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Casson fluid flow dynamics between parallel discs: A neural network-based computational approach 平行圆盘间卡森流体流动动力学:一种基于神经网络的计算方法
Q1 Chemical Engineering Pub Date : 2025-11-01 DOI: 10.1016/j.ijft.2025.101468
Talha Anwar , Mehreen Fiza , Kashif Ullah , Hakeem Ullah , Seham M. Al-Mekhlafi

Significance

Casson fluid flow between parallel discs has significant applications in biomedical devices such as blood pumps, dialysis units, and artificial valves, in industrial processes involving inks, paints, and food pastes, and in engineering systems including lubrication, cooling and polymer processing. Artificial Neural Networks are increasingly applied in fluid dynamics for their ability to approximate nonlinear systems, reduce computational cost, and provide accurate predictions compared to traditional numerical schemes.

Purpose

This work proposes a supervised learning approach using Artificial Neural Network Backpropagation trained with the Levenberg-Marquardt scheme (ANN-BLMS) to obtain numerical solutions of Casson fluid flow between two parallel discs with dissimilar in-plane motion (CFFPD). The method improves accuracy and stability, reduces computational cost, and predicts fluid flow behavior under varying physical parameters, with emphasis on the effects of the rotation parameter, Reynolds number, and Casson parameter on velocity profiles.

Methodology

The system of governing partial differential equations is converted into dimensionless ordinary differential equations through similarity transformation and solved using the ANN-BLMS. The data for this study were obtained using NDSolve method and subsequently optimized with an artificial neural network. The data set for ANN-BLMS is computed by using 15% of the data for testing (TT), 15%for the training (TR), and 75% of the data, selected randomly, for validation (VL). Error histograms (EH) and regression (RG) measurements, together with strong agreement with known solutions, demonstrate the dependability of the developed algorithms, ANN-BLMS, on CFFPD, with an accuracy range from 10−3to 10−7.

Findings

The radial velocity increases with the Casson parameter in the range 0 < η < 0.5, but decreases for 0.5 ≤ η ≤ 1, while the azimuthal velocity decreases for the Casson parameter grows. For both Reynolds number, and rotation parameter the radial velocity declines when 0 < η < 0.5, and rises for 0.5 ≤ η ≤ 1. The azimuthal velocity increases with the increase in both the Reynolds number and rotation parameter. The ANN-BLMS approach demonstrates strong agreement with existing solutions, offering higher accuracy, stability, and lower computational cost compared to traditional numerical methods.
平行圆盘之间的卡森流体流动在生物医学设备(如血泵、透析装置和人工阀门)、涉及油墨、油漆和食品糊的工业过程以及包括润滑、冷却和聚合物加工在内的工程系统中具有重要应用。与传统的数值方案相比,人工神经网络具有近似非线性系统、降低计算成本和提供准确预测的能力,因此越来越多地应用于流体动力学。本文提出了一种基于Levenberg-Marquardt格式(ANN-BLMS)训练的人工神经网络反向传播的监督学习方法,以获得具有不同面内运动(CFFPD)的两个平行圆盘间卡森流体流动的数值解。该方法提高了精度和稳定性,降低了计算成本,并预测了不同物理参数下流体的流动行为,重点研究了旋转参数、雷诺数和Casson参数对速度剖面的影响。方法将控制偏微分方程系统通过相似变换转化为无量纲常微分方程,利用神经网络- blms进行求解。本研究的数据采用NDSolve方法获得,随后使用人工神经网络进行优化。ANN-BLMS的数据集是通过使用15%的数据用于测试(TT), 15%的数据用于训练(TR)和随机选择的75%的数据用于验证(VL)来计算的。误差直方图(EH)和回归(RG)测量结果,以及与已知解的强烈一致性,证明了开发的算法ANN-BLMS在CFFPD上的可靠性,精度范围为10−3至10−7。结果:径向速度在0 <; η <; 0.5范围内随Casson参数增大而增大,0.5≤η≤1范围内随Casson参数增大而减小,而方位速度随Casson参数增大而减小。对于雷诺数和旋转参数,径向速度在0 <; η <; 0.5时下降,在0.5≤η≤1时上升。方位角速度随雷诺数和旋转参数的增大而增大。与传统的数值方法相比,ANN-BLMS方法具有更高的精度、稳定性和更低的计算成本。
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引用次数: 0
Thermal and mechanical characteristics of natural fiber-reinforced composites using bio-binder as sustainable insulation materials 用生物粘合剂作为可持续保温材料的天然纤维增强复合材料的热力学特性
Q1 Chemical Engineering Pub Date : 2025-11-01 DOI: 10.1016/j.ijft.2025.101507
Amged ElHassan , Basim Abu-Jdayil , Waleed Ahmed
