磁场下卡波聚屈服应力 Fe3O4 纳米流体的瑞利-贝纳尔对流:实验研究与 ANN 建模

IF 2.5 4区 工程技术 Q3 CHEMISTRY, PHYSICAL International Journal of Thermophysics Pub Date : 2024-06-12 DOI:10.1007/s10765-024-03390-8
M. A. Hassan, Rishikesh Kumar, N. H. Khan
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引用次数: 0

摘要

本研究介绍了一项全面的实验研究,旨在阐明磁场、纳米粒子浓度和聚合物的存在对屈服应力纳米流体中瑞利-贝纳德对流的影响。测试流体由 Ultrez 30 聚合物粉末和氧化铁纳米颗粒组成。Herschel-Bulkley 模型用于捕捉流变行为。Ultrez 30 聚合凝胶和氧化铁纳米颗粒的浓度从 0.05 % 到 0.10 % 不等。内部开发的实验装置暴露在 0 mT 至 100 mT 范围内的磁场中。在没有磁场的情况下,传热会随着流体中纳米粒子比例的增加而增加。然而,在有磁场的情况下,对流效应会随着纳米粒子浓度的增加而减弱。此外,还提出了一个优化的人工神经网络(ANN)模型,该模型具有一个单隐层和九个隐神经元,用于预测努塞尔特数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Rayleigh–Benard Convection of Carbopol Yield Stress Fe3O4 Nanofluids Under Magnetic Field: An Experimental Investigation and ANN Modelling

This study presents a comprehensive experimental investigation aimed at elucidating the influence of magnetic fields, nanoparticle concentration, and the presence of polymer on Rayleigh–Benard convection in yield stress nanofluids. The test fluid comprises Ultrez 30 polymeric powder and Iron oxide nanoparticles. Herschel–Bulkley's model is applied to capture the rheological behaviour. The concentration of both Ultrez 30 polymeric gel and Iron oxide nanoparticles varies from 0.05 % to 0.10 %. The in-house developed experimental set-up is exposed to the magnetic field in the 0 mT to 100 mT range. Without a magnetic field, heat transfer increases with the elevation of nanoparticle fraction in the fluid. However, in the presence of a magnetic field, the convection effect weakens as the nanoparticle concentration rises. Furthermore, an optimised artificial neural network (ANN) model featuring a single hidden layer with nine hidden neurons is presented to predict the Nusselt number.

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来源期刊
CiteScore
4.10
自引率
9.10%
发文量
179
审稿时长
5 months
期刊介绍: International Journal of Thermophysics serves as an international medium for the publication of papers in thermophysics, assisting both generators and users of thermophysical properties data. This distinguished journal publishes both experimental and theoretical papers on thermophysical properties of matter in the liquid, gaseous, and solid states (including soft matter, biofluids, and nano- and bio-materials), on instrumentation and techniques leading to their measurement, and on computer studies of model and related systems. Studies in all ranges of temperature, pressure, wavelength, and other relevant variables are included.
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