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Lattice Structure Design and Optimization With Additive Manufacturing Constraints

机译:具有加性制造约束的晶格结构设计与优化

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Lattice structures with different desired physical properties are promising for a broad spectrum of applications. The availability of additive manufacturing (AM) technology has relaxed the fabricating limitation of lattice structures. However, manufacturing constraints still exist for AM-fabricated lattice structures, which have a significant influence on the printing quality and mechanical properties of lattice struts. In this paper, a design and optimization strategy is proposed for lattice structures with the consideration of manufacturability to ensure desired printing quality. The concept of manufacturable element is used to link the design and manufacturing process. A meta-model is constructed by experiments and the artificial neural network to obtain the manufacturing constraints. Sizes of struts are optimized by a bidirectional evolutionary structural optimization-based algorithm with these manufacturing constraints. An arm of quadcopter is redesigned and optimized to validate the proposed method. Its result shows that optimized heterogeneous lattice structures can improve the stiffness of the model compared to the homogeneous lattice structure and the original design. Both the Von-Mises stress and the maximum displacement are reduced without increasing the weight of designed part. And by considering the manufacturability constraints, the optimized design has been successfully fabricated by the selected additive manufacturing process. Note to Practitioners-Lattice structures might fail to be fabricated by the additive manufacturing technique if the designed model exceeds the processability of the machine. Our approach has the capability of considering the manufacturing constraints in the design and optimization process. We conducted experiments to investigate the manufacturability and proposed a method that can give the domain of the design variables for a selected manufacturing process. And we also designed an algorithm that can optimize the lattice structure inside the domain of design variables. It ensures that the lattice model can be successfully fabricated by the selected process and the performance is dramatically increased compared to the original design. Engineers can use our approach to optimize the lattice structure automatically without knowing the knowledge of optimization and manufacturability.
机译:具有不同期望物理性质的晶格结构有望用于广泛的应用。增材制造(AM)技术的可用性放松了晶格结构的制造限制。但是,AM制造的格架结构仍然存在制造限制,这对格架撑杆的印刷质量和机械性能有重大影响。在本文中,针对可制造性提出了一种针对晶格结构的设计和优化策略,以确保所需的打印质量。可制造元素的概念用于链接设计和制造过程。通过实验和人工神经网络构造一个元模型以获得制造约束。通过具有这些制造约束的基于双向进化结构优化的算法来优化支柱的大小。重新设计并优化了四轴飞行器的手臂,以验证所提出的方法。结果表明,与同质晶格结构和原始设计相比,优化的异质晶格结构可以提高模型的刚度。冯-米塞斯应力和最大位移都减小了,而没有增加设计零件的重量。并且考虑到可制造性约束,通过选择的增材制造工艺成功地制造出优化设计。执业者注意-如果设计模型超出了机器的可加工性,则可能无法通过增材制造技术来制造晶格结构。我们的方法具有在设计和优化过程中考虑制造约束的能力。我们进行了实验以研究可制造性,并提出了一种方法,该方法可以为选定的制造过程提供设计变量的范围。我们还设计了一种算法,可以优化设计变量域内的晶格结构。它确保了可以通过选定的过程成功制造出晶格模型,并且与原始设计相比,其性能得到了显着提高。工程师可以使用我们的方法自动优化晶格结构,而无需了解优化和可制造性的知识。

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