To reduce deforestation and promote the utilization of agro-industrial by-products this study fabricated a completely bio-derived composite using date trunk fibers and non-edible okra as sustainable feedstock. Composites with 0–50 wt. percentage okra content were produced using compression molding and tested to assess mechanical strength, thermal insulation, and sound absorption. Rising okra proportion improved interfacial bonding and minimized porosity, leading to increased compressive strength (up to 28 MPa) and elastic modulus (0.49 GPa). Thermal conductivity numbers were observed in the range between 0.051and 0.067 W/m.K at room temperature, confirming suitability for insulation applications. The fabricated composites demonstrated high thermal stability with 11 % mass loss at 270 °C, and achieving a maximum acoustic absorption coefficient (0.9). The specific heat capacity values were found between 1.35 × 10³ and 2.38 × 10³ J/kg·K, and corresponding thermal diffusivity between 0.0307 and 0.0651 mm²/s, reflecting effective heat storage. These results validate the use of date palm and okra by-products as feedstock for bio-based composites fabrication via a simple method without depending on any toxic ingredients, pretreatment, and sophisticated processing. These results confirm that valorizing date palm trunk fibers and okra residues into bio-based composites, and acoustically efficient materials for construction use in arid climates.
为了减少森林砍伐和促进农工副产品的利用,本研究以枣干纤维和不可食用秋葵为可持续原料制备了一种完全生物衍生的复合材料。使用压缩成型技术生产了重量为0-50 wt.百分比的秋葵复合材料,并对其进行了机械强度、隔热性能和吸声性能测试。秋葵比例的增加改善了界面结合,降低了孔隙率,从而提高了抗压强度(高达28 MPa)和弹性模量(0.49 GPa)。导热系数在0.051 ~ 0.067 W/m之间。室温K,确认绝缘应用的适用性。制备的复合材料在270°C时具有较高的热稳定性,质量损失为11%,并且声吸收系数最大(0.9)。比热容在1.35 × 10³~ 2.38 × 10³J/kg·K之间,相应的热扩散系数在0.0307 ~ 0.0651 mm²/s之间,反映了有效储热。这些结果验证了使用椰枣和秋葵副产品作为原料,通过一种简单的方法制造生物基复合材料,而不依赖于任何有毒成分,预处理和复杂的加工。这些结果证实,将枣椰树树干纤维和秋葵残留物转化为生物基复合材料和声学高效材料,可用于干旱气候下的建筑。
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引用次数: 0
Thermo-magnetic stratified flow capturing Soret-Dufour impacts in rate type reactive material under varying liquid aspects and stratifications 热磁分层流捕获Soret-Dufour对速率型反应物质在不同液体方面和分层下的影响
Q1 Chemical Engineering Pub Date : 2025-11-01 DOI: 10.1016/j.ijft.2025.101479
F. Shahzad , Ali B.M. Ali , M. Waqas , Gaganjot Kaur , Ramneek Sidhu , Tadesse Walelign , Umid Turdialiyev , Nidhal Ben Khedher
In various industrial frameworks encompassing biofluids, polymers and coatings, interpreting viscoelastic characteristics is indispensable for accomplishing regulated mass and heat transmission. The viscoelastic Oldroyd-B material efficiently characterizes such type of materials where reaction kinetics, concentration and temperature fluctuate at the same time. The current analysis considers the magnetically driven viscoelastic Oldroyd-B material over a magnetized moving surface subjected to variable thermal and variable mass features. The Lorentzian force is introduced due to magnetic field consideration while variable thermosolutal conditions are opted because of dual stratification aspects. In addition, mass transmission features chemical reaction effects. Apposite similarity variables are introduced to transfigure governing PDEs (partial differential equations) into nonlinear ODEs (ordinary differential equations) which are computed analytically through homotopy analysis scheme. A comparative assessment with available published outcomes authenticates the accurateness of analytical outcomes. Besides, the outcomes disclose that Hartman number considerably impact the velocity distribution while solutal and thermal fields are strongly affected via varying conductivity and varying diffusivity factors. These outcomes offer indispensable perception into diffusive-thermo control in coating flows.
在包括生物流体、聚合物和涂料在内的各种工业框架中,解释粘弹性特性对于实现调节的质量和热传递是必不可少的。粘弹性Oldroyd-B材料有效地表征了反应动力学、浓度和温度同时波动的这类材料。目前的分析考虑磁驱动的粘弹性Oldroyd-B材料在磁化的运动表面上受变热变质量特征的影响。由于考虑了磁场,引入了洛伦兹力,而由于双重分层,选择了可变热溶质条件。此外,传质还具有化学反应效应。引入适当的相似变量,将控制偏微分方程转化为非线性常微分方程,并通过同伦分析格式解析计算。与现有已发表结果的比较评估验证了分析结果的准确性。此外,研究结果表明,哈特曼数对速度分布有较大影响,而溶质场和热场则受到电导率和扩散系数变化的强烈影响。这些结果为涂层流动中的扩散热控制提供了不可或缺的认识。
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引用次数: 0
A review of industrial pumps for viscous and non-Newtonian slurry transport 粘性和非牛顿泥浆输送工业泵的研究进展
Q1 Chemical Engineering Pub Date : 2025-11-01 DOI: 10.1016/j.ijft.2025.101450
Oscar Ifidon , Daya Shankar Pandey , Khurshid Ahmad , Artur J. Jaworski , Faisal Asfand
This paper presents a concise review of industrial pumps for viscous and non-Newtonian slurry transport. It combines both the computational fluid dynamics (CFD) and experimental analysis to investigate the performance and limitations of various rotodynamic and positive displacement (PD) pumps for various slurry transport applications. The factors influencing head, efficiency and reliability in rotodynamic and PD pumps were evaluated for viscous and non-Newtonian fluids applications. Available literature showed that centrifugal pumps experience head losses of ≥ 8 m and efficiency reduction of 20 % when viscosity approaches 800–1000 cP, whereas the blade and volute optimisation could improve the overall efficiency. The performance of the multiphase pump showed a sharp decline when handling non-Newtonian fluids, primarily due to the formation of complex vortex structures and tip‑leakages. This study also highlighted key geometric parameters for optimisation to improve overall performance and enable the integration of multiphase pumps as a prime mover in a jet pump system, for a robust handling of highly viscous and solid‑laden fluids. While the special‑effect jet pumps had lower peak efficiencies compared to other rotodynamic pumps, robustness and passability for abrasive and multiphase flows were demonstrated, achieving up to 40 % efficiency in sand slurry applications. PD pumps, such as the reciprocating plunger and diaphragm designs, exhibited the highest viscosity tolerance, however, their performance was limited by valve response and mechanical complexity. This review particularly focused on the capabilities of Tesla disc pump for handling highly viscous and abrasive fluids. Literature on Tesla disc pumps emphasised that geometric optimisation of the disc impeller, combined with the use of a dedicated volute, could significantly enhance its efficiency and position it as a complementary solution to both centrifugal and PD pumps. The analysis of life cycle cost (LCC) showed that the Tesla disc pump maintained moderate costs for harsh applications, indicating a sustainable operational life cycle.
