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

STTR 第一阶段：用于模拟金属增材制造工艺的下一代计算高效软件

• 批准号: 2112175
• 负责人: Ajit Achuthan
• 金额: $ 25.6万
• 依托单位: Additive Manufacturing Innovations LLC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2112175&HistoricalAwards=false
• 关键词: STTR; Phase; Next; Generation; Computationally

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.

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推进具有高计算速度和效率的小规模制造模拟软件。 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，促进增材制造领域的更多创新，为零件设计和材料开发带来范式变革。这将使许多工业部门的效率提高50- 100倍。该STTR第一阶段项目解决了现有制造过程仿真模型由于模型依赖有限元分析（FEA）框架而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：一个新的有限元分析框架称为添加剂有限元分析（AFEA）框架，和两种方法称为拓扑共形再生离散（TCRD）和混合建模（HM）。 拟议的项目将推进金属AM工艺的计算模拟技术，将其转化为工业规模的工程。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。