Vivek Oommen, Aniruddha Bora, Zhen Zhang, George Em Karniadakis
We integrate neural operators with diffusion models to address the spectral limitations of neural operators in surrogate modeling of turbulent flows. While neural operators offer computational efficiency, they exhibit deficiencies in capturing high-frequency flow dynamics, resulting in overly smooth approximations. To overcome this, we condition diffusion models on neural operators to enhance the resolution of turbulent structures. Our approach is validated for different neural operators on diverse datasets, including a high Reynolds number jet flow simulation and experimental Schlieren velocimetry. The proposed method significantly improves the alignment of predicted energy spectra with true distributions compared to neural operators alone. Additionally, proper orthogonal decomposition analysis demonstrates enhanced spectral fidelity in space-time. This work establishes a new paradigm for combining generative models with neural operators to advance surrogate modeling of turbulent systems, and it can be used in other scientific applications that involve microstructure and high-frequency content. See our project page: vivekoommen.github.io/NO_DM
{"title":"Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling","authors":"Vivek Oommen, Aniruddha Bora, Zhen Zhang, George Em Karniadakis","doi":"arxiv-2409.08477","DOIUrl":"https://doi.org/arxiv-2409.08477","url":null,"abstract":"We integrate neural operators with diffusion models to address the spectral\u0000limitations of neural operators in surrogate modeling of turbulent flows. While\u0000neural operators offer computational efficiency, they exhibit deficiencies in\u0000capturing high-frequency flow dynamics, resulting in overly smooth\u0000approximations. To overcome this, we condition diffusion models on neural\u0000operators to enhance the resolution of turbulent structures. Our approach is\u0000validated for different neural operators on diverse datasets, including a high\u0000Reynolds number jet flow simulation and experimental Schlieren velocimetry. The\u0000proposed method significantly improves the alignment of predicted energy\u0000spectra with true distributions compared to neural operators alone.\u0000Additionally, proper orthogonal decomposition analysis demonstrates enhanced\u0000spectral fidelity in space-time. This work establishes a new paradigm for\u0000combining generative models with neural operators to advance surrogate modeling\u0000of turbulent systems, and it can be used in other scientific applications that\u0000involve microstructure and high-frequency content. See our project page:\u0000vivekoommen.github.io/NO_DM","PeriodicalId":501125,"journal":{"name":"arXiv - PHYS - Fluid Dynamics","volume":"39 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142267654","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}
Bimalendu Mahapatra, Tachin Ruangkriengsin, Howard A. Stone, Evgeniy Boyko
We analyze the steady viscoelastic fluid flow in slowly varying contracting channels of arbitrary shape and present a theory based on the lubrication approximation for calculating the flow rate-pressure drop relation at low and high Deborah ($De$) numbers. Unlike most prior theoretical studies leveraging the Oldroyd-B model, we describe the fluid viscoelasticity using a FENE-CR model and examine how the polymer chains' finite extensibility impacts the pressure drop. We employ the low-Deborah-number lubrication analysis to provide analytical expressions for the pressure drop up to $O(De^4)$. We further consider the ultra-dilute limit and exploit a one-way coupling between the parabolic velocity and elastic stresses to calculate the pressure drop of the FENE-CR fluid for arbitrary values of the Deborah number. Such an approach allows us to elucidate elastic stress contributions governing the pressure drop variations and the effect of finite extensibility for all $De$. We validate our theoretical predictions with two-dimensional numerical simulations and find excellent agreement. We show that, at low Deborah numbers, the pressure drop of the FENE-CR fluid monotonically decreases with $De$, similar to the previous results for the Oldroyd-B and FENE-P fluids. However, at high Deborah numbers, in contrast to a linear decrease for the Oldroyd-B fluid, the pressure drop of the FENE-CR fluid exhibits a non-monotonic variation due to finite extensibility, first decreasing and then increasing with $De$. Nevertheless, even at sufficiently high Deborah numbers, the pressure drop of the FENE-CR fluid in the ultra-dilute and lubrication limits is lower than the corresponding Newtonian pressure drop.
