Browse Topic: Aerodynamics
High-speed wet clutches may experience dynamic instability between the friction plates, leading to rattling vibrations and a significant increase in drag torque. This study employs a homogeneous flow model to characterize the gas-liquid two-phase flow within a high-speed clutch. It establishes a dynamic model for the angular oscillation of friction plates. Finite-element numerical simulations and stability analyses were conducted. The results indicate that as the clutch speed difference increases, the density and viscosity of the two-phase flow decrease rapidly, leading to a sharp reduction in fluid stiffness and damping. Consequently, the friction plates become more susceptible to angular oscillation. The stability of angular oscillation is determined by two key parameters: dimensionless comprehensive stiffness and critical frequency ratio. Higher dimensionless comprehensive stiffness and a lower critical frequency ratio enhance oscillation stability. Numerical evaluations of various groove types reveal that as rotational speed and friction plate clearance increase, the fluid stiffness coefficient, damping coefficient, dimensionless comprehensive stiffness, and critical moment of inertia all decrease, thereby reducing angular oscillation stability. Among the tested groove geometries, enclosed grooves and spiral grooves exhibit superior stability due to their strong hydrodynamic effects, yielding the highest dimensionless comprehensive stiffness. The critical frequency ratio for the self-excited angular oscillation of friction plates is approximately 0.5, termed the half-frequency oscillation characteristic. Experimental data validate the proposed angular oscillation model and its frequency response, providing a theoretical foundation for performance prediction and stability optimization in high-speed clutch design.
Aerodynamicists around the globe are developing mechanisms and structures inspired by nature that enable variable camber morphing (VCM) for aerodynamic surfaces. The implementation of the VCM mechanism in an airplane wing enhances the performance and stability during various flight segments. The present review article is focused mainly on the up-to-date VCM methods in a qualitative as well as quantitative approach that are specific to Aircraft/unmanned aerial vehicle (UAV) wing configurations. Initial literature discussions are confined to the conventional mechanisms that enable VCM in different aircraft configurations and the added aerodynamic advantages such as lift enhancement, drag reduction, boundary layer separation, and flow control. However, those designs need either external shape optimization or internal structural refinements to ensure the factor of safety (FoS). The modern aviation industry is also focused on bioinspired technology because of the adaptive flying capabilities and stall-delay characteristics. Therefore, a review of bioinspired VCM methods that are assessed based on the aerodynamic potentials is sequentially organized in the article. Additionally, considerations are motivated by the application of various compliant structural patterns for VCM in the aircraft industry. The discussion indicates the prospective benefits of morphing toward the future of the Green Aviation industry.
The canard configuration has been widely adopted in short-range missiles. However, its main drawbacks include difficulties in roll control and a limited angle-of-attack (AoA) range. Compared to conventional canard missiles, the addition of a pair of control surfaces (referred to as “aileron”) behind the canard control surfaces achieves decoupling between the roll channel and pitch-yaw channel. To investigate the influence of ailerons on the aerodynamic characteristics of canard configuration missiles, numerical simulations were conducted for two typical flow conditions: subsonic (Mach 0.5) and supersonic (Mach2.0). The results show that the introduction of ailerons increases the normal force of missiles, causes the center of pressure to shift forward, and reduces the static stability of missiles, thus enhancing their maneuverability. When the ailerons control the roll channel, the effectiveness of the rolling moment remains consistent over the entire AoA range without adverse effects. However, when the canards control the pitch channel, the interference caused by the deflection of the canards on the ailerons leads to increased lift and generates additional nose-up pitching moments, which reduces the pitching moment effectiveness of the missile.
Efficient optimization of aerodynamic shapes is a critical challenge in aircraft design. Traditional CFD-based optimization workflows suffer from high computational costs and low efficiency, which severely restricts their practical engineering application. In this paper, a novel aerodynamic optimization method based on a hierarchical neural network with adaptive activation functions is proposed. The network adopts learnable B-spline activation functions and is hierarchically constructed in accordance with the sharing status of B-spline control points. After being trained to achieve fast and accurate prediction of aerodynamic performance, the network can effectively replace the traditional CFD module in the optimization loop. The primary advantage of the proposed method is that it significantly reduces the computational cost during the optimization process while ensuring that the prediction accuracy is not compromised. This work thereby presents a novel strategy and technical framework for streamlining the design process of hypersonic vehicles.
