综合数值模型和自适应神经模糊推理系统模型在预测非稳定耦合微波-卡森混合纳米流体的热物理性质中的可行性

Abbai Reddy Divya, Thandra Jithendra, Esambattu Hemalatha
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摘要

本文旨在利用旋转盘上的成对微极性和卡松混合流体探究假定现象。在这一阶段的工作中,设计了一种集成自适应神经模糊推理系统(ANFIS)的数值技术(Runge-Kutta 四阶和射击技术),该系统设想了热和指数空间相关热源、非线性热辐射和熵产生。为此,利用适当的自相似变量将非线性偏微分方程组转化为常微分方程。该模型的研究结果(除少数明显异常值外)与之前的研究结果基本一致,而之前的研究结果已并入用于训练 ANFIS 模型的数据集。在活动因素的影响下,许多剖面的结果都很美观。这表明,随着磁场和辐射的增加,速度和温度曲线急剧上升,导致与电场输入减少的矛盾现象。此外,涡旋粘度、自旋梯度粘度和微惯性密度在各种微气浮成分上的倾斜也显示出倾斜度。此外,还利用 ANFIS 训练分析了特定情况下的近似解,并根据测试数据集对开发的 ANFIS 进行了评估,以强调其性能。由于纳米粒子的渲染时间较长,因此被认为适合用于骨植入物、血液成像碘剂和红细胞刺激。因此,本研究的结果可用于治疗贫血。
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Feasibility of integrated numerical and Adaptive Neuro-Fuzzy Inference System models in predicting the thermophysical properties of unsteady coupled micropolar–Casson hybrid nanofluids
This article aims to probe postulated phenomena using a paired micropolar and Casson hybrid fluid over a rotating disk. The intension to design a numerical technique (Runge–Kutta fourth-order along with shooting technique) integrated Adaptive Neuro-Fuzzy Inference System (ANFIS) envisioned with a thermal and exponentially space-dependent heat source, nonlinear thermal radiation and entropy production is developed in this phase of work. To ensure that, a nonlinear partial differential equation set of equations has been transformed into an ordinary differential equation by using the proper self-similarity variables. The model's research results, with a few notable outliers, are mostly consistent with those from prior research that was merged into the dataset used to train the ANFIS model. With the impact of active factors, the results are esthetically exhibited for numerous profiles. This displays that with the rise in magnetic field and radiation, the velocity and temperature profiles increase sharply, resulting in a contradiction phenomenon with the decreasing electric field inputs. Also, tilting of vortex viscosity, spin gradient viscosity and microinertia density on the various microrotation components displays inclination. Moreover, ANFIS training was exploited to analyze the approximate solutions for specific scenarios, and the developed ANFIS was evaluated against a testing dataset to emphasize its performance. Due to their longer render, the nanoparticles exploited here are deemed suitable for use in bone implants, iodinated agents for blood imaging and red blood cell stimulation. Thus, the results of this study may be applied to therapeutic anemia therapies.
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