{"title":"Viscoelastic fluid flow in a slowly varying planar contraction: the role of finite extensibility on the pressure drop","authors":"Bimalendu Mahapatra, Tachin Ruangkriengsin, Howard A. Stone, Evgeniy Boyko","doi":"arxiv-2409.08150","DOIUrl":"https://doi.org/arxiv-2409.08150","url":null,"abstract":"We analyze the steady viscoelastic fluid flow in slowly varying contracting\u0000channels of arbitrary shape and present a theory based on the lubrication\u0000approximation for calculating the flow rate-pressure drop relation at low and\u0000high Deborah ($De$) numbers. Unlike most prior theoretical studies leveraging\u0000the Oldroyd-B model, we describe the fluid viscoelasticity using a FENE-CR\u0000model and examine how the polymer chains' finite extensibility impacts the\u0000pressure drop. We employ the low-Deborah-number lubrication analysis to provide\u0000analytical expressions for the pressure drop up to $O(De^4)$. We further\u0000consider the ultra-dilute limit and exploit a one-way coupling between the\u0000parabolic velocity and elastic stresses to calculate the pressure drop of the\u0000FENE-CR fluid for arbitrary values of the Deborah number. Such an approach\u0000allows us to elucidate elastic stress contributions governing the pressure drop\u0000variations and the effect of finite extensibility for all $De$. We validate our\u0000theoretical predictions with two-dimensional numerical simulations and find\u0000excellent agreement. We show that, at low Deborah numbers, the pressure drop of\u0000the FENE-CR fluid monotonically decreases with $De$, similar to the previous\u0000results for the Oldroyd-B and FENE-P fluids. However, at high Deborah numbers,\u0000in contrast to a linear decrease for the Oldroyd-B fluid, the pressure drop of\u0000the FENE-CR fluid exhibits a non-monotonic variation due to finite\u0000extensibility, first decreasing and then increasing with $De$. Nevertheless,\u0000even at sufficiently high Deborah numbers, the pressure drop of the FENE-CR\u0000fluid in the ultra-dilute and lubrication limits is lower than the\u0000corresponding Newtonian pressure drop.","PeriodicalId":501125,"journal":{"name":"arXiv - PHYS - Fluid Dynamics","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142212683","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}
A graph neural network (GNN) approach is introduced in this work which enables mesh-based three-dimensional super-resolution of fluid flows. In this framework, the GNN is designed to operate not on the full mesh-based field at once, but on localized meshes of elements (or cells) directly. To facilitate mesh-based GNN representations in a manner similar to spectral (or finite) element discretizations, a baseline GNN layer (termed a message passing layer, which updates local node properties) is modified to account for synchronization of coincident graph nodes, rendering compatibility with commonly used element-based mesh connectivities. The architecture is multiscale in nature, and is comprised of a combination of coarse-scale and fine-scale message passing layer sequences (termed processors) separated by a graph unpooling layer. The coarse-scale processor embeds a query element (alongside a set number of neighboring coarse elements) into a single latent graph representation using coarse-scale synchronized message passing over the element neighborhood, and the fine-scale processor leverages additional message passing operations on this latent graph to correct for interpolation errors. Demonstration studies are performed using hexahedral mesh-based data from Taylor-Green Vortex flow simulations at Reynolds numbers of 1600 and 3200. Through analysis of both global and local errors, the results ultimately show how the GNN is able to produce accurate super-resolved fields compared to targets in both coarse-scale and multiscale model configurations. Reconstruction errors for fixed architectures were found to increase in proportion to the Reynolds number, while the inclusion of surrounding coarse element neighbors was found to improve predictions at Re=1600, but not at Re=3200.
