International Journal of Thermofluids最新文献_第6页

Stability and regression analysis of MHD radiative flow with different shaped Al2O3nanoparticles in a semi-porous channel 半多孔通道中不同形状al2o3纳米颗粒MHD辐射流稳定性及回归分析

Q1 Chemical Engineering

International Journal of Thermofluids

Pub Date : 2026-01-01 Epub Date: 2025-12-02 DOI: 10.1016/j.ijft.2025.101514

Abdul Awal, Md.Maidul Islam, Md.Sarwar Alam, Sumaiya Akter

Nanofluids have recently gained prominence as advanced working fluids in thermal management and fluid dynamics. Detailed assessment of their thermophysical properties particularly shape effect under thermal radiation is crucial for evaluating heat transfer efficiency of channel flow. This study presents a novel analytical and statistical approach for analyzing and optimizing the unsteady magnetohydrodynamic (MHD) two-dimensional Al₂O₃–water nanofluid flow through a semi-porous channel with expanding and contracting walls, focusing on the influence of nanoparticles’ shape on flow and thermal radiation effect. The partial differential equations governing the flow are simplified into a system of coupled, non-dimensional ordinary differential equations using similarity transformations. An analytical solution is obtained using the power series method, and then analyzed using Hermite–Padé approximation approach. The study explores the impact of several physical parameters including Reynolds number, magnetic parameter, expansion/contraction ratio, Prandtl number, Brinkman number, radiation parameter, nanoparticle volume fraction, and shape factor on the velocity and temperature profiles. Results indicate that platelet-shaped (at

m = 5.7

) nanoparticles yield the highest temperature distribution, while increased nanoparticle concentration over 5 % and shape factor

(m > 5.7)

tend to reduce heat transfer. Stability analysis of the solution confirmed the physically viable solution branch of the heat transfer rate and the singular point of the effective physical parameter.

Additionally, Response Surface Methodology (RSM) is employed to develop a statistical model for optimizing heat transfer performance, where the local Nusselt number is considered the key response variable. The adequacy and predictive capability of the regression model are verified through ANOVA, demonstrating both significance and accuracy, with an R² value of 99.95 %. This integrated approach delivers significant insights into the interaction effects of multiple parameters and supports the design of efficient nanofluid-based thermal systems. This research investigates which shaped nanoparticle provides superior thermal performance in nanofluid-based cooling systems and how the expansion/contraction parameter affect the flow and heat transfer mechanism.

纳米流体作为一种先进的工作流体，近年来在热管理和流体动力学领域获得了突出的地位。详细评估它们的热物性，特别是热辐射下的形状效应，是评估通道流换热效率的关键。本文提出了一种新的分析和统计方法，用于分析和优化非定常磁流体（MHD）二维Al₂O₃-水纳米流体在具有膨胀和收缩壁面的半多孔通道中的流动，重点研究了纳米颗粒形状对流动和热辐射效应的影响。利用相似变换将控制流动的偏微分方程简化为一个耦合的无量纲常微分方程系统。用幂级数法得到了解析解，然后用hermite - pad逼近法进行了分析。研究了雷诺数、磁性参数、膨胀/收缩比、普朗特数、布林克曼数、辐射参数、纳米颗粒体积分数和形状因子等物理参数对速度和温度分布的影响。结果表明，血小板形状（atm=5.7）纳米颗粒的温度分布最高，当纳米颗粒浓度大于5%和形状因子（m>5.7）增加时，传热会减小。解的稳定性分析确定了传热率的物理可行解分支和有效物理参数的奇点。此外，采用响应面法（RSM）建立了优化传热性能的统计模型，其中局部努塞尔数被认为是关键的响应变量。通过方差分析验证回归模型的充分性和预测能力，具有显著性和准确性，R²值为99.95%。这种集成的方法提供了对多个参数相互作用影响的重要见解，并支持高效纳米流体热系统的设计。本研究探讨了哪种形状的纳米颗粒在纳米流体冷却系统中提供了优越的热性能，以及膨胀/收缩参数如何影响流动和传热机制。

