2020
DOI: 10.1016/j.ijheatmasstransfer.2020.120152
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A successful general fluid-to-fluid similarity theory for heat transfer at supercritical pressure

Abstract: Highlights A general fluid-to-fluid scaling methodology for heat transfer at supercritical pressure is discussed as a further step of previous studies. Support and validation is provided by independent checks through RANS calculations. The theory is applicable to different fluids of interest and shows excellent performance. Guidelines for the applications and further assessment of the theory are provided.

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Cited by 26 publications
(3 citation statements)
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References 13 publications
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“…Kassem et al 28 developed a fluid to fluid similarity theory to analyze the heat transfer behavior of water, normalCO 2, ammonia and R23 at supercritical pressure condition. In this article, the experimental results performed with dimensional quantities showed a similar trend for all the fluids 29,30 . Zhang et al 31 considered the mixture of normalCO 2 and propane for the experimental analysis of a heat pump.…”
Section: Introductionsupporting
confidence: 62%
“…Kassem et al 28 developed a fluid to fluid similarity theory to analyze the heat transfer behavior of water, normalCO 2, ammonia and R23 at supercritical pressure condition. In this article, the experimental results performed with dimensional quantities showed a similar trend for all the fluids 29,30 . Zhang et al 31 considered the mixture of normalCO 2 and propane for the experimental analysis of a heat pump.…”
Section: Introductionsupporting
confidence: 62%
“…To ensure the validity of the results obtained from the scaled experimental model, a similarity analysis between the scaled model and the prototype building must be conducted. According to relevant research [33,34], the Reynolds number (Re) and Archimedes number (Ar) can be used as the similarity criterion. Indeed, achieving complete identity across all criteria besides the Prandtl number (Pr) is widely acknowledged as impractical.…”
Section: Scaled Experimental Model For Validationmentioning
confidence: 99%
“…Klein et al 5 built a new regularized, parameter free scale similarity type model for Large Eddy, which exhibits good performance for a variety of mesh resolutions and for all configurations. Pucciarelli and Ambrosini 6 introduced a general fluid-to-fluid similarity theory for heat transfer at supercritical pressure, and the RANS CFD analysis of four different fluids was carried out by using this theory. Bao et al 7 used deep learning to explore local physical similarity for global-scale bridging in thermal-hydraulic simulation, which makes it effective to evaluate mesh effect or model scalability independently.…”
Section: Introductionmentioning
confidence: 99%