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Prefabricated technology is gradually being applied to the construction of subway stations due to its characteristic of mechanization. However, the prefabricated subway station in China is in the initial stage of development, which is prone to construction safety issues. This study aims to evaluate the construction safety risks of prefabricated subway stations in China and formulate corresponding countermeasures to ensure construction safety.

A construction safety risk evaluation index system for the prefabricated subway station was established through literature research and the Delphi method. Furthermore, based on the structure entropy weight method, matter-element theory and evidence theory, a hybrid evaluation model is developed to evaluate the construction safety risks of prefabricated subway stations. The basic probability assignment (BPA) function is obtained using the matter-element theory, the index weight is calculated using the structure entropy weight method to modify the BPA function and the risk evaluation level is determined using the evidence theory. Finally, the reliability and applicability of the evaluation model are verified with a case study of a prefabricated subway station project in China.

The results indicate that the level of construction safety risks in the prefabricated subway station project is relatively low. Man risk, machine risk and method risk are the key factors affecting the overall risk of the project. The evaluation results of the first-level indexes are discussed, and targeted countermeasures are proposed. Therefore, management personnel can deeply understand the construction safety risks of prefabricated subway stations.

This research fills the research gap in the field of construction safety risk assessment of prefabricated subway stations. The methods for construction safety risk assessment are summarized to establish a reliable hybrid evaluation model, laying the foundation for future research. Moreover, the construction safety risk evaluation index system for prefabricated subway stations is proposed, which can be adopted to guide construction safety management.

The purpose of this paper is to present the influence of inter-turn short circuit faults (ITSF) on electromagnetic vibration in high-voltage line-starting permanent magnet synchronous motor (HVLSPMSMS).

In this paper, the ampere–conductor wave model of HVLSPMSM after ITSF is established. Second, a mathematical model of the magnetic field after ITSF is established, and the influence law of the ITSF on the air-gap magnetic field is analyzed. Further, the mathematical expression of the electromagnetic force density is established based on the Maxwell tensor method. The impact of HVLSPMSM torque ripple frequency, radial electromagnetic force spatial–temporal distribution and rotor unbalanced magnetic tension force by ITSF is revealed. Finally, the electromagnetic–mechanical coupling model of HVLSPMSM is established, and the vibration spectra of the motor with different degrees of ITSF are solved by numerical calculation.

In this study, it is found that the 2np order flux density harmonics and (2 N + 1) p order electromagnetic forces are not generated when ITSF occurs in HVLSPMSM.

By analyzing the multi-harmonics of HVLSPMSM after ITSF, this paper provides a reliable method for troubleshooting from the perspective of vibration and torque fluctuation and rotor unbalanced electromagnetic force.

The current and modern electrical distribution networks, named smart grids (SGs), use advanced technologies to accomplish all the technical and nontechnical challenges naturally demanded by energy applications. Energy metering collecting is one of these challenges ranging from the most basic (i.e., visual assessment) to the expensive advanced metering infrastructure (AMI) using intelligent meters networks. The AMIs’ data acquisition and system monitoring environment require enhancing some routine tasks. This paper aims to propose a methodology that uses a distributed and sustainable approach to manage wide-range metering networks, focused on using current public or private telecommunication infrastructure, optimizing the implementation and operation, increasing reliability and decreasing costs.

Inspired by blockchain technology, a collaborative metering system architecture is conceived, managing massive data sets collected from the grid. The use of cryptography handles data integrity and security issues.

A robust proof-of-concept simulation results are presented concerning the resilience and performance of the proposed distributed remote metering system.

The methodology proposed in this work is an innovative AMI solution related to SGs. Regardless of the implementation, operation and maintenance of AMIs, the proposed solution is unique, using legacy and new technologies together in a reliable way.

This study collected the bibliographic data of 2034 journal articles published in 2000–2021 from Web of Science (WoS) core collection database and adopted two bibliometric analysis methods, namely historiography and keyword co-occurrence, to identify the evolution trend of construction risk management (CRM) research topics.

CRM has been a key issue in construction management research, producing a big number of publications. This study aims to undertake a review of the global CRM research published from 2000 to 2021 and identify the evolution of the research topics relating to CRM.

This study found that risk analysis methods have shifted from simply ranking risks in terms of their relative importance or significance toward examining the interrelationships among risks, and that the objects of CRM research have shifted from generic construction projects toward specified types of construction projects (e.g. small projects, underground construction projects, green buildings and prefabricated projects). In addition, researchers tend to pay more attention to an individual risk category (e.g. political risk, safety risk and social risk) and integrate CRM into cost, time, quality, safety and environment management functions with the increasing adoption of various information and communication technologies.