本文简要介绍了用于粘性和非牛顿泥浆输送的工业泵。它结合了计算流体动力学(CFD)和实验分析来研究各种旋转动力学和正排量(PD)泵在各种泥浆输送应用中的性能和局限性。在粘性和非牛顿流体应用中,对影响旋转动力泵和PD泵扬程、效率和可靠性的因素进行了评估。现有文献表明,当粘度接近800-1000 cP时,离心泵的扬程损失≥8 m,效率降低20%,而叶片和蜗壳优化可以提高整体效率。当处理非牛顿流体时,多相泵的性能急剧下降,主要是由于复杂涡结构的形成和尖端泄漏。该研究还强调了优化的关键几何参数,以提高整体性能,并将多相泵集成为喷射泵系统中的原动机,以强大地处理高粘性和含固体流体。虽然与其他旋转动力泵相比,特殊效果喷射泵的峰值效率较低,但其在磨料流和多相流中的稳定性和通过性得到了证明,在砂浆应用中效率高达40%。PD泵,如往复柱塞和隔膜设计,具有最高的粘度耐受性,然而,它们的性能受到阀门响应和机械复杂性的限制。这篇综述特别关注了特斯拉圆盘泵处理高粘性和磨蚀性流体的能力。关于特斯拉盘式泵的文献强调,盘式叶轮的几何优化,结合专用蜗壳的使用,可以显著提高其效率,并将其定位为离心泵和PD泵的补充解决方案。生命周期成本(LCC)分析表明,特斯拉盘式泵在恶劣的应用环境中保持了适度的成本,表明其具有可持续的运行生命周期。
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引用次数: 0
Supervised machine learning approach to estimating the convective heat transfer coefficient for heated oblate spheroidal particles 有监督机器学习方法估计受热扁球颗粒的对流换热系数
Q1 Chemical Engineering Pub Date : 2025-11-01 DOI: 10.1016/j.ijft.2025.101476
Belal Al-Zaitone, Tariq Ammar, Al Husain Sami, Mohamed Elshabrawy, Mohamad Kozal
An accurate prediction of the convective heat transfer coefficient for heated non-spherical particles is important in many engineering applications. In this work, a supervised machine learning (ML)-based model is proposed to predict the Nusselt number (Nu) of heated oblate spheroidal particles in laminar flow. A computational fluid dynamics (CFD) dataset of Nusselt numbers is obtained from COMSOL Multiphysics simulations performed at different Reynolds numbers, aspect ratios, and surface temperatures. Three supervised ML models are trained and compared — gradient boosting regressor (GBR), random forest (RF), and ridge regression — and cross-validation and model evaluation are performed using standard performance metrics (R² and RMSE). Among the three models, the GBR model achieves the best predictive performance by capturing the nonlinear joint associations of geometric and thermal factors. Hyperparameter optimization is implemented to improve model performance. An accurate predictive model is suggested as an alternative to classical empirical correlations to estimate Nu for oblate spheroids, establishing a theoretical and data-driven foundation relevant to industrial processes like gas-solid reactions, aerosols, and fluidized beds.
在许多工程应用中,精确地预测加热后非球形颗粒的对流换热系数具有重要意义。在这项工作中,提出了一个基于监督机器学习(ML)的模型来预测层流中加热扁圆球颗粒的努塞尔数(Nu)。在不同雷诺数、宽高比和表面温度下,COMSOL Multiphysics模拟获得了计算流体动力学(CFD)努塞尔数数据集。我们训练并比较了三个有监督的机器学习模型——梯度增强回归(GBR)、随机森林(RF)和山脊回归——并使用标准性能指标(r2和RMSE)进行交叉验证和模型评估。在三种模型中,GBR模型通过捕获几何因素和热因素的非线性联合关系,获得了最佳的预测性能。实现了超参数优化,提高了模型性能。本文提出了一种精确的预测模型,以替代经典的经验关联来估计扁球体的Nu,为气固反应、气溶胶和流化床等工业过程建立理论和数据驱动的基础。
{"title":"Supervised machine learning approach to estimating the convective heat transfer coefficient for heated oblate spheroidal particles","authors":"Belal Al-Zaitone,&nbsp;Tariq Ammar,&nbsp;Al Husain Sami,&nbsp;Mohamed Elshabrawy,&nbsp;Mohamad Kozal","doi":"10.1016/j.ijft.2025.101476","DOIUrl":"10.1016/j.ijft.2025.101476","url":null,"abstract":"<div><div>An accurate prediction of the convective heat transfer coefficient for heated non-spherical particles is important in many engineering applications. In this work, a supervised machine learning (ML)-based model is proposed to predict the Nusselt number (Nu) of heated oblate spheroidal particles in laminar flow. A computational fluid dynamics (CFD) dataset of