STTR Phase I: A Next-Generation Computationally Efficient Software for Simulating Additive Manufacturing Processes of Metals

这个小型技术转移研究(STTR)第一阶段项目的更广泛的影响是为小规模制造推进具有高计算速度和效率的模拟软件。这项拟议的技术将使用当前资源的一小部分(从集群到桌面)更快地执行模拟(从几天到几个小时)，同时仍然准确地捕获底层物理。这样一个强大的工具将作为一个平台，促进加法制造领域的更多创新，给部件设计和材料开发带来范式变化。这将为许多工业部门带来50-100倍的效率提升。这个STTR第一阶段项目解决了现有制造过程仿真模型所依赖的有限元分析(FEA)框架导致的计算效率低下的问题。提出的创新包括三个新的概念：一个新的有限元框架，称为加性有限元框架(AFEA)，以及两种方法，称为拓扑共形再生离散化(TCRD)和混合建模(HM)。拟议的项目将推进这些金属AM过程的计算模拟技术，将它们设计成工业规模的翻译。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact of this Small Technology Transfer Research (STTR) Phase I project is to advance simulation software with high computational speed and efficiency for small-scale manufacturing. The proposed technology will perform simulations faster (from days to hours) using a fraction of current resources (from clusters to desktop), while still capturing the underlying physics accurately. Such a powerful tool will serve as a platform that facilitates more innovations in the field of additive manufacturing, bringing paradigm changes in part design and material development. This will bring efficiency improvements of 50-100x to many industrial sectors. This STTR Phase I project addresses low computational efficiency of existing manufacturing process simulation models due to the finite element analysis (FEA) framework on which the models rely. The proposed innovation consists of three novel concepts: a new FEA framework called additive FEA (AFEA) framework, and two methods called Topologically Conformal Regenerative Discretization (TCRD) and Hybrid Modeling (HM). The proposed project will advance these techniques for computational simulation of AM processes for metals, engineering them for translation at industrial scale.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.