# Experimental Evaluation of Interfacial Surface Cracks in Friction Welded Dissimilar Metals through Image Segmentation Technique (IST)

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## Abstract

**:**

## 1. Introduction

## 2. Experimental Work

## 3. Image Segmentation Technique

## 4. Mathematical Modeling of Input Heat Energy, ${H}_{f}$, and Coefficient of Friction, ${\mathsf{\mu}}_{f}$

## 5. Response Surface Method-RSM

## 6. Results and Discussions

#### 6.1. Effect of Friction Torque on the Coefficient of Friction

#### 6.2. Effect of Friction Pressure on the Coefficient of Friction

#### 6.3. Effect of Friction Time on the Coefficient of Friction

#### 6.4. Investigation of Heat Flux Generated and Spindle Speed on the Coefficient of Friction

#### 6.5. Investigation of Heat Flux Generated, Friction Pressure, and Friction Torque on the Coefficient of Friction

^{2}. These optimum parameters were achieved at the 95% confidence limit. In Figure 11a, the main effect of speed, friction pressure, and Figure 11b the effect of speed, friction torque, and friction force on ${\mathsf{\mu}}_{\mathrm{f}}$ are shown. Due to more heat input energy, the fractured patterns had lesser intensity on the fracture surfaces of the welded interface at the friction time less than 3 s and observed river patterns were confirmed. There were crack detections and porosities distributed on the interfacial fractured surface. Table 15 and Table 16 show the regression coefficients obtained and Anova results. It can be concluded that less friction welding time leads to relatively more fractured surfaces when compared to the extended friction time conditions The regression equation was ${\mathsf{\mu}}_{\mathrm{f}}$ = 0.478 − 0.000007${\mathrm{q}}_{\mathrm{f}}$ − 0.00477${\mathrm{F}}_{\mathrm{p}}$ + 0.0168${\mathrm{T}}_{\mathrm{f}}$, S = 0.0799830, R-Sq = 94.5%, R-Sq (adj) = 91.1%

## 7. Macro Examination of Aluminum-Copper Welded Interface by Using IST

^{2}) as compared to the background crack area (282.743 Px

^{2}), with a less average blue colored mean intensity of 0.0302.

^{2}as shown in Figure 14b. In Figure 15, the screen shot of colored regions obtained from the DIGIMIZER software gives different colored intensities at the fractured surface based on statistical measurements.

^{2}. The mean welded area was found to be 212,357.46 Px

^{2}. Different colored intensities are given for friction welded tracks at the interface having mean crack lengths of 24.60 Px based on statistical measurements of the segments at the welded interface.

## 8. Conclusions

_{2}and SiC, and the effect of these additions on the coefficient of friction with respect to different process parameters.

## Author Contributions

## Funding

## Acknowledgments

## Conflicts of Interest

## Nomenclature

${T}_{f}$ | $FrictionTorque\left(Nm\right)$ |

${R}_{s}$ | $Radiusoftheweldmetal,mm$ |

${F}_{f}$ | $FrictionForce\left(N\right)$ |

${N}_{s}$ | $SpindleSpeed,RPM$ |

${\mathsf{\mu}}_{f}$ | $CoefficientofFriction$ |

${F}_{p}$ | $FrictionPressure,N/m{m}^{2}$ |

${F}_{t}$ | Friction Time, seconds |

R-Sq | Squared Residue |

R-Sq (adj) | Adjoint Squared Residue |

${H}_{f}$ | $InputHeatEnergy\left(W\right)$ |

$\dot{{q}_{f}}$ | $HeatFluxgeneratedduetofriction\left(W/{m}^{2}\right)$ |

DF | Degree of Freedom |

SS | Sum of Squares Value |

MS | Mean Square Value |

F | F-Value |

P | P-Value |

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**Figure 11.**(

**a**) Effect of speed, friction pressure. (

**b**) Effect of speed, friction torque, and friction force on ${\mathsf{\mu}}_{\mathrm{f}}$.

**Figure 14.**(

**a**) Al-Cu fractured surface of the welded interface. (

**b**) Segment based analysis of the fracture surface.

**Figure 17.**(

**a**) Peaks and valleys at Al-Cu interface. (

**b**) Segment based analysis of the welded region.

Metal | Si | Cu | Fe | Mn | Ni | Mg | Sn | Zn | Pb | Al |
---|---|---|---|---|---|---|---|---|---|---|

Al | 0.85 | 0.35 | 0.2 | 0.05 | 0.05 | 0.03 | 0.03 | 0.3 | - | Remaining content |

Cu | - | Balance | 0.04 | 0.05 | 0.05 | 1.83 | 0.03 | 0.06 | 0.04 | - |

Metal | Density, g/cm^{3} | Tensile Strength, MPa | Young’s Modulus, GPa | Brinell Hardness |
---|---|---|---|---|

