Finite Element Model Updating Using Computational Intelligence

Finite Element Model Updating Using Computational Intelligence Techniques: Applications to Structural Dynamics

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.
Country USA
Brand Springer
Manufacturer Springer
Binding Hardcover
ItemPartNumber 16 black & white illustrations, 2 colour
ReleaseDate 2010-06-10
UnitCount 1
Format Illustrated
EANs 9781849963220

Country	USA
Brand	Springer
Manufacturer	Springer
Binding	Hardcover
ItemPartNumber	16 black & white illustrations, 2 colour
ReleaseDate	2010-06-10
UnitCount	1
Format	Illustrated
EANs	9781849963220

Finite Element Model Updating Using Computational Intelligence Techniques: Applications to Structural Dynamics