Prediction for pressure drop and heat transfer coefficient of porous metal fins

In order to evaluate the cooling performance of the porous metal fins, both the friction factor and heat transfer coefficient were taken into account. In this study, we compared six porous metal fins and four kinds of heat exchangers made of porous material. Moreover, we proposed a new model which p...
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Autor*in:	Yoshihiro KONDO [verfasserIn] Hiroyuki KOSHITA [verfasserIn]

Format:	E-Artikel
Sprache:	Japanisch

Erschienen:	2016

Schlagwörter:	porous metal fin heat exchanger pressure drop heat transfer coefficient permeability

Übergeordnetes Werk:	In: Nihon Kikai Gakkai ronbunshu - The Japan Society of Mechanical Engineers, 2022, 82(2016), 844, Seite 16-00173-16-00173
Übergeordnetes Werk:	volume:82 ; year:2016 ; number:844 ; pages:16-00173-16-00173

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1299/transjsme.16-00173

Katalog-ID:	DOAJ08595893X

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520			\|a In order to evaluate the cooling performance of the porous metal fins, both the friction factor and heat transfer coefficient were taken into account. In this study, we compared six porous metal fins and four kinds of heat exchangers made of porous material. Moreover, we proposed a new model which predicts the cooling performance of the porous metal fins. Friction loss factor of porous metal fins became predictable in less than ±10% error by using effective cross-sectional flow area and Ergun coefficient in Forchheimer-extended Darcy model. Heat transfer coefficient of porous metal fins can be predicted within an error of 10% by our model. The predictive model has two assumptions. One is that the perimeter in the porous metal fin per cross-sectional area of porous metal fin is independent of the heights of fins and number of porous cells. Another assumption is that heat transfer coefficient of porous metal fin is also independent of the heights of fins and number of porous cells as long as the velocity is same.
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allfields	10.1299/transjsme.16-00173 doi (DE-627)DOAJ08595893X (DE-599)DOAJe9f0ba115c9c456b9f773187076f088e DE-627 ger DE-627 rakwb jpn TJ1-1570 TA213-215 Yoshihiro KONDO verfasserin aut Prediction for pressure drop and heat transfer coefficient of porous metal fins 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In order to evaluate the cooling performance of the porous metal fins, both the friction factor and heat transfer coefficient were taken into account. In this study, we compared six porous metal fins and four kinds of heat exchangers made of porous material. Moreover, we proposed a new model which predicts the cooling performance of the porous metal fins. Friction loss factor of porous metal fins became predictable in less than ±10% error by using effective cross-sectional flow area and Ergun coefficient in Forchheimer-extended Darcy model. Heat transfer coefficient of porous metal fins can be predicted within an error of 10% by our model. The predictive model has two assumptions. One is that the perimeter in the porous metal fin per cross-sectional area of porous metal fin is independent of the heights of fins and number of porous cells. Another assumption is that heat transfer coefficient of porous metal fin is also independent of the heights of fins and number of porous cells as long as the velocity is same. porous metal fin heat exchanger pressure drop heat transfer coefficient permeability Mechanical engineering and machinery Engineering machinery, tools, and implements Hiroyuki KOSHITA verfasserin aut In Nihon Kikai Gakkai ronbunshu The Japan Society of Mechanical Engineers, 2022 82(2016), 844, Seite 16-00173-16-00173 (DE-627)1028882408 21879761 nnns volume:82 year:2016 number:844 pages:16-00173-16-00173 https://doi.org/10.1299/transjsme.16-00173 kostenfrei https://doaj.org/article/e9f0ba115c9c456b9f773187076f088e kostenfrei https://www.jstage.jst.go.jp/article/transjsme/82/844/82_16-00173/_pdf/-char/en kostenfrei https://doaj.org/toc/2187-9761 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 82 2016 844 16-00173-16-00173
