Ain Shams Engineering Journal最新文献_第5页

Enhancing solar radiation prediction accuracy: A hybrid machine learning approach integrating response surface method and support vector regression 提高太阳辐射预测精度：集成响应面法和支持向量回归的混合机器学习方法

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal

Pub Date : 2024-11-01 DOI: 10.1016/j.asej.2024.103034

Rana Muhammad Adnan , Behrooz Keshtegar , Mona Abusurrah , Ozgur Kisi , Abdulaziz S. Alkabaa

An accurate solar radiation (SR) prediction with a practical training approach is vital in estimating solar energy. A hybrid machine learning (ML) model is proposed for estimating the monthly SR. The proposed model includes two ML approaches: the response surface method (RSM) and support vector regression (SVR). The RSM is used to optimize the input variables and handle the data points for the prediction of SR. The first ML approach presents two input variables to estimate data handling. In the second ML process, the SVR model provides a nonlinear regression for handling data supplied by RSM. A new model was employed to predict the SR data taken from two stations in Turkey, as the temperature and extraterrestrial radiation were used as the model inputs. The RSM, artificial neural networks (ANNs), SVR, multivariate adaptive regression spline (MARS), M5 model tree (M5Tree) and convolutional neural networks (CNN) methods as existing ML approaches were employed to compare the predictions proposed hybrid ML approaches using several criteria. Data were split into training and testing sets, and two scenarios were established to compare models’ efficiencies according to different sets. The outcomes showed that the proposed model provides better accuracy for estimating SR using limited input data than other alternatives. The accuracy of the ANNs, SVR, MARS, M5Tree, RSM and CNN models was improved using a hybrid ML model. The proposed RSM-SVR method enhanced the efficiency of the ANN, SVR, MARS, M5Tree, and RSM methods by RMSE margins ranging from 0.1% to 5.6%, 2.8% to 7.3%, 1.0% to 8.3%, 0.1% to 28%, and 2.0% to 5.9%, respectively.

采用实用的训练方法准确预测太阳辐射（SR）对估算太阳能至关重要。本文提出了一种混合机器学习（ML）模型，用于估算月度太阳辐射量。该模型包括两种 ML 方法：响应面法（RSM）和支持向量回归法（SVR）。RSM 用于优化输入变量和处理预测 SR 的数据点。第一种 ML 方法提出两个输入变量来估计数据处理。在第二个 ML 过程中，SVR 模型为处理 RSM 提供的数据提供了一个非线性回归。由于将温度和地外辐射作为模型输入，因此采用了一种新模型来预测土耳其两个站点的 SR 数据。采用 RSM、人工神经网络 (ANN)、SVR、多元自适应回归样条线 (MARS)、M5 模型树 (M5Tree) 和卷积神经网络 (CNN) 方法作为现有的 ML 方法，使用多个标准对提出的混合 ML 方法的预测结果进行比较。数据被分为训练集和测试集，并根据不同的集建立了两个场景来比较模型的效率。结果表明，与其他替代方法相比，建议的模型在使用有限的输入数据估算 SR 方面具有更高的准确性。使用混合 ML 模型提高了 ANN、SVR、MARS、M5Tree、RSM 和 CNN 模型的准确性。拟议的 RSM-SVR 方法提高了 ANN、SVR、MARS、M5Tree 和 RSM 方法的效率，其 RMSE 分别为 0.1% 至 5.6%、2.8% 至 7.3%、1.0% 至 8.3%、0.1% 至 28% 和 2.0% 至 5.9%。

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引用次数: 0

Computational modeling of petroleum purification for removal of sulfur compounds: Process analysis for reduction of environmental impacts and material costs 石油净化脱硫化合物的计算建模：减少环境影响和材料成本的工艺分析

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal

Pub Date : 2024-11-01 DOI: 10.1016/j.asej.2024.102986

Hui Gao , Tonghui Liu , Xiangyao Zhang , Yajun Ji , Wei Wei , Xiaoyong Liu , Kai Zhang

