High-Resolution Simulations of Richtmyer-Meshkov Instability and variable-density turbulence induced by reshock
ORAL
Abstract
The Richtmyer-Meshkov instability (RMI) and its transition to turbulence appear in many astrophysical events and engineering applications, such as supernova remnant formation, supersonic combustion, and inertial confinement fusion. In this talk, a multi-mode RMI problem with the variable-density turbulence induced by reshock is studied using high-resolution Navier-Stokes simulations, where the highest resolution run has cell counts exceeding 4.5 billion and was computed on the 20 Petaflop machine Trinity of Los Alamos National Laboratory - one of the largest supercomputers in the world. In these simulations, adaptive mesh refinement and high-order shock-capturing methods are employed to prevent excessive use of grid cells while the shocks and turbulence are well captured. Direct numerical simulation (DNS)-like results are obtained before reshock and the turbulent mixing layer is highly resolved after reshock in the highest resolution simulation. Transport equations of second moment turbulent quantities are studied to analyze the dominant mechanisms governing the turbulence and mixing before and after the shocks' interactions with the material interface for Reynolds-averaged Navier-Stokes (RANS) modeling. Budgets of the large-scale turbulent quantities computed with spatially filtered fields after reshock are further studied and the effects of subfilter-scale stress on the transport of large-scale quantities in scale-resolving simulations are also examined.
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Publication: 1. Wong, Man Long, et al. "Analysis of second moments and their budgets for Richtmyer-Meshkov instability and variable-density turbulence induced by reshock." Physical Review Fluids 7.4 (2022): 044602.<br>2. Wong, Man Long, Daniel Livescu, and Sanjiva K. Lele. "High-resolution Navier-Stokes simulations of Richtmyer-Meshkov instability with reshock." Physical Review Fluids 4.10 (2019): 104609.
Presenters
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Man Long Wong
Stanford University/Los Alamos National Laboratory
Authors
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Man Long Wong
Stanford University/Los Alamos National Laboratory
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Jon R Baltzer
Los Alamos Natl Lab
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Sanjiva K Lele
Stanford University
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Daniel Livescu
LANL