By tweaking the flap’s deflection angle, the flap rudder significantly enhances the hydrodynamic performance. This study investigates the influence of the location of the flap rotation axis and the size of the flap’s deflection affect how well the rudder performs in the water, using computer simulations to obtain high-resolution flow-field data. The results demonstrate that the flap rudder consistently generates more lift than your standard rudder. Prior to stall, pushing the flap rotation axis further back results in less lift, but also less drag. For maximum lift at small or moderate angles of attack, a rotation axis located at 0.75 c provides the highest lift coefficient, whereas the 0.85 c configuration combined with δ = 25° offers the best compromise between postponed stall and maintained lift-to-drag ratio. Put the pivot at 85% chord and set the flap deflection to 25 degrees, and an optimal configuration is achieved in terms of lift and drag. The configuration yields a stall angle pushed out to 16 degrees and a maximum lift coefficient that jumps to 3.86. That’s a significant increase of 15.77 % over what you’d get with 15° flap deflection. Ultimately, this research lays the groundwork for designing better flap rudders and gives us some serious pointers on how to increase the performance of ship rudders in the real world.
Despite advances in CFD, wind tunnel testing remains indispensable for aerodynamic validation, correlation, and homologation. Increasing configuration complexity, shortened development cycles, and stringent result robustness and documentation requirements demand a shift from isolated facilities to integrated, data-driven ecosystems within the overall development and company-wide test processes. We present a software-centric approach integrating wind tunnel operations into a strategic element of the Digital Thread. By orchestrating test planning, execution, data acquisition, and documentation within a unified framework, experimental data becomes reusable across projects and traceable for compliance and homologation. The interaction between CFD and physical testing is important. Such approach systematically improves simulation models with wind tunnel tests. And CFD results guide efficient test matrix definition. Extended measurement methodologies include automated actuation of active aerodynamic components in test sequences, while BEVs introduce further aerodynamic and thermal aspects for range and efficiency. Thus, extended and automated test definition down to the step-level of test sequences is introduced. Within such integrated environment, AI can be a supporting engineering tool to enhance testing. AI-based methods can assist in identifying relevant test points within complex parameter spaces and in correlating experimental and simulated results, assisting but not replacing established engineering judgment. Also, for the operating department, analyzing process data for maintenance predictions and efficiency optimizations can be assisted by AI-based methods and supporting AI-agents. The approach boosts efficiency by reducing test effort and tedious manual tasks, leading to shorter development cycles, supporting improved time-to-market. Structured workflows and standardized data handling enhance data quality, improve comparability of results, and ensure robust documentation for reliable audit trails. By combining physical testing, simulation, and intelligent processing, the wind tunnel becomes a reproducible, innovation-enabling element in modern product development, positioning software as the backbone of efficient, future-proof aerodynamic testing.
The payload fairing of a launch vehicle is subjected to extremely high acoustic loads, with peak levels occurring during lift-off and transonic aerodynamic regimes. The external acoustic field penetrates the fairing, producing intense internal sound pressure levels that can challenge the integrity of spacecraft components. Accurate characterization of the vibroacoustic behavior of the payload fairing and its enclosed cavity is therefore essential to ensure spacecraft survivability. The internal acoustic field is governed by the coupled dynamics of the fairing structure and the spacecraft configuration, making it critical to quantify the acoustic environment for different payload arrangements. This study presents a detailed vibroacoustic analysis of a payload fairing with multiple spacecraft configurations to evaluate the resulting internal sound pressure distribution. Vibroacoustic finite element analysis is employed in the low frequency range, while statistical energy analysis is utilized for mid and high frequency ranges. Representative models are developed, and the predicted structural and acoustic responses are validated against experimental acoustic test measurements. The validated models are subsequently extended to other spacecraft configurations to perform sensitivity studies. The influence of various parameters on the internal sound pressure levels is assessed, and the resulting perturbations across frequency bands are quantified. The outcome of this study provides a comprehensive understanding of the internal acoustic environment within payload fairing, aiding in the specification of qualification acoustic test level for spacecraft.
Aircraft verification and certification entail a variety of testing tasks and require coordination among numerous stakeholders across different disciplines to ensure alignment on requirements. Historically, certification strategies have relied on both physical testing and high-fidelity simulation. The integration of these complementary approaches is essential to address their respective blind spots and to support credible certification evidence. A key challenge lies in the rigorous correlation of simulation models with physical test data. Flutter verification, for instance, is a critical component in defining the aircraft’s flight envelope and plays a foundational role in certifying safe operational boundaries. In this work, the process of freedom from flutter verification is demonstrated. This work introduces a novel approach to combining simulation and test data with the aim to accelerate and streamline the verification process leading to more efficient and cost-effective aircraft development. In addition, it is shown how the flutter verification process can be deployed using a simulation process and data management (SPDM) tool from which tasks are assigned and results are collected allowing transparency about the status of the workflow and providing stakeholders access to the data they need when they need it. The workflow is demonstrated using ground vibration test measurement performed on a full-scale F16 aircraft. Throughout the process, simulation data, test results, requirements, and supporting documentation are systematically managed within the SPDM framework. This enables effective cross domain collaboration between simulation and test engineers while also maintaining a single source of truth for proof of compliance and progressively building a robust digital thread throughout the development lifecycle.