In the course of this investigation, three machine learning models (Gaussian Process Regression, Decision Tree Regression, and Kernel Ridge Regression) were examined for determining the correlation between the input variables (x and y) which are spatial coordinates of model’s geometry, and the content of species in adsorption for sulfur capture. For the process modeling, mass transfer was analyzed, and the concentration distribution of sulfur compound was obtained via numerical solution of mass transfer equations, and then used for machine learning models. The machine learning models were trained using a dataset of 19,000 observations, and their performance was assessed through metrics including R² score, MAE, and RMSE. Analysis of the results reveals that Decision Tree Regression surpassed the other two models in performance, with an R² score of 0.9989, MAE of 6.64405E-01, and RMSE of 1.1277E+00. Gaussian Process Regression had an R² score of 0.97106, MAE of 3.65541E+00, and RMSE of 5.6821E+00, while Kernel Ridge Regression had an R² score of 0.86347, MAE of 8.26121E+00, and RMSE of 1.1330E+01. The Clonal Selection Algorithm was used for hyper-parameter optimization for all models. These findings demonstrate the potential of machine learning techniques for accurately and reliably predicting the concentration of chemical species and highlight the importance of considering the choice of model and hyper-parameter optimization for optimal performance.

在这一研究过程中，对三种机器学习模型（高斯过程回归、决策树回归和核岭回归）进行了研究，以确定输入变量（x 和 y）（即模型几何形状的空间坐标）与硫捕获吸附物种含量之间的相关性。在过程建模方面，对传质进行了分析，通过对传质方程的数值求解获得了硫化合物的浓度分布，然后用于机器学习模型。使用 19,000 个观测数据集对机器学习模型进行了训练，并通过 R2 分数、MAE 和 RMSE 等指标对其性能进行了评估。结果分析表明，决策树回归模型的性能超过了其他两个模型，其 R2 得分为 0.9989，MAE 为 6.64405E-01，RMSE 为 1.1277E+00。高斯过程回归的 R2 得分为 0.97106，MAE 为 3.65541E+00，RMSE 为 5.6821E+00；而核岭回归的 R2 得分为 0.86347，MAE 为 8.26121E+00，RMSE 为 1.1330E+01。所有模型都采用了克隆选择算法进行超参数优化。这些发现证明了机器学习技术在准确可靠地预测化学物种浓度方面的潜力，并强调了考虑模型选择和超参数优化以获得最佳性能的重要性。

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引用次数: 0

Evaluation of synergetic structural and EMP shielding performance of novel conductive concrete 新型导电混凝土的协同结构和电磁脉冲屏蔽性能评估

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal

Pub Date : 2024-11-01 DOI: 10.1016/j.asej.2024.103015

Mohamed Wagih , Ismail M. Kamal , Ahmed E. Soltan , Mohamed A.E.M. Ali

Protection of critical facilities, modern devices, and systems against Electromagnetic Pulse (EMP) became a vital necessity due to modern civilization’s needs. Using conductive concrete for EMP shielding became a common practice because of its low cost compared to other approaches and accessible construction and maintenance techniques. An innovative conductive concrete mixtures with an EMP shielding capability is pioneered in this study. The mechanical properties, impact resistance, and Shielding Effectiveness (SE) performance of these conductive concrete mixtures which incorporates novel/non-traditional constituents including; magnetite powder, magnetite aggregate, steel fibers, wired steel mesh, and graphite powder were investigated.

A shielding effectiveness test was performed using an utterly anechoic room following the MIL-STD-188-125-1 requirements, while the impact resistance of concrete shields was assessed using a drop weight impact test. The results demonstrated that there was evidence that the compressive behavior of such conductive mixtures was increased by up to 21.5% relative to normal concrete due to incorporating fine and coarse magnetite aggregate in concrete shields. Furthermore, the incorporation of steel fibers significantly enhanced the splitting tensile properties by about 101% compared to the fibreless concrete specimens. Also, a superior 1st crack and fracture impact energy was sustained by concrete panels, owing to utilizing steel wired mesh and fibers in concrete shields, by about four to six times that of its non-reinforced counterparts. Also, the utilization of the indicated conductive constituents in the fabrication of concrete shields led to a significant improvement in SE performance by up to 196% compared to that of normal concrete constituents. This research underscores the potential to engineer novel conductive concrete shields with superior impact resistance and EMP shielding for the protection of critical infrastructure.

