High-fidelity CFD Research Articles

The wind farm as a sensor in highly complex terrain

Abstract This paper demonstrates the wind farm as a sensor methodology at an onshore site in highly complex terrain. The method provides a site-specific engineering flow model, by using the whole farm as a distributed sensor. Two years of operational turbine data, synthesised to long term observations, are available. For the site-adaption, an engineering wake model is augmented with parametric correction terms that model the heterogenous intra-farm flow field caused by the terrain at the site. This background field, together with the tuning parameters of the engineering wake model, are simultaneously learned through the observational data. High-fidelity CFD RANS simulations from different directions provide an independent source for the intra-farm field caused by the terrain. The data-driven flow field, as well as the CFD simulations, reveal the presence of significant orography-induced effects throughout the site.

In-depth understanding of Sodium Heat Transfer Characteristics with Low Prandtl number in Wire-wrapped Fuel Assemblies using High-Fidelity CFD technique

In-depth understanding of Sodium Heat Transfer Characteristics with Low Prandtl number in Wire-wrapped Fuel Assemblies using High-Fidelity CFD technique

DrivAerNet: A Parametric Car Dataset for Data-Driven Aerodynamic Design and Prediction

Abstract This study introduces DrivAerNet, a large-scale high-fidelity CFD dataset of 3D industry-standard car shapes, and RegDGCNN, a dynamic graph convolutional neural network model, both aimed at aerodynamic car design through machine learning. DrivAerNet, with its 4000 detailed 3D car meshes using 0.5 million surface mesh faces and comprehensive aerodynamic performance data comprising of full 3D pressure, velocity fields, and wall-shear stresses, addresses the critical need for extensive datasets to train deep learning models in engineering applications. It is 60% larger than the previously available largest public dataset of cars, and is the only open-source dataset that also models wheels and underbody. RegDGCNN leverages this large-scale dataset to provide high-precision drag estimates directly from 3D meshes, bypassing traditional limitations such as the need for 2D image rendering or Signed Distance Fields (SDF). By enabling fast drag estimation in seconds, RegDGCNN facilitates rapid aerodynamic assessments, offering a substantial leap towards integrating data-driven methods in automotive design. Together, DrivAerNet and RegDGCNN promise to accelerate the car design process and contribute to the development of more efficient vehicles. To lay the groundwork for future innovations in the field, the dataset and code used in our study are publicly accessible at https://github.com/Mohamedelrefaie/DrivAerNet.

High-Fidelity CFD Simulation of Mixed Convection and Forced Convection in a Pebble Bed Test Reactor Core

The Hermes low-power [35-MW(thermal)] reactor will be built and operated by Kairos Power LLC (KP) to demonstrate its fluoride salt–cooled high-temperature reactor (FHR) technology. In the KP FHR, the reactor core is composed of randomly packed pebbles with TRISO fuel particles inside with FLiBe flow upward through the core acting as a coolant. Previous numerical and experimental studies have been limited to either a small-size bed or to a lack of detailed measurements for heat transfer. To address the lack of high-fidelity heat transfer data in a real-size FHR core, in this study, we simulated a pebble bed core with 34 374 pebbles randomly packed, similar to the Hermes reactor’s size. The core radius was 14 times that of the pebble diameter, while the core height was 45 times. In this work, we were particularly interested in a mixed convection regime, where buoyancy is important. Therefore, we performed several large-eddy simulations at different Reynolds numbers (160 to 1000) with gravitational force included. The spectral element computational fluid dynamics code NekRS with graphics processing unit acceleration was used for this study. The low-Mach number approximation was applied to address property changes in the FLiBe and to account for buoyancy. A pure hexahedral mesh with 60 million elements was generated by the Voronoi cell method. At the polynomial order of 5, the total degrees of freedom was 7.5 billion. The developed case in this work is the first of its kind in terms of size and complexity. The local numerical data across the domain were obtained and compared with empirical correlations. After examining the data, we found the following conclusions. For pressure drop, the Reger correlation predicted less than a 5% error. On the other hand, for heat transfer, the Wakao correlation outperformed the others. Based on our findings, we recommend the use of the Wakao correlation for the Nusselt number calculation, and for pressure drop, the KTA (Kerntechnischer Ausschuss) correclation, among the available experimental correlations. The Reger direct numerical simulation–driven correlation for pressure drops should also be considered, given its best agreement with our calculations.

