Collaborative Research: Uncertainty Quantification and Model Validation in Thin-Walled Structures: A Probabilistic Paradigm for Advancing Analysis-Based Design

合作研究：薄壁结构中的不确定性量化和模型验证：推进基于分析的设计的概率范式

• 批准号: 1235238
• 负责人: Mazdak Tootkaboni
• 金额: $ 21.53万
• 依托单位: University of Massachusetts, Dartmouth
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2017-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1235238&HistoricalAwards=false
• 关键词: Collaborative; Research; Uncertainty; Quantification; Model

This project will pursue research towards an advanced framework for nonlinear stability analysis of thin-walled structures taking into account the uncertainty associated with geometric imperfections. Thin-walled structures most commonly fail in buckling failure mode. Whether this buckling is benign or catastrophic depends, to a great extent, on the details of the structure, most importantly its geometric imperfections. The research aims at providing a leap towards uncertainty quantification and model validation in the analysis of thin-walled structures by devising a probabilistic paradigm that uses advanced uncertainty quantification techniques along with novel structural analysis methods. Methodologies for the characterization and representation of geometric uncertainties as well as probabilistic imperfection sensitivity analysis frameworks are proposed that have the potential to pave the way for a fully stochastic nonlinear analysis of thin-walled structures. The proposed techniques are complemented by experimental measurements of imperfections with high accuracy, and testing of imperfect members.If successful, the results of this research will transform how geometric imperfections are handled in advanced analysis-based design of thin-walled structures. Because of the very general and mathematics-driven nature of the stochastic approaches adopted in this project, the methodologies developed will be applicable to a wide variety of problems and will have potential impact across all science and engineering disciplines. Alongside graduate student mentoring, undergraduate research will be a focus of the efforts at both University of Massachusetts Dartmouth (UMD) and Johns Hopkins University (JHU). The involved undergraduates will be asked to share their experience with students at local high schools and a community college as well as students attending Freshman Summer Institute at UMD, in hopes that their success will be emulated by others. Also, in collaboration with programs that specifically target underrepresented groups, qualified students are invited to participate in research at both universities. In addition to academic dissemination through conferences and papers and providing all developed work as open source, the PIs will capitalize on their involvement in engineering committees (e.g. AISC, AISI etc.) to disseminate the findings outside of the academic community.

该项目将研究与几何缺陷相关的不确定性，对薄壁结构的非线性稳定性分析进行研究。薄壁结构最常见于屈曲失败模式。无论是弯曲还是灾难性的，这在很大程度上取决于结构的细节，最重要的是其几何缺陷。 该研究旨在通过设计一种使用高级不确定性量化技术以及新颖的结构分析方法来分析薄壁结构的分析中的不确定性量化和模型验证。提出了一些几何不确定性以及概率不完美灵敏度分析框架的方法论，这些方法有可能为薄壁结构的完全随机的非线性分析铺平道路。提出的技术通过高精度的实验测量和不完美成员的测试进行了补充。如果成功的结果将改变几何缺陷在基于高级分析的薄壁结构设计中如何处理。由于该项目采用的随机方法的非常普遍和数学驱动的性质，开发的方法将适用于各种各样的问题，并将在所有科学和工程学科中产生潜在的影响。除研究生指导外，本科研究将成为马萨诸塞大学达特茅斯大学（UMD）和约翰·霍普金斯大学（JHU）的努力的重点。参与的大学生将被要求与当地高中和社区学院的学生以及参加UMD大一新生学院的学生分享他们的经验，希望他们的成功能够由其他人效仿。此外，与专门针对代表性不足的群体的计划合作，邀请合格的学生参加两所大学的研究。除了通过会议和论文通过学术传播，并提供所有作为开源的开发作品外，PI还将利用其参与工程委员会（例如AISC，AISI等）的参与，以在学术界以外的研究结果传播。