Numerical simulation of an idealised Richtmyer–Meshkov instability shock tube experiment
The effects of initial conditions on the evolution of the Richtmyer–Meshkov instability (RMI) at early to intermediate times are analysed, using numerical simulations of an idealised version of recent shock tube experiments performed at the University of Arizona (Sewell et al., J. Fluid Mech., vol....
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description | The effects of initial conditions on the evolution of the Richtmyer–Meshkov instability (RMI) at early to intermediate times are analysed, using numerical simulations of an idealised version of recent shock tube experiments performed at the University of Arizona (Sewell et al., J. Fluid Mech., vol. 917, 2021, A41). The experimental results are bracketed by performing both implicit large-eddy simulations of the high-Reynolds-number limit as well as direct numerical simulations (DNS) at Reynolds numbers lower than those observed in the experiments. Various measures of the mixing layer width $h$, known to scale as ${\sim }t^\theta$ at late time, based on both the plane-averaged turbulent kinetic energy and volume fraction profiles are used to explore the effects of initial conditions on $\theta$ and are compared with the experimental results. The decay rate $n$ of the total fluctuating kinetic energy is also used to estimate $\theta$ based on a relationship that assumes self-similar growth of the mixing layer. The estimates for $\theta$ range between 0.44 and 0.52 for each of the broadband perturbations considered and are in good agreement with the experimental results. Decomposing the mixing layer width into separate bubble and spike heights $h_b$ and $h_s$ shows that, while the bubbles and spikes initially grow at different rates, their growth rates $\theta _b$ and $\theta _s$ have equalised by the end of the simulations. Overall, the results demonstrate important differences between broadband and narrowband surface perturbations, as well as persistent effects of finite bandwidth on the growth rate of mixing layers evolving from broadband perturbations. Good agreement is obtained with the experiments for the different quantities considered; however, the results also show that care must be taken when using measurements based on the velocity field to infer properties of the concentration field. |
doi_str_mv | 10.1017/jfm.2023.362 |
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Fluid Mech., vol. 917, 2021, A41). The experimental results are bracketed by performing both implicit large-eddy simulations of the high-Reynolds-number limit as well as direct numerical simulations (DNS) at Reynolds numbers lower than those observed in the experiments. Various measures of the mixing layer width $h$, known to scale as ${\sim }t^\theta$ at late time, based on both the plane-averaged turbulent kinetic energy and volume fraction profiles are used to explore the effects of initial conditions on $\theta$ and are compared with the experimental results. The decay rate $n$ of the total fluctuating kinetic energy is also used to estimate $\theta$ based on a relationship that assumes self-similar growth of the mixing layer. The estimates for $\theta$ range between 0.44 and 0.52 for each of the broadband perturbations considered and are in good agreement with the experimental results. Decomposing the mixing layer width into separate bubble and spike heights $h_b$ and $h_s$ shows that, while the bubbles and spikes initially grow at different rates, their growth rates $\theta _b$ and $\theta _s$ have equalised by the end of the simulations. Overall, the results demonstrate important differences between broadband and narrowband surface perturbations, as well as persistent effects of finite bandwidth on the growth rate of mixing layers evolving from broadband perturbations. Good agreement is obtained with the experiments for the different quantities considered; however, the results also show that care must be taken when using measurements based on the velocity field to infer properties of the concentration field.</description><identifier>ISSN: 0022-1120</identifier><identifier>EISSN: 1469-7645</identifier><identifier>DOI: 10.1017/jfm.2023.362</identifier><language>eng</language><publisher>Cambridge, UK: Cambridge University Press</publisher><subject>Accuracy ; Broadband ; Bubbles ; Decay rate ; Direct numerical simulation ; Experiments ; Fluid flow ; Fluid mechanics ; Growth rate ; High Reynolds number ; Initial conditions ; Interfaces ; JFM Papers ; Kinetic energy ; Large eddy simulation ; Mathematical models ; Mixing layers (fluids) ; Narrowband ; Oceanic eddies ; Perturbation ; Perturbations ; Richtmeyer-Meshkov instability ; Self-similarity ; Simulation ; Stability analysis ; Velocity distribution ; Width</subject><ispartof>Journal of fluid mechanics, 2023-05, Vol.964</ispartof><rights>The Author(s), 2023. Published by Cambridge University Press.