Application of Finite Element Model and Artificial Neural Network in Characterization of Al Matrix Nanocomposites Using Various Training Algorithms

In this research, the effect of the volume fraction of the alumina nanoparticles on the mechanical properties of the Al-Si matrix composites was studied. The yield strength and tensile strength increase, but the elongation decreases with the increase in the volume fraction of the particles, indicating that increasing the volume fraction of the Al₂O₃ particles can improve the strength but degrade the plasticity of the composites. The mechanical properties modeling was carried out using an artificial neural network (ANN) and finite element model (FEM). The neural network was trained using different training algorithms, hidden layers, and neuron numbers in hidden layers in order to check the system accuracy of each training algorithm at the end of learning.