Simone Sandrin, Lorenzo Mazzei, Riccardo Da Soghe, Fabrizio Fontaneto
Given the increasing role of computational fluid dynamics (CFD) simulations in the aerothermal design of gas turbine vanes and blades, their rigorous validation is becoming more and more important. This article exploits an experimental database obtained by the von Karman Institute (VKI) for Fluid Dynamics for the LS-94 test case. This represents a film-cooled transonic turbine vane, investigated in a five-vane linear cascade configuration under engine-like conditions in terms of the Reynolds number and Mach number. The experimental characterization included inlet freestream turbulence measured with hot-wire anemometry, aerodynamic performance assessed with a three-hole pressure probe in the downstream section, and vane convective heat transfer coefficient distribution determined with thin-film thermometers. The test matrix included cases without any film-cooling injection, pressure-side injection, and suction-side injection. The CFD simulations were carried out in Ansys Fluent, considering the impact of mesh sizing and steady-state Reynolds-Averaged Navier-Stokes (RANS) transition modelling, as well as more accurate transient scale-resolving simulations. This work provides insight into the advantages and drawbacks of such approaches for gas turbine hot-gas path designers.
{"title":"Computational Fluid Dynamics Prediction of External Thermal Loads on Film-Cooled Gas Turbine Vanes: A Validation of Reynolds-Averaged Navier–Stokes Transition Models and Scale-Resolving Simulations for the VKI LS-94 Test Case","authors":"Simone Sandrin, Lorenzo Mazzei, Riccardo Da Soghe, Fabrizio Fontaneto","doi":"10.3390/fluids9040091","DOIUrl":"https://doi.org/10.3390/fluids9040091","url":null,"abstract":"Given the increasing role of computational fluid dynamics (CFD) simulations in the aerothermal design of gas turbine vanes and blades, their rigorous validation is becoming more and more important. This article exploits an experimental database obtained by the von Karman Institute (VKI) for Fluid Dynamics for the LS-94 test case. This represents a film-cooled transonic turbine vane, investigated in a five-vane linear cascade configuration under engine-like conditions in terms of the Reynolds number and Mach number. The experimental characterization included inlet freestream turbulence measured with hot-wire anemometry, aerodynamic performance assessed with a three-hole pressure probe in the downstream section, and vane convective heat transfer coefficient distribution determined with thin-film thermometers. The test matrix included cases without any film-cooling injection, pressure-side injection, and suction-side injection. The CFD simulations were carried out in Ansys Fluent, considering the impact of mesh sizing and steady-state Reynolds-Averaged Navier-Stokes (RANS) transition modelling, as well as more accurate transient scale-resolving simulations. This work provides insight into the advantages and drawbacks of such approaches for gas turbine hot-gas path designers.","PeriodicalId":12397,"journal":{"name":"Fluids","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140699961","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}
Simon El Ouafa, Stephane Vincent, V. Le Chenadec, Benoît Trouette, Syphax Ferreka, Amine Chadil
In this paper, we introduce a compressible formulation for dealing with 2D/3D compressible interfacial flows. It integrates a monolithic solver to achieve robust velocity–pressure coupling, ensuring precision and stability across diverse fluid flow conditions, including incompressible and compressible single-phase and two-phase flows. Validation of the model is conducted through various test scenarios, including Sod’s shock tube problem, isothermal viscous two-phase flows without capillary effects, and the impact of drops on viscous liquid films. The results highlight the ability of the scheme to handle compressible flow situations with capillary effects, which are important in computational fluid dynamics (CFD).