Cu | 8.9 | 220 | 104 | 75 |

Al | 2.7 | 170 | 78 | 48 |

S. No | Factors | Symbol | Units | Levels | ||
---|---|---|---|---|---|---|

- | −1 | 0 | 1 | |||

Low | Middle | High | ||||

1 | Friction Force | ${\mathrm{F}}_{\mathrm{f}}$ | N | 6217.2 | 9608.4 | 13,564.8 |

2 | Speed | ${\mathrm{N}}_{\mathrm{s}}$ | RPM | 100 | 500 | 1000 |

3 | Friction Pressure | ${\mathrm{F}}_{\mathrm{p}}$ | MPa | 55 | 85 | 120 |

4 | Friction Time | ${\mathrm{F}}_{\mathrm{t}}$ | s | 3 | 7 | 10 |

Experiment. No | Actual Values | Coded Values | Output Response | |||||
---|---|---|---|---|---|---|---|---|

${\mathbf{N}}_{\mathbf{s}}$ | ${\mathbf{F}}_{\mathbf{p}}$ | ${\mathbf{F}}_{\mathbf{t}}$ | ${\mathbf{N}}_{\mathbf{s}}$ | ${\mathbf{F}}_{\mathbf{p}}$ | ${\mathbf{F}}_{\mathbf{t}}$ | ${\mathsf{\mu}}_{\mathbf{f}}$ | $\dot{{\mathbf{q}}_{\mathbf{f}}}$$,\mathbf{W}/\mathbf{m}{\mathbf{m}}^{2}$ | |

1 | 100 | 55 | 3 | −1 | −1 | −1 | 0.27 | 1727 |

2 | 250 | 85 | 7 | 1 | −1 | −1 | 0.45 | 6672 |

3 | 500 | 120 | 10 | −1 | 1 | −1 | 0.63 | 18,840 |

4 | 250 | 55 | 3 | 1 | 1 | −1 | 0.70 | 4317.5 |

5 | 500 | 85 | 7 | −1 | −1 | −1 | 0.90 | 2239.8 |

6 | 100 | 120 | 10 | 1 | −1 | −1 | 0.12 | 3768 |

7 | 250 | 55 | 3 | −1 | 1 | −1 | 0.70 | 4317.5 |

8 | 100 | 85 | 7 | 1 | 1 | −1 | 0.18 | 2669 |

9 | 500 | 120 | 10 | −1 | −1 | 1 | 0.64 | 18,840 |

Factors | 3 |

Base runs | 20 |

Base blocks | 1 |

Two-level factorial | Full factorial |

Cube points | 8 |

Center points in cube | 6 |

Axial points | 6 |

Center points in axial | 0 |

Alpha | 1.68179 |

Replicates | 1 |

Total runs | 20 |

Total blocks | 1 |

Runs | ${\mathbf{F}}_{\mathbf{p}},\text{}\mathbf{N}/{\mathbf{mm}}^{2}$ | ${\mathbf{F}}_{\mathbf{f}},\text{}\mathbf{N}$ | ${\mathbf{T}}_{\mathbf{f}},\text{}\mathbf{Nm}$ | ${\mathbf{F}}_{\mathbf{t}},\text{}\mathbf{s}$ | ${\mathbf{N}}_{\mathbf{s}},\mathbf{R}\mathbf{P}\mathbf{M}$ | ${\mathbf{H}}_{\mathbf{f}},\mathbf{W}$ | ${\mathsf{\mu}}_{\mathbf{f}}$ | $\dot{{\mathbf{q}}_{\mathbf{f}}}$$,\mathbf{W}/\mathbf{m}{\mathbf{m}}^{2}$ |
---|---|---|---|---|---|---|---|---|

