A mathematical‐boundary‐recognition domain‐decomposition Lattice Boltzmann method combined with large eddy simulation applied to airfoil aeroacoustics simulation
Being a direct computational aeroacoustics method, Lattice Boltzmann method (LBM) has great potential and broad application perspective in the field of numerical simulation of aerodynamic noise due to its low dispersion and low dissipation. A series of numerical algorithms and the related improvemen...
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Veröffentlicht in: | International journal for numerical methods in fluids 2024-07, Vol.96 (7), p.1250-1275 |
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description | Being a direct computational aeroacoustics method, Lattice Boltzmann method (LBM) has great potential and broad application perspective in the field of numerical simulation of aerodynamic noise due to its low dispersion and low dissipation. A series of numerical algorithms and the related improvements based on the standard LBM method are proposed and developed in this paper to adapt to the airfoil noise calculation with complex grid at middle‐high Reynolds number. First, a new mathematical‐boundary‐recognition algorithm based on Green's formula is proposed to deal with complex curved geometric models, which is validated by three‐element airfoil 30P30N benchmark. Then, in order to reduce grid redundancy and improve computing efficiency, the grid refinement technique of domain decomposition model (DDM) is adopted and also improved, which is verified by calculating the flow and sound fields around 2D and 3D cylinders at Reynolds number equal to 90,000. Finally, three different LES turbulence models are combined with the standard MRT‐LBM method, where different finite difference schemes are used to solve Reynolds stress tensor which is different from the traditional one. Through the direct acoustic numerical simulation of NACA0012 airfoil at Reynolds number equal to 200,000, the effects of Smagorinsky models and Wall‐adapting local eddy‐viscosity (WALE) model on aerodynamic noise prediction are compared and analyzed. Overall, the proposed methodology is shown to be appropriate for predicting the aerodynamic noise at low Mach number and can successfully simulate the generation and propagation of far field acoustics. |
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A series of numerical algorithms and the related improvements based on the standard LBM method are proposed and developed in this paper to adapt to the airfoil noise calculation with complex grid at middle‐high Reynolds number. First, a new mathematical‐boundary‐recognition algorithm based on Green's formula is proposed to deal with complex curved geometric models, which is validated by three‐element airfoil 30P30N benchmark. Then, in order to reduce grid redundancy and improve computing efficiency, the grid refinement technique of domain decomposition model (DDM) is adopted and also improved, which is verified by calculating the flow and sound fields around 2D and 3D cylinders at Reynolds number equal to 90,000. Finally, three different LES turbulence models are combined with the standard MRT‐LBM method, where different finite difference schemes are used to solve Reynolds stress tensor which is different from the traditional one. Through the direct acoustic numerical simulation of NACA0012 airfoil at Reynolds number equal to 200,000, the effects of Smagorinsky models and Wall‐adapting local eddy‐viscosity (WALE) model on aerodynamic noise prediction are compared and analyzed. Overall, the proposed methodology is shown to be appropriate for predicting the aerodynamic noise at low Mach number and can successfully simulate the generation and propagation of far field acoustics.</description><identifier>ISSN: 0271-2091</identifier><identifier>EISSN: 1097-0363</identifier><identifier>DOI: 10.1002/fld.5287</identifier><language>eng</language><publisher>Bognor Regis: Wiley Subscription Services, Inc</publisher><subject>Acoustics ; Aerodynamic noise ; Airfoils ; Algorithms ; Computational aeroacoustics ; Computational fluid dynamics ; Computer simulation ; Decomposition ; Domain decomposition methods ; Finite difference method ; Fluid flow ; Grid refinement (mathematics) ; High Reynolds number ; Large eddy simulation ; Mach number ; Mathematical analysis ; Mathematical models ; Noise ; Noise prediction ; Recognition ; Redundancy ; Reynolds number ; Reynolds stress ; Simulation ; Sound fields ; Tensors ; Turbulence ; Turbulence models ; Viscosity ; Vortices</subject><ispartof>International journal for numerical methods in fluids, 2024-07, Vol.96 (7), p.1250-1275</ispartof><rights>2024 John Wiley & Sons, Ltd.