Mathieu Balesdent

Directeur de Recherche (DR 2) à l'ONERA, HDR

Département Traitement de l'Information et Systèmes - Unité Méthodes Multidisciplinaires, Concepts Intégrés

 

In English
 

Centres d'intérêts

• Quantification d'incertitudes
• Optimisation multidisciplinaire
• Optimisation mixte continu / discret
• Conception de véhicules aérospatiaux
• Membre de l'équipe de développement du logiciel open source openTURNS pour le traitement des incertitudes

 

CV

• 2022 - : Directeur de Recherche 2 à l'ONERA - Département Traitement de l'Information et Systèmes (DTIS)
• 2020 - 2022 : Maitre de Recherche 1 à l'ONERA - Département Traitement de l'Information et Systèmes (DTIS)
• 2021 : Habilitation à Diriger des Recherches, sujet : Contributions à l'optimisation et au traitement des incertitudes pour la conception de véhicules aérospatiaux
• 2017-2020: Ingénieur de Recherche à l'Onera - Département Traitement de l'Information et Systèmes (DTIS)
• 2011-2017 : Ingénieur de Recherche à l'Onera - Département Conception et évaluation des Performances des Systèmes (DCPS)
• 2008-2011: thèse de doctorat à l'Ecole Centrale de Nantes et à  l'Onera-DCPS, Palaiseau, Sujet : Optimisation multidisciplinaire de lanceurs (Directeur de thèse : Ph. Dépincé, Encadrant Onera : N. Bérend), cofinancement CNES/Onera
• 2007-2008: DEA/Master 2 Recherche : Automatique et Génie Informatique, Université des Sciences et Technologies de Lille / Ecole Centrale de Lille
• 2005-2008: diplôme d'ingénieur généraliste, ISEN Lille

 

Activités éditoriales

• Coéditeur du numéro spécial "Aerospace System Analysis and Optimization" dans la revue "Applied Sciences"
• Editeur du numéro spécial "Aerospace Vehicle Design under Uncertainty"  dans la revue "Applied Sciences"
• Editeur du numéro spécial "New Insights into Multidisciplinary Design Optimization"  dans la revue "Applied Sciences"

 

Enseignements

• Depuis 2023 à l'INSA Rennes : Machine learning for aerospace system design
• Depuis 2022 à l'ISAE-Supaéro : Conception de lanceurs (optimisation de trajectoire)
• Depuis 2019 à l'Ecole Polytechnique : Optimisation multidisciplinaire avec applications à la conception de véhicules spatiaux
• Depuis 2018 à l'Ecole Supérieure d'Ingénieurs Léonard de Vinci : Advanced methods for multidisciplinary analysis and optimization

 

Liens

• Page google scholar
• Page github

 

 

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Publications et communications

Livres

L. Brevault, M. Balesdent et J. Morio (2020) Aerospace System Analysis and Optimization in Uncertainty, Springer Nature Switzerland AG, ISBN : 978-3-030-39125-6   Informations et disponibilité : [ Springer ] [ Amazon ]

J. Morio et M. Balesdent (2015) Estimation of Rare Event Probabilities in Complex Aerospace and Other Systems, A Practical Approach, Woodhead Publishing, ELSEVIER, ISBN : 978-0-08-100091-5   Informations et disponibilité : [ Elsevier ] [ Amazon ]