Comprehensive CFD Analysis of Hypersonic Missile Nose Cone

Abstract: This study employs high-fidelity CFD to analyze a hypersonic missile nose cone's aerodynamics and boundary layer behavior (Mach > 5, zero angles of attack) under idealized conditions. The simulation leverages ideal gas assumptions for simplicity while incorporating advanced turbulence models to capture hypersonic flow phenomena. The analysis focuses on pressure distribution across the nose cone to assess shockwave and streamline curvature effects. Lift and drag forces are computed to evaluate overall aerodynamic performance. Critically, the investigation delves into the boundary layer, evaluating parameters like thickness, velocity profile, and potential separation points to understand pressure and temperature variations crucial for heat transfer and flow stability

Workflow for high-quality visualisation of large-scale CFD simulations by volume rendering

Workflow for high-quality visualisation of large-scale CFD simulations by volume rendering

High-fidelity CFD simulations of two tandemly arrayed wind turbines under various operating conditions

High-fidelity CFD simulations of two tandemly arrayed wind turbines under various operating conditions

Enhanced Drag Force Estimation in Automotive Design: A Surrogate Model Leveraging Limited Full-Order Model Drag Data and Comprehensive Physical Field Integration

In this paper, a novel surrogate model for shape-parametrized vehicle drag force prediction is proposed. It is assumed that only a limited dataset of high-fidelity CFD results is available, typically less than ten high-fidelity CFD solutions for different shape samples. The idea is to take advantage not only of the drag coefficients but also physical fields such as velocity, pressure, and kinetic energy evaluated on a cutting plane in the wake of the vehicle and perpendicular to the road. This additional “augmented” information provides a more accurate and robust prediction of the drag force compared to a standard surface response methodology. As a first step, an original reparametrization of the shape based on combination coefficients of shape principal components is proposed, leading to a low-dimensional representation of the shape space. The second step consists in determining principal components of the x-direction momentum flux through a cutting plane behind the car. The final step is to find the mapping between the reduced shape description and the momentum flux formula to achieve an accurate drag estimation. The resulting surrogate model is a space-parameter separated representation with shape principal component coefficients and spatial modes dedicated to drag-force evaluation. The algorithm can deal with shapes of variable mesh by using an optimal transport procedure that interpolates the fields on a shared reference mesh. The Machine Learning algorithm is challenged on a car concept with a three-dimensional shape design space. With only two well-chosen samples, the numerical algorithm is able to return a drag surrogate model with reasonable uniform error over the validation dataset. An incremental learning approach involving additional high-fidelity computations is also proposed. The leading algorithm is shown to improve the model accuracy. The study also shows the sensitivity of the results with respect to the initial experimental design. As feedback, we discuss and suggest what appear to be the correct choices of experimental designs for the best results.

Insights Into Turbocharger Centrifugal Compressor Stability Using High-Fidelity CFD and a Novel Impeller Diffusion Factor

Abstract Turbocharger technologies are widely applied in the modern automotive industry to meet increasingly stringent carbon emission standards. To support the continuous enhancement of these tactics, delivering improvement to the performance and stability of turbocharger compressors at low mass flow rate regimes is of paramount importance. The present paper investigated the stability of a turbocharger compressor stage equipped with a ported shroud, using high-fidelity CFD simulations. It was found that the recirculated flow passing through the ported shroud device had primary influence on the flow condition in the vicinity of the impeller tip region (80% to 100% span). This discovery facilitated the definition of a modified impeller diffusion factor (DF), which was applied to the CFD results for three different compressor geometry configurations to lead to the provision of quantitative metrics for impeller stability. Furthermore, the observed change in the limiting impeller DF along the compressor surge line indicated that the dominant components governing the instability of the entire stage had switched, i.e., the stalling behavior of the compressor stage had transitioned from impeller dominated stall to vaneless diffuser dominated stall. Additionally, the limiting impeller DF clearly showed that one of the compressor configurations with a change in the hub endwall recess around the rear of the impeller improved the impeller stability by 3%. By comparison, another configuration with a change to strut geometry in the ported shroud recirculation channel reduced the impeller stability by 10%.

Optimization of Thrust of a Generic X-51 Hypersonic Vehicle

A prune-and-search optimization algorithm was combined with a reduced-order model of the scramjet engine within a generic X-51 vehicle. The goal was to maximize the thrust in order to achieve thrust-to-drag ratios that equal or exceed 1, even for the difficult cases of flight at high altitudes and high Mach numbers up to 10. For the inlet to the engine, the lengths and inclination angles of three wall panels were varied. For the combustor, three parameters were varied: the diameter and number of fuel injector ports and the wall divergence angle. These variables affect both the combustion efficiency and the finite-rate chemistry of the surrogate JP-7 fuel. The optimization algorithm showed that at higher flight Mach numbers an inlet that maximizes static pressure ratio is preferred over one that maximizes the stagnation pressure ratio, because good combustion efficiency requires a sufficient static pressure in the combustor. As the flight Mach number is increased, thrust decreases while the drag increases. Thus, it becomes difficult to achieve thrust that exceeds drag. A solution is shown to be increasing the engine inlet area above a critical value that was computed. Advantages of a reduced-order model over a high-fidelity CFD approach are discussed when thousands of computations of all components within an entire engine are required for optimization.

