Computational Fluid Dynamic Simulation of Single Bubble Growth under High-Pressure Pool Boiling Conditions

Component-scale modeling of boiling is predominantly based on the Eulerian–Eulerian two-fluid approach. Within this framework, wall boiling is accounted for via the Rensselaer Polytechnic Institute (RPI) model and, within this model, the bubble is characterized using three main parameters: departure...
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Autor*in:	Janani Murallidharan [verfasserIn] Giovanni Giustini [verfasserIn] Yohei Sato [verfasserIn] Bojan Ničeno [verfasserIn] Vittorio Badalassi [verfasserIn] Simon P. Walker [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2016

Schlagwörter:	Bubble Growth Rate Direct Numerical Simulation High Pressure Pool Boiling

Übergeordnetes Werk:	In: Nuclear Engineering and Technology - Elsevier, 2016, 48(2016), 4, Seite 859-869
Übergeordnetes Werk:	volume:48 ; year:2016 ; number:4 ; pages:859-869

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1016/j.net.2016.06.004

Katalog-ID:	DOAJ054986222

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520			\|a Component-scale modeling of boiling is predominantly based on the Eulerian–Eulerian two-fluid approach. Within this framework, wall boiling is accounted for via the Rensselaer Polytechnic Institute (RPI) model and, within this model, the bubble is characterized using three main parameters: departure diameter (D), nucleation site density (N), and departure frequency (f). Typically, the magnitudes of these three parameters are obtained from empirical correlations. However, in recent years, efforts have been directed toward mechanistic modeling of the boiling process. Of the three parameters mentioned above, the departure diameter (D) is least affected by the intrinsic uncertainties of the nucleate boiling process. This feature, along with its prominence within the RPI boiling model, has made it the primary candidate for mechanistic modeling ventures. Mechanistic modeling of D is mostly carried out through solving of force balance equations on the bubble. Forces incorporated in these equations are formulated as functions of the radius of the bubble and have been developed for, and applied to, low-pressure conditions only. Conversely, for high-pressure conditions, no mechanistic information is available regarding the growth rates of bubbles and the forces acting on them. In this study, we use direct numerical simulation coupled with an interface tracking method to simulate bubble growth under high (up to 45 bar) pressure, to obtain the kind of mechanistic information required for an RPI-type approach. In this study, we compare the resulting bubble growth rate curves with predictions made with existing experimental data.
650		4	\|a Bubble Growth Rate
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650		4	\|a High Pressure
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callnumber-first	T - Technology
author	Janani Murallidharan
spellingShingle	Janani Murallidharan misc TK9001-9401 misc Bubble Growth Rate misc Direct Numerical Simulation misc High Pressure misc Pool Boiling misc Nuclear engineering. Atomic power Computational Fluid Dynamic Simulation of Single Bubble Growth under High-Pressure Pool Boiling Conditions
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topic_title	TK9001-9401 Computational Fluid Dynamic Simulation of Single Bubble Growth under High-Pressure Pool Boiling Conditions Bubble Growth Rate Direct Numerical Simulation High Pressure Pool Boiling
topic	misc TK9001-9401 misc Bubble Growth Rate misc Direct Numerical Simulation misc High Pressure misc Pool Boiling misc Nuclear engineering. Atomic power
topic_unstemmed	misc TK9001-9401 misc Bubble Growth Rate misc Direct Numerical Simulation misc High Pressure misc Pool Boiling misc Nuclear engineering. Atomic power
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title	Computational Fluid Dynamic Simulation of Single Bubble Growth under High-Pressure Pool Boiling Conditions
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title_full	Computational Fluid Dynamic Simulation of Single Bubble Growth under High-Pressure Pool Boiling Conditions
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title_sort	computational fluid dynamic simulation of single bubble growth under high-pressure pool boiling conditions
callnumber	TK9001-9401
title_auth	Computational Fluid Dynamic Simulation of Single Bubble Growth under High-Pressure Pool Boiling Conditions