Chapitres d'ouvrage

• V. Chabridon, M. Balesdent, G. Perrin, J.Morio, J.-M. Bourinet et N. Gayton (2021) Global reliability-oriented sensitivity analysis under distribution parameter uncertainty. in : Mechanical Engineering in Uncertainties From Classical Approaches to Some Recent Developments, Wiley & Sons
• V. Chabridon, M. Balesdent, G. Perrin, J.Morio, J.-M. Bourinet et N. Gayton (2021) Analyse de sensibilité globale ciblée pour la fiabilité en présence d'incertitudes sur les paramètres de distribution, in : Ingénierie mécanique en conexte incertain : des approches classiques à quelques développements récents, ISTE
• J. Pelamatti, L. Brevault, M. Balesdent, E.-G. Talbi et Y. Guérin (2020) Overview and comparison of Gaussian process-based surrogate models for mixed continuous and discrete variables, application to aerospace design problems, in : High-performance simulation based optimization, series: Springer series on Computational Intelligence, Springer, DOI : 10.1007/978-3-030-18764-4, ISBN : 978-3-030-18763-7
• P. Derennes, V. Chabridon, J. Morio, M. Balesdent, F. Simatos, J.-M. Bourinet et N. Gayton (2019) Nonparametric importance sampling techniques for sensivity analysis and reliability assessment of a launcher stage fallout, in : Modeling and Optimization in Space Engineering : State of the Art and New Challenges, Springer, DOI : 10.1007/978-3-030-10501-3 , ISBN : 978-3-030-10500-6
• M. Balesdent, L. Brevault, N. Price, S. Defoort, R. Le Riche, N.H. Kim, R. Haftka et N. Bérend (2016) Advanced space vehicle design taking into account multidisciplinary couplings and mixed epistemic / aleatory uncertainties  in : Space Engineering: Modeling and Optimization with Case Studies, éditeurs : G. Fasano and J. Pinter, Vol.2 : 1-48., Springer, DOI : 10.1007/978-3-319-41508-6_1, ISBN : 978-3-319-41508-6
• M. Balesdent et H. Piet-Lahanier (2015) A multi-level optimization approach for the planning of heterogeneous sensor networks, in : Modelling, Computation and Optimization in Information Systems and Management Sciences, éditeurs : Hoai An Le Thi, Tao Pham Dinh, Ngoc Tanh Nguyen, série : Advances in Intelligent Systems and Computing,  Vol.360 : 221-233, Springer, DOI: 10.1007/978-3-319-18167-7_20, ISBN: 978-3-319-18166-0

 