{"title":"Mesh-based Super-Resolution of Fluid Flows with Multiscale Graph Neural Networks","authors":"Shivam Barwey, Pinaki Pal, Saumil Patel, Riccardo Balin, Bethany Lusch, Venkatram Vishwanath, Romit Maulik, Ramesh Balakrishnan","doi":"arxiv-2409.07769","DOIUrl":"https://doi.org/arxiv-2409.07769","url":null,"abstract":"A graph neural network (GNN) approach is introduced in this work which\u0000enables mesh-based three-dimensional super-resolution of fluid flows. In this\u0000framework, the GNN is designed to operate not on the full mesh-based field at\u0000once, but on localized meshes of elements (or cells) directly. To facilitate\u0000mesh-based GNN representations in a manner similar to spectral (or finite)\u0000element discretizations, a baseline GNN layer (termed a message passing layer,\u0000which updates local node properties) is modified to account for synchronization\u0000of coincident graph nodes, rendering compatibility with commonly used\u0000element-based mesh connectivities. The architecture is multiscale in nature,\u0000and is comprised of a combination of coarse-scale and fine-scale message\u0000passing layer sequences (termed processors) separated by a graph unpooling\u0000layer. The coarse-scale processor embeds a query element (alongside a set\u0000number of neighboring coarse elements) into a single latent graph\u0000representation using coarse-scale synchronized message passing over the element\u0000neighborhood, and the fine-scale processor leverages additional message passing\u0000operations on this latent graph to correct for interpolation errors.\u0000Demonstration studies are performed using hexahedral mesh-based data from\u0000Taylor-Green Vortex flow simulations at Reynolds numbers of 1600 and 3200.\u0000Through analysis of both global and local errors, the results ultimately show\u0000how the GNN is able to produce accurate super-resolved fields compared to\u0000targets in both coarse-scale and multiscale model configurations.\u0000Reconstruction errors for fixed architectures were found to increase in\u0000proportion to the Reynolds number, while the inclusion of surrounding coarse\u0000element neighbors was found to improve predictions at Re=1600, but not at\u0000Re=3200.","PeriodicalId":501125,"journal":{"name":"arXiv - PHYS - Fluid Dynamics","volume":"59 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142212687","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}
Separated flow transition is a very popular phenomenon in gas turbines, especially low-pressure turbines (LPT). Low-fidelity simulations are often used for gas turbine design. However, they are unable to predict separated flow transition accurately. To improve the separated flow transition prediction for LPTs, the empirical relations that are derived for transition prediction need to be significantly modified. To achieve this, machine learning approaches are used to investigate a large number of functional forms using computational fluid dynamics-driven gene expression programming. These functional forms are investigated using a multi-expression multi-objective algorithm in terms of separation onset, transition onset, separation bubble length, wall shear stress, and pressure coefficient. The models generated after 177 generations show significant improvements over the baseline result in terms of the above parameters. All of the models developed improve the wall shear stress prediction by 40-70% over the baseline laminar kinetic energy model. This method has immense potential to improve boundary layer transition prediction for gas turbine applications across several geometries and operating conditions.
{"title":"Enhancing Accuracy of Transition Models for Gas Turbine Applications Through Data-Driven Approaches","authors":"Harshal D. Akolekar","doi":"arxiv-2409.07803","DOIUrl":"https://doi.org/arxiv-2409.07803","url":null,"abstract":"Separated flow transition is a very popular phenomenon in gas turbines,\u0000especially low-pressure turbines (LPT). Low-fidelity simulations are often used\u0000for gas turbine design. However, they are unable to predict separated flow\u0000transition accurately. To improve the separated flow transition prediction for\u0000LPTs, the empirical relations that are derived for transition prediction need\u0000to be significantly modified. To achieve this, machine learning approaches are\u0000used to investigate a large number of functional forms using computational\u0000fluid dynamics-driven gene expression programming. These functional forms are\u0000investigated using a multi-expression multi-objective algorithm in terms of\u0000separation onset, transition onset, separation bubble length, wall shear\u0000stress, and pressure coefficient. The models generated after 177 generations\u0000show significant improvements over the baseline result in terms of the above\u0000parameters. All of the models developed improve the wall shear stress\u0000prediction by 40-70% over the baseline laminar kinetic energy model. This\u0000method has immense potential to improve boundary layer transition prediction\u0000for gas turbine applications across several geometries and operating\u0000conditions.","PeriodicalId":501125,"journal":{"name":"arXiv - PHYS - Fluid Dynamics","volume":"273 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142212686","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}
Ewen FrogéIMT Atlantique - MEE, ODYSSEY, Lab-STICC_OSE, Carlos Granero-BelinchonODYSSEY, IMT Atlantique - MEE, Lab-STICC_OSE, Stéphane G. RouxENS de Lyon, Nicolas B. GarnierPhys-ENS, Thierry ChonavelIMT Atlantique - MEE, Lab-STICC_MATRIX
This study evaluates the performance of analog-based methodologies to predict the longitudinal velocity in a turbulent flow. The data used comes from hot wire experimental measurements from the Modane wind tunnel. We compared different methods and explored the impact of varying the number of analogs and their sizes on prediction accuracy. We illustrate that the innovation, defined as the difference between the true velocity value and the prediction value, highlights particularly unpredictable events that we directly link with extreme events of the velocity gradients and so to intermittency. This result indicates that while the estimator effectively seizes linear correlations, it fails to fully capture higher-order dependencies. The innovation underscores the presence of intermittency, revealing the limitations of current predictive models and suggesting directions for future improvements in turbulence forecasting.