由于现代文明的需要，保护关键设施、现代设备和系统免受电磁脉冲（EMP）的侵害已成为一项至关重要的必要条件。使用导电混凝土进行电磁脉冲屏蔽已成为一种普遍做法，因为与其他方法相比，导电混凝土的成本较低，而且易于施工和维护。本研究开创了一种具有电磁脉冲屏蔽能力的创新型导电混凝土混合物。根据 MIL-STD-188-125-1 的要求，使用完全消声室进行了屏蔽效果测试，同时使用落锤冲击测试评估了混凝土屏蔽的抗冲击性。结果表明，有证据表明，由于在混凝土防护罩中加入了细粒和粗粒磁铁矿骨料，这种导电混合物的抗压性能比普通混凝土提高了 21.5%。此外，与无纤维混凝土试样相比，钢纤维的加入使劈裂拉伸性能显著提高了约 101%。此外，由于在混凝土防护罩中使用了钢丝网和纤维，混凝土面板所承受的第一裂缝和断裂冲击能量是非加固混凝土面板的四到六倍。此外，与普通混凝土成分相比，在制造混凝土防护罩时使用所述导电成分可显著改善 SE 性能，最高可达 196%。这项研究强调了设计新型导电混凝土防护罩的潜力，这种防护罩具有卓越的抗冲击性和电磁脉冲屏蔽性，可用于保护关键基础设施。

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引用次数: 0

Cogging torque reduction by utilizing the unequal rotor slot arc method for FSPM Machines 利用不等转子槽弧法降低 FSPM 电机的齿槽转矩

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal

Pub Date : 2024-11-01 DOI: 10.1016/j.asej.2024.103008

Emrah Cetin

Cogging torque is a crucial and offending problem for electric machines that consist permanent magnets. Flux switching permanent magnet (FSPM) machines have magnets embedded inside the stator coils. Due to the interaction between the stator magnetic flux and the rotor steel, cogging torque occurs. To express this interaction, Magnetic Permeance Distribution Model is implemented in this study. To minimize the cogging torque, unequal rotor slot arc (URSA) technique is developed and cogging torque is calculated by using finite element method. An optimization study is performed to get the minimum value of the cogging torque under reasonable output torque. Results prove that, the proposed URSA method have promising outcomes for cogging torque reduction.

齿槽转矩是由永磁体组成的电机的一个关键和棘手问题。磁通开关永磁（FSPM）机器的定子线圈中嵌入了磁铁。由于定子磁通和转子钢之间的相互作用，会产生齿槽转矩。为了表达这种相互作用，本研究采用了磁导分布模型。为尽量减小齿槽转矩，开发了不等转子槽弧 (URSA) 技术，并使用有限元法计算齿槽转矩。为了在合理的输出转矩下获得最小的齿槽转矩值，进行了优化研究。结果证明，所提出的 URSA 方法在降低齿槽转矩方面具有良好的效果。

引用次数: 0

The behavioral smart furniture and its relevance to family emotional dynamics 行为智能家具及其与家庭情感动态的相关性

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal

Pub Date : 2024-11-01 DOI: 10.1016/j.asej.2024.103030

Lina Nageb Fewella

Furniture design could contribute to the emotional and healthy development of the family and society’s well-being. This project utilized family members’ social and behavioral needs to produce interactive furniture that benefited it. A smart residential furniture prototype was produced using local resources, materials, and industrial expertise, revealing its mechanics and challenges. The industrial application aims to produce furniture that helps children with Attention Deficit Hyperactivity Disorder integrate with their family members in daily life. Distance sensors at various heights and positions are utilized to provide illumination responses. The initiative encourages family furniture sharing and hyperactive children to engage with family members. The study offers a comprehensive perspective to designers and manufacturers regarding the potential application of psychological, behavioral, and social design elements in developing a modern, interactive furniture item that contributes to community development, which significantly impacts achieving a sustainable living environment.

