Nastran Integration for MBSA and E Framework Development and Assessment

The development of high-fidelity multidisciplinary analysis and optimization (MDAO) capabilities is essential for advancing modern aerospace vehicle design. Traditional workflows often suffer from limited interoperability between structural solvers, aerodynamic tools, and optimization frameworks. To address these limitations, this project focuses on integrating NASTRAN, a structural solver, into the OpenMDAO framework. This effort was conducted under NASA Contract 80GRC023CA047 by M4 Engineering, Inc., as part of the broader initiative to enhance Model-Based Systems Analysis and Engineering (MBSA&E) capabilities. The primary objective of the project was to develop a robust, reusable, and modular Python-based interface that allows NASTRAN to interface within OpenMDAO workflows and improve structural optimization capabilities. This enables engineers to leverage NASTRAN's structural analysis and sensitivity capabilities while benefiting from OpenMDAO's flexibility and advanced optimization drivers. In support of this objective, multiple demonstration models were created across various NASTRAN solution sequences (SOLs), including static, aeroelastic, flutter, and buckling analyses. These models were used to evaluate the accuracy, robustness, and computational performance of the integration. Additionally, capabilities were developed to extract sensitivity data, aggregate constraint outputs, and streamline the generation of OpenMDAO components from existing NASTRAN input decks. The work described herein also included integration of third-party aerodynamic tools (e.g., transonic CFD solvers and GROM) with OpenMDAO, development of representative aircraft configurations such as the truss-braced wing (TTBW) and blended-wing body (BWB), and final deployment into NASA's Aviary conceptual design framework. The outcomes of this project provide a foundation for future multidisciplinary optimizations using high-fidelity structural models and demonstrates some of the challenges.