TY - GEN
T1 - Finite element model updating using evolutionary optimization methods
AU - Marwala, Tshilidzi
AU - Mdlazi, Lungile
PY - 2005
Y1 - 2005
N2 - This paper proposes particle swarm optimization method and response surface method based on genetic algorithm for finite element model updating. These proposed methods are compared to existing finite element model updating approaches, which use simulated annealing and genetic algorithm. The proposed methods are tested on a simple beam and an unsymmetrical H-shaped structure. It is observed that on average the particle swarm optimization method gave the most accurate results. They were followed by simulated annealing, then the genetic algorithm and lastly the response surface method. The response surface method, however, was found to be more computationally efficient than the other three methods.
AB - This paper proposes particle swarm optimization method and response surface method based on genetic algorithm for finite element model updating. These proposed methods are compared to existing finite element model updating approaches, which use simulated annealing and genetic algorithm. The proposed methods are tested on a simple beam and an unsymmetrical H-shaped structure. It is observed that on average the particle swarm optimization method gave the most accurate results. They were followed by simulated annealing, then the genetic algorithm and lastly the response surface method. The response surface method, however, was found to be more computationally efficient than the other three methods.
UR - http://www.scopus.com/inward/record.url?scp=84861563007&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84861563007
SN - 0912053895
SN - 9780912053899
T3 - Conference Proceedings of the Society for Experimental Mechanics Series
BT - IMAC-XXIII
T2 - 23rd Conference and Exposition on Structural Dynamics 2005, IMAC-XXIII
Y2 - 31 January 2005 through 3 February 2005
ER -