{"title":"A Compressible Formulation of the One-Fluid Model for Two-Phase Flows","authors":"Simon El Ouafa, Stephane Vincent, V. Le Chenadec, Benoît Trouette, Syphax Ferreka, Amine Chadil","doi":"10.3390/fluids9040090","DOIUrl":"https://doi.org/10.3390/fluids9040090","url":null,"abstract":"In this paper, we introduce a compressible formulation for dealing with 2D/3D compressible interfacial flows. It integrates a monolithic solver to achieve robust velocity–pressure coupling, ensuring precision and stability across diverse fluid flow conditions, including incompressible and compressible single-phase and two-phase flows. Validation of the model is conducted through various test scenarios, including Sod’s shock tube problem, isothermal viscous two-phase flows without capillary effects, and the impact of drops on viscous liquid films. The results highlight the ability of the scheme to handle compressible flow situations with capillary effects, which are important in computational fluid dynamics (CFD).","PeriodicalId":12397,"journal":{"name":"Fluids","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2024-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140710543","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}
Raúl Alberto Tinajero-Álvarez, C. A. Hernández-Bocanegra, J. A. Ramos-Banderas, N. M. López-Granados, Brandon Farrera-Buenrostro, Enrique Torres-Alonso, G. Solorio‐Diaz
In this work, the effects of jet impact angle and water flow on the heat-transfer coefficient in boron steel probes were analyzed. Angles of 90°, 75° and 60° were used with stirring flows of 33 l·min−1, 25 l·min−1, 13 l·min−1 and 6 l·min−1. The aim consisted of determining the heat-extraction rates by analyzing the correlation programmed in the Ansys Fluent 2020R2 software when different cooling conditions are used, avoiding many experiments, and establishing quenching conditions free of surface defects on the workpiece. This process is currently used in heavy machinery, requiring high hardness and wear resistance. The fluid-dynamic field was validated using a scale physical model using the particle image velocimetry technique, PIV. In contrast, the thermal field was validated with transient state experiments solving the inverse heat conduction problem, IHCP. The results show that for high flows (33 l·min−1), the jets with an angle of 90° impact the entire surface of the piece, but their cooling rate is slower compared to the other angles, being 243.61 K·s−1, and 271.70 K·s−1, 329.56 K·s−1 for 75° and 60°, respectively. However, for low flows (6 l·min−1), the impact velocities are very similar for the three cases, promoting more homogeneous cooling rates of 58.47 K·s−1, 73.58 K·s−1 and 63.98 K s−1 for angles of 90°, 75° and 60°, respectively. Likewise, through the use of CCT diagrams, it was determined that regardless of the cooling rate, the final structure will always be a mixture of martensite–bainite due to the effect of boron as determined experimentally, which implies a more significant proportion of martensite at higher cooling rates.
{"title":"Numerical Analysis of Convective Heat Transfer in Quenching Treatments of Boron Steel under Different Configurations of Immersed Water Jets and Its Effects on Microstructure","authors":"Raúl Alberto Tinajero-Álvarez, C. A. Hernández-Bocanegra, J. A. Ramos-Banderas, N. M. López-Granados, Brandon Farrera-Buenrostro, Enrique Torres-Alonso, G. Solorio‐Diaz","doi":"10.3390/fluids9040089","DOIUrl":"https://doi.org/10.3390/fluids9040089","url":null,"abstract":"In this work, the effects of jet impact angle and water flow on the heat-transfer coefficient in boron steel probes were analyzed. Angles of 90°, 75° and 60° were used with stirring flows of 33 l·min−1, 25 l·min−1, 13 l·min−1 and 6 l·min−1. The aim consisted of determining the heat-extraction rates by analyzing the correlation programmed in the Ansys Fluent 2020R2 software when different cooling conditions are used, avoiding many experiments, and establishing quenching conditions free of surface defects on the workpiece. This process is currently used in heavy machinery, requiring high hardness and wear resistance. The fluid-dynamic field was validated using a scale physical model using the particle image velocimetry technique, PIV. In contrast, the thermal field was validated with transient state experiments solving the inverse heat conduction problem, IHCP. The results show that for high flows (33 l·min−1), the jets with an angle of 90° impact the entire surface of the piece, but their cooling rate is slower compared to the other angles, being 243.61 K·s−1, and 271.70 K·s−1, 329.56 K·s−1 for 75° and 60°, respectively. However, for low flows (6 l·min−1), the impact velocities are very similar for the three cases, promoting more homogeneous cooling rates of 58.47 K·s−1, 73.58 K·s−1 and 63.98 K s−1 for angles of 90°, 75° and 60°, respectively. Likewise, through the use of CCT diagrams, it was determined that regardless of the cooling rate, the final structure will always be a mixture of martensite–bainite due to the effect of boron as determined experimentally, which implies a more significant proportion of martensite at higher cooling rates.","PeriodicalId":12397,"journal":{"name":"Fluids","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2024-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140715563","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}
Lukas M. Fuchs, Jakob G. R. von Saldern, T. Kaiser, K. Oberleithner
The purpose of this work is to explore the potential of deep reinforcement learning (DRL) as a black-box optimizer for turbulence model identification. For this, we consider a Reynolds-averaged Navier–Stokes (RANS) closure model of a round turbulent jet flow at a Reynolds number of 10,000. For this purpose, we augment the widely utilized Spalart–Allmaras turbulence model by introducing a source term that is identified by DRL. The algorithm is trained to maximize the alignment of the augmented RANS model velocity fields and time-averaged large eddy simulation (LES) reference data. It is shown that the alignment between the reference data and the results of the RANS simulation is improved by 48% using the Spalart–Allmaras model augmented with DRL compared to the standard model. The velocity field, jet spreading rate, and axial velocity decay exhibit substantially improved agreement with both the LES reference and literature data. In addition, we applied the trained model to a jet flow with a Reynolds number of 15,000, which improved the mean field alignment by 35%, demonstrating that the framework is applicable to unseen data of the same configuration at a higher Reynolds number. Overall, this work demonstrates that DRL is a promising method for RANS closure model identification. Hurdles and challenges associated with the presented methodology, such as high numerical cost, numerical stability, and sensitivity of hyperparameters are discussed in the study.
