International Journal of Thermofluids最新文献_第2页

Numerical simulation of boiling in wick structures: Comparative analysis of mono-, Bi-, and hybrid porous media 芯结构中沸腾的数值模拟：单、双和混合多孔介质的比较分析

Q1 Chemical Engineering

International Journal of Thermofluids

Pub Date : 2026-03-01 Epub Date: 2026-01-20 DOI: 10.1016/j.ijft.2026.101564

M.E. Nimvari , T. Persoons , M.J. Gibbons

Efficient thermal management is critical in high-power electronic and energy systems, where overheating can lead to performance degradation or material failure. Capillary-driven boiling in porous media is a promising passive cooling solution. The advent of advanced fabrication methods, such as additive and subtractive manufacturing, enables controlled fabrication of porous structure geometry. However, limited research exists to numerically guide porous structure design and explore the complex pore-scale two-phase interplay during the boiling phenomena. The present work provides an in-depth pore-scale numerical investigation of capillary-fed boiling in three porous configurations: monoporous, biporous, and hybrid (combining mono- and biporous) media. Simplified cluster geometries were used to model complex biporous and hybrid structures, and simulations were carried out spanning heat flux levels from 1 to 50 W/cm², validated against experimental data. At low heat fluxes, monoporous and hybrid wicks outperform biporous ones due to reduced vapor entrapment. However, at high heat fluxes, biporous structures exhibit superior performance, thanks to their higher permeability and stronger capillary pumping, which enhance vapor removal and liquid replenishment. Under the peak tested heat flux of 50 W/cm², the biporous media achieves the lowest wall superheat (∼15 K) and vapor saturation (∼0.25), indicating the highest resistance to dry-out. The hybrid wick demonstrates the best performance under low to moderate heat fluxes, whereas at high heat flux levels it exhibits intermediate performance, benefiting from both monoporous and biporous characteristics. The results in this work elucidate the complex two-phase boiling phenomena in varied porous structure geometries that have been commonly experimentally applied. As such, it may serve as a design guide for future advanced wick structures in high-performance cooling systems.

在大功率电子和能源系统中，高效的热管理至关重要，因为过热会导致性能下降或材料失效。多孔介质中毛细管驱动沸腾是一种很有前途的被动冷却解决方案。先进制造方法的出现，如增材制造和减法制造，使多孔结构几何形状的控制制造成为可能。然而，在数值指导多孔结构设计和探索复杂孔隙尺度下的两相相互作用方面的研究有限。目前的工作对三种多孔结构(单孔、双孔和混合（单孔和双孔结合）介质中的毛细管沸腾进行了深入的孔隙尺度数值研究。采用简化的团簇几何形状来模拟复杂的双孔和杂化结构，并在1至50 W/cm²的热流密度范围内进行了模拟，并与实验数据进行了验证。在低热通量下，由于减少了蒸汽夹持，单孔和混合芯优于双孔芯。然而，在高热流密度下，双孔结构表现出更好的性能，因为它们具有更高的渗透率和更强的毛细管泵送，从而增强了蒸汽的去除和液体的补充。在峰值测试热通量为50 W/cm²时，双孔介质达到最低的壁过热度（~ 15 K）和蒸汽饱和度（~ 0.25），表明具有最高的抗干性。混合灯芯在低至中等热流流下表现出最佳性能，而在高热流流下表现出中等性能，受益于单孔和双孔特性。本工作的结果阐明了在不同的多孔结构几何形状中复杂的两相沸腾现象，这些现象在实验中已得到普遍应用。因此，它可以作为高性能冷却系统中未来先进芯结构的设计指南。

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引用次数: 0

Modeling the role of interfacial layer in free convective axisymmetric MHD flow over a heated rotating cone in non-Newtonian based ternary hybrid nanofluids 非牛顿三元混合纳米流体加热旋转锥上自由对流轴对称MHD流动中界面层作用的模拟

