Browsing by Author "Teschner, Tom-Robin"
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Item Open Access Aerodynamic performance investigation through different chemistry modelling approaches for space re-entry vehicles using the DSMC method(Unconfirmed, 2022-04-22) Farah, Elias; Teschner, Tom-RobinHigh-speed flows with Mach numbers well above the hypersonic regime pose significant modelling com-plexities due to increased levels of thermal energy, which in turn result in a variety of chemical reactionsthat become dominant and thus have to be accurately modelled. Within Computational Fluid Dynamics(CFD), the Direct Simulation Monte Carlo (DSMC) method is commonly chosen here as it has shownsuperior performance over traditional Navier-Stokes-based solvers due to a breakdown in the continuumhypothesis. Space re-entering vehicles are commonly exposed to high Mach numbers when entering intoearth’s atmosphere and low density so that the mean free path of particles is comparable to the lengthof the vehicle itself. Thus, these types of applications require challenging modelling approaches which isthe subject of this study. We use the open-source CFD solver OpenFOAM in this study, which comesprebuilt with the dsmcFoam solver. This implementation of the DSMC method lacks, however, the abilityto model chemical reactions and thus is not equipped to predict aerodynamic coefficients for high-speedflows. Recently, the dsmcFoam+ solver has been proposed [1] and implemented into OpenFOAM whichfeatures, among other things, the ability to model chemical reactions through the Quantum-Kinetic (QK)model. The aim of this study, then, is threefold; 1) Validate the new dsmcFoam+ solver against availablereference data from the literature and compare it to the default dsmcFoam solver, highlighting the im-portance of chemical modelling, 2) Publish all simulation and setup files through an online repository tofacilitate an easy case setup for researchers wishing to evaluate or adopt the new dsmcFoam+ solver, 3)Provide documentation for the new dsmcFoam+ solver in the context of OpenFOAM where there is littledocumentation available. We investigate the flow of a re-entry vehicle with a freestream Mach number of25.6 at different angle of attacks and find that the chemical modelling approach taken has a significantinfluence over the aerodynamic coefficients which are up to 24% apart. Similar results are obtained forthe heat transfer coefficient, which shows differences of up to 28%. Based on our findings, we advocatethat the dsmcFoam+ solver should be used for aero-thermodynamic calculations as its ability to predictchemical reactions and thus changes in the flow field will significantly affect the overall solution accuracycompared to a non-reacting modelling approach.Item Open Access Comparative analysis of RANS and DDES methods for aerodynamic performance predictions for high performance vehicles at low ground clearances(2023-04-21) Rijns, Steven; Teschner, Tom-Robin; Blackburn, Kim; Brighton, JamesVarious assessments of RANS and Hybrid RANS-LES turbulence models have been conducted for automotive applications. However, their applicability for high performance vehicles which exhibit much more complex flow phenomena is not well studied yet. In this work, the predictive capabilities of RANS and DDES models are investigated through a comparative study on a high performance configuration of the DrivAer Fastback model at a low ground clearance in an open road computational domain. The results show much agreement in the general pressure distribution, except in areas of highly unsteady flow. Visualisation of the flow field depicts that the DDES simulation is able to capture a wider range of turbulent scales with a higher fidelity. Lastly, variation in the magnitude, distribution and decay of pressure losses in the wake are observed between both simulations. The presented results are used to illustrate the capabilities and limitations of these turbulence models for other academic or industrial users to make an informed decision on the turbulence model suited for their objectives.Item Open Access Critical assessment of the lattice Boltzmann method for cavitation modelling based on single bubble dynamics(Springer, 2024-05-01) Xiong, Xin; Teschner, Tom-Robin; Moulitsas, Irene; Józsa, Tamás IstvánThe lattice Boltzmann Method (LBM) is recognised as a popular technique for simulating