These developments make it possible to advance the state-of-the-art in MDO, but other more specific developments are needed. Since then, numerical simulations have advanced in all disciplines, and the power of computer hardware has increased dramatically. MDO was first conceived to solve aircraft design problems, where disciplines such as aerodynamics, structures, and controls are tightly coupled and require design trade-offs (Haftka 1977). MDO is sometimes referred to as MDAO (multidisciplinary analysis and optimization) to emphasize that the coupled analysis is useful on its own. Second, it performs the simultaneous optimization of all design variables, taking into account the coupling and the interdisciplinary design trade-offs. First, it performs the coupled simulation of the engineering system, taking into account all the interdisciplinary interactions. Multidisciplinary design optimization (MDO) arose from the need to simulate and design complex engineering systems involving multiple disciplines. Design optimization-the use of numerical optimization techniques with engineering simulation-has emerged as a way of incorporating simulation into the design cycle. Simulations are often used within an engineering design cycle to inform design choices. Numerical simulations of engineering systems have been widely developed and used in industry and academia. 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. 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. We demonstrate the framework’s efficiency by benchmarking scalable test problems. OpenMDAO also provides a framework for computing coupled derivatives efficiently and in a way that exploits problem sparsity. 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.
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.
ANALYTIC SOLVER PLATFORM 2016 TYPE LIBRARY FULL
While various MDO software frameworks exist, none of them take full advantage of state-of-the-art algorithms to solve coupled models efficiently. Multidisciplinary design optimization (MDO) is concerned with solving design problems involving coupled numerical models of complex engineering systems.
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