Optimal Topology Design under Fabrication and Demand Uncertainties

制造和需求不确定性下的最优拓扑设计

• 批准号: 0928613
• 负责人: James Guest
• 金额: $ 36万
• 依托单位: Johns Hopkins University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0928613&HistoricalAwards=false
• 关键词: Optimal; Topology; Design; under; Fabrication

The research objective of this award is to develop optimal design methodologies that account for manufacturing defects and demand uncertainties in small-scale structures. In engineering design, there is a natural tendency to push the limits of capacity of existing materials or employ new high performance materials. While this increases efficiency by using more sparse and slender elements, the designs also become more susceptible to flaws that may impair response. The research will address this issue by incorporating fabrication and demand uncertainties into methods of topology optimization, which is an emerging class of design tools for optimizing material distribution across a design domain. The PIs will exploit the relationships between the model for the system uncertainties and the mathematical forms used in the algorithms for topology optimization. Furthermore, methods will be explored for identifying those parameters whose uncertainties have a dominant influence on design. To ensure that the methods can be practically applied, fabrication is included in the scope of work. Tests results from fabricated specimens will be used to quantify fabrication errors and provide feedback for updating the uncertainty models. If successful, the results of this research will facilitate design of efficient structures with optimized and/or tailored reliability. Potential applications include high performance material microstructures, compliant mechanisms, and tunable capacitors. The optimization under uncertainty theory will be incorporated into a general (non-heuristic) topology optimization methodology to ensure wide impact of the results. The educational plan of the project includes curriculum development and research opportunities for undergraduate and graduate education. It also includes engineering design outreach activities to Baltimore Polytechnic High School. The investigators will leverage the visually appealing aspects of topology optimization to attract undergraduates and high school students to research opportunities provided by the project.

该奖项的研究目标是开发最佳的设计方法，以说明制造缺陷并要求小规模结构中的不确定性。 在工程设计中，有一种自然的趋势，即推动现有材料的容量限制或采用新的高性能材料。 尽管这通过使用更稀疏和细长的元素来提高效率，但设计也更容易受到可能损害反应的缺陷的影响。该研究将通过将制造和要求不确定性纳入拓扑优化方法来解决此问题，这是一种新兴的设计工具，用于优化设计领域的材料分布。 PI将利用系统不确定性模型与算法中使用的数学形式之间的关系，以进行拓扑优化。此外，将探讨方法以识别那些不确定性对设计具有主要影响的参数。为了确保可以实际应用这些方法，将制造包含在工作范围中。制造标本的测试结果将用于量化制造错误，并为更新不确定性模型提供反馈。如果成功，这项研究的结果将促进具有优化和/或量身定制的可靠性的有效结构的设计。潜在的应用包括高性能材料微观结构，合规机理和可调节电容器。 在不确定性理论下的优化将纳入一般（非螺旋）拓扑优化方法中，以确保结果的广泛影响。该项目的教育计划包括课程开发和研究生教育的研究机会。 它还包括向巴尔的摩理工高中的工程设计外展活动。 调查人员将利用拓扑优化的视觉吸引力方面吸引本科生和高中生来研究项目提供的机会。