</rights><rights>The Author(s), 2023. Published by Cambridge University Press. This work is licensed under the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c303t-aed35cdc0a3c04a4d22c08a7fb4ab6645d347bc36f5fe4852ee804975a3f9cb03</citedby><orcidid>0000-0003-2473-7229 ; 0000-0002-7665-089X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.cambridge.org/core/product/identifier/S0022112023003622/type/journal_article$$EHTML$$P50$$Gcambridge$$Hfree_for_read</linktohtml><link.rule.ids>164,314,776,780,27903,27904,55606</link.rule.ids></links><search><creatorcontrib>Groom, Michael</creatorcontrib><creatorcontrib>Thornber, Ben</creatorcontrib><title>Numerical simulation of an idealised Richtmyer–Meshkov instability shock tube experiment</title><title>Journal of fluid mechanics</title><addtitle>J. Fluid Mech</addtitle><description>The effects of initial conditions on the evolution of the Richtmyer–Meshkov instability (RMI) at early to intermediate times are analysed, using numerical simulations of an idealised version of recent shock tube experiments performed at the University of Arizona (Sewell et al., J. Fluid Mech., vol. 917, 2021, A41). The experimental results are bracketed by performing both implicit large-eddy simulations of the high-Reynolds-number limit as well as direct numerical simulations (DNS) at Reynolds numbers lower than those observed in the experiments. Various measures of the mixing layer width $h$, known to scale as ${\sim }t^\theta$ at late time, based on both the plane-averaged turbulent kinetic energy and volume fraction profiles are used to explore the effects of initial conditions on $\theta$ and are compared with the experimental results. The decay rate $n$ of the total fluctuating kinetic energy is also used to estimate $\theta$ based on a relationship that assumes self-similar growth of the mixing layer. The estimates for $\theta$ range between 0.44 and 0.52 for each of the broadband perturbations considered and are in good agreement with the experimental results. Decomposing the mixing layer width into separate bubble and spike heights $h_b$ and $h_s$ shows that, while the bubbles and spikes initially grow at different rates, their growth rates $\theta _b$ and $\theta _s$ have equalised by the end of the simulations. Overall, the results demonstrate important differences between broadband and narrowband surface perturbations, as well as persistent effects of finite bandwidth on the growth rate of mixing layers evolving from broadband perturbations. Good agreement is obtained with the experiments for the different quantities considered; however, the results also show that care must be taken when using measurements based on the velocity field to infer properties of the concentration field.</description><subject>Accuracy</subject><subject>Broadband</subject><subject>Bubbles</subject><subject>Decay rate</subject><subject>Direct numerical simulation</subject><subject>Experiments</subject><subject>Fluid flow</subject><subject>Fluid mechanics</subject><subject>Growth rate</subject><subject>High Reynolds number</subject><subject>Initial conditions</subject><subject>Interfaces</subject><subject>JFM Papers</subject><subject>Kinetic energy</subject><subject>Large eddy simulation</subject><subject>Mathematical models</subject><subject>Mixing layers (fluids)</subject><subject>Narrowband</subject><subject>Oceanic eddies</subject><subject>Perturbation</subject><subject>Perturbations</subject><subject>Richtmeyer-Meshkov instability</subject><subject>Self-similarity</subject><subject>Simulation</subject><subject>Stability analysis</subject><subject>Velocity distribution</subject><subject>Width</subject><issn>0022-1120</issn><issn>1469-7645</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>IKXGN</sourceid><sourceid>8G5</sourceid><sourceid>BENPR</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNpFkMtKAzEYhYMoWKs7HyDgesY_l7ktpagVqoLoxs2QSf6xaedSJxmxO9_BN_RJTKng6mw-zjl8hJwziBmw7HJVtzEHLmKR8gMyYTItoiyVySGZAHAeMcbhmJw4twJgAopsQl4fxhYHq1VDnW3HRnnbd7SvqeqoNaga69DQJ6uXvt3i8PP1fY9uue4_qO2cV5VtrN9St-z1mvqxQoqfm9DXYudPyVGtGodnfzklLzfXz7N5tHi8vZtdLSItQPhIoRGJNhqU0CCVNJxryFVWV1JVaXhvhMwqLdI6qVHmCUfMQRZZokRd6ArElFzsezdD_z6i8-WqH4cuTJY8Dzp4Koo8UPGe0qqtBmve8B9jUO78lcFfufNXBn_iF62iZg4</recordid><startdate>20230530</startdate><enddate>20230530</enddate><creator>Groom, Michael</creator><creator>Thornber, Ben</creator><general>Cambridge University Press</general><scope>IKXGN</scope><scope>3V.</scope><scope>7TB</scope><scope>7U5</scope><scope>7UA</scope><scope>7XB</scope><scope>88I</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8G5</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H8D</scope><scope>H96</scope><scope>HCIFZ</scope><scope>KR7</scope><scope>L.G</scope><scope>L6V</scope><scope>L7M</scope><scope>M2O</scope><scope>M2P</scope><scope>M7S</scope><scope>MBDVC</scope><scope>P5Z</scope><scope>P62</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>Q9U</scope><scope>S0W</scope><orcidid>https://orcid.org/0000-0003-2473-7229</orcidid><orcidid>https://orcid.org/0000-0002-7665-089X</orcidid></search><sort><creationdate>20230530</creationdate><title>Numerical simulation of an idealised Richtmyer–Meshkov instability shock tube experiment</title><author>Groom, Michael ; Thornber, Ben</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c303t-aed35cdc0a3c04a4d22c08a7fb4ab6645d347bc36f5fe4852ee804975a3f9cb03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Accuracy</topic><topic>Broadband</topic><topic>Bubbles</topic><topic>Decay rate</topic><topic>Direct numerical simulation</topic><topic>Experiments</topic><topic>Fluid flow</topic><topic>Fluid mechanics</topic><topic>Growth rate</topic><topic>High Reynolds number</topic><topic>Initial conditions</topic><topic>Interfaces</topic><topic>JFM Papers</topic><topic>Kinetic energy</topic><topic>Large eddy simulation</topic><topic>Mathematical models</topic><topic>Mixing layers (fluids)</topic><topic>Narrowband</topic><topic>Oceanic eddies</topic><topic>Perturbation</topic><topic>Perturbations</topic><topic>Richtmeyer-Meshkov instability</topic><topic>Self-similarity</topic><topic>Simulation</topic><topic>Stability analysis</topic><topic>Velocity distribution</topic><topic>Width</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Groom, Michael</creatorcontrib><creatorcontrib>Thornber, Ben</creatorcontrib><collection>Cambridge Journals Open Access</collection><collection>ProQuest Central (Corporate)</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Water Resources Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Science Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>Aerospace Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>SciTech Premium Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>ProQuest Engineering Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Research Library</collection><collection>Science Database</collection><collection>Engineering Database</collection><collection>Research Library (Corporate)</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><collection>ProQuest Central Basic</collection><collection>DELNET Engineering & Technology Collection</collection><jtitle>Journal of fluid mechanics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Groom, Michael</au><au>Thornber, Ben</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Numerical simulation of an idealised Richtmyer–Meshkov instability shock tube experiment</atitle><jtitle>Journal of fluid mechanics</jtitle><addtitle>J. Fluid Mech</addtitle><date>2023-05-30</date><risdate>2023</risdate><volume>964</volume><issn>0022-1120</issn><eissn>1469-7645</eissn><abstract>The effects of initial conditions on the evolution of the Richtmyer–Meshkov instability (RMI) at early to intermediate times are analysed, using numerical simulations of an idealised version of recent shock tube experiments performed at the University of Arizona (Sewell et al., J. Fluid Mech., vol. 917, 2021, A41). The experimental results are bracketed by performing both implicit large-eddy simulations of the high-Reynolds-number limit as well as direct numerical simulations (DNS) at Reynolds numbers lower than those observed in the experiments. Various measures of the mixing layer width $h$, known to scale as ${\sim }t^\theta$ at late time, based on both the plane-averaged turbulent kinetic energy and volume fraction profiles are used to explore the effects of initial conditions on $\theta$ and are compared with the experimental results. The decay rate $n$ of the total fluctuating kinetic energy is also used to estimate $\theta$ based on a relationship that assumes self-similar growth of the mixing layer. The estimates for $\theta$ range between 0.44 and 0.52 for each of the broadband perturbations considered and are in good agreement with the experimental results. Decomposing the mixing layer width into separate bubble and spike heights $h_b$ and $h_s$ shows that, while the bubbles and spikes initially grow at different rates, their growth rates $\theta _b$ and $\theta _s$ have equalised by the end of the simulations. Overall, the results demonstrate important differences between broadband and narrowband surface perturbations, as well as persistent effects of finite bandwidth on the growth rate of mixing layers evolving from broadband perturbations. Good agreement is obtained with the experiments for the different quantities considered; however, the results also show that care must be taken when using measurements based on the velocity field to infer properties of the concentration field.</abstract><cop>Cambridge, UK</cop><pub>Cambridge University Press</pub><doi>10.1017/jfm.2023.362</doi><tpages>37</tpages><orcidid>https://orcid.org/0000-0003-2473-7229</orcidid><orcidid>https://orcid.org/0000-0002-7665-089X</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Accuracy Broadband Bubbles Decay rate Direct numerical simulation Experiments Fluid flow Fluid mechanics Growth rate High Reynolds number Initial conditions Interfaces JFM Papers Kinetic energy Large eddy simulation Mathematical models Mixing layers (fluids) Narrowband Oceanic eddies Perturbation Perturbations Richtmeyer-Meshkov instability Self-similarity Simulation Stability analysis Velocity distribution Width |
title | Numerical simulation of an idealised Richtmyer–Meshkov instability shock tube experiment |
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