Prediction of Tool Eccentricity Effects on the Mechanical Properties of Friction Stir Welded AA5754-H24 Aluminum Alloy Using ANN Model
Abstract
:1. Introduction
2. Collecting the Experimental Data
3. Methodology of the ANN Model
4. Results and Discussion
5. Conclusions
- The ANN model has been developed based on the FSW experimental work data of AA5754-H24, in which FS was welded using 0, 0.2, and 0.8 mm TPE and welding speeds of 50, 100, 150, 200, 300, and 500 mm/min.
- The ANN model was successfully used to predict the effect of tool pin eccentricity on the mechanical properties of FSW AA 5547-H24, and the networks can be used as an alternative.
- The RMS error values for the ultimate tensile strength, elongation, hardness of the TMAZ, and weld metal for the test data were 1.1346, 0.3515, 1.2759, and 0.3743, respectively; the R2 values are all greater than 0.98, except for the hardness of the TMAZ, which is 0.97.
- It is found that the correlations between the measured and predicted values of the ultimate tensile strength, elongation, and hardness of the weld metal are better than those of the hardness of the TMAZ.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Nomenclature
bi | Biases of layer one, i = 1, 2, 3, …, 8 |
bj | Biases of layer two, j = 1, 2, 3, 4 |
oj | Output (prediction data), where j = 1, 2, 3, …, 14 for training and j = 1, 2, 3, 4 for testing. |
p | Samples (p = 14 for training, p = 4 for testing). |
R2 | Absolute fraction of variance |
RMS | Root-mean squared |
tj | Target (measured data), where j = 1, 2, 3, …, 14 for training and j = 1, 2, 3, 4 for testing. |
TMAZ | Thermo mechanical affected zone |
Wi | Weights of layer one, i = 1, 2, 3, …, 8 |
Wj | Weights of layer two, j = 1, 2, 3, 4 |
WNZ | Weld nugget zone |
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wt.% | ||||||||
---|---|---|---|---|---|---|---|---|
Fe | Si | Mn | Cu | Mg | Zn | Ti | Cr | Al |
0.40 ± 0.03 | 0.40 ± 0.02 | 0.50 ± 0.04 | 0.10 ± 0.01 | 2.6–3.2 ± 0.03 | 0.20 ± 0.01 | 0.15 ± 0.01 | 0.30 ± 0.02 | rest - |
Proof Stress 0.2% (MPa) | Tensile Strength (MPa) | Elongation (%) |
---|---|---|
205 ± 5 | 260.57 ± 4.60 | 12.93 ± 1.80 |
No. | e (mm) | Welding Speed (mm/min) | Tensile Strength (Mpa) | Elongation (%) | Average Hardness (HV) | |
---|---|---|---|---|---|---|
HAZ | WNZ | |||||
1 | 0 | 50 | 231.00 | 9.66 | 59.9 ± 0.3 | 59.5 ± 0.6 |
2 | 0 | 100 | 235.38 | 11.36 | 63.0 ± 0.1 | 68.1 ± 0.9 |
3 | 0 | 150 | 234.06 | 11.60 | 63.4 ± 0.1 | 68.1 ± 0.3 |
4 | 0 | 200 | 237.43 | 11.58 | 60.2 ± 0.2 | 66.9 ± 0.7 |
5 | 0 | 300 | 238.58 | 10.21 | 61.6 ± 0.4 | 67.3 ± 0.3 |
6 | 0 | 500 | 244.95 | 7.92 | 66.9 ± 0.5 | 64.05 ± 0.5 |
7 | 0.2 | 50 | 238.80 | 11.32 | 60.6 ± 0.7 | 62.0 ± 0.6 |
8 | 0.2 | 100 | 240.31 | 11.35 | 59.9 ± 0.3 | 62.7 ± 0.4 |