cavitation bubble dynamics due to its simplicity. In the validation of LBM results, the Rayleigh-Plesset (R-P) equation is commonly employed. However, most studies to date have neglected the impact of simulation settings on the predictions. This article sets out to quantify the impact of LBM domain size and bubble size, and the initial conditions of the R-P equations on the predicted bubble dynamics. First, LBM results were validated against the classical benchmarks of Laplace’s law and Maxwell’s area construction. LBM results corresponding to these fundamental test cases were found to be in satisfactory agreement with theory and previous simulations. Secondly, a one-to-one comparison was considered between the predictions of the LBM and the R-P equation. The parameters of the two models were matched based on careful considerations. Findings revealed that a good overlap between the predictions is observable only under certain conditions. The warming-up period of the LBM simulations, small domain size, and small bubble radius were identified as key factors responsible for the measured differences. The authors hope that the results will promote good simulation practices for cavitation simulation including both single bubbles and bubble clusters.Item Open Access Dataset DrivAer hp-F: Force Measurements at Various Rear Wing Angles of Attack(Cranfield University, 2024-04-30 10:36) Rijns, Steven; Teschner, Tom-Robin; Blackburn, Kim; Brighton, JamesDataset for the aerodynamic force measurements on the 35% scale DrivAer hp-F rear wing configuration using the moving ground facility in the 8x6 Wind Tunnel at Cranfield University. The dataset includes aerodynamic force coefficients results from the moving ground experiments on the DrivAer hp-F with rear wing angle of attack settings ranging from 0°-27.5°. The measurements have been conducted three times at each angle of attack setting for repeatability. In reference to the publication: Steven Rijns, Tom-Robin Teschner, Kim Blackburn, James Brighton; Effects of cornering conditions on the aerodynamic characteristics of a high-performance vehicle and its rear wing. Physics of Fluids 1 April 2024; 36 (4): 045119. https://doi.org/10.1063/5.0204204 CAD files for the DrivAer hp-F rear wing configuration are available at: Rijns, Steven; Teschner, Tom-Robin; Blackburn, Kim; Ramos Proenca, Anderson; Brighton, James (2024). DrivAer hp-F: Spoiler & Rear Wing Configurations Geometry Pack. Cranfield Online Research Data (CORD). Dataset. https://doi.org/10.17862/cranfield.rd.25715202 'Item Open Access Dataset DrivAer hp-F: Force Measurements in Yaw Conditions(Cranfield University, 2024-04-30 10:34) Rijns, Steven; Teschner, Tom-Robin; Blackburn, Kim; Ramos Proenca, Anderson; Brighton, JamesDataset for the aerodynamic force measurements conducted on the 35% scale DrivAer hp-F model at various yaw angles in the 8x6 wind Tunnel at Cranfield University. The dataset includes aerodynamic force coefficients results from measurement on the following vehicle configurations: - DrivAer hp-F standard configuration (no spoiler or rear wing) - DrivAer hp-F spoiler configuration - DrivAer hp-F rear wing configuration The measurements on the DrivAer hp-F rear wing configuration have been conducted three times for repeability. In reference to the publication: Steven Rijns, Tom-Robin Teschner, Kim Blackburn, Anderson Ramos Proenca, James Brighton; Experimental and numerical investigation of the aerodynamic characteristics of high-performance vehicle configurations under yaw conditions. Physics of Fluids 1 April 2024; 36 (4): 045112. https://doi.org/10.1063/5.0196979 CAD files for the DrivAer hp-F configurations are available at: Rijns, Steven; Teschner, Tom-Robin; Blackburn, Kim; Ramos Proenca, Anderson; Brighton, James (2024). DrivAer hp-F: Spoiler & Rear Wing Configurations Geometry Pack. Cranfield Online Research Data (CORD). Dataset. https://doi.org/10.17862/cranfield.rd.25715202Item Open Access Dataset DrivAer hp-F: Surface Pressure Measurements in Yaw Conditions(Cranfield University, 2024-04-30 10:42) Rijns, Steven; Teschner, Tom-Robin; Blackburn, Kim; Ramos Proenca, Anderson; Brighton, JamesDataset for the surface pressure measurements conducted on the 35% scale DrivAer hp-F model at various yaw angles in the 8x6 Wind Tunnel at Cranfield University. The dataset includes the surface pressure coefficient results from measurements on