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The influence and a direct judgement method of the flow state in supercritical CO2 dry gas seal
The supercritical carbon dioxide (SCO 2 ) Brayton cycle system is an energy conversion system with great potential, and its efficiency can be improved significantly by using low-leakage dry gas seals in SCO 2 compressors and gas turbines. However, the high-pressure and high-speed conditions of a SCO...
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Published in: | Journal of the Brazilian Society of Mechanical Sciences and Engineering 2021-11, Vol.43 (11), Article 486 |
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container_title | Journal of the Brazilian Society of Mechanical Sciences and Engineering |
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creator | Zhang, Cong Jiang, Jin-bo Peng, Xu-dong Meng, Xiang-kai Li, Ji-yun |
description | The supercritical carbon dioxide (SCO
2
) Brayton cycle system is an energy conversion system with great potential, and its efficiency can be improved significantly by using low-leakage dry gas seals in SCO
2
compressors and gas turbines. However, the high-pressure and high-speed conditions of a SCO
2
dry gas seal make the impact of turbulence not negligible. In this paper, the influences of flow state on flow field distribution and sealing performance of a SCO
2
dry gas seal are studied, the criteria for determining the overall flow state into the sealing gap are proposed. Explicit expressions of the flow factor for flow state determination are obtained based on the artificial neural network algorithm. The results show that turbulent flow is easy to occur in a SCO
2
dry gas seal, leading to a remarkable error in predicting sealing performance using a laminar flow model. When employing a laminar flow model, there is a large error on opening force in the transition regions between turbulent and transitional flows, and a large error on leakage rate at high inlet pressure and close to the critical temperature compared to those obtained by using a turbulent flow model. In addition, the flow state judgment method proposed in this paper can accurately determine the overall flow state of a SCO
2
dry gas seal under different operating conditions. |
doi_str_mv | 10.1007/s40430-021-03211-1 |
format | article |
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2
) Brayton cycle system is an energy conversion system with great potential, and its efficiency can be improved significantly by using low-leakage dry gas seals in SCO
2
compressors and gas turbines. However, the high-pressure and high-speed conditions of a SCO
2
dry gas seal make the impact of turbulence not negligible. In this paper, the influences of flow state on flow field distribution and sealing performance of a SCO
2
dry gas seal are studied, the criteria for determining the overall flow state into the sealing gap are proposed. Explicit expressions of the flow factor for flow state determination are obtained based on the artificial neural network algorithm. The results show that turbulent flow is easy to occur in a SCO
2
dry gas seal, leading to a remarkable error in predicting sealing performance using a laminar flow model. When employing a laminar flow model, there is a large error on opening force in the transition regions between turbulent and transitional flows, and a large error on leakage rate at high inlet pressure and close to the critical temperature compared to those obtained by using a turbulent flow model. In addition, the flow state judgment method proposed in this paper can accurately determine the overall flow state of a SCO
2