{"title":"Analog-Based Forecasting of Turbulent Velocity: Relationship between Predictability and Intermittency","authors":"Ewen FrogéIMT Atlantique - MEE, ODYSSEY, Lab-STICC_OSE, Carlos Granero-BelinchonODYSSEY, IMT Atlantique - MEE, Lab-STICC_OSE, Stéphane G. RouxENS de Lyon, Nicolas B. GarnierPhys-ENS, Thierry ChonavelIMT Atlantique - MEE, Lab-STICC_MATRIX","doi":"arxiv-2409.07792","DOIUrl":"https://doi.org/arxiv-2409.07792","url":null,"abstract":"This study evaluates the performance of analog-based methodologies to predict\u0000the longitudinal velocity in a turbulent flow. The data used comes from hot\u0000wire experimental measurements from the Modane wind tunnel. We compared\u0000different methods and explored the impact of varying the number of analogs and\u0000their sizes on prediction accuracy. We illustrate that the innovation, defined\u0000as the difference between the true velocity value and the prediction value,\u0000highlights particularly unpredictable events that we directly link with extreme\u0000events of the velocity gradients and so to intermittency. This result indicates\u0000that while the estimator effectively seizes linear correlations, it fails to\u0000fully capture higher-order dependencies. The innovation underscores the\u0000presence of intermittency, revealing the limitations of current predictive\u0000models and suggesting directions for future improvements in turbulence\u0000forecasting.","PeriodicalId":501125,"journal":{"name":"arXiv - PHYS - Fluid Dynamics","volume":"22 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142212693","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}
We present a new Eulerian framework for the computation of turbulent compressible multiphase channel flows, specifically to assess turbulence modulation by dispersed particulate matter. By combining a modified low-dissipation numerical scheme for the carrier flow and a quadrature moment-based method for the particle phase, the turbulent statistics of the carrier flow and the fluctuations of the particle phase may be obtained as both are resolved as coupled fields. Using direct numerical simulations, we demonstrate how this method resolves the turbulent statistics, kinetic energy, and drag modulation for moderate Reynolds numbers channel flows for the first time. Validation of our approach to the turbulent clean flow proves the applicability of the carrier flow low dissipation scheme for relatively low Mach number compressible flows. This study also rationalizes the computed drag modulation results using a simplified analytical approach, revealing how the particle migration towards the wall can affect the drag between the two phases at different Stokes numbers and particle loadings. Using our Eulerian approach, we also show the complex interplay between the particles and flow turbulence fluctuations by capturing the preferential clustering of particles in the turbulence streaks. This interplay leads to turbulent flow modulations similar to recent observations reported in prior computational works using Lagrangian simulations. Our study extends the applicability of Eulerian approaches to accurately study particle-fluid interactions in compressible turbulent flows by explicitly calculating the energy equations for both the particle phase and the carrier fluid motion.
