3D Visualization Equipment for Big Data Analysis of Microstructural Evolution Under Dynamic Loading Conditions

Abstract

Major Goals: The PIs current ARO program (Grant: W911NF-14-1-0257) aims to develop microstructure-failure-strength relationships at mesoscales in lightweight metallic systems under dynamic loading conditions and bridge the gap between atomistic and continuum simulations. To achieve this goal, the PIs novel mesoscale modeling method called quasi-coarse-grained-dynamics (QCGD) is developed by the PI that extends the time and length scale capabilities of molecular dynamics (MD) simulations to the mesoscales. While these simulations allow the investigation of the evolution of temperature, pressure during deformation and failure, the investigation of the micromechanisms and the evolution of defects/damage, the interaction of defects/damage and the evolution of microstructure is still a challenge due to the massively large data sets generated in these simulations. The current visualization capabilities available to the PI and the remote access of data (currently ~100 TB) on DoD archives limits the analysis of these snapshots to investigate the micromechanisms. The detailed analysis of this Big Data is the current bottleneck in the generation of the scaling relationships and the investigation of the mechanisms for nucleation, evolution and interactions of defect and damage structures that define the deformation and failure behavior of these lightweight metallic materials under dynamic loading conditions. The requirements are the ability to directly visualize temporal evolution of microstructure comprising of snapshots generated using MD and QCGD simulations. Such a visualization is very demanding in terms of memory and processor requirements due to the large data sets comprising of trajectories of systems comprising of tens to hundreds of millions of atoms. The DURIP award provides the computational infrastructure needed to meet this challenge.

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Document Details

Document Type
Technical Report
Publication Date
Oct 18, 2018
Accession Number
AD1082988

Entities

People

  • Avinash Mohan Dongare

Organizations

  • University of Connecticut

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Classification
  • Contracts
  • Machines
  • Mechanical Equipment
  • Military Research
  • Monitoring
  • Organizational Structure
  • Personal Information Managers
  • Positioning Devices (Machinery)
  • Security
  • Standards
  • Triangles
  • Visualizations

Readers

  • Distributed Systems and Data Platform Development
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers
  • Structural Health Monitoring of Composite Structures.