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Machine learning based flow simulator: Flow around an airfoil with vortex generators 机器学习为基础的流动模拟器:流动周围的翼型与涡发生器
IF 2.5 3区 工程技术 Q2 MECHANICS Pub Date : 2025-11-19 DOI: 10.1016/j.euromechflu.2025.204417
Muharrem Hilmi Aksoy , Murat Ispir , Mahdi Tabatabaei Malazi , Abdulkerim Okbaz
Controlling the flow structure around an airfoil is crucial for increasing lift and reducing drag. Delaying flow separation improves aerodynamic performance, especially in aircraft and wind turbines. In recent years, artificial intelligence and machine learning methods have emerged as fast and cost-effective alternatives to traditional approaches in fluid mechanics. In this study, we aimed to control the flow around the NACA (National Advisory Committee for Aeronautics) 4412 airfoil using vortex generators (VGs) and to develop a machine-learning-based flow simulator that predicts velocity components based on angle of attack, VG yaw angle, and spatial coordinates. Experimental measurements were conducted in an open-surface, closed-loop water channel at a Reynolds number of Re = 1.0 × 10⁴ using a two-dimensional Particle Image Velocimetry (PIV) system. A total of 60,500 data points were collected per velocity component from 20 experimental cases within the range of α = 0°–20° and β = 15°–30°. A Multilayer Perceptron (MLP) model implemented using TensorFlow was trained to predict the ensemble-averaged 〈u〉 and 〈v〉 velocity components. We analyzed the effects of hidden layer neuron count and mini-batch size, achieving the highest accuracy with 41 neurons and a batch size of 4, yielding R² values of 0.978 for 〈u〉 and 0.950 for 〈v〉. The error distributions were symmetric and closely approximated a Gaussian distribution. Experimental results showed that VGs delayed early-stage flow separation at low α but became less effective at higher α. The MLP model successfully reconstructed major flow features, providing a reliable data-driven alternative to CFD-based methods. Future work will extend the model to various airfoils, VG designs, Reynolds numbers, and unsteady flows using time-resolved PIV data.
控制翼型周围的流动结构是增加升力和减少阻力的关键。延迟流动分离可以改善空气动力学性能,特别是在飞机和风力涡轮机中。近年来,人工智能和机器学习方法已经成为流体力学中传统方法的快速和经济的替代品。在这项研究中,我们的目标是使用涡发生器(VG)控制NACA(美国国家航空咨询委员会)4412翼型周围的流动,并开发一个基于机器学习的流动模拟器,该模拟器可以根据迎角、VG偏航角和空间坐标来预测速度分量。实验测量采用二维粒子图像测速(PIV)系统,在雷诺数Re = 1.0 × 10⁴的开表面闭环水道中进行。在α = 0°-20°和β = 15°-30°范围内的20个实验案例中,每个速度分量共收集了60500个数据点。使用TensorFlow实现的多层感知器(MLP)模型被训练来预测集合平均< u >和< v >速度分量。我们分析了隐藏层神经元数量和小批大小的影响,在41个神经元和4个批大小的情况下获得了最高的准确性,< u >和< v >的R²值分别为0.978和0.950。误差分布是对称的,近似于高斯分布。实验结果表明,在低α条件下,VGs延迟了早期的流动分离,而在高α条件下,VGs的作用减弱。MLP模型成功地重建了主要的流体特征,为基于cfd的方法提供了可靠的数据驱动替代方案。未来的工作将扩展模型到各种翼型,VG设计,雷诺数,和非定常流动使用时间分辨PIV数据。
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引用次数: 0
Effect of momentum flux ratio on the flow and combustion behavior of coaxial jets with annular blockage 动量通量比对环形阻塞同轴射流流动和燃烧特性的影响
IF 2.5 3区 工程技术 Q2 MECHANICS Pub Date : 2025-11-14 DOI: 10.1016/j.euromechflu.2025.204415
Shiferaw Regassa Jufar , Minh Duc Le
The flow and combustion characteristics of coaxial jets with annular blockage have been studied numerically. The model was validated with experimental results from related studies. Based on the observations presented in the study, two dominant flow regimes were identified as the momentum flux ratio varied. These regimes can be classified as either central or annular jet-dominated, based on the nature of the vortical structures and stagnation points in the flow field. The central jet-dominated flow occurs at momentum flux ratios below 0.25, where entrainment in the inner mixing region plays a key role. In contrast, the annular jet-dominated flow, which occurs at momentum flux ratios above 2.5, enhances mixing through the recirculation of streams within the counter-rotating vortex rings. In combustion, low momentum flux ratios result in longer flame lengths due to the absence of stagnation points and counter-rotating vortex rings, which lead to poor mixing performance. At higher momentum flux ratios, the formation of counter-rotating vortex rings and the stagnation points enhance mixing, resulting in shorter flame lengths and improved combustion performance. The novelty of this study lies in defining the characteristic flow regimes based on the Reynolds numbers of the annular and central jets, which helps distinguish the dominant flow modes. For a given Reynolds number of the jets, the prevailing mode can be identified to optimize both mixing and combustion performance.
