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The purpose of this study is investigate the transient aerodynamic characteristics of high-speed vehicle with body roll motion under crosswind condition to improve aerodynamic stability.

An overset mesh was used to simulate the rolling motion of the vehicle body. A wind tunnel experiment was conducted to validate the numerical method.

The results revealed that the vehicle’s aerodynamic characteristics changed periodically with the body’s periodic motion. In the absence of crosswind, the pressure distribution on the left and right sides of the vehicle body was symmetrical, and the speed streamline flowed to the rear of the vehicle in an orderly manner. The maximum aerodynamic lift observed in the transient simulation was −0.089, which is approximately 0.70 times that of the quasi-static simulation experiment. In addition, the maximum aerodynamic side force observed in the transient simulation was 0.654, which is approximately 1.25 times that of the quasi-static simulation experiment.

The aerodynamic load varies periodically with the vehicle body’s cyclic motion. However, the extreme values of the aerodynamic load do not occur when the vehicle body is at its highest or lowest position. This phenomenon is primarily attributed to the mutual interference of airflow viscosity and the hysteresis effect in the flow field, leading to the formation of a substantial vortex near the wheel. Consequently, the aerodynamic coefficient at each horizontal position becomes inconsistent during the periodic rolling of the vehicle body.

The purpose of this study is to propose a precise and standardized strategy for numerically simulating vehicle aerodynamics.

Error sources in computational fluid dynamics were analyzed. Additionally, controllable experiential and discretization errors, which significantly influence the calculated results, are expounded upon. Considering the airflow mechanism around a vehicle, the computational efficiency and accuracy of each solution strategy were compared and analyzed through numerous computational cases. Finally, the most suitable numerical strategy, including the turbulence model, simplified vehicle model, calculation domain, boundary conditions, grids and discretization scheme, was identified. Two simplified vehicle models were introduced, and relevant wind tunnel tests were performed to validate the selected strategy.

Errors in vehicle computational aerodynamics mainly stem from the unreasonable simplification of the vehicle model, calculation domain, definite solution conditions, grid strategy and discretization schemes. Using the proposed standardized numerical strategy, the simulated steady and transient aerodynamic characteristics agreed well with the experimental results.

Building upon the modified Low-Reynolds Number k-e model and Scale Adaptive Simulation model, to the best of the authors’ knowledge, a precise and standardized numerical simulation strategy for vehicle aerodynamics is proposed for the first time, which can be integrated into vehicle research and design.

The purpose of this paper is to study the aerodynamic characteristics of Ahmed body in longitudinal and lateral platoons under crosswind by computational fluid dynamics simulation. It helps to improve the aerodynamic characteristics of vehicles by providing theoretical basis and engineering direction for the development and progress of intelligent transportation.

A two-car platoon model is used to compare with the experiment to prove the accuracy of the simulation method. The simplified Ahmed body model and the Reynolds Averaged N-S equation method are used to study the aerodynamic characteristics of vehicles at different distances under cross-winds.

When the longitudinal distance x/L = 0.25, the drag coefficients of the middle and trailing cars at β = 30° are improved by about 272% and 160% compared with β = 10°. The side force coefficients of the middle and trailing cars are increased by 50% and 62%. When the lateral distance y/W = 0.25, the side force coefficients of left and middle cars at β = 30° are reduced by 38% and 37.5% compared with β = 10°. However, the side force coefficient of the right car are increased by about 84.3%.

Most of the researches focus on the overtaking process, and there are few researches on the neat lateral platoon. The innovation of this paper is that in addition to studying the aerodynamic characteristics of longitudinal driving, the aerodynamic characteristics of neat lateral driving are also studied, and crosswind conditions are added. The authors hope to contribute to the development of intelligent transportation.

This study aims to achieve optimum flow separation control for a road vehicle using a reverse flow fan on rear side.

A full-length reverse flow fan array (fan’s air speed is 50% of the car’s speed) is attached throughout the width of the vehicle at rear edge corner.

The reverse flow fan array positioned at rear edge of car pushes the airflow against the car’s rear window. It creates the recirculation region and alters the pressure distribution. This reduces the lift coefficient by 150%, which becomes the downforce and reduces the drag coefficient by 22%. As the car speed increases, fan speed should also be increased for effective flow control.

This active flow control method for 3D Ahmed car body has been studied computationally at low speed (40 m/s).

