利用响应面方法对涡流磁流体动力学(MHD)发电机进行多目标优化

Arleen Natalie, Ridho Irwansyah, Budiarso, Nasruddin
{"title":"利用响应面方法对涡流磁流体动力学(MHD)发电机进行多目标优化","authors":"Arleen Natalie, Ridho Irwansyah, Budiarso, Nasruddin","doi":"10.37934/arfmts.115.2.3349","DOIUrl":null,"url":null,"abstract":"The introduction of electromagnetic fields in fluid dynamics in magnetohydrodynamics (MHD), particularly when those fields are vector and non-uniform, complicates its application in vortex geometry. The imperative to optimize MHD generators arises from the inherent trade-off between voltage and pressure drop in energy conversion systems, to maximize voltage output while minimizing associated pressure drop. This study focuses on optimizing vortex MHD generators by applying Response Surface Methodology (RSM), which is based on mathematical models that capture the complex relationships between factor and response variables. This method offers a comprehensive approach to obtaining the optimum solution to the objectives, voltage and pressure drop, based on fluid velocity and magnetic field strength input parameters. Numerical optimization RSM generates 11 solutions. The optimum solutions obtained are a velocity of 1.415 m/s, and magnetic field strength of 0.43 T, and the corresponding optimum output voltage and pressure drop will be 4.264 mV and 4.254 psi, respectively, with a desirability level of the selected solution is 0.770. This study suggests the RSM method shows a good measurement of R2 and RSME. Our findings contribute to the understanding of optimizing vortex MHD generators and offer insights into achieving efficient energy conversion systems of a set of optimum generator operating parameters.","PeriodicalId":37460,"journal":{"name":"Journal of Advanced Research in Fluid Mechanics and Thermal Sciences","volume":"346 ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-Objective Optimization of Vortex Magnetohydrodynamics (MHD) Generator using Response Surface Methodology\",\"authors\":\"Arleen Natalie, Ridho Irwansyah, Budiarso, Nasruddin\",\"doi\":\"10.37934/arfmts.115.2.3349\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The introduction of electromagnetic fields in fluid dynamics in magnetohydrodynamics (MHD), particularly when those fields are vector and non-uniform, complicates its application in vortex geometry. The imperative to optimize MHD generators arises from the inherent trade-off between voltage and pressure drop in energy conversion systems, to maximize voltage output while minimizing associated pressure drop. This study focuses on optimizing vortex MHD generators by applying Response Surface Methodology (RSM), which is based on mathematical models that capture the complex relationships between factor and response variables. This method offers a comprehensive approach to obtaining the optimum solution to the objectives, voltage and pressure drop, based on fluid velocity and magnetic field strength input parameters. Numerical optimization RSM generates 11 solutions. The optimum solutions obtained are a velocity of 1.415 m/s, and magnetic field strength of 0.43 T, and the corresponding optimum output voltage and pressure drop will be 4.264 mV and 4.254 psi, respectively, with a desirability level of the selected solution is 0.770. This study suggests the RSM method shows a good measurement of R2 and RSME. Our findings contribute to the understanding of optimizing vortex MHD generators and offer insights into achieving efficient energy conversion systems of a set of optimum generator operating parameters.\",\"PeriodicalId\":37460,\"journal\":{\"name\":\"Journal of Advanced Research in Fluid Mechanics and Thermal Sciences\",\"volume\":\"346 \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Advanced Research in Fluid Mechanics and Thermal Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.37934/arfmts.115.2.3349\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Chemical Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Advanced Research in Fluid Mechanics and Thermal Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37934/arfmts.115.2.3349","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Chemical Engineering","Score":null,"Total":0}
引用次数: 0

摘要

在磁流体动力学(MHD)中的流体动力学中引入电磁场,特别是当这些电磁场是矢量和非均匀的时候,使其在涡旋几何中的应用变得更加复杂。优化 MHD 发电机的必要性源于能量转换系统中电压和压降之间的固有权衡,即最大化电压输出,同时最小化相关压降。本研究的重点是通过应用响应面法(RSM)优化涡流 MHD 发电机,响应面法以数学模型为基础,可捕捉因素和响应变量之间的复杂关系。该方法提供了一种综合方法,可根据流体速度和磁场强度输入参数,获得目标、电压和压降的最优解。数值优化 RSM 生成了 11 个解决方案。获得的最佳解决方案是流速为 1.415 m/s,磁场强度为 0.43 T,相应的最佳输出电压和压降分别为 4.264 mV 和 4.254 psi,所选解决方案的可取性水平为 0.770。这项研究表明,RSM 方法能很好地测量 R2 和 RSME。我们的研究结果有助于理解如何优化涡流 MHD 发电机,并为实现一组最佳发电机运行参数的高效能量转换系统提供了启示。
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
Multi-Objective Optimization of Vortex Magnetohydrodynamics (MHD) Generator using Response Surface Methodology
The introduction of electromagnetic fields in fluid dynamics in magnetohydrodynamics (MHD), particularly when those fields are vector and non-uniform, complicates its application in vortex geometry. The imperative to optimize MHD generators arises from the inherent trade-off between voltage and pressure drop in energy conversion systems, to maximize voltage output while minimizing associated pressure drop. This study focuses on optimizing vortex MHD generators by applying Response Surface Methodology (RSM), which is based on mathematical models that capture the complex relationships between factor and response variables. This method offers a comprehensive approach to obtaining the optimum solution to the objectives, voltage and pressure drop, based on fluid velocity and magnetic field strength input parameters. Numerical optimization RSM generates 11 solutions. The optimum solutions obtained are a velocity of 1.415 m/s, and magnetic field strength of 0.43 T, and the corresponding optimum output voltage and pressure drop will be 4.264 mV and 4.254 psi, respectively, with a desirability level of the selected solution is 0.770. This study suggests the RSM method shows a good measurement of R2 and RSME. Our findings contribute to the understanding of optimizing vortex MHD generators and offer insights into achieving efficient energy conversion systems of a set of optimum generator operating parameters.
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
Journal of Advanced Research in Fluid Mechanics and Thermal Sciences
Journal of Advanced Research in Fluid Mechanics and Thermal Sciences Chemical Engineering-Fluid Flow and Transfer Processes
CiteScore
2.40
自引率
0.00%
发文量
176
期刊介绍: This journal welcomes high-quality original contributions on experimental, computational, and physical aspects of fluid mechanics and thermal sciences relevant to engineering or the environment, multiphase and microscale flows, microscale electronic and mechanical systems; medical and biological systems; and thermal and flow control in both the internal and external environment.
期刊最新文献
Synchronous Heat and Mass Transmission in MHD Ohmic Dissipative Viscous Fluid Flow Cavorted by an Upright Surface with Chemical Reaction Energy and Exergy Analysis of R600a as a Substitute for R134a in Automotive Air Conditioning System Exploration of Timber Dry and Wet Rot Defects in Buildings: Types, Causes, Effects and Mitigation Methods Investigating the Effects of Air Bubbles Injection Technique on the Cooling Time of Warm Drinking Water Preparation of TFC-PES Reverse Osmosis Hollow Fibre Membrane for Brackish Water Desalination
×
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