{"title":"Direct Numerical Simulation of Particle Clustering and Turbulence Modulation: An Eulerian Approach","authors":"Ajay Dhankarghare, Yuval Dagan","doi":"arxiv-2409.07988","DOIUrl":"https://doi.org/arxiv-2409.07988","url":null,"abstract":"We present a new Eulerian framework for the computation of turbulent\u0000compressible multiphase channel flows, specifically to assess turbulence\u0000modulation by dispersed particulate matter. By combining a modified\u0000low-dissipation numerical scheme for the carrier flow and a quadrature\u0000moment-based method for the particle phase, the turbulent statistics of the\u0000carrier flow and the fluctuations of the particle phase may be obtained as both\u0000are resolved as coupled fields. Using direct numerical simulations, we\u0000demonstrate how this method resolves the turbulent statistics, kinetic energy,\u0000and drag modulation for moderate Reynolds numbers channel flows for the first\u0000time. Validation of our approach to the turbulent clean flow proves the\u0000applicability of the carrier flow low dissipation scheme for relatively low\u0000Mach number compressible flows. This study also rationalizes the computed drag\u0000modulation results using a simplified analytical approach, revealing how the\u0000particle migration towards the wall can affect the drag between the two phases\u0000at different Stokes numbers and particle loadings. Using our Eulerian approach,\u0000we also show the complex interplay between the particles and flow turbulence\u0000fluctuations by capturing the preferential clustering of particles in the\u0000turbulence streaks. This interplay leads to turbulent flow modulations similar\u0000to recent observations reported in prior computational works using Lagrangian\u0000simulations. Our study extends the applicability of Eulerian approaches to\u0000accurately study particle-fluid interactions in compressible turbulent flows by\u0000explicitly calculating the energy equations for both the particle phase and the\u0000carrier fluid motion.","PeriodicalId":501125,"journal":{"name":"arXiv - PHYS - Fluid Dynamics","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142212685","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}
Philipp Patrick Vieweg, Theo Käufer, Christian Cierpka, Jörg Schumacher
Albeit laboratory experiments and numerical simulations have proven themselves successful in enhancing our understanding of long-living large-scale flow structures in horizontally extended Rayleigh-B'enard convection, some discrepancies with respect to their size and induced heat transfer remain. This study traces these discrepancies back to their origins. We start by generating a digital twin of one standard experimental set-up. This twin is subsequently simplified in steps to understand the effect of non-ideal thermal boundary conditions, and the experimental measurement procedure is mimicked using numerical data. Although this allows explaining the increased observed size of the flow structures in the experiment relative to past numerical simulations, our data suggests that the vertical velocity magnitude has been underestimated in the experiments. A subsequent re-assessment of the latter's original data reveals an incorrect calibration model. The re-processed data show a relative increase in $u_{z}$ of roughly $24 %$, resolving the previously observed discrepancies. This digital twin of a laboratory experiment for thermal convection at Rayleigh numbers $Ra = left{ 2, 4, 7 right} times 10^{5}$, a Prandtl number $Pr = 7.1$, and an aspect ratio $Gamma = 25$ highlights the role of different thermal boundary conditions as well as a reliable calibration and measurement procedure.
尽管实验室实验和数值模拟成功地加深了我们对水平扩展的瑞利对流中长期存在的大尺度流结构的理解，但在它们的尺寸和诱导热传递方面仍然存在一些差异。本研究将追溯这些差异的根源。我们首先生成一个标准实验装置的数字孪生。随后，我们逐步简化了这个孪生体，以了解非理想热边界条件的影响，并使用数值数据模拟了实验测量过程。虽然这可以解释实验中观察到的流动结构的尺寸比过去的数值模拟要大，但我们的数据表明，实验中的垂直速度大小被低估了。随后对后者原始数据的重新评估表明，校准模型不正确。重新处理后的数据显示$u_{z}$相对增加了约24 %$，解决了之前观测到的差异。这是在雷利数为 $Ra = left{ 2, 4, 7 right} 时进行的热对流实验室实验的数字孪生数据。times 10^{5}$, a Prandtl number $Pr = 7.1$, and an aspect ratio $Gamma = 25$ highlights therole of different thermal boundary conditions as well as a reliable calibrationand measurement procedure.
