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This study investigates the impact and role of digital twin technology in building automation (DTBA) from a sustainability viewpoint. It aims to enhance the understanding of how DTBA can boost efficiency, optimize quality and support sustainable practices in contemporary construction. By exploring the integration of DTBA with sustainable practices, the study seeks to demonstrate how DT can revolutionize building management and operations, leading to significant improvements in resource efficiency, environmental impact and overall operational excellence.

This research employs a bibliographic analysis and systematic review of 176 publications from the past five years (January 1, 2019 to December 31, 2023), focusing on the application and development of DTBA. The study methodically analyzes current trends, identifies research gaps and suggests future directions by synthesizing data from various studies, offering a comprehensive overview of the current state of DTBA research. The approach combines quantitative and qualitative analyses to provide robust insights into the advancements and challenges in the field.

The review identifies key development areas in DTBA, such as energy and environmental management, resource utilization within a circular economy and technology integration and interoperability. It highlights the necessity for further research to maximize DTBA’s potential in sustainable building automation. The findings suggest that while significant progress has been made, there is a critical need for innovations in data interoperability, predictive analytics and the integration of renewable energy sources to fully realize the benefits of DTBA in enhancing building sustainability.

This paper provides a thorough review of DTBA from a sustainability perspective, offering valuable insights into its current applications and future development potential. It serves as a crucial resource for researchers and practitioners looking to advance sustainable practices in the construction sector using DT technology. By bridging the gap between theoretical research and practical applications, the paper underscores the transformative potential of DTBA in driving sustainable development and provides a roadmap for future research and innovation in the field.

The purpose of this paper is to conduct a comprehensive study on building, fire and evacuation, so as to effectively improve the efficiency of building fire evacuation and the management level of fire evacuation site. Make up for the difficulties of BIM technology in effectively connecting building information and fire data.

First, this paper establishes a fire model and an evacuation model based on BIM information. Then, the safety index (SI) is introduced as a comprehensive index, and the IRI is established by integrating the SI function to evaluate the safety of evacuation routes. Based on these two indices, the IRI-based fire evacuation model is established.

This study offers an Improved Risk Index (IRI)-based fire evacuation model, which may achieve effective evacuation in fire scenes. And the model is verified by taking the fire evacuation of a shopping center building as an example.

This paper proposes a fire evacuation principle based on IRI, so that the relevant personnel can comprehensively consider the fire factors and evacuation factors to achieve the optimization of building design, thereby improving the fire safety of buildings.

This study introduces a novel approach to preventing construction quality problems by examining the complex interrelations among such issues. Recognizing the overlooked coupling between problems is essential, as it can exacerbate quality issues, triggering chain reactions that compromise project success. The research justifies its focus on these interrelations by highlighting the insufficiency of traditional quality management methods, which often fail to account for interconnected quality problems in the architecture, engineering and construction (AEC) industry.

At the core of this research is the establishment of a knowledge base for construction quality issues, marking a pioneering effort to systematically organize unstructured textual data on construction quality problems and their interconnections. This base serves as a platform for the subsequent application of advanced analytical techniques. Specifically, the study leverages preprocessing, text similarity algorithms and association rule mining to dissect and illuminate the nuanced coupling relationships among construction quality issues, a facet not thoroughly explored in prior research.

The innovative analytical methodology employed here reveals significant insights into the dynamics of construction quality issue coupling. These insights not only deepen the understanding of these complex interactions but also guide the development of targeted intervention strategies. The practical applicability and effectiveness of the proposed approach are demonstrated using selected textual materials as experimental evidence. The findings show that understanding and addressing these couplings can significantly mitigate potential chain reactions of defects, thus enhancing overall project quality.

The originality of this study lies in its threefold contribution: the creation of a dedicated knowledge base for construction quality issues, the application of novel analytical methodologies to decipher coupling relationships and the extension of text analysis techniques to the realm of construction quality problem prevention. Together, these innovations open new avenues for research and practice in construction management, offering a robust framework for the systematic identification and mitigation of quality issues in construction projects.

This paper introduces a novel method to improve building safety management by leveraging building information modeling (BIM) and adaptive information retrieval techniques. The integration aims to overcome the limitations of traditional safety management methods in connecting construction processes with risk management efficiently.

The proposed method involves developing industry foundation classes (IFC) ontologies and integrating them with a safety document ontology to form a comprehensive BIM-based safety context framework. Custom reasoning rules and an inference engine are constructed to enable automatic context-aware safety information retrieval. The methodology is demonstrated through an adaptive information retrieval system using job hazard analysis (JHA) documents.

The implementation of the BIM-based adaptive information retrieval system shows significant improvements in identifying and managing construction risks. By mapping job-specific risks to corresponding safety measures, the system enhances risk detection and management tailored to particular construction tasks. The results indicate a marked improvement in the precision and accuracy of safety assessments and recommendations, aligning them closely with planned construction activities and conditions.

This paper offers an innovative approach to construction safety management through the development of a BIM-facilitated context-aware information retrieval system. This approach provides a more intelligent and automated framework for identifying and managing risks in construction projects. By focusing on specific job steps and related risks, the system enhances the effectiveness and accuracy of safety measures, contributing to better overall building safety management.

This paper provides a thorough examination of the advancements and impacts of artificial intelligence (AI) on construction management (CM) over the past five years, particularly focusing on its role in mitigating prevalent challenges such as inefficiency and ensuring quality. By methodically reviewing and synthesizing the body of research conducted in this period, it underscores key contributions and breakthroughs in the application of AI within construction management (AICM). Additionally, the study aims to shed light on emerging trends and forecast future directions for technological innovation in the construction management sector.

Guided by the preferred reporting items for systematic reviews and meta-analyses (PRISMA) framework, this research conducts a bibliometric analysis of 176 relevant publications from the past five years. The analysis focuses on the adoption of AICM across three critical areas: construction equipment management, improvement of construction safety and construction cost optimization. Additionally, the study systematically identifies and examines 14 emerging themes within this domain, ensuring a comprehensive exploration aligned with PRISMA guidelines.

This manuscript summarizes recent research from the past five years in three key areas: construction equipment management, construction safety management and construction cost management within the realm of AICM. It identifies key gaps and outlines future research directions, including enhancing AI-driven equipment integration, developing sophisticated AI-based safety systems and optimizing cost management with advanced data analytics. These findings and directions are essential for steering the field toward greater digital innovation and sustainability.

This research provides a detailed analysis of the literature within the AICM domain, thoughtfully compiling significant findings and highlighting the importance of addressing user needs. The insights and recommendations shared aim to be beneficial for both academic researchers and industry professionals, contributing to the ongoing development of AICM as it moves toward a future characterized by digital innovation and sustainability.

The purpose of this paper is to identify risk factors in building information modeling (BIM) technology application, analyze the correlation between risk factors, and find the most influential risk factors using interpretative structural model (ISM), put forward a response to targeted suggestions, and provide a reference for widespread BIM technology application.

Literature reviews, ISM, a questionnaire survey and expert interviews were used in this paper. First, the risk factors of BIM technology application and their relationships were determined by consulting the relevant BIM literature. Second, to more intuitively reflect the relationships between risk factors, an ISM model based on expert interviews was established to structure the explanatory relationships and hierarchical relationships between factors. Finally, a questionnaire survey was conducted for relevant practitioners, and a scale was designed to evaluate the risk factors of BIM technology application to determine the risk factors that have a greater impact on implementing BIM technology.

The root risk factors of BIM technology consist of unclear data ownership, incomplete standard BIM systems, lack of industry insurance, lack of BIM technicians, lack of BIM project practice experience, BIM infrastructure preparation, inconsistent thinking about BIM from project participants, changes in delivery mode and software function problems.

The risk-sharing of BIM technology and the analysis of responsibilities, rights and benefits of all parties in a BIM project can be used as future research directions to solve higher management problems.

This paper describes the risks of BIM technology application for related researchers and provides another research train of thought for the follow-up studies.

Random point-contact between the space bearing retainer and the rolling elements may cause wear of the space bearing retainer. The paper aims to clarify the friction and wear behaviors of polyimide bearing retainer under point-contact condition.

Space bearing retainers were cut into flat specimens and the tribological behaviors of the specimens were studied under point-contact condition using a friction and wear testing machine. Different sliding velocities and normal loads were used to simulate the running state of space bearing retainer. The wear behaviors of the space bearing retainer were analyzed by SEM and white light interferometer.