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引用次数: 0

Hydrogen absorption in metal hydrides: A dual-head tree-based framework for material class classification 金属氢化物中的氢吸收：材料类别分类的双头树框架

Q1 Chemical Engineering

International Journal of Thermofluids

Pub Date : 2026-01-01 Epub Date: 2026-01-03 DOI: 10.1016/j.ijft.2025.101521

Zaid Allal , Hassan N. Noura , Flavien Vernier , Ola Salman , Khaled Chahine

Metal hydrides represent a highly promising alternative for hydrogen storage due to their favorable absorption properties and relatively moderate requirements in terms of temperature and pressure during the uptake stage. Furthermore, their ability to undergo multiple absorption–desorption cycles without significant degradation makes them particularly well-suited for repeated charge–discharge operations. In this work, we propose a two-headed machine learning framework for the classification of metal hydrides. The first head determines whether a material belongs to the AB family of hydrides. If not, the second head classifies it into one of the remaining categories: MIS, SS, MG, or complex hydrides. This hierarchical modeling strategy, inspired by fault detection and diagnosis in biphasic systems, proved effective in improving classification accuracy. The framework was trained using six tree-based estimators: Random Forest, LightGBM, XGBoost, CatBoost, Gradient Boosting, and Extra Trees. Strong imputation techniques, including the KNN imputer, were also employed to address missing data and ensure robustness. The results demonstrate that for the first head, the Random Forest model achieved an accuracy of 88.6% in identifying the AB family class. For the second head, Gradient Boosting reached 91.61% accuracy, which was further improved to 92.56% after hyperparameter tuning. When compared to previous studies using the same dataset, our framework exhibits significantly stronger performance. Moreover, its predictions were validated through the integration of explainable artificial intelligence (XAI) methods, ensuring both interpretability and reliability. This framework will be further optimized to extend beyond class-level identification toward the precise prediction of hydride composition formulas, with the aim of better supporting the design of materials with enhanced hydrogen absorption capacities.

由于金属氢化物具有良好的吸收特性，并且在吸收阶段对温度和压力的要求相对适中，因此金属氢化物是一种非常有前途的储氢方法。此外，它们经历多次吸收-解吸循环而没有明显降解的能力使它们特别适合重复充放电操作。在这项工作中，我们提出了一个用于金属氢化物分类的双头机器学习框架。第一个头确定材料是否属于AB族氢化物。如果不是，第二个头部将其分类为其余类别之一：MIS， SS， MG或复合氢化物。这种分层建模策略受到双相系统故障检测和诊断的启发，有效地提高了分类精度。该框架使用六个基于树的估计器进行训练：Random Forest， LightGBM, XGBoost, CatBoost， Gradient Boosting和Extra Trees。强输入技术，包括KNN输入器，也被用来解决缺失的数据和确保鲁棒性。结果表明，对于第一个头部，随机森林模型在识别AB族类方面达到了88.6%的准确率。对于第二个头部，Gradient Boosting的准确率达到了91.61%，经过超参数调优后进一步提高到92.56%。与之前使用相同数据集的研究相比，我们的框架表现出明显更强的性能。此外，通过可解释人工智能（XAI）方法的集成验证了其预测，确保了可解释性和可靠性。该框架将进一步优化，以超越类别级别的识别，扩展到氢化物组成公式的精确预测，以更好地支持具有增强吸氢能力的材料的设计。

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引用次数: 0

Exploring the impact of unit cell size on fluid dynamics in lattice structures: Experimental and numerical insights 探索单元胞大小对晶格结构中流体动力学的影响：实验和数值见解

Q1 Chemical Engineering

International Journal of Thermofluids

Pub Date : 2026-01-01 Epub Date: 2025-12-31 DOI: 10.1016/j.ijft.2025.101543

Leonardo Bernardini , Stefano Piacquadio , Kai-Uwe Schröder , Mauro Mameli , Paolo Di Marco , Sauro Filippeschi