Nusselt numbers is obtained from COMSOL Multiphysics simulations performed at different Reynolds numbers, aspect ratios, and surface temperatures. Three supervised ML models are trained and compared — gradient boosting regressor (GBR), random forest (RF), and ridge regression — and cross-validation and model evaluation are performed using standard performance metrics (R² and RMSE). Among the three models, the GBR model achieves the best predictive performance by capturing the nonlinear joint associations of geometric and thermal factors. Hyperparameter optimization is implemented to improve model performance. An accurate predictive model is suggested as an alternative to classical empirical correlations to estimate Nu for oblate spheroids, establishing a theoretical and data-driven foundation relevant to industrial processes like gas-solid reactions, aerosols, and fluidized beds.</div></div>","PeriodicalId":36341,"journal":{"name":"International Journal of Thermofluids","volume":"30 ","pages":"Article 101476"},"PeriodicalIF":0.0,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145520092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Magneto-thermal analysis of tri-hybrid blood-based nanofluid flow at a stagnation point over a stretching cylinder under Joule heating 焦耳加热下三混合血基纳米流体在拉伸圆柱体上滞止点流动的磁热分析
Q1 Chemical Engineering Pub Date : 2025-11-01 DOI: 10.1016/j.ijft.2025.101506
S. Baskaran , K. Senthilvadivu , K. Chellapriya , K. Loganathan , Saleem Nasir , Abdallah Berrouk , R. Sowrirajan
This study investigates the flow and heat transfer behavior of a ternary hybrid nanofluid composed of gold (Au), silicon dioxide (SiO2), and titanium dioxide (TiO2) nanoparticles dispersed in blood, representing a biologically relevant medium for biomedical applications such as targeted drug delivery, hyperthermia therapy, and diagnostic imaging. The research focuses on stagnation-point flow over a cylindrically stretching surface, simulating arterial flow subjected to external thermal and magnetic effects. The fundamental partial differential formulations were systematically reduced to a set of coupled ordinary differential equations through the application of appropriate transformations, numerically tackled via MATLAB’s bvp4c solver. The validation of the numerical approach against benchmark studies confirmed the accuracy of the results. Key findings reveal that increasing magnetic field strength and porosity parameter suppressed the velocity profile. Elevated Eckert number broadened the thermal boundary layer thickness. Nanofluid concentration levels improved with stronger thermophoretic activity, while larger Lewis number diminished nanoparticle concentration. Wall shear stress exhibited a downward trend under intensified magnetic and porous conditions. Furthermore, heat transfer weakened in response to Eckert number, magnetic effects and Brownian motion, yet was augmented by the Biot number. Enhanced Lewis number contributed to an increase in mass transfer rate. These results highlight the effectiveness of tri-hybrid nanofluids in improving thermal and mass transfer performance in biologically relevant flows and provide essential guidance for the design of advanced biomedical devices and thermal management systems.
