Integrated structural design optimization of space vehicles with multidisciplinary constraints - Borwankar, Pranav; Kapania, Rakesh K.; Inoyama, Daisaku; Stoumbos, Tom (Aerospace science and technology, 2026)
•A novel multidisciplinary design optimization framework for composite spacecraft structures, leveraging a combination of commercial and open-source tools to facilitate easy industry implementation.•Integration of Structures, Thermal and Acoustic disciplines with various static and dynamic loading environments•Use of lamination parameters and mixed integer programming to simplify multi-modal and combinatorial design space for optimizing composite structures.•Extension of lamination parameters to heat transfer analysis in obtaining equivalent thermal conductivities. [Display omitted] The aerospace industry’s competitiveness in the global market relies heavily on the digital transformation of engineering design processes. Central to this transformation are Multidisciplinary Design Optimization (MDO) frameworks, which are pivotal in integrating different engineering disciplines and facilitating the optimization of complex systems. Specifically, a Multidisciplinary Structural Analysis and Design Optimization (MSADO) framework addresses interactions between structural responses. This paper introduces an MSADO framework tailored for spacecraft structures, leveraging commercial software tools and open-source Python libraries. The framework is exemplified through the simplified finite element modeling of a small spacecraft, showcasing its multidisciplinary design capabilities. Optimization is carried out for various launch vehicle and in-orbit loads, adhering to the GEVS, SMC, and MIL 810E standards. The proposed framework seamlessly integrates structural, thermal, and acoustic analyses to optimize overall spacecraft performance while adhering to multiple design constraints. The framework is applied to design a typical spacecraft structure by optimizing structural weight for required performance under varied static and dynamic loading conditions, both within the launch vehicle and in orbit. To enhance optimization performance, especially in scenarios involving composite laminates in the design, lamination parameter optimization and mixed integer programming are integrated into the framework by extending the lamination parameter formulations to facilitate multidisciplinary analysis, resulting in an 84% reduction in computational costs compared to direct fiber angle parameterization.