{"title":"Digital twin of a large-aspect-ratio Rayleigh-Bénard experiment: Role of thermal boundary conditions, measurement errors and uncertainties","authors":"Philipp Patrick Vieweg, Theo Käufer, Christian Cierpka, Jörg Schumacher","doi":"arxiv-2409.08263","DOIUrl":"https://doi.org/arxiv-2409.08263","url":null,"abstract":"Albeit laboratory experiments and numerical simulations have proven\u0000themselves successful in enhancing our understanding of long-living large-scale\u0000flow structures in horizontally extended Rayleigh-B'enard convection, some\u0000discrepancies with respect to their size and induced heat transfer remain. This\u0000study traces these discrepancies back to their origins. We start by generating\u0000a digital twin of one standard experimental set-up. This twin is subsequently\u0000simplified in steps to understand the effect of non-ideal thermal boundary\u0000conditions, and the experimental measurement procedure is mimicked using\u0000numerical data. Although this allows explaining the increased observed size of\u0000the flow structures in the experiment relative to past numerical simulations,\u0000our data suggests that the vertical velocity magnitude has been underestimated\u0000in the experiments. A subsequent re-assessment of the latter's original data\u0000reveals an incorrect calibration model. The re-processed data show a relative\u0000increase in $u_{z}$ of roughly $24 %$, resolving the previously observed\u0000discrepancies. This digital twin of a laboratory experiment for thermal\u0000convection at Rayleigh numbers $Ra = left{ 2, 4, 7 right} times 10^{5}$,\u0000a Prandtl number $Pr = 7.1$, and an aspect ratio $Gamma = 25$ highlights the\u0000role of different thermal boundary conditions as well as a reliable calibration\u0000and measurement procedure.","PeriodicalId":501125,"journal":{"name":"arXiv - PHYS - Fluid Dynamics","volume":"99 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142212684","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}
We conduct systematic experiments to investigate the dynamics of liquid jet breakup and the resulting droplet size distribution, emphasizing the influence of liquid jet velocity and needle exit diameter. We precisely control jet formation using a pressurized water tank equipped with needles of different sizes. Our study quantifies breakup dynamics through dimensionless parameters such as the liquid Weber number and the needle exit area ratio. Our key findings identify three distinct breakup regimes, such as dripping, Rayleigh, and wind-induced, each dictated by the interplay of surface tension and aerodynamic forces for various combinations of liquid jet velocity and needle exit diameter. We construct a regime map to delineate different breakup behaviours in the We - Ar space. It is observed that lower jet velocities produce narrow probability density functions for jet breakup length due to stable jets, whereas higher velocities result in broader distributions. Increasing jet velocity extends breakup lengths for moderate flow rates due to enhanced stability in the Rayleigh regime, but higher velocities induce instability, leading to shorter breakup lengths. Additionally, we analyze the effects of the needle exit area ratio and liquid Weber number on droplet size distribution, highlighting the transition from mono-modal to bi-modal distribution under varying conditions.
我们进行了系统的实验，研究液体射流破裂的动力学以及由此产生的液滴粒度分布，强调液体射流速度和针出口直径的影响。我们使用一个装有不同大小针头的加压水箱来精确控制射流的形成。我们的研究通过液体韦伯数和针出口面积比等无量纲参数来量化破裂动力学。我们的主要发现确定了三种不同的破裂状态，如滴落、瑞利和风引起的破裂，每种状态都是由液体喷射速度和针出口直径的不同组合下表面张力和空气动力的相互作用决定的。我们构建了一个体系图，以划分 We - Ar 空间中的不同断裂行为。我们观察到，较低的射流速度会因稳定的射流而产生较窄的射流破裂长度概率密度函数，而较高的射流速度则会产生较宽的分布。在中等流速下，射流速度的增加会延长破裂长度，这是由于瑞利机制的稳定性增强所致，但较高的射流速度会导致不稳定性，从而缩短破裂长度。此外，我们还分析了针出口面积比和液体韦伯数对液滴大小分布的影响，强调了在不同条件下从单模式到双模式分布的过渡。