本研究研究了分散在血液中的由金(Au)、二氧化硅(SiO2)和二氧化钛(TiO2)纳米颗粒组成的三元混合纳米流体的流动和传热行为,代表了生物医学应用的相关介质,如靶向药物输送、热疗和诊断成像。研究重点是在圆柱形拉伸表面上的停滞点流动,模拟受外部热效应和磁效应影响的动脉流动。通过应用适当的变换,将基本的偏微分公式系统地简化为一组耦合的常微分方程,并通过MATLAB的bvp4c求解器进行数值处理。数值方法与基准研究的验证证实了结果的准确性。结果表明,增大磁场强度和孔隙度参数会抑制速度剖面。升高的Eckert数使热边界层厚度变宽。纳米流体浓度水平随着热泳活性的增强而提高,而路易斯数的增加会降低纳米颗粒浓度。在强磁性和多孔性条件下,壁剪应力呈下降趋势。此外,热传递在埃克特数、磁效应和布朗运动的影响下减弱,而在Biot数的作用下增强。刘易斯数的增加有助于传质速率的提高。这些结果强调了三混合纳米流体在改善生物相关流动中的传热传质性能方面的有效性,并为先进生物医学设备和热管理系统的设计提供了重要的指导。
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引用次数: 0
Applicable temperature prediction of composite heat exchanger group in construction vehicle by area-weighted modified ɛ-Ntu model 应用面积加权修正的ntu模型预测工程车辆复合换热器组的适用温度
Q1 Chemical Engineering Pub Date : 2025-11-01 DOI: 10.1016/j.ijft.2025.101498
Yunjia Liang , Jiaxin Liu , Naijiang Liu , Shikui Jia , Tianci Zhang , Martin Krechel
To address the harsh and variable conditions in recent years, an increasing number of construction vehicles have adopted composite heat exchanger systems. The common recognized performance prediction on a single heat exchanger might be still behind the composite heat exchanger group for its complexity. In this paper, an area-weighted model was proposed for the applicable ambient temperature prediction of the heat exchanger system based on the modified ε-Ntu method involving j and f factors of each heat exchanger in the system. Firstly, an overview of the architecture of a composite “3 + 1″ heat exchanger system were in the first row side by side and a size-matching coolant heat exchanger was placed in the rear row along the airflow direction, was presented, together with the corresponding heat transfer principle for this system. Then, the detailed prediction on the heat transfer quantity of the system was introduced based on the modified ε-Ntu method. Following that, a field experiment was conducted to validate the model correctness to the further prediction. At last, the prediction on the temperature was performed for the stableness of the current system. It is found that the predicted heat transfer quantities of four different heat exchangers, 37,687.24 W, 30,450.47 W, 3660.15 W, and 86,541.42 W under 16 °C, could secure the model duty with the maximum 5.10 % error. The applicable ambient temperature is 34 °C with a 3696.57-W coolant heat exchanger. This paper is expected to provide a scientific basis for the performance evaluation of composite heat exchanger systems for construction vehicles.
近年来,为了应对恶劣多变的工况,越来越多的工程车辆采用复合换热器系统。由于单个换热器的复杂性,普遍认可的性能预测可能仍落后于复合换热器组。本文基于改进的ε-Ntu方法,结合系统中各换热器的j和f因素,提出了换热器系统适用环境温度预测的面积加权模型。首先,概述了第一排并排布置、后排沿气流方向布置尺寸匹配的冷却剂换热器“3 + 1″”复合换热器系统的结构,并给出了该系统的换热原理。然后,介绍了基于改进的ε-Ntu方法对系统换热量的详细预测。随后进行了现场试验,验证了模型对进一步预测的正确性。最后,对电流系统的稳定性进行了温度预测。结果表明,在16℃条件下,4种换热器的预测换热量分别为37,687.24 W、30,450.47 W、3660.15 W和86,541.42 W,均能满足模型要求,最大误差为5.10%。环境温度34℃,配置3696.57 w冷却剂换热器。期望为工程车辆复合换热系统的性能评价提供科学依据。
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引用次数: 0
Conjugate CFD modeling for Multi-Sample drying of deformable porous food materials 可变形多孔食品物料多试样干燥的耦合CFD建模
Q1 Chemical Engineering Pub Date : 2025-11-01 DOI: 10.1016/j.ijft.2025.101449
Mohammad U.H. Joardder , Abdul Mojid Parvej , Md. BakhtierKhalzi , Azharul Karim
Drying of deformable porous materials (DPMs) involves complex coupling of heat transfer, moisture migration, and structural deformation, which are often oversimplified in conventional models. This study introduces a novel CFD-integrated conjugate model for hot air drying of multiple deformable food samples, capturing real-time changes in air properties and sample interactions. A key innovation lies in the investigation of drying kinetics and temperature distribution under two deformation approaches: (i) uniform deformation using a constant shrinkage velocity, and (ii) non-uniform deformation based on transport properties and the glass transition concept. The model reveals that deformation significantly alters drying kinetics by increasing surface area-to-volume ratio (SAVR), reducing internal resistance, and enhancing heat transfer from surface to center. These effects accelerate moisture migration and improve drying efficiency. Additionally, variations in drying conditions such as air velocity, temperature, and sample arrangement further influence the heat and mass transfer dynamics, leading to spatial disparities in drying rates. Upstream samples dry faster due to higher exposure to hot air, while downstream samples experience delayed moisture loss. The study reveals that deformation patterns and air distribution significantly influence temperature, moisture, and velocity profiles in multi-layer drying. These insights contribute to the development of more uniform and energy-efficient drying strategies for porous food materials.
可变形多孔材料(dpm)的干燥涉及到传热、水分迁移和结构变形的复杂耦合,这在传统模型中往往过于简化。本研究介绍了一种新的cfd集成共轭模型,用于多种可变形食品样品的热风干燥,捕捉空气特性和样品相互作用的实时变化。一个关键的创新在于研究两种变形方法下的干燥动力学和温度分布:(i)使用恒定收缩速度的均匀变形,以及(ii)基于输运性质和玻璃化转变概念的非均匀变形。该模型表明,变形通过增加表面积体积比(SAVR)、减小内阻和增强从表面到中心的传热,显著改变了干燥动力学。这些作用加速水分迁移,提高干燥效率。此外,干燥条件的变化,如空气速度、温度和样品排列进一步影响传热传质动力学,导致干燥速率的空间差异。上游样品干燥更快,由于较高的暴露于热空气,而下游样品经历延迟水分损失。研究表明,在多层干燥过程中,变形模式和气流分布对温度、湿度和速度分布有显著影响。这些见解有助于开发更均匀和节能的多孔食品材料干燥策略。
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引用次数: 0
Thermal analysis of metal foam integrated heatsink for electrified aircraft applications 电气化飞机用金属泡沫集成散热器的热分析
Q1 Chemical Engineering Pub Date : 2025-11-01 DOI: 10.1016/j.ijft.2025.101465
Dikshant Sharma , Lukas Radomsky , Akilan Mathiazhagan , Majid Asli , Klaus Höschler , Regine Mallwitz
Metal foams facilitate large heat dissipation in high-power dense systems such as power electronics for electrified propulsion application. This work addresses the cooling of a power semiconductor device with aluminium and copper metal foam integrated hybrid heatsink and its comparative analysis to a conventional finned heatsink using 0D and 3D modelling approach. Two-equation foam model in Fluent is utilized and the numerical approach is validated against experimental dataset. Inlet air velocity is varied such that the Darcy to turbulent regimes of the open-cellular foams are covered. Foam porosities from 0.850.95 with 10–20 PPI are investigated and the thermal performance of the heatsink is found to be independent of the foam material. High porosity (>0.9), 20 PPI foams are found to aid forced-convection by improving the thermal resistance by more than 10% against the 10 PPI counterparts. The hybrid heatsink outperforms the foam-based and conventional heatsink by 40% and 15% respectively when considering the reduction in junction temperatures, while the hydraulic resistance increases 10 times when compared to the conventional one. The 0D thermal resistance model is robust in predicting the junction temperatures for metal foam heatsinks with only a 5%–6% discrepancy for both the 50 W and 100 W heat load scenarios. The key and novel contribution of this study is the integration of detailed 3D simulations of a power electronics cooling environment with the development of a corresponding 0D thermal model. This approach not only eases the physical representation of the system but also enables the model to be extended to diverse heat load conditions.
