Abstract
The design optimization of coupled systems requires the implementation of multidisciplinary design optimization techniques in order to obtain consistent and optimal solutions. The associated research topics include the development of optimization algorithms, computational frameworks, and multidisciplinary design optimization formulations. This paper presents a benchmarking of the combination of monolithic formulations and derivative computation techniques. The monolithic formulations include typical literature formulations as well as new normalized variable hybrid formulation. A novel test problem is proposed which consists in the sizing of a space launcher thrust vector control electro-mechanical actuator. Solving the single multidisciplinary coupling present in this problem is complex due to the possibility to face one, two, or no solutions depending on the external load and reducer gear ratio configuration. A larger scale version of this test problem is also proposed and tested by adding a high degree of freedom point-to-point trajectory. The tests are carried out in order to obtain typical performance criteria but also some proposed additional robustness criteria such as variation of the initial conditions or the external load scale. These additional criteria are particularly relevant in an industrial engineering design context where knowledge capitalization and reuse are sought. The most significant findings are the interesting performances of the new formulation in terms of computational cost and the robustness. Furthermore, the effect of the choice of derivative computation strategy on different performance criteria is assessed for the original and larger scale problem, and thus underlines the benefits of full analytic gradient-based optimization.
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The authors would like to acknowledge Safran and the French National Association of Research and Technology who funded the PhD thesis that produced most of the work presented in this paper.
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Replication of results
The results presented in this paper were generated by the source code available at the following Github repository: https://github.com/SizingLab/RoR_SAMO_paper_Benchmarking_monolythic_MDO_formulations.
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Delbecq, S., Budinger, M. & Reysset, A. Benchmarking of monolithic MDO formulations and derivative computation techniques using OpenMDAO. Struct Multidisc Optim 62, 645–666 (2020). https://doi.org/10.1007/s00158-020-02521-7
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DOI: https://doi.org/10.1007/s00158-020-02521-7