Articles acceptés dans des journaux à comité de lecture

• L. Brevault, M. Balesdent (2024) Bayesian Quality-Diversity approaches for constrained optimization problems with mixed continuous, discrete and categorical variables, Engineering Applications of Artificial Intelligence, Elsevier, Vol.133:108118
• M. Balesdent, L. Brevault, B. Paluch, R. Thépot, R. Wuilbercq, N. Subra, S. Defoort, M. Bourgaie, B. Vieille (2023) Multidisciplinary design and optimization of winged architectures for reusable launch vehicles, Acta Astronautica, Elsevier Vol.211:97-115
• J. Gamot, M. Balesdent, R. Wuilbercq, A. Tremolet, N. Melab, E.-G. Talbi (2023) Hidden-variables metaheuristics for solving variable-sized design space optimal layout with application to aerospace vehicles, Engineering Applications of Artificial Intelligence, Elsevier, Vol.121
• V. Drouet, M. Balesdent, L. Brevault, S. Dubreuil, J. Morio (2023) Multi-fidelity algorithm for the sensitivity analysis of multidisciplinary problems, Journal of Mechanical Design, ASME 145(7): 071703
• A. Hebbal, M. Balesdent, L. Brevault, N. Melab  & E.G. Talbi (2023) Deep Gaussian Process for multi-objective Bayesian optimization, Optimization and Engineering, Springer, Vol.24 (3), 1809-1848
• L Brevault, M. Balesdent, J.L. Valderrama - Zapata (2022) Active Learning Strategy for Surrogate-Based Quantile Estimation of Field Function, Applied Sciences, MDPI, Vol.12(9), 10027
• M. Balesdent, L. Brevault, J.L. Valderrama - Zapata, A. Urbano (2022) All-At-Once formulation integrating pseudo-spectral optimal control for launch vehicle design and uncertainty quantification, Acta Astronautica, Elsevier, Vol. 200:462-477
• L.Brevault et M. Balesdent (2021) Uncertainty quantification for multidisciplinary launch vehicle design using model order reduction and spectral methods, Acta Astronautica, Elsevier, Vol.187:295-314
• J. Pelamatti, L.Brevault, M. Balesdent, E.G. Talbi et Y.Guérin (2021) Mixed-variable Gaussian process based surrogate modeling techniques, application to aerospace design, Journal of Aerospace Information System, AIAA, Vol.18(11):813-837
• G. Sarazin, J. Morio, A.Lagnoux, M. Balesdent et L.Brevault (2021) Reliability-oriented sensitivity analysis in presence of data-driven epistemic uncertainty, Reliability Engineering and System Safety, Elsevier Vol:215, 107733
• A. Hebbal, L. Brevault, M. Balesdent, E.-G. Talbi et N. Melab (2021) Multi-fidelity modeling with different input domain definitions using Deep Gaussian Processes, Structural and Multidisciplinary Optimization, Springer, Vol.63:2267–2288, https://doi.org/10.1007/s00158-020-02802-1
• A. Hebbal, L.Brevault, M. Balesdent, E.G. Talbi et N. Melab (2021) Bayesian Optimization using Deep Gaussian Processes with Applications to Aerospace Systems. Optimization and Engineering, Springer,  Vol.22:321-361, DOI : https://doi.org/10.1007/s11081-020-09517-8
• J. Pelamatti, L. Brevault, M. Balesdent et E.G. Talbi (2021) Bayesian optimization of variable-size design space problems. Optimization and Engineering, Springer,  Vol.22:387-447, DOI : https://doi.org/10.1007/s11081-020-09520-z
• L. Brevault, M. Balesdent et A. Hebbal (2020). Overview of Gaussian process based multi-fidelity techniques with variable relationship between fidelities, application to aerospace systems, Aerospace Science and Technology, Elsevier, Vol.107 : 106339, DOI :https://doi.org/10.1016/j.ast.2020.106339
• L. Brevault, M. Balesdent et A. Hebbal, (2020) Multi-Objective Multidisciplinary Design Optimization Approach for Partially Reusable Launch Vehicle Design, Journal of Spacecraft and Rockets, AIAA, Vol.57(2):373-390, DOI: https://doi.org/10.2514/1.A34601
• J. Pelamatti, L. Brevault, M. Balesdent, E.G. Talbi et Y. Perrin (2018) Efficient global optimization of constrained mixed variable problems, Journal of Global Optimization, Vol.73:583-613, Springer, DOI: https://doi.org/10.1007/s10898-018-0715-1
• V. Chabridon, M. Balesdent, J.-M. Bourinet, J. Morio et N. Gayton (2018) Reliability-based sensitivity estimators of rare event probability in the presence of distribution parameter uncertainty, Reliability Engineering and System Safety, Elsevier, Vol.178:164-178, DOI : https://doi.org/10.1016/j.ress.2018.06.008
• L. Brevault, M. Balesdent et S. Defoort (2018) Preliminary study on launch vehicle design - applications of Multidisciplinary Design Optimization methodologies, Concurrent Engineering: Research and Applications. SAGE, Vol 6(1):93-103, DOI : 10.1177/1063293X17737131
