International Journal of Numerical Methods for Heat & Fluid Flow最新文献_第9页

Optimisation of MHD flow within trapezoidal cavity containing hybrid nanofluid by artificial neural network 利用人工神经网络优化含有混合纳米流体的梯形腔内的 MHD 流动

IF 4.2 3区工程技术 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

International Journal of Numerical Methods for Heat & Fluid Flow

Pub Date : 2024-06-18 DOI: 10.1108/hff-01-2024-0058

Arooj Tanveer, Sami Ul Haq, Muhammad Bilal Ashraf, Muhammad Usman Ashraf, R. Nawaz

Purpose

This study aims to numerically investigate heat transport in a trapezoidal cavity using hybrid nanoparticles (Ag-$Al_2O_3$). Unlike previous studies, this one covers magnetohydrodynamics, joule heating with viscous dissipation, heat absorption and generation. The left and right sides of the chasm are frigid. The upper wall heats, whereas the bottom wall remains adiabatic.

Design/methodology/approach

After reducing the system of dimensional equations to dimensionless equations, the authors use the Galerkin finite element method to solve them numerically. Geometric parameters affect heating efficiency; thus, the authors use flow metrics such as the Reynold number Re, magnetic parameter M, volume fraction coefficient, heat absorption and Eckert number Ec. The authors use the finite volume method to solve the governing equations after converting them to dimensionless form. The authors also try the artificial neural network method to predict the innovative cavity’s heat response in future scenarios. Transition state charts, regression analysis, MSE and error histograms accelerate, smooth and accurately converge solutions.

Findings

As the magnetic parameter and Eckert number increase, the enclosure emits more heat. As Reynold and volume fraction coefficients rise, the Nusselt number falls. It rose as magnetic, Eckert and heat absorption characteristics increased. The average Nusselt number rises with Reynolds and volume fraction coefficients. The magnetic, Eckert and heat absorption characteristics have inverse values.

Originality/value

This study numerically investigates heat transport in a trapezoidal cavity using hybrid nanoparticles (Ag-$Al_2O_3$). Unlike previous studies, this one covers MHD, joule heating with viscous dissipation, heat absorption and generation. The left and right sides of the chasm are frigid. The upper wall heats, whereas the bottom wall remains adiabatic.

目的本研究旨在利用混合纳米粒子（Ag-$Al_2O_3$）对梯形空腔中的热传输进行数值研究。与以往研究不同的是，本研究涵盖了磁流体力学、焦耳加热与粘性耗散、吸热与发热。鸿沟的左右两侧是冰冷的。设计/方法/途径在将一维方程系统简化为无量纲方程后，作者使用 Galerkin 有限元法对其进行数值求解。几何参数会影响加热效率；因此，作者使用了雷诺数 Re、磁参数 M、体积分数系数、吸热和埃克特数 Ec 等流动指标。作者使用有限体积法求解将其转换为无量纲形式的控制方程。作者还尝试使用人工神经网络方法来预测创新型空腔在未来情况下的热响应。研究结果随着磁参数和埃克特数的增加，腔体散发出更多的热量。随着雷诺系数和体积分数系数的增加，努塞尔特数下降。随着磁性、埃克特数和吸热特性的增加，努塞尔特数也随之上升。平均努塞特数随雷诺系数和体积分数系数上升而上升。本研究使用混合纳米粒子（Ag-$Al_2O_3$）对梯形空腔中的热传输进行了数值研究。与以往研究不同的是，本研究涵盖了 MHD、焦耳加热与粘性耗散、吸热与发热。鸿沟的左右两侧是冰冷的。上壁发热，而下壁保持绝热。

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引用次数: 0

Turbo-RANS: straightforward and efficient Bayesian optimization of turbulence model coefficients Turbo-RANS：对湍流模型系数进行直接高效的贝叶斯优化

IF 4.2 3区工程技术 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

International Journal of Numerical Methods for Heat & Fluid Flow

Pub Date : 2024-06-13 DOI: 10.1108/hff-12-2023-0726

Ryley McConkey, Nikhila Kalia, Eugene Yee, Fue-Sang Lien

Purpose

Industrial simulations of turbulent flows often rely on Reynolds-averaged Navier-Stokes (RANS) turbulence models, which contain numerous closure coefficients that need to be calibrated. This paper aims to address this issue by proposing a semi-automated calibration of these coefficients using a new framework (referred to as turbo-RANS) based on Bayesian optimization.

