Compared with traditional design methods, generative design significantly attracts engineers in various disciplines. In thiswork, howto achieve the real-time generative design of optimized structures with various diversities and controllable structural complexities is investigated. To this end, a modified Moving Morphable Component (MMC) method together with novel strategies are adopted to generate high-quality dataset. The complexity level of optimized structures is categorized by the topological invariant. By improving the cost function, the WGAN is trained to produce optimized designs with the input of loading position and complexity level in real time. It is found that, diverse designs with a clear load transmission path and crisp boundary, even not requiring further optimization and different from any reference in the dataset, can be generated by the proposed model. This method holds great potential for future applications of machine learning enhanced intelligent design.

翻译：与传统设计方法相比，生成设计显著吸引了各工程领域的关注。本文研究了如何实现具有多种多样性和可控结构复杂度的优化结构的实时生成设计。为此，采用改进的可移动变形组件（MMC）方法结合新颖策略生成高质量数据集。优化结构的复杂度级别通过拓扑不变量进行分类。通过改进成本函数，训练WGAN根据输入载荷位置和复杂度级别实时生成优化设计。研究发现，所提模型能够生成具有清晰传力路径和分明边界、无需进一步优化且与数据集中任何参考结构不同的多样化设计。该方法为未来机器学习增强智能设计应用展现了巨大潜力。