通过响应面方法优化铁氧体混合纳米流体的物理量:灵敏度和光谱分析

IF 3.1 3区 计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
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引用次数: 0

摘要

本研究利用响应面方法(RSM)和不可逆分析,分析了 20W40 机油(一种由美国汽车工程师协会鉴定的基础液体)+镍锌铁氧体-锰锌铁氧体混合纳米液体在可拉伸薄片上流动时的摩擦系数和传热速率的敏感性分析。考虑了具有浮力效应的熔化现象。与传统纳米流体相比,混合纳米流体具有更好的热连通性、更强的机械弹性、有利的纵横比和更优越的导热性。利用李氏方程组方法将控制方程系统转化为无量纲形式。利用谱局部线性化方法进行了数值计算。结果表明,由于流体中锰和镍锌铁氧体颗粒的增加,努塞尔特数和摩擦阻力都有所下降。此外,熔化参数可将熵的产生减少 41.16%,而粘性耗散参数可将表面摩擦降至最低。通过 RSM 进行的敏感性分析表明,表皮摩擦和努塞尔特数对熔化参数呈正敏感性。数值解与现有结果以及误差估计进行了比较,结果显示两者非常吻合。两种混合纳米流体的比较结果以图表形式显示。最后,这项工作有很多用途,如微波和生物医学应用、电磁界面、熔化和焊接操作,这些都是在核反应堆冷却系统等各个领域中最重要的制造应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimizing physical quantities of ferrite hybrid nanofluid via response surface methodology: Sensitivity and spectral analyses

This study analyses the sensitivity analysis of the friction factor and heat transfer rate within a hybrid nanoliquid flow of 20W40 motor oil (a base liquid that has been characterized by the Society of Automotive Engineers) + nickel zinc ferrite- manganese zinc ferrite over a stretchable sheet utilizing the Response Surface Methodology (RSM) along with irreversibility analysis. The melting phenomenon with buoyancy effect has been considered. Hybrid nanofluids exhibit improved thermal connectivity, enhanced mechanical resilience, favorable aspect ratios, and superior thermal conductivity when compared to conventional nanofluids. The system of governing equations is transformed into dimensionless form using the Lie group approach. Numerical computations are performed utilizing the spectral local linearization method. It is demonstrated that the Nusselt number and friction drag are decreased due to the increase of manganese and nickel zinc ferrites particles in the fluid. Further, the melting parameter reduces entropy generation by 41.16% and the viscous dissipation parameter minimizes surface friction. Sensitivity analysis, conducted through RSM, reveals that skin friction and the Nusselt number are positively sensitive to the melting parameter. The numerical solutions have been compared with the available results along with error estimations, which show excellent agreement. Comparison of both hybrid nanofluids are displayed graphically. Finally, this work has many uses such as microwave and biomedical applications, electromagnetic interfaces, melting, and welding operations which are the most significant manufacturing applications important in various sectors such as cooling systems of nuclear reactors.

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来源期刊
Journal of Computational Science
Journal of Computational Science COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-COMPUTER SCIENCE, THEORY & METHODS
CiteScore
5.50
自引率
3.00%
发文量
227
审稿时长
41 days
期刊介绍: Computational Science is a rapidly growing multi- and interdisciplinary field that uses advanced computing and data analysis to understand and solve complex problems. It has reached a level of predictive capability that now firmly complements the traditional pillars of experimentation and theory. The recent advances in experimental techniques such as detectors, on-line sensor networks and high-resolution imaging techniques, have opened up new windows into physical and biological processes at many levels of detail. The resulting data explosion allows for detailed data driven modeling and simulation. This new discipline in science combines computational thinking, modern computational methods, devices and collateral technologies to address problems far beyond the scope of traditional numerical methods. Computational science typically unifies three distinct elements: • Modeling, Algorithms and Simulations (e.g. numerical and non-numerical, discrete and continuous); • Software developed to solve science (e.g., biological, physical, and social), engineering, medicine, and humanities problems; • Computer and information science that develops and optimizes the advanced system hardware, software, networking, and data management components (e.g. problem solving environments).
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