Q1 Chemical Engineering

International Journal of Thermofluids

Pub Date : 2026-03-01 Epub Date: 2025-12-26 DOI: 10.1016/j.ijft.2025.101538

Yihui Ma, Nour Mamoun Awad, Ayesha Rashed Saif Rashed Alsalmi, Noor Ahmad Mohammad, Ahad Rashed Saif Alsalmi, Qasem M. Al-Mdallal, S. Saranya

This research addresses the influence of the solid–liquid interface layer on free convection flow and heat transfer of non-Newtonian-based ternary hybrid nanofluids over a rotating vertical cone within a curvilinear coordinate framework. The cone is placed upside down and is uniformly heated while rotating at a constant angular velocity. It is submerged in a ternary hybrid nanofluid of sodium alginate containing

A l_{2} O_{3}, Ti O_{2} and Si O_{2}

nanoparticles. The non-Newtonian Casson fluid model is selected as the base fluid model to study the behavior of fluids. Governing equations for mass, momentum and energy are derived and similarity transformed into a dimensionless form. Using MATLAB's BVP4C solver, the transformed governing nonlinear equations are solved numerically. The study focuses on the impacts of interfacial layer thickness, Casson parameter, magnetic field strength, and nanoparticle concentration on flow and thermal fields. The findings indicate that the thermal conductivity ratio has a more pronounced effect on thermal conductivity than nanoparticle size. The interfacial layer's thickness and its thermal conductivity ratio confirm that it can modulate the velocity and the temperature fields. This study presents a comprehensive imaging approach to thermal systems incorporating non-Newtonian effects, magnetic effects, and interfacial effects for enhanced functional systems.

本研究在曲线坐标框架内研究了固液界面层对非牛顿三元杂化纳米流体在旋转垂直锥上自由对流流动和换热的影响。圆锥体倒置放置，以恒定的角速度旋转时均匀加热。将其浸泡在含有Al2O3、tio2和sio2纳米颗粒的海藻酸钠三元杂化纳米流体中。选择非牛顿卡森流体模型作为研究流体行为的基础流体模型。导出了质量、动量和能量的控制方程，并将相似性转化为无量纲形式。利用MATLAB的BVP4C求解器对变换后的非线性控制方程进行数值求解。重点研究了界面层厚度、卡森参数、磁场强度和纳米颗粒浓度对流动场和热场的影响。研究结果表明，导热系数比纳米颗粒尺寸对导热系数的影响更为显著。界面层厚度和导热系数证实了界面层对速度场和温度场的调节作用。本研究提出了一种综合的热系统成像方法，包括非牛顿效应、磁效应和增强功能系统的界面效应。

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引用次数: 0

Data-driven prediction and multi-objective optimization of pemfc performance using an ANN–GA hybrid model 基于ANN-GA混合模型的pemfc性能数据驱动预测与多目标优化

Q1 Chemical Engineering

International Journal of Thermofluids

Pub Date : 2026-03-01 Epub Date: 2026-02-09 DOI: 10.1016/j.ijft.2026.101580

Arom Boekfah , Chayanid Seanglumlert , Supachai Rumnum , Siripat Rattanaphan , Wonsiri Punurai , Chakrit Suvanjumrat

Proton exchange membrane fuel cells (PEMFCs) are regarded as a key clean energy technology for transportation, portable power devices, and stationary power generation due to their high efficiency, low operating temperature, and zero-emission characteristics. Improving PEMFC performance while reducing system cost remains a critical challenge, requiring accurate prediction tools and robust optimization strategies. This study proposes a novel, unified artificial neural network–genetic algorithm (ANN–GA) framework for simultaneous performance prediction and optimization of PEMFC systems. A multilayer perceptron ANN, with its architecture and hyperparameters optimized using a genetic algorithm, was trained using 239 experimentally obtained datasets to predict cell voltage (V) and power density (I). The model accounts for key operating and design parameters, including hydrogen flow rate (

