Search results

The induction of geological disasters is predominantly influenced by the dynamic evolution of the stress and plastic zones of the multilayer rock formations surrounding deep-rock roadways, and the behaviours and mechanisms of high in situ stress are key scientific issues related to deep-resource exploitation. The stress environment of deep resources is more complex owing to the influence of several geological factors, such as tectonic movements and landforms. Therefore, in practical engineering, the in situ stress field is in a complex anisotropic three-dimensional state, which may change the deformation and failure law of the surrounding rock. The purpose of this study is to investigate the tunnelling-induced stress and plastic evolution causing instability of multilayered surrounding rock by varying three-dimensional in situ stresses.

Based on data from the Yangquan Coal Mine, China, a finite difference model was established, and the elastic-plastic constitutive model and element deletion technology designed in the study were analysed. Gradual tunnelling along the roof and floor of the coal seam was used in the model, which predicted the impact tendency, and compared the results with the impact tendency report to verify the validity of the model. The evolutions of the stress field and plastic zone of the coal roadway in different stress fields were studied by modifying the maximum horizontal in situ stress, minimum horizontal in situ stress and lateral pressure coefficient.

The results shown that the in situ stress influenced the stress distribution and plastic zone of the surrounding rock. With an increase in the minimum horizontal in situ stress, the vertical in situ stress release area of the roof surrounding rock slowly decreased; the area of vertical in situ stress concentration area of the deep surrounding rock on roadway sides decreased, increased and decreased by turn; the area of roof now-shear failure area first increased and then decreased. With an increase in the lateral pressure coefficient, the area of the horizontal in situ stress release area of the surrounding rock increased; the area of vertical in situ stress release area of the roof and floor surrounding rock first decreased and then increased; the area of deep stress concentration area of roadway sides decreased; and the plastic area of the surrounding rock and the area of now-shear failure first decreased and then increased.

The results obtained in this study are based on actual cases and reveal the evolution law of the disturbing stress and plastic zone of multilayer surrounding rock caused by three-dimensional in situ stress during the excavation of deep rock roadways, which can provide a practical reference for the extraction of deep resources.

Project scheduling plays an essential role in the implementation of a project due to the limitation of resources in practical projects. However, the existing research tend to focus on finding suitable algorithms to solve various scheduling problems and fail to find the potential scheduling rules in these optimal or near-optimal solutions, that is, the possible intrinsic relationships between attributes related to the scheduling of activity sequences. Data mining (DM) is used to analyze and interpret data to obtain valuable information stored in large-scale data. The goal of this paper is to use DM to discover scheduling concepts and obtain a set of rules that approximate effective solutions to resource-constrained project scheduling problems. These rules do not require any search and simulation, which have extremely low time complexity and support real-time decision-making to improve planning/scheduling.

The resource-constrained project scheduling problem can be described as scheduling a group of interrelated activities to optimize the project completion time and other objectives while satisfying the activity priority relationship and resource constraints. This paper proposes a new approach to solve the resource-constrained project scheduling problem by combining DM technology and the genetic algorithm (GA). More specifically, the GA is used to generate various optimal project scheduling schemes, after that C4.5 decision tree (DT) is adopted to obtain valuable knowledge from these schemes for further predicting and solving new scheduling problems.

In this study, the authors use GA and DM technology to analyze and extract knowledge from a large number of scheduling schemes, and determine the scheduling rule set to minimize the completion time. In order to verify the application effect of the proposed DT classification model, the J30, J60 and J120 datasets in PSPLIB are used to test the validity of the scheduling rules. The results show that DT can readily duplicate the excellent performance of GA for scheduling problems of different scales. In addition, the DT prediction model developed in this study is applied to a high-rise residential project consisting of 117 activities. The results show that compared with the completion time obtained by GA, the DT model can realize rapid adjustment of project scheduling problem to deal with the dynamic environment interference. In a word, the data-based approach is feasible, practical and effective. It not only captures the knowledge contained in the known optimal scheduling schemes, but also helps to provide a flexible scheduling decision-making approach for project implementation.

This paper proposes a novel knowledge-based project scheduling approach. In previous studies, intelligent optimization algorithm is often used to solve the project scheduling problem. However, although these intelligent optimization algorithms can generate a set of effective solutions for problem instances, they are unable to explain the process of decision-making, nor can they identify the characteristics of good scheduling decisions generated by the optimization process. Moreover, their calculation is slow and complex, which is not suitable for planning and scheduling complex projects. In this study, the set of effective solutions of problem instances is taken as the training dataset of DM algorithm, and the extracted scheduling rules can provide the prediction and solution of new scheduling problems. The proposed method focuses on identifying the key parameters of a specific dynamic scheduling environment, which can not only reproduces the scheduling performance of the original algorithm well, but also has the ability to make decisions quickly under the dynamic interference construction scenario. It is helpful for project managers to implement quick decisions in response to construction emergencies, which is of great practical significance for improving the flexibility and efficiency of construction projects.

