Controlling the mechanical behaviour of stochastic lattice structures: The key role of nodal connectivity
Controlling the mechanical behaviour of stochastic lattice structures: The key role of nodal connectivity
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DOI：
10.1016/j.addma.2022.102730
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发表时间：
2022-03-08
影响因子：
11
通讯作者：
Jeffers, Jonathan R. T.
中科院分区：
文献类型：
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作者：
Kechagias, Stylianos;Oosterbeek, Reece N.;Jeffers, Jonathan R. T.
增材制造使得能够制造具有受控微结构和机械性能的晶格结构。这些结构在骨科行业特别有吸引力，其骨整合能力和骨匹配机械性能非常适合用于植入物和骨支架。该应用所需的广泛机械性能是一个挑战 - 它通常需要一系列周期性晶格结构，每个结构都需要单独表征。另一种方法是使用随机晶格结构，其中晶格设计参数（连接性、支柱密度和支柱厚度）与最终的机械性能之间应该存在单一关系。为了研究这一点，我们用纯钛制造了随机晶格，其连通性为 4 至 14，支柱密度为 3 至 7 [支柱/mm3]，支柱厚度为 230 和 300 μm。样本在准静态和疲劳载荷下进行了压缩测试。在静态加载中，低连通性结构表现出弯曲主导的变形，而高连通性结构表现出拉伸主导的变形。该结构的刚度范围为 0.1 至 8 GPa，高连通性和低连通性结构需要不同的 Gibson-Ashby 刚度/相对密度关系。我们发现了一个统一的多变量线性回归模型，可以根据结构的连通性、支柱密度和支柱厚度来预测相对密度。在疲劳载荷中，对于固定相对密度，将连通性从 4 增加到 14，疲劳强度提高了 60%。当使用随机晶格创建结构以最大化所需相对密度或刚度的强度时，这些发现提供了重要的设计信息。本研究中提出的单一集成模型可以定义一个结构来实现广泛的设计要求，甚至是同一组件内的梯度。要使用周期晶格实现相同的效果，需要不同的晶胞，并为每个晶胞使用单独的回归模型。
Additive manufacturing has enabled the fabrication of lattice structures with controlled micro-architectures and mechanical properties. These structures are particularly attractive in the orthopaedic industry where their osseointegration capability and bone-matching mechanical properties are ideally suited for use in implants and bone scaffolds. The broad range of mechanical properties required for this application is a challenge - it typically requires a range of periodic lattice structures, each of which require separate characterisation. An alternative approach is to use a stochastic lattice structure, where a single relationship between the lattice design parameters (connectivity, strut density and strut thickness) and resulting mechanical properties should be possible. To investigate this, we manufactured stochastic lattices in pure Titanium with connectivity from 4 to 14, strut density from 3 to 7 [struts/mm3] and strut thickness of 230 and 300 mu m. Specimens were compression tested in quasi-static and fatigue loading. In static loading, the low connectivity structures displayed bend-dominated deformation while the high connectivity structures displayed stretch-dominated deformation. The structures had a stiffness ranging from 0.1 to 8 GPa and different Gibson-Ashby stiffness/relative density relationships were required for high and low connectivity structures. A unified multivariable linear regression model was found to predict relative density from the connectivity, strut density and strut thickness of the structure. In fatigue loading, increasing the connectivity from 4 to 14 increased the fatigue strength by 60% for a fixed relative density. These findings provide important design information when creating structures using stochastic lattices to maximise strength for a desired relative density or stiffness. The single integrated model presented in this study can define a structure to achieve a broad range of design requirements, even as gradient within the same component. To achieve the same with periodic lattices would require different unit cell, with individual regression models for each unit cell used.