Artificial intelligence analysis of corrosion behavior of H59 brass alloy in red sea conditions with and without ceramic coating

Authors

  • Obaid Saleh Ba Yuosef Department of Mechanical Engineering, College of Engineering and Computer Science, Jazan University, Saudi Arabia.
  • Mohmmad Salah Eldin Haij Department of Mechanical Engineering, College of Engineering and Computer Science, Jazan University, Saudi Arabia.
  • Abdulmajeed Sami Alnemry Department of Mechanical Engineering, College of Engineering and Computer Science, Jazan University, Saudi Arabia.
  • Ammar Ahmed Holbah Department of Mechanical Engineering, College of Engineering and Computer Science, Jazan University, Saudi Arabia.
  • Mohammed Fahmi Lathkani Department of Mechanical Engineering, College of Engineering and Computer Science, Jazan University, Saudi Arabia.
  • Ibrahim Sahban Abuhayyah Department of Mechanical Engineering, College of Engineering and Computer Science, Jazan University, Saudi Arabia.
  • Abdulaziz mahdi alameer Department of Mechanical Engineering, College of Engineering and Computer Science, Jazan University, Saudi Arabia.
  • Turki Nasser Jraba Department of Mechanical Engineering, College of Engineering and Computer Science, Jazan University, Saudi Arabia.
  • Haitham Hadidi Department of Mechanical Engineering, College of Engineering and Computer Science, Jazan University, Saudi Arabia.
  • Rajasekaran Saminathan Department of Mechanical Engineering, College of Engineering and Computer Science, Jazan University, Saudi Arabia.
  • Divya Raju College of Applied Health Sciences and Nursing, Jazan university, Saudi Arabia

Abstract

Due to its exceptional resistance to corrosion, H59 is a marine grade alloy that is utilized widely in the maritime industry for a variety of applications throughout the industry. A scant amount of research has been done on the effects of heat treatment and ceramic coatings such as ceria on the corrosion behavior of H59 in conditions similar to those found in the Red Sea. This study aims to investigate the influence of heat treatment at temperatures of 200, 360, and 600 degrees Celsius over a range of time periods, as well as the application of a cerium oxide coating using the chemical bath technique, on the corrosion behavior of H59 alloy under conditions that are typical of the Red Sea. Furthermore, in order to acquire the artificial intelligence algorithm, the corrosion data of the alloy that has been exposed to heat treatment and surface coating is analyzed by the software that utilizes both machine learning and artificial intelligence. Heat treatment causes topographical changes in grain structures and results in the production of a metallic oxide layer on the surface of the alloy. The machine learning treatment has led to the identification of the quenching treatment at 600 and 200 degrees Celsius, as well as the annealing treatment at 360 degrees Celsius contribute to a greater corrosion rate with severity level 1. The coating made of cerium oxide has resulted in a reduction in the rate of corrosion to a level that is two times lower. .

Keywords: H59 Alloy, Corrosion Behavior, Red Sea, Heat Treatment, Artificial Intelligence, Machine Learning.

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Published

2025-04-20

Issue

Vol. 1 No. 3 (2025)

Section

Articles