用数值方法研究了带环形阻塞的同轴射流的流动和燃烧特性。用相关研究的实验结果对模型进行了验证。根据研究中提出的观察,确定了动量通量比变化时的两种主要流动形式。根据流场中旋涡结构和滞止点的性质,这些状态可以分为中心型和环状型两种。在动量通量比小于0.25时,中心射流占主导地位,内部混合区的夹带起关键作用。相反,在动量通量比大于2.5时,环形射流主导的流动通过在反向旋转的涡旋环内的流的再循环增强了混合。在燃烧过程中,动量通量比较低,由于没有停滞点和反向旋转的涡流环,导致火焰长度较长,导致混合性能较差。在较高的动量通量比下,反向旋转涡环和驻点的形成增强了混合,从而缩短了火焰长度,改善了燃烧性能。本研究的新颖之处在于基于环形和中心射流的雷诺数定义了特征流型,这有助于区分主要的流动模式。对于给定的射流雷诺数,可以识别主导模式,以优化混合和燃烧性能。
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引用次数: 0
Bound states for a quasigeostrophic two-layer model in a baroclinic shear flow 斜压切变流中准等转两层模型的束缚态
IF 2.5 3区 工程技术 Q2 MECHANICS Pub Date : 2025-11-12 DOI: 10.1016/j.euromechflu.2025.204403
Xi-Hu Wu , Yuan Shen
In geophysical hydrodynamics, baroclinic instability refers to the process in which the perturbations absorb energy from potential energy of the mean flow. In this manuscript, we focus our attention on a nonlinear system modeling the propagation of the wave packet within a quasigeostrophic two-layer model in a baroclinic shear flow. With the aid of the generalized Darboux transformation method, we derive several types of the semi-rational solutions to explore bound states among the localized waves and multi-pole localized waves. On different backgrounds, the wave packet and the wave-induced modification of the basic flow manifest themselves as the bound states among multiple solitons/breathers, the bound states among a single soliton/breather component and the multi-pole solitons/breathers, and the bound states among two sets of the double-pole solitons. Physical dynamics of those bound-state nonlinear waves are discussed. We find that the bound states among the solitons/breathers exhibit periodic attractions or repulsions, while the bound states among the solitons/breathers and multi-pole solitons/breathers exhibit non-periodic interactions. This work may provide theoretical support and explanations for the complex and variable natural mechanisms underlying baroclinic instability.
在地球物理流体力学中,斜压不稳定是指扰动从平均流的势能中吸收能量的过程。在本文中,我们将注意力集中在一个非线性系统中,模拟了斜压切变流中准等转两层模型中波包的传播。利用广义Darboux变换方法,导出了几种类型的半有理解,用于探索局域波和多极局域波之间的界态。在不同的背景下,基本流的波包和波致修正表现为多个孤子/呼吸子之间的束缚态、单个孤子/呼吸子与多极孤子/呼吸子之间的束缚态以及两组双极孤子之间的束缚态。讨论了这些束缚态非线性波的物理动力学。我们发现孤子/呼吸子之间的束缚态表现出周期性的吸引或排斥,而孤子/呼吸子和多极孤子/呼吸子之间的束缚态表现出非周期性的相互作用。本研究为斜压不稳定复杂多变的自然机制提供了理论支持和解释。
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引用次数: 0
Electrokinetic ion transport of non-Newtonian fluids in a bipolar nanochannel 双极纳米通道中非牛顿流体的电动力学离子输运
IF 2.5 3区 工程技术 Q2 MECHANICS Pub Date : 2025-11-12 DOI: 10.1016/j.euromechflu.2025.204416
Jie Li, Li Peng, Yu Hao
Precise regulation of ion transport in nanofluidics demonstrates great application prospects in the field of ion separation and pre-enrichment. Compared with unipolar nanochannels, bipolar nanochannels show superior performance in ion transport control and can achieve higher ion enrichment ratio and ion interception efficiency. Beyond these fundamental advantages, such nanofluidics gain additional relevance from the widespread use of non-Newtonian fluids across biomedical and chemical applications. This research explores a novel approach—converting a unipolar nanochannel into a bipolar configuration by integrating a gated structure at its center and utilizing a positively charged surface. The Navier-Stokes equations model fluid dynamics, while the Poisson-Nernst-Planck formulation depicts electric potential and ion concentration profiles. Through numerical simulations, the electrokinetic transport behavior of power-law fluids within the bipolar nanochannel is analyzed. The findings indicate that for the fluid characterized by a power-law index of n = 0.95, a rise in gate surface charge density from 0 to 25 mC/m2 leads to a roughly 25 % boost in ionic current. However, this increase comes at a cost—the ion selectivity coefficient drops sharply by 46 %. Furthermore, at gate densities of 0 and 40 mC/m2, the power-law index rises from 0.95 to 1.05, with the ionic current climbing about 31 % and 4 % accordingly.
