Optimal Procedure for Determining Constitutive Parameters of Giuffrè–Menegotto–Pinto Model for Steel Based on Experimental Results

Describing the nonlinear behaviour of constitutive materials plays an important role in structural analysis. The Giuffrè–Menegotto–Pinto (GMP) model is widely used in the nonlinear modelling of steel structures, with its constituent parameters often calibrated from tests. However, the experimental results obtained require intermediate identification procedures before being used directly, meanwhile, the calibration of model parameters based on experimental data is complicated due to the many interrelated constituent variables. This paper aims to propose a method that calibrates the GMP model parameters optimally based on the experimental data. An available set of test results of high-strength steels subjected to cyclic strain is employed to perform an optimal analysis. The obtained results are then compared to numerical and experimental results to evaluate the effectiveness of the proposed method. An extensive study was carried out to evaluate the applicability of the optimal parameters obtained and those suggested by OpenSees. The findings reveal that the proposed procedure is highly efficient, making it a useful option for developing OpenSees applications that automatically calibrate model parameters. A typical 3D steel frame structure subjected to an earthquake is analyzed to evaluate the applicability of the results obtained. © 2022, Korean Society of Steel Construction.