spelling	10.1299/transjsme.16-00173 doi (DE-627)DOAJ08595893X (DE-599)DOAJe9f0ba115c9c456b9f773187076f088e DE-627 ger DE-627 rakwb jpn TJ1-1570 TA213-215 Yoshihiro KONDO verfasserin aut Prediction for pressure drop and heat transfer coefficient of porous metal fins 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In order to evaluate the cooling performance of the porous metal fins, both the friction factor and heat transfer coefficient were taken into account. In this study, we compared six porous metal fins and four kinds of heat exchangers made of porous material. Moreover, we proposed a new model which predicts the cooling performance of the porous metal fins. Friction loss factor of porous metal fins became predictable in less than ±10% error by using effective cross-sectional flow area and Ergun coefficient in Forchheimer-extended Darcy model. Heat transfer coefficient of porous metal fins can be predicted within an error of 10% by our model. The predictive model has two assumptions. One is that the perimeter in the porous metal fin per cross-sectional area of porous metal fin is independent of the heights of fins and number of porous cells. Another assumption is that heat transfer coefficient of porous metal fin is also independent of the heights of fins and number of porous cells as long as the velocity is same. porous metal fin heat exchanger pressure drop heat transfer coefficient permeability Mechanical engineering and machinery Engineering machinery, tools, and implements Hiroyuki KOSHITA verfasserin aut In Nihon Kikai Gakkai ronbunshu The Japan Society of Mechanical Engineers, 2022 82(2016), 844, Seite 16-00173-16-00173 (DE-627)1028882408 21879761 nnns volume:82 year:2016 number:844 pages:16-00173-16-00173 https://doi.org/10.1299/transjsme.16-00173 kostenfrei https://doaj.org/article/e9f0ba115c9c456b9f773187076f088e kostenfrei https://www.jstage.jst.go.jp/article/transjsme/82/844/82_16-00173/_pdf/-char/en kostenfrei https://doaj.org/toc/2187-9761 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 82 2016 844 16-00173-16-00173
allfields_unstemmed	10.1299/transjsme.16-00173 doi (DE-627)DOAJ08595893X (DE-599)DOAJe9f0ba115c9c456b9f773187076f088e DE-627 ger DE-627 rakwb jpn TJ1-1570 TA213-215 Yoshihiro KONDO verfasserin aut Prediction for pressure drop and heat transfer coefficient of porous metal fins 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In order to evaluate the cooling performance of the porous metal fins, both the friction factor and heat transfer coefficient were taken into account. In this study, we compared six porous metal fins and four kinds of heat exchangers made of porous material. Moreover, we proposed a new model which predicts the cooling performance of the porous metal fins. Friction loss factor of porous metal fins became predictable in less than ±10% error by using effective cross-sectional flow area and Ergun coefficient in Forchheimer-extended Darcy model. Heat transfer coefficient of porous metal fins can be predicted within an error of 10% by our model. The predictive model has two assumptions. One is that the perimeter in the porous metal fin per cross-sectional area of porous metal fin is independent of the heights of fins and number of porous cells. Another assumption is that heat transfer coefficient of porous metal fin is also independent of the heights of fins and number of porous cells as long as the velocity is same. porous metal fin heat exchanger pressure drop heat transfer coefficient permeability Mechanical engineering and machinery Engineering machinery, tools, and implements Hiroyuki KOSHITA verfasserin aut In Nihon Kikai Gakkai ronbunshu The Japan Society of Mechanical Engineers, 2022 82(2016), 844, Seite 16-00173-16-00173 (DE-627)1028882408 21879761 nnns volume:82 year:2016 number:844 pages:16-00173-16-00173 https://doi.org/10.1299/transjsme.16-00173 kostenfrei https://doaj.org/article/e9f0ba115c9c456b9f773187076f088e kostenfrei https://www.jstage.jst.go.jp/article/transjsme/82/844/82_16-00173/_pdf/-char/en kostenfrei https://doaj.org/toc/2187-9761 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 82 2016 844 16-00173-16-00173
allfieldsGer	10.1299/transjsme.16-00173 doi (DE-627)DOAJ08595893X (DE-599)DOAJe9f0ba115c9c456b9f773187076f088e DE-627 ger DE-627 rakwb jpn TJ1-1570 TA213-215 Yoshihiro KONDO verfasserin aut Prediction for pressure drop and heat transfer coefficient of porous metal fins 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In order to evaluate the cooling performance of the porous metal fins, both the friction factor and heat transfer coefficient were taken into account. In this study, we compared six porous metal fins and four kinds of heat exchangers made of porous material. Moreover, we proposed a new model which predicts the cooling performance of the porous metal fins. Friction loss factor of porous metal fins became predictable in less than ±10% error by using effective cross-sectional flow area and Ergun coefficient in