Advanced manufacturing techniques have made it possible to customize the geometry of solids unit cells, creating various architected materials. One type of such material is the strut or surface-based lattice. In this work, we investigated fluid flow through two lattice structure topologies, body-centered cubic (bcc) and face-centered cubic with vertical strut (f₂ccz). The goal is to understand the effect of the unit cell size and cell orientation on pressure drops and permeability. By doing this, we aim to clarify how the scale of the unit cell influences the treatment of lattice structures as porous media. Through the experimental campaign, we characterized the pressure drops across these structures and performed dimensionless analyses of the measurements. The investigation involved a numerical model to simulate fluid flow behavior at low velocities and determine permeability using the Darcy equation. Finally, we coupled the experimental results with numerical simulations to assess the inertial coefficient in the Darcy-Forchheimer correlation. The results showed that, given the cell topology, porosity and flow direction, it is possible to uniquely determine the relationship between velocity and pressure losses as a function of hydraulic diameter. Additionally, the permeability ratio to the square of the hydraulic diameter, with fixed topology, porosity and flow direction, resulted in a constant.

先进的制造技术使得定制固体单元格的几何形状成为可能，从而创造出各种建筑材料。这种材料的一种是支撑或基于表面的晶格。在这项工作中，我们研究了流体在两种晶格结构拓扑中的流动，即体心立方（bcc）和面心立方（f2ccz）。目的是了解单位孔的尺寸和孔的方向对压降和渗透率的影响。通过这样做，我们的目的是澄清单位胞的规模如何影响晶格结构作为多孔介质的处理。通过实验，我们对这些结构的压降进行了表征，并对测量结果进行了无因次分析。该研究涉及一个数值模型来模拟流体在低速下的流动行为，并使用达西方程确定渗透率。最后，我们将实验结果与数值模拟相结合，评估了Darcy-Forchheimer相关中的惯性系数。结果表明，在给定池的拓扑结构、孔隙度和流动方向的情况下，可以唯一地确定速度和压力损失之间的关系，作为水力直径的函数。此外，在拓扑结构、孔隙度和流动方向固定的情况下，渗透率与水力直径的平方比为常数。

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引用次数: 0

Thermodynamic optimization of magnetic hyperthermia via elasticity tuning in non-Newtonian blood flow 磁热疗在非牛顿血流中的弹性调节热力学优化

Q1 Chemical Engineering

International Journal of Thermofluids

Pub Date : 2026-01-01 Epub Date: 2025-11-19 DOI: 10.1016/j.ijft.2025.101499

Ali Ahmadi Azar, Zahra Poolaei Moziraji

The Weissenberg number (We) quantifies the relative dominance of elastic over viscous forces in tangent‐hyperbolic fluids such as blood and is classically divided into three regimes—low to moderate elasticity (We ≈ 0.01–0.1), transitional elasticity (We ≈ 0.1–1.0), and high elasticity (We ≈ 1.0–2.0). A unified analysis reveals that average velocity decreases by 0.17 %, 1.82 %, and 2.27 % across these regimes (from 0.0968 to 0.0927), skin friction intensifies by 0.23 %, 2.43 %, and 3.10 % (from –1.1616 to –1.0957), Nusselt number rises by 0.06 %–0.86 % (from –5.6063 to –5.5192), entropy‐generation rates grow by 0.14 %–2.08 % (from 0.0233 to 0.0242), and temperature distributions shift by less than 0.05 %. Progressive viscoelasticity restructures velocity profiles via boundary‐layer thinning and 0.17–2.27 % velocity reduction; coupled radiation–magnetic effects leave temperature invariant (<0.05 % variation); skin friction and Nusselt number respond through amplified shear and thermal gradients (increasing by 0.23–3.10 % and 0.06–0.86 %, respectively); entropy generation rises by 0.14–2.08 % with viscous dissipation dominating beyond We ≈ 1.0; the critical We for irreversibility shift is ≈1.0; and entropy minimization in magnetic hyperthermia is achieved in the low elasticity regime (We ≤ 0.1). The novelty of the governing equations necessitates validation via residual error assessment of the computational solutions.

