Flow boiling heat transfer of zeotropic mixture R1234yf/R32 inside a horizontal multiport tube

制冷剂 管(容器) 沸腾 冷凝 核沸腾 临界热流密度
作者
Daisuke Jige,Shogo Kikuchi,Naoki Mikajiri,N. Inoue
出处
期刊:International Journal of Refrigeration-revue Internationale Du Froid [Elsevier]
卷期号:119: 390-400 被引量:26
标识
DOI:10.1016/j.ijrefrig.2020.04.036
摘要

The flow boiling heat transfer and pressure drop of zeotropic binary mixture R1234yf/R32 were experimentally investigated inside a horizontal multiport tube with rectangular minichannels. Local heat transfer coefficients were quantified under mass fluxes in the range 50–400 kgm−2s−1, heat fluxes in the range 5–20 kWm−2, and circulation compositions of 80/20 and 50/50mass%. The obtained heat transfer coefficient of the mixtures were compared with those of pure components under the same experimental conditions. The heat transfer of the mixtures was strongly influenced by mass flux, vapor quality, and mass fraction, whereas the influence of heat flux on heat transfer was small. The heat transfer coefficients of the mixtures were lower than those of the pure components under most conditions owing to mass diffusion resistance and temperature glide; however, the heat transfer coefficients of the mixtures were same or higher than those of R1234yf at high mass flux and high vapor quality regions. The frictional pressure drops of the mixtures increased with increasing mass flux, vapor quality, and mass fraction of R1234yf. The database encompassing more than 900 and 190 for boiling heat transfer coefficient and frictional pressure drop were compared with available previous correlations. Previous correlations underestimated the heat transfer coefficients of the mixtures, especially for data with higher temperature glide and dominant forced convective heat transfer. The proposed correlation shows good agreement with the heat transfer coefficients of the R1234yf/R32 mixtures with mean and mean absolute deviations of −5.0% and 10.3%, respectively.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
英俊的铭应助4149采纳,获得10
刚刚
1秒前
老八的嘴完成签到,获得积分10
1秒前
2秒前
孤独千愁发布了新的文献求助10
2秒前
2秒前
3秒前
pluto应助张艺跃采纳,获得10
3秒前
4秒前
潇洒的博完成签到,获得积分10
4秒前
5秒前
6秒前
科研通AI2S应助缥莲采纳,获得10
6秒前
6秒前
Dinglin完成签到,获得积分10
6秒前
丛士乔完成签到 ,获得积分10
6秒前
7秒前
怒发十篇高分sci完成签到,获得积分20
7秒前
乔乔完成签到,获得积分10
8秒前
8秒前
杨昌琪发布了新的文献求助10
8秒前
Tom发布了新的文献求助10
8秒前
灵灵妖发布了新的文献求助10
8秒前
8秒前
情怀应助火星上的大炮采纳,获得10
9秒前
w_完成签到,获得积分10
9秒前
9秒前
majiayang完成签到,获得积分10
9秒前
颖w完成签到,获得积分10
10秒前
光亮的青寒完成签到,获得积分10
10秒前
情怀应助MC采纳,获得10
10秒前
蓝天发布了新的文献求助10
11秒前
11秒前
依依发布了新的文献求助10
11秒前
spencer177完成签到,获得积分10
11秒前
qianhuxinyu完成签到,获得积分10
11秒前
11秒前
量子星尘发布了新的文献求助10
12秒前
完美世界应助emmm采纳,获得10
12秒前
12秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Basic And Clinical Science Course 2025-2026 3000
Encyclopedia of Agriculture and Food Systems Third Edition 2000
人脑智能与人工智能 1000
花の香りの秘密―遺伝子情報から機能性まで 800
Principles of Plasma Discharges and Materials Processing, 3rd Edition 400
Pharmacology for Chemists: Drug Discovery in Context 400
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5608407
求助须知:如何正确求助?哪些是违规求助? 4693040
关于积分的说明 14876313
捐赠科研通 4717445
什么是DOI,文献DOI怎么找? 2544206
邀请新用户注册赠送积分活动 1509230
关于科研通互助平台的介绍 1472836