Benefits of Non-Destructive Evaluation and Probabilistic Damage Tolerance Cosimulation for Fracture Risk Reduction

Abstract

In the context of the damage tolerance approach used to drive aircraft maintenance operations, it is essential to demonstrate the reliability of NDE inspections in detecting structural damage especially for additively manufactured components since this process produces components that may introduce material anomalies at any location within a component. The Probability Of Detection curve (POD) that links the probability to detect a detrimental flaw to its size is generally used as a key indicator for that purpose by giving the maximum flaw size that a NDE process can miss with a given level of probability and confidence. This information can then be used along with other inputs such as component geometries, mechanical properties, constraints, service and residual stresses and damage evolution speed to assess fracture risk and then adapt maintenance scenarios to optimize safety and component service life. NDE reliability and risk assessment are based on statistical indicators that need a large amount of data to provide reliable metrics. It is difficult to obtain such indicators using a purely empirical approach that is based on physical trials and measurements as it may involve many mock-ups and costly processes. Simulation tools can achieve this goal via their ability to include and precisely monitor many parameters as well as high computing capacities that are now available. The work presented in this paper involved cosimulations performed between the DARWIN® probabilistic damage tolerance software and the CIVA NDE simulation software. DARWIN computes fracture risk levels throughout a component, while CIVA can efficiently provide Probability Of Detection curves at different locations in a component and for various NDE methods. The presented application deals with a titanium gas turbine engine impeller disk and involves an Ultrasonic NDE inspection technique. It appears to be a very interesting approach to connect together NDE and Fracture mechanics simulations, two disciplines that generally work on their own. Indeed, DARWIN helps the user to determine detrimental flaw types, locations and sizes which are key inputs to develop an effective NDE inspection method. CIVA can provide location-specific POD curves that enable DARWIN to quantity the effect of dedicated NDE on potential risk reduction. This highlights the importance of NDE simulation for safety and helps to identify potential changes in the physical NDE process and the maintenance cycle that provide the best compromise between detection performance and cost.