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Session: Session 1: Digital engineering I
Session starts: Monday 26 June, 11:10
Presentation starts: 11:50
Room: Theatre room: plenary

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Yan Bombardier (National Research Council Canada)
Guillaume Renaud (National Research Council Canada)
Min Liao (National Research Council Canada)

Abstract:
The National Research Council of Canada (NRC) has been developing an airframe digital twin (ADT) framework and tools to support structural life-cycle management for the Canadian Department of National Defence (DND). The overall goal of this framework is to improve the accuracy and efficiency of diagnosis and prognosis of the structural integrity of individual aircraft components in order to make better maintenance decisions. It relies on state-of-the-art structural analysis probabilistic modelling techniques, such as high-fidelity finite element modelling, advanced crack growth simulations, and quantitative risk assessment. It also provides the capability to periodically update the probabilistic inputs of these models as new information about the airframe becomes available (inspection results, individual aircraft usage, etc.). This paper provides an overview of the ADT framework being developed by NRC and presents recent developments made to improve its tools and methods. The developed methods and tools are demonstrated with a case study from the durability and damage tolerance life extension test of a retired CF-188 inboard leading edge flap (ILEF) carried out by NRC. For this case study, NRC monitored the risk at the blended and shot-peened ILEF transmission lugs critical radii using the ADT framework. Sensitivity studies were performed to assess the effects of assumptions about crack detection capabilities and initial damage state on the resulting probability of failure. This paper also presents a new statistical inference model that is used in the ADT framework to update the damage state of individual airframe components based on non-destructive inspection results. This model provides the ability to develop better physics-based models by segregating different initial damage types, e.g. pores, surface scratches, and/or pits, and updating their contributions as non-destructive inspection results are obtained. The initial results show that the current ADT framework provides a better probabilistic representation of the future state of aircraft fleets and allows more accurate risk-informed decision-making for individual aircraft component maintenance actions.