This study investigates abnormal oscillations of high-speed pantographs in tunnels using the Improved Delayed Detached Eddy Simulation (IDDES) method and overset grid technology, analyzing aerodynamic forces, flow patterns, and spectral characteristics under different train speeds and tunnel cross-sectional areas. The results show that the aerodynamic behaviour of the pantograph can be divided into three stages: open air, transition section and tunnel. In tunnels, the time-averaged value and fluctuation intensity of the aerodynamic force coefficient are higher than in open air, with the disparity increasing as train speed and tunnel blockage ratio rise. In the transition section, the train and pantograph entering the tunnel generate pressure waves, which lead to significant fluctuations in the aerodynamic force of the pantograph. The dominant frequency of the aerodynamic force varies depending on the train speed, tunnel cross-sectional area, and track type. Different from the dominant frequency of 134 Hz observed in the open air, the power spectral density of aerodynamic drag and lift in the tunnel presents multiple harmonic peaks. The fundamental frequency shows a positive correlation with both train speed and tunnel blockage ratio, increasing as train speed rises and tunnel cross-sectional area decreases. The coupling of complex vortices will increase the instability of the flow field, affect the dynamic response of the pantograph, and may induce oscillation.

The object of the study is an autonomous high-altitude airship platform. This type of high-altitude platform is designed for long-term telecommunication retransmission at altitudes of 18–25 km. The main problem lies in the insufficient stability of flight at the height of the stratosphere and the limited energy capabilities of aircraft. An integrated intelligent control system and energy management have been developed to solve the problems. This architecture in portable form includes a sensor module, an STM32 microcontroller, a LoRa telemetry channel, a mathematical model of dynamics taking into account lift, aerodynamic drag, external factors and atmospheric parameters, and most importantly, a hybrid adaptive PID-fuzzy controller was proposed. Additionally, a model of the energy balance was proposed, which directly interacts with solar panels, energy consumption of drives and battery operation. The simulation data obtained shows that the use of the PID-fuzzy controller provides a significant increase in the stability of the platform. The transition time is reduced by 44.4%, the maximum deviation from the set altitude and flight path is reduced by 56.5%, and the average drive consumption is reduced by 20–22%. The energy balance model demonstrates that the developed system is capable of retaining up to 46% of the battery charge after 24 hours of battery life, which is 18% higher compared to a system without adaptive energy management. The practical significance of the project lies in the possibility of using the developed system as part of autonomous telecommunications networks, balloons, an emergency communication system, remote sensing of the earth, as well as in elements of promising 6G and NTN networks.

With the rapid development of the automotive industry and the increasing demand for environmental protection, automotive aerodynamics optimization has become a key approach to enhancing vehicle performance and reducing energy consumption. Based on the Computational Fluid Dynamics (CFD) method, this paper explores the relationship between the shape factors of automobiles and their fluid dynamics characteristics, with a focus on analyzing the influence of key factors such as the front styling, chassis structure, and rear wing design on aerodynamic drag and flow characteristics. Research shows that through the optimization of the front styling flow diversion, the flattening design of the chassis and the application of the adjustable rear wing system, the flow field distribution around the vehicle can be significantly improved and the aerodynamic drag coefficient can be reduced. This paper systematically constructs a research framework from local optimization to overall aerodynamic performance improvement. The research results can provide theoretical basis and practical reference for automotive styling design and aerodynamic performance optimization.

