Artificial neural network based fatigue life assessment of friction stir welding AA2024-T351 aluminum alloy and multi-objective optimization of welding parameters

被引：30

作者：

Nejad, Reza Masoudi ^{[1
]}

Sina, Nima ^{[2
]}

Moghadam, Danial Ghahremani ^{[3
]}

Branco, Ricardo ^{[4
]}

Macek, Wojciech ^{[5
]}

Berto, Filippo ^{[6
]}

机构：

[1] Univ Elect Sci & Technol China, Sch Mech & Elect Engn, Chengdu 611731, Peoples R China

[2] Islamic Azad Univ, Dept Mech Engn, Najafabad Branch, Esfahan, Iran

[3] Quchan Univ Technol, Fac Engn, Dept Mech Engn, Quchan, Iran

[4] Univ Coimbra, Dept Mech Engn, CEMMPRE, Coimbra, Portugal

[5] Gdansk Univ Technol, Fac Mech Engn & Ship Technol, 11-12 Gabriela Narutowicza, PL-80233 Gdansk, Poland

[6] NTNU Norwegian Univ Sci & Technol, Dept Mech & Ind Engn, Trondheim, Norway

来源：

INTERNATIONAL JOURNAL OF FATIGUE | 2022年 / 160卷

关键词：

Friction stir welding; Artificial neural network; Fatigue life; Aluminum alloy; Fracture toughness; MECHANICAL-PROPERTIES; FRACTURE-TOUGHNESS; VICKERS MICROHARDNESS; GENETIC ALGORITHM; TENSILE-STRENGTH; CRACK GROWTH; FSW JOINTS; BEHAVIOR; MICROSTRUCTURE; SPEED;

D O I：

10.1016/j.ijfatigue.2022.106840

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

In this paper, the fracture behavior and fatigue crack growth rate of the 2024-T351 aluminum alloy has been investigated. At first, the 2024-T351 aluminum alloys have been welded using friction stir welding procedure and the fracture toughness and fatigue crack growth rate of the CT specimens have been studied experimentally based on ASTM standards. After that, in order to predict fatigue crack growth rate and fracture toughness, artificial neural network is used. To obtain the best neuron number in the hidden layer of the artificial neural network, different neuron numbers are tested and the best network based on the performance is selected. Then the fitting method is applied and the fitted surfaces that illustrate the behavior of welding are shown and the results of artificial neural network and fitting method are compared. Also, multi-objective optimization algo-rithm is used to obtain the best welding parameters and finally sensitivity analysis is applied to measure the effect of rotational and traverse speeds on the fracture toughness and fatigue crack growth rate.

引用

页数：12

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