Linear regression analysis of Williamson hybrid nanofluid flow with thermal radiation: Numerical simulation

Q1 Chemical Engineering
A. Divya , Gunisetty Ramasekhar , Pooja M N , K V Nagaraja , S K Narasimhamurthy
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引用次数: 0

Abstract

Research Background: In the modern landscape of Industry 4.0 and technological advancements, the control of heat and fluid flow is critical in enhancing the performance and efficiency of industrial and energy systems. Hybrid nanofluids, due to their improved thermal conductivity and energy transport characteristics, have gained significant attention over conventional fluids.
Issue: Despite their potential, the complex behaviour of hybrid nanofluids under the influence of magnetic fields, porous media, and thermal radiation remains insufficiently explored, especially for non-Newtonian models such as the Williamson fluid. A detailed understanding of these effects is essential for optimizing thermal systems.
Method: This study investigates the Williamson hybrid nanofluid flow over a stretching sheet in a porous medium subjected to a magnetic field and thermal radiation. The governing nonlinear partial differential equations are converted into ordinary differential equations using similarity transformations and solved numerically using the Runge-Kutta-Fehlberg (RKF-45) method implemented in MAPLE-18. A regression model is also developed to predict skin friction and Nusselt number using key influencing parameters.
Results: Convergence analysis demonstrates that the numerical solution remains stable and reliable within a relative tolerance range of 10−6 to 10−8. A multiple linear regression model, developed using key parameters K,  M,  Rd, and Ec, shows excellent predictive performance with R2 = 0.96127 for the skin friction coefficient and R2 = 0.99905 for the Nusselt number. These findings validate the robustness of the regression model and highlight the critical influence of magnetic and radiative parameters on heat transfer behavior in hybrid nanofluid flow systems.
含热辐射的Williamson混合纳米流体流动的线性回归分析:数值模拟
研究背景:在工业4.0和技术进步的现代景观中,热量和流体流动的控制对于提高工业和能源系统的性能和效率至关重要。混合纳米流体由于其更好的导热性和能量传输特性,已经比传统流体获得了极大的关注。问题:尽管具有潜力,但混合纳米流体在磁场、多孔介质和热辐射影响下的复杂行为仍未得到充分探索,特别是对于非牛顿模型,如Williamson流体。详细了解这些影响对于优化热系统至关重要。方法:研究了在磁场和热辐射作用下多孔介质中拉伸薄片上的Williamson混合纳米流体流动。利用相似变换将控制非线性偏微分方程转化为常微分方程,并利用MAPLE-18实现的Runge-Kutta-Fehlberg (RKF-45)方法进行数值求解。利用关键影响参数,建立了预测皮肤摩擦和努塞尔数的回归模型。结果:收敛分析表明,数值解在10−6 ~ 10−8的相对容差范围内保持稳定可靠。利用关键参数K、M、Rd和Ec建立的多元线性回归模型显示出良好的预测效果,皮肤摩擦系数R2 = 0.96127,努塞尔数R2 = 0.99905。这些发现验证了回归模型的鲁棒性,并强调了磁性和辐射参数对混合纳米流体流动系统传热行为的关键影响。
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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来源期刊
International Journal of Thermofluids
International Journal of Thermofluids Engineering-Mechanical Engineering
CiteScore
10.10
自引率
0.00%
发文量
111
审稿时长
66 days
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