This study focused on the journal articles in English in WoS core collection database only, thus excluding the publications in other languages, not indexed by WoS and conference proceedings. In addition, the historiography focused on the top documents in terms of document strength and thus ignored the role of the documents whose strengths were a little lower than the threshold.

This review study is more inclusive than any prior reviews on CRM and overcomes the drawbacks of mere reliance on either bibliometric analysis results or subjective opinions. Revealing the evolution process of the CRM knowledge domain, this study provides an in-depth understanding of the CRM research and benefits industry practitioners and researchers.

The construction industry is widely recognized as one of the most hazardous sectors in the world. Despite extensive research on safety management, a critical issue remains that insufficient attention is devoted to safety practices in rural areas. Notably, accidents frequently occur during the construction of rural self-built houses (RSH) in China. Safety management tends to be overlooked due to the perceived simplicity of the construction process. Furthermore, it is essential to acknowledge that China currently lacks comprehensive laws and regulations governing safety management in RSH construction. This paper aims to analyze the behavior of key stakeholders (including households, workmen, rural village committee and the government) and propose recommendations to mitigate safety risks associated with RSH construction.

This paper applies evolutionary game theory to analyze the symbiotic evolution among households, workmen and rural village committee, in situations with or without government participation. Additionally, numerical simulation is utilized to examine the outcomes of various strategies implemented by the government.

Without government participation, households, workmen, and rural village committee tend to prioritize maximizing apparent benefits, often overlooking the potential safety risks. Numerical simulations reveal that while government involvement can guide these parties towards safer decisions, achieving the desired outcomes necessitates the adoption of reasonable and effective strategies. Thus, the government needs to offer targeted subsidies to these stakeholders.

Considering that during the construction phase, stakeholders are the main administrators accountable for safety management. However, there exists insufficient research examining the impact of stakeholder behavior on RSH construction safety. This study aims to analyze the behavior of stakeholders about how to reduce the safety risks in building RSH. Thus, the authors intend to contribute to knowledge in this area by establishing evolutionary game model. Firstly, this study carried out a theoretical by using tripartite evolutionary game to reveal the reasons for the high safety risk during building RSH. Practically, this research points out the important role of households, workmen and rural village committee in improving safety management in rural areas. Besides, some suggestions are proposed to the government about how to reduce construction safety risks in rural areas.

The global resolution of embracing dynamic and intertwined production systems has made it necessary to adopt viable systems like circular economy (CE) to ensure excellency in the business. However, in emerging countries, it is challenging to implement the CE practices due to the existing problems in the supply chain network, as well as due to the vulnerable financial condition of the business after the deadly hit of COVID-19. The main aim of this research is to determine the barriers to implementing CE considering the recent pandemic and suggest strategies to organizations to ensure CE for a cleaner environment and greener economy.

After an extensive literature review and validation from experts, 24 sub-barriers under the class of 6 main barriers are finalized by Pareto analysis, which is further analyzed via the best-worst method to determine the weight and rank of the barriers Further, fuzzy-Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is used to rank the proposed startegies to overcome the analysed barriers.

The results identified “unavailability of initial funding capital”, “need long time investment”, “lack of integrating production system using advance technology” and “lack of strategic planning” as the most acute sub-barriers to CE implementation. Further, fuzzy TOPSIS method is used to suggest the best strategy to mitigate the ranked barriers. The results indicated “integrated design facility to CE”, “ensuring large scale funding for CE facility” as the best strategy.

This study will motivate managers to implement CE practices to enjoy proper utilization of the resources, sustainable benefits in business, and gain competitive advantage.

Periodically, a lot of work is done on CE practices but none of them highlighted the issues in the domain of the leather products industry (LPI) and COVID-19 toward achieving sustainability in production and consumption. Thus, some significant barriers and strategies to implement CE for achieving sustainability in LPI are highlighted in this study, which is a unique contribution to the literature.

This study focused on exploring the performance factors (PFs) that impact Infrastructure Sanitation Projects (ISSPs) in the construction sector. The aim was twofold: firstly, to identify these crucial PFs and secondly, to develop a robust performance model capable of effectively measuring and assessing the intricate interdependencies and correlations within ISSPs. By achieving these objectives, the study aimed to provide valuable insights into and tools for enhancing the efficiency and effectiveness of sanitation projects in the construction industry.

To achieve the study's aim, the methodology for identifying the PFs for ISSPs involved several steps: extensive literature review, interviews with Egyptian industry experts, a questionnaire survey targeting industry practitioners and an analysis using the Relative Importance Index (RII), Pareto principle and analytic network process (ANP). The RII ranked factor importance,  and Pareto identified the top 20% for ANP, which determined connections and interdependencies among these factors.

