Aerodynamic Research Articles

Load-oriented aerodynamic design approach of low-speed axial fans in the preliminary design stage

Load-oriented aerodynamic design approach of low-speed axial fans in the preliminary design stage

Aerodynamic Design and Performance Analysis of a Large-Scale Composite Blade for Wind Turbines

Aerodynamic Design and Performance Analysis of a Large-Scale Composite Blade for Wind Turbines

Development of a Reduced Order Model-Based Workflow for Integrating Computer-Aided Design Editors with Aerodynamics in a Virtual Reality Dashboard: Open Parametric Aircraft Model-1 Testcase

In this paper, a workflow for creating advanced aerodynamics design dashboards is proposed. A CAD modeler is directly linked to the CFD simulation results so that the designer can explore in real time, assisted by virtual reality (VR), how shape parameters affect the aerodynamics and choose the optimal combination to optimize performance. In this way, the time required for the conception of a new component can be drastically reduced because, even at the preliminary stage, the designer has all the necessary information to make more thoughtful choices. Thus, this work sets a highly ambitious and innovative goal: to create a smart design dashboard where every shape parameter is directly and in real-time linked to the results of the high-fidelity analyses. The OPAM (Open Parametric Aircraft Model), a simplified model of the Boeing 787, was considered as a case study. CAD parameterization and mesh morphing were combined to generate the design points (DPs), while Reduced Order Models (ROMs) were developed to link the results of the CFD analyses to the chosen parameterization. The ROMs were exported as FMUs (Functional Mockup Units) to be easily managed in any environment. Finally, a VR design dashboard was created in the Unity environment, enabling the interaction with the geometric model in order to observe in a fully immersive and intuitive environment how each shape parameter affects the physics involved. The MetaQuest 3 headset has been selected for these tests. Thus, the use of VR for a design platform represents another innovative aspect of this work.

Research on the Aerodynamics of Electric Vehicles

A major contributing factor to the growing severity of the global warming issue is greenhouse gas emissions, of which carbon dioxide from moving cars makes up a significant amount. Therefore, electric vehicles have become the focus of countries to replace conventional internal combustion engine vehicles due to their low emission characteristics. However, the weight of electric vehicles is increased by their reinforced structures and batteries, which reduces their range. In the short run, it is challenging to lower the weight of electric vehicles greatly because of the constraints of battery technology. Thus, lowering air resistance has emerged as a key strategy for extending the range of electric cars. This paper first analyses the reasons why electric vehicles need better aerodynamic design to increase range, including increased environmental demands, battery technology limitations and the high weight of electric vehicles. Next, the causes of air resistance are explored. Finally, the paper discusses ways to design active aerodynamic components to increase or decrease drag under different operating conditions. For example, a front air dam design can reduce the amount of airflow into the underbody, reducing lift and increasing grip. Variable air dams can optimize aerodynamics by automatically adjusting their position according to speed and driving conditions. In conclusion, the aim of this paper is to find and discover ways to optimize the aerodynamic performance of electric vehicles in order to solve the range problem. This paper provides an important theoretical and practical basis for aerodynamic optimization of electric vehicles

Impact of Aerodynamic Design on Vehicle Performance and Vortex Wake Flow

This thesis examines vortex and wake formation mechanisms in automotive aerodynamics and their impact on vehicle performance, emphasizing strategies to mitigate adverse airflow effects through optimal design and computational techniques. It demonstrates that vortices and wake turbulence elevate drag, diminish fuel efficiency, and compromise high-speed vehicle stability. Streamlined body design, optimized rear-end shape, and underbody airflow management can effectively reduce wake turbulence and vortex intensity, enhancing aerodynamic performance. This paper also introduces a variety of computational techniques, including theoretical analysis, wind tunnel experiments and Computational Fluid Dynamics (CFD), and explores the application of these methods in the real-world design process. CFD simulation demonstrates its advantages in evaluating airflow characteristics and optimising design solutions, enabling engineers to carry out efficient iterative design. Future research directions include the application of active aerodynamic systems and the integration of intelligent design algorithms for more efficient airflow control and vehicle performance enhancement.

Deep Learning Method for Airfoil Flow Field Simulation Based on Unet++

ABSTRACTThis paper investigates the accuracy of U‐Net++ networks in predicting Reynolds‐Averaged Navier‐Stokes (RANS) solutions. The study employs the symbolic distance function (SDF) to represent geometry and flow conditions, utilizing parameterized airfoil data from the UIUC (University of Illinois at Urbana‐Champaign) airfoil datasets. The research assesses the performance of multiple trained neural networks in predicting pressure and velocity distributions. Specifically, the study examines the influence of varying network weights on solution accuracy. Through the optimization of the model, the research demonstrates that the mean relative error is below 1.72% for a range of previously unseen wing shapes, with a computational speedup factor of up to 1,000× in certain scenarios. The accuracy achieved by this model underscores the significant potential of deep learning‐based approaches as reliable tools for aerodynamic design and optimization.