dry gas seal under different operating conditions.</description><identifier>ISSN: 1678-5878</identifier><identifier>EISSN: 1806-3691</identifier><identifier>DOI: 10.1007/s40430-021-03211-1</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Algorithms ; Artificial neural networks ; Brayton cycle ; Carbon dioxide ; Compressors ; Critical temperature ; Energy conversion ; Engineering ; Errors ; Fluid dynamics ; Gas seals ; Gas turbines ; Inlet pressure ; Laminar flow ; Leakage ; Mechanical Engineering ; Performance prediction ; Sealing ; Technical Paper ; Turbulence ; Turbulent flow</subject><ispartof>Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2021-11, Vol.43 (11), Article 486</ispartof><rights>The Brazilian Society of Mechanical Sciences and Engineering 2021</rights><rights>The Brazilian Society of Mechanical Sciences and Engineering 2021.</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c319t-ba90d21b665280c3e88b23c9b612554dca49509ebcebec50519a5662d720ce9e3</citedby><cites>FETCH-LOGICAL-c319t-ba90d21b665280c3e88b23c9b612554dca49509ebcebec50519a5662d720ce9e3</cites><orcidid>0000-0002-6158-1713</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Zhang, Cong</creatorcontrib><creatorcontrib>Jiang, Jin-bo</creatorcontrib><creatorcontrib>Peng, Xu-dong</creatorcontrib><creatorcontrib>Meng, Xiang-kai</creatorcontrib><creatorcontrib>Li, Ji-yun</creatorcontrib><title>The influence and a direct judgement method of the flow state in supercritical CO2 dry gas seal</title><title>Journal of the Brazilian Society of Mechanical Sciences and Engineering</title><addtitle>J Braz. Soc. Mech. Sci. Eng</addtitle><description>The supercritical carbon dioxide (SCO
2
) Brayton cycle system is an energy conversion system with great potential, and its efficiency can be improved significantly by using low-leakage dry gas seals in SCO
2
compressors and gas turbines. However, the high-pressure and high-speed conditions of a SCO
2
dry gas seal make the impact of turbulence not negligible. In this paper, the influences of flow state on flow field distribution and sealing performance of a SCO
2
dry gas seal are studied, the criteria for determining the overall flow state into the sealing gap are proposed. Explicit expressions of the flow factor for flow state determination are obtained based on the artificial neural network algorithm. The results show that turbulent flow is easy to occur in a SCO
2
dry gas seal, leading to a remarkable error in predicting sealing performance using a laminar flow model. When employing a laminar flow model, there is a large error on opening force in the transition regions between turbulent and transitional flows, and a large error on leakage rate at high inlet pressure and close to the critical temperature compared to those obtained by using a turbulent flow model. In addition, the flow state judgment method proposed in this paper can accurately determine the overall flow state of a SCO
2
dry gas seal under different operating conditions.</description><subject>Algorithms</subject><subject>Artificial neural networks</subject><subject>Brayton cycle</subject><subject>Carbon dioxide</subject><subject>Compressors</subject><subject>Critical temperature</subject><subject>Energy conversion</subject><subject>Engineering</subject><subject>Errors</subject><subject>Fluid dynamics</subject><subject>Gas seals</subject><subject>Gas turbines</subject><subject>Inlet pressure</subject><subject>Laminar flow</subject><subject>Leakage</subject><subject>Mechanical Engineering</subject><subject>Performance prediction</subject><subject>Sealing</subject><subject>Technical Paper</subject><subject>Turbulence</subject><subject>Turbulent flow</subject><issn>1678-5878</issn><issn>1806-3691</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNp9kEtLAzEURoMoWKt_wFXAdTSPSSZZSvEFhW7qOmSSO-2U6UxNMkj_vdEK7lzlLs75AgehW0bvGaX1Q6poJSihnBEqOGOEnaEZ01QRoQw7L7eqNZG61pfoKqUdLZRUcobsegu4G9p-gsEDdkPADocugs94N4UN7GHIeA95OwY8tjgXvO3HT5yyy98mTtMBoo9d7rzr8WLFcYhHvHEJJ3D9NbpoXZ_g5vedo_fnp_XilSxXL2-LxyXxgplMGmdo4KxRSnJNvQCtGy68aRTjUlbBu8pIaqDx0ICXVDLjpFI81Jx6MCDm6O60e4jjxwQp2904xaF8abnUtKxypQvFT5SPY0oRWnuI3d7Fo2XUfoe0p5C2hLQ_IS0rkjhJqcDDBuLf9D_WF8vsdS0</recordid><startdate>20211101</startdate><enddate>20211101</enddate><creator>Zhang, Cong</creator><creator>Jiang, Jin-bo</creator><creator>Peng, Xu-dong</creator><creator>Meng, Xiang-kai</creator><creator>Li, Ji-yun</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><orcidid>https://orcid.org/0000-0002-6158-1713</orcidid></search><sort><creationdate>20211101</creationdate><title>The