The literature review identified 36 PFs, and an additional 13 were uncovered during interviews. The highest-ranked PF is PF5, while PF19 is the lowest-ranked. Pareto principle selected 11 PFs, representing the top 20% of factors. The ANP model produced an application for measuring ISSP effectiveness, validated through two case studies. Application results were 92.25% and 91.48%, compared to actual results of 95.77% and 97.37%, indicating its effectiveness and accuracy, respectively.

This study addresses a significant knowledge gap by identifying the critical PFs that influence ISSPs within the construction industry. Subsequently, it constructs a novel performance model, resulting in the development of a practical computer application aimed at measuring and evaluating the performance of these projects.

Sources highlight that lack of systematic labour training components results in low performance and productivity of labour, which leads the construction industry of many countries to face various challenges. This study aims to quantify the variations in the performance and productivity levels of labour in building construction projects through the applications of effective work-based training components.

A comprehensive literature review and a series of experts’ discussions with action-oriented communication approaches were conducted to develop a set of practices related to labour training, performance assessment and productivity measurements within a framework. The developed practices were applied to around 100 labourers working on nine building construction projects through a construction supervisory training programme.

The study presents the detailed patterns of the significant changes in labour performance and productivity levels. The majority of trained labourers have grown to perform the work process with some relevant theoretical and operational knowledge and skills. The overall results spotlight the significant behavioural changes that can be observed in workforce operations by improving labour performance, which resulted in implementing effective labour-rewarding practices within a framework.

Although the study findings were limited to the Sri Lankan context, the proposed practices can be applied to the industry practices of the construction sector of other developing countries and the other developing industries in similar ways/scenarios.

The study outcomes contribute to uplifting the work qualities of labourers with life-long learning opportunities and unlocking the potential barriers for expanding the local labour supply while controlling the excessive inclination of the local firms towards foreign labour. This paper describes further implications and future scopes of the study elaborately.

The study provides generalised mechanisms and practices that transform the labour characteristics and add new attributes for strengthening the values of construction supervision practices to obtain well-improved work outputs. The study outcomes reinforce the chain relationships among the training elements, labour performance and productivity levels, leading to upgrading current planning and operational management practices, especially adding constructive mechanisms in resource levelling and productivity benchmarking practices.

This paper aims to study a neural network-based fault-tolerant controller to improve the tracking control performance of an unmanned autonomous helicopter with system uncertainty, external disturbances and sensor faults, using the prescribed performance method.

To ensure that the tracking error satisfies the prescribed performance, the authors adopt an error transformation function method. A control scheme based on the neural network and high-order disturbance observer is designed to guarantee the boundedness of the closed-loop system. A simulation is performed to prove the validity of the control scheme.

The developed adaptive fault-tolerant control method makes the system with sensor fault realize tracking control. The error transformation function method can effectively handle the prescribed performance requirements. Sensor fault can be regarded as a type of system uncertainty. The uncertainty can be approximated accurately using neural networks. A high-order disturbance observer can effectively suppress compound disturbances.

The tracking performance requirements of unmanned autonomous helicopter system are considered in the design of sensor fault-tolerant control. The inequality constraint that the output tracking error must satisfy is transformed into an unconstrained problem by introducing an error transformation function. The fault state of the velocity sensor is considered as the system uncertainty, and a neural network is used to approach the total uncertainty. Neural network estimation errors and external disturbances are treated as compound disturbances, and a high-order disturbance observer is constructed to compensate for them.

The purpose of this paper is to construct an event-triggered finite-time fault-tolerant formation tracking controller, which can achieve a time-varying formation control for multiple unmanned aerial vehicles (UAVs) during actuator failures and external perturbations.

First, this study developed the formation tracking protocol for each follower using UAV formation members, defining the tracking inaccuracy of the UAV followers’ location. Subsequently, this study designed the multilayer event-triggered controller based on the backstepping method framework within finite time. Then, considering the actuator failures, and added self-adaptive thought for fault-tolerant control within finite time, the event-triggered closed-loop system is subsequently shown to be a finite-time stable system. Furthermore, the Zeno behavior is analyzed to prevent infinite triggering instances within a finite time. Finally, simulations are conducted with external disturbances and actuator failure conditions to demonstrate formation tracking controller performance.

It achieves improved performance in the presence of external disturbances and system failures. Combining limited-time adaptive control and event triggering improves system stability, increase robustness to disturbances and calculation efficiency. In addition, the designed formation tracking controller can effectively control the time-varying formation of the leader and followers to complete the task, and by adding a fixed-time observer, it can effectively compensate for external disturbances and improve formation control accuracy.

A formation-following controller is designed, which can handle both external disturbances and internal actuator failures during formation flight, and the proposed method can be applied to a variety of formation control scenarios and does not rely on a specific type of UAV or communication network.