结霜的实验评估和半经验估计——以背脊翅片倒V管阵列蒸发器为例

IF 4.7 2区 工程技术 Q1 ENGINEERING, MECHANICAL Frontiers of Mechanical Engineering Pub Date : 2023-02-24 DOI:10.3389/fmech.2023.1101425
I. Carvajal-Mariscal, J. D. De León-Ruiz, J. M. Belman-Flores, E. Martínez-Espinosa, O. José-Pineda
{"title":"结霜的实验评估和半经验估计——以背脊翅片倒V管阵列蒸发器为例","authors":"I. Carvajal-Mariscal, J. D. De León-Ruiz, J. M. Belman-Flores, E. Martínez-Espinosa, O. José-Pineda","doi":"10.3389/fmech.2023.1101425","DOIUrl":null,"url":null,"abstract":"Present work focuses on frost accretion in a spine-finned inverted-V tube array evaporator. An experimental evaluation was performed using a standard issue, vertical top-mount, 18 cubic feet, 0.5 m3, refrigerator. Evaporator temperature distribution, inner airflow velocity, and relative humidity were measured to account for convective phenomena influencing frost distribution. Frost formation and accretion on the surface of the evaporator were visualized using thermal and microscopic imagery. The images were processed using a machine vision algorithm to measure frost thickness. Complementarily, frost density and vapor mass transfer were computed using available correlations. An estimation function was derived from the compiled data using a semi empirical approach, i.e., direct measurements and thermophysical substance properties. The resulting mathematical expression estimated the frost accretion rate within an error expectancy, RMSE, of 0.1479 and displayed a goodness-of-fit, R-Squared, of 0.9029. Based on these results, semi empirical estimation, is proposed as a viable approach to construct adequate limits for new predictions, vis-à-vis evaporator performance, ultimately reducing appliance energy consumption via implementing more effective control strategies regarding internal defrosting.","PeriodicalId":48635,"journal":{"name":"Frontiers of Mechanical Engineering","volume":" ","pages":""},"PeriodicalIF":4.7000,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Experimental assessment and semi empirical estimation of frost accretion—A case study on a spine-finned inverted-V tube array evaporator\",\"authors\":\"I. Carvajal-Mariscal, J. D. De León-Ruiz, J. M. Belman-Flores, E. Martínez-Espinosa, O. José-Pineda\",\"doi\":\"10.3389/fmech.2023.1101425\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Present work focuses on frost accretion in a spine-finned inverted-V tube array evaporator. An experimental evaluation was performed using a standard issue, vertical top-mount, 18 cubic feet, 0.5 m3, refrigerator. Evaporator temperature distribution, inner airflow velocity, and relative humidity were measured to account for convective phenomena influencing frost distribution. Frost formation and accretion on the surface of the evaporator were visualized using thermal and microscopic imagery. The images were processed using a machine vision algorithm to measure frost thickness. Complementarily, frost density and vapor mass transfer were computed using available correlations. An estimation function was derived from the compiled data using a semi empirical approach, i.e., direct measurements and thermophysical substance properties. The resulting mathematical expression estimated the frost accretion rate within an error expectancy, RMSE, of 0.1479 and displayed a goodness-of-fit, R-Squared, of 0.9029. Based on these results, semi empirical estimation, is proposed as a viable approach to construct adequate limits for new predictions, vis-à-vis evaporator performance, ultimately reducing appliance energy consumption via implementing more effective control strategies regarding internal defrosting.\",\"PeriodicalId\":48635,\"journal\":{\"name\":\"Frontiers of Mechanical Engineering\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":4.7000,\"publicationDate\":\"2023-02-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Frontiers of Mechanical Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.3389/fmech.2023.1101425\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, MECHANICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers of Mechanical Engineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.3389/fmech.2023.1101425","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
引用次数: 1

摘要

目前的工作集中在背脊翅片倒V管阵列蒸发器中的结霜。使用标准版、垂直顶部安装、18立方英尺、0.5立方米冰箱进行实验评估。测量蒸发器温度分布、内部气流速度和相对湿度,以解释影响霜分布的对流现象。利用热成像和显微成像对蒸发器表面的结霜和积冰进行了可视化。使用机器视觉算法对图像进行处理,以测量霜的厚度。作为补充,使用可用的相关性计算了霜密度和蒸汽传质。使用半经验方法,即直接测量和热物理物质性质,从汇编的数据中导出估计函数。由此产生的数学表达式估计了在0.1479的误差预期RMSE内的结霜率,并显示出0.9029的拟合优度R-Squared。基于这些结果,半经验估计被认为是一种可行的方法,可以为蒸发器性能的新预测构建足够的极限,最终通过实施更有效的内部除霜控制策略来降低设备能耗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Experimental assessment and semi empirical estimation of frost accretion—A case study on a spine-finned inverted-V tube array evaporator
Present work focuses on frost accretion in a spine-finned inverted-V tube array evaporator. An experimental evaluation was performed using a standard issue, vertical top-mount, 18 cubic feet, 0.5 m3, refrigerator. Evaporator temperature distribution, inner airflow velocity, and relative humidity were measured to account for convective phenomena influencing frost distribution. Frost formation and accretion on the surface of the evaporator were visualized using thermal and microscopic imagery. The images were processed using a machine vision algorithm to measure frost thickness. Complementarily, frost density and vapor mass transfer were computed using available correlations. An estimation function was derived from the compiled data using a semi empirical approach, i.e., direct measurements and thermophysical substance properties. The resulting mathematical expression estimated the frost accretion rate within an error expectancy, RMSE, of 0.1479 and displayed a goodness-of-fit, R-Squared, of 0.9029. Based on these results, semi empirical estimation, is proposed as a viable approach to construct adequate limits for new predictions, vis-à-vis evaporator performance, ultimately reducing appliance energy consumption via implementing more effective control strategies regarding internal defrosting.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Frontiers of Mechanical Engineering
Frontiers of Mechanical Engineering Engineering-Mechanical Engineering
CiteScore
7.20
自引率
6.70%
发文量
731
期刊介绍: Frontiers of Mechanical Engineering is an international peer-reviewed academic journal sponsored by the Ministry of Education of China. The journal seeks to provide a forum for a broad blend of high-quality academic papers in order to promote rapid communication and exchange between researchers, scientists, and engineers in the field of mechanical engineering. The journal publishes original research articles, review articles and feature articles.
期刊最新文献
Causal inference with a mediated proportional hazards regression model. Revolution and challenges in machining processing aimed at carbon reduction Multi-material additive manufacturing-functionally graded materials by means of laser remelting during laser powder bed fusion Review of key technologies of climbing robots A new modeling approach for stress–strain relationship taking into account strain hardening and stored energy by compacted graphite iron evolution
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1