纳米流体中离子输运的精确调控在离子分离和预富集领域具有广阔的应用前景。与单极纳米通道相比,双极纳米通道具有更好的离子输运控制性能,可以实现更高的离子富集率和离子拦截效率。除了这些基本优势之外,这种纳米流体还因非牛顿流体在生物医学和化学应用中的广泛应用而获得了额外的相关性。本研究探索了一种新颖的方法,通过在其中心集成门控结构并利用带正电的表面将单极纳米通道转换为双极结构。Navier-Stokes方程模拟流体动力学,而泊松-能斯特-普朗克公式描述电势和离子浓度分布。通过数值模拟,分析了幂律流体在双极纳米通道内的电动力学输运行为。研究结果表明,对于幂律指数为n = 0.95的流体,栅极表面电荷密度从0增加到25 mC/m2,导致离子电流增加约25 %。然而,这种增加是有代价的——离子选择系数急剧下降了46% %。在栅极密度为0和40 mC/m2时,幂律指数从0.95上升到1.05,离子电流相应上升约31% %和4% %。
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引用次数: 0
Development of aeroacoustic control devices for a square cylinder using adjoint lattice Boltzmann method 用伴随晶格玻尔兹曼方法研制方形圆柱体气动声控制装置
IF 2.5 3区 工程技术 Q2 MECHANICS Pub Date : 2025-11-08 DOI: 10.1016/j.euromechflu.2025.204413
Kazuya Kusano
The control of aerodynamic noise is essential in various fields, including mechanical and aerospace engineering applications such as pantographs of high-speed trains and aircraft landing gears. Traditional devices, such as splitter plates, have long been employed to suppress wake flows and the resulting noise; however, the development of novel devices that outperform these classical designs has yet to be achieved. The present study seeked to develop innovative control devices using an aeroacoustic optimization framework that integrates the lattice Boltzmann method (LBM) with the adjoint method to modify the rear surface of a square cylinder. The Reynolds number was set to 150 for a two-dimensional laminar flow, and the Mach number was set to 0.2. The optimization created a ridge shape near the rear edge. Flow and acoustic analyses using the LBM showed that this shape successfully suppressed wake flow oscillations and mitigated the generation of aeolian tones. Additionally, a new passive control technique, namely, the installation of tapered splitter plates near the rear edge of the square cylinder, was proposed by simplifying the optimized shape. The LBM simulations demonstrated that the tapered splitter plates outperformed the conventional straight splitter plates in controlling the wake flow and flow-induced sound of the square cylinder.