Q_{H_{2}}

), anode relative humidity (

R H_{a}

), anode back pressure (

P_{a}

), cell operating temperature (

T_{P E M F C}

), anode stoichiometric ratio (

λ_{a}

), oxygen flow rate (

Q_{O_{2}}

), cathode relative humidity (

R H_{c}

), cathode back pressure (

P_{c}

), stack number (n), active area (A), and current density (J). Sensitivity analysis revealed that operating temperature is the most influential factor affecting PEMFC performance, followed by stack number. The optimized ANN exhibited excellent predictive accuracy, achieving a coefficient of determination of R² = 0.99868 and a mean squared error of 0.0007655, with a mean absolute prediction error of 6.27% across the independent ANN test dataset, corresponding to a coefficient of determination of R² = 0.99868. For the optimization stage, the trained ANN was coupled with a genetic algorithm to perform multi-objective optimization, in which PEMFC performance indicators and cost-related outputs were simultaneously predicted and subsequently aggregated using a weighted-sum strategy to identify an optimal trade-off operating condition. The proposed framework represents a distinct advancement over existing data-driven PEMFC models, offering a computationally efficient, experimentally validated, and practically deployable tool for the design and optimization of high-performance, cost-effective PEMFC systems for next-generation hydrogen energy applications.

质子交换膜燃料电池（pemfc）以其高效、低工作温度和零排放的特点，被认为是交通运输、便携式电力设备和固定式发电的关键清洁能源技术。在降低系统成本的同时提高PEMFC性能仍然是一个关键挑战，需要准确的预测工具和稳健的优化策略。本研究提出了一种新的、统一的人工神经网络遗传算法（ANN-GA）框架，用于同时预测和优化PEMFC系统的性能。利用239个实验数据集训练多层感知器ANN，并对其结构和超参数进行遗传算法优化，以预测电池电压(V)和功率密度(I)。该模型考虑了关键的操作和设计参数，包括氢流量（QH2）、阳极相对湿度（RHa）、阳极背压（Pa）、电池工作温度（TPEMFC）、阳极化学计量比（λa）、氧流量（QO2）、阴极相对湿度（RHc）、阴极背压（Pc）、堆数(n)、有效面积(A)和电流密度(J)。灵敏度分析表明，工作温度是影响PEMFC性能的最大因素，其次是堆叠数。优化后的人工神经网络具有优异的预测精度，在独立的人工神经网络测试数据集上的平均绝对预测误差为6.27%，对应的决定系数为R²= 0.99868，其决定系数为0.0007655。在优化阶段，将训练好的人工神经网络与遗传算法相结合进行多目标优化，其中同时预测PEMFC性能指标和成本相关输出，随后使用加权和策略进行汇总，以确定最优的权衡操作条件。该框架代表了现有数据驱动PEMFC模型的一个明显进步，为下一代氢能应用的高性能、低成本PEMFC系统的设计和优化提供了一个计算效率高、实验验证和实际可部署的工具。

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引用次数: 0

The conundrum of employability of 2D simplifications in phase change numerical problems: A case of finite sized PCM heat sink 二维化简在相变数值问题中的应用难题：以有限尺寸PCM散热器为例

Q1 Chemical Engineering

International Journal of Thermofluids

Pub Date : 2026-03-01 Epub Date: 2025-12-08 DOI: 10.1016/j.ijft.2025.101509

Salah Addin Burhan Al-Omari , Farooq Mahmoud , Mohammad Qasem , Zahid Ahmed Qureshi , Emad Elnajjar

