The accumulation of years imbues historical buildings within universities with a profound sense of heritage, evident not only in the temporal imprints within their internal spaces but also in the evolution of their external surroundings. This cultural legacy subtly enriches students’ spatial awareness of history and fosters a collective memory of campus context. Current scholarly inquiry into university historical buildings primarily revolves around comprehensive considerations encompassing the preservation of these edifices, the overarching planning of academic institutions, and the safeguarding of the distinctive features inherent to historical structures. However, the predominant focus lies on qualitative analyses, leaving a pressing need for quantitative assessments and the establishment of an evaluation framework to gauge the efficacy of historical building preservation in academia. Addressing this gap, this study employs the Analytic Hierarchy Process (AHP) and Fuzzy Comprehensive Evaluation (FCE) to formulate the University Historical Building Protection Evaluation Framework (UHBPEF). Drawing from the examination and categorization of the primary instructional edifices within the Yujiatou campus of Wuhan University of Technology through the Research Classification Method (RCM), along with the consolidation of insights from experts and academic stakeholders, this study underscores the imperative of enhancing the scientific precision and pertinence of the university’s strategy for preserving historical buildings. By employing both qualitative and quantitative methodologies, this study offers innovative insights into the challenges facing historical building preservation in university settings, therefore propounding effective preservation strategies and offering a roadmap for future endeavors in this domain.

This paper focuses on the application of human–computer interaction technology in construction project safety management. Through bibliometric methods, we carried out an in-depth analysis of 286 relevant papers from Web of Science and Google Scholar from 2000 to 2024. The research results indicate that human–computer interaction technology has achieved remarkable development in four aspects: intelligent monitoring systems, risk assessment and management, ergonomics and cognitive psychology, as well as computer simulation and virtual reality. Meanwhile, this research has given rise to a series of new research topics, such as the safety operation decision-making method for intelligent construction machinery, the application of human action behavior recognition technology, and the application of Internet of Things technology in the safety control of smart construction sites. Additionally, future research modules have been identified, including personalized safety training, digital twin technology, and multimodal data analysis. This study not only summarizes the existing research achievements but also puts forward targeted suggestions for future development trends in the field of construction safety management from a practical perspective, aiming to promote the in-depth application and development of human–computer interaction technology in construction safety management.

Based on the up-floating incident of the basement in a high-rise residential building, the finite element (FE) model of the up-floating destruction region is established to investigate the damage mechanism. The stress states and the deformations of the basement structure are obtained under complex loads including water buoyancy forces, vehicle loads and construction loads. To assess the extent of damage, a novel damage indicator is defined based on two levels: the cracking bending moments and the yield bending moment. The first-level cracking bending moment, second-level cracking bending moment and the yield bending moment can be determined using the section stratification method. By comparing the maximum bending moment of the component with its corresponding cracking moment, one can determine whether the cracks have occurred and assess their severity. Meanwhile, the antifloating failure model is constructed to analyze the mechanism of the up-floating destruction. Finally, a detailed reinforcement treatment plan of ‘decompression first and then reinforcement’ is presented to reinforce and repair the damaged basement structure. The mechanism analysis of the up-floating destruction and the comprehensive reinforcement treatments ensure the simulation of the life cycle of emergence, development and treatment to ensure structural safety.

In recent years, the preservation of historic university buildings has gained increasing attention, particularly in the context of fire safety, as building fires pose significant threats to these structures. In alignment with global initiatives on resilient cities and communities, a focus on enhancing fire resilience in historic university buildings has emerged. From the perspective of fire resilience in historic university buildings, this study constructs an IDIA model for evaluating fire resilience in historic university buildings based on the improved Delphi method(ID), the Interpretive Structure Model (ISM), and the Analytical Network Process (ANP). This model objectively identifies fire resilience indicators for historic university buildings, explores the interactions between influencing factors, and analyzes the priorities of factors influencing fire resilience in historic university buildings, thereby improving the overall fire resilience of the historic university building system. This research focused on the administrative and teaching buildings of the former Central South School of Architecture and Engineering on the Mafangshan Campus of Wuhan University of Technology. The results indicate that fire resistance levels, the fire water supply system and fire awareness are extremely important indicators of fire resilience in historic university buildings. This research framework contributes to understanding the fire resilience of historic university buildings and is of vital importance for building resilient communities.

Historical districts are the mark of the continuity of urban history and are non-renewable. Typhoon disasters rank among the most serious and frequent natural threats to China’s coastal regions. Improving the wind resilience of China’s coastal historical districts is of great significance for their protection and inheritance. Accurately analyzing the different characteristics of the influencing factors of wind resilience in China’s coastal historical districts can provide a theoretical basis for alleviating the damage caused by typhoons and formulating disaster prevention measures. This paper accurately identifies the main influencing factors of wind resilience in China’s coastal historical districts and constructs an influencing factor system from four aspects: block level, building level, typhoon characteristics, and emergency management. An IIM model for the systematic analysis of influencing factors of wind resilience in China’s coastal historical districts based on the Improved Decision Making Trial and Evaluation Laboratory (IDEMATEL), Interpretive Structural Modeling (ISM), and Matrices Impacts Croises-Multiplication Appliance Classement (MICMAC) methods is established. This allows us to explore the mechanism of action of internal influencing factors of typhoon disasters and construct an influencing factor system, in order to propose prevention measures from the perspective of typhoon disaster characteristics and the overall perspective of China’s coastal historical districts. The results show that the driving force of a building’s windproof design in China’s coastal historical districts is low, but its dependence is strong; the driving forces of block morphology, typhoon level, and emergency plan are strong, but their dependence is low. A building’s windproof design is a direct influencing factor of the wind resilience of China’s coastal historical districts; block morphology, typhoon level, and emergency plan are the most fundamental and key influencing factors of the wind resilience of China’s coastal historical districts.

The rational selection of subway station locations is an interdisciplinary problem encompassing architecture, transportation, and other fields. Few evaluation index systems and quantitative evaluation methods exist for choosing subway station locations; thus, this paper establishes a novel evaluation framework. Overall, 21 indicators covering the construction and operation phases are selected by a literature review, providing a basis for planning decision makers. The Projection Pursuit Method (PPM) and the Bald Eagle Search (BES) algorithm are employed to assign objective weights. The Continuous Ordered Weighted Averaging (COWA) operator is utilized to obtain subjective weights. A combination weighting method is used based on game theory to improve the accuracy of weight calculation. Game theory and extension cloud theory are applied to develop an improved extension cloud model and evaluate the suitability based on optimal cloud entropy. We conduct a case study of 15 stations on the Chengdu Metro Line 11, China. The results reveal that the coordination of the development plans, the alignment with the land use plan, and regional population density are the most crucial tertiary indicators that should be considered in selecting subway station locations. These findings agree with the actual conditions, demonstrating the scientific validity of the proposed evaluation method, which outperforms classical evaluation methods. The proposed method is efficient and feasible for selecting subway station locations.