Charles F Buynak

Aging Aircraft NDE: Capabilities, Challenges, and Opportunities

US Air Force aircraft are managed by Damage Tolerance Assessment (DTA) and Nondestructive Evaluation (NDE) plays a critical role in insuring their flight safety. This paper provides an overview of current NDE capabilities for aircraft structures. The potential migration to Condition‐Based Maintenance (CBM) will require NDE to evolve from detection of defects to characterization of their location and size. This represents multiple significant challenges as aircraft have many material and geometry factors that complicate this analysis. This paper provides a strategy to resolve these factors.

CASE STUDIES FOR MODEL‐ASSISTED PROBABILISTIC RELIABILITY ASSESSMENT FOR STRUCTURAL HEALTH MONITORING SYSTEMS

This paper describes progress on the development of a protocol and presents several case studies for model‐assisted probabilistic reliability assessment of structural health monitoring (SHM) technologies. The design and progress of an experimental demonstration study is presented highlighting the protocol and test plan. A simulation‐based study for an SHM system incorporating vibration methods is also introduced to demonstrate the protocol process. Probability of detection and probability of correct characterization curves were generated for different transducer locations providing key insight on sensor placement and expected detection and characterization performance.

Demonstration study for reliability assessment of SHM systems incorporating model-assisted probability of detection approach

This paper presents the results of a demonstration featuring the application of a validation protocol to a vibration-based structural damage sensing system. The results of the full validation study highlight the general protocol feasibility, emphasize the importance of evaluating key application characteristics prior to the POD study, and demonstrate an approach to quantify varying sensor durability on the POD performance. Challenges remain to properly address long time-scale effects with accelerated testing and large testing requirements due to the independence of the inspection of each flaw location.

MODEL‐ASSISTED PROBABILISTIC RELIABILITY ASSESSMENT FOR STRUCTURAL HEALTH MONITORING SYSTEMS

This paper describes a model‐assisted probabilistic methodology to ensure the reliability of SHM systems for damage detection, localization, and sizing. A hierarchical approach is presented that attempts to minimize the number of samples, the length of time, and degree of full‐scale testing required for statistically meaningful characterization results. The feasibility of applying this approach to typical sensing methods found in SHM systems is investigated, and additional challenges concerning model reliability and uncertainty propagation are addressed.