Unraveling the Relationship between Microstructure and Mechanical Properties of Friction Stir-Welded Copper Joints by Fuzzy Logic Neural Networks
Abstract
:1. Introduction
2. Experimental Procedure
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Parameters | Unit | Levels | ||||
---|---|---|---|---|---|---|
−1.68 | −1 | 0 | 1 | 1.68 | ||
Rotational speed (A) | rpm | 463 | 600 | 800 | 1000 | 1136 |
Traverse speed (B) | mm/min | 16 | 50 | 100 | 150 | 184 |
Axial force (C) | kN | 1.66 | 2 | 2.5 | 3 | 3.34 |
Run | Rotational Speed (rpm) | Traverse Speed (mm/min) | Axial Force (kN) |
---|---|---|---|
1 | 600 | 50 | 2 |
2 | 1000 | 50 | 2 |
3 | 600 | 150 | 2 |
4 | 1000 | 150 | 2 |
5 | 600 | 50 | 3 |
6 | 1000 | 50 | 3 |
7 | 600 | 150 | 3 |
8 | 1000 | 150 | 3 |
9 | 463 | 100 | 2.5 |
10 | 1136 | 100 | 2.5 |
11 | 800 | 16 | 2.5 |
12 | 800 | 184 | 2.5 |
13 | 800 | 100 | 1.66 |
14 | 800 | 100 | 3.34 |
15 | 800 | 100 | 2.5 |
16 | 800 | 100 | 2.5 |
17 | 800 | 100 | 2.5 |
18 | 800 | 100 | 2.5 |
19 | 800 | 100 | 2.5 |
20 | 800 | 100 | 2.5 |
Run | Micro-Hardness (HV) | Fuzzy Micro-Hardness (HV) | Nano-Hardness (GPa) | Fuzzy Nano-Hardness (GPa) | Yield Strength (MPa) | Fuzzy Yield Strength (MPa) |
---|---|---|---|---|---|---|
1 | 75 | 72.7 | 1.48 | 1.49 | 83 | 83.8 |
2 | 58 | 57.8 | 0.84 | 0.88 | 39 | 40.9 |
3 | 108 | 105 | 1.88 | 1.84 | 103 | 101 |
4 | 79 | 81.5 | 1.39 | 1.36 | 75 | 77.4 |
5 | 75 | 72.7 | 1.34 | 1.36 | 78 | 64.6 |
6 | 62 | 63.8 | 1.33 | 1.36 | 61 | 58.2 |
7 | 70 | 72.7 | 1.24 | 1.23 | 63 | 77.4 |
8 | 67 | 63.8 | 1.23 | 1.23 | 80 | 77.4 |
9 | 97 | 99.2 | 1.61 | 1.62 | 89 | 90.2 |
10 | 62 | 63.8 | 1.24 | 1.23 | 60 | 58.2 |
11 | 63 | 63.8 | 1.26 | 1.23 | 54 | 51.8 |
12 | 69 | 72.7 | 1.3 | 1.36 | 58 | 58.2 |
13 | 71 | 72.7 | 1.37 | 1.36 | 66 | 64.6 |
14 | 55 | 57.8 | 0.93 | 0.97 | 42 | 40.9 |
15 | 74 | 72.7 | 1.41 | 1.36 | 76 | 77.4 |
16 | 74 | 72.7 | 1.39 | 1.36 | 77 | 77.4 |
17 | 75 | 72.7 | 1.4 | 1.36 | 78 | 77.4 |
18 | 75 | 72.7 | 1.42 | 1.36 | 77 | 77.4 |
19 | 75 | 72.7 | 1.42 | 1.36 | 77 | 77.4 |
20 | 78 | 81.5 | 1.42 | 1.36 | 77 | 77.4 |
Response | Goal | Lower | Target | Upper |
---|---|---|---|---|
Micro-hardness (HV) | Maximum | 57.8 | 104 | 105 |
Nano-hardness (Gpa) | Maximum | 0.88 | 1.85 | 1.84 |
Yield strength (Mpa) | Maximum | 40.9 | 100 | 101 |
Sample | Grain Size (μm) | HAGB (mm) | Average GAM Value | Average Taylor Factor | Peak Temperature (°C) |
---|---|---|---|---|---|
Run 2 (high heat input) | 26.9 | 5.01 | 0.56 | 2.8 | 450 |
Run 5 (low heat input) | 12.1 | 8.72 | 1.82 | 3.2 | 310 |
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Javidani, M.; Heidarzadeh, A.; Vatankhah Barenji, R.; Paidar, M.; Jafarian, H.R. Unraveling the Relationship between Microstructure and Mechanical Properties of Friction Stir-Welded Copper Joints by Fuzzy Logic Neural Networks. Crystals 2022, 12, 216. https://doi.org/10.3390/cryst12020216
Javidani M, Heidarzadeh A, Vatankhah Barenji R, Paidar M, Jafarian HR. Unraveling the Relationship between Microstructure and Mechanical Properties of Friction Stir-Welded Copper Joints by Fuzzy Logic Neural Networks. Crystals. 2022; 12(2):216. https://doi.org/10.3390/cryst12020216
Chicago/Turabian StyleJavidani, Mousa, Akbar Heidarzadeh, Reza Vatankhah Barenji, Moslem Paidar, and Hamid Reza Jafarian. 2022. "Unraveling the Relationship between Microstructure and Mechanical Properties of Friction Stir-Welded Copper Joints by Fuzzy Logic Neural Networks" Crystals 12, no. 2: 216. https://doi.org/10.3390/cryst12020216
APA StyleJavidani, M., Heidarzadeh, A., Vatankhah Barenji, R., Paidar, M., & Jafarian, H. R. (2022). Unraveling the Relationship between Microstructure and Mechanical Properties of Friction Stir-Welded Copper Joints by Fuzzy Logic Neural Networks. Crystals, 12(2), 216. https://doi.org/10.3390/cryst12020216