{"title":"Deep Reinforcement Learning-Augmented Spalart–Allmaras Turbulence Model: Application to a Turbulent Round Jet Flow","authors":"Lukas M. Fuchs, Jakob G. R. von Saldern, T. Kaiser, K. Oberleithner","doi":"10.3390/fluids9040088","DOIUrl":"https://doi.org/10.3390/fluids9040088","url":null,"abstract":"The purpose of this work is to explore the potential of deep reinforcement learning (DRL) as a black-box optimizer for turbulence model identification. For this, we consider a Reynolds-averaged Navier–Stokes (RANS) closure model of a round turbulent jet flow at a Reynolds number of 10,000. For this purpose, we augment the widely utilized Spalart–Allmaras turbulence model by introducing a source term that is identified by DRL. The algorithm is trained to maximize the alignment of the augmented RANS model velocity fields and time-averaged large eddy simulation (LES) reference data. It is shown that the alignment between the reference data and the results of the RANS simulation is improved by 48% using the Spalart–Allmaras model augmented with DRL compared to the standard model. The velocity field, jet spreading rate, and axial velocity decay exhibit substantially improved agreement with both the LES reference and literature data. In addition, we applied the trained model to a jet flow with a Reynolds number of 15,000, which improved the mean field alignment by 35%, demonstrating that the framework is applicable to unseen data of the same configuration at a higher Reynolds number. Overall, this work demonstrates that DRL is a promising method for RANS closure model identification. Hurdles and challenges associated with the presented methodology, such as high numerical cost, numerical stability, and sensitivity of hyperparameters are discussed in the study.","PeriodicalId":12397,"journal":{"name":"Fluids","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140727704","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}
K. Tsiakas, X. Trompoukis, V. Asouti, K. Giannakoglou, G. Rogé, Sarah Julisson, Ludovic Martin, S. Kleinveld
This article presents single- and multi-disciplinary shape optimizations of a generic business jet wing at two transonic cruise flow conditions. The studies performed are based on two high-fidelity gradient-based optimization tools, assisted by the adjoint method (following both discrete and continuous approaches). Single discipline and coupled multi-disciplinary sensitivity derivatives computed from the two tools are compared and verified against finite differences. The importance of not making the frozen turbulence assumption in adjoint-based optimization is demonstrated. Then, a number of optimization runs, ranging from a pure aerodynamic with a rigid structure to an aerostructural one exploring the trade-offs between the involved disciplines, are presented and discussed. The middle-ground scenario of optimizing the wing with aerodynamic criteria and, then, performing an aerostructural trimming is also investigated.
