Finite Element Model Updating Using Computational Intelligence Techniques - Applications to Structural Dynamics (Paperback, 2010 ed.)

FEM updating allows FEMs to be tuned better to reflect measured data. It can be conducted using two different statistical frameworks: the maximum likelihood approach and Bayesian approaches. This book applies both strategies to the field of structural mechanics, using vibration data. Computational intelligence techniques including: multi-layer perceptron neural networks; particle swarm and GA-based optimization methods; simulated annealing; response surface methods; and expectation maximization algorithms, are proposed to facilitate the updating process. Based on these methods, the most appropriate updated FEM is selected, a problem that traditional FEM updating has not addressed. This is found to incorporate engineering judgment into finite elements through the formulations of prior distributions. Case studies, demonstrating the principles test the viability of the approaches, and. by critically analysing the state of the art in FEM updating, this book identifies new research directions.

General

Imprint:	Springer London
Country of origin:	United Kingdom
Release date:	November 2014
First published:	2010
Authors:	Tshilidzi Marwala
Dimensions:	235 x 155 x 14mm (L x W x T)
Format:	Paperback
Pages:	250
Edition:	2010 ed.
ISBN-13:	978-1-4471-5716-8
Categories:	Books > Professional & Technical > Civil engineering, surveying & building > General Books > Computing & IT > Applications of computing > Computer modelling & simulation Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematics for scientists & engineers Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematical modelling Books > Computing & IT > Applications of computing > Artificial intelligence > General Books > Professional & Technical > Mechanical engineering & materials > Materials science > Mechanics of solids > General
LSN:	1-4471-5716-8
Barcode:	9781447157168

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