Study of bioconvective couple-stress nanofluid flow subject to stratified conditions by using numerical and Levenberg Marquardt back-propagation algorithms

IF 6.4 2区 工程技术 Q1 MECHANICS International Communications in Heat and Mass Transfer Pub Date : 2025-05-01 Epub Date: 2025-04-11 DOI:10.1016/j.icheatmasstransfer.2025.108947
Shuai Yuan , Dapeng Cheng
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Abstract

The heterogeneous fluid model is expressed for the nanofluid flow to study the consequence of Fourier's and Fick's laws. The magnetohydrodynamics couple-stress bioconvective nanofluid flow is considered across an extending surface with the impact of heat source/sink and stratified boundary conditions. The solid nano particulates and concentrations of motile microorganisms are added to the nonlinear system of differential equations conveying the non-Newtonian nanoliquid flow model. The similarity transformations are employed to transfigure the system of partial differential equations into the lowest order of ordinary differential equations. The artificial neural network (ANN) based on the LMBP (Levenberg Marquardt Back-propagation) algorithm is employed to solve these equations. The dataset is formed using the MATLAB package bvp4c. The dataset is created for diverse circumstances of flow factors, as well as validation and testing of the ANN. The accuracy of the problem is assessed through numerous statistical results (histogram, curve fitting, regression measures, and performance plots). The relative percent error between present outcomes and published studies is 0.00486 % at Pr = 2.0 (Prandtl number), where it gradually decreases up to 0.00069 % at Pr = 7.0. The outcomes are presented through the table and figures. It has been noticed that the Couple-stress nanofluid (CSNF) flow drops with the effect of the magnetic field. The CSNF temperature augments with the improvement of the thermophoresis effect, buoyancy ratio factor, Rayleigh number, and thermal radiation. Moreover, the concentration curve lessens under the impact of the Lewis number while enriched with the outcome of the concentration stratification parameter. The absolute error of reference and targeted date is attained within 10−3–10−6 which proves the exceptional precision of the results.
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利用数值和Levenberg - Marquardt反向传播算法研究分层条件下的生物对流耦合应力纳米流体流动
建立了纳米流体流动的非均质流体模型,研究了傅里叶定律和菲克定律的结果。考虑了磁流体力学耦合应力纳米流体在扩展表面上的流动,并考虑了热源/汇和分层边界条件的影响。将固体纳米颗粒和运动微生物的浓度加入非线性微分方程组中,传递非牛顿纳米液体流动模型。利用相似变换将偏微分方程组转化为最低阶常微分方程组。采用基于Levenberg - Marquardt反向传播(LMBP)算法的人工神经网络(ANN)来求解这些方程。使用MATLAB包bvp4c形成数据集。该数据集是为流量因素的不同情况以及人工神经网络的验证和测试而创建的。通过大量统计结果(直方图、曲线拟合、回归测量和性能图)来评估问题的准确性。当前结果与已发表研究之间的相对误差百分比在Pr = 2.0时为0.00486% (Prandtl数),在Pr = 7.0时逐渐减小至0.00069%。结果通过表格和图表呈现。研究发现,耦合应力纳米流体(CSNF)的流动随磁场的作用而下降。CSNF温度随热泳效应、浮力比因子、瑞利数和热辐射的提高而升高。浓度曲线在Lewis数的影响下减小,在浓度分层参数的影响下增大。参考数据与目标数据的绝对误差在10−3 ~ 10−6之间,证明了计算结果的精度。
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来源期刊
CiteScore
11.00
自引率
10.00%
发文量
648
审稿时长
32 days
期刊介绍: International Communications in Heat and Mass Transfer serves as a world forum for the rapid dissemination of new ideas, new measurement techniques, preliminary findings of ongoing investigations, discussions, and criticisms in the field of heat and mass transfer. Two types of manuscript will be considered for publication: communications (short reports of new work or discussions of work which has already been published) and summaries (abstracts of reports, theses or manuscripts which are too long for publication in full). Together with its companion publication, International Journal of Heat and Mass Transfer, with which it shares the same Board of Editors, this journal is read by research workers and engineers throughout the world.
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