Description

This project aims to provide functions created to calculate some mechanical properties of unidirectional composites. These functions were created using artificial neural networks (ANN) based on data collected from the literature. For more details see the following articles:

https://doi.org/10.1016/j.jmrt.2023.01.195 (Y_t)

https://doi.org/10.1016/j.compositesb.2019.107171 (G₁₂ and X_t)

https://doi.org/10.1016/j.compositesb.2011.04.042 (E₂)

The highlighted properties are: longitudinal shear modulus (G₁₂), ultimate longitudinal tensile strength (X_t), transverse elastic modulus (E₂) and the ultimate transverse tensile strength (Y_t).

How to use

The functions follow a common principle of usage, where the input data needs to be provided, varying according to each property. As an example, let's consider the function that calculates the value of G₁₂. This function requires three input values: volumetric fraction of fiber (V_f), shear modulus of fiber (G_f) and shear modulus of matrix (G_m).

Let's consider a laminate with a volumetric fraction of fibers of 0.6, made of glass fibers (G_f = 35 GPa), and with an epoxy resin (G_m = 2 GPa). To display the results, you can use either Python or MATLAB:

In Python, you can use the following code:

from your_module import G12_M_ANN

Vf = 0.6
Gf = 35
Gm = 2

G12 = G12_M_ANN(0.6, 35, 2)
print(f"G12 = {G12:.2f}")

In MATLAB, you can use the following code:

Vf = 0.6
Gf = 35
Gm = 2

[G12, ~] = G12_M_ANN(0.6, 35, 2)
fprintf("G12 = %.2f\n", G12);

Both codes will yield the same result:

G12 = 7.29

The value obtained, 7.29 GPa, represents the G₁₂ value of the unidirectional composite, measured in gigapascals (GPa).