AI-based Decision Support System for Heritage Aircraft Corrosion Prevention
This addresses the specific challenge of multi-material corrosion prevention for aviation museums, but it is incremental as it builds on existing models and focuses on a narrow domain.
The paper tackles the problem of preserving heritage aircraft by developing a decision support system that integrates knowledge on degradation mechanisms for materials like ancient aluminum alloys and wood, tailored to museum storage conditions, and tests it on WWII aircraft in a Czech museum.
The paper presents a decision support system for the long-term preservation of aeronautical heritage exhibited/stored in sheltered sites. The aeronautical heritage is characterized by diverse materials of which this heritage is constituted. Heritage aircraft are made of ancient aluminum alloys, (ply)wood, and particularly fabrics. The decision support system (DSS) designed, starting from a conceptual model, is knowledge-based on degradation/corrosion mechanisms of prevailing materials of aeronautical heritage. In the case of historical aircraft wooden parts, this knowledge base is filled in by the damage function models developed within former European projects. Model-based corrosion prediction is implemented within the new DSS for ancient aluminum alloys. The novelty of this DSS consists of supporting multi-material heritage protection and tailoring to peculiarities of aircraft exhibition/storage hangars and the needs of aviation museums. The novel DSS is tested on WWII aircraft heritage exhibited in the Aviation Museum Kbely, Military History Institute Prague, Czech Republic.