Damage tolerance reliability analysis combining Kriging regression and support vector machine classification

Abstract Damage tolerance analysis associates a Fracture Mechanical model with the Failure Assessment Diagram to define the state of a space engine component. The reliability analysis treats the variability of numerical models assessing the probability of failure within Linear Elastic Fracture Mechanics (LEFM) hypotheses. However, these models, while providing quantitative information in the safe domain, give only qualitative information for failed components. This work proposes an original methodology to combine Kriging regression and the Support Vector Machine classification along with transition criteria between both approaches. To accurately describe the limit state, we define a specific enrichment strategy. The efficiency of the proposed methodology is illustrated on reference test cases.