This study investigated the conundrum of 2D simplification employability in transient thermal management problems by comparing 2D and 3D numerical simulations of finite-size finned Phase Change Material (PCM) heat sinks. Gallium has been employed as the PCM in the heat sinks owing to its superior thermal response as opposed to conventional paraffinic PCMs. We analyzed two designs; a taller/narrower (Case 2A) and a shorter/wider (Case 1A); both with identical PCM volume, fin material, and heated base dimensions, subjected to a constant 10 W/cm² heat flux. Initial 2D simulations indicated superior heat dissipation for the shorter/wider design. Consistent with this, 3D results corroborated the shorter/wider finned PCM heat sink's superior performance, exhibiting peak base temperatures 10 to 25 K lower than the taller/narrower configuration (Fig. 4a). This advantage is attributed to the strategic PCM allocation in the shorter/wider design, positioning a larger latent heat storage capacity closer to the heat source. Crucially, 3D effects, notably the onset and nature of chaotic mixing, were found to be highly dependent on the applied base boundary conditions. In Case 1A, an unheated base portion created a stabilizing cool region, promoting prolonged near-two-dimensional flow despite emerging 3D effects. Conversely, Case 2A, with its entirely heated base, lacked this stabilization, leading to earlier and more pronounced three-dimensionality and highly chaotic mixing. Quantitatively, these enhanced 3D effects in Case 2A resulted in peak sink base temperatures up to about 10 °C lower than its 2D counterpart (Case 2), alongside faster melting. Despite these significant quantitative deviations, 2D simulations demonstrated qualitative consistency with 3D findings regarding the relative performance ranking of the two designs and the overall PCM melting behavior. These results confirm that while 3D simulations offer a more complete capture of the underlying physics, 2D models remain invaluable for preliminary design purposes, serving as a computationally efficient approach for initial comparative assessments and concept screening before detailed 3D modeling or experimental validation for final design optimization.

本研究通过比较有限尺寸翅片相变材料（PCM）散热器的二维和三维数值模拟，探讨了二维简化可就业性在瞬态热管理问题中的难题。由于与传统石蜡PCM相比，镓具有优越的热响应性能，因此已被用作散热器中的PCM。我们分析了两种设计；一个较高/较窄（个案2A）及一个较短/较宽（个案1A）；两者都具有相同的PCM体积，翅片材料和加热底座尺寸，承受恒定的10 W/cm²热流。最初的2D模拟表明，较短/较宽的设计具有较好的散热性。与此一致的是，3D结果证实了短/宽翅片PCM散热器的优越性能，其峰值基温比高/窄配置低10至25 K（图4a）。这一优势归因于短/宽设计中的策略性PCM分配，使更大的潜热储存能力更靠近热源。至关重要的是，三维效果，特别是混沌混合的开始和性质，被发现高度依赖于应用的基本边界条件。在案例1A中，未加热的基础部分创造了稳定的冷区，尽管出现了3D效果，但仍促进了长时间的近二维流动。相反，情况2A，其完全加热的基础，缺乏这种稳定性，导致更早，更明显的三维和高度混乱的混合。从数量上看，在情况2A中，这些增强的3D效果导致峰值汇基温度比其2D对应（情况2）低约10°C，同时融化速度更快。尽管存在这些显著的定量偏差，但在两种设计的相对性能排名和整体PCM熔化行为方面，2D模拟与3D结果在定性上是一致的。这些结果证实，虽然3D模拟提供了更完整的底层物理捕获，但2D模型对于初步设计目的仍然非常宝贵，在详细的3D建模或最终设计优化的实验验证之前，作为初始比较评估和概念筛选的计算高效方法。

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引用次数: 0

Machine learning integrated higher-order model application for critical heat flux investigations in pressurized water reactors 机器学习集成高阶模型在压水堆临界热流研究中的应用

