2021
DOI: 10.1103/physrevfluids.6.104001
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Contribution of Mach number to the evolution of the Richtmyer-Meshkov instability induced by a shock-accelerated square light bubble

Abstract: Contribution of Mach number to the evolution of the Richtmyer-Meshkov instability induced by a shock-accelerated square light bubble Singh, Satyvir 2021 Singh, S. (2021). Contribution of Mach number to the evolution of the Richtmyer-Meshkov instability induced by a shock-accelerated square light bubble. Physical Review Fluids,

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Cited by 17 publications
(2 citation statements)
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“…Drawing from these investigations, Singh [49] conducted computational simulations to scrutinize the effects of the Atwood numbers on RM phenomena within square bubbles containing diverse gases. Following this, Singh and collaborators [50,51] examined how varying shock Mach numbers impact RM phenomena within square bubbles containing light/heavy gases. Subsequent research by Singh and colleagues [52,53] provided a comparative numerical study of RM phenomena between shock-driven square and rectangular bubbles containing light gases.…”
Section: Introductionmentioning
confidence: 99%
“…Drawing from these investigations, Singh [49] conducted computational simulations to scrutinize the effects of the Atwood numbers on RM phenomena within square bubbles containing diverse gases. Following this, Singh and collaborators [50,51] examined how varying shock Mach numbers impact RM phenomena within square bubbles containing light/heavy gases. Subsequent research by Singh and colleagues [52,53] provided a comparative numerical study of RM phenomena between shock-driven square and rectangular bubbles containing light gases.…”
Section: Introductionmentioning
confidence: 99%
“…The DG approaches integrate the advantages of modern CFD methods, including Finite Element (FE) and Finite Volume (FV) methods, and have been effectively utilized to a broad spectrum of scientific problems, including computational fluid dynamics, plasma physics, quantum physics, biological sciences, and many others. (Le et al 2014;Raj et al, 2017;Singh and Myong, 2017;Singh, 2018;Chourushi et al, 2020;Singh, 2021a;Singh, 2021b;Singh, 2021c). The DG approaches have several key characteristics that make them interesting for usage in applications.…”
Section: Introductionmentioning
confidence: 99%