AI-based Decision Support System for Heritage Aircraft Corrosion Prevention

Fuente: arXiv
Salvato in:
Dettagli Bibliografici
Autori principali: Kuchař, Michal, Fišer, Jaromír, Oswald, Cyril, Vyhlídal, Tomáš
Natura: Preprint
Pubblicazione: 2025
Soggetti:
Accesso online:
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
_version_ 1866909618714705920
author Kuchař, Michal
Fišer, Jaromír
Oswald, Cyril
Vyhlídal, Tomáš
author_facet Kuchař, Michal
Fišer, Jaromír
Oswald, Cyril
Vyhlídal, Tomáš
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2505_15462
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle AI-based Decision Support System for Heritage Aircraft Corrosion Prevention
Kuchař, Michal
Fišer, Jaromír
Oswald, Cyril
Vyhlídal, Tomáš
Systems and Control
Machine Learning
62C25
H.4.2; I.6.5
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.
title AI-based Decision Support System for Heritage Aircraft Corrosion Prevention
topic Systems and Control
Machine Learning
62C25
H.4.2; I.6.5
url https://arxiv.org/abs/2505.15462