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Related papers: Transonic Buffet Modeling via Invariant Manifolds

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Accurate prediction of laminar-turbulent transition is a critical element of computational fluid dynamics simulations for aerodynamic design across multiple flow regimes. Traditional methods of transition prediction cannot be easily…

Fluid Dynamics · Physics 2021-06-17 Muhammad I. Zafar , Meelan M. Choudhari , Pedro Paredes , Heng Xiao

Effectively predicting transonic unsteady flow over an aerofoil poses inherent challenges. In this study, we harness the power of deep neural network (DNN) models using the attention U-Net architecture. Through efficient training of these…

Fluid Dynamics · Physics 2024-03-27 Li-Wei Chen , Nils Thuerey

The present paper develops a reduced-order model capable of modeling unsteady aerodynamic loads in the transonic regime using system identification techniques. The computational fluid dynamics (CFD) calculations are based on the Euler…

Fluid Dynamics · Physics 2023-07-20 Ana Cristina Neves Carloni , João Luiz F. Azevedo

This work provides an overview of aerodynamic data acquired in the European Transonic Windtunnel using an XRF-1 transport aircraft configuration both at cruise conditions and at the edges of the flight envelope. The goals and design of the…

In the age of globalization, commercial aviation plays a central role in maintaining our international connectivity by providing fast air transport services for passengers and freight. However, the upper limit of the aircraft flight…

Fluid Dynamics · Physics 2024-01-26 Esther Lagemann , Steven L. Brunton , Wolfgang Schröder , Christian Lagemann

The current work is concerned with studying processes for constructing reduced-order models capable of performing transonic aeroelastic stability analyses in the frequency domain based on computational fluid dynamics (CFD) techniques. The…

Fluid Dynamics · Physics 2023-07-21 Ana Cristina Neves Carloni , João Luiz F. Azevedo

Within the transonic regime, the aeroelastic problems exhibit many unique characteristics compared with subsonic and supersonic cases. Although a lot of research has been carried out in this field, the underlying mechanisms of these complex…

Fluid Dynamics · Physics 2020-02-11 Chuanqiang Gao , Weiwei Zhang

Dynamic mode decomposition (DMD) is a data-driven technique widely used to analyze and model fluid problems including transonic buffet flows. Despite its strengths, DMD is known to suffer from sensitivities to the selected settings and the…

Fluid Dynamics · Physics 2023-05-09 Andre Weiner , Richard Semaan

This paper presents a novel modeling approach for unsteady aircraft airflow, leveraging the Lorenz attractor framework. The proposed model is based on the force distribution exerted by a lift-generating wing on the surrounding fluid. It…

Fluid Dynamics · Physics 2026-03-09 Marcel Menner , Eugene Lavretsky

Obtaining predictive low-order models is a central challenge in fluid dynamics. Data-driven frameworks have been widely used to obtain low-order models of aerodynamic systems; yet, resulting models tend to yield predictions that grow…

Machine-learning surrogate models have shown promise in accelerating aerodynamic design, yet progress toward generalizable predictors for three-dimensional wings has been limited by the scarcity and restricted diversity of existing…

Machine Learning · Computer Science 2026-05-08 Yunjia Yang , Weishao Tang , Mengxin Liu , Nils Thuerey , Yufei Zhang , Haixin Chen

Aeroelasticity in the transonic regime is challenging because of the strongly nonlinear phenomena involved in the formation of shock waves and flow separation. In this work, we introduce a computationally efficient framework for accurate…

Fluid Dynamics · Physics 2023-04-17 Nicola Fonzi , Steven L. Brunton , Urban Fasel

Aeroelastic structures, from insect wings to wind turbine blades, experience transient unsteady aerodynamic loads that are coupled to their motion. Effective real-time control of flexible structures relies on accurate and efficient…

Fluid Dynamics · Physics 2022-07-14 Michelle Hickner , Urban Fasel , Aditya G. Nair , Bingni W. Brunton , Steven L. Brunton

We present a data-driven feedforward control to attenuate large transient lift experienced by an airfoil disturbed by an extreme level of discrete vortex gust. The current analysis uses a nonlinear machine-learning technique to compress the…

Fluid Dynamics · Physics 2024-09-18 Kai Fukami , Hiroya Nakao , Kunihiko Taira

Accurate machine-learning models for aerodynamic prediction are essential for accelerating shape optimization, yet remain challenging to develop for complex three-dimensional configurations due to the high cost of generating training data.…

Machine Learning · Computer Science 2026-04-21 Yunjia Yang , Babak Gholami , Caglar Gurbuz , Mohammad Rashed , Nils Thuerey

Machine learning has been widely utilized in fluid mechanics studies and aerodynamic optimizations. However, most applications, especially flow field modeling and inverse design, involve two-dimensional flows and geometries. The…

Fluid Dynamics · Physics 2023-04-19 Runze Li , Yufei Zhang , Haixin Chen

The transonic flow around the OAT15A airfoil is computed at buffet conditions, i.e., freestream Mach number $Ma_\infty = 0.73$, chord-based freestream Reynolds number $Re_c = 2\cdot10^6$, and angle of attack $\alpha = 3.5^\circ$ using…

Fluid Dynamics · Physics 2024-03-20 Thomas Lürkens , Matthias Meinke , Wolfgang Schröder

This study investigates the relationship between low-frequency shock-wave oscillations and buffet cells on the main wing of the NASA common research model. The flow conditions were set at a Mach number of 0.85, Reynolds number of 2.27…

Fluid Dynamics · Physics 2025-09-22 Yuya Ohmichi , Yosuke Sugioka

Recent research into buffet in the transonic flow regime has been focused on a limited number of proprietary airfoil geometries and has mainly considered parametric variations in Mach number and angle of attack. In contrast, relatively…

The accurate prediction of flow fields around airfoils is crucial for aerodynamic design and optimisation. Computational Fluid Dynamics (CFD) models are effective but computationally expensive, thus inspiring the development of surrogate…

Machine Learning · Computer Science 2025-11-19 Kenechukwu Ogbuagu , Sepehr Maleki , Giuseppe Bruni , Senthil Krishnababu