pyMDO: A Framework for High-Fidelity Multi-Disciplinary Optimization

This paper presents a new approach to the software architecture of a high-fidelity multidisciplinary design framework that facilitates the reuse of existing components, the addition of new ones, and the scripting of MDO procedures. As a first step towards this goal, we implement the necessary components of a high-fidelity aero-structural design environment for complete aircraft configurations, and demonstrate them with two separate aero-structural analyses: a supersonic jet and a launch vehicle. At the core of the framework is an aero-structural solver that uses high-fidelity models for both disciplines as well as an accurate coupling procedure. The Euler or Navier–Stokes equations are solved for the aerodynamics and a detailed finite-element model is used for the primary structure. Rather than focusing on the actual design method and results, this paper emphasizes the role that sound software development environments can play in the creation of complex high-fidelity design optimization applications. In particular, we describe lessons learned during the course of this experience using the Python programming language, the development cost incurred in comparison with a traditional, Fortran 90/95, C, or C++ based development method, and the impact that this type of approach can have on both the establishment of high-and multi-fidelity design environments and in the productivity of research groups in academic settings.