@inproceedings{167be83b1b7648da99c12ef5f32d9da1,
title = "Numerical Modeling of Part Formation in Volumetric Additive Manufacturing",
abstract = "Volumetric additive manufacturing (VAM) is a promising manufacturing method that enables the printing of high-accuracy structures in a short time. However, it faces difficulty with printing fine structures, highlighting the need for better process understanding. In this study, we propose a numerical method based on the energy threshold model to predict the shape of printed parts in VAM. We have combined a solver developed in OpenFOAM with an in-house code to interpolate images on the computational domain, which provides accurate VAM predictions. The framework has been used to study the development of the energy within the resin.",
keywords = "Energy threshold model, Photopolymerization modeling, Volumetric additive manufacturing",
author = "Roozbeh Salajeghe and Meile, {Daniel Helmuth} and Kruse, {Carl Sander} and Deepak Marla and Jon Spangenberg",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.; International Conference on Additive Manufacturing in Products and Applications, AMPA 2023 ; Conference date: 12-09-2023 Through 14-09-2023",
year = "2024",
doi = "10.1007/978-3-031-42983-5_13",
language = "English",
isbn = "978-3-031-42982-8",
series = "Springer Tracts in Additive Manufacturing",
publisher = "Springer",
pages = "189--197",
editor = "Christoph Klahn and Meboldt, {Mirko } and Ferchow, { Julian }",
booktitle = "Industrializing Additive Manufacturing. AMPA 2023.",
}