This design increases the downforce, thus gives better cornering speed and stability, and decreases the drag which improves fuel efficiency. It can be used for effective flow control of cars (hatchback/sedan). The findings can be applied to the bluff bodies, road vehicles, UAV and helicopter fuselage for flow separation control.

The fan array is attached on car’s rear side, which blows air against the car’s rear window. It alters the pressure distribution and aerodynamics forces favorably. But the existing high-speed fan used in a sports cars sucks the air from bottom and pushes it rearward, which increases both the traction force and drag.

The purpose of this paper is to investigate the optimal average drag coefficient of the Ahmed body for mixed platoon driving under crosswind and no crosswind conditions using the response surface optimization method. This study has extraordinary implications for the planning of future intelligent transportation.

First, the single vehicle and vehicle platoon models are validated. Second, the configuration with the lowest average drag coefficient under the two conditions is obtained by response surface optimization. At the same time, the aerodynamic characteristics of the mixed platoon driving under different conditions are also analyzed.

The configuration with the lowest average drag coefficient under no crosswind conditions is 0.3 L for longitudinal spacing and 0.8 W for lateral spacing, with an average drag coefficient of 0.1931. The configuration with the lowest average drag coefficient under crosswind conditions is 10° for yaw angle, 0.25 L for longitudinal spacing, and 0.8 W for lateral spacing, with an average drag coefficient of 0.2251. Compared to the single vehicle, the average drag coefficients for the two conditions are reduced by 25.1% and 41.3%, respectively.

This paper investigates the lowest average drag coefficient for mixed platoon driving under no crosswind and crosswind conditions using a response surface optimization method. The computational fluid dynamics (CFD) results of single vehicle and vehicle platoon are compared and verified with the experimental results to ensure the reliability of this study. The research results provide theoretical reference and guidance for the planning of intelligent transportation.

An experimental investigation of hemispherical forebody interaction effects on the drag coefficient of a D-shaped model is carried out for three-dimensional flow in the subcritical range of Reynolds number 1 × 10⁵ ≤ Re ≤ 1.8 × 10⁵. To study the interaction effect, hemispherical shapes of various sizes are attached to the upriver of the D-shaped bluff body model. The diameter of the hemisphere (b₁) varied from 0.25 to 0.75 times the diameter of the D-shaped model (b₂) and its gap from the D-shaped model (g/b₂) ranged from 0.25 to 1.75 b₂.

The experiments were carried out in a low-speed open-circuit closed jet wind tunnel with test section dimensions of 1.2 × 0.9 × 1.8 m (W × H × L) capable of generating maximum velocity up to 45 m/s. The wind tunnel is equipped with a driving unit which has a 175-hp motor with three propellers controlled by a 160-kW inverter drive. Drag force is measured with an internal six-component balance with the help of the Spider 3013 E-pro data acquisition system.

The wind tunnel results show that the hemispherical forebody has a diameter ratio of 0.75 with a gap ratio of 0.25, resulting in a maximum drag reduction of 67%.

The turbulence intensity of the wind tunnel is about 5.6% at a velocity of 18 m/s. The uncertainty in the velocity and the drag coefficient measurement are about ±1.5 and ±2.83 %, respectively. The maximum error in the geometric model is about ±1.33 %.

The results from the research work are helpful in choosing the optimum spacing of road vehicles, especially truck–trailer and launch vehicle applications.

Drag reduction of road vehicle resulting less fuel consumption as well as less pollution to the environment. For instance, tractor trailer experiencing approximately 45% of aerodynamics drag is due to front part of the vehicle. The other contributors are 30% due to trailer base and 25% is due to under body flow. Nearly 65% of energy was spent to overcome the aerodynamic drag, when the vehicle is traveling at the average of 70 kmph (Seifert 2008 and Doyle 2008).

The benefits of placing the forebody in front of the main body will have a strong influence on reducing fuel consumption.

This paper aims to investigate the effect of different wing height layouts on the aerodynamic performance and flow structure of high-speed train, in a train-wing coupling method with multiple tandem wings installed on the train roof.

The improved delayed detached eddy simulation method based on shear stress transport k- ω turbulence model has been used to conduct computational fluid dynamics simulation on the train with three different wing height layouts, at a Reynolds number of 2.8 × 10⁶. The accuracy of the numerical method has been validated by wind tunnel experiments.

