CHS: Small: Printable Partitioning of 3D Models using Level Set Methods

CHS：小：使用水平集方法对 3D 模型进行可打印分区

• 批准号: 1524992
• 负责人: Huamin Wang
• 金额: $ 40.79万
• 依托单位: Ohio State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1524992&HistoricalAwards=false
• 关键词: CHS; Small; Printable; Partitioning; 3D

As 3D printing technology becomes mainstream and starts to revolutionize our daily lives as well as the manufacturing industries, a critical problem is about to emerge: how can we effectively divide an object into multiple printable components, when the design of this object does not provide such a partitioning? We might need such a partitioning because the object is too large to fit into the printer, or we want to reduce the printing time, or the object needs to be packed more tightly, or we just want to make part of the object replaceable or reusable. In this project, the PI will investigate object partitioning from six aspects: printability, stress load, surface details, packing, assembly, and consistency among multiple objects. The computational tools developed from this research will broaden the use of 3D printing technology in a wide range of areas. the PI's existing collaborations with industrial partners such as Adobe and NVIDIA will enable project outcomes to have broad impact, while the PI will publish demo applications and make source code available online to further accelerate dissemination. The PI will also collaborate with his institution's University Center for the Advancement of Teaching (UCAT) on incorporating the results of this research into both undergraduate and graduate graphics courses.The ultimate goal is to develop an automatic partitioning system that quickly converts the mesh of one object into a series of meshes, each of which represents an object component. Preliminary results indicate that the level set framework is a promising approach. The project encompasses a comprehensive research agenda focused on three fundamental subproblems: how to analyze the quality of a partitioning according to a variety of printing, packing, and assembly criteria; based on the previous analysis, how to improve the quality of a partitioning using level set methods; and how to facilitate the practical use of a partitioning by constructing auxiliary structures. Many of the subproblems central to this research are new and have not been systematically studied before. The development of this technology will require both theoretical and practical studies of system integration, computational efficiency, and time-stepping. Finding solutions to such issues within the level set framework will allow the PI to formulate his system as a localized iterative partitioning optimization process, whose result can meet the requirement of different 3D printing applications.

随着3D打印技术成为主流并开始彻底改变我们的日常生活以及制造业，一个关键问题即将出现：当一个物体的设计没有提供这样的划分时，我们如何有效地将一个物体划分为多个可打印的组件？ 我们可能需要这样的分区，因为对象太大而无法放入打印机，或者我们想要减少打印时间，或者对象需要包装得更紧密，或者我们只是想让对象的一部分可替换或可重复使用。 在这个项目中，PI将从六个方面研究对象划分：可打印性、应力负载、表面细节、包装、组装以及多个对象之间的一致性。 这项研究开发的计算工具将扩大 3D 打印技术在更广泛领域的应用。 PI 与 Adob​​e 和 NVIDIA 等行业合作伙伴的现有合作将使项目成果产生广泛的影响，同时 PI 将发布演示应用程序并在线提供源代码以进一步加速传播。 PI 还将与所在机构的大学教学促进中心 (UCAT) 合作，将这项研究成果纳入本科生和研究生图形课程中。最终目标是开发一种自动分区系统，快速将一个对象的网格转换为一系列网格，每个网格代表一个对象组件。 初步结果表明水平集框架是一种有前途的方法。 该项目包含一个全面的研究议程，重点关注三个基本子问题：如何根据各种印刷、包装和组装标准分析分区的质量；根据前面的分析，如何提高水平集方法的划分质量；以及如何通过建造辅助结构来促进隔断的实际使用。 这项研究的许多核心子问题都是新的，以前从未被系统地研究过。 这项技术的发展需要对系统集成、计算效率和时间步长进行理论和实践研究。 在水平集框架内找到此类问题的解决方案将使PI能够将其系统制定为局部迭代分区优化过程，其结果可以满足不同3D打印应用的要求。