GOALI/Collaborative Research: Topology Optimization for Additively Manufactured Metal Castings

这个学术与工业联络（GOALI）计划合作研究奖的资助机会将通过将拓扑优化设计方法与增材制造工艺相结合来开发集成的设计-制造框架。拓扑优化是设计高性能器件和组件的系统计算工具。 然而，拓扑优化的设计通常在几何形状上是复杂的，并且因此难以（如果不是不可能的话）用传统的制造工艺来制造。增材制造正在成为克服这一障碍的潜在手段，因为其逐层制造方法能够在不对生产成本或产量产生负面影响的情况下创建几何复杂的组件。然而，尽管有这种自然的协同作用，增材制造和拓扑优化方法尚未集成到一个全面的设计制造框架中。在没有这种集成的情况下，拓扑优化设计可能与增材制造不兼容，并且需要繁琐且潜在有害的后处理更改以符合制造限制。 因此，本研究的主要目标是通过（i）识别、表征和理解增材制造工艺对零件几何形状施加约束的方面以及（ii）改进拓扑优化方法以纳入这些约束，针对竣工条件优化零件。因此，这项工作将大大提高工程设计过程的效率和所得到的工程工件的功效。 集成的设计-制造优化能力将对包括汽车、农业和航空航天在内的广泛行业带来相当大的好处，其中（例如）实现轻量化大规模组件可以节省大量能源。多学科研究团队还将创建综合教育模块，并为代表性不足的群体提供研究机会。由于每个增材制造工艺都有特定的制造限制，研究团队将专注于设计通过3D砂打印工艺制造的部件，其中金属部件通过将熔融金属铸造到3D打印砂模中制成。 该团队将识别、表征和量化这种增材制造和金属铸造工艺链的各个方面，这些方面对部件几何形状施加了约束，并将这些约束数学上纳入拓扑优化方法。 拓扑优化方法将植根于基于投影的算法，其中制造设计变量耦合到物理和分析空间以自然地实现可制造性。保持设计框架的严谨性将有助于扩展到其他#8232;材料和增材制造工艺。 该团队将设计，制造和实验测试一个工程组件的案例研究（由工业合作伙伴提供），以验证开发的设计制造框架。

This Grant Opportunity for Academic Liaison with Industry (GOALI) Program collaborative research award will develop an integrated design-manufacture framework by coupling topology optimization design methods with additive manufacturing processes. Topology optimization is a systematic, computational tool for designing high performance devices and components. Topology-optimized designs, however, are often geometrically complex and thus difficult, if not impossible, to fabricate with traditional manufacturing processes. Additive manufacturing is arising as a potential means for overcoming this obstacle, as its layer-wise fabrication approach enables the creation of geometrically complex components without negatively affecting production cost or throughput. However, despite this natural synergy, additive manufacturing and topology optimization approaches have not yet been integrated into a comprehensive design-manufacture framework. Without this integration, topology-optimized designs may be incompatible with additive manufacturing and require tedious and potentially deleterious post-process alterations to conform to manufacturing restrictions. The primary goal of this research is thus to optimize parts for as-built conditions by (i) identifying, characterizing, and understanding the aspects of an additive manufacturing process that impose constraints on part geometry and (ii) advancing topology optimization methods to incorporate these constraints. Thus the work will substantially improve both the efficiency of the engineering design process and the efficacy of the resultant engineered artifacts. The integrated design-manufacture optimization capability will be of considerable benefit to a broad range of industries, including automotive, agricultural, and aerospace where (for example) the realization of lightweight large-scale components could lead to substantial energy savings. The multidisciplinary research team will also create integrated educational modules and provide research opportunities for underrepresented groups.As manufacturing constraints are specific to each additive manufacturing process, the research team will focus on designing components to be manufactured via the 3D sand printing process in which metal parts are made by casting molten metal into 3D printed sand molds. The team will identify, characterize, and quantify the aspects of this additive manufacturing and metal casting process chain that impose constraints on component geometry and mathematically incorporate these constraints into the topology optimization method. The topology optimization approach will have roots in projection-based algorithms where manufacturing design variables are coupled to the physical and analysis spaces to naturally achieve manufacturability. Maintaining rigor in the design framework will facilitate extension to other
materials and additive manufacturing processes. The team will design, fabricate, and experimentally test an engineered component for a case-study (provided by the industrial partner) to validate the developed design-manufacture framework.