{"title":"Dynamics of jet breakup and the resultant drop size distribution: effect of nozzle size and impingement velocity","authors":"Pavan Kumar Kirar, Nikhil Kumar, Kirti Chandra Sahu","doi":"arxiv-2409.07056","DOIUrl":"https://doi.org/arxiv-2409.07056","url":null,"abstract":"We conduct systematic experiments to investigate the dynamics of liquid jet\u0000breakup and the resulting droplet size distribution, emphasizing the influence\u0000of liquid jet velocity and needle exit diameter. We precisely control jet\u0000formation using a pressurized water tank equipped with needles of different\u0000sizes. Our study quantifies breakup dynamics through dimensionless parameters\u0000such as the liquid Weber number and the needle exit area ratio. Our key\u0000findings identify three distinct breakup regimes, such as dripping, Rayleigh,\u0000and wind-induced, each dictated by the interplay of surface tension and\u0000aerodynamic forces for various combinations of liquid jet velocity and needle\u0000exit diameter. We construct a regime map to delineate different breakup\u0000behaviours in the We - Ar space. It is observed that lower jet velocities\u0000produce narrow probability density functions for jet breakup length due to\u0000stable jets, whereas higher velocities result in broader distributions.\u0000Increasing jet velocity extends breakup lengths for moderate flow rates due to\u0000enhanced stability in the Rayleigh regime, but higher velocities induce\u0000instability, leading to shorter breakup lengths. Additionally, we analyze the\u0000effects of the needle exit area ratio and liquid Weber number on droplet size\u0000distribution, highlighting the transition from mono-modal to bi-modal\u0000distribution under varying conditions.","PeriodicalId":501125,"journal":{"name":"arXiv - PHYS - Fluid Dynamics","volume":"59 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142212696","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}
We address the Reynolds-number dependence of the turbulent skin-friction drag reduction induced by streamwise-travelling waves of spanwise wall oscillations. The study relies on direct numerical simulations of drag-reduced flows in a plane open channel at friction Reynolds numbers in the range $1000 le Re_tau le 6000$, which is the widest range considered so far in simulations with spanwise forcing. Our results corroborate the validity of the predictive model proposed by Gatti & Quadrio, J. Fluid Mech. (2016): regardless of the control parameters, the drag reduction decreases monotonically with $Re$, at a rate that depends on the drag reduction itself and on the skin-friction of the uncontrolled flow. We do not find evidence in support of the results of Marusic et al., Nat. Comm. (2021), which instead report by experiments an increase of the drag reduction with $Re$ in turbulent boundary layers, for control parameters that target low-frequency, outer-scaled motions. Possible explanations for this discrepancy are provided, including obvious differences between open channel flows and boundary layers, and possible limitations of laboratory experiments.
{"title":"Turbulent skin-friction drag reduction via spanwise forcing at high Reynolds number","authors":"Davide Gatti, Maurizio Quadrio, Alessandro Chiarini, Federica Gattere, Sergio Pirozzoli","doi":"arxiv-2409.07230","DOIUrl":"https://doi.org/arxiv-2409.07230","url":null,"abstract":"We address the Reynolds-number dependence of the turbulent skin-friction drag\u0000reduction induced by streamwise-travelling waves of spanwise wall oscillations.\u0000The study relies on direct numerical simulations of drag-reduced flows in a\u0000plane open channel at friction Reynolds numbers in the range $1000 le Re_tau\u0000le 6000$, which is the widest range considered so far in simulations with\u0000spanwise forcing. Our results corroborate the validity of the predictive model\u0000proposed by Gatti & Quadrio, J. Fluid Mech. (2016): regardless of the control\u0000parameters, the drag reduction decreases monotonically with $Re$, at a rate\u0000that depends on the drag reduction itself and on the skin-friction of the\u0000uncontrolled flow. We do not find evidence in support of the results of Marusic\u0000et al., Nat. Comm. (2021), which instead report by experiments an increase of\u0000the drag reduction with $Re$ in turbulent boundary layers, for control\u0000parameters that target low-frequency, outer-scaled motions. Possible\u0000explanations for this discrepancy are provided, including obvious differences\u0000between open channel flows and boundary layers, and possible limitations of\u0000laboratory experiments.","PeriodicalId":501125,"journal":{"name":"arXiv - PHYS - Fluid Dynamics","volume":"273 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142212695","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}
