Effect of B4C/Gr on Hardness and Wear Behavior of Al2618 Based Hybrid Composites through Taguchi and Artificial Neural Network Analysis
Abstract
:1. Introduction
2. Results and Discussions
2.1. X-ray Analysis and Microstructural Study
2.2. Density and Porosity
2.3. Hardness Test
2.4. Wear Behavior
3. Materials and Methods
3.1. Fabrication of Composites by Using Stir Casting Method
3.2. X-ray Diffraction and Microstructural Study
3.3. Hardness Test
3.4. Wear Test
4. Evaluation of Wear Behavior
4.1. Analysis of Factors by Taguchi Method: Mini Tab_17
4.2. Analysis of Factors by Artificial Neural Network: IBMSSPSS Statistics 22
4.2.1. ANN Analysis for Sample A0
4.2.2. ANN Analysis for Sample A1
4.2.3. ANN Analysis for Sample A2
5. Worn Surface Morphology
6. Conclusions
- Hybridized composites were successfully fabricated through a liquid stir casting process.
- B4C and Gr particles were homogenously distributed in the Al2618 matrix.
- B4C and Gr particles were included in the B4C and Gr particles phase, creating a barrier to dislocation and helping to increase the matrix’s hardness.
- It was discovered that the degree of resistance to wear was exactly proportional to the hardness.
- The addition of the B4C and Gr particles makes it possible to speculate that this has the effect of increasing the matrix’s wear resistance.
- For the 10 wt.% B4C and 5 wt.% Gr, the presence of a mechanically mixed layer with B4C and Gr means the weight loss is substantially smaller.
- The ANN and Taguchi results confirm that load contributed more to the wear rate of the composites.
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Element | Si | Fe | Cu | Mn | Mg | Cr | Ni | Zn | Ti | B | Ca | Al |
---|---|---|---|---|---|---|---|---|---|---|---|---|
Wt.% | 0.24 | 1.30 | 2.52 | 0.004 | 1.46 | 0.02 | 1.14 | 0.01 | 0.07 | 0.003 | 0.002 | Balance |
Sample Designations | Composition | Al2618, % | Boron Carbide (B4C) wt.% | Graphite (Gr) wt.% |
---|---|---|---|---|
A0 | Al 2618 | 100 | 0 | 0 |
A1 | Al 2618 + 5% B4C-5% Gr | 90 | 5 | 5 |
A2 | Al 2618 + 10% B4C-5% Gr | 90 | 10 | 5 |
Experimental Runs | Load (N) | Speed (m/s) | Distance (m) |
---|---|---|---|
1 | 20 | 1.25 | 400 |
2 | 20 | 1.25 | 600 |
3 | 20 | 1.25 | 800 |
4 | 20 | 2.51 | 400 |
5 | 20 | 2.51 | 600 |
6 | 20 | 2.51 | 800 |
7 | 20 | 3.75 | 400 |
8 | 20 | 3.75 | 600 |
9 | 20 | 3.75 | 800 |
10 | 30 | 1.25 | 400 |
11 | 30 | 1.25 | 600 |
12 | 30 | 1.25 | 800 |
13 | 30 | 2.51 | 400 |
14 | 30 | 2.51 | 600 |
15 | 30 | 2.51 | 800 |
16 | 30 | 3.75 | 400 |
17 | 30 | 3.75 | 600 |
18 | 30 | 3.75 | 800 |
19 | 40 | 1.25 | 400 |
20 | 40 | 1.25 | 600 |
21 | 40 | 1.25 | 800 |
22 | 40 | 2.51 | 400 |
23 | 40 | 2.51 | 600 |
24 | 40 | 2.51 | 800 |
25 | 40 | 3.75 | 400 |
26 | 40 | 3.75 | 600 |
27 | 40 | 3.75 | 800 |
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Ballupete Nagaraju, S.; Kodigarahalli Somashekara, M.; Puttegowda, M.; Manjulaiah, H.; Kini, C.R.; Channarayapattana Venkataramaiah, V. Effect of B4C/Gr on Hardness and Wear Behavior of Al2618 Based Hybrid Composites through Taguchi and Artificial Neural Network Analysis. Catalysts 2022, 12, 1654. https://doi.org/10.3390/catal12121654
Ballupete Nagaraju S, Kodigarahalli Somashekara M, Puttegowda M, Manjulaiah H, Kini CR, Channarayapattana Venkataramaiah V. Effect of B4C/Gr on Hardness and Wear Behavior of Al2618 Based Hybrid Composites through Taguchi and Artificial Neural Network Analysis. Catalysts. 2022; 12(12):1654. https://doi.org/10.3390/catal12121654
Chicago/Turabian StyleBallupete Nagaraju, Sharath, Madhu Kodigarahalli Somashekara, Madhu Puttegowda, Hareesha Manjulaiah, Chandrakant R. Kini, and Venkatesh Channarayapattana Venkataramaiah. 2022. "Effect of B4C/Gr on Hardness and Wear Behavior of Al2618 Based Hybrid Composites through Taguchi and Artificial Neural Network Analysis" Catalysts 12, no. 12: 1654. https://doi.org/10.3390/catal12121654