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Joaquim R. R. A. Martins is a Professor at the University of Michigan, where he heads the Multidisciplinary Design Optimization Laboratory (MDO Lab) in the Department of Aerospace Engineering. His research involves the development and application of MDO methodologies to the design of aircraft configurations, with a focus on high-fidelity simulations that take advantage of high-performance parallel computing. Before joining the University of Michigan faculty in September 2009, he was an Associate Professor at the University of Toronto Institute for Aerospace Studies, where from 2002 he held a Tier II Canada Research Chair in Multidisciplinary Optimization. Prof. Martins received his undergraduate degree in Aeronautical Engineering from Imperial College, London, with a British Aerospace Award. He obtained both his M.Sc. and Ph.D. degrees from Stanford University, where he was awarded the Ballhaus prize for best thesis in the Department of Aeronautics and Astronautics. He has been a keynote speaker at several conferences including the International Forum on Aeroelasticity and Structural Dynamics (2007), the Aircraft Structural Design Conference (2010), the SIAM Conference on Optimization (2014), the EUROGEN Conference (2017), and the AIAA Aviation Forum (2018). He has received the Best Paper Award in the AIAA Multidisciplinary Analysis and Optimization Conference four times (2002, 2006, 2012, and 2014). He was a member of the AIAA MDO Technical Committee (2006–2018.) and was the technical co-chair for the 2008 AIAA Multidisciplinary Analysis and Optimization Conference.. He has served as Associate Editor for the AIAA Journal, and Optimization and Engineering. He is currently an Associate Editor for the Journal of Aircraft, and Structural and Multidisciplinary Optimization.
Online Profiles
orcid.org/0000-0003-2143-1478Education
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Ph.D, Nov 2002, Stanford University, Dept. of Aeronautics and Astronautics
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M.Sc., Jun 1997, Stanford University, Dept. of Aeronautics and Astronautics
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M.Eng., Jun 1995, Imperial College, Dept. of Aeronautics, London, UK(Final project at Technion—Israel Institute of Technology, Faculty of Aerospace Engineering)
Keynote Presentations
- AIAA Aviation MDO Keynote, Atlanta, GA, Jun 2018
- Workshop on MDO for Industrial Applications in Aeronautics, Braunschweig, Germany, Oct 2017
- EUROGEN Conference, Madrid, Spain, Sep 2017
- Plenary speaker, MOPTA Conference, Bethlehem, PA, Aug 2017
- Congress on Numerical Methods in Engineering, Lisbon, Portugal, Jun 2015
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International Conference on Engineering and Applied Sciences Optimization, Kos, Greece, Jun 2014 (Semi-plenary).
- SIAM Conference on Optimization, San Diego, May 2014
- Aircraft Structural Design Conference, Royal Aeronautical Society, London, UK, Oct 2010
- International Forum on Aeroelasticity and Structural Dynamics, Stockholm, Sweden, Jun 2007
Honors and Awards
- Fellow, Royal Aeronautical Society, 2019.
- AIAA Applied Aerodynamics Best Paper, 2019
- Marie Skłodowska-Curie Fellow, 2015–2016
- Best Paper Award, 15th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Sep 2014
- Best Paper Award, 14th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Sep 2012
- Best Paper Award, 11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Sep 2006
- Canada Research Chair in Multidisciplinary Design Optimization (Tier II), 2003–2009
- Ballhaus Prize for Best Thesis in the Department of Aeronautics, Stanford University, Jun 2003
- Best Paper Award, 9th AIAA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, Sep 2002
- Praxis XXI Scholarship, 1997–2001
- US–Norway Fulbright Foundation Stipend, 1996–1997
- British Aerospace Award, May 1995
Full CV [PDF]
Publications
Journal Articles
. A Jacobian-free approximate Newton--Krylov startup strategy for RANS simulations. Journal of Computational Physics. In Press .
Yildirim2019b-A Jacobian-free approximate Newton--Krylov startup strategy for RANS simulations.pdf (3.84 MB)
DOI DOI:10.1016/j.jcp.2019.06.018
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Yildirim2019b-A Jacobian-free approximate Newton--Krylov startup strategy for RANS simulations.pdf (3.84 MB)
DOI DOI:10.1016/j.jcp.2019.06.018
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. Electric, Hybrid, and Turboelectric Fixed-Wing Aircraft: A Review of Concepts, Models, and Design Approaches. Progress in Aerospace Sciences. 2019 ;104:1--19. Brelje2019-Electric, Hybrid, and Turboelectric Fixed-Wing Aircraft A Review_preprint.pdf (2.29 MB)
DOI DOI:10.1016/j.paerosci.2018.06.004
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Brelje2019-Electric, Hybrid, and Turboelectric Fixed-Wing Aircraft A Review_preprint.pdf (2.29 MB)
DOI DOI:10.1016/j.paerosci.2018.06.004
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. RANS-Based Aerodynamic Shape Optimization of a Strut-Braced Wing with Overset Meshes. Journal of Aircraft [Internet]. 2019 ;56:217-227. Available from: https://arc.aiaa.org/doi/abs/10.2514/1.C034934 sbw2018_preprint.pdf (11.18 MB)
DOI DOI:10.2514/1.C034934
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sbw2018_preprint.pdf (11.18 MB)
DOI DOI:10.2514/1.C034934
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. OpenMDAO: An open-source framework for multidisciplinary design, analysis, and optimization. Structural and Multidisciplinary Optimization. 2019 ;59(4):1075--1104. OpenMDAO_preprint.pdf (2.75 MB)
For a quick overview of what OpenMDAO is and what it does, read the introduction, the overview of applications (Sec. 7, especially Table 13), and the conclusions (Sec. 8). Potential OpenMDAO users should also read Sec. 3, which explains the basic usage and features through a simple example. The rest of the paper provides a background on MDO frameworks and the history of OpenMDAO development (Sec. 2), the theory behind OpenMDAO (Sec. 4), and the details of the major new contributions in OpenMDAO V2 in terms of multidisciplinary solvers (Sec. 5) and coupled derivative computation (Sec. 6).
DOI DOI:10.1007/s00158-019-02211-z
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OpenMDAO_preprint.pdf (2.75 MB)
For a quick overview of what OpenMDAO is and what it does, read the introduction, the overview of applications (Sec. 7, especially Table 13), and the conclusions (Sec. 8). Potential OpenMDAO users should also read Sec. 3, which explains the basic usage and features through a simple example. The rest of the paper provides a background on MDO frameworks and the history of OpenMDAO development (Sec. 2), the theory behind OpenMDAO (Sec. 4), and the details of the major new contributions in OpenMDAO V2 in terms of multidisciplinary solvers (Sec. 5) and coupled derivative computation (Sec. 6).
DOI DOI:10.1007/s00158-019-02211-z
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. Multimodality in Aerodynamic Wing Design Optimization. AIAA Journal. 2019 . bons2019a_preprint.pdf (4.4 MB)
DOI DOI:10.2514/1.J057294
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bons2019a_preprint.pdf (4.4 MB)
DOI DOI:10.2514/1.J057294
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. High-fidelity Aerostructural Optimization of Tow-steered Composite Wings. Journal of Fluids and Structures [Internet]. 2019 ;88:122-147. Available from: https://www.sciencedirect.com/science/article/pii/S0889974618306340?via%3Dihub Brooks2019-High-fidelity Aerostructural Optimization of Tow-steered Composite Wings.pdf (14.71 MB)
DOI DOI:10.1016/j.jfluidstructs.2019.04.005
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Brooks2019-High-fidelity Aerostructural Optimization of Tow-steered Composite Wings.pdf (14.71 MB)
DOI DOI:10.1016/j.jfluidstructs.2019.04.005
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. Robust aerodynamic shape optimization–-from a circle to an airfoil. Aerospace Science and Technology. 2019 ;87:48–61. He2019-Robust aerodynamic shape optimization---from a circle to an airfoil.pdf (14.02 MB)
DOI DOI:10.1016/j.ast.2019.01.051
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He2019-Robust aerodynamic shape optimization---from a circle to an airfoil.pdf (14.02 MB)
DOI DOI:10.1016/j.ast.2019.01.051
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. Impact of Morphing Trailing Edge on Mission Performance for the Common Research Model. Journal of Aircraft. 2019 ;56:369–384.
DOI DOI:10.2514/1.C034967
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. Viscous Fluid Structure Interaction Response of Composite Hydrofoils. Composite Structures. 2019 ;212:571–585. Liao2019a_preprint.pdf (4.15 MB)
DOI DOI:10.1016/j.compstruct.2019.01.043
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Liao2019a_preprint.pdf (4.15 MB)
DOI DOI:10.1016/j.compstruct.2019.01.043
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. High-fidelity design-allocation optimization of a commercial aircraft maximizing airline profit. Journal of Aircraft. 2019 . hwang_AMD_preprint.pdf (4.1 MB)
(In press)
DOI DOI:10.2514/1.C035082
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hwang_AMD_preprint.pdf (4.1 MB)
(In press)
DOI DOI:10.2514/1.C035082
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. Experimental Investigation of a Hydrofoil Designed via Hydrostructural Optimization. Journal of Fluids and Structures. 2019 ;84:243–262. NG_JFS_2017.pdf (27.9 MB)
DOI DOI:10.1016/j.jfluidstructs.2018.10.010
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NG_JFS_2017.pdf (27.9 MB)
DOI DOI:10.1016/j.jfluidstructs.2018.10.010
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. A Python surrogate modeling framework with derivatives. Advance in Engineering Software. 2019 . preprint_SMT.pdf (1.99 MB)
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preprint_SMT.pdf (1.99 MB)
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. Flutter and Post-Flutter Constraints in Aircraft Design Optimization. Progress in Aerospace Sciences. 2019 . Jonsson2019-Flutter-and-Post-Flutter-Constraints-in-Aircraft-Design-Optimization-preprint.pdf (576.98 KB)
DOI DOI:10.1016/j.paerosci.2019.04.001
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Jonsson2019-Flutter-and-Post-Flutter-Constraints-in-Aircraft-Design-Optimization-preprint.pdf (576.98 KB)
DOI DOI:10.1016/j.paerosci.2019.04.001
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. Effective Adjoint Approaches for Computational Fluid Dynamics. Progress in Aerospace Sciences. 2019 . Kenway2019-Effective Adjoint Approaches for Computational Fluid Dynamics.pdf (2.78 MB)
The meshes, configurations, and run scripts used in this paper are avaiable at Mendeley Data: http://dx.doi.org/10.17632/w4hsj8wzm8
DOI DOI:10.1016/j.paerosci.2019.05.002
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Kenway2019-Effective Adjoint Approaches for Computational Fluid Dynamics.pdf (2.78 MB)
The meshes, configurations, and run scripts used in this paper are avaiable at Mendeley Data: http://dx.doi.org/10.17632/w4hsj8wzm8
DOI DOI:10.1016/j.paerosci.2019.05.002
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. Aerothermal Optimization of a Ribbed U-Bend Cooling Channel Using the Adjoint Method. International Journal of Heat and Mass Transfer. 2019 . UBend_Aerothermal_Opt_Preprint.pdf (6.48 MB)
In press
DOI DOI:10.1016/j.ijheatmasstransfer.2019.05.075
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UBend_Aerothermal_Opt_Preprint.pdf (6.48 MB)
In press
DOI DOI:10.1016/j.ijheatmasstransfer.2019.05.075
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. High-Reynolds number transitional flow simulation via parabolized stability equations with an adaptive RANS solver. Aerospace Science and Technology. 2019 ;91. Halila_AST_2019b_preprint.pdf (913.08 KB)
DOI DOI:10.1016/j.ast.2019.05.018
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Halila_AST_2019b_preprint.pdf (913.08 KB)
DOI DOI:10.1016/j.ast.2019.05.018
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. Data-driven Constraint Approach to Ensure Low-speed Performance in Transonic Aerodynamic Shape Optimization . Aerospace Science and Technology. 2019 . DataDrivenCon_JichaoLi.pdf (17.79 MB)
DOI DOI:10.1016/j.ast.2019.06.008
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DataDrivenCon_JichaoLi.pdf (17.79 MB)
DOI DOI:10.1016/j.ast.2019.06.008
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. Design Optimization for Self-propulsion of a Bulk Carrier Hull Using a Discrete Adjoint Method. Computers & Fluids. 2019 . Hull_Opt_Paper.pdf (5.64 MB)
In press
DOI DOI:10.1016/j.compfluid.2019.104259
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Hull_Opt_Paper.pdf (5.64 MB)
In press
DOI DOI:10.1016/j.compfluid.2019.104259
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. Tilt-wing eVTOL takeoff trajectory optimization. Journal of Aircraft. 2019 . eVTOL_preprint.pdf (999.68 KB)
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eVTOL_preprint.pdf (999.68 KB)
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. A computational architecture for coupling heterogeneous numerical models and computing coupled derivatives. ACM TOMS. 2018 ;44(4). paper_mdolab.pdf (986.89 KB)
DOI DOI:10.1145/3182393
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paper_mdolab.pdf (986.89 KB)
DOI DOI:10.1145/3182393
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