Selecting the objective function during the inverse identification of the parameters of a material model of concrete

Selecting the objective function during the inverse identification of the parameters of a material model of concrete

WoS Article

Selecting the correct objective function is the critical precondition for a successful optimization task. The validity of this condition is also required when optimization algorithms are needed for the inverse identification of the unknown parameters of nonlinear material models of concrete, where experimentally measured load-displacement curves can be conveniently applied. In such cases, the objective function expressions can be formulated as the difference between the functional values of the curves or via comparing the characteristic features, which comprise the area under the curve and also the maximum functional value. The proposed article brings a study of the influence of the different formulations of the objectives functions to achieving optimum in the inverse analysis using genetic algorithm. The numerical part of the study was performed in the ANSYS computational system with use of multiPlas library of elasto-plastic material models from which the model based on formulations of Menetrey and Willam was chosen.

Selecting the correct objective function is the critical precondition for a successful optimization task. The validity of this condition is also required when optimization algorithms are needed for the inverse identification of the unknown parameters of nonlinear material models of concrete, where experimentally measured load-displacement curves can be conveniently applied. In such cases, the objective function expressions can be formulated as the difference between the functional values of the curves or via comparing the characteristic features, which comprise the area under the curve and also the maximum functional value. The proposed article brings a study of the influence of the different formulations of the objectives functions to achieving optimum in the inverse analysis using genetic algorithm. The numerical part of the study was performed in the ANSYS computational system with use of multiPlas library of elasto-plastic material models from which the model based on formulations of Menetrey and Willam was chosen.

Identification; Objective function; RMSE; Optimization; Sensitivity analysis

Identification; Objective function; RMSE; Optimization; Sensitivity analysis

HOKEŠ, F.; KALA, J.

2021

01.01.2017

Gruppo Italiano Frattura

Itálie

1971-8993

Frattura ed Integrita Strutturale

11

39

Republic of Italy

7

16

10

https://www.fracturae.com/index.php/fis/article/view/IGF-ESIS.39.02

http://hdl.handle.net/

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