数据驱动的参数化生成式设计研究与应用

Research and application of data-driven parametric generative design

文中探讨了数据驱动的参数化生成式设计理论与实践,强调生成式设计的自下而上、自组织和生成等核心特征。通过案例分析与设计实践,提出了如何从用户面部特征数据中提取设计变量,进而驱动创新的设计过程,从而创造与用户身体特征相匹配的个性化产品。以加州迪士尼公园路径设计和一款基于鱼群运动轨迹的鱼缸设计为两个分析案例,说明了物质自然的客观规律在形态方案探索中的作用。研究进一步通过一个3D打印定制化眼镜的案例,探索了如何通过用户面部特征识别技术获取设计变量,并将其应用于参数化生成式设计程序中,以产生既符合功能要求又满足审美需求的个性化眼镜。结果表明:参数化生成式设计能够有效地利用自组织系统的优化原则,生成符合物质自然规律的最佳形态,强调尊重自组织系统客观性的重要性,以及基于设计变量进行形态创新和功能性、人性化设计的方法论意义。

This article delves into the theory and practice of data-driven parametric generative design,emphasizing the core characteristics of generative design such as bottom-up approaches,self-organization,and genesis.Through case analyses and design practices,the paper proposes methods for extracting design variables from user facial feature data,thereby driving innovative design processes that result in personalized products tailored to individual body characteristics.The design of pathways in Disneyland California and an aquarium design based on the movement trajectories of schools of fish serve as two analytical case studies,illustrating the role of material nature's objective laws in the exploration of form solutions.The research further explores how design variables can be acquired through facial feature recognition technology in users,and applied within a parametric generative design framework to produce personalized eyewear that meets both functional requirements and aesthetic desires.This study demonstrates that parametric generative design can effectively leverage the optimization principles of self-organizing systems to generate optimal forms in accordance with the laws of material nature,underscoring the importance of respecting the objectivity of self-organizing systems and the methodological significance of morphological innovation and functional,humanized design based on design variables.