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Received: December 05, 2022; Revised: April 03, 2023; Accepted: June 13, 2023
Abstract: Aircraft washing is performed periodically for corrosion control. Currently, the aircraft washing interval is qualitatively set according to the geographical conditions of each base. We developed a washing interval determination algorithm based on atmospheric corrosion environment monitoring data at the Republic of Korea Air Force (ROKAF) bases and United States Air Force (USAF) bases to determine the optimal interval. The main factors of the washing interval decision algorithm were identified through hierarchical clustering, sensitivity analysis, and analysis of variance, and criteria were derived. To improve the classification accuracy, we developed a washing interval decision model based on an artificial neural network (ANN). The ANN model was calibrated and validated using the atmospheric corrosion environment monitoring data and washing intervals of the USAF bases. The new algorithm returned a three-level washing interval, depending on the corrosion rate of steel and the results of the ANN model. A new base-specific aircraft washing interval was proposed by inputting the atmospheric corrosion environment monitoring results of the ROKAF bases into the algorithm.