Quasi-static testing is the primary seismic research method employed.The method proposed in this study utilizes the neural network(NN)algorithm for restoring force identification to extend the hysteretic performance o...Quasi-static testing is the primary seismic research method employed.The method proposed in this study utilizes the neural network(NN)algorithm for restoring force identification to extend the hysteretic performance of nonlinear complex components obtained from quasi-static tests shared or performed at a lower cost to the time history analysis of the seismic response of the entire structure.This approach enables accurate analysis of the seismic performance of the structure under real earthquake ground motions at a relatively low experimental costs.At the level of restoring force model recognition,the eight-path hysteresis model recognition theory and the corresponding complete set of input and output variables in the NN algorithm are proposed.The NN restoring force model was established using input and output parameters that characterize hysteresis state features,with a two-hidden-layer NN architecture.The case study results indicate that the prediction results of the NN restoring force model align well with the target values when trained on samples obtained under both seismic and quasi-static loading conditions.At the level of the nonlinear dynamic analysis of structures,the hybrid analysis method of structural seismic response based on NN restoring force model is proposed.In this method,the potentially severe nonlinear and elastic parts of the structure are divided into several NN substructures and principal numerical substructure,respectively.The pseudo-static test data of nonlinear regions were used to train the proposed NN restoring force model to identify the restoring force of NN substructures in the same region under time-history dynamic analysis.The platform was built to complete the data interaction between several NN substructures and principal numerical substructures,and a precise integration method was used to program the dynamic equation solving module,gradually completing dynamic response analysis of the entire structure.A multi-degree-offreedom nonlinear frame case study indicate that the proposed method has good accuracy and can effectively analyze the structural nonlinear seismic response.展开更多
基金supports from the National Natural Science Foundation of China(Grant Nos.52478305 and 52308483)Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.KYCX22_0213).
文摘Quasi-static testing is the primary seismic research method employed.The method proposed in this study utilizes the neural network(NN)algorithm for restoring force identification to extend the hysteretic performance of nonlinear complex components obtained from quasi-static tests shared or performed at a lower cost to the time history analysis of the seismic response of the entire structure.This approach enables accurate analysis of the seismic performance of the structure under real earthquake ground motions at a relatively low experimental costs.At the level of restoring force model recognition,the eight-path hysteresis model recognition theory and the corresponding complete set of input and output variables in the NN algorithm are proposed.The NN restoring force model was established using input and output parameters that characterize hysteresis state features,with a two-hidden-layer NN architecture.The case study results indicate that the prediction results of the NN restoring force model align well with the target values when trained on samples obtained under both seismic and quasi-static loading conditions.At the level of the nonlinear dynamic analysis of structures,the hybrid analysis method of structural seismic response based on NN restoring force model is proposed.In this method,the potentially severe nonlinear and elastic parts of the structure are divided into several NN substructures and principal numerical substructure,respectively.The pseudo-static test data of nonlinear regions were used to train the proposed NN restoring force model to identify the restoring force of NN substructures in the same region under time-history dynamic analysis.The platform was built to complete the data interaction between several NN substructures and principal numerical substructures,and a precise integration method was used to program the dynamic equation solving module,gradually completing dynamic response analysis of the entire structure.A multi-degree-offreedom nonlinear frame case study indicate that the proposed method has good accuracy and can effectively analyze the structural nonlinear seismic response.