Q1 Chemical Engineering

International Journal of Thermofluids

Pub Date : 2026-03-01 Epub Date: 2026-01-17 DOI: 10.1016/j.ijft.2026.101561

Stephen A. Ajah , Lateef Akanji , Jefferson Gomes

Nuclear power station disasters like those at Chernobyl, Three Mile Island, and Fukushima Daiichi have highlighted how urgently improved nuclear safety is needed. This usually happened due to impeded cooling systems, resulting in heat accumulation, coolant boiling, and phase transformation leading to critical heat flux (CHF) events. Understanding bubble nucleation and dynamics during boiling heat transfer is crucial for ensuring the safety and reliability of pressurized water reactors (PWRs), particularly during postulated severe accident scenarios. Existing numerical models often struggle to accurately capture the complex multifluid interfaces and non-isothermal flow conditions inherent in these events, leading to potential inaccuracies in accident progression predictions. To address this gap, this study presents a novel numerical approach combining a high-order discontinuous Galerkin method (CVFEM), a conservative adaptive interface capturing method (CAICM), and a machine learning (ML) model (CVFEM+CAICM+ML/EoS). The ML component significantly enhances the accuracy of multifluid interface capturing in non-isothermal flows through precise fluid density evaluation, a key improvement over traditional methods. An adaptive mesh algorithm was implemented to optimize computational resource allocation, focusing on critical material interfaces. The model was validated against experimental data on single rising bubble dynamics, demonstrating its reliability. Analysis of dimensionless parameters, specifically the Galileo and Eötvös numbers, revealed the transition from laminar liquid flow to mixed vapor regimes, indicative of severe accident progression. This research provides a robust and validated tool for understanding complex boiling heat transfer mechanisms and bubble nucleation dynamics in PWRs, contributing to enhanced reactor safety.

切尔诺贝利、三里岛和福岛第一核电站等核电站灾难凸显了提高核安全的迫切需要。这通常是由于冷却系统受阻，导致热量积聚，冷却剂沸腾和相变导致临界热流密度（CHF）事件。了解沸腾传热过程中的气泡成核和动力学对于确保压水堆（pwr）的安全性和可靠性至关重要，特别是在假定的严重事故情况下。现有的数值模型往往难以准确地捕捉这些事件中固有的复杂的多流体界面和非等温流动条件，从而导致事故进展预测的潜在不准确性。为了解决这一差距，本研究提出了一种新的数值方法，结合了高阶不连续伽辽金方法（CVFEM）、保守自适应界面捕获方法（CAICM）和机器学习（ML）模型（CVFEM+CAICM+ML/EoS）。ML组件通过精确的流体密度评估显着提高了非等温流动中多流体界面捕获的准确性，这是传统方法的一个关键改进。采用自适应网格算法优化计算资源分配，重点关注关键材料界面。用单个上升气泡动力学实验数据对模型进行了验证，验证了模型的可靠性。对无量纲参数的分析，特别是伽利略和Eötvös数字，揭示了从层流液体流动到混合蒸汽状态的转变，表明了严重的事故进展。该研究为理解压水堆中复杂的沸腾传热机制和气泡成核动力学提供了可靠的工具，有助于提高反应堆的安全性。

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引用次数: 0

A technical note on solar thermal applications of semi-transparent liquid films 半透明液体薄膜的太阳能热应用技术说明

Q1 Chemical Engineering

International Journal of Thermofluids

Pub Date : 2026-03-01 Epub Date: 2026-02-05 DOI: 10.1016/j.ijft.2026.101578

Boris V. Balakin

With over 500 GWth of installed total capacity, solar thermal generation provides approximately one-third of the world’s solar power. However, this important branch is based on the last-century thermal technology, flat plate solar collectors, which demonstrate low efficiency in moderate-to-cold climates. This contribution proposes a concept of a film solar collector (FSC) based on thin semi-transparent liquid layers cooling the collector’s absorbing surface. A prototype collector was tested at 0.13-0.74 sun and air temperatures of ∼25°C using water, an edible oil, and a red-colored oil to enhance the film’s volumetric absorption. Due to evaporation, the water-based FSC has a low thermal efficiency of 20%. The colored oil increased efficiency to 55%, and the semi- transparent oil film collected about 85% of solar heat.

太阳能热发电装机容量超过500gwth，约占全球太阳能发电量的三分之一。然而，这一重要分支是基于上个世纪的热技术，平板太阳能集热器，在中冷气候下效率较低。这篇论文提出了一种薄膜太阳能集热器（FSC）的概念，这种薄膜太阳能集热器是基于薄的半透明液体层来冷却集热器的吸收表面。原型收集器在0.13-0.74太阳温度和~ 25°C的空气温度下测试，使用水，食用油和红色油来增强薄膜的体积吸收。由于蒸发，水基FSC的热效率较低，只有20%。有色油的效率提高到55%，半透明的油膜收集了大约85%的太阳热量。

引用次数: 0

CFD analysis of temperature-driven flow for passive HVAC applications in Irish homes 爱尔兰家庭被动式暖通空调应用中温度驱动流量的CFD分析