Effect of curvature on the hypersonic turbulent boundary over the curved compression ramp

Direct numerical simulation of the shock wave/turbulent boundary layer interaction on a compression ramp and curved compression ramps with different radii of the curvature at the Mach number Ma=5.0 and Reynolds number Re=16 800/mm is performed, and the purpose of the study is to investigate the impact of different radii of the curvature on the development of the flow. The flow structure and turbulence properties are analyzed. As the curved angle radius increases, the range of flow deceleration and the impact of the shock wave interaction on the turbulent boundary layer gradually decrease, and the peak value of turbulent pulsation amplification in the interaction zone becomes smaller. Mean skin friction decomposition is carried in upstream undisturbed region and reattachment region. The skin friction coefficient in the upstream is primarily composed of the viscous dissipation term Cf,V and the turbulent kinetic energy production term Cf,T. While in the reattachment zone, it is mainly balanced by the term Cf,T and the spatial growth term Cf,G. Bidimensional empirical mode decomposition is applied to further study the contribution of the turbulent motion at different scales to Cf,T, and the result shows that for the compression ramp, Cf,T is mainly contributed by the large-scale vortex structure generated in the interaction zone, while for the curved compression ramp, it is mainly contributed by the rapid amplification of turbulent pulsations caused by the shock wave interaction. This study is not only a new parametric study of the shock wave/turbulent boundary interaction but also provides a reference for the aerodynamic design of hypersonic vehicles.

An optimization procedure of shape and position of the aerodynamic device at the rear side of a semi-trailer truck model.

The paper outlines the development and optimization of an aerodynamic device for a semi-trailer truck model to reduce aerodynamic drag force. The optimization procedure involves the selection of a basic aerodynamic device shape, using airfoil profiles, and refining its shape and position through established optimization techniques like Full Factorial Design and Response Surface Method within the Design of Experiments framework. The test subject is a 1:10 scale model of the semi-trailer truck. To validate the results obtained from the Computational Fluid Dynamics (CFD) simulations, experimental measurements of aerodynamic drag forces were performed in a wind tunnel. This combination of simulation and experimental testing ensures the reliability and effectiveness of the optimization process for improving vehicle aerodynamics.

Enhancing aerodynamic efficiency: shape modification of airfoils

Small wind turbines (SWTs) are essential for harnessing renewable energy, particularly in developing regions where energy demands are significant. They provide a sustainable solution to meet the critical energy needs of these areas. However, the low Reynolds number (Re) airflow characteristics can pose challenges, making optimising airfoil shapes essential for enhancing aerodynamic performance and energy capture. This study offers a thorough analysis of six different airfoil profiles within a Re range of 50k to 500k. Modifications to the thickness-to-camber ratio (t/c) were strategically targeted to improve aerodynamic efficiency and structural viability. Using QBLADE software, we evaluated these design alterations to optimise the lift coefficient ( C L ), drag coefficient ( C D ), stall angle of attack ( α stall ) and lift-to-drag coefficient ratio (L/D). The analysis revealed significant improvements in the maximum power coefficient ( C p . max ), with the modified BW-3 airfoil achieving a C p . max of 0.441 at a Re of 500k – a remarkable 40.5% increase over baseline values. This consistent enhancement across various Re emphasises the essential impact of aerodynamic design in enhancing energy capture and reinforcing the feasibility of SWT applications across diverse operating conditions, along with material savings that lead to lighter wind turbine (WT) blades.

A novel strategy for mitigating the vortex-induced vibration of long-span bridges by using flexible membranes

The structural damping of a long-span bridge girder after completion is difficult to predict accurately in the design stage, and could be obviously lower than the value suggested by the code of wind-resistance design, which could lead to large-amplitude vortex-induced vibration (VIV) of the girder after completion. To address this problem, proposed here is a novel VIV mitigation strategy for a long-span bridge: in the design stage, aerodynamic design involving VIV of the girder is conducted based on the normal structural damping suggested by the design code, and flexible membranes (FMs) are designed for emergency VIV mitigation of the girder in case of very low structural damping after completion; if the girder experience large-amplitude VIV after completion because of very low structural damping, then the pre-designed FMs are used as a temporary emergency aerodynamic measure for fast VIV mitigation, providing a transition period until permanent measures (such as mechanical dampers, or aerodynamic measures) are implemented. To investigate the feasibility of this strategy, a case study was conducted involving a series of wind tunnel tests on a cable-stayed bridge with a Π-shaped girder, and the results indicate that appropriate FMs are effective for suppressing the VIV of the girder under very low structural damping. The FMs have great potential for emergency VIV mitigation because of the low cost, convenience, and rapidity.

