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Journal ArticleDOI

SCC Analysis of Austenitic Stainless Steels in Chloride-Bearing Water by Neural Network Techniques

H.M.G Smets, +1 more
- 01 Aug 1992 - 
- Vol. 48, Iss: 8, pp 618-623
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TLDR
Although case histories reflecting engineers' experiences with chloride-induced stress corrosion cracking of austenitic stainless steels in water, are multifold, this source of informatio... as discussed by the authors.
Abstract
Although case histories, reflecting engineers' experiences with chloride-induced stress corrosion cracking of austenitic stainless steels in water, are multifold, this source of informatio...

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Book

Handbook of Corrosion Engineering

TL;DR: In this article, the authors present an approach to accelerate and amplify the amount of damage caused by aqueous and high-temperature corrosion in a given environment and application.
Journal ArticleDOI

Phenomenological modelling of atmospheric corrosion using an artificial neural network

TL;DR: In this article, a neural network was used to predict the atmospheric corrosion of steel and zinc, and the cross validity criterion was employed as the criterion to stop the training of the neural network.
Journal ArticleDOI

Hybrid genetic algorithms and support vector regression in forecasting atmospheric corrosion of metallic materials

TL;DR: The result shows that the hybrid model provides better prediction capability and is therefore considered as a promising alternative method for forecasting atmospheric corrosion of zinc and steel.
Journal ArticleDOI

The improvement of localized corrosion resistance in sensitized stainless steel by laser surface remelting

TL;DR: In this article, the effect of laser surface melting on the localized corrosion resistance of sensitized type 321 austenitic stainless steel was investigated by means of SEM, TEM, XRD analyses, and corresponding localized corrosion resistances were evaluated by pitting and electrochemical potentiokinetic reactivation (EPR).
Journal ArticleDOI

Molecular modelling of compounds used for corrosion inhibition studies: a review.

TL;DR: In this article, the authors present a collection of major advancements in the field of computational modelling for the design and testing of the corrosion inhibition effectiveness of organic corrosion inhibitors, which can be regarded as a time saving and eco-friendly approach for screening organic compounds for corrosion inhibition potential before their wet laboratory synthesis would be carried out.
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