Forchheimer-extended Darcy model. Heat transfer coefficient of porous metal fins can be predicted within an error of 10% by our model. The predictive model has two assumptions. One is that the perimeter in the porous metal fin per cross-sectional area of porous metal fin is independent of the heights of fins and number of porous cells. Another assumption is that heat transfer coefficient of porous metal fin is also independent of the heights of fins and number of porous cells as long as the velocity is same. porous metal fin heat exchanger pressure drop heat transfer coefficient permeability Mechanical engineering and machinery Engineering machinery, tools, and implements Hiroyuki KOSHITA verfasserin aut In Nihon Kikai Gakkai ronbunshu The Japan Society of Mechanical Engineers, 2022 82(2016), 844, Seite 16-00173-16-00173 (DE-627)1028882408 21879761 nnns volume:82 year:2016 number:844 pages:16-00173-16-00173 https://doi.org/10.1299/transjsme.16-00173 kostenfrei https://doaj.org/article/e9f0ba115c9c456b9f773187076f088e kostenfrei https://www.jstage.jst.go.jp/article/transjsme/82/844/82_16-00173/_pdf/-char/en kostenfrei https://doaj.org/toc/2187-9761 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 82 2016 844 16-00173-16-00173
allfieldsSound	10.1299/transjsme.16-00173 doi (DE-627)DOAJ08595893X (DE-599)DOAJe9f0ba115c9c456b9f773187076f088e DE-627 ger DE-627 rakwb jpn TJ1-1570 TA213-215 Yoshihiro KONDO verfasserin aut Prediction for pressure drop and heat transfer coefficient of porous metal fins 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In order to evaluate the cooling performance of the porous metal fins, both the friction factor and heat transfer coefficient were taken into account. In this study, we compared six porous metal fins and four kinds of heat exchangers made of porous material. Moreover, we proposed a new model which predicts the cooling performance of the porous metal fins. Friction loss factor of porous metal fins became predictable in less than ±10% error by using effective cross-sectional flow area and Ergun coefficient in Forchheimer-extended Darcy model. Heat transfer coefficient of porous metal fins can be predicted within an error of 10% by our model. The predictive model has two assumptions. One is that the perimeter in the porous metal fin per cross-sectional area of porous metal fin is independent of the heights of fins and number of porous cells. Another assumption is that heat transfer coefficient of porous metal fin is also independent of the heights of fins and number of porous cells as long as the velocity is same. porous metal fin heat exchanger pressure drop heat transfer coefficient permeability Mechanical engineering and machinery Engineering machinery, tools, and implements Hiroyuki KOSHITA verfasserin aut In Nihon Kikai Gakkai ronbunshu The Japan Society of Mechanical Engineers, 2022 82(2016), 844, Seite 16-00173-16-00173 (DE-627)1028882408 21879761 nnns volume:82 year:2016 number:844 pages:16-00173-16-00173 https://doi.org/10.1299/transjsme.16-00173 kostenfrei https://doaj.org/article/e9f0ba115c9c456b9f773187076f088e kostenfrei https://www.jstage.jst.go.jp/article/transjsme/82/844/82_16-00173/_pdf/-char/en kostenfrei https://doaj.org/toc/2187-9761 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 82 2016 844 16-00173-16-00173
language	Japanese
source	In Nihon Kikai Gakkai ronbunshu 82(2016), 844, Seite 16-00173-16-00173 volume:82 year:2016 number:844 pages:16-00173-16-00173
sourceStr	In Nihon Kikai Gakkai ronbunshu 82(2016), 844, Seite 16-00173-16-00173 volume:82 year:2016 number:844 pages:16-00173-16-00173
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topic_facet	porous metal fin heat exchanger pressure drop heat transfer coefficient permeability Mechanical engineering and machinery Engineering machinery, tools, and implements
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container_title	Nihon Kikai Gakkai ronbunshu
authorswithroles_txt_mv	Yoshihiro KONDO @@aut@@ Hiroyuki KOSHITA @@aut@@
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callnumber-first	T - Technology
author	Yoshihiro KONDO
spellingShingle	Yoshihiro KONDO misc TJ1-1570 misc TA213-215 misc porous metal fin misc heat exchanger misc pressure drop misc heat transfer coefficient misc permeability misc Mechanical engineering and machinery misc Engineering machinery, tools, and implements Prediction for pressure drop and heat transfer coefficient of porous metal fins
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topic_title	TJ1-1570 TA213-215 Prediction for pressure drop and heat transfer coefficient of porous metal fins porous metal fin heat exchanger pressure drop heat transfer coefficient permeability