1 | 55 | 6217.2 | 10.4 | 3 | 100 | 17.3 | 0.27 | 1727 |

2 | 85 | 9608.4 | 26 | 7 | 250 | 108.34 | 0.45 | 6672 |

3 | 120 | 13,564.8 | 52 | 10 | 500 | 433.34 | 0.63 | 18,840 |

4 | 55 | 6217.2 | 26 | 3 | 250 | 108.34 | 0.70 | 4317.5 |

5 | 85 | 9608.4 | 52 | 7 | 500 | 433.34 | 0.90 | 2239.8 |

6 | 120 | 13,564.8 | 10.4 | 10 | 100 | 17.3 | 0.12 | 3768 |

7 | 55 | 6217.2 | 26 | 3 | 250 | 108.34 | 0.70 | 4317.5 |

8 | 85 | 9608.4 | 10.4 | 7 | 100 | 17.3 | 0.18 | 2669 |

9 | 120 | 13,564.8 | 52 | 10 | 500 | 433.34 | 0.64 | 18,840 |

Predictor | Coef | SE Coef | T | P |
---|---|---|---|---|

Constant | 0.53517 | 0.09138 | 5.86 | 0.001 |

${\mathrm{F}}_{\mathrm{p}}$ | −0.00555 | 0.001098 | −5.052 | 0.002 |

${\mathrm{T}}_{\mathrm{f}}$ | 0.015471 | 0.001700 | 9.10 | 0.000 |

Source | DF | SS | MS | F | P |
---|---|---|---|---|---|

Regression | 2 | 0.5396 | 0.26982 | 42.42 | 0.000 |

Residual Error | 6 | 0.0381 | 0.00636 | - | - |

Total | 8 | 0.5778 | - | - | - |

Predictor | Coef | SE Coef | T | P |
---|---|---|---|---|

Constant | 0.4878 | 0.2319 | 2.10 | 0.089 |

$\dot{{\mathrm{q}}_{\mathrm{f}}}$ | −0.000031 | 0.00007 | −0.42 | 0.693 |

${\mathrm{H}}_{\mathrm{f}}$ | 0.00160 | 0.00019 | 8.35 | 0.000 |

${\mathrm{N}}_{\mathrm{s}}$ | −0.0180 | 0.0800 | −0.23 | 0.830 |

Source | DF | SS | MS | F | P |
---|---|---|---|---|---|

Regression | 3 | 0.540 | 0.180 | 23.82 | 0.002 |

Residual Error | 5 | 0.037 | 0.007 | - | - |

Total | 8 | 0.577 | - | - | - |

Predictor | Coef | SE Coef | T | P |
---|---|---|---|---|

Constant | 0.4878 | 0.2319 | 2.10 | 0.089 |

$\dot{{\mathrm{q}}_{\mathrm{f}}}$ | −0.00003199 | 0.000076 | −0.4 | 0.69 |

${\mathrm{H}}_{\mathrm{f}}$ | 0.0016098 | 0.00019 | 8.35 | 0.000 |

${\mathrm{N}}_{\mathrm{s}}$ | −0.01808 | 0.080 | −0.2 | 0.83 |

Source | DF | SS | MS | F | P |
---|---|---|---|---|---|

Regression | 3 | 0.5400 | 0.18001 | 23.82 | 0.002 |

Residual Error | 5 | 0.0377 | 0.00756 | - | - |

Total | 8 | 0.5778 | - | - | - |

Predictor | Coef | SE Coef | T | P |
---|---|---|---|---|

Constant | −0.2055 | 0.1228 | −1.67 | 0.155 |

${\mathrm{q}}_{\mathrm{f}}$ | −0.000018 | 0.0000061 | −2.97 | 0.031 |

${\mathrm{H}}_{\mathrm{f}}$ | −0.003039 | 0.0009467 | −3.21 | 0.024 |

${\mathrm{N}}_{\mathrm{s}}$ | 0.004981 | 0.001012 | 4.92 | 0.004 |

Source | DF | SS | MS | F | P |
---|---|---|---|---|---|

Regression | 3 | 0.5416 | 0.1805 | 25.00 | 0.002 |

Residual Error | 5 | 0.03612 | 0.00722 | - | - |

Total | 8 | 0.57780 | - | - | - |

Predictor | Coef | SE Coef | T | P |
---|---|---|---|---|

Constant | 0.4775 | 0.1088 | 4.39 | 0.007 |

${\mathrm{q}}_{\mathrm{f}}$ | −0.00000696 | 0.00000708 | −0.98 | 0.371 |

${\mathrm{H}}_{\mathrm{f}}$ | −0.004767 | 0.001360 | −3.51 | 0.017 |

${\mathrm{N}}_{\mathrm{s}}$ | 0.016785 | 0.002167 | 7.75 | 0.001 |

Source | DF | SS | MS | F | P |
---|---|---|---|---|---|

Regression | 3 | 0.54581 | 0.18194 | 28.44 | 0.001 |

Residual Error | 5 | 0.03199 | 0.00640 | - | - |

Total | 8 | 0.57780 | - | - | - |

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**MDPI and ACS Style**

Sayeed Ahmed, G.M.; Algahtani, A.; Mahmoud, E.R.I.; Badruddin, I.A.
Experimental Evaluation of Interfacial Surface Cracks in Friction Welded Dissimilar Metals through Image Segmentation Technique (IST). *Materials* **2018**, *11*, 2460.
https://doi.org/10.3390/ma11122460

**AMA Style**

Sayeed Ahmed GM, Algahtani A, Mahmoud ERI, Badruddin IA.
Experimental Evaluation of Interfacial Surface Cracks in Friction Welded Dissimilar Metals through Image Segmentation Technique (IST). *Materials*. 2018; 11(12):2460.
https://doi.org/10.3390/ma11122460

**Chicago/Turabian Style**

Sayeed Ahmed, Gulam Mohammed, Ali Algahtani, Essam R. I. Mahmoud, and Irfan Anjum Badruddin.
2018. "Experimental Evaluation of Interfacial Surface Cracks in Friction Welded Dissimilar Metals through Image Segmentation Technique (IST)" *Materials* 11, no. 12: 2460.
https://doi.org/10.3390/ma11122460