• Title/Summary/Keyword: Aircraft wash interval

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Wash Interval Optimization to Prevent Atmospheric Corrosion of Korean Aircrafts Made of Aluminum Alloys (알루미늄 합금 대기부식 예방을 위한 대한민국 공군 항공기 세척주기 최적화 연구)

  • Park, Won Dong;Gook, Phil Jun;Cho, Younho;Bahn, Chi Bum
    • Corrosion Science and Technology
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    • v.15 no.4
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    • pp.189-197
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    • 2016
  • It is a common practice to conduct periodic washes at designated intervals in order to prevent the atmospheric corrosion of aircraft. The wash interval depends on the atmospheric conditions, but the wash intervals set by the U.S. Air Force were widely adopted in Korea without detailed knowledge of the background data. Therefore, it is necessary to determine our own wash intervals representing the atmospheric and geographical conditions in Korea. This study analyzed previous wash interval algorithms and atmospheric data in Korea. New wash intervals are then proposed based on the corrosion rate equation in ISO-9223:2012. Atmospheric corrosion testing was conducted using 7075 and 1050 aluminum alloy specimens to verify the accuracy of the corrosion rate equation in ISO-9223:2012. Test results showed a reasonable agreement with the corrosion rates predicted by the equation.

Algorithm for Determining Aircraft Washing Intervals Using Atmospheric Corrosion Monitoring of Airbase Data and an Artificial Neural Network (인공신경망과 대기부식환경 모니터링 데이터를 이용한 항공기 세척주기 결정 알고리즘)

  • Hyeok-Jun Kwon;Dooyoul Lee
    • Corrosion Science and Technology
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    • v.22 no.5
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    • pp.377-386
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    • 2023
  • 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.