{"title":"Discrete and Continuous Adjoint-Based Aerostructural Wing Shape Optimization of a Business Jet","authors":"K. Tsiakas, X. Trompoukis, V. Asouti, K. Giannakoglou, G. Rogé, Sarah Julisson, Ludovic Martin, S. Kleinveld","doi":"10.3390/fluids9040087","DOIUrl":"https://doi.org/10.3390/fluids9040087","url":null,"abstract":"This article presents single- and multi-disciplinary shape optimizations of a generic business jet wing at two transonic cruise flow conditions. The studies performed are based on two high-fidelity gradient-based optimization tools, assisted by the adjoint method (following both discrete and continuous approaches). Single discipline and coupled multi-disciplinary sensitivity derivatives computed from the two tools are compared and verified against finite differences. The importance of not making the frozen turbulence assumption in adjoint-based optimization is demonstrated. Then, a number of optimization runs, ranging from a pure aerodynamic with a rigid structure to an aerostructural one exploring the trade-offs between the involved disciplines, are presented and discussed. The middle-ground scenario of optimizing the wing with aerodynamic criteria and, then, performing an aerostructural trimming is also investigated.","PeriodicalId":12397,"journal":{"name":"Fluids","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140739666","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}
Yuri Theodoro Barbosa de Lima, Liércio André Isoldi, E. D. dos Santos, B. N. Machado, M. N. Gomes, C. Biserni, Luiz Alberto Oliveira Rocha
This research conducts a numerical study of a wave energy converter (WEC) device with five coupled hydropneumatic chambers, operating based on the principle of an oscillating water column (OWC). A turbine was not included, only considering the tube without it. The computational domain was defined by a wave channel housing an OWC device subjected to regular incident waves. The central objective was to assess the impact of chamber geometry on maximizing the total hydropneumatic power in energy conversion. The numerical simulations consider the pressure, mass flow rate, and total hydropneumatic power, with the latter being the performance indicator. To determine the geometries to be analyzed, the Constructal Design method was employed in conjunction with the exhaustive search optimization method to maximize the performance indicator. The degrees of freedom defined were the ratios between the height (Hn) and the length (Ln) of the hydropneumatic chambers (Hn/Ln, where n varies from one to five). Based on the results of the mass flow rate and pressure, their influence on power was evaluated. It was observed that the influence of the degrees of freedom on the pressure difference, mass flow rate, and hydrodynamic power was quite similar, displaying an increase for low ratios of Hn/Ln up to a maximum magnitude and followed by a decrease in magnitude. The best performance was achieved for the geometric configuration with Hn/Ln = 0.2613 (Hn = 5.0625 m and Ln = 15.8219 m), representing an improvement of 98.6% compared to the worst case analyzed.
{"title":"Study of the Geometry of an Oscillating Water Column Device with Five Chambers Coupled under Regular Waves through the Constructal Design Method","authors":"Yuri Theodoro Barbosa de Lima, Liércio André Isoldi, E. D. dos Santos, B. N. Machado, M. N. Gomes, C. Biserni, Luiz Alberto Oliveira Rocha","doi":"10.3390/fluids9040086","DOIUrl":"https://doi.org/10.3390/fluids9040086","url":null,"abstract":"This research conducts a numerical study of a wave energy converter (WEC) device with five coupled hydropneumatic chambers, operating based on the principle of an oscillating water column (OWC). A turbine was not included, only considering the tube without it. The computational domain was defined by a wave channel housing an OWC device subjected to regular incident waves. The central objective was to assess the impact of chamber geometry on maximizing the total hydropneumatic power in energy conversion. The numerical simulations consider the pressure, mass flow rate, and total hydropneumatic power, with the latter being the performance indicator. To determine the geometries to be analyzed, the Constructal Design method was employed in conjunction with the exhaustive search optimization method to maximize the performance indicator. The degrees of freedom defined were the ratios between the height (Hn) and the length (Ln) of the hydropneumatic chambers (Hn/Ln, where n varies from one to five). Based on the results of the mass flow rate and pressure, their influence on power was evaluated. It was observed that the influence of the degrees of freedom on the pressure difference, mass flow rate, and hydrodynamic power was quite similar, displaying an increase for low ratios of Hn/Ln up to a maximum magnitude and followed by a decrease in magnitude. The best performance was achieved for the geometric configuration with Hn/Ln = 0.2613 (Hn = 5.0625 m and Ln = 15.8219 m), representing an improvement of 98.6% compared to the worst case analyzed.","PeriodicalId":12397,"journal":{"name":"Fluids","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140740429","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}
Characterization of the physiological hemodynamic environment in normal pulmonary arteries is a key factor in understanding pathological conditions. This study aimed to analyze the morphology and hemodynamics in the healthy adult pulmonary bifurcation in comparison to age-matched repaired Tetralogy of Fallot (rTOF) geometries. The pulmonary trunk of five healthy volunteers was reconstructed from 4D Flow-MRI data and was compared to rTOF results. Subject-specific boundary conditions were assigned in both the inlet and outlets of the models, and flow characteristics were analyzed computationally. The morphological and flow features were consistent among the healthy geometries, highlighting the ability of an averaged geometry derived from this small cohort to capture the main flow characteristics. A slightly higher mean time-averaged wall shear stress (TAWSS) was found in the right pulmonary artery, which was also the branch with a higher mean curvature and local Reynolds number. Compared to rTOF results, the averaged healthy geometry demonstrated more than an 8-fold lower value in TAWSS, with the individual patient-specific healthy volunteers showing further reduced TAWSS than the rTOF patients. These observations could be useful in clinical assessment and decision making based on hemodynamic indices.