The friction coefficient of the polyimide composites decreased with increase in sliding velocity from 1  to 5 mm/s. Moreover, with increase in sliding velocity and normal load, the wear rate of the polyimide composites decreased and increased, respectively. Moreover, the wear behaviors of the polyimide composites were mainly determined by the combined actions of ploughing friction and adhesive friction. The lubricating properties of transfer film and wear debris were limited under point-contact condition.

The paper includes implications for the understanding of the wear mechanism of the polyimide composites space bearing retainer under point-contact condition and then to optimize space bearing retainer materials further.

Under point-contact condition, wear debris can hardly participate in the friction process because of limited contact area. Consequently, the wear debris has limited impact on the wear process to decrease the friction and wear.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-01-2020-0017/

Because of the advantages of high deposition efficiency and low manufacturing cost compared with other additive technologies, robotic wire arc additive manufacturing (WAAM) technology has been widely applied for fabricating medium- to large-scale metallic components. The additive manufacturing (AM) method is a relatively complex process, which involves the workpiece modeling, conversion of the model file, slicing, path planning and so on. Then the structure is formed by the accumulated weld bead. However, the poor forming accuracy of WAAM usually leads to severe dimensional deviation between the as-built and the predesigned structures. This paper aims to propose a visual sensing technology and deep learning–assisted WAAM method for fabricating metallic structure, to simplify the complex WAAM process and improve the forming accuracy.

Instead of slicing of the workpiece modeling and generating all the welding torch paths in advance of the fabricating process, this method is carried out by adding the feature point regression branch into the Yolov5 algorithm, to detect the feature point from the images of the as-built structure. The coordinates of the feature points of each deposition layer can be calculated automatically. Then the welding torch trajectory for the next deposition layer is generated based on the position of feature point.

The mean average precision score of modified YOLOv5 detector is 99.5%. Two types of overhanging structures have been fabricated by the proposed method. The center contour error between the actual and theoretical is 0.56 and 0.27 mm in width direction, and 0.43 and 0.23 mm in height direction, respectively.

The fabrication of circular overhanging structures without using the complicate slicing strategy, turning table or other extra support verified the possibility of the robotic WAAM system with deep learning technology.

In recent years, Asian countries have experienced rising rates of premarital cohabitation, mirroring a similar trend that could be observed in many European countries several decades ago. As international differences in these trends are often attributed to institutional and societal differences, this study explores how China’s and Germany’s welfare and cultural regimes relate to national differences in the timing and prevalence of premarital cohabitation and direct marriage.

On the basis of two post-hoc harmonized surveys (pairfam for Germany; CFPS for China), descriptive analyses and logistic regressions were conducted. A higher standardization of partnership trajectories during the transition to adulthood was observed in China; this being probably related to China’s collectivist and Germany’s individualistic culture. While urban–rural differences prevail in China, and are attributable to China’s hukou system, East and West Germans differ considerably in this regard, a finding which can be traced back to regional differences in historical legacy. Discrepancies in economic modernization explain why the likelihood of experiencing these events differs for individuals in the Eastern and Western Chinese provinces.

Besides these differences, the two national contexts resemble each other in the prevalence of educational hypergamy, as well as in greater rates of cohabitation prior to first marriage, in contrast to direct marriage, seen among wealthier individuals and those with higher education. For the first time, the effects of cultural and institutional differences on the transition to adulthood were compared between a collectivistic vs. individualistic cultural regime and a productivist vs. corporatist conservative welfare regime, enabling researchers to draw conclusions about the link between cultural and welfare regime types and partnership patterns.

In this study, an eco-friendly cotton fabric (CF) treatment method was proposed to induce anti-ultraviolet and flame retardant properties, and a new application of tannic acid (TA) and phytic acid (PA) in ultraviolet protection and flame retardant fabric was put forward.

By combining diethylenetriamine, PA and TA on CF, a chemical reaction intumescent flame retardant CF with anti-ultraviolet and anti-flame retardance was developed.

The flame retardant and ultraviolet resistance of CF were characterized by LOI, vertical combustion, cone calorimetry and ultraviolet resistance testing. SEM, XPS, FTIR and other tests were used to analyze the chemical composition, surface morphology and residual carbon after combustion of the CF, and it was confirmed that the modified CF has good ultraviolet resistance and flame retardant performance.

In this study, an eco-friendly CF treatment method was proposed to induce anti-ultraviolet and flame retardant properties, and a new application of TA and PA in ultraviolet protection and flame retardant fabric was put forward.