Bayesian Network Modeling of Corrosion - Sridhar, Narasi; (ed.) - Prospero Internet Bookshop

 
Product details:

ISBN13:9783031561276
ISBN10:3031561279
Binding:Hardback
No. of pages:338 pages
Size:235x155 mm
Language:English
Illustrations: 7 Illustrations, black & white; 140 Illustrations, color
658
Category:

Bayesian Network Modeling of Corrosion

 
Edition number: 2024
Publisher: Springer
Date of Publication:
Number of Volumes: 1 pieces, Book
 
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EUR 181.89
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  Piece(s)

 
Short description:

This book represents a compilation of experience from a slate of experts involved in developing and deploying Bayesian Networks (BN) for corrosion management. The contributors describe how probability distributions can be developed for corroding systems and BN can be applied as an ideal framework to deal with corrosion risk. Corrosion can develop suddenly and grow rapidly after a long incubation period and take many non-uniform aspects, including pitting and stress corrosion cracking, that cannot be mitigated by simply bulking up the system. They also describe how complex engineering structures and systems are influenced by many natural and engineering factors that come together in myriad ways. It provides a broad perspective to the reader on the potential of BN as an artificial intelligence tool for corrosion risk management and the challenges for implementing it.

Long description:

This book represents a compilation of experience from a slate of experts involved in developing and deploying Bayesian Networks (BN) for corrosion management. The contributors describe how probability distributions can be developed for corroding systems and BN can be applied as an ideal framework to deal with corrosion risk. Corrosion can develop suddenly and grow rapidly after a long incubation period and take many non-uniform aspects, including pitting and stress corrosion cracking, that cannot be mitigated by simply bulking up the system. They also describe how complex engineering structures and systems are influenced by many natural and engineering factors that come together in myriad ways. It provides a broad perspective to the reader on the potential of BN as an artificial intelligence tool for corrosion risk management and the challenges for implementing it.




Table of Contents:

Chapter1. Introduction: Risk Assessment.- Chapter.2. Bayesian Network Basics.- Chaoter.3. Corrosion Models.- Chapter.4. Statistical Models: Propagation of Uncertainty and Monte Carlo modeling.- Chapter.5. Corrosion Risk Assessment in Pipelines.- Chapter.6. Oil and Gas Production Systems.- Chapter.7.Nuclear Energy.- Chapter.8. Localized Corrosion in Saline Environments.- Chapter.9. BN for reinforced concrete structures.- Chapter.10.Coatings.- Chapter.11.Summary and Future.