Spall Fracture of Solid and Molten Copper: Molecular Dynamics, Mechanical Model and Strain Rate Dependence

In this study, we formulate a mechanical model of spall fracture of copper, which describes both solid and molten states. The model is verified, and its parameters are found based on the data of molecular dynamics simulations of this process under ultrahigh strain rate of tension, leading to the formation of multiple pores within the considered volume element. A machine-learning-type Bayesian algorithm is used to identify the optimal parameters of the model. We also analyze the influence of the initial size distribution of pores or non-wettable inclusions in copper on the strain rate dependence of its spall strength and show that these initial heterogeneities explain the existing experimental data for moderate strain rates. This investigation promotes the development of atomistically-based machine learning approaches to description of the strength properties of metals and deepens the understanding of the spall fracture process

Influence of θ′ Phase Cutting on Precipitate Hardening of Al–Cu Alloy during Prolonged Plastic Deformation: Molecular Dynamics and Continuum Modeling

We investigate the prolonged plastic deformation of aluminum containing θ′ phase with a multistage approach combining molecular dynamics (MD), continuum modeling (CM) and discrete dislocation dynamics (DDD). The time of performed MD calculations is sufficient for about a hundred dislocation–precipitate interactions. With this number of interactions, the inclusion of θ′ is not only cut, but also scattered into individual copper atoms in an aluminum matrix. Damage to the crystal structure of inclusion and activation of the cross-slip of dislocation segments cause a decrease in acting stresses in the MD system. The rate of this effect depends on θ′ diameter and occurs faster for small inclusions. The effect of decreasing the resistance of precipitate is further introduced into the dislocation–precipitate interaction CM by reducing the precipitate effective diameter with an increase in the number of interactions. A model of dislocation–precipitate interaction accounting for the softening of inclusions is further implemented into DDD. Dependences of flow stress in aluminum with θ′ phases on volume fraction and typical diameter of precipitates are obtained. Manifestation of inclusion softening is possible in such an alloy, which leads to the flow stress decrease during deformation. The range of volume fractions and typical diameters of θ′ phases corresponding to the possible decrease in flow stress is distinguished

Modified Taylor Impact Tests with Profiled Copper Cylinders: Experiment and Optimization of Dislocation Plasticity Model

Current progress in numerical simulations and machine learning allows one to apply complex loading conditions for the identification of parameters in plasticity models. This possibility expands the spectrum of examined deformed states and makes the identified model more consistent with engineering practice. A combined experimental-numerical approach to identify the model parameters and study the dynamic plasticity of metals is developed and applied to the case of cold-rolled OFHC copper. In the experimental part, profiled projectiles (reduced cylinders or cones in the head part) are proposed for the Taylor impact problem for the first time for material characterization. These projectiles allow us to reach large plastic deformations with true strains up to 1.3 at strain rates up to 105 s−1 at impact velocities below 130 m/s. The experimental results are used for the optimization of parameters of the dislocation plasticity model implemented in 3D with the numerical scheme of smoothed particle hydrodynamics (SPH). A Bayesian statistical method in combination with a trained artificial neural network as an SPH emulator is applied to optimize the parameters of the dislocation plasticity model. It is shown that classical Taylor cylinders are not enough for a univocal selection of the model parameters, while the profiled cylinders provide better optimization even if used separately. The combination of different shapes and an increase in the number of experiments increase the quality of optimization. The optimized numerical model is successfully validated by the experimental data about the shock wave profiles in flyer plate experiments from the literature. In total, a cheap, simple, but efficient route for optimizing a dynamic plasticity model is proposed. The dislocation plasticity model is extended to estimate grain refinement and volume fractions of weakened areas in comparison with experimental observations