Weissenberg数（We）量化了在正切双曲流体（如血液）中弹性力相对于粘性力的相对优势，通常分为三种状态——低至中等弹性（We≈0.01-0.1）、过渡弹性（We≈0.1-1.0）和高弹性（We≈1.0-2.0）。统一分析表明，在这些区域（从0.0968到0.0927），平均速度分别降低了0.17%、1.82%和2.27%，表面摩擦力分别增强了0.23%、2.43%和3.10%（从-1.1616到-1.0957），努塞尔数增加了0.06% - 0.86%（从-5.6063到-5.5192），熵产率增加了0.14% - 2.08%（从0.0233到0.0242），温度分布变化不到0.05%。渐进粘弹性通过边界层变薄和0.17 - 2.27%的速度降低来重构速度剖面；耦合辐射-磁效应使温度保持不变（<； 0.05%变化）；表面摩擦和努塞尔数通过剪切梯度和热梯度的放大来响应（分别增加0.23 - 3.10%和0.06 - 0.86%）；当We≈1.0以上时，熵产增加0.14 ~ 2.08%；不可逆性位移的临界We≈1.0；磁热疗的熵最小化在低弹性状态下实现（We≤0.1）。控制方程的新颖性需要通过计算解的残差评估来验证。

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引用次数: 0

Passive control of turbulent flow around a circular cylinder using slots at separation points 利用分离点上的狭缝对圆柱周围湍流进行被动控制

Q1 Chemical Engineering

International Journal of Thermofluids

Pub Date : 2026-01-01 Epub Date: 2025-12-12 DOI: 10.1016/j.ijft.2025.101531

Irfan Ahmad Sheikh , Emad Elnajjar , Mahmoud Elgendi

Flow control is essential in various engineering applications and environmental contexts to ensure safety, improve efficiency, and enhance overall performance. This study examines the influence of slot configurations at turbulent flow separation points on a circular cylinder and their ability to passively control vortex shedding at a high Reynolds number (Re) = 3.6 × 10⁶. An unsteady Reynolds-Averaged Navier–Stokes (URANS) simulation using a realizable k–ε turbulence model with standard wall treatment was employed to evaluate the aerodynamic behavior of two slot geometries, straight and curved, under identical flow conditions. The results reveal that the introduction of slots substantially modifies the wake structure and aerodynamic loading, increasing the mean drag coefficient from 0.379 for the smooth cylinder to 0.99 and 1.5 for the straight and curved slot configurations, respectively. Similarly, the lift coefficient amplitude increased nearly tenfold, from ±0.1 to approximately ±1 for the curved-slotted cylinder. These findings confirm that slot-induced flow reattachment and momentum exchange enhance vortex coherence and wake stability, providing a robust passive flow-control mechanism. The proposed configuration demonstrates strong potential for integration into bluff-body-based systems such as bladeless wind turbines and tidal energy harvesters, where enhanced lift and controlled drag can improve energy capture efficiency and structural performance.

在各种工程应用和环境环境中，流量控制对于确保安全、提高效率和提高整体性能至关重要。本文研究了在高雷诺数(Re) = 3.6 × 10 26时，圆柱湍流分离点的狭缝构型对其被动控制旋涡脱落的影响。采用可实现的k -ε湍流模型和标准壁面处理，采用非定常reynolds - average Navier-Stokes （URANS）模拟，对两种几何形状的直槽和弯槽在相同流动条件下的气动性能进行了评估。结果表明，狭缝的引入极大地改变了尾流结构和气动载荷，使平均阻力系数从光滑圆柱体的0.379提高到直线和弯曲狭缝构型的0.99和1.5。同样，曲线开槽圆柱的升力系数幅值增加了近10倍，从±0.1增加到约±1。这些发现证实了狭缝诱导的流动再附着和动量交换增强了涡相干性和尾迹稳定性，提供了一个强大的被动流动控制机制。该设计方案展示了将其集成到基于崖体的系统（如无叶片风力涡轮机和潮汐能收集器）的巨大潜力，在这些系统中，增强升力和控制阻力可以提高能量捕获效率和结构性能。

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引用次数: 0

Analysis of thermal and concentration transport in unsteady MHD squeezing nanofluid flow under the influence of chemical reaction and joule heating 化学反应和焦耳加热影响下非定常MHD压缩纳米流体的热输运和浓度输运分析

