Today, the inverse identification or optimization of material model parameters is very often used to find input parameter values for use in relevant nonlinear material models. These parameter values should enable the responses of structures obtained from numerical simulations to very closely approximate the real responses of such structures obtained from experiments. Due to the popularity of concrete as a construction material, much attention is paid to nonlinear material models that aim to describe its behavior. This paper is focused on the optimization-based inverse identification of the parameters of two related nonlinear concrete material models which are known as the Karagozian & Case Concrete model and the Karagozian & Case Concrete model - Release III. Within this paper, the identification of the material model parameters is performed on the basis of interaction between nonlinear numerical simulations, optimization algorithms and experimental data, the latter of which take the form of a loading curve measured during a triaxial compression test. A comparison of the responses of both of the used material models when the optimized parameters are employed is, of course, part of this paper.Today, the inverse identification or optimization of material model parameters is very often used to find input parameter values for use in relevant nonlinear material models. These parameter values should enable the responses of structures obtained from numerical simulations to very closely approximate the real responses of such structures obtained from experiments. Due to the popularity of concrete as a construction material, much attention is paid to nonlinear material models that aim to describe its behavior. This paper is focused on the optimization-based inverse identification of the parameters of two related nonlinear concrete material models which are known as the Karagozian & Case Concrete model and the Karagozian & Case Concrete model - Release III. Within this paper, the identification of the material model parameters is performed on the basis of interaction between nonlinear numerical simulations, optimization algorithms and experimental data, the latter of which take the form of a loading cur...
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