Browse Topic: Aerodynamics
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
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
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
This document describes a rigorous engineering test procedure that utilizes industry-accepted data collection and statistical analysis methods to determine the road load and to estimate the aerodynamic drag area of trucks and buses weighing more than 10000 pounds. The test procedure may be conducted on a test track or on a public road under controlled conditions and supported by extensive data collection and data analysis constraints. The estimated aerodynamic-drag-area result represents a single-speed and single-yaw-angle condition. Test results that do not rigorously follow the method described herein shall not be represented as an SAE J2978 result.
The front wing of a Formula 1 car is one of the most important aerodynamic components in design development. Particularly, as it is the first to interact with the upcoming airflow, the aerodynamic flow structures generated will have a strong interaction with the remainder of the car’s components. In 2026, the Fédération Internationale de l’Automobile will introduce new regulations that incorporate new aerodynamic philosophies for the front wing, including active aerodynamics. This paper presents a design methodology study for the development of a Formula 1 2026 front wing, compliant with Issue 9 of the technical regulations. A computational-based, structured optimisation series was conducted to enhance the aerodynamic performance of a front wing concept with a focus on improving downforce, maximising efficiency, and enhancing trailing flow for the remainder of the car. The final front wing concept at 40%, running at 30 m/s, generated 189 N of downforce and 19 N of drag. Active
Aerodynamic simulations are crucial in vehicle design and performance evaluation. Traditionally, these simulations utilize Computational Fluid Dynamics (CFD) techniques to compute flow quantities such as velocity, pressure, and wall-shear stresses. Accurate prediction of these quantities is vital for estimating drag and lift forces, which directly impact fuel efficiency, stability, and acoustics. This study focuses on developing an AI surrogate for aerodynamic design of production mideo-size SUVs using NVIDIA’s PhysicsNeMo framework. Firstly, high-fidelity 3D CFD data are generated using first-principles solvers on 102 different geometry variants at a uniform inlet velocity of 38.89 m/s and a fixed set of boundary conditions. The DoMINO (Decomposable Multiscale Iterative Neural Operator) AI model, part of the PhysicsNeMo framework, is then used to train on this dataset, accurately predicting surface pressure and flow fields around vehicles for rapid estimation of critical aerodynamic
MSIL (Maruti Suzuki India Limited), India’s leading automotive manufacturer, offers a diverse range of SUVs (Sports Utility Vehicles) in its portfolio. Traditionally, SUVs are associated with an assertive stance and a commanding road presence; however, this bold design language often compromises aerodynamic drag performance. Over the past decade, demand for this segment has surged, while CAFE (Corporate Average Fuel Economy) regulations have become increasingly stringent. To address this growing market need, MSIL conceptualized a new SUV - Victoris - targeted to deliver best-in-class aerodynamic efficiency in MSIL SUV portfolio. This paper details the aerodynamic development process using CFD (Computational Fluid Dynamics) and full-scale WTT (Wind Tunnel Testing). Initially, the aggressive styling of Victoris negatively impacted drag performance. Strategic exterior surface refinements and integration of aero components enabled recovery of aerodynamic efficiency. Key interventions
The design of thermal components (such as automotive heat exchangers) requires balancing multiple competing objectives—thermal performance, aerodynamic efficiency, structural integrity, and manufacturability. Traditional design workflows rely on manual Computer Aided Design (CAD) modeling and iterative simulations, which are both labor-intensive and time-consuming. Recent advances in Large Language Models (LLMs) present untapped potential for automating parametric CAD generation. However, current LLM-based approaches primarily handle simple, isolated geometric primitives rather than complex multi-component assemblies. This work introduces a progressive framework that leverages fine-tuned LLMs (Qwen2.5-3B-SFT) integrated with the CadQuery CAD kernel to automatically generate parametric geometries from natural language descriptions. As a foundational study, this work focuses on Step 1 of the framework: generating and optimizing isolated geometric primitives (cylinders, pipes, etc.) that
Thermal and lubrication management is critical for the performance characteristics of Electric Drive Units (EDUs) in electrified powertrains. Accurate assessment of lubrication flow, particularly in terms of wetting behavior and churning losses, is essential for optimizing EDU performance across various driving conditions. This study presents a comprehensive numerical investigation of lubrication flow behavior within an EDU using an advanced Smoothed Particle Hydrodynamics (SPH) method. The mesh-free SPH approach provides significant advantages in modeling intricate oil dynamics, such as oil splashing, and the behavior of oil in contact with rotating components. The primary focus of this study is to investigate the phenomena of oil splashing, wetting behavior characterized by the Wetting Fraction(WF), and churning losses within the gearbox environment. Key flow characteristics such as oil distribution, particle trajectories, torque resistance due to fluid drag, and oil volume fraction
A research team developed a smart strake system that dynamically adapts to flight conditions, showing a promising drag reduction in the wind tunnel with respect to passive strakes. This approach has the potential to save airlines hundreds of kilograms of fuel per flight. University of Washington Department of Aeronautics & Astronautics (A&A), Seattle, WA For decades, aircraft have carried a fundamental compromise between their engines and wing flow interactions by using strakes. These are small fins attached at the sides of engine nacelles that generate helpful vortices during takeoff and landing that boost lift and avoid stall, but create unwanted drag during cruise flight. Now, seven William E. Boeing Department of Aeronautics & Astronautics (A&A) undergraduates have advanced a solution that improves this trade-off, achieving up to 33 percent drag reduction, on the limited tested conditions, during cruise while maintaining critical safety benefits at high angles of attack. The team
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