家具设计可以促进家庭的情感和健康发展，增进社会福祉。该项目利用家庭成员的社会和行为需求，制作出有益于家庭成员的互动家具。利用当地资源、材料和工业专业知识制作了一个智能住宅家具原型，揭示了其力学原理和面临的挑战。工业应用旨在生产家具，帮助患有注意力缺陷多动障碍的儿童在日常生活中与家人融为一体。不同高度和位置的距离传感器用于提供照明响应。该倡议鼓励家庭共享家具，并鼓励多动儿童与家庭成员互动。这项研究为设计师和制造商提供了一个全面的视角，让他们了解在开发现代互动家具产品时，心理、行为和社会设计元素的潜在应用，从而促进社区发展，对实现可持续的生活环境产生重大影响。

引用次数: 0

Daylighting and energy consumption in museums and bridging the gap by multi-objective optimization 博物馆的采光和能耗以及通过多目标优化缩小差距

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal

Pub Date : 2024-09-04 DOI: 10.1016/j.asej.2024.102944

Mohamed Mostafa R. Ismail , Ashraf Nessim , Fatma Fathy

Museums environment is complicated and defined by indoor air quality, thermal and lighting comfort. Artifacts deterioration is factored by extreme conditions of thermal exposure or excessive lighting. With high control required for exposed old monuments and visitor comfort, museums energy systems reach extreme levels. In this paper, we aim to find the gap in museums high energy loads and reach solutions through architectural design. The paper studies comparison results for different techniques in fifty recent case studies to identify the specific factors that matter most to museum buildings. These factors are implemented simultaneously on one base model in three climatic states by multi-objective optimization. The best option will showcase each climate optimum conditions. The paper introduces optimum architectural procedures optimizing sDA and ASE to minimum 70% and maximum 10% respectively while decreasing thermal load. The results help architects and policy makers achieve daylighting and energy optimization in museums through architecture.

博物馆环境复杂，取决于室内空气质量、热舒适度和照明舒适度。文物的老化是热暴露或过度照明等极端条件造成的。由于需要对暴露在外的古迹和游客的舒适度进行高度控制，博物馆的能源系统达到了极端水平。本文旨在找到博物馆高能耗负荷的差距，并通过建筑设计找到解决方案。本文研究了最近 50 个案例研究中不同技术的比较结果，以确定对博物馆建筑最重要的特定因素。通过多目标优化，这些因素在三种气候状态下的一个基础模型上同时实现。最佳方案将展示每种气候的最佳条件。论文介绍了优化建筑程序，在降低热负荷的同时，将 sDA 和 ASE 分别优化到最低 70% 和最高 10%。这些结果有助于建筑师和政策制定者通过建筑实现博物馆的采光和能源优化。

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引用次数: 0

On the modeling and computation of molecular descriptors of a novel next-generation wonder material γ-graphyne and zig-zag Gamma graphyne nanoribbon 新一代新型神奇材料γ-石墨烯和 "之 "字形伽马石墨烯纳米带的分子描述符建模与计算

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal

Pub Date : 2024-08-24 DOI: 10.1016/j.asej.2024.102868

Abdul Hakeem , Nek Muhammad Katbar , Shah nawaz phulpoto , irfan ali bozdar , Ashiqie Hussain , Sohail Asalam , Fikadu Tesgera Tereda , Hisamuddin Shaikh , Saeed Ullah

Researchers have been trying to synthesize a novel carbon form called Graphyne. For over a decade but with no success. Recently, some researchers have made a breakthrough in generating Carbons elusive allotrope and solved a long-standing problem in carbon materials. This wonder material is created to rival the conductivity of graphene but with control. These results opened new ways of research in the fields of semiconductors, electronics and optics. Topological indices are mathematical descriptors of the Structure of a molecule that can be used to predict its properties. They are derived from the graph theory, which describes the topology of a molecule and its connectivity. γ- graphyne is a specific type of graphyne, which is a carbon-based material similar to graphene. In this paper our focus is on two structures made from hexagonal honeycomb graphite lattices, like γ- graphyne,and Zig-zag Gamma graphyne nanoribbon. The first, second, third and fourth Zagreb indices, the first and second hyper-Zagreb indices, third redefined Zagreb indices, are all computed in this paper. Furthermore mathematical closedform expressions for some of its essential degree-based molecular descriptors are derived. These obtained results will help to investigate the structure–property relationships in γ-Graphyne.