abstract	Component-scale modeling of boiling is predominantly based on the Eulerian–Eulerian two-fluid approach. Within this framework, wall boiling is accounted for via the Rensselaer Polytechnic Institute (RPI) model and, within this model, the bubble is characterized using three main parameters: departure diameter (D), nucleation site density (N), and departure frequency (f). Typically, the magnitudes of these three parameters are obtained from empirical correlations. However, in recent years, efforts have been directed toward mechanistic modeling of the boiling process. Of the three parameters mentioned above, the departure diameter (D) is least affected by the intrinsic uncertainties of the nucleate boiling process. This feature, along with its prominence within the RPI boiling model, has made it the primary candidate for mechanistic modeling ventures. Mechanistic modeling of D is mostly carried out through solving of force balance equations on the bubble. Forces incorporated in these equations are formulated as functions of the radius of the bubble and have been developed for, and applied to, low-pressure conditions only. Conversely, for high-pressure conditions, no mechanistic information is available regarding the growth rates of bubbles and the forces acting on them. In this study, we use direct numerical simulation coupled with an interface tracking method to simulate bubble growth under high (up to 45 bar) pressure, to obtain the kind of mechanistic information required for an RPI-type approach. In this study, we compare the resulting bubble growth rate curves with predictions made with existing experimental data.
abstractGer	Component-scale modeling of boiling is predominantly based on the Eulerian–Eulerian two-fluid approach. Within this framework, wall boiling is accounted for via the Rensselaer Polytechnic Institute (RPI) model and, within this model, the bubble is characterized using three main parameters: departure diameter (D), nucleation site density (N), and departure frequency (f). Typically, the magnitudes of these three parameters are obtained from empirical correlations. However, in recent years, efforts have been directed toward mechanistic modeling of the boiling process. Of the three parameters mentioned above, the departure diameter (D) is least affected by the intrinsic uncertainties of the nucleate boiling process. This feature, along with its prominence within the RPI boiling model, has made it the primary candidate for mechanistic modeling ventures. Mechanistic modeling of D is mostly carried out through solving of force balance equations on the bubble. Forces incorporated in these equations are formulated as functions of the radius of the bubble and have been developed for, and applied to, low-pressure conditions only. Conversely, for high-pressure conditions, no mechanistic information is available regarding the growth rates of bubbles and the forces acting on them. In this study, we use direct numerical simulation coupled with an interface tracking method to simulate bubble growth under high (up to 45 bar) pressure, to obtain the kind of mechanistic information required for an RPI-type approach. In this study, we compare the resulting bubble growth rate curves with predictions made with existing experimental data.
abstract_unstemmed	Component-scale modeling of boiling is predominantly based on the Eulerian–Eulerian two-fluid approach. Within this framework, wall boiling is accounted for via the Rensselaer Polytechnic Institute (RPI) model and, within this model, the bubble is characterized using three main parameters: departure diameter (D), nucleation site density (N), and departure frequency (f). Typically, the magnitudes of these three parameters are obtained from empirical correlations. However, in recent years, efforts have been directed toward mechanistic modeling of the boiling process. Of the three parameters mentioned above, the departure diameter (D) is least affected by the intrinsic uncertainties of the nucleate boiling process. This feature, along with its prominence within the RPI boiling model, has made it the primary candidate for mechanistic modeling ventures. Mechanistic modeling of D is mostly carried out through solving of force balance equations on the bubble. Forces incorporated in these equations are formulated as functions of the radius of the bubble and have been developed for, and applied to, low-pressure conditions only. Conversely, for high-pressure conditions, no mechanistic information is available regarding the growth rates of bubbles and the forces acting on them. In this study, we use direct numerical simulation coupled with an interface tracking method to simulate bubble growth under high (up to 45 bar) pressure, to obtain the kind of mechanistic information required for an RPI-type approach. In this study, we compare the resulting bubble growth rate curves with predictions made with existing experimental data.
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title_short	Computational Fluid Dynamic Simulation of Single Bubble Growth under High-Pressure Pool Boiling Conditions
url	https://doi.org/10.1016/j.net.2016.06.004 https://doaj.org/article/163ab540414f49a6b64f7b92ad7e211c http://www.sciencedirect.com/science/article/pii/S1738573316300912 https://doaj.org/toc/1738-5733
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author2	Giovanni Giustini Yohei Sato Bojan Ničeno Vittorio Badalassi Simon P. Walker
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