Using the inverse identification of parameters of a nonlinear concrete material model for analysis of RC structural element

Using the inverse identification of parameters of a nonlinear concrete material model for analysis of RC structural element

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Finite element (FE) analyses of reinforced concrete (RC) structures or structural elements using nonlinear concrete material models are currently a subject of interest for many scientific institutions or departments. Obtaining of relevant results from such analyses depends on a number of aspects, including (for example) the level of complexity of the computational model used, correct boundary conditions, the correct definition of parameter values of the material models used, etc. A key aspect from the above-mentioned aspects is especially the problematic of the definition of correct parameter values of the used material models. Defining the correct parameter values of the material models is often a very difficult task because we usually do not have enough knowledges about the given parameters or their possible ranges. However, the current level of computational technology combined with the current state of knowledge in the fields of mathematical statistics, artificial neural networks and optimization allows us to successfully deal with the given task by so called inverse identification of parameters whose correct numerical values we need to obtain. The aim of this paper is to show the possibility of using the optimization-based inverse identification of parameter values of a nonlinear concrete material model for FE analysis of structural element which is a high RC beam subjected to a four-point bending. For this purpose, the results of the corresponding experiment are used.

Finite element (FE) analyses of reinforced concrete (RC) structures or structural elements using nonlinear concrete material models are currently a subject of interest for many scientific institutions or departments. Obtaining of relevant results from such analyses depends on a number of aspects, including (for example) the level of complexity of the computational model used, correct boundary conditions, the correct definition of parameter values of the material models used, etc. A key aspect from the above-mentioned aspects is especially the problematic of the definition of correct parameter values of the used material models. Defining the correct parameter values of the material models is often a very difficult task because we usually do not have enough knowledges about the given parameters or their possible ranges. However, the current level of computational technology combined with the current state of knowledge in the fields of mathematical statistics, artificial neural networks and optimization allows us to successfully deal with the given task by so called inverse identification of parameters whose correct numerical values we need to obtain. The aim of this paper is to show the possibility of using the optimization-based inverse identification of parameter values of a nonlinear concrete material model for FE analysis of structural element which is a high RC beam subjected to a four-point bending. For this purpose, the results of the corresponding experiment are used.

experiment; FE analysis; four-point bending test; concrete; reinforcement; inverse parameter identification.

experiment; FE analysis; four-point bending test; concrete; reinforcement; inverse parameter identification.

KRÁL, P.; HRADIL, P.; KALA, J.; KALA, Z.; HOKEŠ, F.

2021

24.07.2019

AIP Conference Proceedings

1551-7616

AIP conference proceedings

2019

Spojené státy americké

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