Model-Driven Dynamic Case Simulation for Exploration of Outcome Space

In the aerospace community, case studies and lessons learned are key sources of historical information for both system acquisition and systems engineering. However, traditional case studies do not illuminate the assumptions and decisions that led to the outcome, nor how the outcome would change (or not) if a different decision or assumption were made. To overcome this limitation, what is needed is a way to systemically explore the decision space of a historical case and then perturb the case by changing assumptions to assess the impact of those changes on the outcome space. This paper formalizes the representation of cases from historical case studies to illuminate key decision and tradeoffs that bear on the outcome. The overall approach combines domain ontology, formal representation of cases using model-based methods, tradeoff analyses techniques for alternative generation and evaluation, dashboard for monitoring, visualization, what-if intervention, and control of case execution, and data analytics. The domain ontology and case/system representation are to perturb assumptions and decisions, with case simulation-based analysis used to illuminate the impact of changes in decisions and assumptions on case outcomes.