Q1 Chemical Engineering

International Journal of Thermofluids

Pub Date : 2026-01-01 Epub Date: 2025-12-23 DOI: 10.1016/j.ijft.2025.101537

Sharad Sinha , Prachi Gupta , Saleem Nasir , K. Loganathan , Kavita Jat , Abdallah Berrouk

This research investigates the unsteady magnetohydrodynamic (MHD) squeezing flow of a viscous incompressible nanofluid enclosed between two parallel plates and affected by an inclined magnetic field. Suction/injection at the lower plate is also considered to enhance control over the flow. Such flow occurs in microfluidics, lubrication, material processing, and cooling devices, which indicates the need to introduce transport mechanisms at small scales. The flow is driven by the motion of the lower plate translating in its own plane, while the upper plate moves perpendicularly. The flow governing equations are converted to a set of coupled, nonlinear ordinary differential equations through similarity transformations. These reduced equations are then numerically solved using the bvp4c MATLAB solver. Validation is achieved for the obtained outcomes by comparing with existing literature. The study presents comprehensive parametric analyses of velocity, temperature, and concentration profiles through their graphical representations under varying parameter conditions. When the squeezing parameter increases, the velocity profile improves in both suction and injection cases. For the Schmidt parameter (0.1 ≤ Sc≤ 1.0), the concentration profile decreases ϕ(η = 0.3) = 0.200695 to ϕ(η = 0.3) = 0.163544) in the injection case. The temperature profile enhances, but the concentration profile declines when distance parameter goes from δ=0.1 to δ=0.8. Furthermore, detailed analyses of skin friction, Nusselt number, and Sherwood number are provided at both plates to offer more profound insights into the physical phenomena, with potential implications for applications in microfluidic systems, cooling technologies, and industrial fluid processes.

本文研究了粘滞不可压缩纳米流体在倾斜磁场作用下的非定常磁流体压缩流动。下部板的吸入/喷射也被认为可以加强对流动的控制。这种流动发生在微流体、润滑、材料加工和冷却装置中，这表明需要在小尺度上引入输送机制。流动是由下板在其自身平面内平移的运动驱动的，而上板是垂直运动的。通过相似变换将流动控制方程转化为一组耦合的非线性常微分方程。然后使用bvp4c MATLAB求解器对这些简化方程进行数值求解。通过与已有文献的比较，对所得结果进行验证。该研究通过在不同参数条件下的图形表示，对速度、温度和浓度剖面进行了全面的参数分析。随着挤压参数的增大，吸入和喷射工况下的速度分布都有所改善。当Schmidt参数为0.1≤Sc≤1.0时，注入情况下的φ (η = 0.3) = 0.200695减小到φ (η = 0.3) = 0.163544。当距离参数从δ=0.1增大到δ=0.8时，温度曲线增大，浓度曲线减小。此外，在两个板上提供了皮肤摩擦，努塞尔数和舍伍德数的详细分析，以提供对物理现象的更深刻的见解，对微流体系统，冷却技术和工业流体过程的应用具有潜在的意义。

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引用次数: 0

Numerical and artificial neural network time-series modeling of Casson–Jeffrey nanofluid flow over linear and nonlinear stretching surfaces in porous media 多孔介质中线性和非线性拉伸表面上Casson-Jeffrey纳米流体流动的数值和人工神经网络时间序列建模

Q1 Chemical Engineering

International Journal of Thermofluids

Pub Date : 2026-01-01 Epub Date: 2025-12-23 DOI: 10.1016/j.ijft.2025.101534

Yogesh K. , Varatharaj K. , Tamizharasi R.