the slant of the following vehicle configurations: - DrivAer hp-F standard configuration (no spoiler or rear wing) - DrivAer hp-F spoiler configuration - DrivAer hp-F rear wing configuration The measurements on the DrivAer hp-F rear wing configuration have been conducted three times for repeatability. The dataset also includes a log file of the data structure and wind tunnel conditions for each experiment. In reference to the publication: Steven Rijns, Tom-Robin Teschner, Kim Blackburn, Anderson Ramos Proenca, James Brighton; Experimental and numerical investigation of the aerodynamic characteristics of high-performance vehicle configurations under yaw conditions. Physics of Fluids 1 April 2024; 36 (4): 045112. https://doi.org/10.1063/5.0196979 CAD files for the DrivAer hp-F configurations are available at: Rijns, Steven; Teschner, Tom-Robin; Blackburn, Kim; Ramos Proenca, Anderson; Brighton, James (2024). DrivAer hp-F: Spoiler & Rear Wing Configurations Geometry Pack. Cranfield Online Research Data (CORD). Dataset. https://doi.org/10.17862/cranfield.rd.25715202Item Open Access Dataset DrivAer hp-F: Wake Total Pressure Measurements in Yaw Conditions(Cranfield University, 2024-04-30 10:39) Rijns, Steven; Teschner, Tom-Robin; Blackburn, Kim; Ramos Proenca, Anderson; Brighton, JamesDataset for the wake total pressure measurements conducted on the 35% scale DrivAer hp-F model at various yaw angles in the 8x6 Wind Tunnel at Cranfield University. The measurements are performed on the DrivAer hp-F rear wing configuration with an angle of attack of 15°. The dataset includes the total pressure coefficient results from measurements on the P1, P2, and P3 wake planes, which are located 400 mm, 700 mm, and 1000 mm downstream of the vehicle model respectively. Additionally, the horizontal and vertical measurements positions (in mm) are provided for each wake plane. A horizontal sweep on the P3 wake plane has been conducted three times for repeatability. In reference to the publication: Steven Rijns, Tom-Robin Teschner, Kim Blackburn, Anderson Ramos Proenca, James Brighton; Experimental and numerical investigation of the aerodynamic characteristics of high-performance vehicle configurations under yaw conditions. Physics of Fluids 1 April 2024; 36 (4): 045112. https://doi.org/10.1063/5.0196979 CAD files for the DrivAer hp-F rear wing configuration are available at: Rijns, Steven; Teschner, Tom-Robin; Blackburn, Kim; Ramos Proenca, Anderson; Brighton, James (2024). DrivAer hp-F: Spoiler & Rear Wing Configurations Geometry Pack. Cranfield Online Research Data (CORD). Dataset. https://doi.org/10.17862/cranfield.rd.25715202Item Open Access DrivAer hp-F: Spoiler & Rear Wing Configurations Geometry Pack(Cranfield University, 2024-04-30 09:44) Rijns, Steven; Teschner, Tom-Robin; Blackburn, Kim; Ramos Proenca, Anderson; Brighton, JamesCAD geometry files for the 35% scale high-performance DrivAer model (DrivAer hp-F). The dataset includes CAD files for the: - DrivAer hp-F vehicle body, equipped with a 41 mm front bumper splitter, a full set of large forebody strakes, and a 10° underbody multichannel diffuser. - Rear wing with a NACA 6412 profile, chord of 110 mm, and span of 420 mm. - Spoiler with a plate size of 350 x 80 mm at a 40° angle of attack - Wheels (stationary and rotating) In reference to the publications: Steven Rijns, Tom-Robin Teschner, Kim Blackburn, Anderson Ramos Proenca, James Brighton; Experimental and numerical investigation of the aerodynamic characteristics of high-performance vehicle configurations under yaw conditions. Physics of Fluids 1 April 2024; 36 (4): 045112. https://doi.org/10.1063/5.0196979 Steven Rijns, Tom-Robin Teschner, Kim Blackburn, James Brighton; Effects of cornering conditions on the aerodynamic characteristics of a high-performance vehicle and its rear wing. Physics of Fluids 1 April 2024; 36 (4): 045119. https://doi.org/10.1063/5.0204204 This geometry pack uses components from the original DrivAer hp-F: the CAD geometry pack collection: Soares, Renan francisco; Olives, Sergio Goñalons; Knowles, Andrew Paul; Garry, Kevin; Holt, Jenny (2018). DrivAer hp-F: the CAD geometry pack. Cranfield Online Research Data (CORD). Collection. https://doi.org/10.17862/cranfield.rd.c.3969120Item Open Access dsmcFoam+ case setup for the Orion Crew Module(Cranfield University, 2021-06-04 09:10) Teschner, Tom-RobinThis material provides the OpenFOAM