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Content Provider | IET Digital Library |
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Author | Manivelmuralidaran, Velumani Senthilkumar, Krishnasamy |
Abstract | The objective of the study is to predict the cold cracking resistance of high strength low alloy 950A welded joints using an artificial neural network (ANN) model. A bead on plate welding is carried out using the gas metal arc welding process. The identified process parameters for the ANN are preheating temperature, oxide particle content, and heat input. The impact strength of the weld metal is considered as the output parameter. A feed-forward back propagation model with ten neurons in the hidden layer is developed to predict the impact strength of the weld metal. The neural network model is created, trained, and tested with a set of experimental data. The proposed model correctly predicted the impact strength of the given input parameters. The predicted value of the impact strength is in agreement with the experimental data. The error percentage between the predicted and observed values is <5% and the root mean square error value is 2.2%. Sensitivity analysis is performed to identify the significance of input parameters. It is evident that the preheating temperature contributes 50.04%, oxide particles content contributes 37.15%, and heat input contributes 12.81% to impact strength. |
Starting Page | 447 |
Ending Page | 454 |
Page Count | 8 |
Volume Number | 2019 |
e-ISSN | 20513305 |
Issue Number | Issue 2, Feb (2019) |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/joe/2019/2 |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/joe.2018.5277 |
Journal | The Journal of Engineering |
Publisher | The Institution of Engineering and Technology |
Publisher Date | 2018-12-12 |
Access Restriction | Open |
Rights License | Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) |
Subject Keyword | Alloy Steel ANN Arc Welding Artificial Neural Network Model Artificial Neural Network Modelling Cold Cracking Resistance Cold-crack Resistance Cracks Current 950.0 A Engineering Material Experimental Data Gas Metal Arc Welding Process Given Input Parameter Heat Input High Strength Low Identified Process Parameter Impact Strength Joining Processes And Welding Neural Computing Technique Neural Nets Oxide Particle Content Plate Plate Welding Predicted Observed Value Preheating Temperature Propagation Model Sensitivity Analysis Weld Metal Welded Joints Welding Welds |
Content Type | Text |
Resource Type | Article |
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