Collaborative Research: HCC: Medium: Co-Design of Shape and Fabrication Plans for Direct-Ink Write Printing Through Predictive Simulation

合作研究：HCC：中：通过预测模拟共同设计直接墨水书写打印的形状和制造计划

• 批准号: 2212048
• 负责人: Paul Vouga
• 金额: $ 39.92万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-10-01 至 2025-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2212048&HistoricalAwards=false
• 关键词: Collaborative; Research; HCC; Medium; Co

Extrusion-based 3D printing is becoming an important tool in aerospace, automotive, medical, and defense applications, all of which require the highest confidence in their components. With the growth in the use of 3D-printed parts designed for cushioning, impact absorption, and integration of sensors and actuators, the importance of design tools that correctly account for and shape how a part is fabricated has never been more pronounced. Despite this need, current design tools focus exclusively on the part's outer geometric shape and ignore the printing process itself. In other words, the focus is on what is being printed rather than on how it's being printed, such as the path the printer nozzle takes when printing each layer of the part, despite the crucial effect the printing process has on the mechanical properties of the final part. This research will transform the design of 3D-printed parts by allowing users, for the first time, to design not only the part's shape but also its function. New algorithms developed by this project will automatically map from user-specified mechanical behavior to a Fabrication Plan that specifies the low-level details of how the printer should fabricate the part in order to achieve those goals. Since manufacturing applications excite students about STEM in an accessible, tangible way, this project will have additional broad impact by developing educational materials around the relationship between manufacturing and STEM careers, and by sharing project outcomes through established connections to local outreach efforts.This work will close the "form-function design gap" by creating new algorithms for co-designing both an object's macroscale shape and microscale fabrication plan, for 3D printers based on Direct-Ink-Write (DIW) technology. A microstructure-aware rod-based simulation will be developed to accurately analyze mechanical behavior of DIW-printed parts an order of magnitude more efficiently than traditional finite element methods. By allowing continuous variation of fabrication plans, the novel intermediate representation defined in this project will open the door for new interactive search and offline optimization strategies for additive manufacturing. Finally, the research will develop a novel bi-level optimization strategy that can jointly design object geometry and fabrication plan, while solving the challenge that each geometric design defines a different manifold of possible fabrication plans. The algorithms developed in this effort will be thoroughly tested against both mechanical experiments in the lab and simulated benchmarks.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.

基于挤出的3D打印已成为航空航天，汽车，医疗和国防应用中的重要工具，所有这些都需要对其组件充满信心。随着使用3D打印零件的增长，设计用于缓冲，影响吸收和集成传感器和执行器的零件，设计工具的重要性是正确地说明和塑造零件如何制造的设计工具的重要性从未如此明显。尽管需要此需求，但当前的设计工具仅专注于零件的外部几何形状，而忽略了打印过程本身。换句话说，重点是要打印的内容而不是打印的内容，例如打印零件的每一层时所采用的路径，尽管印刷过程对最终部分的机械属性产生了关键效果。这项研究将通过首次允许用户设计零件的形状，还可以设计其功能，从而改变3D打印零件的设计。该项目开发的新算法将自动从用户指定的机械行为映射到制造计划，该计划指定了打印机应如何制造零件以实现这些目标的低级细节。 由于制造应用程序以一种可访问，有形的方式激发了学生对STEM的激发，因此该项目将通过围绕制造业和STEM职业之间的关系开发教育材料以及通过与当地外展工作的建立联系来共享项目成果来产生更大的影响Direct-Ink-Write（DIW）技术。 将开发基于微观结构的杆模拟，以准确地分析二压打印零件的机械行为比传统有限元方法更有效地分析了一个数量级。通过允许制造计划的持续变化，该项目中定义的新型中间表示将为新的交互式搜索和离线优化策略添加添加剂制造打开大门。最后，该研究将制定一种新型的双层优化策略，可以共同设计对象几何图形和制造计划，同时解决每个几何设计定义了可能制造计划的不同多种歧视的挑战。这项工作中开发的算法将针对实验室中的两个机械实验和模拟基准进行彻底测试。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子和更广泛影响的评估评估标准的评估值得支持的。