Corrosion prediction for preventive protection of aircraft heritage

Abstract The paper presents a study on corrosion prediction for preventive aeronautical heritage protection, considering the aeronautical heritage stored or exhibited in an aviation museum. For the purpose of the study, the hangar with exhibited historical aircraft of significant cultural and societal value is located in the Aviation Museum Kbely, Prague, Czech Republic. Until now, such a preventive approach to protecting the aircraft heritage constituted from ancient aluminum alloys, in particular, has not been presented rigorously. Monitoring the hangar meteorological, pollution, and environmental data are acquired and interrelated with measured corrosion data to find a statistical model describing atmospheric corrosion in the hangar environment. The statistical model searched represents a Gaussian process based on a likelihood approach. As a result, the Gaussian process model is regressed to predict the corrosion of aluminum alloy-based artifacts in the monitored hangar with the marginal likelihood that is compared to machine learning-based prediction. Finally, it is shown that atmospheric corrosion is accurately predicted only when, among others, a synergistic effect of airborne pollutants and wind speed is considered.