The wing height layout has a significant effect on the lift, while its influence on the drag is weak. There are three distinctive vortex structures in the flow field: wingtip vortex, train body vortex and pillar vortex, which are influenced by the variation in wing height layout. The incremental wing layout reduces the mixing and merging between vortexes in the flow field, weakening the vorticity and turbulence intensity. This enhances the pressure difference between the upper and lower surfaces of both the train and wings, thereby increasing the overall lift. Simultaneously, it reduces the slipstream velocity at platform and trackside heights.

This paper contributes to understanding the aerodynamic characteristics and flow structure of a high-speed train coupled with wings. It provides a reference for the design aiming to achieve equivalent weight reduction through aerodynamic lift synergy in trains.

Bionic flapping-wing aerial vehicles (FWAVs) mimic natural flyers to generate the lift and thrust, such as birds, bats and insects. As an important component of the FWAVs, the flapping wings are crucial for the flight performance. The aim of this paper is to study the effects of different wings on aerodynamic performance.

Inspired by the wings structure of birds, the authors design four cambered wings to analyze the effect of airfoils on the FWAVs aerodynamic performance. The authors design the motor-driven mechanism of flapping wings, and realize the control of flapping frequency. Combined with the wind tunnel equipment, the authors build the FWAVs force test platform to test the static and dynamic aerodynamic performance of different flapping wings under the state variables of flapping frequency, wind speed and inclined angle.

The results show that the aerodynamic performance of flapping wing with a camber of 20 mm is the best. Compared with flat wing, the average lift can be improved by 59.5%.

Different from the traditional flat wing design of FWAVs, different cambered flapping wings are given in this paper. The influence of airfoils on aerodynamic performance of FWAVs is analyzed and the optimal flapping wing is obtained.

The purpose of this paper is to improve autonomous flight performance of a fixed-wing unmanned aerial vehicle (UAV) via simultaneous morphing wingtip and control system design conducted with optimization, computational fluid dynamics (CFD) and machine learning approaches.

The main wing of the UAV is redesigned with morphing wingtips capable of dihedral angle alteration by means of folding. Aircraft dynamic model is derived as equations depending only on wingtip dihedral angle via Nonlinear Least Squares regression machine learning algorithm. Data for the regression analyses are obtained by numerical (i.e. CFD) and analytical approaches. Simultaneous perturbation stochastic approximation (SPSA) is incorporated into the design process to determine the optimal wingtip dihedral angle and proportional-integral-derivative (PID) coefficients of the control system that maximizes autonomous flight performance. The performance is defined in terms of trajectory tracking quality parameters of rise time, settling time and overshoot. Obtained optimal design parameters are applied in flight simulations to test both longitudinal and lateral reference trajectory tracking.

Longitudinal and lateral autonomous flight performances of the UAV are improved by redesigning the main wing with morphing wingtips and simultaneous estimation of PID coefficients and wingtip dihedral angle with SPSA optimization.

This paper originally discusses the simultaneous design of innovative morphing wingtip and UAV flight control system for autonomous flight performance improvement. The proposed simultaneous design idea is conducted with the SPSA optimization and a machine learning algorithm as a novel approach.

This paper aims to propose a structural sizing approach of an unmanned aerial vehicle (UAV) wing that takes into account the aeroelasticity effects through a fluid–structure interaction analysis.

The sizing approach proposed in this study is an iterative process, each iteration of which consists of two sub-loops, a multidisciplinary analysis (MDA) loop followed by a structural optimization loop. The MDA loop seeks the aeroelastic equilibrium between aerodynamic forces and structural displacements using a fixed-point iteration scheme. Once the equilibrium is reached, the converged pressure loads are used for the structural optimization, which aims to find the structural thicknesses that minimize the wing weight under failure criteria. The two sub-loops are run sequentially in an iterative process until the mass is converged. The analysis models are implemented in open-source software, namely, PANUKL for aerodynamics and MYSTRAN for structures, while the whole process is automated with Python and integrated in the open-source optimization framework OpenMDAO.

The approach was applied to the design of the Predator MQ-1 wing. The results of the MDAs show the convergence of the wing deformations to the flight shape after few iterations. At the end of the aeroelastic sizing loop, the result is a structurally sized wing with minimal weight considering the aeroelasticity effects.

The approach proposed takes into account the wing aero-structural coupling effects while sizing its structure instead of a fixed load distribution. In addition, the approach is fully based on open-source codes, which are freely available for public use and can be fully reproducible.