This study investigates the synergistic influence of magnetohydrodynamics, thermal radiation and porous medium on the transport of Casson–Jeffrey hybrid nanofluid over both linear and nonlinear stretching sheets. The governing equations are solved numerically using the Runge–Kutta with Shooting method and the outcomes are validated with a multilayer perceptron artificial neural network in neural network time series. The key controlling parameters include magnetic number, Casson parameter, Jeffrey parameter, buoyancy ratio, radiation parameter, Brownian motion, thermophoresis, Prandtl number and heat generation. The results demonstrate that increasing the magnetic parameter from 0.1 to 0.4 enhances the skin friction magnitude by approximately 12% for linear stretching and 15% for nonlinear stretching. Similarly, raising the radiation parameter from 0.1 to 0.4 increases skin friction magnitude by about 10% in the linear case and 25% in the nonlinear case. In contrast, the Nusselt number decreases when the Brownian motion parameter rises from 0.1 to 0.4, leading to an almost 11% reduction in both linear and nonlinear flows. Thermophoresis effects further suppress the heat transfer rate, showing a 5% decline when its value increases from 0.1 to 0.4. Neural network validation confirms the accuracy of the solver, with regression coefficients very close to unity

R \approx 0.9999

and mean square error values as low as

1.84 \times 1 0^{- 6}

. These findings underline the physical importance of magnetic, radiative, and porous medium effects in hybrid nanofluid transport and demonstrate the effectiveness of artificial intelligence tools for predictive modeling. Future research can extend this framework to unsteady, three-dimensional and experimentally validated configurations.

本文研究了磁流体力学、热辐射和多孔介质对卡森-杰弗里混合纳米流体在线性和非线性拉伸片上输运的协同影响。采用龙格-库塔射击法对控制方程进行数值求解，并用多层感知器人工神经网络在神经网络时间序列中对结果进行验证。关键控制参数包括磁数、卡森参数、杰弗里参数、浮力比、辐射参数、布朗运动、热游、普朗特数和产热。结果表明，将磁参量从0.1增加到0.4，在线性拉伸情况下，表面摩擦强度提高约12%，在非线性拉伸情况下，表面摩擦强度提高约15%。同样，将辐射参数从0.1提高到0.4，在线性情况下，皮肤摩擦值增加约10%，在非线性情况下，皮肤摩擦值增加约25%。相反，当布朗运动参数从0.1上升到0.4时，努塞尔数减少，导致线性和非线性流动都减少了近11%。热泳效应进一步抑制了传热速率，当传热速率从0.1增加到0.4时，传热速率下降5%。神经网络验证证实了求解器的准确性，回归系数非常接近单位R≈0.9999，均方误差值低至1.84×10−6。这些发现强调了磁性、辐射和多孔介质效应在混合纳米流体输运中的物理重要性，并证明了人工智能工具用于预测建模的有效性。未来的研究可以将该框架扩展到非定常、三维和实验验证的构型。

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引用次数: 0

Exploring the impact of variable viscosity on thermal mechanics in Casson hybrid nanofluid flow in a porous channel 探讨变粘度对多孔通道中卡森混合纳米流体流动热力学的影响

Q1 Chemical Engineering

International Journal of Thermofluids

Pub Date : 2026-01-01 Epub Date: 2025-11-29 DOI: 10.1016/j.ijft.2025.101513

Annapurna Tarapuram , Syed Mohiuddin , Suneetha Kolasani , M. Karuna Prasad

This study explores the mixed convective and heat transfer flow characteristics of a Casson hybrid nanofluid, consisting of gold (Au) and titanium (Ti) nanoparticles suspended in blood, traversing a vertical channel within a porous medium. Motivated by the growing relevance of nanofluids in biomedical applications, particularly in targeted drug delivery and hyperthermia-based cancer treatments, this work aims to understand how variable viscosity and thermal conductivity influence heat transfer enhancement. The research addresses a key gap in the literature by modeling a non-Newtonian blood-based hybrid nanofluid using Casson fluid theory, which better represents the rheological properties of blood compared to Newtonian assumptions. The governing nonlinear momentum and energy equations are obtained and translated by similarity transformations, and hence, solved numerically using MATLAB's BVP5C technique. Quantitative results show that the incorporation of nanoparticles enhances the heat transfer rate by up to 21.7 % compared to the nanofluid and 46.06 % to the viscous fluid.

Additionally, variable viscosity significantly modulates flow velocity, while variable thermal conductivity sharply constrains thermal diffusion. Velocity and temperature contour plots, accompanied by the tabulated skin friction and Nusselt number, provide a detailed overview of parameter effects. The novelty of this work lies in the absorption of blood-based Casson hybrid nanofluid with variable thermophysical properties, enabling a more realistic model for biomedical heat transfer processes. This model holds promise for optimizing cooling techniques in therapeutic procedures and designing advanced drug delivery systems.

