39 citations · 99 across the 6 of their papers we have counts for
6 papers
Predicting electrical conductivity in Cu/Nb composites: a combined model-experiment study
Daniel N. Blaschke, Cody Miller, Ryan Mier +6
The generation of high magnetic fields requires materials with high electric conductivity and good strength properties. Cu/Nb composites are considered to be good candidates for th…
Accelerating High-Strain Continuum-Scale Brittle Fracture Simulations with Machine Learning
M. Giselle Fernández-Godino, Nishant Panda, Daniel O'Malley +4
Failure in brittle materials under dynamic loading conditions is a result of the propagation and coalescence of microcracks. Simulating this mechanism at the continuum level is com…
Analytic model of the remobilization of pinned glide dislocations: including dislocation drag from phonon wind
Daniel N. Blaschke, Abigail Hunter, Dean L. Preston
In this paper we discuss the effect of a non-constant dislocation drag coefficient on the very high strain rate regime within an analytic model describing mobile-immobile dislocati…
A 3D phase field dislocation dynamics model for body-centered cubic crystals
Xiaoyao Peng, Nithin Mathew, Irene J. Beyerlein +2
In this work, we present a 3D Phase Field Dislocation Dynamics (PFDD) model for body-centered cubic (BCC) metals. The model formulation is extended to account for the dependence of…
Estimating Failure in Brittle Materials using Graph Theory
M. K. Mudunuru, N. Panda, S. Karra +5
In brittle fracture applications, failure paths, regions where the failure occurs and damage statistics, are some of the key quantities of interest (QoI). High-fidelity models for…
Reduced-Order Modeling through Machine Learning Approaches for Brittle Fracture Applications
A. Hunter, B. A. Moore, M. K. Mudunuru +9
In this paper, five different approaches for reduced-order modeling of brittle fracture in geomaterials, specifically concrete, are presented and compared. Four of the five methods…