• V. Chabridon, M. Balesdent, J.-M. Bourinet, J. Morio et N. Gayton (2017) Evaluation of failure probability under parameter epistemic uncertainty: application to aerospace system reliability assessment, Aerospace Science and Technology, Elsevier, Vol(69):526-537, DOI : 10.1016/j.ast.2017.07.016
• N. Price, N.-H. Kim, R.-T. Haftka, M. Balesdent, S. Defoort et R. Le Riche (2016) Deciding Degree of Conservativeness in Initial Design Considering Risk of Future Redesign, Journal of Mechanical Design, ASME, Vol138(11):111409-111409-13, DOI : 10.1115/1.4034347
• L. Brevault, M. Balesdent, S. Lacaze et S. Missoum (2016) Reliability analysis in the presence of aleatory and epistemic uncertainties, application to the prediction of a launch vehicle fallout zone, Journal of Mechanical Design, ASME, Vol.138(11):111401-111401-11, DOI : 10.1115/1.4034106
• C. Durantin, J. Marzat et M. Balesdent (2016) Analysis of multi-objective Kriging-based methods for constrained global optimization, Computational Optimization and Applications, Springer, Vol.63(3): 903-926, DOI : 10.1007/s10589-015-9789-6
• M. Balesdent, J. Morio et L. Brevault (2016) Rare event probability estimation in the presence of epistemic uncertainty on input probability distribution parameters, Methodology and Computing in Applied Probability, Springer. Vol.18(1):197-216, DOI : 10.1007/s11009-014-9411-x
• J. Morio et M. Balesdent (2016) Estimation of a launch vehicle stage fallout zone with parametric and non parametric importance sampling algorithms in presence of uncertain input distributions, Aerospace Science and Technology, Elsevier, Vol.52: 95-101, DOI : 10.1016/j.ast.2016.02.018
• L. Brevault, M. Balesdent, N. Bérend et R. Le Riche (2016) Decoupled MDO formulation for interdisciplinary coupling satisfaction under uncertainty, AIAA Journal, Vol. 54(1) : 186-205, DOI : 10.2514/1.J054121
• R. Chocat, L. Brevault, M. Balesdent et S. Defoort (2015) Modified Covariance Matrix Adaptation - Evolution Strategy algorithm for constrained optimization under uncertainty, application to rocket design, International Journal for Simulation and Multidisciplinary Optimization, Vol.6:A1, EDP Sciences
• S. Lacaze, L. Brevault, S. Missoum et M. Balesdent (2015) Probability of Failure Sensitivity with respect to Decision Variables, Structural and Multidisciplinary Optimization, Springer, Vol.52(2) : 375-381, DOI : 10.1007/s00158-015-1232-1
• M. Balesdent, J. Morio et J.Marzat (2015) Recommendations for the tuning of rare event probability estimators, Reliability Engineering & System Safety, Elsevier. Vol.133 : 68-78, DOI : 10.1016/j.ress.2014.09.001
• J. Morio, M. Balesdent, D. Jacquemart et C. Vergé (2014) A survey of rare event simulation methods for static input-output models, Simulation Modelling Practice and Theory, Elsevier. Vol.49: 287-304, DOI: 10.1016/j.simpat.2014.10.007
• M. Balesdent, J. Morio et J. Marzat (2013) Kriging-based adaptive Importance Sampling algorithms for rare event estimation, Structural Safety, Elsevier. Vol.44 : 1-10, DOI : 10.1016/j.strusafe.2013.04.001
• J. Morio, D. Jacquemart, M. Balesdent et J. Marzat (2013) Optimisation of Interacting Particle Systems for Rare Event Estimation, Computational Statistics & Data Analysis, Elsevier. Vol.66 : 117-128. DOI : 10.1016/j.csda.2013.03.025
• M. Balesdent, N. Bérend et Ph. Dépincé (2013) New MDO approaches for Launch Vehicle Design, Proceedings of the Institution of Mechanical Engineers, Part G, Journal of Aerospace Engineering, Sage. Vol. 227(10):1545-1555, DOI : 10.1177/0954410012460013
• M. Balesdent, N. Bérend et Ph. Dépincé (2012) Stagewise Multidisciplinary Design Optimization Formulation for Optimal Design of Expendable Launch Vehicles, Journal of Spacecraft and Rockets, AIAA. Vol. 49(4):720-730 DOI : 10.2541/1.52507
• M. Balesdent, N. Bérend, Ph. Dépincé et A. Chriette (2012) A Survey of Mutidisciplinary Design Optimization methods in Launch Vehicle Design, Structural and Multidisciplinary Optimization, Springer. Vol.45(5):619-642 DOI : 10.1007/s00158-011-0701-4
• M. Balesdent, N. Bérend et Ph. Dépincé (2010) Multidisciplinary Design Optimization of a multistage launch vehicle using flight phases decomposition, International Journal for Simulation and Multidisciplinary Design Optimization, EDP Sciences. Vol.4(3-4) :117-125 DOI :10.1051/ijsmdo/2010015