case setup files for the Orion Crew Module (OCM) in support of the submitted manuscript "Aerodynamic performance investigation through different chemistry modelling approaches for space re-entry vehicles using the DSMC method", presented at the UKACM 2022 conference. The case setup files are for the dsmcFoam+ solver and provide the mesh as well as the full setup for the Orion Crew Module (OCM) in 2D using the QK chemical model. All reactions are implemented for a 5-species flow.Item Open Access Effects of cornering conditions on the aerodynamic characteristics of a high-performance vehicle and its rear wing(American Institute of Physics (AIP), 2024-04-09) Rijns, Steven; Teschner, Tom-Robin; Blackburn, Kim; Brighton, JamesThis study investigates the aerodynamic behavior of a high-performance vehicle and the interaction with its rear wing in straight-line and steady-state cornering conditions. Analyses are performed with Reynolds-averaged Navier–Stokes based computational fluid dynamics simulations using a moving reference frame and overset mesh technique, validated against moving ground wind tunnel experiments. The results indicate a significant 20% decrease in downforce and 35% increase in drag compared to straight-line conditions at the smallest considered corner radius of 2.9 car-lengths. Downforce losses primarily stem from performance deficits on the underbody and rear wing, alongside elevated upper body lift. Drag penalties mainly result from additional pressure drag induced by a recirculation wake vortex generated behind the vehicle's inboard side. The vehicle's lateral pressure distribution is also affected, introducing a centripetal force that increases with smaller corner radii. Additionally, analyses of the rear wing reveal alternations of its aerodynamic characteristics in cornering, particularly impacting vortical flow and suction on the lower surface. Throughout the operating conditions, the rear wing's individual downforce contribution falls off beyond its stall angle. At higher angles of attack, the rear wing primarily generates downforce by pressurizing the vehicle's upper surfaces, but its interaction with the near-wake leads to a substantially increased pressure drag. Overall, these findings provide crucial insights into the intricate aerodynamic interactions of high-performance vehicles in diverse operating conditions as well as form an essential foundation for future research on static and active aerodynamic designs in the pursuit to optimize vehicle performance in dynamic driving conditions.Item Open Access Experimental and numerical aerodynamic analysis of an elevated beachfront house(Elsevier, 2022-11-23) Townsend, Jamie F.; Teschner, Tom-Robin; Xu, Guoji; Zou, Lianghao; Han, Yan; Cai, C. S.Elevating coastal houses enables residential communities to reduce the risk of flooding due to tropical cyclones. However, wind-induced damage during such events requires an understanding of the inherent wind forces to improve damage mitigation techniques and assessment of climate-related risk in insurance models. In this study, wind-tunnel experiments and computational fluid dynamics (CFD) simulations are conducted for a typical elevated 1:25 scale beachfront house, possessing a 5:12 pitched gable roof with overhanging eave. An atmospheric boundary layer (ABL) wind field is generated in a low-speed wind-tunnel to replicate conditions experienced during tropical cyclones. Testing is performed for a range of incident wind angles to understand the full aerodynamic consequences of strong winds. Measured pressure coefficient (Cp) distributions are compared with CFD simulations using steady-state and transient Delayed Detached-Eddy Simulation (DDES) within ANSYS Fluent 2021 R1. Net Cp values surrounding the overhanging eave are considered to evaluate the role of this typical geometrical feature. It was found that larger uplift suction occurred at incident wind angles of 45°and above, after which the suction remained stable. The roof panels are subjected to the greatest upward suction, where critical regions occur at the roof ridge. The size of the low-pressure regions is determined by the incident wind angle and ensuing flow separation wherein DDES is found to reproduce additional aerodynamic features arising from unsteady turbulent flow. DDES offers improved predictive capability when mean pressure forces are considered but falls short as