本研究探讨了卡森混合纳米流体的混合对流和传热流动特性，该流体由悬浮在血液中的金（Au）和钛（Ti）纳米颗粒组成，在多孔介质中穿过垂直通道。受纳米流体在生物医学应用中日益增长的相关性的激励，特别是在靶向药物输送和基于高温的癌症治疗中，这项工作旨在了解可变粘度和导热性如何影响传热增强。该研究利用卡森流体理论对非牛顿血液混合纳米流体进行建模，填补了文献中的一个关键空白。与牛顿假设相比，卡森流体理论更好地代表了血液的流变特性。通过相似变换得到控制非线性动量和能量方程并进行转换，从而利用MATLAB的BVP5C技术进行数值求解。定量结果表明，与纳米流体相比，纳米颗粒的加入使换热率提高了21.7%，比粘性流体提高了46.06%。此外，变粘度显著调节流速，而变热导率严重限制热扩散。速度和温度等高线图，加上表示的表面摩擦和努塞尔数，提供了参数影响的详细概述。这项工作的新颖之处在于吸收具有可变热物理性质的基于血液的卡森混合纳米流体，从而为生物医学传热过程提供更现实的模型。该模型有望优化治疗过程中的冷却技术和设计先进的药物输送系统。

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引用次数: 0

Enhanced heat transport in magneto-nanofluidic thermal systems: adiabatic block effects in grooved channels and ANN modeling 磁纳米流体热系统中增强的热传递：沟槽通道中的绝热块效应和人工神经网络建模

Q1 Chemical Engineering

International Journal of Thermofluids

Pub Date : 2026-01-01 Epub Date: 2025-12-02 DOI: 10.1016/j.ijft.2025.101515

Dipak Kumar Mandal , Nirmal K. Manna , Nirmalendu Biswas , Tansu Rudra , Rajesh Kumar , Ali Cemal Benim

This study investigates heat transfer enhancement in magneto-nanofluidic systems through the strategic placement of adiabatic blocks in grooved channels. Using CuOH₂O nanofluid in a bottom-heated channel with circular expansion, we examine the complex interactions between forced convection, magnetic fields, and buoyancy effects. Through systematic numerical analysis, we explore the combined influences of Rayleigh, Reynolds, and Hartmann numbers on thermal performance. Our findings reveal significant heat transfer enhancement (up to 137 %) under optimal conditions, particularly with vertical magnetic field orientation at Re = 100 and Ha = 30. The results demonstrate how adiabatic blocks modify flow structures, with larger blocks diminishing vortex intensity while elevated Ra generates secondary vortices that interact with primary circulations. Magnetic field effects show notable dependence on orientation, with vertical fields generally promoting better heat transfer than horizontal configurations. To complement the numerical analysis, we develop a predictive model using Artificial Neural Network (ANN) for Nusselt numbers across various operating conditions, achieving over 99 % accuracy. The integrated computational-ANN approach offers significant advancements in optimizing thermal systems in various areas, ranging from electronics cooling to microfluidic devices.

本研究通过在沟槽通道中策略性地放置绝热块来研究磁纳米流体系统中的传热增强。利用CuOH2O纳米流体在底部加热的圆形膨胀通道中，我们研究了强制对流、磁场和浮力效应之间的复杂相互作用。通过系统的数值分析，探讨了瑞利数、雷诺数和哈特曼数对热工性能的综合影响。我们的研究结果表明，在最佳条件下，特别是在Re = 100和Ha = 30的垂直磁场方向下，传热增强显著（高达137%）。结果表明，绝热块如何改变流动结构，较大的块降低了涡强度，而升高的Ra产生了与初级环流相互作用的二次涡。磁场效应明显依赖于取向，垂直磁场通常比水平磁场促进更好的传热。为了补充数值分析，我们使用人工神经网络（ANN）开发了一个预测模型，用于各种操作条件下的努塞尔数，准确率超过99%。综合计算-人工神经网络方法在优化各个领域的热系统方面取得了重大进展，从电子冷却到微流体装置。

