Adapting a Multi-Material ALE with AMR Method for Physics of High-Speed Material Interactions

Peter Yip, Erik Torres, Ioannis Nompelis, Thomas E. Schwartzentruber, Aaron Fisher, David Eder, Alice Koniges

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

High speed flight induces extreme aerothermal loads on a vehicle. As a result, material selection and understanding material response to aerothermal loading is important. The presence of particles in the atmosphere and the potential for a vehicle to fly through precipitation at low altitudes may cause substantial damage to leading edges and control surfaces of high-speed flight vehciles. Computational techniques for modeling the physics of particles and droplets, and their interactions with solids in various flow regimes, are investigated, particularly those that might impact thermal protection systems for aircraft at high velocities. A multi-material fluid based approach for modeling problems in this regime is examined. This method combines Arbitrary Lagrangian Eulerian (ALE) hydrodynamics with Adaptive Mesh Refinement (AMR) and includes an anisotropic stress tensor and multi-zone physics. The method is tested for small particles (4 µm diameter) impacting a material surface at high speeds (500-700 m/s)

Original languageEnglish (US)
Title of host publicationAIAA SciTech Forum 2022
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
ISBN (Print)9781624106316
DOIs
StatePublished - 2022
EventAIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2022 - San Diego, United States
Duration: Jan 3 2022Jan 7 2022

Publication series

NameAIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2022

Conference

ConferenceAIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2022
Country/TerritoryUnited States
CitySan Diego
Period1/3/221/7/22

Bibliographical note

Funding Information:
This application of PISALE is supported by the Office of Naval Research, under ONR MURI Grant #N00014-20-1-2682. The PISALE code also receives funding from the National Science Foundation, Office of Advanced Cyberinfrastructure Grant #2005259 and from U. S. Department of Energy, Office of Science, Fusion Energy Sciences Research Division Grant #DE-SC0021374. This research used resources of the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility operated under Contract No. DE-AC02-05CH11231.

Publisher Copyright:
© 2022, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

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