气动噪声的控制在各个领域都是必不可少的,包括机械和航空航天工程应用,如高速列车和飞机起落架的受电弓。传统的装置,如分流板,长期以来一直被用来抑制尾流和由此产生的噪音;然而,超越这些经典设计的新型设备的开发尚未实现。本研究旨在利用结合晶格玻尔兹曼方法(LBM)和伴随方法的气动声学优化框架来开发创新的控制装置,以修改方形圆柱体的后表面。二维层流的雷诺数设为150,马赫数设为0.2。优化创造了一个山脊形状附近的后边缘。利用LBM进行的流动和声学分析表明,这种形状成功地抑制了尾流振荡,减轻了风成调的产生。此外,通过简化优化形状,提出了一种新的被动控制技术,即在方柱体后缘附近安装锥形分流板。LBM仿真结果表明,锥形分流板对方形圆柱尾流和流声的控制效果优于传统的直线分流板。
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引用次数: 0
Sliding dynamics of shear-thinning liquid droplets on inclined compliant hydrophobic substrates 倾斜柔顺疏水基板上剪切减薄液滴的滑动动力学
IF 2.5 3区 工程技术 Q2 MECHANICS Pub Date : 2025-11-03 DOI: 10.1016/j.euromechflu.2025.204404
Rohit, Ashish Sonker, Abhishek Raj
This study numerically and experimentally investigates the motion of a shear-thinning liquid droplet on an inclined compliant substrate, highlighting its distinct dynamics compared to Newtonian fluids. Unlike Newtonian liquids with constant viscosity, the shear-thinning droplet exhibits variations in viscosity due to differences in shear rate across its height. These viscosity changes significantly influence its movement, interaction with the substrate, and deformation. Newtonian (μ) and Newtonian μ, were selected to match the zero- shear viscosity (μ) and infinite shear viscosity (μ) of the shear-thinning liquid (XG-1) for comparative analysis. The shear-thinning droplet (XG-1) was found to have a velocity 8.76 % lower than the low-viscosity Newtonian (μ) droplet but 528 % higher than the high-viscosity Newtonian (μ0) droplet. Consequently, its displacement was found to be 7.5 % lesser than Newtonian (μ) but 171 % greater than Newtonian (μ0). Compared to Newtonian liquids, the shear-thinning droplet exhibits moderate fluctuations in base length and height, as well as an intermediate level of contact angle hysteresis (CAH). The motion of the droplet also affects the deformation in the flexible substrate, leading to 6.5 % greater membrane deflection than Newtonian (μ) but 7.63 % less than Newtonian (μ0). The deformation of the shear-thinning droplet is significant due to rapid viscosity transitions, distinguishing it from the stable shape of a highly viscous Newtonian (μ0)droplet. Changes in membrane flexural rigidity and droplet size further influence displacement, deformation, and wobbling. Higher flexural rigidity reduces membrane deflection, increases droplet displacement, and reduces droplet CAH, while larger droplets with higher Bond numbers experience greater deformation and instability. These findings provide valuable insights into the role of viscosity variations in droplet dynamics.
本研究通过数值和实验研究了剪切变薄液滴在倾斜柔顺基底上的运动,突出了与牛顿流体相比其独特的动力学特性。与具有恒定粘度的牛顿液体不同,剪切变薄液滴由于其高度上剪切速率的差异而表现出粘度的变化。这些粘度变化显著影响其运动、与基体的相互作用和变形。选择牛顿(μ 0)和牛顿μ∞来匹配剪切减稀液(XG-1)的零剪切粘度(μ 0)和无限剪切粘度(μ∞),进行对比分析。剪切减薄液滴(XG-1)的速度比低粘度牛顿液滴(μ∞)低8.76%,比高粘度牛顿液滴(μ0)高528%。因此,其位移比牛顿量(μ∞)小7.5%,比牛顿量(μ0)大171%。与牛顿液体相比,剪切变薄液滴在基底长度和高度上表现出适度的波动,以及中等水平的接触角滞后(CAH)。液滴的运动也会影响柔性衬底的变形,导致膜挠度比牛顿(μ∞)大6.5%,比牛顿(μ0)小7.63%。剪切变薄液滴的变形是显著的,由于快速的粘度转变,区别于高粘性牛顿(μ0)液滴的稳定形状。薄膜抗弯刚度和液滴尺寸的变化进一步影响位移、变形和摆动。较高的抗弯刚度降低了膜挠度,增加了液滴位移,降低了液滴CAH,而越大的液滴,键数越高,变形和不稳定性越大。这些发现为液滴动力学中粘度变化的作用提供了有价值的见解。
{"title":"Sliding dynamics of shear-thinning liquid droplets on inclined compliant hydrophobic substrates","authors":"Rohit,&nbsp;Ashish Sonker,&nbsp;Abhishek Raj","doi":"10.1016/j.euromechflu.2025.204404","DOIUrl":"10.1016/j.euromechflu.2025.204404","url":null,"abstract":"<div><div>This study numerically and experimentally investigates the motion of a shear-thinning liquid droplet on an inclined compliant substrate, highlighting its distinct dynamics compared to Newtonian fluids. Unlike Newtonian liquids with constant viscosity, the shear-thinning droplet exhibits variations in viscosity due to differences in shear rate across its height. These viscosity changes significantly influence its movement, interaction with the substrate, and deformation. Newtonian (<span><math><mrow><mi>μ</mi><mi>₀</mi></mrow></math></span>) and Newtonian <span><math><mrow><mfenced><mrow><msub><mrow><mi>μ</mi></mrow><mrow><mi>∞</mi></mrow></msub></mrow></mfenced></mrow></math></span>, were