 

Autres articles et pre-prints arXiv

• Brevault, L., & Balesdent, M. (2023). Bayesian Quality-Diversity approaches for constrained optimization problems with mixed continuous, discrete and categorical variables. arXiv preprint arXiv:2310.05955.
• Gamot, J., Balesdent, M., Wuilbercq, R., Tremolet, A., Melab, N., & Talbi, E. G. (2023). A Vitual-Force Based Swarm Algorithm for Balanced Circular Bin Packing Problems. arXiv preprint arXiv:2306.01021.
• J. Pelamatti, L. Brevault, M. Balesdent, E.G. Talbi et Y. Guerin (2020) Bayesian optimization of variable-size design space problems arXiv preprint arXiv:2003.03300
• N.B. Price, M. Balesdent, S. Defoort, L. Le Riche, N.H. Kim, et R.T. Haftka, (2019). Safety-margin-based design and redesign considering mixed epistemic model uncertainty and aleatory parameter uncertainty. arXiv preprint arXiv:1904.08978.
• A. Hebbal, L. Brevault, M. Balesdent, E.G. Talbi, et N. Melab (2019). Bayesian Optimization using Deep Gaussian Processes. arXiv preprint arXiv:1905.03350.
• J.Pelamatti, L. Brevault, M. Balesdent, E.G. Talbi et Y. Guerin (2018) Efficient global optimization of constrained mixed variable problems, arXiv preprint arXiv:1806.03975
• S. Defoort, M. Balesdent, P. Klotz et al.  (2012) Multidisciplinary Aerospace System Design: Principles, Issues and Onera Experience, Aerospace Lab, Vol.4, doi:10.12762/2012.AL04-12

