Robust Design to Account for Geometric Imperfections in Small-Scale Structures

稳健的设计可解决小型结构中的几何缺陷

• 批准号: 1130640
• 负责人: Wei Chen
• 金额: $ 40万
• 依托单位: Northwestern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1130640&HistoricalAwards=false
• 关键词: Robust; Design; Account; Geometric; Imperfections

The objective of this research is to develop a design methodology with robust shape and topology optimization (RSTO) that accounts for various forms of geometric uncertainties in association with imperfections in manufacturing small-scale structures. The research will provide a level-set based dynamic topological design model that conveniently captures various forms of local and global geometric uncertainties. A computational framework for probabilistic topology design will be developed to integrate high performance uncertainty propagation techniques with existing deterministic topology optimization methods. The design testbed addresses the critical demand in sustainable energy source through the design of optical metamaterials. The seamless integration of the nano-fabrication and the RSTO methodology that requires no post processing of geometry boundary offers 'hardware-in-the-loop' validation using fully functional prototypes. If successful, the proposed research will transform existing techniques in deterministic topology optimization to new methods for simultaneous shape and topology optimization under geometric uncertainties. Although the testbed is focused on a nano-engineered system, the methodology is general and widely applicable to handling geometric uncertainties at micro, meso, and macro scales where geometric variations have a large impact on product performance. The fruition of this research will offer a unique research and educational environment for multidisciplinary researchers across the fields of design and nano-manufacturing while training students in an interdisciplinary learning environment. The metamaterial design applications developed from this research will serve as excellent examples for promoting engineering awareness in K-12 by illustrating what is new in engineering and its impact on creating a sustainable environment.

本研究的目的是开发一种具有鲁棒形状和拓扑优化 (RSTO) 的设计方法，该方法可以解决与制造小型结构缺陷相关的各种形式的几何不确定性。 该研究将提供一种基于水平集的动态拓扑设计模型，该模型可以方便地捕获各种形式的局部和全局几何不确定性。 将开发概率拓扑设计的计算框架，将高性能不确定性传播技术与现有的确定性拓扑优化方法相集成。 该设计测试台通过光学超材料的设计满足了可持续能源的关键需求。 纳米制造和 RSTO 方法的无缝集成无需对几何边界进行后处理，使用功能齐全的原型提供“硬件在环”验证。 如果成功，所提出的研究将把确定性拓扑优化中的现有技术转变为几何不确定性下同时形状和拓扑优化的新方法。 尽管该测试平台专注于纳米工程系统，但该方法是通用的，广泛适用于处理微观、细观和宏观尺度的几何不确定性，其中几何变化对产品性能有很大影响。 这项研究的成果将为设计和纳米制造领域的多学科研究人员提供独特的研究和教育环境，同时在跨学科学习环境中培训学生。这项研究开发的超材料设计应用程序将通过说明工程领域的新内容及其对创建可持续环境的影响，成为提高 K-12 工程意识的绝佳范例。