selected to match the zero- shear viscosity <span><math><mrow><mo>(</mo><mi>μ</mi><mi>₀</mi><mo>)</mo></mrow></math></span> and infinite shear viscosity <span><math><mrow><msub><mrow><mo>(</mo><mi>μ</mi></mrow><mrow><mi>∞</mi></mrow></msub><mo>)</mo></mrow></math></span> of the shear-thinning liquid (XG-1) for comparative analysis. The shear-thinning droplet (XG-1) was found to have a velocity 8.76 % lower than the low-viscosity Newtonian (<span><math><msub><mrow><mi>μ</mi></mrow><mrow><mi>∞</mi></mrow></msub></math></span>) droplet but 528 % higher than the high-viscosity Newtonian (<span><math><msub><mrow><mi>μ</mi></mrow><mrow><mn>0</mn></mrow></msub></math></span>) droplet. Consequently, its displacement was found to be 7.5 % lesser than Newtonian (<span><math><msub><mrow><mi>μ</mi></mrow><mrow><mi>∞</mi></mrow></msub></math></span>) but 171 % greater than Newtonian (<span><math><msub><mrow><mi>μ</mi></mrow><mrow><mn>0</mn></mrow></msub></math></span>). Compared to Newtonian liquids, the shear-thinning droplet exhibits moderate fluctuations in base length and height, as well as an intermediate level of contact angle hysteresis (CAH). The motion of the droplet also affects the deformation in the flexible substrate, leading to 6.5 % greater membrane deflection than Newtonian (<span><math><msub><mrow><mi>μ</mi></mrow><mrow><mi>∞</mi></mrow></msub></math></span>) but 7.63 % less than Newtonian (<span><math><msub><mrow><mi>μ</mi></mrow><mrow><mn>0</mn></mrow></msub></math></span>). The deformation of the shear-thinning droplet is significant due to rapid viscosity transitions, distinguishing it from the stable shape of a highly viscous Newtonian <span><math><mrow><mo>(</mo><msub><mrow><mi>μ</mi></mrow><mrow><mn>0</mn></mrow></msub><mo>)</mo><mspace></mspace></mrow></math></span>droplet. Changes in membrane flexural rigidity and droplet size further influence displacement, deformation, and wobbling. Higher flexural rigidity reduces membrane deflection, increases droplet displacement, and reduces droplet CAH, while larger droplets with higher Bond numbers experience greater deformation and instability. These findings provide valuable insights into the role of viscosity variations in droplet dynamics.</div></div>","PeriodicalId":11985,"journal":{"name":"European Journal of Mechanics B-fluids","volume":"116 ","pages":"Article 204404"},"PeriodicalIF":2.5,"publicationDate":"2025-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145517714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Deterministic diffusion models for Lagrangian turbulence: Robustness and encoding of extreme events 拉格朗日湍流的确定性扩散模型:极端事件的鲁棒性和编码
IF 2.5 3区 工程技术 Q2 MECHANICS Pub Date : 2025-11-03 DOI: 10.1016/j.euromechflu.2025.204402
Tianyi Li , Flavio Tuteri , Michele Buzzicotti , Fabio Bonaccorso , Luca Biferale
Modeling Lagrangian turbulence remains a fundamental challenge due to its multiscale, intermittent, and non-Gaussian nature. Recent advances in data-driven diffusion models have enabled the generation of realistic Lagrangian velocity trajectories that accurately reproduce statistical properties across scales and capture rare extreme events. This study investigates three key aspects of diffusion-based modeling for Lagrangian turbulence. First, we assess architectural robustness by comparing a U-Net backbone with a transformer-based alternative, finding strong consistency in generated trajectories, with only minor discrepancies at small scales. Second, leveraging a deterministic variant of diffusion model formulation, namely the deterministic denoising diffusion implicit model (DDIM), we identify structured features in the initial latent noise that align consistently with extreme acceleration events. Third, we explore accelerated generation by reducing the number of diffusion steps, and find that DDIM enables substantial speedups with minimal loss of statistical fidelity. These findings highlight the robustness of diffusion models and their potential for interpretable, scalable modeling of complex turbulent systems.
