It is acknowledged that construction safety is pivotal to the project management objectives. Meanwhile, the concept of resilience provides an effective and pragmatic countermeasure to improve the safety management level of construction projects. However, the “resilience” has not gained considerable attention in the construction safety management system. In this context, the paper aims to develop the key safety management factors for construction projects from the resilience perspective. Firstly, the theoretical framework and key safety management factors of construction safety management system based on the resilience theory are proposed. The importance of each factor is then obtained by using the method of structural equation modeling (SEM). The results indicate that information management, material and technology management, organization management and personnel management would improve the safety and resilience of the project. Specifically, improving the resilience of information flow to strengthen the interaction among elements of the system can enhance the safety management level. These findings can be used as references for construction safety managers to improve the abilities of preventing safety accidents and recovering after safety accidents.

Value creation is the primary motivation for public-private cooperation. The development of urban rail transit (URT) projects requires heavy investment and abundant construction and management experience. Thus, public-private partnership (PPP) is usually adopted in URT project development to benefit the public and private sectors. However, with the high-quality development of PPP projects, the value creation of URT PPP projects is not only about achieving basic project objectives but also relying on partner synergy to achieve value-added. Based on the extended connotation of value creation, this study intends to systematically identify the influencing factors of value creation of URT PPP projects in China. The grounded theory approach was adopted to deduce the influencing factors of value creation through analyzing the various types of articles related to Chinese URT PPP projects. Resources complementarity among stakeholders, cooperation environment, and partnership synergy were identified as the main influencing factors. Meanwhile, a theoretical model that described how these influencing factors combined to promote value creation during public-private sectors cooperation of URT projects was established. This research helps broaden the understanding of how public and private sectors should cooperate and collaborate in URT projects to realize value maximization and promote the sustainable development of URT PPP projects and provides a model for further empirical examination.

This study presents an in-depth investigation into the intersection of Building Information Modeling (BIM) and green building practices within China’s rapidly evolving construction industry. As China intensifies its efforts to mitigate environmental impacts and promote sustainable growth, the integration of BIM into green building practices emerges as a crucial area of study. A qualitative research method was adopted in this research. In the first step, utilizing semi-structured interviews with a diverse array of industry professionals, this research provides nuanced insights into the current state and prospects of BIM in the green building landscape. Secondly, thematic analysis is used to formalize the views and points from interviewees. Finally, a novel conceptual framework is proposed, addressing these challenges through technological innovation, supportive policies, cultural and educational reform, economic incentives, and collaborative dynamics. This study contributes a systematic approach to amalgamate BIM with sustainable construction, offering insights for industry professionals and policymakers to promote environmentally conscious building practices in China.

In urban underground construction, Earth Pressure Balance (EPB) tunneling faces complex geological uncertainties and dynamic operational risks. Traditional safety management approaches often struggle under such conditions. This paper proposes an integrated safety resilience assessment framework for EPB tunneling that combines an entropy-weighted TOPSIS method, the Analytic Network Process (ANP), and an extension cloud model to capture interdependencies and uncertainties. A hierarchical indicator system with four primary dimensions (stability, redundancy, efficiency, and fitness) is constructed. The entropy-TOPSIS algorithm provides objective initial weights and scenario ranking, while ANP models the feedback relationships among criteria. The extension cloud model quantifies fuzziness in expert judgments and converts qualitative assessments into probabilistic resilience ratings. The methodology is applied to a case study of the EPB shield tunnel section of Jinan Metro Line 6 (China). The section’s resilience is classified as a medium level, which agrees with expert evaluation. The results demonstrate that the proposed approach yields accurate and robust safety resilience evaluations, supporting data-driven decision-making. This framework offers a quantitative tool for resilience-based safety management of shield tunneling projects, providing guidance for shifting from traditional risk control toward a resilience-enhancement strategy.