{"title":"Computational Analysis of Blood Flow in Healthy Pulmonary Arteries in Comparison to Repaired Tetralogy of Fallot Results: A Small Cohort Study","authors":"M. Boumpouli, S. Black, A. Kazakidi","doi":"10.3390/fluids9040085","DOIUrl":"https://doi.org/10.3390/fluids9040085","url":null,"abstract":"Characterization of the physiological hemodynamic environment in normal pulmonary arteries is a key factor in understanding pathological conditions. This study aimed to analyze the morphology and hemodynamics in the healthy adult pulmonary bifurcation in comparison to age-matched repaired Tetralogy of Fallot (rTOF) geometries. The pulmonary trunk of five healthy volunteers was reconstructed from 4D Flow-MRI data and was compared to rTOF results. Subject-specific boundary conditions were assigned in both the inlet and outlets of the models, and flow characteristics were analyzed computationally. The morphological and flow features were consistent among the healthy geometries, highlighting the ability of an averaged geometry derived from this small cohort to capture the main flow characteristics. A slightly higher mean time-averaged wall shear stress (TAWSS) was found in the right pulmonary artery, which was also the branch with a higher mean curvature and local Reynolds number. Compared to rTOF results, the averaged healthy geometry demonstrated more than an 8-fold lower value in TAWSS, with the individual patient-specific healthy volunteers showing further reduced TAWSS than the rTOF patients. These observations could be useful in clinical assessment and decision making based on hemodynamic indices.","PeriodicalId":12397,"journal":{"name":"Fluids","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140787769","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}
R. Hassanian, Marcel Aach, A. Lintermann, Á. Helgadóttir, M. Riedel
This study presents a novel approach to using a gated recurrent unit (GRU) model, a deep neural network, to predict turbulent flows in a Lagrangian framework. The emerging velocity field is predicted based on experimental data from a strained turbulent flow, which was initially a nearly homogeneous isotropic turbulent flow at the measurement area. The distorted turbulent flow has a Taylor microscale Reynolds number in the range of 100 < Reλ < 152 before creating the strain and is strained with a mean strain rate of 4 s−1 in the Y direction. The measurement is conducted in the presence of gravity consequent to the actual condition, an effect that is usually neglected and has not been investigated in most numerical studies. A Lagrangian particle tracking technique is used to extract the flow characterizations. It is used to assess the capability of the GRU model to forecast the unknown turbulent flow pattern affected by distortion and gravity using spatiotemporal input data. Using the flow track’s location (spatial) and time (temporal) highlights the model’s superiority. The suggested approach provides the possibility to predict the emerging pattern of the strained turbulent flow properties observed in many natural and artificial phenomena. In order to optimize the consumed computing, hyperparameter optimization (HPO) is used to improve the GRU model performance by 14–20%. Model training and inference run on the high-performance computing (HPC) JUWELS-BOOSTER and DEEP-DAM systems at the Jülich Supercomputing Centre, and the code speed-up on these machines is measured. The proposed model produces accurate predictions for turbulent flows in the Lagrangian view with a mean absolute error (MAE) of 0.001 and an R2 score of 0.993.