由于拉格朗日湍流的多尺度、间歇性和非高斯性质,其建模仍然是一个根本性的挑战。数据驱动扩散模型的最新进展使得生成真实的拉格朗日速度轨迹能够准确地再现跨尺度的统计特性并捕获罕见的极端事件。本研究探讨了拉格朗日湍流基于扩散建模的三个关键方面。首先,我们通过比较U-Net主干与基于变压器的替代方案来评估体系结构的鲁棒性,发现生成的轨迹具有很强的一致性,在小尺度上只有微小的差异。其次,利用扩散模型公式的确定性变体,即确定性去噪扩散隐式模型(DDIM),我们在初始潜在噪声中识别与极端加速事件一致的结构化特征。第三,我们通过减少扩散步骤的数量来探索加速生成,并发现DDIM可以在最小的统计保真度损失的情况下实现实质性的加速。这些发现突出了扩散模型的稳健性及其对复杂湍流系统的可解释、可扩展建模的潜力。
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引用次数: 0
Interpretability of snapshot-based convolutional autoencoder for flow decomposition and feature decoupling 基于快照的卷积自编码器流分解和特征解耦的可解释性
IF 2.5 3区 工程技术 Q2 MECHANICS Pub Date : 2025-10-30 DOI: 10.1016/j.euromechflu.2025.204400
Qingliang Zhan , Zhiyong Wang , Zihan Cao , Xin Liu
Image-based deep learning methods, such as two dimensional convolutional neural networks, have recently played an increasingly important role in the study of fluids. However, the flow decomposition mechanism of these deep learning models remains open. In this work, by extracting and decoupling the spatial features hidden in the snapshots, the physical meaning of the flow decomposition and order reduction model is investigated. The observed snapshot at each time stamp is compressed into a low dimensional latent code with independent component by the encoder, and then the decoder reconstructs the flow spatial feature from the latent space, forming an unsupervised scheme for flow decomposition. Laminar and turbulent flows around circular cylinder at Re= 100 and Re= 3900 are analyzed. The results of the laminar case show that the code parameters represent the magnitude of respective spatial features at each instant, while the decoder output of the unit latent vector is the corresponding flow spatial mode. Furthermore, the turbulence results indicate that the deep learning models are more accurate in reconstructing the turbulence than conventional linear theory-based method, while maintaining the independence of the decomposed features. This study presents the decomposition mechanism and the interpretability of 2-dimensional convolutional autoencoders for flow decomposition and feature decoupling.
基于图像的深度学习方法,如二维卷积神经网络,最近在流体研究中发挥着越来越重要的作用。然而,这些深度学习模型的流分解机制仍然是开放的。本文通过提取和解耦隐藏在快照中的空间特征,研究了流分解和降阶模型的物理意义。编码器将每个时间戳的观测快照压缩成具有独立分量的低维潜码,然后由该潜码重构流空间特征,形成无监督流分解方案。分析了Re= 100和Re= 3900时圆柱周围的层流和湍流。层流情况下的结果表明,编码参数代表了每个瞬间各自空间特征的大小,而单位潜在向量的解码器输出是相应的流空间模式。此外,湍流结果表明,深度学习模型比传统的基于线性理论的方法更准确地重建湍流,同时保持了分解特征的独立性。本文研究了二维卷积自编码器的流分解和特征解耦的分解机制和可解释性。
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引用次数: 0
Deep learning framework for casson fluid flow: A PINN approach to heat and mass transfer with chemical reaction and viscous dissipation 卡森流体流动的深度学习框架:具有化学反应和粘性耗散的传热传质的PINN方法
IF 2.5 3区 工程技术 Q2 MECHANICS Pub Date : 2025-10-29 DOI: 10.1016/j.euromechflu.2025.204401
Shravan Kumar Rudrabhatla , D. Srinivasacharya
Physics-Informed Neural Networks (PINNs) provide a powerful framework for solving complex engineering problems by integrating governing physical laws with noisy or incomplete data. This study applies PINNs to analyse boundary layer flow and heat transfer in a non-Newtonian Casson fluid over a vertically stretching sheet. By incorporating physical constraints into the network’s loss function, PINNs optimise weights and biases to approximate solutions of governing ordinary differential equations (ODEs), ensuring physics-consistent predictions. Key parameters such as the Casson fluid parameter, chemical reaction parameter, thermal and concentration buoyancy parameters, Eckert number, Prandtl number, and suction/injection parameter are examined. The effects of these parameters on flow, temperature, and concentration fields are analysed using graphical representations. Furthermore, the accuracy of the PINN-based approach is validated through a comparative study with MATLAB’s BVP4C routine (Boundary Value Problem 4th-Order Collocation), demonstrating strong agreement and confirming its effectiveness in solving nonlinear differential equations in heat and mass transfer problems.
