Correlation Degree Analysis of Surface Settlement Influence Factors Around the Pit

Abstract

The excavation of city subway pit breaking the original balance of the soil, affecting the safety of existed buildings and the surface subsidence of construction are important and direct factors which react to construction impacts. Using the Gray Relational Analysis Theory, through monitoring measured data of factors, building gray correlation analysis among excavation of subway construction surface subsidence, horizontal displacement of pile top, deep displacement, the groundwater level, the support axial force, the anchor cable tension and other factors, get the collective degree of different monitoring program. The results show that, the factors, from maximal to minimum correlation degree, which affect surface subsidence includes horizontal displacement of pile top, anchor cable tension, the groundwater level, deep displacement, strut axial forces. It provides a theoretical basis for law of surface subsidence and similar monitoring program optimization for the future projects. The excavation of city subway pit breaks the original balance of the soil. Before the excavation and construction process, in order to prevent pit deformation, measures has been taken, such as diaphragm wall, concrete support, steel support, anchor and so on. However, it does not eliminate the impact of excavation on the surrounding environment. Construction causes the movement of surrounding ground, and it leads to different degrees of surface subsidence and horizontal displacement. Most projects are located in the bustling city center, if the settlement exceeds a certain level, will cause surface subsidence, collapse pit, building damage, underground pipelines damage, etc., and it will have serious impact on personal property, the economy and life. Some scholars study the deep foundation pit bottom uplift calculation method (1), monitor excavation during construction (2), and use a theoretical model to predict the surface movement and deformation which based on geotechnical characteristics during excavation (3). They also developed many kinds of surface subsidence model law based on measured data(4, 5, 6), such as Logistic Model, Neural Network Model, GM Gray System Model, Time Series Forecasting Model, and Gray- BP Neural Network Prediction Model (7, 8). This paper analyzes the gray correlation excavation of the monitoring project and surface subsidence values, and distinguishes the various factors that influence the degree of surface subsidence.