Estimation of stress concentration factors in butt and T-welded joints using artificial neural network-based models

In this study, the capability of artificial neural network-based models in estimation of stress concentration factor of welds in forms of butt-welded joint (single-V and double-V) and T-welded joint (as-welded and TIG-dressed conditions) was investigated. The joints were analyzed under axial-tension and bending load cases. A large set of finite element models were used for each configuration in order to train, validate and test the corresponding networks. The estimations by the neural network- based models yielded the results with higher accuracy for all configurations compared to the available parametric equations. The proposed models also cover the joints with broader range of local weld parameters.