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

该小型企业创新研究（SBIR）第一阶段项目通过自动化设计软件加速了最终用途零件增材制造的增长。增材制造已成为传统减材制造的一种有吸引力的替代方案，以制造具有定制刚度和强度的最终用途部件。释放最终用途零件增材制造潜力所需的关键生产阶段是设计过程，目前需要丰富的工程经验和大量的工程设计时间。新技术将允许从当前缓慢，繁琐和容易失败的设计过程到自动化设计过程的范式转变。该算法利用高性能计算，并根据强度、特定材料特性和制造约束条件设计组件。该技术预计将减少工程设计时间，从而减少生产成本和时间，使该行业能够规模化生产。此外，通过使用自动化设计过程，可以定制材料分布以实现期望的结构响应，并且可以制造轻质结构。该小型企业创新研究（SBIR）第一阶段项目通过（a）开发优化布局、纤维路径和塑料填充物分布的新方法，（B）基于结构性能和效率生成增材制造工具路径，（b）开发基于结构性能和效率的增材制造工具路径，以及（c）实施多个失效标准以理解复合增材制造中的失效载荷。由于连续纤维丝和塑料填充物之间存在显着的成本差异，因此考虑纤维路径、碳纤维增强区域和塑料填充物布局的设计至关重要。另一个挑战是，目前的设计过程不包括一个单一的故障标准，可以预测在不同的负载情况下的故障。为了解决这两个挑战，该团队正在研究基于刚度和强度的复合材料增材制造拓扑优化，这将同时实现3D打印的几何布局和刀具路径设计。在不同方向上实现刚度和强度的各向异性材料属性，以充分利用复合材料部件的潜力。在优化过程中还实现了曲率、最小长度和宽度等刀具路径约束，以防止打印失败。最后，将开发智能切片程序，以控制3D打印机喷嘴的运动，消除因应力集中而导致的零件故障。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.