monitor the impact of blasting on the surrounding construction scene, and can provide strong support for construction operations and project risk investigation. [ABSTRACT FROM AUTHOR]