Neural Concept is an AI-first engineering platform that is being used at OEMs, including Subaru, Jaguar Land Rover (JLR) and General Motors. The company, which grew out of the Swiss Federal Institute of Technology Lausanne in 2018, is applying AI in real aerodynamic engineering workflows, visualized through NVIDIA Omniverse. Today, the company has 120 employees and works with companies in Europe, the U.S., India, South Korea and Japan. SAE Media met up with Thomas von Tschammer, managing director of Neural Concept USA, at WCX in Detroit in April. This has been lightly edited for clarity.
High-speed maglev trains are recognized for their superior velocity, environmental benefits, and enhanced passenger comfort, positioning them as a key area of interest in modern transport research. Nonetheless, tunnel operations introduce complex aerodynamic challenges that can impede performance. This research examines the aerodynamic load behaviors of maglev trains in single and double-track tunnel settings, with particular emphasis on transient drag variations in lead and trail cars during solo and passing operations. A computational fluid dynamics model was constructed to capture detailed flow field attributes, including pressure wave propagation, reflection, and superposition. Findings indicate that aerodynamic loads intensify with increasing speed. When velocity rises from 300 km/h to 600 km/h during solo tunnel transit, the lateral force on the head-car and the drag on the trail-car both surge approximately fivefold. During meets in double-track tunnels, the head-car’s lift force increases most drastically—by 7.6 times. Entry and exit events induce pressure waves that cause notable drag fluctuations on both cars, with train interactions further amplifying these variations in dual-track scenarios.
Rotorcraft airfoils often feature a tab which aides in the manufacturing of composite rotor blades, but also has aerodynamic merits. This study performs a comprehensive analysis of the impact of this tab on the 2D airfoil performance, structural adjustments and 3D rotor performance. The aerodynamics are evaluated using CFD, with CFD/CSD coupled results for the rotor performance. The structural data is adjusted using an FEM based in-house process. The HART II model rotor has been taken as a baseline and modified according to the tab variation studies. These included the comparison of a sharp trailing edge versus a tabbed airfoil, various tab thicknesses, lengths, and angles. The studies showed a variation of peak Figure of Merit between 66% to 68% and peak rotor L/D from 4.2 to 4.6 The careful design of the airfoil tab is therefore advised, but similarly the structural design of rotor blades.
This paper investigates amplitude effects in the aeroelastic damping and frequency characteristics of the Maryland Tiltrotor Rig across four configurations: gimballed or hingeless hubs, each paired with straight or swept-tip blades. The recovery rate method is used to identify the aeroelastic parameters of the primary modes dominated by out-of-plane and in-plane wing bending from experimental free-decay strain time histories, capturing variations in dynamic behavior with the response amplitude. Results from conventional methods that assume linear (amplitude-independent) behavior are also presented for comparison. The local damping ratio of the examined modes generally decreases with increasing strain amplitude across all configurations, a trend missed by conventional linear estimation methods. The strength of amplitude effects varies as the system approaches instability: for gimballed configurations, they weaken near instability; for hingeless configurations, they become more pronounced. While the local frequency of the mode dominated by out-of-plane wing bending remains relatively constant with strain amplitude, the frequency of the mode dominated by in-plane wing bending displays significant amplitude-dependent shifts, particularly for hingeless hubs. The findings demonstrate the importance of accounting for nonlinear effects in aeroelastic parameter identification based on experimental tiltrotor data and provide insights into tiltrotor nonlinear dynamics.
Atmospheric turbulence is a major source of uncertainty for unmanned rotorcraft operating in confined or disturbed environments, where robust trajectory planning requires reliable bounds on vehicle response. High-fidelity turbulence models are typically too computationally demanding for onboard use and difficult to integrate into planning frameworks. This paper presents a Control Equivalent Turbulence Input (CETI)–based approach to characterize turbulence effects on the inner-loop dynamics of a small unmanned helicopter and to derive disturbance-induced state deviation bounds suitable for robust planning. CETI models are identified from manually piloted hover flight tests of the unmanned research helicopter midiARTIS using a linear bare-airframe model and a Kalman filter for disturbance estimation. CETI transfer functions are fitted to averaged power spectral densities of the extracted disturbance inputs. The resulting model is validated by reproducing the identified transfer functions and by comparing open-loop simulation results to flight-test data in both time and frequency domain. Based on simulations with CETI inputs, probabilistic bounds on state deviations are derived and related to measured flight-test responses. The results demonstrate that the proposed CETI workflow provides a compact and computationally efficient turbulence surrogate that captures the dominant effects of atmospheric gusts on rotorcraft dynamics and is well suited for inner-loop performance assessment and as an input to robust model predictive control algorithms.
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