Design/methodology/approach

The authors introduce the generalized error and default coefficient preference (GEDCP) objective function, which can be used with integral, sparse or dense reference data for the purpose of calibrating RANS turbulence closure model coefficients. Then, the authors describe a Bayesian optimization-based algorithm for conducting the calibration of these model coefficients. An in-depth hyperparameter tuning study is conducted to recommend efficient settings for the turbo-RANS optimization procedure.

Findings

The authors demonstrate that the performance of the k-ω shear stress transport (SST) and generalized k-ω (GEKO) turbulence models can be efficiently improved via turbo-RANS, for three example cases: predicting the lift coefficient of an airfoil; predicting the velocity and turbulent kinetic energy fields for a separated flow; and, predicting the wall pressure coefficient distribution for flow through a converging-diverging channel.

Originality/value

To the best of the authors’ knowledge, this work is the first to propose and provide an open-source black-box calibration procedure for turbulence model coefficients based on Bayesian optimization. The authors propose a data-flexible objective function for the calibration target. The open-source implementation of the turbo-RANS framework includes OpenFOAM, Ansys Fluent, STAR-CCM+ and solver-agnostic templates for user application.

目的湍流的工业模拟通常依赖于雷诺平均纳维-斯托克斯（RANS）湍流模型，其中包含大量需要校准的闭合系数。作者介绍了广义误差和默认系数偏好（GEDCP）目标函数，该函数可用于积分、稀疏或密集参考数据，以校准 RANS 湍流闭合模型系数。然后，作者介绍了一种基于贝叶斯优化的算法，用于校准这些模型系数。研究结果作者证明了 k-ω 剪切应力传输 (SST) 和广义 k-ω (GEKO) 湍流模型的性能可以通过涡轮-RANS 得到有效改善，适用于以下三种情况：预测机翼的升力系数；预测分离流的速度场和湍流动能场；预测流经汇聚-发散通道的壁面压力系数分布。原创性/价值据作者所知，这项研究首次提出并提供了基于贝叶斯优化的湍流模型系数开源黑盒校准程序。作者为校准目标提出了一个数据灵活的目标函数。turbo-RANS 框架的开源实现包括 OpenFOAM、Ansys Fluent、STAR-CCM+ 和面向用户应用的求解器无关模板。

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引用次数: 0

Effects of vibration on natural convection in a square inclined porous enclosure filled with Cu-water nanofluid 振动对充满铜-水纳米流体的方形倾斜多孔围墙内自然对流的影响