Q1 Chemical Engineering

International Journal of Thermofluids

Pub Date : 2026-03-01 Epub Date: 2026-01-04 DOI: 10.1016/j.ijft.2026.101551

Rahul D , Anjaneya G , Manjunatha N K , Sunil S , Mohan Kumar G R , Girish Kumar G S , C.Durga Prasad , Nithesh Kumble Gokuldas , Nilesh H. Khandare , Nimona Hailu

Buoyancy-driven ventilation is a sustainable alternative to conventional HVAC systems, leveraging temperature differences to induce airflow. This study analyzes buoyancy-driven flow using Computational Fluid Dynamics (CFD) in ANSYS Fluent to evaluate its feasibility for natural ventilation. The simulation models a contracting pipe with internal heating fins, made of copper, which gets heated by sunlight up to 60 °C, inducing airflow through natural convection. A pressure inlet at 0 gauge pressure and a pressure outlet at −20 Pa were applied. The steady-time simulation used the realizable k-ε turbulence model with buoyancy effects enabled and the energy equation enabled. Results show flow from the inlet to the outlet domain, which was confirmed by evaluating volumetric flow rate at the outlet and observing velocity streamlines, confirming that the design effectively enhances natural ventilation. A grid independence study was conducted by evaluating the Grashof number (Gr) on one of the heated walls. Grid independence was achieved with 693635 elements with a Grashof number value of 3*e¹⁰. A parametric study was conducted for varying wall temperatures (30 °C, 40 °C, 50 °C, and 60 °C), and the Volumetric flow rate at the outlet was monitored. Results indicate a linear trend between temperature and volumetric flow at the outlet, proving that more air can be expelled with higher blade temperatures.

浮力驱动通风是传统暖通空调系统的可持续替代方案，利用温差诱导气流。本研究利用ANSYS Fluent中的计算流体动力学（Computational Fluid Dynamics， CFD）对浮力驱动的流动进行分析，以评估其用于自然通风的可行性。该模拟模拟了一个内部带有铜制发热片的收缩管道，该管道被阳光加热到60°C，通过自然对流诱导气流。施加0表压力的压力入口和−20 Pa的压力出口。稳态时间模拟采用可实现的k-ε湍流模型，启用浮力效应并启用能量方程。结果表明，通过对出口体积流量的评估和对速度流线的观察，证实了从进口到出口的流动，证实了该设计有效地增强了自然通风。通过对其中一个加热壁面的Grashof数（Gr）进行评估，进行了网格独立性研究。使用693635个元素实现网格独立性，Grashof数值为3*e10。在不同的壁面温度（30°C、40°C、50°C和60°C）下进行了参数化研究，并监测了出口的体积流量。结果表明，出口温度与体积流量呈线性关系，表明叶片温度越高，排风量越大。

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引用次数: 0

Research on preparation and thermal performance of carbon sphere-modified PCM perlite-paraffin composite 碳球改性PCM珍珠岩-石蜡复合材料的制备及热性能研究

Q1 Chemical Engineering

International Journal of Thermofluids

Pub Date : 2026-03-01 Epub Date: 2026-01-06 DOI: 10.1016/j.ijft.2026.101553

Qi Chen , Wei Na , Quanhe Gai , Jie Yang , Yan Wang , Xucheng Chen , Zhao Cao , Shuguang Li

A carbon sphere modification approach was developed to construct a perlite/paraffin composite phase change material (CS-PCM) with both high photothermal conversion efficiency and stable thermal energy storage capability. The surface of the perlite matrix was modified using sodium carboxymethyl cellulose (CMCNa), increasing the water contact angle from 0° to 67° Micro/nanoscale carbon spheres (0.1–20 μm) derived from tea waste were embedded into a resin matrix, demonstrating superior performance compared to conventional carbon-based additives. The CS-PCM was incorporated into thermal storage walls through a scalable manufacturing process, with phase change materials comprising 30 % of the system. Experimental application in high-latitude greenhouses during winter confirmed that the integrated system maintained an internal crop environment at 13.6 ± 4 °C. This composite material features both low cost and reduced carbon emissions. The results offer a promising solution for thermal management in protected agriculture in cold regions and provide a theoretical and technical reference for the design of multifunctional phase change materials.

