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Automatic Evaluation Of Multidisciplinary Derivatives Using A Graph-Based Problem Formulation In Openmdao, Justin Gray, Tristan Hearn, Kenneth Moore, John Hwang, Joaquim Martins, Andrew Ning
Automatic Evaluation Of Multidisciplinary Derivatives Using A Graph-Based Problem Formulation In Openmdao, Justin Gray, Tristan Hearn, Kenneth Moore, John Hwang, Joaquim Martins, Andrew Ning
Faculty Publications
The optimization of multidisciplinary systems with respect to large numbers of design variables is best pursued using a gradient-based optimization together with a method that efficiently evaluates coupled derivatives, such as the coupled adjoint method. However, implementing such a method in a problem with more than a few disciplines is time consuming and error prone. To address this issue, we develop an automated procedure for assembling and solving the coupled derivative equations that takes into account the disciplinary couplings using the interdisciplinary dependency graph of the problem. The coupled derivatives can be computed completely analytically, if analytic derivatives are available …