Abstract
There are no rigorous, generalizable models governing corrosion behavior analogous to, for example, the Navier-Stokes equations of fluid mechanics. Much of what is known about corrosion has been derived from case histories of actual failures and laboratory work. In this respect, the practice of corrosion failure analysis is very much like that of medical diagnosis: although we can simulate real-world phenomena in the laboratory, we tend to rely heavily on actual case data. Thus corrosion has served as an excellent domain in which to develop knowledge-based systems(KBS). Two recent surveys point to 57 KBS projects. Virtually all of them infer conclusions from rules distilled from previous experience.
Resume
Il n’y a pas de modèles généralisables et rigoureux qui gouvernent le comportement de la corrosion. Les faits connus de la corrosion sont identifiés souvent à partir de cas de faiblesse bien connus, autant qu’à partir de données recueillies dans les expériences de laboratoire. Bien que nous puissions simuler des phénomènes du monde réel en laboratoire, nous avons tendance à nous reposer sur l’enseignement des données des situations connues. Comme la médecine, la corrosion a pu être un excellent domaine de développement des systèmes à base de connaissances “SBC”. Deux études récentes ont mis en évidence l’existence de 57 projets SBC en corrosion. Virtuellement tous ces systèmes tirent des conclusions par inférence à partir des règles déduites d’expériences.
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References
American Society for Metals, Case Histories in Failure Analysis (1979)
During E.E., Corrosion Atlas — A Collection of Illustrated Case Histories, Elsevier Science Publishers (1991)
Corrosion of Metals and Alloys — Vocabulary
Shepard R.N., Multidimensional Scaling, Tree-Fitting, and Clustering, Science, Vol. 210, N° 24 (1980)
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© 1996 Springer-Verlag Berlin Heidelberg
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Sturrock, C.P., Bogaerts, W.F. (1996). Reasoning about Corrosion from Cases Instead of Rules. In: Dubois, JE., Gershon, N. (eds) Industrial Information and Design Issues. Data and Knowledge in a Changing World. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-80286-7_9
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DOI: https://doi.org/10.1007/978-3-642-80286-7_9
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