Data of compressible multi-material flow simulations utilizing an efficient bimaterial Riemann problem solver
Description
The data set is associated with two test cases in the research article: W. Ma, X. Zhao, S. Islam, A. Narkhede, K. Wang, Efficient solution of bimaterial Riemann problems for compressible multi-material flow simulations, Journal of Computational Physics, Volume 493, 2023, 112474, which develops an efficient bimaterial Riemann problem solver that significantly accelerates multi-material flow simulations featuring arbitrary complex equations of state (EOS) and strong discontinuity across a material interface. The first test case is a challenging one-dimensional benchmark problem, with a large density jump (4 orders of magnitude) and drastically different EOS across the material interface. The second test case simulates a pear-shaped cavitation bubble induced by a long-pulse laser. In laboratory experiments using the same type of laser, bubbles of similar shape have been observed. This simulation considers various realistic physical phenomena, including laser radiation, vaporization, non-spherical bubble expansion, and the emission of acoustic and shock waves. Both simulations are performed using the M2C solver, which is a three-dimensional finite volume Navier-Stokes computational fluid dynamics code, utilizing the accelerated bimaterial Riemann solver at material interfaces. Source codes provided in this data set include the M2C solver and a standalone version of the accelerated bimaterial Riemann problem solver. These source codes serve as references for researchers seeking to implement the acceleration algorithms introduced in the related research article. Simulation data provided include fluid pressure, velocity, density, laser radiance and bubble dynamics. The input files to perform the simulations are also provided. Researchers can replicate these simulations and use them as a foundation for exploring a range of related topics, such as laser-induced cavitation, bubble dynamics, and multiphase flow in general.
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Funding
National Science Foundation
CBET-1751487
Office of Naval Research
N00014-19-1-2102
National Institutes of Health
2R01-DK052985-24A1
U.S. Department of Transportation
693JK32250007CAAP