Structure Excavation Numerical Simulation And Distortion Forecast Research

With the development of urban construction and people's living standards, multi-storey and high-rise buildings in the basement, underground garage, subway, large-scale bridges, etc. in the construction process will be faced with varying degrees of deep foundation engineering problems. Especially in the process of excavation the level of pile top displacement and excavation of the settlement issue, which has been around the surface was closely, and it is urgent to solve. As the stress state of geotechnical engineering and geological parameters is complex, uncertain and nonlinear, therefore, we need to find one in the excavation process to provide real-time reference model in order to achieve construction design, the measures and the protection of construction safety purposes.This article is from engineering reality. It took Shenyang Hang Lung Plaza City Hall for example, pit-site monitoring of the deformation analysis of the data processing, combined with numerical simulation and finite-difference simulation of the excavation to maintain the structure and surface subsidence analysis and forecasting, and integration of the finite difference analysis, time series, neural networks, genetic algorithms, MATLAB, etc. a number of theories and tools. Among them, application of finite-difference simulation of the pit excavation process, reasonable given the excavation process, as well as the stress analysis of cloud cloud pile deformation, completing the construction process in the finite-difference simulation process. Application of time series and genetic optimization of neural networks to pile top displacement and the surrounding ground surface settlement and made a further analysis of forecast data processing, thereby establishing the time series and genetic optimization of neural network model is proposed that prediction of surface subsidence pit and its deformation value, the construction process so that it can provide a reference for real-time predictive analysis to prevent construction damage to the environment in order to play a role in advance to plan for it. At the end of this article, we put the time-series model and genetic optimization of neural network package into a system as a platform for human-computer interaction for future similar projects, which to provide some degree of convenience.