IF 4.2 3区工程技术 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

International Journal of Numerical Methods for Heat & Fluid Flow

Pub Date : 2024-06-13 DOI: 10.1108/hff-01-2024-0074

Hamza Sayyou, Jabrane Belabid, Hakan F. Öztop, Karam Allali

<h3>Purpose</h3><p>The purpose of this paper is to investigate the effects of gravitational modulation on natural convection in a square inclined porous cavity filled by a fluid containing copper nanoparticles.</p><h3>Design/methodology/approach</h3><p>The present study uses a system of equations that couple hydrodynamics to heat transfer, representing the governing equations of fluid flow in a square domain. The Boussinesq–Darcy flow with Cu-water nanofluid is considered. The dimensionless partial differential equations are solved numerically using finite difference method based on alternating direction implicit scheme. The cavity is differentially heated by constant heat flux, while the top and bottom walls are insulated. The authors examined the effects of gravity amplitude (λ), vibration frequency (σ), tilt angle (α) and Rayleigh number (Ra) on flow and temperature.</p><h3>Findings</h3><p>The numerical simulations, in the form of streamlines, isotherms, Nusselt number and maximum stream function for different values of amplitude, frequency, tilt angle and Rayleigh number, have revealed an oscillatory behavior in the development of flow and temperature under gravity modulation. An increase of amplitude from 0.5 to 1 intensifies the flow stream (from |ψ<sub>max</sub>| = 21.415 to |ψ<sub>max</sub>| = 25.262) and improves heat transfer (from <span><mml:math display="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mover accent="true"><mml:mrow><mml:mi>N</mml:mi><mml:mi>u</mml:mi></mml:mrow><mml:mo stretchy="true">¯</mml:mo></mml:mover></mml:math></span> = 17.592 to <span><mml:math display="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mover accent="true"><mml:mrow><mml:mi>N</mml:mi><mml:mi>u</mml:mi></mml:mrow><mml:mo stretchy="true">¯</mml:mo></mml:mover></mml:math></span> = 20.421). Low-frequency vibration below 50 has a significant impact on the flow and thermal distributions. However, once this threshold is exceeded, the flow weakens, leading to a gradual decrease in heat transfer rate. The inclination angle is an effective parameter for controlling the flow and temperature characteristics. Thus, transitioning the tilt angle from 30° to 60° can increase the flow velocity (from 22.283 to 23.288) while reducing the Nusselt number (from 16.603 to 13.874). Therefore, by manipulating the combination of vibration and inclination, it is founded that for a fixed frequency value of σ = 100 and for increased amplitude (from 0.5 to 1), the flow intensity at inclination of 60° is boosted, and an increase of the heat transfer rate at inclination of 30° is also observed. Convective thermal instabilities may arise depending on the different key factors.</p><h3>Originality/value</h3><p>To the best of the authors’ knowledge, this study is original in its examination of the combined effects of modulated gravity and cavity inclination on free convection in

本文旨在研究重力调制对由含铜纳米颗粒的流体填充的正方形倾斜多孔空腔中自然对流的影响。考虑了铜-水纳米流体的 Boussinesq-Darcy 流动。采用基于交替方向隐式方案的有限差分法对无量纲偏微分方程进行数值求解。空腔通过恒定热通量进行差分加热，而顶壁和底壁是隔热的。作者研究了重力振幅 (λ)、振动频率 (σ)、倾斜角 (α) 和瑞利数 (Ra) 对流动和温度的影响。研究结果数值模拟显示，在不同的振幅、频率、倾斜角和瑞利数值下，流线、等温线、努塞尔特数和最大流函数的形式显示了重力调制下流动和温度发展的振荡行为。振幅从 0.5 增加到 1 会增强流体流动（从 |ψmax| = 21.415 增加到 |ψmax| = 25.262）并改善传热（从 Nu¯ = 17.592 增加到 Nu¯ = 20.421）。低于 50 的低频振动对流动和热分布有显著影响。然而，一旦超过这个阈值，流动就会减弱，导致传热率逐渐下降。倾斜角是控制流动和温度特性的有效参数。因此，将倾斜角从 30° 过渡到 60° 可以提高流速（从 22.283 提高到 23.288），同时降低努塞尔特数（从 16.603 降低到 13.874）。因此，通过调节振动和倾角的组合，可以发现在固定频率值 σ = 100 和增加振幅（从 0.5 到 1）的情况下，倾角为 60°的流动强度会得到提高，倾角为 30°的传热速率也会增加。根据不同的关键因素，可能会产生对流热不稳定性。原创性/价值据作者所知，这项研究是对调制重力和空腔倾角对纳米流体多孔介质中自由对流的综合影响进行的原创性研究。它强调了这两个重要因素在影响流动和传热特性方面的关键作用。

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引用次数: 0

Honeycomb-configured dissipative nanofluid flow within a squeezed channel with entropy generation: regression and numerical evaluations 带熵生成的挤压通道内的蜂窝配置耗散纳米流体流动：回归和数值评估

IF 4.2 3区工程技术 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

International Journal of Numerical Methods for Heat & Fluid Flow

Pub Date : 2024-06-05 DOI: 10.1108/hff-12-2023-0739

Syed Modassir Hussain, Rohit Sharma, Manoj Kumar Mishra, Jitendra Kumar Singh

Purpose

Nanosized honeycomb-configured materials are used in modern technology, thermal science and chemical engineering due to their high ultra thermic relevance. This study aims to scrutinize the heat transmission features of magnetohydrodynamic (MHD) honeycomb-structured graphene nanofluid flow within two squeezed parallel plates under Joule dissipation and solar thermal radiation impacts.

