Among the construction methods for subway projects, shield method construction technology has become a more widely used construction method for urban subway construction due to the advantages of a high degree of construction mechanization, low impact of the construction process on the environment, and strong adaptability of the shield machine to the stratum, etc. However, because of the complexity of the surrounding buildings (structures) in the subway construction, coupled with the diversity of the subway shield method construction activities and the uncertainties in the construction environment, to a certain extent, it is determined that the subway construction process is very complicated. The purpose of this study is based on the text mining method, where text is mined and utilized to realize the identification, extraction, and display of safety risk factors. Thus, it guides the safety management on site and provides a basis for knowledge reuse in other metro shield construction projects. Firstly, we analyze the shortcomings of safety risk management in domestic and international metro shield construction via a literature review, especially the utilization of safety risk text data. Secondly, we collect the risk reports submitted by all parties via the “Metro Project Safety Risk Early Warning System”, and manually screen the hidden danger statements with risk characterization to establish a corpus. Thirdly, we use the Jieba word separation package to extract and display the safety risk factors, so as to guide the on-site safety management. Subsequently, with the help of the Jieba word segmentation package for Chinese word segmentation, we develop a professional thesaurus to improve the effect of word segmentation; then, we use the TF-IDF parameter assignment to achieve the structural transformation of the text to extract high-frequency vocabulary; finally, from the high-frequency vocabulary to screen words containing the semantics of the risk to establish the risk of an initial set of words, we use the existing standards and norms to form the collection of safety risk factors of subway shield construction and generate the cloud diagram for visual display.

Old residential areas present unique challenges in terms of design, stakeholders, and renovation requirements compared to traditional building projects. However, unreasonable construction plans can lead to delays, cost overruns, poor quality, and conflicts between the construction party and local residents. This article proposes an optimization model that prioritizes progress, quality, and cost as the key control objectives, leveraging the actual conditions of renovating old residential areas. The NSGA-II genetic algorithm is employed to solve the mathematical model. To validate the effectiveness and scientific rigor of the algorithm, a renovation project in an old residential area in Wuhan is used as a case study. The findings of this study offer valuable theoretical support for decision makers in selecting appropriate construction plans.

With its advantages such as large capacity, punctuality and low environmental impact, the metro has become one of the primary means of alleviating urban traffic congestion. However, safety accidents still occur frequently during the construction of metro deep foundation pits. A review of domestic and international studies reveals that safety risk management for metro deep foundation pit construction remains insufficient, particularly in terms of comprehensive risk identification, analysis of risk interrelationships and systematic risk assessment. To improve the level of safety risk management in metro deep foundation pit construction, this study analyzes safety risk factors using Chinese word segmentation, AHP, ISM, and MICMAC methods. Based on text mining and literature review, a case database comprising 156 metro deep foundation pit construction safety accidents reports was established and integrated into a unified text corpus. Chinese word segmentation was then performed on the corpus, and through risk interpretation combined with relevant standards and codes, 29 safety risk factors were identified and classified into five categories: technology, management, material, personal and environment. On this basis, 22 main safety risk factors were extracted using the AHP method. The results indicate that management-related factors constitute the most critical type of safety risk. Subsequently, the ISM method was employed to identify the interactions among the main safety risk factors and to construct a five-level hierarchical model, in which the top level contains nine safety risk factors, while the bottom level consists of two factors. Through MICMAC analysis, the safety risk factors were classified into three categories, based on which a safety risk management framework for metro deep foundation pit construction was established, and specific control measures were proposed for six representative safety risk factors.

Building Information Modeling (BIM) is an emerging information technology tool and management concept in the construction industry, enabling the transition from traditional 2D drawings to 3D models. It helps improve efficiency and promote industrial upgrading in the construction sector. However, in actual project practices, the effectiveness of BIM application has not been as expected, and the return on investment (ROI) may even be negative. Through a literature review, we found that risk identification, correlation analysis, and risk assessment related to BIM implementation require further research. To better promote the application of BIM in the construction industry, this study employs relevant methods to analyze the risk factors of BIM implementation. Through the literature review, 31 BIM implementation risk factors were identified, and 24 major risk factors were extracted using the AHP (Analytic Hierarchy Process) method. The ISM (Interpretative Structural Modeling) method was then used to determine the interrelationships among these major risk factors, establishing a hierarchical model with seven levels. Through MICMAC (Matrices Impacts Corises-Multiplication Appliance Classment) analysis, the BIM implementation risk factors were categorized into three groups, and three-tiered response strategies were proposed at the industry, organizational, and project levels. By analyzing the main risk factors of BIM application in China’s construction industry and formulating corresponding response strategies to promote its successful application, this study contributes to the knowledge system. The findings also provide a reference for other countries and regions to clarify major risk factors and their interrelationships, thereby improving the effectiveness of BIM implementation.

Tropical buildings face the coupled effects of four-high environmental factors, which accelerate thermal–humidity degradation, increase operational energy demands, and diminish building health attributes. This paper systematically integrates global research advancements to establish a theoretical framework for Tropical Low-Carbon Healthy Building Enclosures (TLHBEs) by linking materials, structures, and buildings across scales. It identifies three key scientific questions: (1) Establishing a multi-scale parametric design model that couples materials, structures, and architecture. (2) Elucidating experimental and simulated multi-scale equivalent relationships under the coupled effects of temperature, humidity, radiation, and salinity. (3) Design multi-objective optimization strategies balancing energy efficiency, comfort, indoor air quality, and carbon emissions. Based on this, a technical implementation pathway is proposed, integrating multi-scale unified parametric design, multi-physics testing and simulation, machine learning, and intelligent optimization technologies. This aims to achieve multi-scale parametric design, data–model fusion, interpretable decision-making, and robust performance prediction under tropical climatic conditions, providing a systematic technical solution to address the key scientific questions. This framework not only provides scientific guidance and engineering references for designing, retrofitting, and evaluating low-carbon healthy buildings in tropical regions but also aligns with China’s dual carbon goals and healthy building development strategies.