The biggest environmental problem caused by the construction of tunnels adjacent to high-rise buildings is the settlement of buildings.The paper analyzes the influence of tunnel excavation on the deformation of the su...The biggest environmental problem caused by the construction of tunnels adjacent to high-rise buildings is the settlement of buildings.The paper analyzes the influence of tunnel excavation on the deformation of the superstructure and the deformation mode of the superstructure.It introduces the indicators and standards for the construction control of tunnel adjacent to the building at home and abroad.Combined with the Yuzhong tunnel project under construction in Chongqing,the main monitoring indicators and control standards of the Yuzhong Tunnel passing through the main buildings are given after comprehensive analysis and considerations,which provide a reference for the deformation control indicators of similar urban traffic tunnels adjacent to high-rise buildings.展开更多
This paper describes a building subsidence deformation prediction model with the self-memorization principle.According to the non-linear specificity and monotonic growth characteristics of the time series of building ...This paper describes a building subsidence deformation prediction model with the self-memorization principle.According to the non-linear specificity and monotonic growth characteristics of the time series of building subsidence deformation,a data-based mechanistic self-memory model considering randomness and dynamic features of building subsidence deformation is established based on the dynamic data retrieved method and the self-memorization equation.This model first deduces the differential equation of the building subsidence deformation system using the dynamic retrieved method,which treats the monitored time series data as particular solutions of the nonlinear dynamic system.Then,the differential equation is evolved into a difference-integral equation by the self-memory function to establish the self-memory model of dynamic system for predicting nonlinear building subsidence deformation.As the memory coefficients of the proposed model are calculated with historical data,which contain useful information for the prediction and overcome the shortcomings of the average prediction,the model can predict extreme values of a system and provide higher fitting precision and prediction accuracy than deterministic or random statistical prediction methods.The model was applied to subsidence deformation prediction of a building in Xi'an.It was shown that the model is valid and feasible in predicting building subsidence deformation with good accuracy.展开更多
基金National Key R&D Program of China Special Funding(2017YFC0805305)National Natural Science Foundation of China(41601574)Chinese Academy of Engineering Institute-Local Cooperation Project(2019-CQ-ZD-4)。
文摘The biggest environmental problem caused by the construction of tunnels adjacent to high-rise buildings is the settlement of buildings.The paper analyzes the influence of tunnel excavation on the deformation of the superstructure and the deformation mode of the superstructure.It introduces the indicators and standards for the construction control of tunnel adjacent to the building at home and abroad.Combined with the Yuzhong tunnel project under construction in Chongqing,the main monitoring indicators and control standards of the Yuzhong Tunnel passing through the main buildings are given after comprehensive analysis and considerations,which provide a reference for the deformation control indicators of similar urban traffic tunnels adjacent to high-rise buildings.
基金supported by the Twelfth Five National Key Technology R&D Program of China (2009BAJ28B04,2011BAK07B01,2011BAJ08B03,2011BAJ08B05)the National Natural Science Foundation of China(51108428)+1 种基金Beijing Postdoctoral Research Foundation (2012ZZ-17)China Postdoctoral Science Foundation (2011M500199)
文摘This paper describes a building subsidence deformation prediction model with the self-memorization principle.According to the non-linear specificity and monotonic growth characteristics of the time series of building subsidence deformation,a data-based mechanistic self-memory model considering randomness and dynamic features of building subsidence deformation is established based on the dynamic data retrieved method and the self-memorization equation.This model first deduces the differential equation of the building subsidence deformation system using the dynamic retrieved method,which treats the monitored time series data as particular solutions of the nonlinear dynamic system.Then,the differential equation is evolved into a difference-integral equation by the self-memory function to establish the self-memory model of dynamic system for predicting nonlinear building subsidence deformation.As the memory coefficients of the proposed model are calculated with historical data,which contain useful information for the prediction and overcome the shortcomings of the average prediction,the model can predict extreme values of a system and provide higher fitting precision and prediction accuracy than deterministic or random statistical prediction methods.The model was applied to subsidence deformation prediction of a building in Xi'an.It was shown that the model is valid and feasible in predicting building subsidence deformation with good accuracy.