Introduction. One of the most effective technologies for removing dispersed impurities from gas is liquid purification, because inertial separators cannot capture fine particles. The challenge arises of increasing the efficiency of gas-dispersed media purification using this method. One way to solve this challenge is determining the injection angle of the droplet fractions at which the coagulation process will be most effective. Aim of the Study. The aim of the academic work was to study the effect of the injection direction of the droplet fraction jet on the intensity of the absorption of solid particles by liquid droplets. Materials and Methods. To describe the flow of a multiphase medium, there was used a continual approach for modeling the dynamics of inhomogeneous media, which involves solving a complete hydrodynamic system of motion equations for each mixture components. The dispersed phase was modeled as a multifractional polydisperse one; the dispersed phase fractions may differ in both the material density and the size of dispersed particles. There were taken into account interphase heat exchange and momentum exchange including the aerodynamic drag force, the dynamic Archimedes force, and the added mass force. The dynamics of the carrier medium was described by the Navier–Stokes system of equations for a viscous, compressible heat-conducting gas. The mathematical model also took into account the collisional coagulation of particles of different fractions. The system of the mathematical model equations was supplemented with boundary conditions. An explicit finite-difference method was used to integrate the equations of the mathematical model. A nonlinear correction scheme was used to overcome numerical oscillations. Results. There was simulated the injection of droplet fractions into a dust-laden flow at various angles to the channel wall. It has been found that the most intense decrease in the average density of the dust fraction is observed for an angle of φ = π/2. For gas-droplet flow injection angles of φ and π–φ, the distributions of the volumetric contents of the dust fraction are similar. The calculations have shown that for a wide range of droplet fraction sizes the highest velocity slip is observed for droplet injection perpendicular to the direction of dust-laden flow. Discussion and Conclusion. The identified patterns allow us to determine the injection direction of droplet fractions that maximizes the absorption of solid particles. The results can be used to optimize liquid purification technologies for gas-dispersed media. In the future, these results can be used to improve the efficiency of gas-liquid filters.

Predicting lift and drag in hydro turbine design is important to optimize its performance. However, it poses significant challenges due to the complexity of fluid dynamics, which is traditionally addressed by Reynolds-Averaged Navier–Stokes equations, which is time-consuming. Moreover, these methods are computationally demanding, making them a costly approach and less efficient for complex turbine designs. Recent advancements in machine learning (ML) offer a promising alternative with reduced computational costs while maintaining accuracy. This paper explores the use of a data-driven ML model for predicting aerodynamic performance, specifically lift and drag, in hydro turbine design. The models were developed from experimental hydro turbine data gathered from various blade designs and flow conditions. CatBoost yielded the highest predictive accuracy among all the models tested. The findings indicate that CatBoost achieved the best predicted accuracy, followed by LGBM, demonstrating the efficacy of machine learning methodologies in modeling hydrodynamic forces in turbine design.

The pursuit of optimal vehicle dynamics necessitates the real-time balancing of ride comfort, handling stability, and aerodynamic efficiency. Traditional suspension control systems often rely on pre-tuned, static models that fail to adapt to dynamic road conditions and changing aerodynamic loads (e.g., due to vehicle speed, crosswinds, or load distribution). This paper proposes a novel framework utilizing a Digital Twin (DT) integrated with an Adaptive Neural Network (ANN) controller for real-time aero-dynamic ride optimization. The DT, a high-fidelity virtual replica of the physical vehicle, incorporates real-time sensor data (accelerometers, LiDAR/Vision for road profile, vehicle speed, and active aerodynamic surfaces). The ANN is trained on this DT data to predict optimal semi-active/active suspension damping and spring rate adjustments that instantaneously counteract changes in aerodynamic downforce and drag. This approach is expected to significantly enhance ride quality and stability over varying speeds and conditions while simultaneously minimizing aerodynamic performance penalties, outperforming traditional Skyhook and linear control strategies.

Drag force is very important for high-speed rail’ s energy efficiency and operating speed. This study compares bullet-nosed and canted-nosed train designs through meta-analysis of existing experimental data and verifies the validity of the possible explanations through existing simulations. The result shows that the bullet-nose train can reduce 29.2% of drag force in 41.66 m/s and 35.6% in 79.1667 m/s, which primarily because of a better pressure management and the reduction of flow separation. Although it is superior in aerodynamics, the durability of the canted-nose design reflects necessary compromises on crosswise stability and space requirements. These findings provide a quantitative guidance for the superiority of bullet-nose in reducing drag force compares to canted-nose. Moreover, this paper analyzes the cause and the physical principle behind the phenomenon by dividing the composition of drag force. Also, this study reveals the balancing between aerodynamic performance with other critical design considerations in current and future train development.

