针对带对流加热的辐射 MHD 普朗特-艾林流体流动模型的反向多四边形径向基神经进化综合智能系统

Zeeshan Ikram Butt, Iftikhar Ahmad, Muhammad Shoaib, Hira Ilyas, A. Kiani, Muhammad Asif Zahoor Raja
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引用次数: 0

摘要

在这篇通讯中介绍了一种新的随机数值范例,用于深入研究普朗特-艾林流体模型的磁流体(MHD)边界层沿拉伸片流动对热辐射和对流加热情景的影响。人工神经网络(ANN)建模的精确近似诀窍,利用反向多曲(IMQ)函数,通过遗传算法(GA)的全局搜索和连续二次编程(SQP)的局部搜索功效进行优化/训练、即 ANNs-IMQ-GA-SQP。普朗特-艾林流体流动的数学模型以 PDE 的形式描述,然后通过适当的相似性变换转换为非线性 ODE 系统的形式,以计算/分析解的动态。通过改变各种物理参数,研究/观测了 MHD 普朗特-艾林流体流动的运动学和热力学特性。所获得的基于智能计算设计的求解器数值结果与通过亚当斯数值技术获得的参考结果一致。在对普朗特-艾林流体系统进行详尽模拟的基础上,广泛利用了基于一阶和二阶累积量的统计评估,对基于 ANNs-IMQ-GA-SQP 求解器的功效给予了充分肯定。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Integrated intelligence of inverse multiquadric radial base neuro‐evolution for radiative MHD Prandtl–Eyring fluid flow model with convective heating
In this communication, a new stochastic numerical paradigm is introduced for thorough scrutinization of the magnetohydrodynamic (MHD) boundary layer flow of Prandtl–Eyring fluidic model along a stretched sheet impact on thermal radiation as well as convective heating scenarios by exploiting the accurate approximation knacks of ANNs (artificial‐neural‐networks) modeling by using the inverse multiquadric (IMQ) function optimized/trained with well‐reputed global search with genetic algorithms (GAs) and local search efficacy of sequential quadratic programming (SQP), that is, ANNs‐IMQ‐GA‐SQP. The mathematical model of the Prandtl–Eyring fluid flow is portrayed in the form of PDEs and then converted in the form of a nonlinear system of ODEs by utilizing suitable similarity transformation to calculate/analyze the solution dynamics. The kinematic and thermodynamic properties of MHD Prandtl–Eyring fluid flow are examined/observed by varying the sundry physical parameters. The obtained intelligent computing designed solver‐based numerical results are consistently found in good agreement with reference results obtained through the Adams numerical technique. First and second‐order cumulant‐based statistical assessments are extensively exploited to endorse trustily the efficacy of ANNs‐IMQ‐GA‐SQP solver based on exhaustive simulations for the Prandtl–Eyring fluidic system.
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