Intelligent Black Box Verification, Validation, And Accreditation For Rotorcraft Performance Modeling

The paper addresses process and tool development in support of qualification assessments of performance models. Details are provided regarding developing enablers in the fields of data science, uncertainty quantification, and machine learning. Performance models are delivered for assessment in all different shapes, for different purposes, with different pedigrees. All or parts of these models may be proprietary. Some models are delivered without documentation and pedigree, referred to as black box models. Traditionally these gaps in information, if possible, are filled by time-consuming, resource-intensive work of subject matter experts (SMEs). New processes and tools are proposed for reducing this burden and providing direction for SME efforts. The new approach is exercised for validation of an AH-64 performance model. Efforts contrast new applications of high-powered computational tools with the long-accepted SME-driven methods to establish value and increase capabilities. Results indicate that emerging methodologies can provide valuable guidance without SME involvement.