This study investigates the aerodynamic characteristics of drafting cyclists during 45° cornering through numerical simulations, and under the conditions of a vehicle speed of 15 m/s and a 45° body inclination, the SST k-ω turbulence model and grid independence verification (final grid count:12 million) are used to systematically analyze the distribution of velocity, vortex, pressure, and wall shear stress fields. The effects of riding velocity (5–25 m/s) and inter-rider spacing (100–500 mm) on aerodynamic drag were analyzed to reveal the underlying flow mechanisms. The results indicate that as velocity increases, airflow acceleration and boundary-layer shear intensify, leading to enhanced vortex shedding and elevated wall shear stress. In contrast, reduced spacing significantly strengthens wake coupling between riders, effectively lowering the frontal pressure and skin-friction drag of trailing cyclists. The drag reduction rate decreases monotonically with increasing spacing, with the second rider consistently achieving higher aerodynamic benefits than the third rider. Distinct from previous studies that predominantly focus on straight-line motion, this work fills a critical knowledge gap in sports aerodynamics and competitive cycling strategy. By elucidating the unique wake coupling mechanisms induced by body inclination, this study provides scientific evidence for optimizing drafting tactics specifically during high-speed technical cornering.

This paper addresses the improvement of energy efficiency in intermodal freight trains by reducing aerodynamic drag through optimisation of container arrangement on railcars. In current terminal practice, loading plans are usually driven by local criteria such as minimising crane operating time or travel distance, which may result in non-compact cargo configurations and increased aerodynamic losses during train movement. A mathematical model of aerodynamic drag is formulated using position-dependent drag coefficients and a gap-penalty function that reflects the length and location of empty slots in the train consist. The loading problem is modelled as a constrained assignment task with the primary objective of minimising crane working time. Three approaches to generating the initial loading plan are analysed: a slot-priority heuristic, a greedy algorithm, and an ant colony optimisation algorithm. On this basis, a dedicated post-processing algorithm is applied, which iteratively relocates containers towards the front of the train, reduces gaps between units, and preserves all technical and operational constraints. The method is implemented by linking a FlexSim simulation model of an inland intermodal terminal with Python-based optimisation procedures. Nine scenarios with different shares of containers from the road zone and storage yard are evaluated using 16 replications each. The results show that the proposed procedure can reduce estimated aerodynamic drag by approximately 5–9%, at the cost of increased crane operating time. An energy balance comparison indicates that the additional terminal energy consumption is significantly lower than the traction energy savings, confirming that aerodynamic criteria should be explicitly incorporated into train loading strategies.

Study objective. Assessment of the stability of freight train cars in mountainous and transshipment areas under the influence of crosswinds using modern computer modeling methods. Task. Determination of the values of aerodynamic forces and drag coefficients acting on train cars in various wind directions ranging from 0 to 180 degrees, and assessment of the effect of these forces on the margin of stability against tipping, especially in difficult mountainous conditions. Research methods. In Solidworks Flow Simulation software package, an aerodynamic calculation was performed using computer simulation method. Detailed 3D computer models of cars (tank cars, gondola cars, covered cars) have been developed, taking into account their structural elements and geometric dimensions. The obtained aerodynamic results are used in specialized software for calculating the safety margin coefficients of each carriage. The novelty of the work. Quantitative patterns of distributing aerodynamic forces along the length of the train, depending on the angle of the wind flow, are found out. The dependence of the coefficient of aero-dynamic drag on the position of the car in the train (depending on the type of car and the wind direction by more than 2 times) is determined. The effect of accelerating the air flow in the surface layer in mountainous terrain and its effect on the stability of the train is studied. Study results. During the study, the greatest transverse force of the air flow acting on the wind at normal wind direction (900) is determined. In mountainous conditions, the wind speed at the surface can increase by 3 times, creating critical loads. Conclusions. Reducing the speed of the train makes it possible to increase the stability margin to standard values, and the data obtained can be used to optimize train operating modes in difficult weather conditions.

