About this Research Topic
The multiphysics and multiscale nature of AM processes still poses significant challenges to reveal the physical phenomena occurring during and after the fabrication process. Computational models span several length scales, ranging from macroscale models for thermal stress and materials properties, mesoscale models for powder spreading/deposition, sintering and/or melt pool dynamics, and microscale models for microstructure and defects. However, most of these models have been independently developed or interdependently coupled to provide an in-depth understanding of the process itself and the behaviors of the resultant material, enabling the prediction of process-microstructure-property relationships. Novel experimental techniques, such as dynamic transmission electron microscope, in situ X-ray imaging and diffraction, and high-speed thermal imaging, have also been developed to reveal the previously inaccessible dynamics, providing data to support theoretical predictions and validating models at different temporal and spatial scales.
The aim of this Research Topic is to solicit state-of-the-art developments in the broad field of computational modeling for AM. Areas covered in this Research Topic include, but are not limited to:
• Materials of metal, plastics, and ceramics
• Advanced multi-scale computational methods
• New modeling capabilities
• High-performance computing
• Integrated computational materials engineering
• Model-based process optimization
• Applications of artificial intelligence
• Microstructure and defects
• Recrystallization and phase transformation
• Combined experimental and numerical studies
Keywords: Additive manufacturing, modeling and simulation, multiscale modeling, microstructure and defects, solidification, phase transformation
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.