Based on the identification and analysis of safety risks in TBM tunnel construction, we construct a comprehensive safety risk dynamic evaluation index system tailored to this context. To account for the dynamic nature of safety risks during TBM tunnel construction, variable weight theory is incorporated, allowing for a more accurate reflection of the time-varying importance of risk indicators. Building on the theoretical framework of attribute interval recognition theory, we establish a TBM tunnel construction safety risk evaluation model grounded in attribute interval theory. This model effectively addresses the various uncertainties inherent in the risk evaluation process for TBM tunnel construction. It determines the evaluation level and attribute intervals for each individual indicator, and subsequently calculates the interval values for both the individual indicators and the composite attribute. Finally, a case study demonstrates the model’s effectiveness and practical applicability.

The traditional quality gain-loss function(QGLF) considers the case that the primary term loss cannot be ignored, does not consider the cubic term loss, but in practice the cubic term loss should not be ignored. In this paper, based on the existing QGLF model, the Taylor expansion is reserved to the third order, the determination of the quality loss coefficient is discussed and analyzed under the condition that the compensation quantity is constant, and the asymmetric cubic QGLF model is established, and uses an example of concrete mixture out of the machine slump during the dam concrete construction to analyze and discuss the relationship between the proposed model and the traditional quadratic QGLF, which verifies the rationality of the proposed model.

In the past, the optimization of engineering specifications primarily included the influence of quality loss terms on product quality; however, in actual production practice, compensation quantity inevitably affects the optimization quality of engineering specifications. In this paper, the quadratic exponential quality loss and gain function was first supplemented, and the quadratic exponential quality loss and gain function was constructed under the larger-the-better characteristic and the smaller-the-better characteristic; in order to accurately represent the change in compensation amount in the process of quality control, the optimization method of engineering specification under the calculation of quality loss and compensation was given in combination with the hyperbolic tangent function. Finally, with the support of the dam construction quality acceptance assessment, the engineering specification optimization model was tested. The optimal coefficient was obtained as 0.162, and the specification range was reduced from 0.744 to 0.648, achieving the optimization goal.

Considering the influence of process complexity, resource tension, human complexity and external influence on the buffer size, and the relay potential effect of mutual cooperation and cross-construction among processes, a calculation model of critical chain buffer size is proposed, which comprehensively considers the influencing factors of process entropy, resource entropy, human entropy, external entropy and relay potential. This model considers the local correlated complexity of processes, and uses the allowable relative deviation value of process quality characteristic target values as the standard to judge the technical complexity of processes. At the same time, it proposes a resource tension calculation that considers the efficiency of flexible resource substitution, thereby optimizing the calculation of process correlated and technical complexity, as well as the impact of resource tension on buffer size. Through example analysis, it can be concluded that in the case where the model in this article considers more factors than other comparative models, the calculated import buffer value is within the range of import buffer values calculated by other comparative models, and the project buffer and project schedule only increase by an average of about 4 days. Therefore, the model proposed in this article is used to control the buffer size reasonably and effectively reduce the project schedule risk.

Optimizing Rural Water Supply Network (RWSN) is the basis for improving rural people’s lives and improving people’s health. Currently, the RWSN in China is relatively backward and can no longer meet the needs of the unified management of rural water resources. To optimize the RWSN, this study innovatively established a Multi-Objective Optimization Mathematical Model (MOMM) of RWSN, combining economic factors and reliability. This experiment first analyzes the characteristics of the RWSN system and then establishes a MOMM of a water supply network. NSGA-II algorithm and LM algorithm are introduced to handle the multi-objective model. The research results show that compared to Web decision tools, the RWSN based on the LM-NSGA-II algorithm can save 5.4% of the total annual cost of water supply pipelines. Therefore, the MOMM of the rural water supply pipeline based on the LM-NSGA-II algorithm has better economy and reliability. The experiment aims to provide certain reference values for the optimal control of RWSN through this study.