This study briefly presents four concrete models used for ballistic impact simulations. The models are the RHT model (*MAT_272 or *MAT_RHT), the CSCM model (*MAT_159 or *MAT_CSCM), the K&C model (*MAT_072R3 or *MAT_CONCRETE_DAMAGE_REL3) and a modified Holmquist-Jonson-Cook model (MHJC). The first three are available as standard models in LS-DYNA with the option to automatically generate their constitutive parameters. The MHJC model has been implemented as a user subroutine. In the present study, we calibrated the MHJC model parameters for C75 high-strength concrete by using laboratory material experiments and data from the literature. Ballistic simulations of C75 concrete slabs impacted by ogival projectiles validated the accuracy of the calibrated parameters. We evaluated the default parameter generation of the former three models compared to the latter.
The cement hydration reaction has long been recognized as an important contributor to defects throughout the service life of concrete structures. As the hydration reaction is highly exothermic, and the thermal conductivity of concrete is relatively low, high temperatures and temperature gradients have special relevance in massive concrete structures. Massive concrete structures can endure significant cracking when temperature induced deformations are restrained. Uncontrolled cracking may compromise the structure durability and reliability, e.g. in massive concrete slabs for rail infrastructures or marine structures or the structure functionality, e.g. watertightness in liquid retaining structures or may even represent an aesthetically unacceptable defect for a concrete structure with demanding architectural finishing requirements. The heat generation and the consequent temperature rise in concrete structures is also a problem for the damaging effects on the concrete mechanical properties following deleterious chemical reactions such as Delayed Ettringite Formation (DEF). This chemical reaction is known to be associated with thermal fields in early-age concrete usually of the order 65°C to 75°C.
A deep understanding of advanced material plasticity and fracture is one of the cornerstones of mechanical engineering to overcome present and future challenges in the automotive industry with respect to lightweight multi-material body solutions. The von Mises plasticity model is well-known and efficiently implemented in the various CAE solvers conventionally used in the automotive industry. One of the principal characteristics of the von Mises model is the assumption of isochoric plasticity (i.e. no change of volume is caused by yielding). The literature and experiments show that some materials, like extruded aluminium or polymers, exhibit non-isochoric plastic behaviour. Since this effect cannot be captured by the von Mises plasticity model, an optimal design for lightweight structural solutions is compromised.
Saturated sandy soils can be prone to liquefaction during earthquakes: the soil loses strength and stiffness due to cyclic shear loading, becoming more like a liquid or quicksand. When liquefaction occurs, structures founded on such soils may experience severe damage or large settlement, or may even overturn. Designers of structures in seismically-active regions where liquefiable soils are present need to assess the likelihood of liquefaction occurring under design-level earthquakes and, if required, provide mitigating measures in the design. Three-dimensional nonlinear finite element analysis can be used to understand the effects of liquefaction on a structure and, if sufficient validation of the soil properties has been carried out under a range of stress conditions, can potentially predict the extent of liquefaction that will occur as a result of a given earthquake time-history. However, this requires a soil material model capable of reproducing the phenomena relevant to liquefaction.
Forming simulation models and the associated material characterisation are important factors when representing the increasingly complex deep drawing operations. Especially in context of automotive components, the finite element analysis ensures producibility prior to pilot series and minimises the risk of wasting resources by predicting the material behaviour as accurately as possible, such as plastic, thermal and anisotropic behaviour. For the representation of the plastic material deformation during forming, material models like Barlat or Hill, representing the real material behaviour as precisely as possible, must be implemented in the simulation. For this purpose, the model needs to describe occurring effects of the material such as anisotropy or further effects.
The substitution of classical constitutive material models with data-driven models supported by machine learning techniques could provide a leap in the modelling of materials. The most notable benefits are a faster description of new materials without a tedious manual parameter identification procedure, lower computational time for simulations due to efficient computation within the material model and a more efficient selection of the correct material model for the use-case. The base for any data-driven model is adequate amount and quality of training data. Based on this, machine learning techniques can be used to train neural networks such that they learn the relationship between given input and output. The mapping in the machine learning based material model will be the strain measures to the stresses, similar to classical models.
*MAT_258 (*MAT_NON_QUADRATIC_FAILURE) is a through-thickness failure regularization model for shells in LS-DYNA. In this model the failure indicator is computed as a function of both the size of the element and its bending-to-membrane loading ratio. The constitutive behavior and fracture surface in *MAT_258 are represented by well-known analytical expressions which simplify calibration. We present the calibration process for *MAT_258 with a three-parameter Extended Cockcroft-Latham fracture surface for the high strength steel Docol 1500M. The material card is applied in shell element simulations of three-point bend tests.
During plastic deformation of a metal, a part of the plastic work is stored in the material due to local distortion of the crystal lattice, while the remainder is dissipated as heat. The part of the plastic work dissipated as heat can be observed on a macroscopic scale through thermal measurements in high strain rate experiments. Typically, this fraction of plastic work converted into heat is assumed to be constant and around 90%. In this study, we have performed tension tests at a constant crosshead velocity of 0.6 mm/s on flat notched specimens from a DP600 steel material. Digital image correlation (DIC) was used to apply virtual extensometers spanning the length of the notched area. Furthermore, an infrared camera was used to measure the temperature increase over the same area as monitored by DIC, enabling correlation between temperature and displacement. These temperature-displacement curves were used as the target curves in thermomechanical simulations to obtain the Taylor-Quinney coefficient as a function of the equivalent plastic strain. It was found that the Taylor-Quinney coefficient exhibits quite large variations during the experiment, ranging from a minimum of about 0.5 in the beginning of the test, to about 0.95 at the end of test.
Survey of four material models for ballistic simulations of high-strength concrete