To implement the performance-based seismic design of engineered structures,the failure modes of members must be classified.The classification method of column failure modes is analyzed using data from the Pacific Eart...To implement the performance-based seismic design of engineered structures,the failure modes of members must be classified.The classification method of column failure modes is analyzed using data from the Pacific Earthquake Engineering Research Center(PEER).The main factors affecting failure modes of columns include the hoop ratios,longitudinal reinforcement ratios,ratios of transverse reinforcement spacing to section depth,aspect ratios,axial compression ratios,and flexure-shear ratios.This study proposes a data-driven prediction model based on an artificial neural network(ANN)to identify the column failure modes.In this study,111 groups of data are used,out of which 89 are used as training data and 22 are used as test data,and the ANN prediction model of failure modes is developed.The results show that the proposed method based on ANN is superior to traditional methods in identifying the column failure modes.展开更多
By using Karamata regular variation theory and upper and lower solution method,we investigate the existence and the global asymptotic behavior of large solutions to a class of semilinear elliptic equations with nonlin...By using Karamata regular variation theory and upper and lower solution method,we investigate the existence and the global asymptotic behavior of large solutions to a class of semilinear elliptic equations with nonlinear convection terms.In our study,the weight and nonlinearity are controlled by some regularly varying functions or rapid functions,which is very different from the conditions of previous contexts.Our results largely extend the previous works,and prove that the nonlinear convection terms do not affect the global asymptotic behavior of classical solutions when the index of the convection terms change in a certain range.展开更多
基金China Energy Engineering Group Planning&Engineering Co.,Ltd.Concentrated Development Scientific Research Project Under Grant No.GSKJ2-T11-2019。
文摘To implement the performance-based seismic design of engineered structures,the failure modes of members must be classified.The classification method of column failure modes is analyzed using data from the Pacific Earthquake Engineering Research Center(PEER).The main factors affecting failure modes of columns include the hoop ratios,longitudinal reinforcement ratios,ratios of transverse reinforcement spacing to section depth,aspect ratios,axial compression ratios,and flexure-shear ratios.This study proposes a data-driven prediction model based on an artificial neural network(ANN)to identify the column failure modes.In this study,111 groups of data are used,out of which 89 are used as training data and 22 are used as test data,and the ANN prediction model of failure modes is developed.The results show that the proposed method based on ANN is superior to traditional methods in identifying the column failure modes.
基金Supported by Startup Foundation for Docotors of Weifang University(2016BS04)
文摘By using Karamata regular variation theory and upper and lower solution method,we investigate the existence and the global asymptotic behavior of large solutions to a class of semilinear elliptic equations with nonlinear convection terms.In our study,the weight and nonlinearity are controlled by some regularly varying functions or rapid functions,which is very different from the conditions of previous contexts.Our results largely extend the previous works,and prove that the nonlinear convection terms do not affect the global asymptotic behavior of classical solutions when the index of the convection terms change in a certain range.
