While significant progress has been made in the last few years, the reliability of Additively Manufactured (AM) parts is often less than desirable as they suffer from manufacturing defects and hence subpar strength and fatigue life. To address this challenge, numerical methods are sought to provide insight into the process and help accelerate progress in raising the quality of AM parts. In metal AM applications, assessing the amount of unfused powder, melt pool volumes, and metallurgical phase transformations is often of interest. In this work, we introduce a generic framework for assessing metallurgical phase transformations, building on a previously-developed general simulation framework for predicting temperature evolution, distortions, and residual stresses.
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