研究人员一直在尝试合成一种名为石墨烯的新型碳。但十多年来一直没有成功。最近，一些研究人员在生成碳这种难以捉摸的同素异形体方面取得了突破性进展，解决了碳材料领域的一个老大难问题。这种神奇的材料可以与石墨烯的导电性相媲美，但却可以控制。这些成果为半导体、电子学和光学领域的研究开辟了新途径。拓扑指数是分子结构的数学描述符，可用于预测其特性。它们源自图论，图论描述了分子的拓扑结构及其连通性。γ-石墨烯是石墨烯的一种特殊类型，是一种与石墨烯类似的碳基材料。在本文中，我们将重点研究由六角蜂窝石墨晶格（如γ-石墨）和之字形伽马石墨纳米带组成的两种结构。本文计算了第一、第二、第三和第四萨格勒布指数，第一和第二超萨格勒布指数，第三重新定义的萨格勒布指数。此外，本文还推导出了一些基本的基于度的分子描述符的数学封闭式表达式。这些结果将有助于研究γ-Graphyne 的结构-性质关系。

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引用次数: 0

Non-Fourier heat and mass transport enhancement by hybrid nanofluid-flow over a non-linearly stretchable surface having variable thickness 厚度可变的非线性拉伸表面上的混合纳米流体流对非傅里叶热量和质量传输的增强作用

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal

Pub Date : 2024-08-21 DOI: 10.1016/j.asej.2024.102980

Sayer Obaid Alharbi , Rai Sajjad Saif , Maryam Haneef , Muhammad Nawaz , Taseer Muhammad

This article uses non-classical Fick's law, non-Fourier's law, and conservation laws for mass and thermal transport. The hybrid nanoparticles Cu and $A l_{2} O_{3}$ are considered. The new correlations among the thermo-physical properties of base fluid, Cu and $A l_{2} O_{3}$ are coupled with simplified nonlinear mathematical models. The resulting models are solved numerically by the finite element method (FEM). The linear shape functions are chosen for the approximation of residual equations. This approximation leads to a nonlinear algebraic system that is linearized by the Picard scheme. The numerical results are ensured to be grid-independent, and convergence is analyzed. The results are validated, and an excellent agreement is obtained between available benchmarks and current outcomes. Thermal solutal relaxation phenomena are responsible for a significant reduction in the transport of heat and mass in Newtonian fluids. These non-Fourier's and non-classical Fick's laws are capable of capturing thermal and solutal elastic phenomena, respectively. Cu and $A l_{2} O_{3}$ simultaneously act as good conductors of heat, and their simultaneous dispersion in base fluid results in a significant rise in thermal conductivity. Numerical experiments have shown that the transport of heat can be optimized by simultaneous suspension of Cu and $A l_{2} O_{3}$ .

本文采用非经典菲克定律、非傅里叶定律以及质量和热传输守恒定律。文章考虑了混合纳米粒子 Cu 和 Al2O3。基础流体、Cu 和 Al2O3 的热物理性质之间的新关联与简化的非线性数学模型相结合。所得模型采用有限元法（FEM）进行数值求解。选择线性形状函数作为残差方程的近似值。这种近似导致一个非线性代数系统，该系统通过 Picard 方案线性化。确保数值结果与网格无关，并对收敛性进行了分析。结果得到了验证，现有基准与当前结果非常吻合。热溶质弛豫现象是牛顿流体中热量和质量传输显著减少的原因。这些非傅里叶定律和非经典菲克定律能够分别捕捉热和溶质弹性现象。铜和 Al2O3 同时是热的良导体，它们同时分散在基质流体中会导致热导率显著上升。数值实验表明，同时悬浮 Cu 和 Al2O3 可以优化热量的传输。

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引用次数: 0

Stability enhancement and EMI mitigation in SSBC by soft switching and slope compensation techniques 利用软开关和斜率补偿技术增强 SSBC 的稳定性并降低 EMI

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal

Pub Date : 2024-08-20 DOI: 10.1016/j.asej.2024.102969

M. Radha , S. Archana

This paper proposes a control technique of soft switching operation or quasi-resonance intrusion along with slope compensation in a conventional Hard Switched Boost Converter (HSBC) to realize the proposed Soft Switched Boost Converter (SSBC) under Current Mode Control (CMC for a part of the switching cycle to mitigate intermittent instabilities, Electro Magnetic Interference (EMI) and to extend the stable operating region. An intensified stability analysis was performed and the viability of the converter was tested with the effect of diversified periodic interference signals and comparative analysis was made between HSBC and SSBC. The impact of switching manifold due to the increase in modes of operation by soft switching was considered. The system dynamics were captured using MATLAB/Simulink, and the results were validated using appropriate experimental setup results. Furthermore, to demonstrate the proposed control technique’s improved stability, theoretical bifurcation analysis was performed in SSBC as Power Factor Correction (PFC) converter.

