管内基于氧化石墨烯的[EMIM]Cl离子流体及其在高普朗特数下的传热和摩擦因子分析:实验和人工神经网络预测

L. Syam Sundar
{"title":"管内基于氧化石墨烯的[EMIM]Cl离子流体及其在高普朗特数下的传热和摩擦因子分析:实验和人工神经网络预测","authors":"L. Syam Sundar","doi":"10.1016/j.jil.2025.100144","DOIUrl":null,"url":null,"abstract":"<div><div>In this study, the stable Graphene Oxide (GO) ionanofluids were prepared and investigated the thermophysical properties, heat transfer coefficient, and friction factor experimentally. These ionanofluids were prepared by dispersing the synthesized GO into the ionic liquid of 1-ethyl-3-methylimidazolium chloride [EMIM]Cl in the weight percentages of 0.05 %, 0.1 %, 0.3 % and 0.5 %, respectively. The obtained experimental data of Reynolds number, and weight percentage was used as input parameters, and heat transfer coefficient, Nusselt number, and friction factor was used as output parameters for the Artificial Neural Network- Scaled Conjugate Gradient (ANN-SCG) analysis. The results indicated that, the thermal conductivity is enhanced by 26.39 % at a temperature of 60°C, and the viscosity enhancement of 30.44 % at a temperature of 30°C, and at 0.5 % weight percentage. The results were also indicated that, the Nusselt number, heat transfer coefficient is enhanced by 32.27 %, and 41.96 %, with a friction factor penalty of 14.04 % at 0.5 % weight percentage and at a Reynolds number of 297.4, respectively, over base fluid. The ANN-SCG results are almost predicts high accuracy when compared with the experimental data. The correlation coefficient (R<sup>2</sup>) of Nusselt number, heat transfer coefficient, and friction factor are 0.9815, 0.9812, and 0.9918, respectively. Using the experimental data, a new Nusselt number and friction factor correlations were proposed.</div></div>","PeriodicalId":100794,"journal":{"name":"Journal of Ionic Liquids","volume":"5 1","pages":"Article 100144"},"PeriodicalIF":0.0000,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Graphene oxide based [EMIM]Cl ionanofluids in a tube and their heat transfer, and friction factor analyses under high Prandtl numbers: Experimental and ANN predictions\",\"authors\":\"L. Syam Sundar\",\"doi\":\"10.1016/j.jil.2025.100144\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>In this study, the stable Graphene Oxide (GO) ionanofluids were prepared and investigated the thermophysical properties, heat transfer coefficient, and friction factor experimentally. These ionanofluids were prepared by dispersing the synthesized GO into the ionic liquid of 1-ethyl-3-methylimidazolium chloride [EMIM]Cl in the weight percentages of 0.05 %, 0.1 %, 0.3 % and 0.5 %, respectively. The obtained experimental data of Reynolds number, and weight percentage was used as input parameters, and heat transfer coefficient, Nusselt number, and friction factor was used as output parameters for the Artificial Neural Network- Scaled Conjugate Gradient (ANN-SCG) analysis. The results indicated that, the thermal conductivity is enhanced by 26.39 % at a temperature of 60°C, and the viscosity enhancement of 30.44 % at a temperature of 30°C, and at 0.5 % weight percentage. The results were also indicated that, the Nusselt number, heat transfer coefficient is enhanced by 32.27 %, and 41.96 %, with a friction factor penalty of 14.04 % at 0.5 % weight percentage and at a Reynolds number of 297.4, respectively, over base fluid. The ANN-SCG results are almost predicts high accuracy when compared with the experimental data. The correlation coefficient (R<sup>2</sup>) of Nusselt number, heat transfer coefficient, and friction factor are 0.9815, 0.9812, and 0.9918, respectively. Using the experimental data, a new Nusselt number and friction factor correlations were proposed.</div></div>\",\"PeriodicalId\":100794,\"journal\":{\"name\":\"Journal of Ionic Liquids\",\"volume\":\"5 1\",\"pages\":\"Article 100144\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-03-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Ionic Liquids\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2772422025000138\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Ionic Liquids","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772422025000138","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

本研究制备了稳定的氧化石墨烯(GO)离子流体,并对其热物理性质、传热系数和摩擦系数进行了实验研究。将合成的氧化石墨烯分别以0.05%、0.1%、0.3%和0.5%的质量分数分散到1-乙基-3-甲基咪唑氯离子液体[EMIM]Cl中,制备了这些离子流体。以获得的实验数据雷诺数、重量百分比作为输入参数,传热系数、努塞尔数和摩擦系数作为输出参数,进行人工神经网络-尺度共轭梯度(ANN-SCG)分析。结果表明,在温度为60℃时,导热系数提高了26.39%;在温度为30℃时,粘度提高了30.44%;结果还表明,在0.5%的重量百分比和297.4的雷诺数下,基液上的努塞尔数和换热系数分别提高了32.27%和41.96%,摩擦系数损失14.04%。与实验数据相比,ANN-SCG结果具有较高的预测精度。Nusselt数、换热系数和摩擦系数的相关系数R2分别为0.9815、0.9812和0.9918。利用实验数据,提出了一种新的努塞尔数与摩擦因数的关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Graphene oxide based [EMIM]Cl ionanofluids in a tube and their heat transfer, and friction factor analyses under high Prandtl numbers: Experimental and ANN predictions
In this study, the stable Graphene Oxide (GO) ionanofluids were prepared and investigated the thermophysical properties, heat transfer coefficient, and friction factor experimentally. These ionanofluids were prepared by dispersing the synthesized GO into the ionic liquid of 1-ethyl-3-methylimidazolium chloride [EMIM]Cl in the weight percentages of 0.05 %, 0.1 %, 0.3 % and 0.5 %, respectively. The obtained experimental data of Reynolds number, and weight percentage was used as input parameters, and heat transfer coefficient, Nusselt number, and friction factor was used as output parameters for the Artificial Neural Network- Scaled Conjugate Gradient (ANN-SCG) analysis. The results indicated that, the thermal conductivity is enhanced by 26.39 % at a temperature of 60°C, and the viscosity enhancement of 30.44 % at a temperature of 30°C, and at 0.5 % weight percentage. The results were also indicated that, the Nusselt number, heat transfer coefficient is enhanced by 32.27 %, and 41.96 %, with a friction factor penalty of 14.04 % at 0.5 % weight percentage and at a Reynolds number of 297.4, respectively, over base fluid. The ANN-SCG results are almost predicts high accuracy when compared with the experimental data. The correlation coefficient (R2) of Nusselt number, heat transfer coefficient, and friction factor are 0.9815, 0.9812, and 0.9918, respectively. Using the experimental data, a new Nusselt number and friction factor correlations were proposed.
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
CiteScore
3.70
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信