Design/methodology/approach

Mass, energy and momentum preservation laws are assumed to find the mathematical model. A set of unified ordinary differential equations with nonlinear behavior is used to express the correlated partial differential equations of the established models, adopting a reasonable similarity adjustment. An approximate convergent numerical solution to these equations is evaluated by the shooting scheme with the Runge–Kutta–Fehlberg (RKF45) technique.

Findings

The impression of pertinent evolving parameters on the temperature, fluid velocity, entropy generation, skin friction coefficients and the heat transference rate is explored. Further, the significance of the irreversibility nature of heat transfer due to evolving flow parameters are evaluated. It is noted that the heat transference rate performance is improved due to the imposition of the allied magnetic field, Joule dissipation, heat absorption, squeezing and thermal buoyancy parameters. The entropy generation upsurges due to rising magnetic field strength while its intensification is declined by enhancing the porosity parameter.

Originality/value

The uniqueness of this research work is the numerical evaluation of MHD honeycomb-structured graphene nanofluid flow within two squeezed parallel plates under Joule dissipation and solar thermal radiation impacts. Furthermore, regression models are devised to forecast the correlation between the rate of thermal heat transmission and persistent flow parameters.

目的纳米蜂窝结构材料因其高度的超热相关性而被广泛应用于现代科技、热科学和化学工程领域。本研究旨在仔细研究在焦耳耗散和太阳热辐射影响下，两块挤压平行板内的磁流体力学（MHD）蜂窝结构石墨烯纳米流体的传热特性。采用合理的相似性调整，用一组统一的非线性常微分方程来表达已建立模型的相关偏微分方程。采用 Runge-Kutta-Fehlberg (RKF45) 技术的射击方案对这些方程的近似收敛数值解进行了评估。此外，还评估了由于流动参数不断变化而导致传热不可逆的重要性。研究发现，由于施加了联合磁场、焦耳耗散、吸热、挤压和热浮力参数，热传导率性能得到了改善。该研究工作的独特之处在于对焦耳耗散和太阳热辐射影响下两个挤压平行板内的 MHD 蜂窝结构石墨烯纳米流体流动进行了数值评估。此外，还设计了回归模型来预测热传导率与持续流动参数之间的相关性。

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引用次数: 0

AI based optimal analysis of electro-osmotic peristaltic motion of non-Newtonian fluid with chemical reaction using artificial neural networks and response surface methodology 基于人工智能的非牛顿流体电渗透蠕动运动优化分析（使用人工神经网络和响应面方法

IF 4.2 3区工程技术 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

International Journal of Numerical Methods for Heat & Fluid Flow

Pub Date : 2024-06-04 DOI: 10.1108/hff-01-2024-0016

Ahmed Zeeshan, Zaheer Asghar, Amad ur Rehaman

Purpose

The present work is devoted to investigating the sensitivity analysis of the electroosmotic peristaltic motion of non-Newtonian Casson fluid with the effect of the chemical reaction and magnetohydrodynamics through the porous medium. The main focus is on flow efficiency quantities such as pressure rise per wavelength, frictional forces on the upper wall and frictional forces on the lower wall. This initiative is to bridge the existing gap in the available literature.

Design/methodology/approach

The governing equations of the problem are mathematically formulated and subsequently simplified for sensitivity analysis under the assumptions of a long wavelength and a small Reynolds number. The simplified equations take the form of coupled nonlinear differential equations, which are solved using the built-in Matlab routine bvp4c. The response surface methodology and artificial neural networks are used to develop the empirical model for pressure rise per wavelength, frictional forces on the upper wall and frictional forces on the lower wall.

