化学反应对粗糙边界和被动控制微极性纳米流体热稳定性的影响:神经网络  

Impact of chemical reaction on the thermal stability of micropolar nanofluid with rough boundaries and passive control on nanoparticles:Neural networking

作　　者：GUPTA Vishal RANA Puneet KUMAR Lokendra GUPTA Vishal;RANA Puneet;KUMAR Lokendra(Department of Mathematics,Jaypee Institute of Information Technology,Noida 201309,India;School of Mathematical Sciences,College of Science,Mathematics and Technology,Wenzhou-Kean University,Wenzhou 325060,China)

机构地区：[1]Department of Mathematics,Jaypee Institute of Information Technology,Noida 201309,India [2]School of Mathematical Sciences,College of Science,Mathematics and Technology,Wenzhou-Kean University,Wenzhou 325060,China

出　　处：《Journal of Central South University》2023年第5期1581-1600,共20页中南大学学报（英文版）

摘　　要：本文在无通量和粗糙边界的情况下演示了化学反应对微极性纳米流体中热对流初始状态的影响。本研究应用Saffman界面条件求解粗糙边界。考虑在许多工业应用中具有重要作用的微极性非牛顿纳米流体。对于线性稳定性,利用正态模态技术(NMT)将控制系统的偏微分方程(PDE)转化为特征值问题(EVP),并采用基于有限差分的三阶段LobattoⅢa方法进行数值求解。发现对流的主要模式是静止模式。增加纳米流体中热流通量与自旋霍尔效应的耦合系数(δ)、自旋霍尔效应与涡度的耦合系数(K)、粗糙度参数(λ_(1),λ_(2))、化学反应参数(Cr)、修正扩散比(NA)和微极性参数(A)的取值,可以降低对流,从而稳定系统。然后,在81个数据点的基础上,利用嵌入多人感知的人工神经网络(ANN)确定四个控制参数与Rayleigh临界数之间的关系。This paper demonstrates the impact of chemical reactions on the onset of thermal convection in micropolar nanofluid using no flux and rough boundaries.For solving rough boundaries,we have implemented a Saffman-interface condition.Here,we consider the micropolar non-Newtonian nanofluid,which has an important role in many industrial applications.For linear stability,we use the normal mode technique(NMT)to convert the controlling system of a partial differential equation(PDE)into an eigenvalue problem(EVP)and solve it numerically using the finite difference based three stage LobattoⅢa method.The stationary mode is found to be the dominant mode of convection.Increasing the values of coupling coefficient between heat flux and spin Hall effect(δ),the coupling coefficient between spin Hall effects and vorticity(K),roughness parameters(λ_(1),λ_(2)),chemical reaction parameter(Cr)and modified diffusivity ratio(NA)and parameter of micro-polarity(A)in the nanofluid delays the convection,thus stabilizing the system.Later,with 81 data points,an artificial neural network(ANN)embedded with multiplayer perception(MLP)is used to determine the relationship between four controlling parameters and Rayleigh critical number.

关 键 词：纳米流体 RAYLEIGH-BENARD对流 FDM法 粗糙表面 化学反应 神经计算 

分 类 号：TB383.1[一般工业技术—材料科学与工程] TP183[自动化与计算机技术—控制理论与控制工程] TQ021.2[自动化与计算机技术—控制科学与工程]