本文在传统的硬开关升压转换器（HSBC）中提出了一种软开关操作或准谐振侵入的控制技术，同时还提出了斜坡补偿，以实现在电流模式控制（CMC）下部分开关周期的软开关升压转换器（SSBC），从而缓解间歇性不稳定性、电磁干扰（EMI）并扩大稳定工作区域。在多种周期性干扰信号的影响下，对转换器进行了强化稳定性分析和可行性测试，并对 HSBC 和 SSBC 进行了比较分析。此外，还考虑了软开关增加运行模式对开关歧管的影响。使用 MATLAB/Simulink 捕捉了系统动态，并使用适当的实验设置结果对结果进行了验证。此外，为了证明所提出的控制技术提高了稳定性，还对作为功率因数校正（PFC）转换器的 SSBC 进行了理论分岔分析。

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引用次数: 0

Soret-Dufour mechanisms and thermal radiation effects on magnetized SWCNT/MWCNT nanofluid in a convective transport and solutal stratification analysis 对磁化 SWCNT/MWCNT 纳米流体的 Soret-Dufour 机制和热辐射效应的对流传输与溶质分层分析

IF 6 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Ain Shams Engineering Journal

Pub Date : 2024-08-17 DOI: 10.1016/j.asej.2024.102853

Bidemi Olumide Falodun , Ogiboina Ramakrishna , Ahmed Senior Ismail , Tijani Musa Oladipupo , Ogunsanya Tolulope Idiat , Adenekan Ibrahim Oyeyemi , Gurrampati Venkata Ramana Reddy

This research elucidates the mechanisms of Soret-Dufour on magnetized SWCNT/MWCNT nanofluid in a convective transport and solutal stratification analysis. The solutal stratification plays a significant role in this study's heat and mass transfer process. The solutal stratification involves the distribution of nanoparticles within the boundary layer flow regime. The fluid flow was considered to rotate vertically downward/upward in a disk and the physical interpretation is presented as partial differential equations (PDEs). The set of PDEs was first changed into total differential equations before applying the numerical scheme of the spectral relaxation method (SRM). The magnetized SWCNT/MWCNT's numerical simulations were rigorously examined using the iterative techniques of SRM. The crucial role of pertinent flow parameters is graphically illustrated while the calculated values of engineering quantities of interest are tabulated. The azimuthal profile increases due to an increase in the magnetic parameter. An increase in the Prandtl number was found to depreciate the velocity alongside the temperature profile because of the low thermal conductivity possessed by water. A rise in thermal radiation increases the fluid thermal condition by enhancing the temperature profile. The present analysis was compared with the analysis in the literature and was found to be in good agreement.

本研究通过对流传输和溶质分层分析，阐明了磁化 SWCNT/MWCNT 纳米流体的 Soret-Dufour 机理。溶质分层在本研究的传热和传质过程中起着重要作用。溶质分层涉及纳米颗粒在边界层流动机制中的分布。流体流被视为在圆盘中垂直向下/向上旋转，其物理解释为偏微分方程（PDEs）。在应用频谱弛豫法（SRM）数值方案之前，首先将偏微分方程组转换为全微分方程。利用 SRM 的迭代技术对磁化的 SWCNT/MWCNT 进行了严格的数值模拟。相关流动参数的关键作用以图表说明，相关工程量的计算值则以表格形式列出。方位角剖面因磁性参数的增加而增大。由于水的热导率较低，普朗特数的增加会降低速度和温度曲线。热辐射的增加会增强温度曲线，从而改善流体的热状况。本分析与文献分析进行了比较，发现两者非常一致。

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引用次数: 0