Findings

The empirical model demonstrates an excellent fit with a coefficient of determination reaching 100% for responses, frictional forces on the upper wall and frictional forces on the lower wall and 99.99% for response, for pressure rise per wavelength. It is revealed through the sensitivity analysis that pressure rise per wavelength, frictional forces on the upper wall and frictional forces on the lower wall are most sensitive to the permeability parameter at all levels.

Originality/value

The objective of this study is to use artificial neural networks simulation and analyze the sensitivity of electroosmotic peristaltic motion of non-Newtonian fluid with the effect of chemical reaction.

目的本文致力于研究非牛顿卡逊流体在化学反应和磁流体力学作用下通过多孔介质的电渗蠕动运动的敏感性分析。重点是流动效率量，如每波长压力上升、上壁摩擦力和下壁摩擦力。在长波长和小雷诺数的假设条件下，对问题的支配方程进行了数学计算和简化，以便进行敏感性分析。简化方程采用耦合非线性微分方程的形式，使用 Matlab 内置的 bvp4c 例程求解。研究结果经验模型的拟合度非常高，对每波长压力上升、上壁摩擦力和下壁摩擦力的响应的判定系数达到 100%，对每波长压力上升的响应的判定系数达到 99.99%。敏感性分析表明，在所有水平上，每波长压力上升、上壁摩擦力和下壁摩擦力对渗透性参数最为敏感。

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引用次数: 0

A modified Green-Naghdi fractional order model for analyzing thermoelectric MHD 用于分析热电 MHD 的改进型格林-纳格迪分数阶模型

IF 4.2 3区工程技术 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

International Journal of Numerical Methods for Heat & Fluid Flow

Pub Date : 2024-05-31 DOI: 10.1108/hff-02-2024-0133

Mohamed M. Hendy, Magdy A. Ezzat

Purpose

Whereas, the classical Green-Naghdi Type II (GN-II) model struggles to accurately represent the thermo-mechanical behavior of thermoelectric MHD due to its inability to account for the memory effect. A new mathematical model of the GN-II theory incorporates a fractional order of heat transport to address this issue.

Design/methodology/approach

The employment of the matrix exponential method, which forms the basis of the state-space approach in contemporary theory, is central to this strategy. The resulting formulation, together with the Laplace transform techniques, is applied to a variety of problems. Solutions to a thermal shock problem and to a problem of a layer media both without heat sources are obtained. Also, a problem with the distribution of heat sources is considered. The numerical technique is used to achieve the Laplace transform inversion.

Findings

According to the numerical results and its graphs, the influences of the fractional order parameters, figure-of-merit factor, thermoelectric power and Peltier coefficient on the behavior of the field quantities are investigated in the new theory.

Originality/value

The new modeling of thermoelectric MHD has advanced significantly as a result of this work, providing a more thorough and precise tool for forecasting the behavior of these materials under a range of thermal and magnetic conditions.

目的由于经典的格林-纳格迪 II 型（GN-II）模型无法解释记忆效应，因此难以准确表示热电 MHD 的热机械行为。为解决这一问题，GN-II 理论的一个新数学模型纳入了分数阶热传输。由此产生的公式与拉普拉斯变换技术一起被应用于各种问题。我们获得了热冲击问题和无热源层介质问题的解决方案。此外，还考虑了热源分布问题。根据数值结果及其图表，新理论研究了分数阶参数、商数因子、热电功率和珀尔帖系数对场量行为的影响。原创性/价值由于这项工作，热电 MHD 的新建模取得了重大进展，为预测这些材料在一系列热和磁条件下的行为提供了更全面、更精确的工具。

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引用次数: 0

A neural based modeling approach for predicting effective thermal conductivity of brewer’s spent grain 基于神经建模的啤酒糟有效导热率预测方法

IF 4.2 3区工程技术 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

International Journal of Numerical Methods for Heat & Fluid Flow

Pub Date : 2024-05-31 DOI: 10.1108/hff-10-2023-0594

Amanda de Oliveira e Silva, Alice Leonel, Maisa Tonon Bitti Perazzini, Hugo Perazzini

Purpose

Brewer's spent grain (BSG) is the main by-product of the brewing industry, holding significant potential for biomass applications. The purpose of this paper was to determine the effective thermal conductivity (k_eff) of BSG and to develop an Artificial Neural Network (ANN) to predict k_eff, since this property is fundamental in the design and optimization of the thermochemical conversion processes toward the feasibility of bioenergy production.

Design/methodology/approach

The experimental determination of k_eff as a function of BSG particle diameter and heating rate was performed using the line heat source method. The resulting values were used as a database for training the ANN and testing five multiple linear regression models to predict k_eff under different conditions.

Findings

Experimental values of k_eff were in the range of 0.090–0.127 W m⁻¹ K⁻¹, typical for biomasses. The results showed that the reduction of the BSG particle diameter increases k_eff, and that the increase in the heating rate does not statistically affect this property. The developed neural model presented superior performance to the multiple linear regression models, accurately predicting the experimental values and new patterns not addressed in the training procedure.

Originality/value

The empirical correlations and the developed ANN can be utilized in future work. This research conducted a discussion on the practical implications of the results for biomass valorization. This subject is very scarce in the literature, and no studies related to k_eff of BSG were found.

目的酿酒废谷物（BSG）是酿造业的主要副产品，在生物质应用方面具有巨大潜力。本文的目的是确定 BSG 的有效热导率（keff），并开发一个人工神经网络（ANN）来预测 keff，因为这一特性是设计和优化热化学转换过程以实现生物能源生产可行性的基础。实验结果实验值在 0.090-0.127 W m-1 K-1 之间，是生物质的典型值。结果表明，BSG 颗粒直径的减小会增加 keff，而加热速率的增加在统计学上不会影响这一特性。与多元线性回归模型相比，所开发的神经模型性能更优越，能准确预测实验值和训练程序中未涉及的新模式。本研究就结果对生物质价值评估的实际影响进行了讨论。这一主题在文献中非常罕见，也没有发现与 BSG keff 相关的研究。

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引用次数: 0

Investigating embedded data distribution strategy on reconstruction accuracy of flow field around the crosswind-affected train based on physics-informed neural networks 基于物理信息神经网络的嵌入式数据分布策略对横风影响列车周围流场重建精度的影响研究

IF 4.2 3区工程技术 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

International Journal of Numerical Methods for Heat & Fluid Flow

Pub Date : 2024-05-28 DOI: 10.1108/hff-11-2023-0709

Guang-Zhi Zeng, Zheng-Wei Chen, Yi-Qing Ni, En-Ze Rui

Purpose

Physics-informed neural networks (PINNs) have become a new tendency in flow simulation, because of their self-advantage of integrating both physical and monitored information of fields in solving the Navier–Stokes equation and its variants. In view of the strengths of PINN, this study aims to investigate the impact of spatially embedded data distribution on the flow field results around the train in the crosswind environment reconstructed by PINN.

Design/methodology/approach

PINN can integrate data residuals with physical residuals into the loss function to train its parameters, allowing it to approximate the solution of the governing equations. In addition, with the aid of labelled training data, PINN can also incorporate the real site information of the flow field in model training. In light of this, the PINN model is adopted to reconstruct a two-dimensional time-averaged flow field around a train under crosswinds in the spatial domain with the aid of sparse flow field data, and the prediction results are compared with the reference results obtained from numerical modelling.

Findings

The prediction results from PINN results demonstrated a low discrepancy with those obtained from numerical simulations. The results of this study indicate that a threshold of the spatial embedded data density exists, in both the near wall and far wall areas on the train’s leeward side, as well as the near train surface area. In other words, a negative effect on the PINN reconstruction accuracy will emerge if the spatial embedded data density exceeds or slips below the threshold. Also, the optimum arrangement of the spatial embedded data in reconstructing the flow field of the train in crosswinds is obtained in this work.

Originality/value

In this work, a strategy of reconstructing the time-averaged flow field of the train under crosswind conditions is proposed based on the physics-informed data-driven method, which enhances the scope of neural network applications. In addition, for the flow field reconstruction, the effect of spatial embedded data arrangement in PINN is compared to improve its accuracy.

目的物理信息神经网络（PINNs）因其在求解纳维-斯托克斯方程及其变体时可同时整合物理场和监测场信息的自身优势，已成为流动模拟领域的一种新趋势。鉴于 PINN 的优势，本研究旨在探讨空间嵌入式数据分布对 PINN 重建的横风环境下列车周围流场结果的影响。此外，借助标注的训练数据，PINN 还能将流场的实际现场信息纳入模型训练。有鉴于此，我们采用 PINN 模型，借助稀疏流场数据，在空间域重建了横风条件下列车周围的二维时均流场，并将预测结果与数值模拟的参考结果进行了比较。研究结果表明，在列车背风面的近壁和远壁区域，以及列车近表面区域，都存在空间嵌入数据密度的临界值。换句话说，如果空间嵌入数据密度超过或低于阈值，就会对 PINN 重建精度产生负面影响。原创性/价值在这项工作中，基于物理信息数据驱动方法，提出了一种在横风条件下重建列车时均流场的策略，扩大了神经网络的应用范围。此外，针对流场重建，比较了 PINN 中空间嵌入数据排列的效果，以提高其准确性。

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引用次数: 0

Phase transition of multiple encapsulated PCMs in a U-shaped channel under MHD with ternary nanofluid 三元纳米流体 MHD 下 U 形通道中多个封装 PCM 的相变

IF 4.2 3区工程技术 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

International Journal of Numerical Methods for Heat & Fluid Flow

Pub Date : 2024-05-21 DOI: 10.1108/hff-12-2023-0732

Fatih Selimefendigil, Hakan F. Oztop

Purpose

Multiple encapsulated phase change materials (PCMs) are used in a wide range of applications, including convective drying, electronic cooling, waste heat recovery and air conditioning. Therefore, it is important to understand the performance of multiple PCMs in channels with flow separation and develop methods to increase their effectiveness. The aim of the study is to analyze the phase transition dynamics of multiple encapsulated PCMs mounted in a U-shaped tube under inclined magnetic field by using ternary nanofluid.

Design/methodology/approach

The PCMs used in the upper horizontal channel, vertical channel and lower horizontal channel are denoted by M1, M2 and M3. Magnetic field is uniform and inclined while finite element method is used as the solution technique. Triple encapsulated-PCM system study is carried out taking into account different values of Reynolds number (Re, ranges from 300 to 1,000), Hartmann number (Ha ranges from 0 and 60), magnetic field inclination (between 0 and 90) and solid volume fraction of ternary nanofluid (between 0 and 0.03). The dynamic response of the liquid fraction is estimated for each PCM with varying Re, Ha and t using an artificial neural network.

Findings

It is observed that for PCMs M2 and M3, the influence of Re on the phase transition is more effective. For M2 and M3, entire transition time (t-F) lowers by approximately 47% and 47.5% when Re is increased to its maximum value, whereas it only falls by 10% for M1. The dynamic characteristics of the phase transition are impacted by imposing MGF and varying its strength and inclination. When Ha is raised from Ha = 0 to Ha = 50, the t-F for PCM-M2 (PCM-M3) falls (increases) by around 30% (29%). For PCMs M1, M2 and M3, the phase transition process accelerates by around 20%, 30% and 28% when the solid volume fraction is increased to its maximum value.

Originality/value

Outcomes of this research is useful for understanding the phase change behavior of multiple PCMs in separated flow and using various methods such as nano-enhanced magnetic field to improve their effectiveness. Research outputs are beneficial for initial design and optimization of using multiple PCMs in diverse energy system technologies, including solar power, waste heat recovery, air conditioning, thermal management and drying.

