Digital engineering initiatives in aerospace demand more than conventional finite element analyses; they require integrated, traceable, and systematic workflows that shorten iteration cycles, enable rapid trade-off studies, and ensure verification across the design process. FEAST (Finite Element Analysis of Structures)—an indigenous finite element software developed by VSSC, ISRO—provides structural analysis capabilities, but its native command structure is not directly compatible with automated, iterative design exploration. This limitation creates a gap between solver functionality and the needs of modern model-based engineering, where efficiency, reproducibility, and scalability are critical.
To address this gap, a unified workflow is proposed that links parametric geometry modeling, load-case management, solver execution, and results visualization in a seamless manner. The framework automates repetitive pre- and post-processing tasks, enables systematic evaluation of alternative configurations, and supports the inclusion of numerical methods for sensitivity analyses and optimization. By doing so, it reduces turnaround time, enables large-scale design-space exploration, and provides a structured foundation for optimization-driven aerospace design.
The approach is demonstrated on an adapter structure subjected to multiple static load cases and stringent natural frequency requirements. The workflow automates the evaluation of candidate designs, balancing mass–stiffness trade-offs while enforcing structural constraints. This facilitates the identification of configurations that achieve substantial mass reduction without compromising required safety margins, thereby highlighting the practical value of the framework in real-world aerospace applications.
Key contributions include a reusable interface that allows rapid re-analysis of modified designs, automated extraction of modal and stress metrics to support the constraint verification, and an auditable data structure linking model inputs, solver runs, and outputs to ensure complete traceability and verification. Beyond this case study, the framework establishes a scalable template for integrating indigenous solvers into digital engineering pipelines, thereby reducing design cycle time and enabling reproducible, verifiable results across complex aerospace systems.