Prediction of Atmospheric Corrosion of Carbon Steel Using Artificial Neural Network Model in Local Geographical Regions

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F25794787%3A_____%2F11%3A%230000421" target="_blank" >RIV/25794787:_____/11:#0000421 - isvavai.cz</a>

Result on the web

<a href="http://corrosionjournal.org/doi/pdf/10.5006/1.3595099" target="_blank" >http://corrosionjournal.org/doi/pdf/10.5006/1.3595099</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5006/1.3595099" target="_blank" >10.5006/1.3595099</a>

Result language

angličtina

Original language name

Prediction of Atmospheric Corrosion of Carbon Steel Using Artificial Neural Network Model in Local Geographical Regions

Original language description

Atmospheric corrosion of metals is a complex, nonlinear process. It involves a large number of interacting and varying factors governed by material composition, form, size, testing procedure, location of exposure, and type of application. Possible environmental factors include temperature, relative humidity, wet-dry patterns, hours of sunshine, pH of rainfall, amount of precipitation, concentration of main pollutants, etc. All factors are a part of the variables in artificial neural network (ANN) modeling. The most important variables are chosen from long-term experiences as elements in the development of a prototype ?artificial intelligent sensor??a model designed for the assessment of atmospheric corrosion of carbon steel under local geographical conditions. The variable impact analysis and 2D maps gave accurate prediction of the atmospheric corrosion of carbon steel. Future climatic scenarios, mainly the calculation of mass losses under different simulated concentrations of sulfur d

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

JK - Corrosion and material surfaces

OECD FORD branch

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Project

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Continuities

Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year

2011

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Corrosion

ISSN

0010-9312

e-ISSN

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Volume of the periodical

67

Issue of the periodical within the volume

6

Country of publishing house

US - UNITED STATES

Number of pages

6

Pages from-to

06004-1-065004-6

UT code for WoS article

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EID of the result in the Scopus database

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