Dynamics of structural defects and plasticity: models and numerical implementation for dynamical problems

We report the plasticity model with explicit description of kinetics of the material defects (dislocations, grain boundaries). This method becomes especially effective for computation of the dynamical deformation of materials at high strain rates because it allows for a simple accounting of the strain rate effects. The equation system is written out and discussed; its implementation is demonstrated for the problem of the plastic flow localization

Ibrutinib as initial therapy for patients with chronic lymphocytic leukemia

Background: chronic lymphocytic leukemia (CLL) primarily affects older persons who often have coexisting conditions in addition to disease-related immunosuppression and myelosuppression. We conducted an international, open-label, randomized phase 3 trial to compare two oral agents, ibrutinib and chlorambucil, in previously untreated older patients with CLL or small lymphocytic lymphoma. Methods: we randomly assigned 269 previously untreated patients who were 65 years of age or older and had CLL or small lymphocytic lymphoma to receive ibrutinib or chlorambucil. The primary end point was progression-free survival as assessed by an independent review committee. Results: the median age of the patients was 73 years. During a median follow-up period of 18.4 months, ibrutinib resulted in significantly longer progression-free survival than did chlorambucil (median, not reached vs. 18.9 months), with a risk of progression or death that was 84% lower with ibrutinib than that with chlorambucil (hazard ratio, 0.16; P<0.001). Ibrutinib significantly prolonged overall survival; the estimated survival rate at 24 months was 98% with ibrutinib versus 85% with chlorambucil, with a relative risk of death that was 84% lower in the ibrutinib group than in the chlorambucil group (hazard ratio, 0.16; P=0.001). The overall response rate was higher with ibrutinib than with chlorambucil (86% vs. 35%, P<0.001). The rates of sustained increases from baseline values in the hemoglobin and platelet levels were higher with ibrutinib. Adverse events of any grade that occurred in at least 20% of the patients receiving ibrutinib included diarrhea, fatigue, cough, and nausea; adverse events occurring in at least 20% of those receiving chlorambucil included nausea, fatigue, neutropenia, anemia, and vomiting. In the ibrutinib group, four patients had a grade 3 hemorrhage and one had a grade 4 hemorrhage. A total of 87% of the patients in the ibrutinib group are continuing to take ibrutinib. Conclusions: ibrutinib was superior to chlorambucil in previously untreated patients with CLL or small lymphocytic lymphoma, as assessed by progression-free survival, overall survival, response rate, and improvement in hematologic variables. (Funded by Pharmacyclics and others; RESONATE-2 ClinicalTrials.gov number, NCT01722487.)

Dynamics of structural defects and plasticity: models and numerical implementation for dynamical problems

We report the plasticity model with explicit description of kinetics of the material defects (dislocations, grain boundaries). This method becomes especially effective for computation of the dynamical deformation of materials at high strain rates because it allows for a simple accounting of the strain rate effects. The equation system is written out and discussed; its implementation is demonstrated for the problem of the plastic flow localization

Incipience of Plastic Flow in Aluminum with Nanopores: Molecular Dynamics and Machine-Learning-Based Description

Incipience of plastic flow in nanoporous metals under tension is an important point for the development of mechanical models of dynamic (spall) fracture. Here we study axisymmetric deformation with tension of nanoporous aluminum with different shapes and sizes of nanopores by means of molecular dynamics (MD) simulations. Random deformation paths explore a sector of tensile loading in the deformation space. The obtained MD data are used to train an artificial neural network (ANN), which approximates both an elastic stress–strain relationship in the form of tensor equation of state and a nucleation strain distance function. This ANN allows us to describe the elastic stage of deformation and the transition to the plastic flow, while the following plastic deformation and growth of pores are described by means of a kinetic model of plasticity and fracture. The parameters of this plasticity and fracture model are identified by the statistical Bayesian approach, using MD curves as the training data set. The present research uses a machine-learning-based approximation of MD data to propose a possible framework for construction of mechanical models of spall fracture in metals

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

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