Gap-fill Methods for Estimating Fatigue Damage

The fatigue damage calculated for an aircraft by the Individual Aircraft Tracking (IAT) programs is dependent on the quality of input data. When the input data quality is poor or invalid, aircraft operators resort to gap-filling techniques to account for missing or invalid data. Invariably, conservative estimates of fatigue damage are obtained by imposing severe penalties for invalid or missing data, which leads to early retirement of aircraft when there is a large amount of gap-fill. In an environment where there is a demand to keep flying older aircraft, it becomes essential to assess the amount of gap-fill and the gap-fill technique used in the Individual Aircraft Tracking (IAT) programs to estimate fatigue damage for invalid or missing data. This paper first addresses common problems with the aircraft data and its causes. The paper then examines usage and damage based gap-fill techniques that are used in IAT programs with a focus on fatigue damage assessment and then provides relative merits of gap-fill techniques. The paper proposes a modified damage gap-fill method based on mitigating the fleet-wide risk. The application of the proposed gap-fill method is then illustrated for a hypothetical fleet of aircraft.