SBIR Phase I: Computational Synthesis of 3D Printed Composite and Infill Layouts

SBIR 第一阶段：3D 打印复合材料和填充布局的计算合成

• 批准号: 2334913
• 负责人: Zhichao Wang
• 金额: $ 27.5万
• 依托单位: NOVINEER, INC.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-12-15 至 2024-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2334913&HistoricalAwards=false
• 关键词: SBIR; Phase; Computational; Synthesis; 3D

This Small Business Innovation Research (SBIR) Phase I project expedites the growth of additive manufacturing for end-use parts through automated design software. Additive manufacturing has emerged as an appealing alternative to traditional subtractive manufacturing to fabricate end-use parts with tailored stiffness and strength. A critical production stage required to unlock the potential of additive manufacturing for end-use parts is the design process, which currently requires extensive engineering experience and high engineering design time. The new technology will allow a paradigm shift from the current slow, tedious, and failure-prone design process to an automated design process. The algorithm utilizes high-performance computing and designs components based on strength, specific material properties, and manufacturing constraints. The technology is expected to reduce engineering design time and, as a result, the production cost and time, which will enable the industry to scale production. Additionally, by using the automated design process, the material distribution can be tailored to achieve the desired structural responses, and lightweight structures can be fabricated. The reduction in weight results in a reduction in fuel consumption in aviation and auto industries, which will provide both ecological and economic benefits.This Small Business Innovation Research (SBIR) Phase I project advances the state of the art by (a) developing novel approaches to optimize layout, fiber paths, and plastic infill distribution, (b) generating additive manufacturing toolpaths based on structural performance and efficiency, and (c) implementing multiple failure criteria to understand failure loads in composite additive manufacturing. Due to the significant cost difference between continuous fiber filament and plastic infill, it is crucial to consider the design of fiber paths, carbon fiber reinforced regions, and plastic infill layout. Another challenge is that current design processes do not include a single failure criterion that can predict failure under different loading scenarios. To address these two challenges, the team is investigating a stiffness and strength-based topology optimization for composite additive manufacturing that will enable the design of the geometric layout and toolpath for 3D printing simultaneously. Anisotropic material properties for stiffness and strength in different directions are implemented to utilize the full potential of composite parts. Toolpath constraints such as curvature, minimum length, and width are also implemented in the optimization process to prevent print failure. Finally, an intelligent slicing program will be developed to control the movement of the 3D printer nozzle and eliminate part failure due to stress concentration.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.

这项小型企业创新研究（SBIR）I阶段项目通过自动设计软件加速了最终用途零件的增材制造的增长。添加剂制造已成为传统减法制造业的一种吸引人的替代品，以制造具有量身定制的刚度和强度的最终用途零件。设计过程是最终用途零件的添加剂生产潜力所需的关键生产阶段，目前需要广泛的工程经验和高工程设计时间。这项新技术将使范式从当前的慢速，乏味和失败的设计过程转变为自动设计过程。该算法利用了基于强度，特定材料特性和制造约束的高性能计算和设计组件。该技术有望减少工程设计的时间，因此，生产成本和时间，这将使行业能够扩展生产。此外，通过使用自动设计过程，可以对材料分布进行量身定制以实现所需的结构响应，并且可以制造出轻质的结构。体重减轻的减轻导致航空和汽车行业的燃料消耗减少，这将提供生态和经济利益。该小​​型企业创新研究（SBIR）I阶段项目通过（a）开发新颖的方法来优化布局，纤维路径，纤维路径和塑料工具的实现（b）实施添加性效率（b）实施（b）实施（b）实施（b）的新方法，并实现（b）实施（B）在复合添加剂制造中。由于连续纤维细丝和塑料填充物之间的成本差异很大，因此考虑纤维路径，碳纤维增强区域和塑料填充布局的设计至关重要。另一个挑战是，当前的设计过程不包括单个故障标准，该标准可以在不同的加载方案下预测故障。为了应对这两个挑战，该团队正在研究对复合添加剂制造的基于刚度和强度的拓扑优化，该优化将使几何布局和工具路径的设计同时设计。各向异性材料的刚度和强度在不同方向上的特性被实施，以利用复合零件的全部潜力。在优化过程中还实现了曲率，最小长度和宽度等工具路径约束，以防止打印故障。最后，将制定一项智能切片计划，以控制3D打印机喷嘴的运动，并因压力集中而消除零件故障。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审查标准来通过评估来获得支持的。