influence and a direct judgement method of the flow state in supercritical CO2 dry gas seal</title><author>Zhang, Cong ; Jiang, Jin-bo ; Peng, Xu-dong ; Meng, Xiang-kai ; Li, Ji-yun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c319t-ba90d21b665280c3e88b23c9b612554dca49509ebcebec50519a5662d720ce9e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Algorithms</topic><topic>Artificial neural networks</topic><topic>Brayton cycle</topic><topic>Carbon dioxide</topic><topic>Compressors</topic><topic>Critical temperature</topic><topic>Energy conversion</topic><topic>Engineering</topic><topic>Errors</topic><topic>Fluid dynamics</topic><topic>Gas seals</topic><topic>Gas turbines</topic><topic>Inlet pressure</topic><topic>Laminar flow</topic><topic>Leakage</topic><topic>Mechanical Engineering</topic><topic>Performance prediction</topic><topic>Sealing</topic><topic>Technical Paper</topic><topic>Turbulence</topic><topic>Turbulent flow</topic><toplevel>online_resources</toplevel><creatorcontrib>Zhang, Cong</creatorcontrib><creatorcontrib>Jiang, Jin-bo</creatorcontrib><creatorcontrib>Peng, Xu-dong</creatorcontrib><creatorcontrib>Meng, Xiang-kai</creatorcontrib><creatorcontrib>Li, Ji-yun</creatorcontrib><collection>CrossRef</collection><jtitle>Journal of the Brazilian Society of Mechanical Sciences and Engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhang, Cong</au><au>Jiang, Jin-bo</au><au>Peng, Xu-dong</au><au>Meng, Xiang-kai</au><au>Li, Ji-yun</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The influence and a direct judgement method of the flow state in supercritical CO2 dry gas seal</atitle><jtitle>Journal of the Brazilian Society of Mechanical Sciences and Engineering</jtitle><stitle>J Braz. Soc. Mech. Sci. Eng</stitle><date>2021-11-01</date><risdate>2021</risdate><volume>43</volume><issue>11</issue><artnum>486</artnum><issn>1678-5878</issn><eissn>1806-3691</eissn><abstract>The supercritical carbon dioxide (SCO
2
) Brayton cycle system is an energy conversion system with great potential, and its efficiency can be improved significantly by using low-leakage dry gas seals in SCO
2
compressors and gas turbines. However, the high-pressure and high-speed conditions of a SCO
2
dry gas seal make the impact of turbulence not negligible. In this paper, the influences of flow state on flow field distribution and sealing performance of a SCO
2
dry gas seal are studied, the criteria for determining the overall flow state into the sealing gap are proposed. Explicit expressions of the flow factor for flow state determination are obtained based on the artificial neural network algorithm. The results show that turbulent flow is easy to occur in a SCO
2
dry gas seal, leading to a remarkable error in predicting sealing performance using a laminar flow model. When employing a laminar flow model, there is a large error on opening force in the transition regions between turbulent and transitional flows, and a large error on leakage rate at high inlet pressure and close to the critical temperature compared to those obtained by using a turbulent flow model. In addition, the flow state judgment method proposed in this paper can accurately determine the overall flow state of a SCO
2
dry gas seal under different operating conditions.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s40430-021-03211-1</doi><orcidid>https://orcid.org/0000-0002-6158-1713</orcidid></addata></record> |
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subjects | Algorithms Artificial neural networks Brayton cycle Carbon dioxide Compressors Critical temperature Energy conversion Engineering Errors Fluid dynamics Gas seals Gas turbines Inlet pressure Laminar flow Leakage Mechanical Engineering Performance prediction Sealing Technical Paper Turbulence Turbulent flow |
title | The influence and a direct judgement method of the flow state in supercritical CO2 dry gas seal |
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