Interest in components with detailed structures increased with the progress in advanced manufacturing techniques in recent years. Parts with graded lattice elements can provide interesting mechanical, thermal, and acoustic properties compared to parts where only coarse features are included. One of these improvements is better global buckling resistance of the component. However, thin features are prone to local buckling. Normally, analyses with high computational effort are conducted on high-resolution finite element meshes to optimize parts with good global and local stability. Until recently, works focused only on either global or local buckling behavior. We use two-scale optimization based on asymptotic homogenization of elastic properties and local buckling behavior to reduce the effort of full-scale analyses. For this, we present an approach for concurrent local and global buckling optimization of parameterized graded lattice structures. It is based on a worst-case model for the homogenized buckling load factor, which acts as a safeguard against pure local buckling. Cross-modes residing on both scales are not detected. We support our theory with numerical examples and validations on dehomogenized designs, which show the capabilities of our method, and discuss the advantages and limitations of the worst-case model.
翻译:近年来,随着先进制造技术的进步,对详细结构组成部分的兴趣随着先进制造技术的进展而增加。具有分级装饰元素的部件可以提供有趣的机械、热和声学特性,而只有粗糙特征的部件除外。这些改进之一是使部件具有更好的全球阻力。然而,薄质特征容易在当地造成挤压。通常,对高分辨率有限元素的中间体进行高计算分析,以优化具有良好全球和当地稳定的部件。直到最近,工作只侧重于全球或地方的压强行为。我们使用基于弹性特性和局部压强行为的无症状同质化的两层优化,以减少全面分析努力。为此,我们提出了一个同时进行本地和全球对参数定级装饰优化的方法。该方法基于一个最差的情况模型,该模型是防止纯粹的当地压强行为。两个尺度的交叉模式都没有被检测出来。我们用数字实例和验证模型设计模型的理论支持我们的理论,该模型显示了我们方法的最差的优势和优势。</s>