This study aims to investigate the literature related to the use of digital technologies for promoting circular economy (CE) in the construction industry.

A comprehensive approach was adopted, involving bibliometric analysis, text-mining analysis and content analysis to meet three objectives (1) to unveil the evolutionary progress of the field, (2) to identify the key research themes in the field and (3) to identify challenges hindering the implementation of digital technologies for CE.

A total of 365 publications was analysed. The results revealed eight key digital technologies categorised into two main clusters including “digitalisation and advanced technologies” and “sustainable construction technologies”. The former involved technologies, namely machine learning, artificial intelligence, deep learning, big data analytics and object detection and computer vision that were used for (1) forecasting construction and demolition (C&D) waste generation, (2) waste identification and classification and (3) computer vision for waste management. The latter included technologies such as Internet of Things (IoT), blockchain and building information modelling (BIM) that help optimise resource use, enhance transparency and sustainability practices in the industry. Overall, these technologies show great potential for improving waste management and enabling CE in construction.

This research employs a holistic approach to provide a status-quo understanding of the digital technologies that can be utilised to support the implementation of CE in construction. Further, this study underlines the key challenges associated with adopting digital technologies, whilst also offering opportunities for future improvement of the field.

Sustainability and competitiveness have received extensive attentions. Despite a large number of studies on sustainability and competitiveness in the construction industry, little research has been conducted to holistically explore the interactions between these two concepts. From a dynamic transition perspective, the purpose of this paper is to link sustainability and competitiveness of construction firms by developing a Sustainability-Competitiveness Dynamic Interaction Framework (SCDIF).

Conceptual theory-building approach was adopted to develop the conceptual framework. It is an iterative analysis and synthesis process, which involves reading literature, identifying commonalities and differences, synthesizing, proposing an initial framework, collecting additional literature, and revisiting and revising the framework.

There are complex interactions between sustainability and competitiveness of construction firms. This leads to uncertain relationships between sustainability and competitiveness, which is context dependent. Under evolving economic and socio-political environments, sustainability and competitiveness of construction firms could transition from mutually exclusive to mutually supportive, and finally merge into “sustainable competitiveness.”

A SCDIF proposed in this study demonstrates that the interactions between sustainability and competitiveness evolves according to the evolving economic and socio-political environments and firms’ strategies, and thus the relationships and interactions between sustainability and competitiveness are context dependent. This framework helps corporate managers to understand how corporate sustainability and competitiveness interact with each other, thereby informing their decision-making of sustainability strategy. Similarly, the framework provides useful references for policymakers to understand the mechanisms of transitioning industries toward sustainable competitiveness.

The proposed framework offers a new perspective for understanding sustainability and competitiveness. From the dynamic transition perspective, this study effectively illustrates that the interactions between sustainability and competitiveness evolves according to the evolving economic and socio-political environments and firms’ strategies. Compared to existing approaches, the dynamic and holistic approach proposed in this paper provides the capacity to capture the complexity of sustainability and competitiveness.

Prefabricated construction (PC) will play a vital role in the transformation and upgrading of the construction industry in the future. However, high capital cost is currently one of the biggest obstacles to the application and promotion of PC in China. Clarifying the factors that affect the PC cost from the perspectives of stakeholders and exploring key cost control paths help to achieve effective cost management, but few studies have paid enough attention to this. Therefore, this research aims to explore the critical cost influencing factors (CIFs) and critical stakeholders of PC based on stakeholder theories and propose corresponding strategies for different stakeholders to reduce the cost of PC.

Based on the stakeholder theory and social network theory, literature review and two rounds of expert interviews were used to obtain the stakeholder-associated CIFs and their mutual effects, then the consistency of the data was tested. After that, social network analysis was applied to identify the critical CIFs, critical interaction and key stakeholders in PC cost control and mine the influence conduction paths between CIFs.

The results reveal that the cognition and attitude of developer and relevant standards and codes are the most critical CIFs while the government, developer and contractor are crucial to the cost control of PC. The findings further suggest that measures should be taken to reduce the transaction costs of the developer, and the contractor ought to efficiently apply information technology. Moreover, the collaborative work between designer and manufacturer can avoid unnecessary cost consumption.

This research combines stakeholder management and cost management in PC for the first time and explores the effective cost control paths. The research results can contribute to clarifying the key points of cost management for different stakeholders and improving the cost performance of PC projects.