CAREER: Next-Generation Shape Optimization of Geometrically Complex Artifacts
CAREER: Next-Generation Shape Optimization of Geometrically Complex Artifacts
批准号:
0745398
负责人:
Krishnan Suresh
金额:
$40.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2008
资助国家:
美国
项目状态:
已结题
起止时间:
2008-01-01 至 2013-08-31
中文摘要
该职业奖的研究目标是为几何复杂产品的形状优化建立下一代计算框架。现有的形状优化方法通常速度慢、繁琐,而且缺乏健壮性,特别是当产品的几何形状复杂时。因此,今天的产品模型在优化之前,通过去除功能,在几何上得到了简化。该框架将用稳健且数学合理的代数简化方法取代脆弱的几何简化方法。将使用伴随校正器方法来避免因简化而出现的错误。此外,还将探索新的特征灵敏度方法,以消除形状优化过程中重新分析的需要。建议的框架将针对航空航天、汽车和精密机械行业中发现的复杂人工制品进行应用和测试。如果成功,这项研究的结果将对行业和社会产生重大影响,主要是通过设计高度优化、成本更低和环境友好的产品。在设计过程中可以探索更广泛的产品设计,这将导致新的新产品。在计算上,该框架将几何简化和形状优化结合在一起,将这些研究领域与未来发展的潜力联系起来。作为试验台,这项研究的结果将被威斯康星大学和威斯康星技术学院的研究生和本科生用来参加全国汽车设计挑战赛。研究成果还将通过在两个校区开设技术选修课和扩大学生设计经验,嵌入本科课程。在业界的支持下,参与的学生,特别是少数族裔和女性,将获得奖学金,以完成必要的CAD培训,并参加全国范围的比赛。
英文摘要
The research objective of this CAREER award is to establish a next-generation computational framework for shape optimization of geometrically complex products. Existing methods of shape optimization are typically slow and tedious, and lack robustness, especially when a product is geometrically complex. Product models are therefore geometrically simplified today, prior to optimization, through feature removal. The proposed framework will replace fragile geometric simplification methods with robust and mathematically sound algebraic simplification methods. An adjoint corrector method will be used to avoid errors that appear as a result of simplification. In addition, novel feature sensitivity methods will be explored that will eliminate the need for reanalysis during shape optimization. The proposed framework will be applied and tested against complex artifacts found in the aerospace, automobile and precision machinery industries.If successful, the results of this research will have a major impact on industry and society, primarily through the design of highly optimized, less expensive and environmentally friendly products. A wider range of product designs can be explored during the design process which will lead to novel new products. Computationally, this framework will integrate geometric simplification and shape optimization, linking these research areas with the potential for future advances. As a test bed, the results of this research will be used by graduate and undergraduate students from the University of Wisconsin and Wisconsin Technical Colleges to compete in national car design challenges. The research results will also be embedded within the undergraduate curricula through technical elective offerings and expanded student design experiences at both campuses. With support from industry, participating students, especially minority and women, will receive scholarships to complete necessary CAD training and take part in nation-wide competitions.
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项目类别:--
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