Sequential surrogate modeling for efficient finite element model updating. (May 2016) - Jin, Seung-Seop; Jung, Hyung-Jo
Highlights: This study propose a sequential surrogate modeling for FE model updating. Identical input parameters can produce simple and highly complex response-surfaces. Accordingly, the use of the identical samples for surrogate modeling is not efficient. The proposed method adds samples automatically based on the Kriging model. The proposed method can be customized for a variety of the response-surfaces. Abstract: Despite the numerous studies concerning finite element model updating (FEMU), a challenging computational cost issue persists. Therefore, surrogate modeling has recently gained considerable attention in FEMU. Conventionally, surrogate models are constructed by identical samples for all outputs. It is very inefficient and subjective, if various response-surfaces exhibit even for identical parameters. Accordingly, we propose a sequential surrogate modeling for FEMU. It uses infill criteria to guide sampling for updating surrogate models automatically. The proposed method is successful to construct the different response-surfaces and apply FEMU. It is promising for constructing surrogate models with minimal user intervention and tremendous computational efficiency.