 

Conférences

• Mori, S., Arnoult, G., Balesdent, M., Brevault, L., Dubreuil, S., & Liauzun, C. (2024). Multi-fidelity reduced order surrogate modeling methodology applied to the multidisciplinary analysis of transonic strut-braced wing aircraft. In AIAA SCITECH 2024 Forum
• Mori, S., Arnoult, G., Balesdent, M., Brevault, L., Liauzun, C., & Dubreuil, S. (2023). Comparative study of multidisciplinary analysis of transonic strut-braced wing aircraft using different aerodynamic simulation fidelity levels. In EUCASS-CEAS 2023.
• J. Gamot, M. Balesdent, R. Wuilbercq, A. Tremolet, N. Melab, E.G. Talbi (2023) Two-Level Algorithm Combining Bayesian Optimization and Swarm Intelligence for Variable-Size Optimal Layout Problems, Genetic and Evolutionary Computation Conference, Lisbon, Portugal
• R. Espoeys, L. Brevault, M. Balesdent, S. Ricci, P. Mycek (2023) Multi-fidelity Sequential Bayesian Optimization and Reliability Assessment Method for the Design of Complex Systems, 5th ECCOMAS Thematic Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP), Athens, Greece
• E. Tormena, A.R. Silva Teixeira, L. Brevault, M. Balesdent, A. Urbano (2022) Multidisciplinary deisng analysis and optimization of launch vehicles including environmental impact, 9th European Conference for Aeronautical and Space Sciences, Lille, France
• M. Balesdent, L. Brevault, B. Paluch, R. Wuilbercq, S. Defoort, R. Thépot, B. Vieille (2022) Design of  fly-back reusable launch vehicle architecture using air-breathing propulsion, 9th European Conference for Aeronautical and Space Sciences, Lille, France
• J. Gamot, R. Wuilbercq, M. Balesdent, A. Tremolet, N. Melab, E.G. Talbi (2022) Component Swarm Optimization using Virtual Forces for Solving Layout Problems, 13th International Conference on Swarm Intelligence, Malaga, Spain
• C. Laboulfie, M. Balesdent, L. Brevault, F.X. Irisarri, J.F. Maire, L. Le Riche, S. Da Veiga (2022) Mixed-effects methods for material model calibration: influence of assumptions on parameter distributions, European Community on Computational Methods in Applied Sciences (ECCOMAS),  Oslo, Norway
• C. Laboulfie, M. Balesdent, L. Brevault, F.X. Irisarri, J.F. Maire, L. Le Riche, S. Da Veiga (2022) Sequential calibration of material model using mixed-effects, 25ème congrès français de la mécanique, Nantes
• L. Brevault, M. Balesdent (2022) All-At-Once formulation integrating pseudo-spectral optimal control for launch vehicle design and uncertainty quantification, 22nd ONERA DLR Aerospace Symposium, Hamburg, Germany
• R. Espoeys, M. Balesdent, S. Ricci, L. Brevault, P. Mycek  (2022) Overview and comparison of reliability analysis techniques based on different multi-fidelity Gaussian Processes, ASMO-UK 12 / ASMO-Europe 1 / ISSMO Conference on Engineering Design Optimization, Leeds, UK
• M. Balesdent (2022) Multiphysics system analysis and optimization under uncertainty, MASCOT-NUM annual meeting
• M. Balesdent (2021) System analysis and design in uncertainty, World Congress of Structural and Multidisciplinary Optimization, Boulder, USA
• J. Valderrama, L.Brevault, M. Balesdent, A. Urbano (2021) All-At-Once MDO formulation for coupled optimization of launch vehicle design and its trajectory using a pseudo spectral method, World Congress of Structural and Multidisciplinary Optimization, Boulder, USA
• L. Brevault, M. Balesdent (2021) Uncertainty quantification for multidisciplinary launch vehicle design using model order reduction and spectral methods, World Congress of Structural and Multidisciplinary Optimization, Boulder, USA
• C. Laboulfie, M. Balesdent, L. Brevault, S. da Veiga, F.X. Irisarri, R. Le Riche, J.F. Maire (2021) Calibration of material model using mixed-effects models, 4th International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP 2021)
• A Hebbal, L. Brevault, M. Balesdent, E.G. Talbi et N. Melab (2019) Multi-fidelity modeling using DGPs: Improvements and a generalization to varying input space dimensions, Bayesian Deep Learning Workshop, 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada
• G. Sarazin, J. Morio, A. Lagnoux, M. Balesdent et L. Brevault (2019) Sensitivity Analysis of Risk Assessment with Data-Driven Dependence Modeling, 29th European Safety and Reliability Conference, Septembre 2019, Hannover, Germany
• M. Balesdent, L. Brevault, B. Paluch, R. Wuilbercq, N. Subra, R. Thépot et A. Patureau de Mirand (2019) Design and optimization of glide-back reusable launch vehicle architectures, 8th European Conference For Aeronautics and Aerospace Sciences, Juillet  2019, Madrid, Spain
• L. Brevault, M. Balesdent, R. Wuilbercq, N. Subra, S. Oriol, C. Bonnal, O. Nailard, R. Bond et R. Varvill (2019) Conceptual design of a Two-Stage-To-Orbit vehicle using SABRE engines, 8th European Conference For Aeronautics and Aerospace Sciences, Juillet 2019, Madrid, Spain
• A. Hebbal, L. Brevault, M. Balesdent, E.-G. Talbi et N. Melab (2019) Multi-objective optimization using Deep Gaussian Processes:
  Application to Aerospace Vehicle Design, AIAA Scitech Conference, 7-11 Janvier, 2019, San Diego, USA
• J. Pelamatti, L. Brevault, M. Balesdent, E.-G. Talbi et Y. Guerin (2019) Surrogate model based optimization of constrained mixed