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引用次数: 0

Mixed convective two phase flow of an electrically conducting micropolar nanofluid in a double lid-driven square cavity 双盖驱动方形腔中导电微极纳米流体的混合对流两相流动

Q1 Chemical Engineering

International Journal of Thermofluids

Pub Date : 2026-01-01 Epub Date: 2025-11-22 DOI: 10.1016/j.ijft.2025.101508

Vasileios C. Loukopoulos , Georgios C. Bourantas , Vasileios P. Georgopoulos , Vasilis N. Burganos

We study the non-stationary, incompressible, laminar mixed-convection flow in a double lid-driven square enclosure filled with an electrically conducting micropolar nanofluid under the influence of an external magnetic field. The aim is to enhance understanding of heat and mass transport phenomena in nanofluids by examining the impact of key flow parameters – including the Grashof, Hartmann, Reynolds, and Prandtl numbers, as well as the micropolar material parameter, lid-motion parameter, Brownian motion, buoyancy ratio, and thermophoresis – on heat and mass transfer characteristics, expressed through local and average Nusselt and Sherwood numbers, streamlines, isotherms, microrotation, and concentration contours. The nanofluid is modeled as a two-phase mixture following a modified form of Buongiorno’s framework, which incorporates nanoparticle redistribution via an advection–diffusion concentration equation coupled with the Navier–Stokes equations. The governing system is solved numerically using a meshless point collocation method (MPCM), where spatial derivatives are computed through the Discretization-Corrected Particle Strength Exchange (DC PSE) technique, and transient terms are approximated using the Runge–Kutta–Fehlberg (RKF) scheme. This work is the first to couple Buongiorno’s two-phase nanofluid model with micropolar effects and magnetohydrodynamic (MHD) forces in a double lid-driven cavity. The results demonstrate that buoyancy enhancement (higher Gr) strengthens convection, whereas magnetic damping (higher Ha) suppresses it by flattening streamlines and thickening thermal layers. Tilting the magnetic field toward the vertical direction restores circulation and enhances heat transfer. Increasing the micropolar coupling parameter (K) augments microrotation and improves both heat and mass transport, partially counteracting magnetic damping. The lid-motion parameter (

λ

) governs flow symmetry: co-directional motion enhances, while counter-motion weakens convection, whereas higher nanoparticle concentration (

ϕ

) further boosts thermal performance due to increased effective conductivity.

我们研究了在外加磁场影响下，在一个充满导电微极纳米流体的双层盖子驱动的方形外壳中，非平稳、不可压缩、层流混合对流的流动。目的是通过检查关键流动参数（包括Grashof、Hartmann、Reynolds和Prandtl数，以及微极性材料参数、薄膜运动参数、布朗运动、浮力比和热电泳）对传热和传质特性的影响，通过局部和平均努塞尔和舍伍德数、流线、等温线、微旋转和浓度等高线来表达，从而增强对纳米流体中热和质量传递现象的理解。纳米流体被建模为遵循Buongiorno框架的改进形式的两相混合物，其中通过平流-扩散浓度方程和Navier-Stokes方程结合纳米颗粒再分配。控制系统采用无网格点配点法（MPCM）进行数值求解，其中通过离散化校正粒子强度交换（DC PSE）技术计算空间导数，并使用Runge-Kutta-Fehlberg （RKF）格式逼近瞬态项。这项工作是第一次将Buongiorno的两相纳米流体模型与微极效应和磁流体动力（MHD）力在双盖驱动腔中耦合起来。结果表明，浮力增强（更高的Gr）增强对流，而磁阻尼（更高的Ha）通过平坦流线和增厚热层来抑制对流。将磁场向垂直方向倾斜可以恢复循环并增强传热。增加微极性耦合参数(K)可以增强微旋转，改善热量和质量输运，部分抵消磁阻尼。盖子运动参数（λ）控制流动对称性：共向运动增强，而反运动减弱对流，而更高的纳米颗粒浓度（φ）进一步提高热性能，因为增加了有效导电性。

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引用次数: 0