Issue 62

A. Mishra et alii, Frattura ed Integrità Strutturale, 62 (2022) 448-459; DOI: 10.3221/IGF-ESIS.62.31

Si

Fe

Cu

Cr

Mn

Mg

Zn

0.4-0.8

0.0-0.7

0.4-1.4

0.0-0.2

0.0-0.15

0.8-1.2

0.0-0.25

Table 1: Chemical Composition of Aluminium alloy 6262 (wt%).

Density

Young’s Modulus

Ultimate Tensile Strength

Yield Strength

69 GPa 260 MPa Table 2: Physical and Mechanical properties of Aluminium alloy 6262. 280 MPa

2.72 g/cm 3

Ultimate Tensile Strength (MPa)

Tool rotational speed (rpm)

Tool traverse speed (mm/min)

Plunge depth (mm)

S.No

Sample ID

1. 2. 3. 4. 5. 6. 7. 8. 9.

Sample 1 Sample 2 Sample 3 Sample 4 Sample 5 Sample 6 Sample 7 Sample 8 Sample 9

800 800 800

40 50 60 40 50 60 40 50 60

0.1 0.2 0.3 0.2 0.3 0.1 0.3 0.2 0.1

167.47 188.51 164.80 165.4 186.32 171.66 188.90 179.94 176.75

1000 1000 1000 1200 1200 1200

Table 3: Experimental Parameters for preparation of specimens and obtained UTS value.

Now, the next step is to implement the Bio-inspired algorithms on the obtained data. Firstly, data from the research investigation is gathered. The dataset is set up in a CSV (comma-separated values) file format. The Google Colab platform is then imported using the CSV file. For carrying out the necessary activities, Python libraries including pandas, NumPy, seaborn, and matplotlib.pyplot were imported. The work's process procedure is depicted in Fig. 4.

Figure 4: Implementation of the Bio-Inspired Algorithms on the experimental dataset Exploratory data analysis (EDA), which is frequently used to discover what data might reveal more than the standard modeling or hypothesis assignment, aids in a complete understanding of the variables in the data collection and their

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