Abstract
In the field of engineering, simulations are often used to save experimental cost and time. Since most of the simulation models have various model errors, the simulation results may differ from the actual one. It is important to accurately calibrate and predict parameters as the calibrated parameters can be applied to other simulations and are used as important design criteria. Therefore, if there is an error in the simulation model, this model error should be taken into consideration when parameters are calibrated. The calibration method usually uses a function value based least squares method, but when there is an error in the simulation model, it fits well at the training point, but an error may occur at the prediction point. For this reason, Qiu et al. [1] proposed a sensitivity based the least squares method—a method of calibrating model parameters by matching the slope of the simulation result and the slope of the actual value. In this paper, the performance and applicabiliy of SLS is further investigated with two examples. In the cantilever beam example which was studied earlier by Qiu et al. [1], a finite element model is introduced to account for various sources of error. In the open hole tenstion test example, the performance of SLS in a multidimensional problem was examined and compared with FLS.
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Acknowledgments
This research was supported by the MOTIE (Ministry of Trade, Industry, and Energy) in Korea, under the Fostering Global Talents for Innovative Growth Program (P0008751) supervised by the Korea Institute for Advancement of Technology (KIAT).
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Gwangtaeck Lee received his Bachelor’s and Master’s in Mechanical Engineering from Keimyung University, Daegu, Korea. His research interests include optimal design and dynamic impact simulation
Sanghoon Lee is an Assistant Professor of Mechanical and Automotive Engineering at the Keimyung University, Daegu, South Korea. His Ph.D. in Mechanical Engineering is from Korea Advanced Institute of Science and Technology in 2006. His research area is design optimization, design under uncertainty, and radioactive waste package design and safety evaluation
Nam-Ho Kim is presently Professor of Mechanical and Aerospace Engineering at the University of Florida. He graduated with a Ph.D. in Mechanical Engineering from the University of Iowa in 1999. His research area is structural design optimization, design sensitivity analysis, design under uncertainty, structural health monitoring, nonlinear structural mechanics, and structural-acoustics
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Lee, G., Lee, S. & Kim, N. A study on model calibration using sensitivity based least squares method. J Mech Sci Technol 36, 809–815 (2022). https://doi.org/10.1007/s12206-022-0128-4
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DOI: https://doi.org/10.1007/s12206-022-0128-4