Open AccessNeural Network Model for Synthesis of Thermally Sprayed (AI/AI2O3) Composite Protective Coatings
Author(s) -
Thamir A. Jumah,
Saad Ali Ahmed
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2063/1/012013
Subject(s) - materials science , composite number , polarization (electrochemistry) , aluminium , artificial neural network , composite material , corrosion , nonlinear system , metallurgy , computer science , machine learning , chemistry , physics , quantum mechanics
Al 2 O 3 and Al 2 O 3 –Al composite coatings were deposited on steel specimens using Oxy-acetylene gas thermal spray gun. Alumina was mixed with Aluminum in six groups of concentrations (0, 5, 10,12,15 and 20% ) Al2O3, Specimens were tested for corrosion using Potentiodynamic polarization technique. Further tests were conducted for the effect of temperature on polarization curve and the hardness tests for the coated specimens. At first, Modelling was carried out using MINITAB-19, least square method, as a 2nd degree nonlinear model, bad results were achieved because of the high nonlinearity. Better result was achieved using neural network fitting tool. The network was designed using five neurons in the hidden layer and the input was I input with two layers, the electrical potential and alumina concentration.