Integrated Modeling and Error Budget Framework Development for Future Large Missions

Future space science missions will continue to push the limits of technical performance: larger, colder, more stable, more precise, more agile. So too will these missions push the limits of our ability to verify and validate their performance. Missions such as Chandra, JWST, and WFIRST have shown that analysis is a key tool in the verification and validation process. Yet even these missions have stretched the software and modeling capabilities to their limits. We propose here to study the state-of-the-practice of two analysis tools, specifically integrated structural-thermal-optical-control system models, and the use of detailed optical error budgets. We will identify capability gaps and recommend or develop new tools and methods to close those gaps. This study will be performed in the context of future mission concepts such as the Laser Interferometer Space Antenna (LISA), the Habitable Worlds Observatory (HWO), as well as Xray Probes.

Implementation of an advanced software framework to support Integrated Modeling will result in a number of benefits to engineering, science activities spanning the mission life cycle, from concept formulation through development and eventually operations. Rather than having to find information by traversing multiple and often-inconsistent documents, stakeholders will have access to a centralized, internally-consistent and authoritative system-level model describing the mission, spacecraft, payload, science objectives, requirements, data and more. For engineers and scientists involved in computational modeling and simulation efforts, supporting system development and mission operations, the ability to access all the necessary information electronically, via this system model, will lead to reduction in time and effort developing computational models to support simulations and analysis. This new software framework will enable rapid integration of various scientific and engineering discipline-specific modeling and simulation tools, in whatever combinations are required to support analysis objectives, to create automated workflows that can be exploited to support design trade studies, multidisciplinary design optimization, uncertainty quantification, and more. Analysts will spend less time creating custom "glue-ware" to connect tools, and more time concentrating on the mission, the design, and the analysis. Decision makers will get results more quickly. All stakeholders will gain more insight into the behavior and performance of complex systems, be able to better manage margins, reduce risk and/or reduce cost.

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