  variable problems: application to the design of a launch vehicle bottom skirt, AIAA Scitech Conference, 7-11 Janvier, 2019, San Diego, USA
• L. Brevault, M. Balesdent, A. Hebbal et A. Patureau de Mirand (2019) Surrogate model-based multi-objective MDO approach for partially Reusable Launch Vehicle design, AIAA Scitech Conference, 7-11 Janvier, 2019, San Diego, USA
• A. Hebbal, L. Brevault, M. Balesdent, E.-G. Talbi et N. Melab (2018) Multi-Disciplinary Design Multi-Objective Optimization of Aerospace Vehicles using Surrogate Models, International Workshop on Optimization and Learning : Challenges and Applications, 26 - 28 Février, 2018, Alicante, Espagne
• A. Hebbal, L. Brevault, M. Balesdent, E.-G. Talbi et N. Melab (2018)  Efficient Global Optimization using Deep gaussian Processes, IEEE Congress on Evolutionary Computation, 8-13 Juillet, 2018, Rio de Janeiro, Brésil
• J. Pelamatti, L. Brevault, M. Balesdent, E.-G. Talbi et Y. Guerin (2018) Surrogate model based optimization of constrained mixed variable problems, 8th International Conference on Bio inspired Optimization Methods  and their Applications, 16-18 Mai, 2018, Paris, France
• V. Chabridon, M. Balesdent, J.-M. Bourinet, J. Morio et N. Gayton (2018) Nonparametric adaptive importance sampling strategy for reliability assessment and sensitivity analysis under distribution parameter uncertainty – Application to a launch vehicle fallback zone estimation 10elmes journées Fiabilité des Matéroaix et des Structures, 27-28 mars, 2018, Bordeaux, France
• J. Pelamatti, L. Brevault, M. Balesdent, E.-G. Talbi et Y. Guerin (2017) How to deal with mixed-variable optimization problem : An overview of algorithms and formulation. Dans : Schumacher A., Vietor T., Fiebig S., Bletzinger KU., Maute K. (eds) Advances in Structural and Multidisciplinary Optimization. WCSMO 2017. Springer
• V. Chabridon, N. Gayton, J.-M. Bourinet, M. Balesdent et J. Morio (2017) Some Bayesian insights about the APTA method for statistical tolerance analysis. 23e Congrès Français de Mécanique, 28 Aout - 1er Septembre, 2017, Lille, France
• L. Brevault, M. Balesdent et J. Morio (2017) Rare event probability estimation in the presence of epistemic uncertainty. 10th International Conference on Mathematical Methods in Reliability, 3-6 Juillet, 2017, Grenoble, France
• L. Brevault, M. Balesdent et J. Morio (2017) Impact of modeling uncertainties on input probability distribution tails to rare event probability estimation, application to aerospace vehicle reliability assessment. 12th International Conference on Structural Safety & Reliability, 6-10 Août, 2017, Vienne, Autriche
• V. Chabridon, M. Balesdent, J.-M. Bourinet, J. Morio et N. Gayton  (2017) Reliability-based sensitivity analysis of aerospace systems under distribution parameter uncertainty using an augmented approach. 12th International Conference on Structural Safety & Reliability, 6-10 Août, 2017, Vienne, Autriche
• L. Brevault, M. Balesdent et S. Defoort (2016) Preliminary study on launcher design – an illustration of Onera’s knowledge and tools. 7th International Conference on Systems and Concurrent Engineering for Space Applications, 5-7 Octobre, 2016, Madrid, Espagne
• N. Price, M. Balesdent, S. Defoort, R. Le Riche, N.H. Kim et R. Haftka (2016) Simulating Future Test and Redesign Considering Epistemic Model Uncertainty.18th AIAA Non-Deterministic Approaches Conference, AIAA Science and Technology Forum and Exposition, 4-8 Janvier, 2016, San Diego, USA
• S. Lacaze, S. Missoum, L. Brevault et M. Balesdent (2015) A Sampling-based RBDO Algorithm with Local Refinement and Efficient Gradient Estimation. 12th International Conference on Applications of Statistics and Probability in Civil Engineering, 12-15 Juillet, 2015, Vancouver, Canada
• L. Brevault, M. Balesdent, N. Bérend et R. Le Riche (2015) Multi-level Hierarchical MDO formulation with functional coupling satisfaction under uncertainty, application to sounding rocket design. 11th ISSMO World Congress on Structural and Multidisciplinary Optimization, 7-12 Juin, 2015, Sydney, Australie
• L. Brevault, M. Balesdent, N. Bérend et R. Le Riche (2014) Decoupled UMDO formulation for interdisciplinary coupling satisfaction under uncertainty. 15th AIAA/ISSMO Multidisciplinary Analysis Optimization Conference.  16 - 20 Juin, 2014 Atlanta, USA
• T. Gorecki, H. Piet-Lahanier, J. Marzat and M. Balesdent (2013) Cooperative guidance of UAVs for area exploration with final target allocation, Proceedings of the 19th IFAC Symposium on Automatic Control in Aerospace,  2 - 6 Septembre, 2013, Würzburg, Germany
• L. Brevault, M. Balesdent, N. Bérend et R. Le Riche (2013) Challenges and future trends in Uncertainty-Based Multidisciplinary Design Optimization for space transportation system design, 5th European Conference for Aerospace Sciences, 1 – 4 Juillet, 2013, Munich, Germany
• L. Brevault, M. Balesdent, N. Bérend et R. Le Riche (2013) Comparison of different global sensitivity analysis methods for aerospace vehicle optimal design, 10th ISSMO World Congress on Structural and Multidisciplinary Optimization, 19-24 Mai, 2013, Orlando, USA
• M. Balesdent, N. Bérend et Ph. Dépincé (2011) New MDO approaches for Launch Vehicle Design. 4th European Conference for Aerospace Sciences,  4 – 8 Juillet, 2011, St Pétersbourg, Russia.

