Noise Propagation and Uncertainty Quantification in Hybrid Multiphysics Models: Initiation and Reaction Propagation in Energetic Materials

Abstract

Granular energetic materials exhibit complex chaotic behavior due to the coexistence of a wide range of energy scales without scale separation. The main challenges involved in modeling the physical processes leading to initiation of explosive reactions are (i) the lack of a general model for heterogeneous granular media under compaction and (ii) the lack of a reliable multi-scale discrete-to-continuum framework for describing diffusion-advection-reaction processes in heterogeneous particulate media. This heterogeneity plays a major role in stress and heat localization, which is responsible for initiating reactions in energetic materials. In particular, hot-spots emerge as a consequence of visco-plastic pore collapse, intergranular friction, and granular compaction. We developed a number of computation tools for stochastic analysis of granular materials dynamics. These include a continuum-discrete model of heat dissipation/diffusion and a continuum-discrete model of compaction of a granular material with macro-pores. We have also proposed a class of randomly fluctuating macroscopic equations of motion for granular materials and powders.

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Document Details

Document Type
Technical Report
Publication Date
May 23, 2016
Accession Number
AD1010617

Entities

People

  • Daniel M. Tartakovsky

Organizations

  • University of California, San Diego

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force Research Laboratories
  • Algorithms
  • Brownian Motion
  • Chemical Reactions
  • Computational Science
  • Contracts
  • Differential Equations
  • Electronic Mail
  • Energetic Materials
  • Equations
  • Equations Of Motion
  • Granular Materials
  • Hybrid Simulations
  • Intellectual Property
  • Materials
  • Particles
  • Simulations

Readers

  • Combustion Dynamics and Shock Wave Physics.
  • Computational Fluid Dynamics (CFD)
  • Mechanical Engineering/Mechanics of Materials.

Technology Areas

  • AI & ML