Abstract
The development of material models for concrete subject to intense dynamic loadings, e.g., impact, penetration and blast loadings, is a topic of current research. A high-fidelity physics-based concrete material model should not only capture the high strain-rate, high pressure and large strain generated by intense dynamic loadings, but also the typical failure phenomena of concrete material, e.g., spalling and cracking. This paper presents a new concrete material model, which includes the advantages and discards the disadvantages of frequently used commercial material models. In this model, a three-invariant failure surface is proposed by interpolating the maximum strength surface and the residual strength surface based on the level of current damage. The compressive damage and tensile damage are separately treated. The compressive damage is a function of the modified equivalent plastic strain, while the tensile damage is based on observations of recent dynamic tensile tests which demonstrated that, at high strain-rate, the fracture strain is a constant and the fracture energy increases with increase of strain-rate. Strain-rate effect is taken into account through the radial enhancement approach where the failure surface is enhanced equally in radial direction. To capture the shear dilation of concrete material that is ignored by most commercial concrete material models, a partially associative flow rule is introduced. Automated generation of parameters is suggested for convenience of practical application. The new concrete material model is implemented into the finite element code LS-DYNA through user defined material model. To validate the new material model, comprehensive single element tests including the uniaxial, biaxial and triaxial compressions and tensions are firstly conducted, where the improved performances are demonstrated by comparisons of corresponding predictions by the commercial concrete material models. Then selected numerical examples covered a wide range of loading intensity are presented, and numerical predictions are found to be in excellent agreement with corresponding experimental data.
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