SUBSTRUCTURE ONLINE TEST USING PARALLEL HYSTERESIS MODELING BY NEURAL NETWORK
In general, hysteresis models that are applied to a numerical analysis part of substructure online tests do not refer directly to the experimental behavior of the members or subassemblage under loading tests. The objective of this study is to develop a new experimental technique for substructure online tests based on nonlinear hysteretic characteristics estimated with a neural network. A new learning algorithm for the network applicable to substructure online tests is proposed, focusing on input layer variables and their scaling method, and its validity is examined through several numerical and experimental investigations. The results show that the proposed testing scheme successfully reproduces the dynamic behavior of the model structure.
earthquake response substructure online test neural network Ramberg-Osgood model
Y. Nakano W. J. Yang
Dept. of Fundamental Engineering ,Institute of Industrial Science, The University of Tokyo, Tokyo, J Research Fellow, ESnS Structure Research Center, Kwangwoon University, Seoul, Korea
国际会议
14th World Conference on Earthquake Engineering(第十四届国际地震工程会议)
北京
英文
2008-10-12（万方平台首次上网日期，不代表论文的发表时间）