GOALI/Collaborative Research: Optimization of Infrastructure-Scale Thin-Walled Tube Towers including Uncertainty

GOALI/合作研究：包括不确定性在内的基础设施规模薄壁管塔的优化

• 批准号: 1912481
• 负责人: Benjamin Schafer
• 金额: $ 44.9万
• 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: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1912481&HistoricalAwards=false
• 关键词: GOALI; Collaborative; Research; Optimization; Infrastructure

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.

薄壁管是一种高性能和高效的结构元件，在机械系统和民用基础设施中具有广泛的应用。然而，这种管可能是脆弱的：当由刚性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负载非常敏感。对这种敏感性的基本性质缺乏了解一直是结构工程和制造业发展的长期障碍。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而无法进行原型制作，迭代设计和全尺寸测试。由于这些原因，结构强度的估计使用不令人满意的方法，要么外推的测试结果过于保守或不准确的简化的管理力学或使用计算方法是不可靠的。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。这个赠款机会与行业学术联络（GOALI）计划奖提供了一条克服这些限制的途径;该奖项的成果将有助于提高机械系统的效率，促进创新，以加强和重建民用基础设施，振兴国内制造业，并教育高中，本科和研究生。利用首个同类工厂的访问，该项目将产生一个开创性的数据集，耦合薄壁管的缺陷和结构行为的测量，包括不确定性，模拟近两个数量级的规模，用于广泛的非弹性钢性能。该研究结合了实验和数值方法，包括在具有多个横截面作用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，制造和倒塌行为的壳体有限元模拟，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。多尺度系列的物理测试提供了对薄壁管在复杂和相应现象存在下的力学的理解：几何缺陷、残余应力、非弹性和复杂载荷。这些测试为模拟提供信息，使随机优化方法能够改变民用基础设施和机械系统的设计实践。该奖项反映了NSF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。