an accurate means to efficiently evaluate peak distributions.Item Open Access Experimental and numerical investigation of the aerodynamic characteristics of high-performance vehicle configurations under yaw conditions(AIP Publishing, 2024-04-05) Rijns, Steven; Teschner, Tom-Robin; Blackburn, Kim; Ramos Proenca, Anderson; Brighton, JamesThis study investigates the impact of yaw conditions on the aerodynamic performance and flow field of three high-performance vehicle model configurations by means of wind tunnel testing and unsteady Reynolds-Averaged Navier–Stokes-based computational fluid dynamics simulations. While yaw effects on automotive vehicles have been explored, the effects on far more complex flow fields of high-performance vehicles remain insufficiently researched. This paper reveals that yaw conditions have a significant negative influence both downforce and drag performance. Spoiler and rear wing devices enhance downforce but increase the vehicle's sensitivity to yaw. Furthermore, yaw conditions significantly alter vortex structures and local flow velocities, affecting downstream flow behavior. Surface pressure measurements on the slant confirm these findings and highlight notable yaw effects and upstream effects from spoiler and rear wing devices. Wake analyses through total pressure measurements show that yaw induces a substantial deviation from straight-line wake characteristics, which become dominated by an inboard rotating vehicle body vortex. Overall, this research enhances the understanding of the effects of yaw conditions on high-performance vehicle aerodynamics and provides valuable data for future vehicle aerodynamics research in real-world operating conditions.Item Open Access Flow field analysis around pressure shielding structures(2021-07-28) Szoke, Máté; Hari, Nandita Nurani; Devenport, William J.; Glegg, Stewart A.; Teschner, Tom-RobinThe flow field around a series of streamwise rods, referred to as canopies, is investigated using two-dimensional two-component time-resolved particle image velocimetry (PIV) and large eddy simulations (LES) to characterize the changes in the flow field responsible for reducing the low and high-frequency surface pressure fluctuations previously observed. It was found that an axisymmetric turbulent boundary layer (ATBL) develops over the rods, whose thickness grows at a greater rate above the rods than below. This boundary layer reaches the wall below the rods at a point where previously a saturation was found in the low-frequency noise attenuation, revealing that the ATBL is responsible for the low-frequency noise attenuation. The flow is displaced by the presence of the rods, particularly above them, which offset was primarily caused by the blockage of the ATBL. The flow below the rods exhibits the properties of a turbulent boundary layer as its profile still conforms to the logarithmic layer, but the friction velocity was found to drop. This viscous effect was found to be responsible for the high-frequency noise attenuation reported previously.Item Open Access A generalised and low-dissipative multi-directional characteristics-based scheme with inclusion of the local Riemann problem investigating incompressible flows without free-surfaces,(Elsevier, 2019-01-21) Teschner, Tom-Robin; Könözsy, László Z.; Jenkins, Karl W.In the present study, we develop a generalised Godunov-type multi-directional characteristics-based (MCB) scheme which is applicable to any hyperbolic system for modelling incompressible flows. We further extend the MCB scheme to include the solution of the local Riemann problem which leads to a hybrid mathematical treatment of the system of equations. We employ the proposed scheme to hyperbolic-type incompressible flow solvers and apply it to the Artificial Compressibility (AC) and Fractional-Step, Artificial Compressibility with Pressure Projection (FSAC-PP) method. In this work, we show that the MCB scheme may improve the accuracy and convergence properties over the classical single-directional characteristics-based (SCB) and non-characteristic treatments. The inclusion of a Riemann solver in conjunction with the MCB scheme is capable of reducing the number of iterations up to a factor of 4.7 times compared to a solution when a Riemann solver is not included. Furthermore, we found that both the AC and FSAC-PP method showed similar levels of accuracy while the FSAC-PP method