Abstract:
Ever-increasing modeling and simulation capabilities and the desire to use simulations in support of system qualification, regulatory compliance, and other critical decision-making roles, raises the bar on the need for rigorous V&V of all aspects of the models used to create the simulation data. US Department of Defense Directives and Instructions, and emerging regulatory and industry standards on Modeling and Simulation in a Digital Engineering context require rigorous M&S Verification, Validation, and Accreditation (M&S VV&A). These specifications aim to create trusted and credible simulation data that can be used in critical decision-making roles on complex systems. Implementing a well-defined, structured, model-based and standards-based M&S VV&A Process early in the program lifecycle facilitates collaboration and documented buy-in on M&S VV&A for program with customers and/or regulatory agencies. This collaboration increases acceptance throughout the program and product lifecycles. This paper describes how Model-Based Systems Engineering tools and Digital Engineering ecosystems can support the M&S VV&A Process. The model-based construct facilitates creating metrics dashboards, leveraging model-based artifacts for improved communication of M&S VV&A status, quality, maturity, and completeness.