采用碳球改性的方法制备了光热转换效率高、储热性能稳定的珍珠岩/石蜡复合相变材料（CS-PCM）。采用羧甲基纤维素钠（CMCNa）对珍珠岩基体表面进行改性，将水接触角从0°增加到67°，将茶渣制备的微纳碳球（0.1 ~ 20 μm）嵌入树脂基体中，表现出优于传统碳基添加剂的性能。CS-PCM通过可扩展的制造工艺集成到储热壁中，相变材料占系统的30%。冬季在高纬度温室的试验应用证实，该综合系统将作物内部环境维持在13.6±4°C。这种复合材料具有成本低、碳排放少的特点。研究结果为寒冷地区保护农业的热管理提供了一种有希望的解决方案，并为多功能相变材料的设计提供了理论和技术参考。

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引用次数: 0

Flow behaviors of anionic polyacrylamide aqueous solutions 阴离子聚丙烯酰胺水溶液的流动行为

Q1 Chemical Engineering

International Journal of Thermofluids

Pub Date : 2026-03-01 Epub Date: 2026-01-19 DOI: 10.1016/j.ijft.2026.101562

Mamdouh T. Ghannam , Mohamed Y.E. Selim , Ahmed Thaher , Taif Ali Alameri , Shaikha Salem Alamri , Mariam Khalifa Alketbi

This experimental study investigates the flow behaviors of anionic polyacrylamide (APAA) aqueous solutions to better understand their characteristics for different industrial uses and applications. This study examined numerous experimental samples of polymer solutions using FLOC 24 APAA powder over concentration range of 500-5000 mg/L, and two different electrolytes of NaCl and CaCl₂ were included with concentration range of 1-10 Wt.%. To scrutinize the flow behavior of APAA aqueous solutions, rheological measurements of shear stress and dynamic viscosity versus shear rate were carried out employing MCR 92 rotational rheometer over four temperatures of 20, 40, 60, and 80 °C. The main outcomes of the current study include, firstly, the shear stress increases with both shear rate and APAA concentration. The effect of polymer concentration is mostly notable at shear rate of less than 200 s^-1, above this verge, the shear stress contours are similar regardless of APAA concentration. Secondly, the rheogram contours decline significantly as the temperature rises from 20 °C to 80 °C, attributed to negative thermal effects on molecular cohesion forces of APAA solutions. The APAA solutions generally exhibit shear-thinning behavior up to a critical shear rate, after which a shear-thickening behavior is observed. Thirdly, temperature has a strong negative influence on the reported dynamic viscosity across the tested range of 20 °C to 80 °C. Lastly, the introduction of varying concentrations of NaCl and CaCl₂ salinity consistently leads to a reduction in dynamic viscosity of APAA polymer solutions.

本实验研究了阴离子聚丙烯酰胺（APAA）水溶液的流动行为，以更好地了解其在不同工业用途和应用中的特性。本研究使用FLOC 24 APAA粉末在500- 5000mg /L的浓度范围内对聚合物溶液进行了大量实验样品的检测，包括NaCl和CaCl2两种不同的电解质，浓度范围为1- 10wt .%。为了仔细研究APAA水溶液的流动行为，使用MCR 92旋转流变仪在20、40、60和80℃四种温度下进行了剪切应力和动态粘度随剪切速率的流变学测量。本研究的主要结果包括：①剪切应力随剪切速率和APAA浓度的增加而增加；在剪切速率小于200 s-1时，聚合物浓度的影响最为显著，在此水平以上，无论APAA浓度如何，剪应力轮廓都是相似的。其次，温度从20℃升高到80℃，流变图轮廓明显下降，这是由于APAA溶液的分子内聚力受到负热效应的影响。在临界剪切速率之前，APAA溶液通常表现出剪切减薄行为，在此之后，观察到剪切增厚行为。第三，在20°C至80°C的测试范围内，温度对报告的动态粘度有很强的负面影响。最后，引入不同浓度的NaCl和cacl2盐度会导致APAA聚合物溶液的动态粘度下降。