converged up to 5.8 times faster than the AC method for steady state flows. Independent of the characteristics- and Riemann solver-based treatment of all primitive variables, we found that the FSAC-PP method is 7–200 times faster than the AC method per pseudo-time step for unsteady flows. We investigate low- and high-Reynolds number problems for well-established validation benchmark test cases focusing on a flow inside of a lid driven cavity, evolution of the Taylor–Green vortex and forced separated flow over a backward-facing step. In addition to this, comparisons between a central difference scheme with artificial dissipation and a low-dissipative interpolation scheme have been performed. The results show that the latter approach may not provide enough numerical dissipation to develop the flow at high-Reynolds numbers. We found that the inclusion of a Riemann solver is able to overcome this shortcoming. Overall, the proposed generalised Godunov-type MCB scheme provides an accurate numerical treatment with improved convergence properties for hyperbolic-type incompressible flow solvers.Item Open Access A generalised multi-directional characteristic-based Godunov-type framework for elliptic, parabolic and hyperbolic pressure-based incompressible methods(2018-02) Teschner, Tom-Robin; Könözsy, László Z.; Jenkins, Karl W.The objective of the current research is to construct numerical methods based on physical principles to reduce modelling errors in the field of computational fluid dynamics. In order to investigate the non-linearities of the convective flux term, a multi-directional characteristic-based scheme has been developed in this work to capture the anisotropic behaviour of the incompressible Navier{Stokes equations. To avoid the pressure-velocity decoupling and to promote stability at high Reynolds numbers, the Riemann problem has been incorporated into the scheme which creates a multi-directional Godunov-type framework. In order to capture the pressure correctly, which through its coupling to the velocity field is depending on the velocity's non-linear effects, it is postulated that the pressure should have its own transport equation which should have a parabolic type. This is necessary to align the pressure with the mathematical properties of the Navier{Stokes equations. Thus, a novel incompressible method has been developed which features a pressure transport equation which is referred to as the Fractional-Step with Velocity Projection (or FSVP) method. It is further extended through a perturbed continuity equation of the Arti cial Compressibility (AC) method to hyperbolise the first Fractional-Step of the system of equations, while the second Fractional-Step retains the required parabolic behaviour, which is called the FSAC-VP method in turn. Through the hyperbolic Fractional-Step, the multi-directional Godunov-type framework is directly applicable to the newly developed method. Parametric simulations for the lid driven cavity, backward facing step, sudden expan- sion and Taylor{Green vortex problem have been performed using the AC, FSVP, FSAC-VP and the Fractional-Step, Arti cial Compressibility with Pressure Projection, or FSAC-PP, method. The FSVP and FSAC-VP method showed superior convergence properties compared to the AC method for unsteady flows, where a speed up of a factor up to 193.0 times has been observed. Since the parabolic pressure transport equation has a memory of the time history of the flow, smooth error curves have been produced over time while the other methods showed oscillatory profi les. Generally speaking, the most accurate results have been obtained with the FSAC-PP method, closely followed by the FSAC-VP and FSVP method. The inclusion of the multi-directional Godunov-type framework showed generally better or equally well resolved results compared to the benchmark numerical scheme for the FSAC-PP and FSAC-VP / FSVP method. Furthermore, the multi-directional scheme by itself showed its capabilities to predict vortical flows better than a simple numerical reconstruction scheme. The FSAC-VP method has shown a higher degree of scheme independence where velocity and pressure curves showed little variations compared to reference data. This was particularly pronounced for the sudden expansion which had consequences on the prediction of the correct bifurcation behaviour. Finally, it has been argued that what the numerical