Numerical Simulation Method for the Aeroelasticity of Flexible Wind Turbine Blades under Standstill Conditions

With the trend towards larger and lighter designs of wind turbines, blades are progressively being developed to have longer and more flexible configurations. Under standstill conditions, the separated flow induced by a wide range of incident flow angles can cause complex aerodynamic elastic phenomena on blades. However, classical momentum blade element theory methods show limited applicability at high angles of attack, leading to significant inaccuracies in wind turbine performance prediction. In this paper, the geometrically accurate beam theory and high-fidelity CFD method are combined to establish a bidirectional fluid–structure coupling model, which can be used for the prediction of the aeroelastic response of wind turbine blades and the analysis of fluid–structure coupling. Aeroelastic calculations are carried out for a single blade under different working conditions to analyze the influence of turbulence, gravity and other parameters on the aeroelastic response of the blade. The results show that the dominant frequency of the vibration deformation response in the edgewise direction is always the same as the first-order edgewise frequency of the blade when the incoming flow condition is changed. The loading of gravity will make the aeroelastic destabilization of the blade more significant, which indicates that the influence of gravity should be taken into account in the design of the aeroelasticity of the wind turbine. Increasing the turbulence intensity will change the dominant frequency of the vibration response in the edgewise direction, and at the same time, it will be beneficial to the stabilization of the aeroelasticity response.

Machine learning of unsteady transonic aerodynamics of a pitching truss-braced wing section

Machine learning of unsteady transonic aerodynamics of a pitching truss-braced wing section

Aeroelastic fluid dynamics assessment of performance and vibration on active twisting rotors

The effects of passive, and higher-harmonic rotor blade twist on helicopter main rotors are investigated. High-fidelity CFD is used for calculations due to the demanding flow conditions considered, including high blade loading, and high-speed cases. A strong structural coupling scheme is employed for enhanced performance and vibration predictions. Quantitative predictions are made for the effects of blade twist in hover, and the results showed: figure of merit improvements of up to 1 count per degree of twist, and diminishing returns with increasing twist. In high-speed level flight, the higher twist blade showed 18% increased vibration. A 2/rev active twist input shows vibration reductions of 22% in high-speed and 8% at high load cases. The active twist achieved a marginally improved aerodynamic efficiency at high-speed, and reduced the aerodynamic rolling moment in the dynamic stall conditions.

Tuning the Actuator Line Method to Properly Modelling Tip Effects in Finite-Length Blades

The Actuator Line Method (ALM) is gaining popularity in wind turbine simulations, as it can better handle some of the challenging operating conditions experienced by modern machines, such as highly turbulent inflows, severe aero-elastic forcing, and complex rotor-to-rotor interactions. However, it still falls behind other medium-fidelity methods such as the Lifting Line Free Vortex Wake (LLFVW) when it comes to resolving tip vortices and their effect on the blade spanwise load profile. The reason for such behavior is still unclear. A recent study suggested that this issue can be solved by reducing the scale of the angle of attack (α) sampling and force insertion towards the tip, without the need of additional corrections. This study builds on these findings to further investigate how the ALM base formulation - in terms of α sampling and force insertion - can be tuned to properly describe tip effects. An in-house ALM tool was employed to simulate a finite, constant-chord, NACA0018 wing, for which high-fidelity blade-resolved CFD (BR-CFD) data are available as benchmark. In the first part of the work, different strategies are outlined, including a novel approach for the de-coupling of the angle of attack sampling step from the force projection one, here called DE-coupled LineAverage (DELA). Their accuracy and sensitivity to ALM numerical settings are assessed at a fixed wing pitch angle of 6°. The analysis is then extended to a wider range of blade pitch angles, benchmarking the new ALM formulation against BR-CFD, ALM with the Dağ and Sørensen correction, and LLFVW in terms of blade loads, tip vortex structure, and computational effort.

Multi-fidelity, steady-state aeroelastic modelling of a 22-megawatt wind turbine

In this work we present multi-fidelity steady-state aeroelastic framework that leverages the state-of-the-art simulation tool HAWC2 for the structural model, and a variety of aerodynamic models, comprising of the low fidelity blade element momentum (BEM) method, the medium fidelity blade element vortex cylinder (BEVC) method and the coupled near wake and vortex cylinder method, and finally the high-fidelity CFD solver EllipSys3D. The aeroelastic framework is part of AESOpt, an aerostructural framework for design of wind turbine blades. The different aerodynamic models are applied to compute the aeroelastic steady state of the newly designed IEA 22 MW Reference Wind Turbine. The results show a very good agreement between the medium- and high-fidelity aerodynamic models with a maximum of 2.7% difference between the high-fidelity aeroelastic response and that of the lower fidelities.