{"title":"Turbulent Flow Prediction-Simulation: Strained Flow with Initial Isotropic Condition Using a GRU Model Trained by an Experimental Lagrangian Framework, with Emphasis on Hyperparameter Optimization","authors":"R. Hassanian, Marcel Aach, A. Lintermann, Á. Helgadóttir, M. Riedel","doi":"10.3390/fluids9040084","DOIUrl":"https://doi.org/10.3390/fluids9040084","url":null,"abstract":"This study presents a novel approach to using a gated recurrent unit (GRU) model, a deep neural network, to predict turbulent flows in a Lagrangian framework. The emerging velocity field is predicted based on experimental data from a strained turbulent flow, which was initially a nearly homogeneous isotropic turbulent flow at the measurement area. The distorted turbulent flow has a Taylor microscale Reynolds number in the range of 100 < Reλ < 152 before creating the strain and is strained with a mean strain rate of 4 s−1 in the Y direction. The measurement is conducted in the presence of gravity consequent to the actual condition, an effect that is usually neglected and has not been investigated in most numerical studies. A Lagrangian particle tracking technique is used to extract the flow characterizations. It is used to assess the capability of the GRU model to forecast the unknown turbulent flow pattern affected by distortion and gravity using spatiotemporal input data. Using the flow track’s location (spatial) and time (temporal) highlights the model’s superiority. The suggested approach provides the possibility to predict the emerging pattern of the strained turbulent flow properties observed in many natural and artificial phenomena. In order to optimize the consumed computing, hyperparameter optimization (HPO) is used to improve the GRU model performance by 14–20%. Model training and inference run on the high-performance computing (HPC) JUWELS-BOOSTER and DEEP-DAM systems at the Jülich Supercomputing Centre, and the code speed-up on these machines is measured. The proposed model produces accurate predictions for turbulent flows in the Lagrangian view with a mean absolute error (MAE) of 0.001 and an R2 score of 0.993.","PeriodicalId":12397,"journal":{"name":"Fluids","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140789763","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}
C. Beggs, R. Abid, Fariborz Motallebi, Abdus Samad, Nithya Venkatesan, Eldad J. Avital
COVID-19 is an airborne disease, with the vast majority of infections occurring indoors. In comparison, little transmission occurs outdoors. Here, we investigate the airborne transmission pathways that differentiate the indoors from outdoors and conclude that profound differences exist, which help to explain why SARS-CoV-2 transmission is much more prevalent indoors. Near- and far-field transmission pathways are discussed along with factors that affect infection risk, with aerosol concentration, air entrainment, thermal plumes, and occupancy duration all identified as being influential. In particular, we present the fundamental equations that underpin the Wells–Riley model and show the mathematical relationship between inhaled virus particles and quanta of infection. A simple model is also presented for assessing infection risk in spaces with incomplete air mixing. Transmission risk is assessed in terms of aerosol concentration using simple 1D equations, followed by a description of thermal plume–ceiling interactions. With respect to this, we present new experimental results using Schlieren visualisation and computational fluid dynamics (CFD) based on the Eulerian–Lagrangian approach. Pathways of airborne infection are discussed, with the key differences identified between indoors and outdoors. In particular, the contribution of thermal and exhalation plumes is evaluated, and the presence of a near-field/far-field feedback loop is postulated, which is absent outdoors.
{"title":"Airborne Transmission of SARS-CoV-2: The Contrast between Indoors and Outdoors","authors":"C. Beggs, R. Abid, Fariborz Motallebi, Abdus Samad, Nithya Venkatesan, Eldad J. Avital","doi":"10.3390/fluids9030054","DOIUrl":"https://doi.org/10.3390/fluids9030054","url":null,"abstract":"COVID-19 is an airborne disease, with the vast majority of infections occurring indoors. In comparison, little transmission occurs outdoors. Here, we investigate the airborne transmission pathways that differentiate the indoors from outdoors and conclude that profound differences exist, which help to explain why SARS-CoV-2 transmission is much more prevalent indoors. Near- and far-field transmission pathways are discussed along with factors that affect infection risk, with aerosol concentration, air entrainment, thermal plumes, and occupancy duration all identified as being influential. In particular, we present the fundamental equations that underpin the Wells–Riley model and show the mathematical relationship between inhaled virus particles and quanta of infection. A simple model is also presented for assessing infection risk in spaces with incomplete air mixing. Transmission risk is assessed in terms of aerosol concentration using simple 1D equations, followed by a description of thermal plume–ceiling interactions. With respect to this, we present new experimental results using Schlieren visualisation and computational fluid dynamics (CFD) based on the Eulerian–Lagrangian approach. Pathways of airborne infection are discussed, with the key differences identified between indoors and outdoors. In particular, the contribution of thermal and exhalation plumes is evaluated, and the presence of a near-field/far-field feedback loop is postulated, which is absent outdoors.","PeriodicalId":12397,"journal":{"name":"Fluids","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2024-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139958027","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}
R. Pasolari, C. Ferreira, Alexander van van Zuijlen, Carlos Fernando Baptista
The past few decades have witnessed a growing popularity in Eulerian–Lagrangian solvers due to their significant potential for simulating aerodynamic flows, particularly in cases involving strong body–vortex interactions. In this hybrid approach, the two component solvers are mutually coupled in a two-way fashion. Initially, the Lagrangian solver can supply boundary conditions to the Eulerian solver, while the Eulerian solver functions as a corrector for the Lagrangian solution in regions where the latter cannot achieve high accuracy. To utilize such tools effectively, it is vital for them to be capable of handling dynamic mesh movements. This study builds upon the previous research conducted by our team and extends the capabilities of the hybrid solver to handle dynamic meshes. While OpenFOAM, the Eulerian component of this hybrid code, incorporates built-in dynamic mesh properties, certain modifications are necessary to ensure its compatibility with the Lagrangian solver. More specifically, the evolution algorithm of the pimpleFOAM solver needs to be divided into two discrete steps: first, updating the mesh, and later, evolving the solution. This division enables a proper coupling between pimpleFOAM and the Lagrangian solver as an intermediate step. Therefore, the primary objective of this specific paper is to adapt the OpenFOAM solver to meet the demands of the hybrid solver and subsequently validate that the hybrid solver can effectively address dynamic mesh challenges using this approach. This approach introduces a pioneering method for conducting dynamic mesh simulations within the OpenFOAM framework, showcasing its potential for broader applications. To validate the approach, various test cases involving dynamic mesh movements are employed. Specifically, all these cases employ the Lamb–Oseen diffusing vortex, but each case incorporates different types of mesh movements, including translational, rotational, oscillational, and combinations thereof. The results from these cases demonstrate the effectiveness of the proposed OpenFOAM algorithm, with the maximum relative errors —when compared to the analytical solution across all presented cases—capped at 2.0% for the worst-case scenario. This affirms the algorithm’s capability to successfully handle dynamic mesh simulations with the proposed solver.
{"title":"Dynamic Mesh Simulations in OpenFOAM: A Hybrid Eulerian–Lagrangian Approach","authors":"R. Pasolari, C. Ferreira, Alexander van van Zuijlen, Carlos Fernando Baptista","doi":"10.3390/fluids9020051","DOIUrl":"https://doi.org/10.3390/fluids9020051","url":null,"abstract":"The past few decades have witnessed a growing popularity in Eulerian–Lagrangian solvers due to their significant potential for simulating aerodynamic flows, particularly in cases involving strong body–vortex interactions. In this hybrid approach, the two component solvers are mutually coupled in a two-way fashion. Initially, the Lagrangian solver can supply boundary conditions to the Eulerian solver, while the Eulerian solver functions as a corrector for the Lagrangian solution in regions where the latter cannot achieve high accuracy. To utilize such tools effectively, it is vital for them to be capable of handling dynamic mesh movements. This study builds upon the previous research conducted by our team and extends the capabilities of the hybrid solver to handle dynamic meshes. While OpenFOAM, the Eulerian component of this hybrid code, incorporates built-in dynamic mesh properties, certain modifications are necessary to ensure its compatibility with the Lagrangian solver. More specifically, the evolution algorithm of the pimpleFOAM solver needs to be divided into two discrete steps: first, updating the mesh, and later, evolving the solution. This division enables a proper coupling between pimpleFOAM and the Lagrangian solver as an intermediate step. Therefore, the primary objective of this specific paper is to adapt the OpenFOAM solver to meet the demands of the hybrid solver and subsequently validate that the hybrid solver can effectively address dynamic mesh challenges using this approach. This approach introduces a pioneering method for conducting dynamic mesh simulations within the OpenFOAM framework, showcasing its potential for broader applications. To validate the approach, various test cases involving dynamic mesh movements are employed. Specifically, all these cases employ the Lamb–Oseen diffusing vortex, but each case incorporates different types of mesh movements, including translational, rotational, oscillational, and combinations thereof. The results from these cases demonstrate the effectiveness of the proposed OpenFOAM algorithm, with the maximum relative errors —when compared to the analytical solution across all presented cases—capped at 2.0% for the worst-case scenario. This affirms the algorithm’s capability to successfully handle dynamic mesh simulations with the proposed solver.","PeriodicalId":12397,"journal":{"name":"Fluids","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2024-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139962482","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：