Civil structure condition assessment by FE model updating: methodology and case studies
Finite Elements in Analysis and Design
Response Surface Methodology: Process and Product in Optimization Using Designed Experiments
Response Surface Methodology: Process and Product in Optimization Using Designed Experiments
Finite Element Model Updating Using Computational Intelligence Techniques: Applications to Structural Dynamics
| Hi-index | 0.00 |
The requirement of repeated evaluation of structural responses in typical sensitivity based Finite Element Model Updating (FEMU) procedure limits its popular applications for large structures. The least-squares method (LSM) based response surface method (RSM) is applied as a potential alternative for responses approximations in iterative model updating procedure. However, the LSM is a major source of error in response prediction and the moving least-squares method (MLSM) is found to be more efficient in this regard. An attempt has been made in the present study to explore the effectiveness of MLSM based RSM in FEMU. A comparative assessment is performed between the MLSM based and the conventional LSM based RSM for model parameter updating. The comparative study is being illustrated with the help of two example problems using artificially generated input responses. It is generally observed that the MLSM based RSM identifies better than the LSM based approach.