目的多重封装相变材料（PCM）应用广泛，包括对流干燥、电子冷却、废热回收和空调。因此，了解多重 PCM 在具有流动分离的通道中的性能并开发提高其有效性的方法非常重要。本研究的目的是利用三元纳米流体分析安装在 U 形管中的多个封装 PCM 在倾斜磁场下的相变动力学。磁场为均匀倾斜磁场，采用有限元法作为求解技术。在考虑到雷诺数（Re，范围在 300 到 1,000 之间）、哈特曼数（Ha，范围在 0 到 60 之间）、磁场倾斜度（0 到 90 之间）和三元纳米流体的固体体积分数（0 到 0.03 之间）的不同值时，进行了三重封装-PCM 系统研究。研究结果表明，对于 PCM M2 和 M3，Re 对相变的影响更为有效。对于 M2 和 M3，当 Re 增加到最大值时，整个转变时间 (t-F) 缩短了约 47% 和 47.5%，而对于 M1，仅缩短了 10%。施加 MGF 并改变其强度和倾斜度会影响相变的动态特性。当 Ha 从 Ha = 0 增加到 Ha = 50 时，PCM-M2（PCM-M3）的 t-F 下降（增加）约 30%（29%）。对于 PCM-M1、M2 和 M3，当固体体积分数增加到最大值时，相变过程会加快约 20%、30% 和 28%。研究成果有助于在太阳能发电、废热回收、空调、热管理和干燥等各种能源系统技术中使用多重 PCM 的初步设计和优化。

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引用次数: 0

On the extension of a Riemann solver for RANS simulations 关于为 RANS 模拟扩展黎曼求解器

IF 4.2 3区工程技术 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

International Journal of Numerical Methods for Heat & Fluid Flow

Pub Date : 2024-05-16 DOI: 10.1108/hff-11-2023-0708

Axel Buck, Christian Mundt

Purpose

Reynolds-averaged Navier–Stokes (RANS) models often perform poorly in shock/turbulence interaction regions, resulting in excessive wall heat load and incorrect representation of the separation length in shockwave/turbulent boundary layer interactions. The authors suggest that this can be traced back to inadequate numerical treatment of the inviscid fluxes. The purpose of this study is an extension to the well-known Harten, Lax, van Leer, Einfeldt (HLLE) Riemann solver to overcome this issue.

Design/methodology/approach

It explicitly takes into account the broadening of waves due to the averaging procedure, which adds numerical dissipation and reduces excessive turbulence production across shocks. The scheme is derived based on the HLLE equations, and it is tested against three numerical experiments.

Findings

Sod’s shock tube case shows that the scheme succeeds in reducing turbulence amplification across shocks. A shock-free turbulent flat plate boundary layer indicates that smooth flow at moderate turbulence intensity is largely unaffected by the scheme. A shock/turbulent boundary layer interaction case with higher turbulence intensity shows that the added numerical dissipation can, however, impair the wall heat flux distribution.

Originality/value

The proposed scheme is motivated by implicit large eddy simulations that use numerical dissipation as subgrid-scale model. Introducing physical aspects of turbulence into the numerical treatment for RANS simulations is a novel approach.

目的雷诺平均纳维-斯托克斯（RANS）模型在冲击波/湍流相互作用区域通常表现不佳，导致壁面热负荷过大以及在冲击波/湍流边界层相互作用中分离长度表示不正确。作者认为，这可以追溯到对不粘性通量的数值处理不当。本研究的目的是对著名的 Harten、Lax、van Leer、Einfeldt（HLLE）黎曼求解器进行扩展，以克服这一问题。该方案是基于 HLLE 方程推导出来的，并通过三个数值实验对其进行了测试。无冲击湍流平板边界层表明，中等湍流强度的平滑流动基本不受该方案的影响。在湍流强度较高的冲击/湍流边界层相互作用情况下，增加的数值耗散可能会影响壁面热通量分布。在 RANS 模拟的数值处理中引入湍流的物理方面是一种新方法。

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引用次数: 0