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Statistical and Thermomechanical Modeling of Dynamic Porosity-Based Ductile Damage

ORAL

Abstract

Microstructural features have a significant effect on the development of porosity in weakly shocked polycrystalline metallic materials. The statistical nature of void emergence in these materials is hypothesized to be driven by the interaction between heterogeneous local stress and distributed material weak points. Under weak shock conditions, material deformation is accommodated by elastic, plastic, and damage mechanisms. External power is partitioned into these mechanisms in a new probabilistic thermodynamically consistent finite deformation porosity-based dynamic ductile damage model. Included in the damage model is a new isotropic dislocation-based plasticity model that partitions plastic power into cold work and temperature increase as dictated by an evolving Taylor-Quinney coefficient. The spatial appearance frequency of nucleated voids follows a physically informed distribution supported by molecular dynamics and polycrystal calculations whose left tail we are beginning to understand as very important. Void evolution is described by a tensile pressure driven thick-walled sphere local power balance accounting for surface energy and micro-inertial effects. The computational plasticity work and damage model comparison to flyer plate impact experiments will be presented.

Publication: Schmelzer, N. J., Lieberman, E. J., Chen, N., Dunham, S. D., Anghel, V., Gray III, G. T., Bronkhorst, C. A. Statistical evaluation of microscale stress conditions leading to void nucleation in the weak shock regime. International Journal of Plasticity. In Revision.<br><br>Schmelzer, N. J., Lieberman, E.J., Chen, N., Bronkhorst, C. A. Quantifying power partitioning during void growth for dynamic mechanical loading in reduced form. International Journal of Plasticity. In Revision.<br><br>Schmelzer, N. J., Lieberman, E. J., Gray III, G. T., Bronkhorst, C. A. Thermodynamically consistent porosity-based dynamic ductile damage model. In Preparation.

Presenters

  • Noah J Schmelzer

    University of Wisconsin - Madison

Authors

  • Noah J Schmelzer

    University of Wisconsin - Madison

  • Sam D Dunham

    University of Wisconsin - Madison

  • Hansohl Cho

    KAIST

  • Evan Lieberman

    Los Alamos National Laboratory

  • Nan Chen

    University of Wisconsin - Madison

  • Veronica Anghel

    Los Alamos National Laboratory (LANL)

  • George T Gray III

    Los Alamos National Laboratory

  • Curt A Bronkhorst

    University of Wisconsin - Madison