9 | 0.2 | 150 | 240.02 | 11.39 | 63.4 ± 0.4 | 64.9 ± 0.8 |
10 | 0.2 | 200 | 243.22 | 12.39 | 60.9 ± 0.8 | 65.3 ± 0.3 |
11 | 0.2 | 300 | 243.69 | 11.25 | 65.7 ± 0.4 | 64.82 ± 0.7 |
12 | 0.2 | 500 | 249.87 | 9.21 | 67.5 ± 0.6 | 73.1 ± 0.6 |
13 | 0.8 | 50 | 242.26 | 11.74 | 68.9 ± 0.9 | 61.1 ± 0.9 |
14 | 0.8 | 100 | 239.76 | 10.99 | 60.9 ± 0.6 | 65.7 ± 0.4 |
15 | 0.8 | 150 | 238.97 | 10.54 | 64.2 ± 0.8 | 67.2 ± 0.7 |
16 | 0.8 | 200 | 238.87 | 10.50 | 66.9 ± 0.5 | 68.1 ± 0.8 |
17 | 0.8 | 300 | 238.74 | 11.10 | 58.9 ± 0.3 | 62.3 ± 0.3 |
18 | 0.8 | 500 | 237.15 | 6.14 | 64.2 ± 0.4 | 71.9 ± 0.5 |
Layer | Neurons per Layer | Weights | Biases | ||||||||
i | Wi1 | Wi2 | bi | ||||||||
1 | 8 | 1 | 2.7009 | 4.5649 | −1.7555 | ||||||
2 | −2.0315 | −3.4643 | 1.3986 | ||||||||
3 | −3.1972 | 18.3450 | 22.1916 | ||||||||
4 | 3.9171 | −3.6640 | 1.4856 | ||||||||
5 | −15.2546 | −39.2993 | −7.1898 | ||||||||
6 | 3.8393 | −3.3341 | 1.5511 | ||||||||
7 | 7.4015 | 1.4190 | 6.2523 | ||||||||
8 | 0.6582 | −1.6493 | 1.0211 | ||||||||
j | Wj1 | Wj2 | Wj3 | Wj4 | Wj5 | Wj6 | Wj7 | Wj8 | bj | ||
2 | 4 | 1 | 0.6098 | 0.6742 | −0.5132 | 4.8089 | 0.0594 | −5.3504 | 0.7177 | −0.0521 | 0.2423 |
2 | 3.0641 | 3.2349 | −0.1842 | 5.0439 | 0.0677 | −5.7714 | 0.5053 | 1.1842 | −0.2822 | ||
3 | −2.0024 | −2.1078 | −4.1730 | 9.0617 | −0.4064 | −9.6011 | 0.4018 | 0.1366 | 3.8853 | ||
4 | −17.6851 | −19.4517 | 0.8332 | 15.4643 | 0.4267 | −16.9510 | 0.8747 | 0.9753 | −0.3709 |
RMS of Train | R2 of Train | Mean Error of Train | RMS of Test | R2 of Test | Mean Error of Test | |
---|---|---|---|---|---|---|
Tensile strength | 0.3993 | 0.9993 | 0.0608 | 1.1346 | 0.9946 | 0.2512 |
Elongation | 0.0904 | 0.9992 | 0.0536 | 0.3515 | 0.9894 | 0.2865 |
Hardness of TMAZ | 0.5167 | 0.9958 | 0.3159 | 1.2759 | 0.9735 | 3.3267 |
Hardness of WNZ | 0.0755 | 0.9999 | 0.0036 | 0.3743 | 0.9979 | 0.0101 |
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Essa, A.R.S.; Ahmed, M.M.Z.; Aboud, A.R.K.; Alyamani, R.; Sebaey, T.A. Prediction of Tool Eccentricity Effects on the Mechanical Properties of Friction Stir Welded AA5754-H24 Aluminum Alloy Using ANN Model. Materials 2023, 16, 3777. https://doi.org/10.3390/ma16103777
Essa ARS, Ahmed MMZ, Aboud ARK, Alyamani R, Sebaey TA. Prediction of Tool Eccentricity Effects on the Mechanical Properties of Friction Stir Welded AA5754-H24 Aluminum Alloy Using ANN Model. Materials. 2023; 16(10):3777. https://doi.org/10.3390/ma16103777
Chicago/Turabian StyleEssa, Ahmed R. S., Mohamed M. Z. Ahmed, Aboud R. K. Aboud, Rakan Alyamani, and Tamer A. Sebaey. 2023. "Prediction of Tool Eccentricity Effects on the Mechanical Properties of Friction Stir Welded AA5754-H24 Aluminum Alloy Using ANN Model" Materials 16, no. 10: 3777. https://doi.org/10.3390/ma16103777