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MDO / AIRCRAFT DESIGN

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Results and Papers

D 4 septembre 2017    

Designing Next-Generation Aircraft via High-Fidelity Computational Models and Optimization


Workshops

- Multidisciplinary Design Optimization of Aircraft Configurations. Part 1 : A modular coupled adjoint approach, von Karman Institute Lecture Series, Brussels, Belgium, May 2016.
- Multidisciplinary Design Optimization of Aircraft Configurations. Part 2 : High-fidelity aerostructural optimization, von Karman Institute Lecture Series, Brussels, Belgium, May 2016.
- Invited lecturer for a class on Structural and Optimization at ISAE-SUPAERO, March 2015&2016, Toulouse, France.
- Optimisation numérique de la conception d’une aile d’avion : Rêve ou realité ?, ENSEEIHT,Toulouse, France, May 2016.
- Optimisation numérique de la conception d’une aile d’avion : Rêve ou realité ?, ONERA Fluid Mechanics and Energetics Branch, Paris, France, Mar 2016.
- Multidisciplinary design optimization (MDO) : A new scalable and modular approach, ROMA Seminar, ISAE, Toulouse, France, Jan 2016.
- A Very Short Course on Multidisciplinary Design Optimization, ISAE, Toulouse, France, Mar 2016.
- High-Fidelity Multidisciplinary Design Optimization, Airbus Technical Workshop, Airbus, Filton, UK, Dec 2015.
- Practical wing design via numerical optimization : Are we there yet ?, University of Bristol, UK, Dec 2015.
- Optimisation numérique de la conception d’une aile d’avion : Rêve ou realité ?, Institut Clément Ader, Toulouse, France, Nov 2015.
- Wing design via numerical optimization : Are we there yet ?, ONERA AGILE Workshop, Toulouse, Dec 2015.
- Optimisation numérique de la conception d’une aile d’avion : Rêve ou realité ?, Dassault Aviation, Paris, France, Oct 2015.
- Optimisation numérique de la conception d’une aile d’avion : Rêve ou realité ?, École Polytechnique, Paliseau, France, Oct 2015.
- Optimisation numérique de la conception d’une aile d’avion : Rêve ou realité ?, Séminaire DAEP, ISAE, Toulouse, France, Oct 2015.
- High-Fidelity Multidisciplinary Design Optimization for the Next-Generation of Commercial Transport Aircraft, AMEDEO ESR Training Course, ONERA, Paris, France, Oct 2015.
- High-Fidelity Multidisciplinary Design Optimization for the Next Generation of Aircraft, Congress on Numerical Methods in Engineering, Lisbon, Portugal, Jul 2015.

Seminars
ERC MDO #1 the Third of December 2016
ERC MDO #2 the Third of March 2017

PDF - 48.2 ko

Papers

- J. M. Colomer, N. Bartoli, T. Lefebvre, S. Dubreuil, J. R. R. A. Martins, E. Benard, and J. Morlier. Similarity maximization of a scaled aeroelastic flight demonstrator via multidisciplinary optimization. In Proceedings of the AIAA SciTech Conference, Grapevine, TX, January 2017. AIAA 2017-0573.

- N. Bartoli, T. Lefevbre, N. Bons, M. Bouhlel, S. Dubreuil, R. Olivanti, J. R. R. A. Martins and J. Morlier. An adaptive optimization strategy based on mixture of experts for wing aerodynamic design optimization. Proceedings of AIAA AVIATION Forum 5-9 June 2017, Denver, Colorado 18th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference 2017

- Mas Colomer, N. Bartoli, T. Lefebvre, S. Dubreil, P. Schmollgruber, J. R. R. A. Martins and J. Morlier. Static and Dynamic Aeroelastic Scaling of the CRM Wing via Multidisciplinary Optimization. WCSMO12 12th World Congress of Structural and Multidisciplinary Optimisation 5 - 9 June 2017, Braunschweig, Germany 2017

PhDs
Prof Martins is Co-advisor Joan Mas Colomer
Prof Martins is Co-advisor Alessandro Sgueglia

Softwares & HPC

OpenAeroStruct is a lightweight tool to perform aerostructural optimization using OpenMDAO. It couples a vortex-lattice method (VLM) and a 6 degrees of freedom 3-dimensional spatial beam model to simulate the aerodynamic and structural properties of lifting surfaces. These simulations are wrapped in an optimizer using NASA’s OpenMDAO framework.

https://github.com/johnjasa/OpenAeroStruct/

SMT is an Open source Surrogate Modeling Toolbox in Python. Includes surrogate modeling methods (emphasis on derivatives and high dimension), sampling techniques and benchmarking functions.

https://github.com/SMTorg/SMT

CALMIP - Projet P17012

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