Blast design in drill-and-blast tunnelling requires geological interpretation and parameter selection for each excavation cycle, yet these tasks are often conducted separately, making it difficult to adapt plans to changing ground conditions. This study develops a multi-agent framework that integrates multimodal large language models with graph-based retrieval-augmented generation (GraphRAG) to connect geological assessment with preliminary blast-plan generation. A geological analysis agent, adapted through low-rank adaptation (LoRA)-based supervised fine-tuning on 1222 training cycles, combines tunnel-face images, ground-penetrating radar (GPR) profiles, and geological logs to classify the rock mass. A blast design agent uses the predicted class, cross-sectional geometry, planned advance, and site constraints to retrieve code provisions, design rules, and historical cases from a domain knowledge graph. It generates a structured preliminary plan with associated source and applicability records. On the held-out tunnel test set, domain adaptation increased classification macro-F1 from 78.6% to 89.7%. A seven-condition ablation supported the complementary contributions of the three modalities, with geological logs providing the strongest single-source performance. Across 60 design tasks under a common evidence-budget limit, GraphRAG improved blast-plan macro-F1 over conventional RAG by 4.1 percentage points with Qwen2.5-VL-7B-Instruct and 7.7 percentage points with MiMo-VL-7B. On an independent project, classification and blast-plan macro-F1 reached 82.4% and 84.0%, respectively, exceeding the unadapted classification model and conventional-RAG comparator by 7.5 and 4.4 percentage points. An illustrative Jinan Tunnel plan received an aggregate expert score of approximately 91. These findings support the framework’s use in integrating geological information and design evidence to prepare preliminary blast plans for engineering review.

During operation, shield tunnel linings commonly develop ovalization and cracking. Steel-plate strengthening is an effective measure for delaying structural performance degradation and extending the service life of shield tunnel linings. However, the effects of steel-plate strengthening parameters on the deformation response of shield tunnel linings are not yet fully understood. The associated control mechanisms remain unclear. Moreover, rapid and accurate evaluation of strengthening effectiveness is not achievable with existing methods. To address these issues, a rapid evaluation method integrating refined numerical simulation with the Bayesian optimization–random forest (BO-RF) model was proposed. A refined three-dimensional numerical model was established. The tracking element method was used to ensure continuity of the structural state of the shield tunnel linings throughout the steel-plate strengthening process. The reliability of the model was verified against previously reported full-scale model test results. On this basis, the deformation response of the shield tunnel linings under the reference load was predicted. The initial ovality of the shield tunnel linings and the steel-plate strengthening parameters were used as input variables to evaluate the deformation-control performance. Strengthening time, represented by the initial ovality before strengthening, had the greatest influence on the deformation response and deformation-control performance of the shield tunnel linings. Steel plate thickness had the second-greatest influence, whereas that of steel plate width was relatively limited. Within the parameter range investigated in this study, the deformation-control rate ranged from 16.53% to 91.02%. Four prediction models were constructed, and their hyperparameters were optimized using Bayesian optimization (BO). The following model types were considered: extreme gradient boosting (XGBoost), a one-dimensional convolutional neural network (1D-CNN), a support vector machine (SVM), and a random forest (RF). The corresponding models were denoted as BO-XGBoost, BO-1D-CNN, BO-SVM, and BO-RF, respectively. The best overall performance in terms of prediction accuracy and computational efficiency was achieved by the BO-RF model. The coefficient of determination (R²), root mean square error (RMSE), and mean absolute error (MAE) were 0.9817, 2.8704, and 1.7669, respectively. The model was trained in 206.6 s. Compared with numerical simulation alone, the computational time was reduced by 31.38 h. This reduction corresponded to a 99.62% reduction in computational time. Mechanistic analysis showed that tensile stress on the inner surface of the shield tunnel linings was redistributed through interfacial force transfer at the steel plate-lining interface. Local stress concentration and expansion of the damage zones were thereby inhibited. The steel plate was installed on the inner surface of the shield tunnel linings. Consequently, damage evolution was suppressed to a significantly greater extent on the inner surfaces than on the outer surfaces.