Numerical Analysis on the Aerodynamic Characteristics of SUV Car Model Install with Vortex Generator

The investigation of automotive aerodynamics involves analysing several forces operating on a car while driving on the road, such as drag and lift forces. The flow separation at the vehicle's rear end is one of the primary causes of aerodynamic drag for automobile vehicles. It is feasible to improve fuel efficiency by lowering the drag force. The study focuses on the influence of a vortex generator (VG) on the aerodynamics of a sport utility vehicle (SUV) car. The study aims to simulate fluid flow analysis for an SUV car that uses VG and without VG, as well as to assess the impact of a different configuration of VG and a varying number and fillet radius of VG. The number of VG are 3, 5, and 9. The different fillet radius of VG are 5, 10, and 15 mm. Using the Reynold-Averaged Navier Stokes Equation (RANS) in the numerical simulation, the Reynolds number at the computational domain is 1.1391 × 107 and 1.4808 × 107, which is determined by the height of the model and the freestream velocity. The results show that aerodynamic characteristics are significantly influenced by the number of VG and various size radius fillets of VG. From the result, 9 number of VG and 5 mm fillet radius obtained the lowest value of coefficient of drag, Cd compared with the others which is Cd = 0.3747 for 27.78 m/s and Cd = 0.5031 for 33.33 m/s, respectively. Furthermore, the analysis of flow structures suggested the locations of vortex formation and wake turbulence at the rear of the vehicle. In contrast, the 9 number of VG with a 5 mm radius fillet of VG emerged as the most suitable VG for this scenario, exhibiting a Cd value closest to the base model and the lowest Cd value.

Aerodynamic-driven morphing aircraft and its aerodynamic design

Aerodynamic-driven morphing aircraft and its aerodynamic design

Aerodynamic design and analysis of a two-stage high pressure turbine with large flow coefficient

Aerodynamic design and analysis of a two-stage high pressure turbine with large flow coefficient

Aerodynamic-driven morphing aircraft and its overall design

Fixed-wing long-endurance aircraft play an important role in many fields. However, to reduce drag, these aircraft often have an enormous aspect ratio and wingspan, leading to challenges such as high requirements for takeoff and landing sites and poor wind resistance. Morphing may be able to solve this problem, but conventional morphing aircraft often employ complex actuation mechanisms and actuators to drive the morphing process. The associated costs in terms of structural weight increase and space occupancy are prohibitively high. First, this article develops a high-aspect-ratio aircraft with aerodynamic-driven morphing and validates the rationality and feasibility of this concept through flight tests. Then, focusing on the RQ-4 “Global Hawk” as the design baseline, the article explores multidisciplinary overall design methods for the aircraft, analyzing the comprehensive impact of morphing on aerodynamic, structural, and flight control design. Finally, the article elaborates on the benefits and costs associated with aerodynamic-driven morphing.

Optimizing Fuel Efficiency in Intercity Buses: Aerodynamic Design Enhancements and Implications for Sustainable Transportation in Bangladesh

Optimizing Fuel Efficiency in Intercity Buses: Aerodynamic Design Enhancements and Implications for Sustainable Transportation in Bangladesh

Deep learning-enhanced aerodynamics design of high-load compressor cascade at low Reynolds numbers

This study addresses the challenges of designing high-efficiency compressors for long-endurance, high-altitude unmanned aerial vehicles (UAVs) under low Reynolds number (Re) and high load conditions, exploring the aerodynamic performance limits of compressor blades under extreme conditions. The research integrates advanced numerical simulations, experimental methods, and deep learning technologies to minimize profile losses and deviation angle on compressor blades. An orthogonal experimental design systematically explored the impact of key geometric factors on aerodynamic performance. A deep learning model incorporating neural networks with spatial attention mechanisms was developed to significantly enhance the accuracy of aerodynamic predictions. This model adeptly captured the complex nonlinear interactions between aerodynamic and geometric parameters. Sobol sensitivity analysis revealed that the dimensionless maximum thickness is the most critical factor, accounting for 44 % of the total variance in total pressure loss and deviation angle. The position of maximum thickness and the aspect ratio of the elliptical leading edge also significantly influenced performance. The optimized high-load compressor blade profile was validated through experimental data and detailed computational fluid dynamics analysis using large eddy simulation methods. This analysis revealed flow separation and reattachment mechanisms, shedding light on turbulence and vortex dynamics critical to performance. This research deepens the theoretical understanding of compressor cascade fluid dynamics and provides practical insights for designing more efficient compressors, especially for micro axial compressors in high-altitude UAVs.

