论文标题
将深度学习整合到CAD/CAE系统中：3D概念轮的生成设计和评估
Integrating Deep Learning into CAD/CAE System: Generative Design and Evaluation of 3D Conceptual Wheel
论文作者
论文摘要
正在积极进行工程设计研究将人工智能（AI）集成到计算机辅助设计（CAD）和计算机辅助工程（CAE）中。这项研究建议在概念设计阶段进行基于学习的CAD/CAE框架，该阶段自动生成3D CAD设计并评估其工程性能。提出的框架包括七个阶段：（1）2D生成设计，（2）维度降低，（3）潜在空间中实验的设计，（4）CAD自动化，（5）CAE自动化，（6）传输学习和（7）可视化和分析。提出的框架通过路轮设计案例研究证明了这一框架，并表明可以将AI实际纳入最终用途的产品设计项目中。工程师和工业设计师可以通过使用此框架以及AI估计的工程性能结果，共同审查大量生成的3D CAD模型，并为随后的详细设计阶段找到概念设计候选。
Engineering design research integrating artificial intelligence (AI) into computer-aided design (CAD) and computer-aided engineering (CAE) is actively being conducted. This study proposes a deep learning-based CAD/CAE framework in the conceptual design phase that automatically generates 3D CAD designs and evaluates their engineering performance. The proposed framework comprises seven stages: (1) 2D generative design, (2) dimensionality reduction, (3) design of experiment in latent space, (4) CAD automation, (5) CAE automation, (6) transfer learning, and (7) visualization and analysis. The proposed framework is demonstrated through a road wheel design case study and indicates that AI can be practically incorporated into an end-use product design project. Engineers and industrial designers can jointly review a large number of generated 3D CAD models by using this framework along with the engineering performance results estimated by AI and find conceptual design candidates for the subsequent detailed design stage.
