Adaptive and Compressed Kinetic Simulations

Abstract

This presentation overviews recent progress and future directions at the Air Force Research Laboratory's In-Space Propulsion Branch in developing accelerated, compressed models of rarefied fluid and plasma flows. The talk first describes recent work by Taitano while working at Los Alamos National Laboratory for development of adaptive moving mesh discretization of the Vlasov-Fokker-Planck Equation to be adapted to thruster applications. The talk then describes progress in accelerating solution of the Boltzmann collisional integral through the construction of stabilized Galerkin reduced order models (ROMs) and Neural Network approximations of the collision operator. Finally, streaming nonlinear state-based spatiotemporal variance reduction and the further extension of these concepts towards the construction of transient data-driven compression of kinetic flow information extracted from noisy particle simulations is described.

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Document Details

Document Type
Technical Report
Publication Date
Aug 25, 2021
Accession Number
AD1174387

Entities

People

  • Alex Alekseenko
  • Robert R. S. Martin
  • William Taitano

Organizations

  • Air Force Research Laboratory

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Abstracts
  • Air Force
  • Air Force Research Laboratories
  • Algorithms
  • Applied Mathematics
  • Collisions
  • Compression
  • Compressors
  • Computational Complexity
  • Construction
  • Convolutional Neural Networks
  • Coordinate Systems
  • Equations
  • Experimental Data
  • Fokker Planck Equations
  • Grids
  • Materials
  • Mathematics
  • Military Research
  • Neural Networks
  • Probability
  • Scientific Research
  • Simulations
  • Space Propulsion
  • Steady State
  • Trajectories
  • United States

Fields of Study

  • Physics

Readers

  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Neural Network Machine Learning.
  • Plasma Physics / Magnetohydrodynamics

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy
  • AI & ML - Machine Learning Algorithms
  • Space