FEM and ANN modeling of stress concentration factors (Kt) of circular plates with various circular holes according to internal and external pressures

Stress concentration factors (SCFs) play a critical role in the structural integrity of circular plates subjected to internal and external compressive loading. This study uses Artificial Neural Networks (ANNs) and the Finite Element Method (FEM) to examine SCFs of circular plates with different circular hole configurations. The stress distribution and stacking patterns were thoroughly examined using FEM. Then, using geometrical and loading parameters, an ANN model was created that can predict SCFs. The FEM-generated data sets were used to train and validate the ANN model, which showed that it could generalize to various hole configurations and pressure levels. A comparison of the FEM and ANN findings revealed a strong connection, confirming the suggested ANN model’s dependability. The study’s conclusions offer valuable information for perforated plate design and optimization, offering a computationally effective substitute for traditional numerical methods.