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c216t-3e90bca35f132f106e19d2449625153f20cb7363eab74ecc2c55d323708fe0c73</cites><orcidid>0000-0002-3177-4901</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids></links><search><creatorcontrib>Jia, Qi</creatorcontrib><creatorcontrib>Zhang, Jin</creatorcontrib><creatorcontrib>Liang, Wen‐zhi</creatorcontrib><creatorcontrib>Liu, Pei‐qing</creatorcontrib><creatorcontrib>Qu, Qiu‐lin</creatorcontrib><title>A mathematical‐boundary‐recognition domain‐decomposition Lattice Boltzmann method combined with large eddy simulation applied to airfoil aeroacoustics simulation</title><title>International journal for numerical methods in fluids</title><description>Being a direct computational aeroacoustics method, Lattice Boltzmann method (LBM) has great potential and broad application perspective in the field of numerical simulation of aerodynamic noise due to its low dispersion and low dissipation. A series of numerical algorithms and the related improvements based on the standard LBM method are proposed and developed in this paper to adapt to the airfoil noise calculation with complex grid at middle‐high Reynolds number. First, a new mathematical‐boundary‐recognition algorithm based on Green's formula is proposed to deal with complex curved geometric models, which is validated by three‐element airfoil 30P30N benchmark. Then, in order to reduce grid redundancy and improve computing efficiency, the grid refinement technique of domain decomposition model (DDM) is adopted and also improved, which is verified by calculating the flow and sound fields around 2D and 3D cylinders at Reynolds number equal to 90,000. Finally, three different LES turbulence models are combined with the standard MRT‐LBM method, where different finite difference schemes are used to solve Reynolds stress tensor which is different from the traditional one. Through the direct acoustic numerical simulation of NACA0012 airfoil at Reynolds number equal to 200,000, the effects of Smagorinsky models and Wall‐adapting local eddy‐viscosity (WALE) model on aerodynamic noise prediction are compared and analyzed. Overall, the proposed methodology is shown to be appropriate for predicting the aerodynamic noise at low Mach number and can successfully simulate the generation and propagation of far field acoustics.</description><subject>Acoustics</subject><subject>Aerodynamic noise</subject><subject>Airfoils</subject><subject>Algorithms</subject><subject>Computational aeroacoustics</subject><subject>Computational fluid dynamics</subject><subject>Computer simulation</subject><subject>Decomposition</subject><subject>Domain decomposition methods</subject><subject>Finite difference method</subject><subject>Fluid flow</subject><subject>Grid refinement (mathematics)</subject><subject>High Reynolds number</subject><subject>Large eddy simulation</subject><subject>Mach number</subject><subject>Mathematical analysis</subject><subject>Mathematical models</subject><subject>Noise</subject><subject>Noise prediction</subject><subject>Recognition</subject><subject>Redundancy</subject><subject>Reynolds number</subject><subject>Reynolds stress</subject><subject>Simulation</subject><subject>Sound fields</subject><subject>Tensors</subject><subject>Turbulence</subject><subject>Turbulence models</subject><subject>Viscosity</subject><subject>Vortices</subject><issn>0271-2091</issn><issn>1097-0363</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNpNkc9KAzEQxoMoWKvgIwS8eNk6SfZP91iL_6DgRc9LNsm2KdlkTbKInnwE38L38klMrQcvM8PHb2bg-xA6JzAjAPSqM3JW0Hl1gCYE6ioDVrJDNAFakYxCTY7RSQhbAKjpnE3Q1wL3PG5UKlpw8_3x2brRSu7f0uiVcGuro3YWS9dzbZMok9gPLuzlFY9pUeFrZ-J7z63FvYobJ3GCWm2VxK86brDhfq2wkvINB92Phv8u82EwOiHRYa5957TBXHnHhRtDuhr-safoqOMmqLO_PkXPtzdPy_ts9Xj3sFysMkFJGTOmamgFZ0VHGO0IlIrUkuZ5XdKCFKyjINoqOaJ4W-VKCCqKQjLKKph3CkTFpuhif3fw7mVUITZbN3qbXjYMypwVOw8TdbmnhHcheNU1g9d9Mq0h0OxiaFIMzS4G9gN5DIJp</recordid><startdate>20240701</startdate><enddate>20240701</enddate><creator>Jia, Qi</creator><creator>Zhang, Jin</creator><creator>Liang, Wen‐zhi</creator><creator>Liu, Pei‐qing</creator><creator>Qu, Qiu‐lin</creator><general>Wiley Subscription Services, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7SC</scope><scope>7TB</scope><scope>7U5</scope><scope>7UA</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>FR3</scope><scope>H8D</scope><scope>H96</scope><scope>JQ2</scope><scope>KR7</scope><scope>L.G</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0002-3177-4901</orcidid></search><sort><creationdate>20240701</creationdate><title>A mathematical‐boundary‐recognition domain‐decomposition Lattice Boltzmann method combined with large eddy simulation applied to airfoil aeroacoustics simulation</title><author>Jia, Qi ; Zhang, Jin ; Liang, Wen‐zhi ; Liu, Pei‐qing ; Qu, Qiu‐lin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c216t-3e90bca35f132f106e19d2449625153f20cb7363eab74ecc2c55d323708fe0c73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Acoustics</topic><topic>Aerodynamic noise</topic><topic>Airfoils</topic><topic>Algorithms</topic><topic>Computational aeroacoustics</topic><topic>Computational fluid dynamics</topic><topic>Computer simulation</topic><topic>Decomposition</topic><topic>Domain decomposition methods</topic><topic>Finite difference method</topic><topic>Fluid flow</topic><topic>Grid refinement (mathematics)</topic><topic>High Reynolds number</topic><topic>Large eddy simulation</topic><topic>Mach number</topic><topic>Mathematical analysis</topic><topic>Mathematical models</topic><topic>Noise</topic><topic>Noise prediction</topic><topic>Recognition</topic><topic>Redundancy</topic><topic>Reynolds number</topic><topic>Reynolds stress</topic><topic>Simulation</topic><topic>Sound fields</topic><topic>Tensors</topic><topic>Turbulence</topic><topic>Turbulence models</topic><topic>Viscosity</topic><topic>Vortices</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Jia, Qi</creatorcontrib><creatorcontrib>Zhang, Jin</creatorcontrib><creatorcontrib>Liang, Wen‐zhi</creatorcontrib><creatorcontrib>Liu, Pei‐qing</creatorcontrib><creatorcontrib>Qu, Qiu‐lin</creatorcontrib><collection>CrossRef</collection><collection>Aqualine</collection><collection>Computer and Information Systems Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>International journal for numerical methods in fluids</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Jia, Qi</au><au>Zhang, Jin</au><au>Liang, Wen‐zhi</au><au>Liu, Pei‐qing</au><au>Qu, Qiu‐lin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A mathematical‐boundary‐recognition domain‐decomposition Lattice Boltzmann method combined with large eddy simulation applied to airfoil aeroacoustics simulation</atitle><jtitle>International journal for numerical methods in fluids</jtitle><date>2024-07-01</date><risdate>2024</risdate><volume>96</volume><issue>7</issue><spage>1250</spage><epage>1275</epage><pages>1250-1275</pages><issn>0271-2091</issn><eissn>1097-0363</eissn><abstract>Being a direct computational aeroacoustics method, Lattice Boltzmann method (LBM) has great potential and broad application perspective in the field of numerical simulation of aerodynamic noise due to its low dispersion and low dissipation. A series of numerical algorithms and the related improvements based on the standard LBM method are proposed and developed in this paper to adapt to the airfoil noise calculation with complex grid at middle‐high Reynolds number. First, a new mathematical‐boundary‐recognition algorithm based on Green's formula is proposed to deal with complex curved geometric models, which is validated by three‐element airfoil 30P30N benchmark. Then, in order to reduce grid redundancy and improve computing efficiency, the grid refinement technique of domain decomposition model (DDM) is adopted and also improved, which is verified by calculating the flow and sound fields around 2D and 3D cylinders at Reynolds number equal to 90,000. Finally, three different LES turbulence models are combined with the standard MRT‐LBM method, where different finite difference schemes are used to solve Reynolds stress tensor which is different from the traditional one. Through the direct acoustic numerical simulation of NACA0012 airfoil at Reynolds number equal to 200,000, the effects of Smagorinsky models and Wall‐adapting local eddy‐viscosity (WALE) model on aerodynamic noise prediction are compared and analyzed. Overall, the proposed methodology is shown to be appropriate for predicting the aerodynamic noise at low Mach number and can successfully simulate the generation and propagation of far field acoustics.</abstract><cop>Bognor Regis</cop><pub>Wiley Subscription Services, Inc</pub><doi>10.1002/fld.5287</doi><tpages>26</tpages><orcidid>https://orcid.org/0000-0002-3177-4901</orcidid></addata></record> |
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subjects | Acoustics Aerodynamic noise Airfoils Algorithms Computational aeroacoustics Computational fluid dynamics Computer simulation Decomposition Domain decomposition methods Finite difference method Fluid flow Grid refinement (mathematics) High Reynolds number Large eddy simulation Mach number Mathematical analysis Mathematical models Noise Noise prediction Recognition Redundancy Reynolds number Reynolds stress Simulation Sound fields Tensors Turbulence Turbulence models Viscosity Vortices |
title | A mathematical‐boundary‐recognition domain‐decomposition Lattice Boltzmann method combined with large eddy simulation applied to airfoil aeroacoustics simulation |
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