Skip to main content
SpringerLink
Log in
Book cover

Expert Systems in Structural Safety Assessment pp 360–374Cite as

A.I.-Based Corrosion Risk Analysis in Oil Refinery Operation

  • Conference paper

Part of the book series: Lecture Notes in Engineering ((LNENG,volume 53))

Abstract

The assessment of corrosion and related risk behavior in oil refinery operation is both based on practical experience and basic understanding of the prevailing corrosion mechanisms. It was thought necessary to automate to a larger extent the process of corrosion risk analysis. This automated process would enable corrosion and material experts to give a faster and more uniform evaluation of corrosion risks. The usefulness of artificial intelligence techniques in this domain was investigated. Some preliminary studies have been made and prototypes built to demonstrate what can be done with state of the art technology. Right from the conception of the project, much attention was given to produce a useful working product.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Arents, H.C, Bogaerts, W.F.L. (1989). Use of Hypertext for Corrosion Analysis, this volume.

    Google Scholar 

  2. Vancoille, M.J.S., Bogaerts, W.F.L., Rijckaert, MJ. (1988). PRIME, The European Project on Expert Systems for Materials Selection, Proc. Corrosion’88, ed. NACE, Houston, Texas, USA

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Dept. MTM, Katholieke Universiteit Leuven, W. de Croylaan 2, Leuven, B-3030, Belgium

    Marc J. S. Vancoille (Faculty of Engineering) & Walter F. L. Bogaerts (Faculty of Engineering)

  2. Esso Refinery Antwerp Polderdijkweg, Antwerp, B-2030, Belgium

    Felix Perdieus

Authors
  1. Marc J. S. Vancoille
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Walter F. L. Bogaerts
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Felix Perdieus
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Staatliche Materialprüfungsanstalt (MPA), Universität Stuttgart, Pfaffenwaldring 32, Stuttgart 80, 7000, Germany

    Aleksandar S. Jovanović  & Karl F. Kussmaul  & 

  2. Institute for Systems Engineering JRC Ispra, Ispra (VA), I-21020, Italy

    Alfredo C. Lucia

  3. General Electric Company, CRD-K-1, 5C32A, Schenectady, NY, 12301, USA

    Piero P. Bonissone

Rights and permissions

Reprints and permissions

Copyright information

© 1989 Springer-Verlag Berlin, Heidelberg

About this paper

Cite this paper

Vancoille, M.J.S., Bogaerts, W.F.L., Perdieus, F. (1989). A.I.-Based Corrosion Risk Analysis in Oil Refinery Operation. In: Jovanović, A.S., Kussmaul, K.F., Lucia, A.C., Bonissone, P.P. (eds) Expert Systems in Structural Safety Assessment. Lecture Notes in Engineering, vol 53. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-83991-7_20

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-83991-7_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-51823-5

  • Online ISBN: 978-3-642-83991-7

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation