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contributor authorHossain, Md Naim
contributor authorGhosh, Koushik
date accessioned2023-08-16T18:07:30Z
date available2023-08-16T18:07:30Z
date copyright3/31/2023 12:00:00 AM
date issued2023
identifier issn1948-5085
identifier othertsea_15_6_061001.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4291459
description abstractThe objective of the present work is to find out the optimal mass flux of two common refrigerants, R32 and R410A, undergoing boiling in an evaporator tube based on the entropy generation minimization approach. An entropy generation model is developed for two-phase boiling flow based on the drift flux approach. The distinct terms for entropy generation due to heat transfer and pressure drop are developed. The optimal solutions of the present model under a practical range of parametric conditions are compared with that obtained from the existing homogeneous and separated flow-based model. Analysis reveals that increasing the evaporator diameter and heat flux increases the optimal mass flux at minimum entropy generation for both refrigerants. On the other hand, increasing the evaporator length decreases the optimal mass flux. It is observed that the optimal mass flux data for all parametric conditions deviate within 10–15% on the positive and negative sides for drift flux and homogeneous models, respectively, compared to separate flow model. The present analysis also reveals that the overall deviation of data of the drift flux model and homogeneous flow model indicates a standard deviation of 1.95–1.98%, respectively.
publisherThe American Society of Mechanical Engineers (ASME)
titleEntropy Generation Minimization for Boiling Flow Inside Evaporator Tube With R32 and R410A Refrigerants: A Comparison of Different Two-Phase Flow Models
typeJournal Paper
journal volume15
journal issue6
journal titleJournal of Thermal Science and Engineering Applications
identifier doi10.1115/1.4056979
journal fristpage61001-1
journal lastpage61001-13
page13
treeJournal of Thermal Science and Engineering Applications:;2023:;volume( 015 ):;issue: 006
contenttypeFulltext


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