identifying defect size in two dimensional plates based on boundary measurements using reduced model and genetic algorithm

identifying defect size in two dimensional plates based on boundary measurements using reduced model and genetic algorithm

;BRAHIM BENAISSA;IDIR BELAIDI;ADERRACHID HAMRANI
journal of big data 2014 pp. 115-120
137
benaissa2014sciencesidentifying

Abstract

­In this study the proper orthogonal decomposition method is utilised as a model reduction technique in crack size estimation in a cracked plate under traction problem. The idea is to create a reduced model based on the results issued from finite element method, thus the crack size parameter is directly related to the boundary displacement obtained from the boundary nodes considered as sensor points. The inverse investigation is run using a genetic algorithm to minimization the error function expressed as the difference between data caused by the crack proposed by genetic algorithm in every individual and the one measured at the actual crack identity. The reduced model is validated by comparing the estimated structural response with the corresponding results from the finite element model. The effectiveness of the approach related to the used number of sensors is presented. Finally the stability of the method against uncertainty is tested by introducing different levels of white noise to the reference data.

Citation

ID: 168875
Ref Key: benaissa2014sciencesidentifying
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
168875
Unique Identifier:
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet