OpenMDAO: an open-source framework for multidisciplinary design, analysis, and optimization

Multidisciplinary design optimization (MDO) is concerned with solving design problems involving coupled numerical models of complex engineering systems. While various MDO software frameworks exist, none of them take full advantage of state-of-the-art algorithms to solve coupled models efficiently. F...

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Published in:	Structural and multidisciplinary optimization Vol. 59; no. 4; pp. 1075 - 1104
Main Authors:	Gray, Justin S., Hwang, John T., Martins, Joaquim R. R. A., Moore, Kenneth T., Naylor, Bret A.
Format:	Journal Article
Language:	English
Published:	Berlin/Heidelberg Springer Berlin Heidelberg 01.04.2019 Springer Nature B.V
Subjects:	Algorithms Computational Mathematics and Numerical Analysis Design analysis Design optimization Engineering Engineering Design Multidisciplinary design optimization Numerical models Open source software Research Paper Theoretical and Applied Mechanics Topology optimization Trajectory optimization Wing design Derivative computation Coupled systems Adjoint methods Sensitivity analysis Complex systems Multidisciplinary design optimization Python
ISSN:	1615-147X, 1615-1488
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Abstract	Multidisciplinary design optimization (MDO) is concerned with solving design problems involving coupled numerical models of complex engineering systems. While various MDO software frameworks exist, none of them take full advantage of state-of-the-art algorithms to solve coupled models efficiently. Furthermore, there is a need to facilitate the computation of the derivatives of these coupled models for use with gradient-based optimization algorithms to enable design with respect to large numbers of variables. In this paper, we present the theory and architecture of OpenMDAO, an open-source MDO framework that uses Newton-type algorithms to solve coupled systems and exploits problem structure through new hierarchical strategies to achieve high computational efficiency. OpenMDAO also provides a framework for computing coupled derivatives efficiently and in a way that exploits problem sparsity. We demonstrate the framework’s efficiency by benchmarking scalable test problems. We also summarize a number of OpenMDAO applications previously reported in the literature, which include trajectory optimization, wing design, and structural topology optimization, demonstrating that the framework is effective in both coupling existing models and developing new multidisciplinary models from the ground up. Given the potential of the OpenMDAO framework, we expect the number of users and developers to continue growing, enabling even more diverse applications in engineering analysis and design.
AbstractList	Multidisciplinary design optimization (MDO) is concerned with solving design problems involving coupled numerical models of complex engineering systems. While various MDO software frameworks exist, none of them take full advantage of state-of-the-art algorithms to solve coupled models efficiently. Furthermore, there is a need to facilitate the computation of the derivatives of these coupled models for use with gradient-based optimization algorithms to enable design with respect to large numbers of variables. In this paper, we present the theory and architecture of OpenMDAO, an open-source MDO framework that uses Newton-type algorithms to solve coupled systems and exploits problem structure through new hierarchical strategies to achieve high computational efficiency. OpenMDAO also provides a framework for computing coupled derivatives efficiently and in a way that exploits problem sparsity. We demonstrate the framework’s efficiency by benchmarking scalable test problems. We also summarize a number of OpenMDAO applications previously reported in the literature, which include trajectory optimization, wing design, and structural topology optimization, demonstrating that the framework is effective in both coupling existing models and developing new multidisciplinary models from the ground up. Given the potential of the OpenMDAO framework, we expect the number of users and developers to continue growing, enabling even more diverse applications in engineering analysis and design.
Author	Gray, Justin S. Martins, Joaquim R. R. A. Moore, Kenneth T. Naylor, Bret A. Hwang, John T.
Author_xml	– sequence: 1 givenname: Justin S. surname: Gray fullname: Gray, Justin S. email: justin.s.gray@nasa.gov organization: NASA Glenn Research Center – sequence: 2 givenname: John T. surname: Hwang fullname: Hwang, John T. organization: University of California, San Diego – sequence: 3 givenname: Joaquim R. R. A. orcidid: 0000-0003-2143-1478 surname: Martins fullname: Martins, Joaquim R. R. A. organization: Department of Aerospace Engineering, University of Michigan – sequence: 4 givenname: Kenneth T. surname: Moore fullname: Moore, Kenneth T. organization: DB Consulting Group (NASA Glenn Research Center) – sequence: 5 givenname: Bret A. surname: Naylor fullname: Naylor, Bret A. organization: DB Consulting Group (NASA Glenn Research Center)
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Snippet	Multidisciplinary design optimization (MDO) is concerned with solving design problems involving coupled numerical models of complex engineering systems. While...
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SubjectTerms	Algorithms Computational Mathematics and Numerical Analysis Design analysis Design optimization Engineering Engineering Design Multidisciplinary design optimization Numerical models Open source software Research Paper Theoretical and Applied Mechanics Topology optimization Trajectory optimization Wing design
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Title	OpenMDAO: an open-source framework for multidisciplinary design, analysis, and optimization
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