具有无限剪切速率多重特征的 Cross 纳米流体在 Falkner-Skan 楔形表面上的熔化热传输机制的数值模拟

Adil Darvesh, Luis Jaime Collantes Santisteban, Shahzeb Khan, Fethi Mohamed Maiz, Hakim AL Garalleh, Manuel Sánchez‐Chero
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摘要

楔形几何是热传输机制的基石,尤其是在涉及流体在表面上流动的情况下。当前的研究强调了氧化石墨烯纳米流体在福克纳-斯坎楔形几何体上的熔化热传输机制,这种流体具有无限剪切速率、热传输特性和活化能可变的多重特征。此外,系统中还加入了 Cross 模型,可预测复杂流动的精确行为,从而更好地进行热模拟。流动受基于纳弗-斯托克斯关系的偏微分方程组的控制。高度非线性系统使用相似变量以简化的非维形式进行改变。数值模拟是通过高效的 MATLAB(bvp4c)求解器方案进行的,新出现的参数结果通过不同的图形和表格进行了汇编。在 Falkner-Skan 楔形几何结构中,速度比和熔化热参数值越高,传热率越高,而纳米流体分子的布朗运动是由热泳引起的,从而降低了浓度曲线。施密特数数值的增长会降低质量扩散率,从而降低流体的温度分布。同样,普朗特数的增加也会导致导热性降低,从而导致温度下降。值得注意的是,这种计算评估在热过程中至关重要,因为通过分析得出的结果可以优化设计,从而在实际应用中获得更好的性能、效率和控制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Numerical simulation of melting heat transport mechanism of Cross nanofluid with multiple features of infinite shear rate over a Falkner‐Skan wedge surface
The wedge geometry is a cornerstone in thermal transport mechanism, sepcially in scenarios involving fluid flow over surfaces. The current study emphasizes the melting heat transport mechanism in a Graphene oxide nanofluid over a Falkner‐Skan wedge geometry in the presence of multiple features of infinite shear rate accompanied with variable thermal transport characteristics and activation energy. Additionally, Cross model incorporated in the sytem, which predicts accurate behavior of intricate flow for better thermal simulation. The flow is governed by framed set of partial differential equations based on Naver stokes relations. A highly nonlinear system is altered in simplified non dimensional form using similarity variables. Numerical simulations are performed by an efficient MATLAB (bvp4c) solver scheme and the results of emerging parameters are compiled via different pictorial and tabular representations. The higher values of velocity ratio and melting heat parameter boost up the heat transfer rate over the Falkner‐Skan wedge geometry, whereas Brownian motion of nanofluid molecules arises by thermophoresis which declines the concentration profile. Numeric growth in the values of Schmidt number reduce the mass diffusivity, which declines the fluid temperature distribution. Likewise, Increasing value of Prandtl number causes reduction in thermal conductivity and produces temperature fall. It is worth noting that, this computational assessment is crucial in thermal processes because the results derived from this analysis enable the optimization of designs for better performance, efficiency, and control in practical applications.
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