Artificial neural networks application for modeling of friction stir welding effects on mechanical properties of 7075-T6 aluminum alloy
Author:
Publisher
IOP Publishing
Subject
General Medicine
Link
http://stacks.iop.org/1757-899X/103/i=1/a=012034/pdf
Reference46 articles.
1. Effect of Postweld Aging Treatment on Fatigue Behavior of Pulsed Current Welded AA7075 Aluminum Alloy Joints
2. Metallurgical Studies on Cracked Al–5.5Zn–2.5Mg–1.5Cu Aluminum Alloy Injector Disc of Turbine Rotor
3. Optimization of homogenizing mode for aluminum alloy AA7075 using calorimetric and microstructural studies
4. Hot Corrosion Behavior of Bare, Cr3C2-(NiCr) and Cr3C2-(NiCr) + 0.2wt.%Zr Coated SuperNi 718 at 900 °C
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3. Prediction of coefficient of friction of solid powder lubricants under high pressure conditions using machine learning algorithms;Materialwissenschaft und Werkstofftechnik;2024-07
4. Influence of tool pin profiles on the mechanical and microstructural properties of a single-pass friction stir-welded AA7075-T6 aluminium alloy;Canadian Metallurgical Quarterly;2024-05-29
5. A comparative analysis of forecasting surface hardness in various aluminum friction stir welded joints: FEM-ANN hybrid versus ANN-PSO-integrated approaches;The International Journal of Advanced Manufacturing Technology;2024-05-17
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