Construction and Quality Control of Subway Wet Loess in Concealed Tunnel Based on Particle Swarm Optimization Algorithm

Abstract

To reduce urban pressure, urban rail transit has become an effective way to reduce traffic congestion, mitigate traffic accidents, reduce environmental pollution, and improve commuting efficiency. Subway as the main means of urban public transport travel, in recent years by people’s favor, although the construction industry of rail transit is developing rapidly and the industry scale is expanding, but because the construction of rail transit construction projects is very difficult, especially in the wet loess within the concealed excavation tunnel, but also frequent accidents, and the quality of the project is not easy to guarantee, so the underground railroad wet loess within the concealed excavation tunnel construction technology is poor. Therefore, it is especially important to study the construction technology and project quality management of underground railway concealed tunnel in wet loess. In this paper, based on the in-depth study of the basic principle of quantum particle swarm optimization calculation and the realization of key engineering technologies, the particle swarm optimization algorithm is programed using MATLAB software, and the coding scheme, operation specification, and operation parameters are designed. Then, combined with the particle swarm optimization algorithm and assisted MATLAB software, the main analysis of the construction and quality control of wet loess in concealed tunnels of subway projects was carried out, mainly by systematizing the relationship between the three major elements of subway project schedule, cost, and management and the construction and quality control of wet loess in concealed tunnels of a subway, and concluded that the construction and quality control of wet loess in concealed tunnels of the subway needed schedule. It is concluded that the construction and quality control of subway wet loess tunnel requires stable schedule, adequate cost budget, and management personnel.