Shi-Long Jia

Deep Learning-Based Inverse Identification of the Johnson–Cook Yield and Fracture Parameters for Ti-6Al-4V Fabricated by Laser Powder Bed Fusion Using Batch Finite Element Simulation Data

Finite element analysis (FEA) is a key tool for predicting the mechanical behavior of additively manufactured parts. However, its predictive accuracy relies on the underlying constitutive model and, in particular, on precise model parameters. The main purpose of this study is to develop and validate a condition-grouped...