Repair tolerance assessment for aircraft composite structures using Bayesian updating

Abstract

Detection and repair of composite damage is crucial to ensure the safety and reliability of aircraft structures. A novel approach to quantitatively evaluate the repair tolerance of composite structures in civil aircraft based on Bayesian updating is presented. The method incorporates historical damage inspection data to determine the prior distribution of damage size, which is then updated with newly collected damage size data using Bayesian theory. Monte Carlo simulation is employed to investigate the probability of failure and estimate maintenance costs, considering various factors such as the frequency and timing of damage events, damage detection, structural strength, gust loads, and maintenance expenses throughout the lifecycle of composite structures. Safety and economic factors are considered to establish a lower threshold for repairs and an upper threshold for maintenance based on the occurrence of accidental impact damage. Verification of the effectiveness and feasibility of a quantitative assessment method for repair tolerance is conducted using damage statistics data from civil aircraft routes utilizing the structural skin panels of composite outer wing. The results demonstrate that the method proposed in conjunction with extensive simulations and full utilization of field damage inspection data can effectively simulate unexpected impact damage situations that may occur during civil aircraft service and evaluate the reliability and economic feasibility of the repair of structure. The research findings hold significant theoretical and practical value for the preparation of documents for continued airworthiness of composite structures, including structural repair manuals and maintenance programs.