Wall-bounded sedimentation of spherical particles at low particle Reynolds numbers $Re_text{P}lessapprox 0.1$ under the influence of elastic deformation was investigated experimentally. The complete kinematics of both elastic and rigid spheres sedimenting from rest near a rigid or an elastic plane wall in a rectangular duct were recorded. Several specific phenomena related to both inertial and elastohydrodynamic effects were identified and discussed. Among these phenomena is an inertial wall attraction, i.e., particles approach the wall while being accelerated from rest. It was found, that this initial attraction was a universal, purely hydrodynamic phenomenon which occurred in all experiments at $Re_text{P}lessapprox 0.1$. After the initial stage, rigid spheres sedimenting at $Re_text{P}approx O(10^{-1}$) near the wall behaved in the classical way, showing linear migration due to hydrodynamic lift forces. Non-classic evolution of the particle velocity with respect to the wall distance was observed for both rigid and elastic spheres sedimenting at $Re_text{P}approx O(10^{-2}$). Sedimentation was persistently unsteady and the spheres decelerated although the wall distance was increased. Another phenomenon is that very soft spheres showed instationarities superimposed by nonlinearities. These peculiarities in the kinematics are attributed to the non-trivial coupling between particle-fluid inertial forces and elastic effects, i.e., to the existence of elastohydrodynamic memory. Instationarities were also observed during the sedimentation of rigid spheres along an elastic wall. For example, in the near-wall region, elastohydrodynamic interactions damped the dynamics during mass acceleration. Meanwhile, persistent undulating motion towards the wall was observed, i.e., elastohydrodynamic particle trapping instead of hydrodynamic lift was observed.
{"title":"Inertial forces and elastohydrodynamic interaction of spherical particles in wall-bounded sedimentation experiments at low particle Reynolds number","authors":"Isabell Noichl, Clarissa Schönecker","doi":"arxiv-2409.07209","DOIUrl":"https://doi.org/arxiv-2409.07209","url":null,"abstract":"Wall-bounded sedimentation of spherical particles at low particle Reynolds\u0000numbers $Re_text{P}lessapprox 0.1$ under the influence of elastic deformation\u0000was investigated experimentally. The complete kinematics of both elastic and\u0000rigid spheres sedimenting from rest near a rigid or an elastic plane wall in a\u0000rectangular duct were recorded. Several specific phenomena related to both\u0000inertial and elastohydrodynamic effects were identified and discussed. Among\u0000these phenomena is an inertial wall attraction, i.e., particles approach the\u0000wall while being accelerated from rest. It was found, that this initial\u0000attraction was a universal, purely hydrodynamic phenomenon which occurred in\u0000all experiments at $Re_text{P}lessapprox 0.1$. After the initial stage, rigid\u0000spheres sedimenting at $Re_text{P}approx O(10^{-1}$) near the wall behaved in\u0000the classical way, showing linear migration due to hydrodynamic lift forces.\u0000Non-classic evolution of the particle velocity with respect to the wall\u0000distance was observed for both rigid and elastic spheres sedimenting at\u0000$Re_text{P}approx O(10^{-2}$). Sedimentation was persistently unsteady and\u0000the spheres decelerated although the wall distance was increased. Another\u0000phenomenon is that very soft spheres showed instationarities superimposed by\u0000nonlinearities. These peculiarities in the kinematics are attributed to the\u0000non-trivial coupling between particle-fluid inertial forces and elastic\u0000effects, i.e., to the existence of elastohydrodynamic memory. Instationarities\u0000were also observed during the sedimentation of rigid spheres along an elastic\u0000wall. For example, in the near-wall region, elastohydrodynamic interactions\u0000damped the dynamics during mass acceleration. Meanwhile, persistent undulating\u0000motion towards the wall was observed, i.e., elastohydrodynamic particle\u0000trapping instead of hydrodynamic lift was observed.","PeriodicalId":501125,"journal":{"name":"arXiv - PHYS - Fluid Dynamics","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142212692","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}
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