Parameter Identification for Off-line Model Fitting and On-line Model Updating Using Gradient-based Methods

• Main Authors: Ming-Chieh Chuang, 莊明介
• Other Authors: Shang-Hsien Hsieh
• Format: Others
• Language: en_US
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/z7b2km

博士 === 國立臺灣大學 === 土木工程學研究所 === 105 === In the nonlinear structural response simulations, researchers often need to calibrate the parameters of a nonlinear material model with the experimental data by using the trial and error method. This can be very tedious and time consuming. In order to improve the calibration efficiency, the efficient method of parameter identification is desired. This study is to present two gradient-based parameter identification methods (GBM_MF and GBM_MU) for off-line model fitting and on-line model updating, respectively. The proposed GBM_MF method for off-line model fitting can assist the engineers and researchers, who are engaged in the nonlinear structural analyses, in model calibration. In addition, for the advanced hybrid simulation with on-line model updating, the proposed parameter identification method (GBM_MU) with innovative modification is presented in this dissertation. The shaking table test of a five-story BRB frame (BRBF) conducted in E-defense Japan in 2009 is utilized to verify the effectiveness of the proposed methods in the off-line and on-line applications. Compared with the measured responses, the results of off-line model fitting application can confirm that the proposed gradient-based method (GBM_MF) allows the efficient model calibration for the accurate simulation of the nonlinear responses of the BRBF. Moreover, the advantage of the on-line model updating with the proposed parameter identification method (GBM_MU) is demonstrated through the simulated hybrid tests. As a result, the proposed gradient-based methods of parameter identification for off-line model fitting and on-line model updating can advance the earthquake engineering research and practice.