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Introduction

This special issue focuses on emerging approaches in aerodynamics, taking advantage of massive data collected from high-fidelity numerical simulations, highly instrumented wind-tunnel testing and innovative flight tests measurements. Experimental, theoretical and numerical aspects will be addressed, ranging from fundamental research to industrial applications. They will cover both external and internal aerodynamics, with the corresponding thermal phenomena.

The research works will consider problems encountered in the aerospace and transportation domains including electric air taxis and in energy production, such as wind turbines for instance.

The emerging methods such as big data, machine learning, artificial intelligence and high-fidelity simulations, provide enhanced capabilities to major models. Data-driven turbulence modelling, disruptive geometry modelling techniques, self-adaptive meshing are among the models that benefit from these techniques. Generative modelling allows aerodynamic data fusion from multiple sources providing a more complete coverage of flight envelope. Physics-aware surrogate models combined with high-order simulation improve interdisciplinary predictions and multidisciplinary design optimization, essential for next generation of environmentally friendly products.

All contributions with numerical, theoretical and/or experimental approaches falling within the theme of this special issue are welcome. It could contain, among others, the completed versions of the most instructive contributions to the 58th 3AF International Conference on Applied Aerodynamics AERO2024 (March 27-28-29, 2024), organized in Orléans (France) by the Aerodynamics Technical Committee of the French Aeronautics and Aerospace Society (3AF). This special issue does not constitute the proceedings of this conference.

• Reviewing process: Each submitted paper is reviewed by the Guest Editor-In-Chief and Advisory Editor of the IJNMHFF journal, Prof. Abderrahmane Baïri. If it is judged suitable for publication, it will be sent to at least two independent referees for peer review with the rigorous expertise process of the IJNMHFF journal.
• Decision on article (acceptance, rejection, revision): as soon as the peer reviews have arrived
• Publication date of the special issue: March 2025
• References of the special issue: Volume 35 Issue 4 (HFF 35.4)
• Guest Editor-In-Chief: Prof. Abderrahmane Baïri (University of Paris)
• Contact: on behalf of the Guest Editor-In-Chief: Ms Aude Lurbe [email protected]

 

List of topic areas

The following items will be considered to address the above challenges (the list not being exhaustive):

• Data-driven aerodynamic models through data science and machine learning;
• Impact of machine learning on aerodynamic design optimization;
• Aerodynamic design assisted by reduced-order modelling and machine learning;
• Thermal modelling in aeronautics and space;
• Machine Learning for Turbulence Modelling;
• Unsteady aerodynamics, unducted propellers, wind turbines…;
• Innovative tools for numerical simulation: RANS, LES, LBM;
• Innovative mesh Generation of complex geometry, Self-adaptive mesh techniques;
• Multidisciplinary Design Optimization;
• Multiphysics interactions: heat and mass transfer, aeroacoustics, aeroelasticity;
• Data assimilation, Digital twins, Real-time flight measurements;
• Wind tunnel experiments, Innovative Post-processing of experimental measurements;
• In-flight identification of aerodynamic performance.

 

Guest Editors 

Professor Abderrahmane BAÏRI
Université de Paris, France
[email protected]

Dr. Nacim ALILAT
University of Paris, France
[email protected]

Dr Vincent BRION
ONERA (The French Aerospace Lab), France
[email protected]
 

Submissions Information

Submissions are made using Scholar One Manuscripts. Registration and access are available by clicking the button below.

Submit your paper here!

Author guidelines must be strictly followed.

Authors should select (from the drop-down menu) the special issue title "Emerging Approaches in Aerodynamics" at the appropriate step in the submission process, i.e. in response to “Please select the issue you are submitting to”. 

Submitted articles must not have been previously published, nor should they be under consideration for publication anywhere else, while under review for this journal.

 

Key Deadlines

Closing date for manuscript submissions: 16 November 2024