Extreme Peak Distribution and Its Applications in Stochastic Structural Dynamics Problems

1991 ◽  
pp. 17-32
Author(s):  
Siu-Tong Choi ◽  
Wen-Fang Wu
Keyword(s):  
Structural Dynamics ◽  
Stochastic Structural Dynamics ◽  
Dynamics Problems

scholarly journals Substructuring and Component Mode Synthesis

1997 ◽  
Vol 4 (3) ◽  
pp. 199-210 ◽  
Author(s):  
P. Seshu
Keyword(s):  
Model Reduction ◽  
Structural Dynamics ◽  
Component Mode Synthesis ◽  
Popular Method ◽  
Dynamics Problems

Substructuring and component mode synthesis (CMS), is a very popular method of model reduction for large structural dynamics problems. Starting from the pioneering works on this technique in the early 1960s, many researchers have studied and used this technique in a variety of applications. Besides model reduction, CMS offers several other crucial advantages. The present work aims to provide a review of the available literature on this important technique.

Neural Networks for the Simulation and Identification Analysis of Buildings Subjected to Paraseismic Excitations

2007 ◽  
pp. 393-432 ◽  
Author(s):  
Krystyna Kuzniar ◽  
Zenon Waszczyszyn
Keyword(s):  
Neural Networks ◽  
Structural Dynamics ◽  
Dynamic Properties ◽  
Response Spectra ◽  
Engineering Practice ◽  
Identification Analysis ◽  
Dynamics Problems ◽  
Mining Tremors ◽  
Testing Patterns ◽  
Mining Regions

The chapter deals with an application of neural networks to the analysis of vibrations of medium-height prefabricated buildings with load-bearing walls subjected to paraseismic excitations. Neural network technique was used for identification of dynamic properties of actual buildings, simulation of building responses to paraseismic excitations as well as for the analysis of response spectra. Mining tremors in strip mines and in the most seismically active mining regions in Poland with underground exploitation were the sources of these vibrations. On the basis of the experimental data obtained from the measurements of kinematic excitations and dynamic building responses of actual structures the training and testing patterns were formulated. It was stated that the application of neural networks enables us to predict the results with accuracy quite satisfactory for engineering practice. The results presented in this chapter lead to a conclusion that the neural technique gives new prospects of efficient analysis of structural dynamics problems related to paraseismic excitations.

Sign in / Sign up

Export Citation Format

Share Document