An efficient parallel multi-fidelity multi-objective Bayesian optimization method and application to 3-stage axial compressor with 144 variables

An efficient parallel multi-fidelity multi-objective Bayesian optimization method and application to 3-stage axial compressor with 144 variables

High-fidelity aero-acoustic evaluations of a heavy-lift eVTOL in hover

Electric Vertical Take-off Landing (eVTOL) vehicles can transform aviation, but the unconventional aircraft development currently requires an extensive knowledge base. This paper presents a high-fidelity aerodynamic and acoustic evaluation of a heavy-lift multi-rotor eVTOL design in hover. The design, known as Skybus, has an MTOW of 14,000 kg, and six tiltable rotors attached at the tip of three sets of tandem wings with flaps. High-fidelity scale-adaptive CFD simulations of the full-scale Skybus vehicle in hover, with three design variations, were conducted using the HMB3 framework. The aerodynamic performance and interactions were analysed in detail. The baseline airframe caused a blockage force of about 13% of the MTOW, and the compact hovering rotors induced a sinusoidal single-blade loading variation, blended with small local interactions. The near-field acoustics were then directly extracted from the high-fidelity CFD results, and far-field acoustic propagation was computed using the acoustic analogy, following reference acoustic measurements for eVTOLs proposed by EASA. Different aerodynamic interactions and propeller acoustic characteristics showed strong impacts on the vehicle acoustics. The EPNL metric was also computed and analysed assuming various hover duration, and restrictions on maximum EPNL and hover duration are recommended for future rotorcraft hover noise certification. These novel results provide valuable guidance for eVTOL acoustic design, infrastructure planning, and policy-making.

Validation of a Mid-Fidelity Numerical Approach for Wind Turbine Aerodynamics Characterization

This work is aimed at investigating the capabilities and limits of the mid-fidelity numerical solver DUST for the evaluation of wind turbines aerodynamic performance. In particular, this study was conducted by analysing the benchmarks NREL-5 MW and Phase VI wind turbines, widely investigated in the literature via experimental and numerical activities. The work was started by simulating a simpler configuration of the NREL-5 MW turbine to progressively integrate complexities such as shaft tilt, cone effects and yawed inflow conditions, offering a detailed portrayal of their collective impact on turbine performance. A particular focus was then given to the evaluation of aerodynamic responses from the tower and nacelle, as well as aerodynamic behavior in yawed inflow condition, crucial for optimizing farm layouts. In the second phase, the work was focused on the NREL Phase VI turbine due to the availability of experimental data on this benchmark case. A comparison of DUST simulation results with both experimental data and high-fidelity CFD tools shows the robustness and adaptability of this mid-fidelity solver for these applications, thus opening a new scenario for the use of such mid-fidelity tools for the preliminary design of novel wind turbine configurations or complex environments as wind farms, characterised by robust interactional aerodynamics.

Numerical Evaluation of Aircraft Aerodynamic Static and Dynamic Stability Derivatives by a Mid-Fidelity Approach

The present study aimed to investigate the capability of mid-fidelity aerodynamic solvers in performing a preliminary evaluation of the static and dynamic stability derivatives of aircraft configurations in their design phase. In this work, the mid-fidelity aerodynamic solver DUST, which is based on the novel vortex particle method (VPM), was used to perform simulations of the static and dynamic motion conditions of the Stability And Control CONfiguration (SACCON): an unmanned combat aerial vehicle geometry developed by NATO’s Research and Technology Organisation (RTO), which is used as a benchmark test case in the literature for the evaluation of aircraft stability derivatives. Two different methods were exploited to extract the dynamic stability derivative values from the aerodynamic coefficient time histories that were calculated with DUST. The results for the mid-fidelity approach were in good agreement with the obtained experimental data, as well as with the results obtained using more demanding high-fidelity CFD simulations. This demonstrates its suitability when implemented in DUST for predicting the static and dynamic behavior of airloads in different conditions, as well as in reliably predicting the values of stability derivatives, with the advantage of requiring limited computational effort with respect to classical high-fidelity numerical approaches and the use of wind tunnel tests.

Low-Noise Airfoils for Turbomachinery Applications: Two Examples of Optimization

Automotive fans, small wind turbines, and manned and unmanned aerial vehicles (MAVs/UAVs) are just a few examples in which noise generated by the flow’s interaction with aerodynamic surfaces is a major concern. The current work shows the potential of a new airfoil shape to minimize noise generation, maintaining a high lift-to-drag ratio in a prescribed Reynolds regime. This investigation uses a multifidelity approach: a low-fidelity semiempirical model is exploited to evaluate the sound pressure level (SPL). Fast evaluation of a low-cost function enables the computation of a large range of possible profiles, and accuracy is added to the low-fidelity response surface with high-fidelity CFD data. The constraint of maintaining a predefined range of the lift coefficient and lift-to-drag ratio ensures the possibility of using this profile in usual design procedures.