scheme development is to the non-linear term of the Navier{Stokes equations should be similarly done with incompressible flow method development to capture the correct pressure behaviour. This work shows that differences between elliptic, parabolic and hyperbolic pressure treatments do exist which can have a significant effect on the overall prediction of the flow features.Item Open Access A high-resolution, unified incompressible solver framework for turbulent flows in OpenFOAM(2023-04-21) Teschner, Tom-RobinThis work introduces the Factional-Step, Artificial Compressibility with Pressure Projection (FSAC-PP) method into OpenFOAM, a fast pressure-velocity coupling algorithm for incompressible flows. It is tested for the lid driven cavity problem and it is shown that the pressure Poisson solver speeds up the solution by up to 27.1% compared to the Pimple algorithm available in OpenFOAM. Comparison against the Pressure Projection method from which the FSAC-PP method is derived, are similar favourably.Item Open Access A hybrid computer vision and machine learning approach for robust vortex core detection in fluid mechanics applications(Unconfirmed, 2022-04-22) Abolholl, Hazem Ashor Amran; Teschner, Tom-Robin; Moulitsas, IreneVortex core detection remains a challenging topic within the field of computational fluid dynamics (CFD). Local methods, such as the Q, delta, or swirling-strength criterion, are commonly used to detect vortices and these methods are entirely based on the local velocity gradient tensor. Results have shown that reasonable estimates can be obtained with these methods, however, at the same time, these methods produce a significant number of false positives and negatives. User-defined tuning parameters are introduced to keep the number of false positives and negatives in balance, but this requires knowledge of the vortices and thus does not present a robust and self-contained approach. We recently proposed a novel computer vision approach where we have trained a convolutional neural network (CNN) to look at line integral convolution (LIC)-based streamline plots. We showed that this approach is capable of accurately predicting the regions where vortices reside, and we were able to reduce the false positives and negatives to zero. Furthermore, we showed the universality of this approach by successfully applying our trained CNN to a different test case for which it has not been trained and which featured different vortical structures (generated through a different physical process). The CNN-based approach is limited in the sense that it is only able to predict the bounding boxes of vortex cores, but not the exact location of the vortex core itself. Therefore, we propose a hybrid machine learning and computer vision approach in this study, where we first identify areas of vortical structures using computer vision to which we add a layer of machine learning to find the vortex core within the vortex region. We test different sets of input parameters for both the hybrid and pure machine learning approach, starting with just the primitive variables (velocity and pressure), and adding more derived quantities (velocity gradients, pressure gradients, Q-criterion, vorticity, and magnitude of vector quantities). Comparing the hybrid with the pure machine learning approach applied to the full flow field, we show that the hybrid approach reduces the training time for all tested cases up to a factor of 2. We also find that using the primitive variables along with their derivatives provide fewer false positives and negatives using the hybrid approach. At the same time, using the variable set with all possible inputs does not provide a more accurate prediction of vortex cores and thus we demonstrate that our hybrid computer vision and machine learning approach is an effective way to reduce false positives and negatives entirely using just the primitive variables and their derivatives.Item Open Access A hybrid computer vision and machine learning approach for robust vortex core detection in fluid mechanics applications(American Society of Mechanical Engineers, 2024-01-12) Abolholl, Hazem Ashor Amran; Teschner, Tom-Robin; Moulitsas, IreneVortex core detection remains an unsolved problem in the field of experimental and computational fluid dynamics. Available methods such as the Q, delta and swirling-strength criterion are based on a decomposed