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引用次数: 0

LMA-driven analysis of transient MHD Eyring–powell flow in stretching squeezing channel with Raditive-reactive and heat generation/absorption 具有辐射反应和热生成/吸收的拉伸挤压通道中瞬态MHD埃林-鲍威尔流动的lma驱动分析

Q1 Chemical Engineering

International Journal of Thermofluids

Pub Date : 2026-03-01 Epub Date: 2026-01-27 DOI: 10.1016/j.ijft.2026.101570

Davood Domiri Ganji, Mehdi Mahboobtosi, Fateme Nadalinia Chari

This work investigates unsteady heat and mass transfer in a squeezing channel filled with a magnetohydrodynamic Eyring–Powell non-Newtonian fluid, incorporating the effects of thermal radiation, chemical reaction, and internal heat generation or absorption. The investigation is significant for understanding complex flow behaviors in industrial and engineering applications where magnetic forces, non-Newtonian fluids, and wall motion interact. Nonlinear equations have been solved using MATLAB. The squeezing motion of the channel walls, together with magnetic forces and non-Newtonian fluid characteristics, produces complex flow behavior marked by velocity suppression in one region of the channel and enhancement in another. Thermal analysis reveals that stronger squeezing and internal heat generation elevate the temperature field, whereas thermal radiation promotes heat dissipation. In addition, an increase in the Schmidt number reduces the concentration distribution due to weakened mass diffusion. To complement the mathematical modeling, an Artificial Neural Network (ANN) framework is employed to capture the nonlinear relationships between governing parameters and the resulting velocity, temperature, and concentration profiles. The complete dataset for all parameters was divided into training, validation, and testing sets, with 70%, 15%, and 15% of the data allocated to each set, respectively. The ANN demonstrates strong predictive capability, as evidenced by low mean squared error values and close agreement between predicted and reference data across training, validation, and testing stages. The combined physical and data-driven analysis provides a comprehensive understanding of the parametric influences governing MHD Eyring–Powell squeezing flows and highlights the potential of ANN-based approaches for analyzing complex nonlinear heat and mass transfer phenomena relevant to advanced engineering and industrial applications. This study’s findings contribute to the analysis of nonlinear heat and mass transfer in advanced engineering and industrial applications, offering a new perspective compared to earlier literature.

这项工作研究了在充满磁流体动力学的埃林-鲍威尔非牛顿流体的挤压通道中的非定常传热和传质，包括热辐射、化学反应和内部热产生或吸收的影响。这项研究对于理解工业和工程应用中磁力、非牛顿流体和壁面运动相互作用的复杂流动行为具有重要意义。用MATLAB对非线性方程进行了求解。通道壁的挤压运动，加上磁力和非牛顿流体特性，产生了复杂的流动行为，其特征是通道的一个区域速度抑制而另一个区域速度增强。热分析表明，更强的挤压和内部热产生使温度场升高，而热辐射促进了散热。此外，由于质量扩散减弱，施密特数的增加降低了浓度分布。为了补充数学建模，采用人工神经网络（ANN）框架来捕获控制参数与由此产生的速度、温度和浓度分布之间的非线性关系。将所有参数的完整数据集分为训练集、验证集和测试集，每个集分别分配70%、15%和15%的数据。人工神经网络显示出强大的预测能力，这一点可以从训练、验证和测试阶段的低均方误差值和预测数据与参考数据之间的密切一致中得到证明。结合物理和数据驱动的分析提供了对控制MHD Eyring-Powell挤压流的参数影响的全面理解，并强调了基于人工神经网络的方法在分析与先进工程和工业应用相关的复杂非线性传热和传质现象方面的潜力。本研究的发现有助于分析先进工程和工业应用中的非线性传热和传质，与早期文献相比提供了新的视角。

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引用次数: 0