• M. Balesdent, N. Bérend et Ph. Dépincé (2011) MDO formulations and techniques adapted to multistage launch vehicle design, 9th ISSMO World Congress on Structural and Multidisciplinary Optimization. 13 – 17 Juin, 2011, Shizuoka, Japan.

• L. Planckaert, P. Coton et M. Balesdent (2010) Tools for dynamic adjustment of aircraft separations in wake vortices, 27th International Congress of the Aeronautical Sciences.  19 – 24 Septembre, 2010, Nice, France.

• M. Balesdent, N. Bérend et Ph. Dépincé (2010) Optimal Design of Expendable Launch Vehicles using Stage-Wise MDO Formulation, 13th AIAA/ISSMO Multidisciplinary Analysis Optimization Conference.   13 – 15 Septembre, 2010, Fort Worth, USA.

• M. Balesdent, N. Bérend et Ph. Dépincé (2010) Multidisciplinary Design Optimization of a multistage launch vehicle using flight phases decomposition, 3rd ASMDO International Conference on Multidisciplinary Design Optimization and Applications. 21 – 23 Juin, 2010, Paris, France

Encadrements

Thèses

En cours :

• Edimah Songo, Analyse de sensibilité pour systèmes multiphysiques (Directeur de thèse : S. Da Veiga, co-encadrants : L. Brevault, R. El-Amri (IFPEn), A. Spagnol (IFPEn))
• Lucas Baraton, Multidiscipinary Optimization for variable-size design space problem, application to space launchers. (Directrice de thèse : Annafederica Urbano, co-encadrants: L. Brevault)
• Lucas Brunel, Multi-Fidelity based machine learning approaches for uncertainty propagation of field variables, application to the design of aerospace vehicles (Directeur de thèse : R. Le Riche , co-encadrants : L. Brevault, B. Sudret)
• Shon Mori, Méthodologie de couplage aéro-structure pour la conception avant-projet avion (Directeur de thèse : M. Balesdent, co-encadrants : G. Arnoult, L. Brevault, S. Dubreuil, C. Liauzun)
• R. Espoeys,Optimisation multi-fidélité sous incertitudes, application à la conception de véhicules aérospatiaux (Directrice de thèse : S. Ricci (CERFACS), co-encadrants : L. Brevault, P. Mycek (CERFACS))

Soutenues :

• Juliette Gamot, Développement d’algorithmes d’optimisation de l’agencement interne pour l’analysemultidisciplinaire de véhicules aérospatiaux  (Directeurs de thèse : E.-G. Talbi, N. Melab, co-encadrant ONERA : A. Tremolet et R. Wuilbercq)
• Clément Laboulfie, Gestion des incertitudes pour l’identification de lois de comportement composites (Directeur de thèse : R. Le Riche, co-encadrants: J.F. Maire, F.X. Irisarri, S. Da Veiga (ENSAI))
• Gabriel Sarazin, Evaluation des méconnaissances des systèmes embarqués sur la retombée d'un étage de lanceur spatial (Directeur de thèse : J. Morio, A. Lagnoux co-encadrant ONERA : L. Brevault)
• Ali Hebbal, Methodologies for multiobjective parallel optimization, application to aerospace vehicle design (Directeurs de thèse : E.-G. Talbi, N. Melab, co-encadrant ONERA : L. Brevault)
• Julien Pelamatti, Optimisation multidisciplinaire de lanceurs avec prise en compte de choix technologiques (Directeur de thèse : E.-G. Talbi, co-encadrant ONERA : L. Brevault)
• Vincent Chabridon, Propagation d'incertitudes au sein de modèles coûteux en temps de calcul, application au secteur aérospatial (Directeurs de thèse  J. Morio, J.-M. Bourinet et N. Gayton), 2015 - 2018
• Nathaniel Price, Optimizing the safety margins governing a deterministic process while considering the effects of a future test and redesign on epistemic model uncertainty (Directeurs de thèse : R. Haftka, N.-H. Kim, R. Le Riche, co-encadrant ONERA : S. Defoort), 2014 - 2016
• Loïc Brevault, Optimisation multidisciplinaire sous incertitudes, application à la conception de lanceurs (Directeur de thèse R. Le Riche, co-encadrant ONERA : N. Bérend), 2013 - 2015

 

Contact

Chemin de la Hunière

FR-91761

PALAISEAU CEDEX

E-mail : mathieu(dot)balesdent(at)onera(dot)fr

tel:  01 80 38 66 08