GOALI/Collaborative Research: Optimization of Infrastructure-Scale Thin-Walled Tube Towers including Uncertainty
GOALI/Collaborative Research: Optimization of Infrastructure-Scale Thin-Walled Tube Towers including Uncertainty
批准号:
1912354
负责人:
Andrew Myers
金额:
$44.97万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-01 至 2024-08-31
中文摘要
薄壁管是一种高性能、高效的结构元件,在机械系统和民用基础设施中有着广泛的应用。然而,这种管道可能很脆弱:当由坚硬的材料制成并受到压缩时,它们的失效对制造过程中不可避免地出现的缺陷和现场不可避免地发生的复杂载荷非常敏感。缺乏对这种敏感性的基本性质的理解一直是结构工程和制造进步的长期障碍。民用基础设施和一些机械系统的巨大规模带来了额外的挑战,因为管状元件可能太大,无法进行原型设计、迭代设计和全尺寸测试。由于这些原因,使用不满意的方法来估计结构强度,要么用过于保守或不准确的控制力学简化来推断试验结果,要么使用不可靠的计算方法。这两种方法大多忽略了制造、材料选择和结构行为之间的紧密联系,这限制了与制造创新相结合的结构创新的潜力。“学术与行业联络资助机会”(GOALI)项目为克服这些限制提供了途径;该奖项的成果将用于提高机械系统效率,促进创新,加强和重建民用基础设施,振兴国内制造业,并为高中、本科生和研究生提供教育。利用首次进入工厂的机会,该项目将产生一个开创性的数据集,对薄壁管的缺陷和结构行为(包括不确定性)进行耦合测量,并对各种非弹性钢性能进行近两个数量级的模拟。该研究结合了实验和数值方法,包括在多种横截面作用下的复杂载荷下薄壁管的非弹性行为的详细测量,几何缺陷和残余应力的高分辨率测量,外壳制造和崩溃行为的有限元模拟,以及集成到基于模拟的优化过程中的混合数据/物理驱动的随机场模型。多尺度系列物理测试提供了对存在复杂和相应现象的薄壁管力学的理解:几何缺陷、残余应力、非弹性和复杂载荷。这些测试然后为模拟提供信息,使随机优化方法能够转变民用基础设施和机械系统的设计实践。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
Thin-walled tube is a high-performing and efficient structural element with versatile applications in mechanical systems and civil infrastructure. Such tubes, however, can be fragile: when made of stiff materials and subjected to compression, their failure is acutely sensitive to imperfections that inevitably arise during manufacturing and to complex loading that inevitably occurs in the field. A lack of understanding of the fundamental nature of this sensitivity has been a longstanding barrier to advancement of structural engineering and manufacturing. The enormous scale of civil infrastructure and some mechanical systems present additional challenges, as tubular elements can be too large to be prototyped, iteratively designed and tested at full-scale. For these reasons, structural strength is estimated using unsatisfactory methods, either extrapolating test results with overly conservative or inaccurate simplifications of the governing mechanics or using computational methods that are unreliable. Both approaches mostly ignore the strong links between manufacturing, material selection, and structural behavior and this restricts the potential for structural innovations that are coupled with innovations in manufacturing. This Grant Opportunities for Academic Liaison with Industry (GOALI) Program award provides a path to overcome these limitations; the outcomes of this award will serve to improve mechanical system efficiencies, to foster innovations to strengthen and rebuild civil infrastructure, to revitalize domestic manufacturing, and to educate high school, undergraduate and graduate students. Leveraging first-of-its-kind factory access, this project will yield a seminal dataset, coupling measurements of imperfections and structural behavior of thin-walled tubes, including uncertainty, with simulations across nearly two orders of magnitude of scale for a broad range of inelastic steel properties. The research combines experimental and numerical methods, including detailed measurements of the inelastic behavior of thin-walled tubes under complex loading with multiple cross-sectional actions, high-resolution measurements of geometric imperfections and residual stresses, shell finite element simulations of manufacturing and collapse behavior, and hybrid data/physics-driven random field models that are integrated into a simulation-based optimization process. The multi-scale series of physical tests provides understanding of the mechanics of thin-walled tubes in the presence of complicating and consequential phenomena: geometric imperfections, residual stresses, inelasticity, and complex loading. These tests then inform simulations that will enable stochastic optimization methods to transform design practice for civil infrastructure and mechanical systems.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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