Assessment of turbulence adjoint method in sensitivity calculation and aerodynamic design optimization of turbomachinery cascades

Adjoint-based optimization faces the challenges from sensitivity accuracy when applying in design optimization of turbomachinery cascades with strong turbulence flow. In the study, sensitivities of aerodynamic parameters of different cascades are calculated using the discrete adjoint method, which are then used for design optimization of the cascades. The principles of adjoint method are firstly introduced and the procedures of sensitivity calculation using discrete adjoint method are described. Aerodynamic sensitivities of a high-pressure-turbine cascade and a controlled-diffusion compressor cascade are calculated by both the turbulence adjoint and constant-eddy-viscosity (CEV) adjoint methods. Through comparisons against the sensitivities by finite difference method, the improved accuracy in sensitivity calculation by turbulence adjoint method is demonstrated. Moreover, at the off-design condition of the compressor cascade with intensified turbulence flow, more improvements in sensitivity accuracy are gained. Finally, aerodynamic design optimizations of these two cascades are conducted. The results illustrate that more gains in performance improvements can be obtained by turbulence adjoint method, especially in the optimization of compressor cascade at the off-design condition. The impacts of aerodynamic shape optimization on performance variations of the cascades are addressed.

Study on Aerodynamic Performance of Propeller with Tip Winglet

Based on the Reynolds-averaged Navier-Stokes governing equations and the unstructured grid rotating/stationary sliding surface technology, this paper studies the aerodynamic layout and efficiency enhancement mechanism of the near-space propeller blade tip winglet configuration. First, the feasibility of the configuration is verified by comparing and analyzing different lift propeller layout schemes. Secondly, the aerodynamic layout design of the blade tip winglet propeller is studied by changing the winglet inclination angle and length parameter indicators. Finally, the ANSYS simulation analysis is used to calculate the influence of the winglet design on the propeller velocity vector distribution, blade pressure and propeller aerodynamic efficiency, and the performance influence law of the basic parameters is preliminarily established, and the overall design scheme of the new blade tip winglet propeller design is completed. The study shows that the blade tip winglet propeller layout is a reasonable and feasible technical approach to improve the aerodynamic efficiency in the near-space working environment, and it has a certain reference role in the development of new configuration propeller aircraft.

Aerodynamic optimization of aircraft wings using machine learning

This study proposes a fast yet reliable optimization framework for the aerodynamic design of transonic aircraft wings. Combining Computational Fluid Dynamics (CFD) and Machine Learning (ML), the framework is successfully applied to the Common Research Model (CRM) benchmark aircraft proposed by NASA. The framework relies on a series of automated CFD simulations, from which no less than 160 planform variations of the CRM wing are assessed from an aerodynamic standpoint. This database is used to educate an ML surrogate model, for which two specific algorithms are explored, namely eXtreme Gradient Boosting (XGB) and Light Gradient Boosting Machine (LGBM). Once trained with 80 % of this database and tested with the remaining 20 %, the ML surrogates are employed to explore a larger design space, their optimum being then inferred using an optimization framework relying on a Multi-Objective Genetic Algorithm (MOGAO). Each ML-based optimal planform is then simulated through CFD to confirm its aerodynamic merits, which are then compared against those of a conventional, fully CFD-based optimization. The comparison is very favourable, the best ML-based optimal planform exhibiting similar performances as its CFD-optimized counterpart (e.g. a 14 % higher lift-to-drag ratio) for only half of the CPU cost. Overall, this study demonstrates the potential of ML-based methods for optimizing aircraft wings, thereby paving the way to the adoption of more disruptive, data-driven aircraft design paradigms.

Aerodynamics-guided machine learning for design optimization of electric vehicles

The transition to electric vehicles is driving a fundamental shift in the automobile design process. Changes in constraints afforded by the absence of a combustion engine create new opportunities for modifying vehicle geometries. Current approaches to optimizing vehicle aerodynamics require a vast amount of computational studies and physical experiments, which are expensive when performing parameter sweeps over conceivable geometric configurations, suggesting the need for more efficient surrogate models to assist analysis. Here we analyze a dataset of industry-quality automobile geometries with their associated aerodynamic performance obtained from experimentally validated, high-fidelity large-eddy simulations. We show that a relationship between these geometries and their respective aerodynamics can be extracted in a low-dimensional manner by leveraging a nonlinear autoencoder which is simultaneously trained to estimate the drag coefficient from the latent variables. We perform aerodynamic design optimization of vehicle designs by making use of the learned aerodynamic relationship in the low-order space obtained by the model. We demonstrate that the aerodynamic trends for the geometries produced from the optimization process show agreement with validation simulations. The findings of this work demonstrate the application of data-driven approaches to the analysis and design of vehicles in a production environment.