| dc.description.abstract | As space-based precision-pointed telescopes continue to grow in scale and complexity, integrated models are increasingly relied upon to inform early design decisions and support system-level verification. When ground testing of full-system configurations is infeasible, integrated models, including structural-thermal-optical performance models, are essential for predicting performance and validating requirements across multidisciplinary, coupled domains. In early design phases, when uncertainty is high and design decisions have long-term implications for cost and schedule, it is especially important to understand which uncertain parameters most influence system performance. Global sensitivity analysis can help identify dominant uncertainty sources and inform decisions about model reduction, testing priorities, and resource allocation. However, the computational cost of applying global sensitivity analysis to integrated models often exceeds available resources. The presence of cross-disciplinary coupling between subsystem models further complicates analysis efforts. Coupled and dependent variables obscure how specific inputs influence system-level performance, limiting the ability to reduce model dimensionality or focus testing efforts on individual subsystems. There is a need for integrated modeling methodologies that enable tractable global sensitivity analysis of large, feedforward-coupled systems while preserving the accuracy needed to support early-phase design.
This thesis develops both exact and approximate methods for performing global sensitivity analysis on integrated models. A set of exact propagation techniques is introduced to compute end-to-end sensitivity indices when specific structural conditions are met, including functional linearity, non-interacting transforms, and monotonic intermediate mappings. These methods are evaluated using a suite of benchmark test cases that isolate when the exact sensitivity analysis method is valid and when structural assumptions begin to break down. A modular modeling framework is developed to compute exact or approximate end-to-end sensitivity indices and to enable automated mapping between disciplinary models in the integrated chain. The approach is also applied to a representative linearized structural-thermal-optical performance model, demonstrating how end-to-end global sensitivity analysis can be performed efficiently across thermal, structural, and optical subsystems.
To extend tractable sensitivity analysis to black-box models, several approximate strategies are introduced, including multifidelity surrogate modeling and statistical regression. These methods support both forward uncertainty propagation and variance-based global sensitivity analysis for structurally complex integrated models, without requiring full-system evaluation at every iteration. Together, the exact and approximate strategies developed in this work provide a foundation for scalable end-to-end global sensitivity analysis in early-phase design, where identifying influential parameters and constraining model complexity are essential for evaluating candidate architectures and informing mission decisions. | |