Passenger cars, sports utility vehicles (SUVs), and light trucks/vans, constituting the overwhelming majority of all road vehicles globally, burn about 25% of all fossil fuels, emit significant amounts of greenhouse gas emissions (CO2), and deteriorate the environment. Nearly three-quarters of the engine power generated by burning fossil fuels is required to overcome aerodynamic resistance (drag) at highway driving speeds. Streamlining the body shape, especially the projected frontal area, can lead to a decrease in aerodynamic drag. Even though drag coefficients have plateaued since the late 1990s, further altering body shape might worsen vehicle cooling. Thus, the primary objective of this study is to explore the potential for aerodynamic drag reduction and improved cooling performance through careful component design unaffected by stylistic restraints. A variety of strategies for protecting the cooling intakes to reduce the drag coefficient are considered. The potential cooling drag reduction was found to be around 7% without compromising the cooling performance, which is in line with predictions for roughly 2.9% and 1.7% fuel consumption reductions for highway and city driving conditions, respectively. The study also reveals that passenger electric cars designed for city driving conditions possess a battery-to-kerb weight ratio of around one-quarter of the kerb weight, and vehicles designed for higher ranges have significantly higher ratios (nearly one-third), resulting in higher rolling resistance and energy consumption. The reduction of battery weight for EVs, streamlining vehicle shapes, and applying active and passive airflow management can help reduce aerodynamic drag and rolling resistance further, enhance driving range, and reduce energy consumption and greenhouse gas emissions.

Abstract The Vertical Take-Off and Landing (VTOL) aircraft exhibit complex and rapidly varying dynamics during the transition flight phase, which poses significant challenges for accurate modeling and aerodynamic parameter estimation. This paper presents a parameter estimation framework to identify unknown aerodynamic coefficients governing the transition flight, leveraging experimental flight data of a tilt-rotor VTOL UAV in outdoor experiments. The VTOL UAV has a hybrid configuration with two tilting rotors, two static rotors, and fixed wings. A nonlinear dynamic model describing the longitudinal motion is developed and reformulated into a regression structure suitable for parameter estimation. A projection-based constrained Recursive Least Squares (RLS) algorithm is then applied to estimate critical aerodynamic parameters, including lift, drag, and thrust coefficients, under physical constraints. The convergence and accuracy of estimation algorithm for time-varying coefficients is firstly verified by simulation. The parameter estimation is further validated by six experimental flight tests with different tilting rates of 12 deg/s and 14 deg/s. Experimental results demonstrate the accurate estimation by accurate predictions of the aircraft states υx, υz, ωy with RMSEs of 0.7230 m/s, 0.0990 m/s, and 0.0508 rad/s, respectively.

The reduction of the aerodynamic drag, a fundamental factor for the optimization of the performance of modern vehicles, is also because it has clear values of influence on power consumption, dynamic stability, and driving autonomy, particularly for electric vehicles. This paper, being a work of review, provides a state-of-the-art of the main principles and methods of air resistance reduction and focuses on the application of CFD to the analysis and optimization of the flow around the vehicle body. This research focuses on the fundamentals of pneumatic traction, design, and technology to mitigate pneumatic traction (i.e., spoilers, baseboards, active ventilation) as well as a literature review on the most noteworthy previous studies that applied CFD to analyze and improve pneumatic behaviour of conventional and electric vehicles. It also talks about drag coefficient and energy efficiency correlation, and the potential of applying artificial intelligence and generative design in the process of creating more efficient and sustainable results. The obtained results prove that the application of CFD tools to the preliminary design definition of the vehicle can widely improve the performance of the system, thanks to the reduction of the drag coefficient. The paper emphasizes the necessity for combining numerical simulations and laboratory work, and promotes the utilization of advanced analysis tools to enhance sustainable and efficient energy transfer in the vehicular environment.

Air resistance modulates horizontal ground reaction forces during treadmill running.

Operating satellites in the very-low-Earth-orbit (VLEO) region has a number of advantages. However, a primary challenge to the sustained operation of VLEO satellites is the significant atmospheric drag resulting from the higher ambient density, which leads to rapid orbital decay and eventual reentry. Therefore, reducing aerodynamic drag is essential for extending the operational lifetime of VLEO satellites. At the same time, it is important to consider the internal volume to ensure that the satellite maintains its functional capabilities. This work presents a shape optimization framework for VLEO satellites aimed at minimizing the aerodynamic drag without compromising the internal volume. The optimization is performed using a genetic algorithm, with drag force calculated via the panel method and validated by the direct simulation Monte Carlo simulations. Under a fixed-volume constraint, the optimal satellite geometry achieves a maximum drag reduction of 60.3% compared to the reference satellite. Furthermore, this study employs multi-objective optimization to simultaneously minimize aerodynamic drag and maximize internal volume. The results demonstrate that the notable improvements in both drag and volume can be simultaneously achieved through shape optimization. Compared to the reference satellite, the optimal satellite geometry offers a drag reduction of 53.9% and a volume increase of 7.6%.