物理信息神经网络(pinn)通过将控制物理定律与嘈杂或不完整的数据相结合,为解决复杂的工程问题提供了强大的框架。本研究应用PINNs分析了非牛顿卡森流体在垂直拉伸薄片上的边界层流动和传热。通过将物理约束纳入网络的损失函数,pinn优化权重和偏差,以近似控制常微分方程(ode)的解,确保物理一致的预测。考察了卡森流体参数、化学反应参数、热和浓浮力参数、Eckert数、Prandtl数、吸注参数等关键参数。这些参数对流量、温度和浓度场的影响用图形表示进行了分析。此外,通过与MATLAB的BVP4C例程(边值问题四阶配置)的对比研究,验证了基于pnp的方法的准确性,证明了其在求解传热传质问题非线性微分方程中的有效性。
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引用次数: 0
Compressible effects in the propagation of nonlinear shallow water waves: Models and simulations 非线性浅水波浪传播中的可压缩效应:模型和模拟
IF 2.5 3区 工程技术 Q2 MECHANICS Pub Date : 2025-10-28 DOI: 10.1016/j.euromechflu.2025.204397
E. Zuccoli, U. Kadri
We investigate the effects of compressibility in the propagation of shallow-water waves and extend the classical shallow-water equations to a compressible regime. Both non-dispersive and weakly-dispersive nonlinear waves are then analysed with the help of the multiple scales method, ultimately leading to the studying of a Burgers and a Korteweg–deVries equation, respectively. A parametric study is conducted in order to investigate the interplay of both nonlinearity and compressibility and assess how compressibility may alter the nonlinear properties of the waves. In particular, parameters varied are the compressibility coefficient μ, the amplitude of the waves ϵ and the width of the initial wave profile σ. In a non-dispersive regime, shock and rarefaction waves form and interact one another leading to a progressive reduction of the wave amplitude in time. The compressibility of the fluid μ speeds up the shock formation, with beneficial effects in terms of wave amplitude reduction. In a weakly dispersive regime, on the other hand, higher compressibility values may amplify the initial perturbation, leading to the formation of a discrete number of solitons having amplitudes much greater than the amplitude at the initial stage. The analysis presented in this work aims at improving our predictions on the dynamics of nonlinear compressible shallow-water waves both in terms of wave amplitude variation and propagation time. Among various applications, our enhanced models can notably improve the estimation of tsunami arrival times and contribute to more accurate weather forecasts. Furthermore, the work presented here lays the foundation for future experimental studies and assessments in this field.
我们研究了可压缩性对浅水波传播的影响,并将经典浅水方程推广到可压缩状态。然后用多尺度方法分析非色散和弱色散非线性波,最终分别得到Burgers方程和Korteweg-deVries方程。为了研究非线性和可压缩性的相互作用,并评估可压缩性如何改变波的非线性特性,进行了参数化研究。具体而言,变化的参数是压缩系数μ、波幅值λ和初始波廓线宽度σ。在非色散状态下,激波和稀薄波形成并相互作用,导致波振幅随时间逐渐减小。流体的可压缩性μ加速了激波的形成,在波幅减小方面产生了有益的影响。另一方面,在弱色散状态下,较高的压缩率值可能会放大初始扰动,导致形成离散数量的孤子,其振幅远大于初始阶段的振幅。在这项工作中提出的分析旨在改进我们对非线性可压缩浅水波的振幅变化和传播时间的动力学预测。在各种应用中,我们的增强模式可以显著改善海啸到达时间的估计,并有助于更准确的天气预报。此外,本文提出的工作为该领域未来的实验研究和评估奠定了基础。
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引用次数: 0
期刊
European Journal of Mechanics B-fluids
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