topic	misc TJ1-1570 misc TA213-215 misc porous metal fin misc heat exchanger misc pressure drop misc heat transfer coefficient misc permeability misc Mechanical engineering and machinery misc Engineering machinery, tools, and implements
topic_unstemmed	misc TJ1-1570 misc TA213-215 misc porous metal fin misc heat exchanger misc pressure drop misc heat transfer coefficient misc permeability misc Mechanical engineering and machinery misc Engineering machinery, tools, and implements
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title	Prediction for pressure drop and heat transfer coefficient of porous metal fins
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title_full	Prediction for pressure drop and heat transfer coefficient of porous metal fins
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title_sort	prediction for pressure drop and heat transfer coefficient of porous metal fins
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title_auth	Prediction for pressure drop and heat transfer coefficient of porous metal fins
abstract	In order to evaluate the cooling performance of the porous metal fins, both the friction factor and heat transfer coefficient were taken into account. In this study, we compared six porous metal fins and four kinds of heat exchangers made of porous material. Moreover, we proposed a new model which predicts the cooling performance of the porous metal fins. Friction loss factor of porous metal fins became predictable in less than ±10% error by using effective cross-sectional flow area and Ergun coefficient in Forchheimer-extended Darcy model. Heat transfer coefficient of porous metal fins can be predicted within an error of 10% by our model. The predictive model has two assumptions. One is that the perimeter in the porous metal fin per cross-sectional area of porous metal fin is independent of the heights of fins and number of porous cells. Another assumption is that heat transfer coefficient of porous metal fin is also independent of the heights of fins and number of porous cells as long as the velocity is same.
abstractGer	In order to evaluate the cooling performance of the porous metal fins, both the friction factor and heat transfer coefficient were taken into account. In this study, we compared six porous metal fins and four kinds of heat exchangers made of porous material. Moreover, we proposed a new model which predicts the cooling performance of the porous metal fins. Friction loss factor of porous metal fins became predictable in less than ±10% error by using effective cross-sectional flow area and Ergun coefficient in Forchheimer-extended Darcy model. Heat transfer coefficient of porous metal fins can be predicted within an error of 10% by our model. The predictive model has two assumptions. One is that the perimeter in the porous metal fin per cross-sectional area of porous metal fin is independent of the heights of fins and number of porous cells. Another assumption is that heat transfer coefficient of porous metal fin is also independent of the heights of fins and number of porous cells as long as the velocity is same.
abstract_unstemmed	In order to evaluate the cooling performance of the porous metal fins, both the friction factor and heat transfer coefficient were taken into account. In this study, we compared six porous metal fins and four kinds of heat exchangers made of porous material. Moreover, we proposed a new model which predicts the cooling performance of the porous metal fins. Friction loss factor of porous metal fins became predictable in less than ±10% error by using effective cross-sectional flow area and Ergun coefficient in Forchheimer-extended Darcy model. Heat transfer coefficient of porous metal fins can be predicted within an error of 10% by our model. The predictive model has two assumptions. One is that the perimeter in the porous metal fin per cross-sectional area of porous metal fin is independent of the heights of fins and number of porous cells. Another assumption is that heat transfer coefficient of porous metal fin is also independent of the heights of fins and number of porous cells as long as the velocity is same.
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title_short	Prediction for pressure drop and heat transfer coefficient of porous metal fins
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Prediction for pressure drop and heat transfer coefficient of porous metal fins

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