Abstract
One of the biggest challenges associated with modelling the behaviour of reinforced concrete is the difficulty of incorporating realistic material models that can represent the observable behaviour of the physical system. Experiments for relevant loading rates and pressures reveal that steel and concrete exhibits a complicated nonlinear behavior that is difficult to capture in a single constitutive model. LS-DYNA provides several material models to simulate the structural behaviour of reinforced concrete. To provide some guidance in selecting the proper one for users who have limited experience on numerical simulation of steel and concrete, this paper reviews the background theory and evaluates performance of different material models to predicting the response of reinforced concrete structures to dynamic loads as well as advantageous and disadvantageous of models. Comparisons of several widely available concrete constitutive models are presented pertaining to their ability to reproduce basic laboratory data for concrete and steel as well as predict the response of structures subjected to shock and impact loadings. The performance of these models was assessed by comparison of finite element analysis model and experimental results of reinforced concrete structures to insure that the overall behaviour prediction is qualitatively acceptable, even if the exact parameter fit or material characterization is not available. The authors concluded that the accuracy of the finite element results relied on the selection of material model as well as the input parameter values. The material model assessment presented in this study can be used in the numerical simulation to generate appropriate models for concrete and steel.
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Acknowledgements
The research is financially supported by the Ministry of Science and Technology of China (Grant No. 2017YFC0703603), the Taishan Scholar Priority Discipline Talent Group program funded by the Shandong Province.
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Abedini, M., Zhang, C. Performance Assessment of Concrete and Steel Material Models in LS-DYNA for Enhanced Numerical Simulation, A State of the Art Review. Arch Computat Methods Eng 28, 2921–2942 (2021). https://doi.org/10.1007/s11831-020-09483-5
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DOI: https://doi.org/10.1007/s11831-020-09483-5