Abstract The integration of aerodynamic drag is a fundamental step in simulating dust dynamics in hydrodynamical simulations. We propose a novel integration scheme, designed to be compatible with Strang splitting techniques, which allows for the straightforward integration of external forces and hydrodynamic fluxes in general-purpose hydrodynamic simulation codes. Moreover, this solver leverages an analytical solution to the problem of drag acceleration, ensuring linear complexity even in cases with multiple dust grain sizes, as opposed to the cubic scaling of methods that require a matrix inversion step. This new general implicit Runge–Kutta (GIRK) integrator is evaluated using standard benchmarks for dust dynamics such as DUSTYBOX, DUSTYWAVE, and DUSTYSHOCK. The results demonstrate not only the accuracy of the method but also the expected scalings in terms of accuracy, convergence to equilibrium, and execution time. GIRK can be easily implemented in hydrodynamical simulations alongside hydrodynamical steps and external forces and is especially useful in simulations with a large number of dust grain sizes.

CFD-neural network collaborative optimization drives aerodynamic drag reduction of container ship fairings

Abstract Flow past circular cylinders is a classical fluid dynamics problem with wide-ranging engineering applications. This review critically examines passive surface modification techniques aimed at reducing drag and mitigating vortex-induced vibrations (VIV). Following the PRISMA 2020 methodology, 29 peer-reviewed studies published between 2005 and 2025 were analyzed, focusing on surface geometries such as grooves, dimples, riblets, and hybrid textures. These modifications alter boundary-layer development, delay separation, and modify vortex shedding, achieving drag reductions of 10–40% depending on geometry and Reynolds number. Grooves, particularly helical and longitudinal types, were the most frequently studied and demonstrated consistent suppression of wake instabilities, while dimples showed favorable results through boundary-layer reattachment and pressure redistribution. Despite progress, research remains dominated by computational fluid dynamics (CFD), with limited experimental validation and few investigations at high Reynolds numbers. Additional challenges include scalability, durability, and performance consistency under real-world conditions. Future research should prioritize experimental validation, high-Re studies, and optimization of hybrid or adaptive surfaces to enhance robustness and applicability. Overall, passive surface modifications present an energy-efficient strategy for aerodynamic drag reduction in bluff body flows. From an engineering perspective, even modest drag reductions can yield substantial energy savings, improve structural durability, and enhance operational efficiency.

Research on the influence of splitter plates on the aerodynamic drag reduction and energy-saving performance of express boxcars

Abstract Modern wireless communication systems include phased array antennas as essential components. Cylindrical Dielectric Resonator Antenna (CDRA) arrays on planar ground planes are widely explored. Conformal arrays have several advantages over flat arrays, including reduced aerodynamic drag, and wider coverage angles. Therefore, a conformal phased array CDRA is proposed in this paper. For efficient radiation, a CDRA fed by a rectangular slot aperture coupled feed excites the HEM 11δ mode. For obtaining a higher directive gain, a 1 × 4 CDRA array is designed. 5 dBi improvement in gain is obtained by a 1 × 4 CDRA array. A cylindrically conformal phased array, placed on a 360 mm radius cylindrical surface, is presented for wide beam scanning. The impedance bandwidth obtained for the proposed conformal CDRA array is 22% which ranges from 7.6 to 9.5 GHz. The proposed array can scan from −25° to +25° with a gain fluctuation of less than 4 dBi. Within the impedance bandwidth, the isolation between neighboring elements is less than −25 dB. The peak gain of the conformal CDRA array is 10.2 dBi at a frequency of 8.7 GHz. The efficiency of the antenna is more than 91% for the whole band. Additionally, with a height of 0.08 λ 0 , the 1 × 4 CDRA array has a low profile which offer significant benefits in advanced packaging. The study that is being proposed finds applications for conformal platforms in high-speed vehicles, missiles, and aircraft.