A Digital Engineering Quality Assurance Framework for Engineering Models and Simulation Data

To ensure the accuracy and reliability of engineering simulation models used towards Simulation-based Verification, it is crucial to implement robust model and data integrity quality controls. These controls are essential for verifying the context, configuration, and validity of simulation models. The Department of Defense (DoD) emphasizes the importance of Verification, Validation, and Accreditation (VV&A) of models and simulations, and has established guidelines and standards for VV&A. The use of metadata is crucial in supporting the VV&A process, as it provides context and provenance information about the model and simulation data. This paper proposes an automated digital engineering quality assurance framework for engineering models and simulation (M&S) data, building on existing research and industry standards. This computational framework integrates metadata, data quality assessment, uncertainty quantification, and VV&A to provide a comprehensive approach to ensuring the credibility and reliability of computational model and simulation results.