A comprehensive investigation of flexible and multi-dimensional simulation-based PoD analysis

This study presents a comprehensive investigation into the simulation-based reliability assessment of NDE inspections, thereby enabling efficient, flexible, and multi-dimensional Probability of Detection (PoD) analysis. Building on existing literature and incorporating several new aspects, a complete framework is proposed and its various components are thoroughly discussed. The framework integrates validated, physics-based computer simulations with Kriging meta-modeling and Monte-Carlo integration, rigorously addressing challenging, multi-dimensional parameter spaces and uncertainty quantification. It constitutes an alternative to the traditional a ˆ -versus- a method, which relies on oversimplifying statistical assumptions and is limited to one-dimensional PoD curves. While the Kriging-based approach provides a foundation for the more general stochastic case, the current research focuses on the simpler deterministic case as an initial step. An ultrasonic inspection example demonstrates this approach. First, a Finite Element model is validated against experimental results and its limitations are discussed. Then, the suggested framework is used to generate Probability of Detection (PoD) functions with uncertainty bounds highlighting its enhanced flexibility. Results are compared to ground-truth simulations, demonstrating the reliability of the analysis compared to traditional methods. Overall, the study takes a step forward towards the generation of a more efficient, robust, and adaptable NDE assessment, facilitating enhanced inspection design and confidence in reliability evaluations.