Quantitative and Qualitative Analysis of Atmospheric Effects on Carbon Steel Corrosion Using an ANN Model

Quantitative and Qualitative Analysis of Atmospheric Effects on Carbon Steel Corrosion Using an ANN Model

This study develops an artificial neural network (ANN) model to predict the corrosion rate of carbon steel under a wide range of atmospheric conditions. The model incorporates input variables, including temperature (−3.1–28.2 °C), relative humidity (33.3–91.1%), time of wetness (0.003–0.976), precip...

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Bibliographic Details
Main Authors: Pasupuleti L. Narayana, Saurabh Tiwari, Anoop K. Maurya, Muhammad Ishtiaq, Nokeun Park, Nagireddy Gari Subba Reddy
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Metals
Subjects:
atmospheric conditions
corrosion rate
carbon steel
artificial neural network
quantitative estimation
Online Access:https://www.mdpi.com/2075-4701/15/6/607
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