Seismic Response Prediction of Multiple Base-Isolated Structures for Monitoring

2020 ◽  
pp. 33-41
Author(s):  
Francesco Potenza ◽  
Vincenzo Gattulli ◽  
Satish Nagarajaiah
Keyword(s):  
Seismic Response ◽  
Response Prediction ◽  
Isolated Structures

Seismic response prediction of base-isolated structures with high damping rubber bearings

2015 ◽  
Vol 39 (1) ◽  
pp. 12-25
Author(s):  
Yin-Han Yang ◽  
Jenn-Shin Hwang ◽  
Shiang-Jung Wang ◽  
Chia-Yi Shiau ◽  
Nobuo Murota
Keyword(s):  
Seismic Response ◽  
Response Prediction ◽  
High Damping Rubber Bearings ◽  
Isolated Structures ◽  
High Damping Rubber ◽  
Rubber Bearings

Seismic Reliability Analysis in the Framework of Metamodelling Based Monte Carlo Simulation

2017 ◽  
pp. 192-208 ◽  
Author(s):  
Shyamal Ghosh ◽  
Soham Mitra ◽  
Swarup Ghosh ◽  
Subrata Chakraborty
Keyword(s):  
Least Squares ◽  
Reliability Analysis ◽  
Response Surface ◽  
Seismic Response ◽  
Least Squares Method ◽  
Response Prediction ◽  
Seismic Intensity ◽  
Seismic Reliability ◽  
Moving Least Squares Method ◽  
Artificial Neural Network Ann

A comparative study of various metamodelling approaches namely the least squares method (LSM), moving least squares method (MLSM) and artificial neural network (ANN) based response surface method (RSM) are presented to demonstrate the effectiveness to approximate the nonlinear dynamic response of structure required for efficient seismic reliability analysis (SRA) of structures. The seismic response approximation by the LSM, MLSM and ANN based RSMs are explained with a brief note on the important issue of ground motion bin generation. The procedure adopted herein for SRA is based on the dual response surface approach. In doing so, the repetition of seismic intensity for SRA at different intensity levels is avoided by including this as one of the predictors in the seismic response prediction model. A nonlinear SDOF system has been taken up to elucidate the effectiveness of various metamodels in SRA.

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