velocity gradient tensor but detect spurious vortices (false positives and false negatives), making these methods less robust. To overcome this, we propose a new hybrid machine learning approach in which we used a convolutional neural network to detect vortex regions within surface streamline plots and an additional deep neural network to detect vortex cores within identified vortex regions. Furthermore, we propose an automatic labelling approach based on K-means clustering to pre-process our input images. We show results for two classical test cases in fluid mechanics; the Taylor-Green vortex problem and two rotating blades. We show that our hybrid approach is up to 2.6 times faster than a pure deep neural network-based approach and furthermore show that our automatic K-means clustering labelling approach is within 0.45% mean square error of the more labour-intensive, manual labelling approach. At the same time, using a sufficient number of samples, we show that we are able to reduce false positives and negatives entirely and thus show that our hybrid machine learning approach is a viable alternative to currently used vortex detection tools in fluid mechanics applications.Item Open Access Implementation of the fractional-step, artificial compressibility with pressure projection (FSAC-PP) method into openfoam for unsteady flows(University of Miskolc, 2021-12-03) Sánchez Gil, Jesús Miguel; Teschner, Tom-Robin; László, KönözsyCommercial and open-source CFD solvers rely mostly on incompressible approximate projection methods to overcome the pressure-velocity decoupling, such as the SIMPLE (Patankar, 1980) or PISO (Issa, 1986) algorithm. Incompressible methods based on the Artificial Compressibility method (Chorin, 1967) lack a mechanism to evolve in time and need to be supplemented by a real time derivative through the dual time scheme. The current study investigates the implementation of the explicit dual time discretization of the Artificial Compressibility method into OpenFOAM and extends on that by applying the dual time scheme to the incompressible FSAC-PP method (Könözsy, 2012). Applied to the Couette 2D flow at Re=100 and Re=1000, results show that for both methods accurate time evolutions of the velocity profiles are presented, where the FSAC-PP methods seemingly produces smoother profiles compared to the AC method, especially during the start-up of the simulation.Item Open Access Integrated numerical and experimental workflow for high-performance vehicle aerodynamics(Society of Automotive Engineers, 2024-02-06) Rijns, Steven; Teschner, Tom-Robin; Blackburn, Kim; Brighton, JamesThe high-performance and motorsport vehicle sectors are pushing the performance frontiers of aerodynamically efficient vehicles. Well-balanced use of accurate and consistent numerical simulation tools in combination with wind tunnel experiments is crucial for cost-effective aerodynamic research and development processes. Therefore, this study assesses the simulation performance of four Reynolds-averaged Navier–Stokes (RANS) turbulence models in relation to experimental and high-fidelity delayed detached eddy simulation (DDES) data for the aerodynamic assessment of a high-performance variant of the DrivAer model (DrivAer hp-F). The influences of predominant wind tunnel conditions on the vehicle’s aerodynamic force coefficients and flow field are also investigated. Additionally, a novel CFD-based blockage correction method is introduced and applied to evaluate the accuracy of conventional blockage correction methods. Among the RANS models, the k-ω SST model exhibited notable relative accuracy in the prediction of force coefficients and demonstrated generally the best correlation with detailed DDES flow field data. The wind tunnel blockage effect caused a 9% increase in downforce and 16% increase in drag, whereas the interference effects from the overhead measurement system reduced downforce by 4% and drag by 8%. The novel CFD-based blockage correction method confirmed that conventional blockage correction methods adequately estimate the dynamic pressure in proximity of a wind tunnel model (<3%), but do not consider local effects on downforce and drag individually. Overall, the research extends beyond prior work on automotive applications, contributing to the advancement of aerodynamic research methodologies suitable for the complex flow fields of high-performance vehicles.