金属泡沫有利于高功率密度系统的大散热,例如用于电气化推进应用的电力电子设备。这项工作解决了铝和铜金属泡沫集成混合散热器的功率半导体器件的冷却问题,并使用0D和3D建模方法对其与传统翅片散热器的比较分析。利用Fluent软件中的双方程泡沫模型,通过实验数据对数值方法进行了验证。入口气流速度的变化使得开孔泡沫的达西到湍流状态被覆盖。研究了10-20 PPI的泡沫孔隙率为~ 0.85 ~ 0.95,发现散热器的热性能与泡沫材料无关。高孔隙率(>0.9), 20 PPI泡沫与10 PPI泡沫相比,热阻提高了10%以上,有助于强制对流。考虑到结温的降低,混合散热器的性能分别比泡沫散热器和传统散热器高40%和15%,而液压阻力比传统散热器提高了10倍。0D热阻模型在预测金属泡沫散热器的结温方面是可靠的,在50w和100w热负荷情况下只有5%-6%的差异。本研究的关键和新颖贡献在于将电力电子冷却环境的详细3D模拟与相应的0D热模型的开发相结合。这种方法不仅简化了系统的物理表示,而且使模型能够扩展到不同的热负荷条件。
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引用次数: 0
Nanofluid natural convection in trapezoidal annuli: Comparative effects of triangular, circular, and square inner walls 纳米流体在梯形环空中的自然对流:三角形、圆形和方形内壁的比较效果
Q1 Chemical Engineering Pub Date : 2025-11-01 DOI: 10.1016/j.ijft.2025.101461
M.M. Hasan , M.A. Halim , M.S. Rana , S.Y. Jannaty , M.J. Uddin
This work presents a novel numerical study on how inner-wall geometry influences natural convection in nanofluid-filled trapezoidal annular cavities, which has not been systematically addressed in previous studies. An Al2O3–water nanofluid is examined in three inner-wall configurations: square (Case 1), circular (Case 2), and triangular (Case 3). The governing equations, formulated under the Boussinesq approximation, are solved using the Galerkin finite element method and validated against established benchmark data. The numerical simulations were conducted for nanoparticle volume fractions in the range of ϕ=0.00–0.1, the characteristic length L=0.020.07m, and particle diameters of dp=160nm. These ranges were selected to represent typical conditions encountered in nanofluid-based natural convection systems. The results reveal that the circular wall enhances peak velocity, whereas the triangular wall provides more uniform velocity fields, higher average velocity magnitude, and consistently larger Nusselt numbers compared to the square and circular cases. In addition, the triangular geometry ensures more homogeneous temperature and concentration distributions, which is advantageous for stable thermal performance. The study also identifies optimal nanoparticle loading for enhanced convection, while showing that particle sizes beyond 60nm lead to suppressed transport phenomena. Aspect ratio and wall shape strongly influence skin-friction behavior, highlighting geometry as a key design parameter. Over time, velocity magnitude, Nusselt number, temperature, and nanoparticle concentration initially exhibit transient fluctuations before reaching steady-state, with Case 3 (triangular inner wall configuration) stabilizing fastest in velocity and concentration and achieving the highest heat transfer efficiency. These findings provide physically grounded design guidelines for engineering compact and efficient nanofluid-based thermal management systems.
这项工作提出了一个新的数值研究,内壁几何形状如何影响纳米流体填充的梯形环形腔的自然对流,这在以前的研究中没有系统地解决。在三种内壁结构中检测了al2o3 -水纳米流体:方形(案例1)、圆形(案例2)和三角形(案例3)。用Galerkin有限元法求解了在Boussinesq近似下建立的控制方程,并对建立的基准数据进行了验证。数值模拟的纳米颗粒体积分数范围为φ = 0.00-0.1,特征长度L= 0.02-0.07m,粒径dp= 1-60nm。选择这些范围来代表基于纳米流体的自然对流系统中遇到的典型条件。结果表明,与方形和圆形壁面相比,圆形壁面提高了峰值速度,而三角形壁面提供了更均匀的速度场,更高的平均速度大小和更大的努塞尔数。此外,三角形的几何结构保证了更均匀的温度和浓度分布,这有利于稳定的热性能。该研究还确定了增强对流的最佳纳米颗粒负载,同时表明颗粒尺寸超过~ 60nm会抑制传输现象。宽高比和墙体形状强烈影响摩擦行为,突出几何形状作为关键设计参数。随着时间的推移,速度大小、努塞尔数、温度和纳米颗粒浓度在达到稳态之前最初表现出瞬态波动,情况3(三角形内壁结构)在速度和浓度方面稳定得最快,传热效率最高。这些发现为设计紧凑高效的纳米流体热管理系统提供了物理基础设计指南。
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International Journal of Thermofluids
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