Rapid Identification, Control, and Uncertainty Analysis of Structural Models

结构模型的快速识别、控制和不确定性分析

• 批准号: 1100528
• 负责人: Steve Wojtkiewicz
• 金额: $ 29.99万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-04-01 至 2014-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1100528&HistoricalAwards=false
• 关键词: Rapid; Identification; Control; Uncertainty; Analysis

The main goal of this research project is to study and develop validated approaches which can accurately and efficiently determine the responses of mostly linear but locally nonlinear and uncertain structural systems. The structural systems in civil, mechanical and aerospace engineering often encounter nonlinearities that are localized. For designs, control, and identification and health monitoring, such locally nonlinear systems are, however, numerically analyzed as if the whole systems were nonlinear. The numerical analyses of such nonlinear systems can be computationally demanding. To accomplish this goal, a novel model reduction strategy utilizing the Volterra convolution integrals will be examined to include time-varying local features and feedback characteristics, and the use of emerging computing architectures such as Graphics Processing Units will be investigated for efficient data processing. The computational approaches developed in the research will be validated through applications to a series of germane benchmark problems involving dynamic analyses, identification and control of base-isolated buildings, bridge with nonlinear bearings, and bridge stay cables.The research results will enable engineers to efficiently design, identify, and optimize passive and semi-active nonlinear response control devices that are used for the mitigation of the impact of natural hazards. The research will also facilitate more efficient characterization of the impacts of structural system degradation. The project will give advanced training to graduate and undergraduate students at the University of Minnesota and University of Southern California through their involvements in the research project. The internal programs at both institutions will be utilized to recruit students from underrepresented backgrounds to work on this research project. For their wider utilization in future research and practice, the project findings will be disseminated to the broader technical community through demonstration modules developed for formal courses, conference presentations, and journal publications. The research will be integrated in the investigators' ongoing outreach activities involving elementary, middle and high school students to expose them to structural dynamics and engineering design problems involving uncertainty.

本研究项目的主要目标是研究和开发有效的方法，能够准确和有效地确定大部分线性但局部非线性和不确定结构系统的响应。在土木工程、机械和航天工程中，结构系统经常遇到局部化的非线性。然而，对于设计、控制、辨识和健康监测，这样的局部非线性系统被数值分析，就好像整个系统是非线性的。这种非线性系统的数值分析可能需要大量的计算。为了实现这一目标，将研究一种利用Volterra卷积积分的新的模型降阶策略，以包括时变的局部特征和反馈特性，并将研究使用新兴的计算体系结构，如图形处理单元，以实现高效的数据处理。研究中开发的计算方法将通过对一系列关键基准问题的应用进行验证，这些基准问题涉及基础隔震建筑、非线性支座桥梁和桥梁斜拉索的动力分析、识别和控制。研究成果将使工程师能够有效地设计、识别和优化用于减轻自然灾害影响的被动和半主动非线性响应控制装置。这项研究还将有助于更有效地描述结构系统退化的影响。该项目将通过参与研究项目，为明尼苏达大学和南加州大学的研究生和本科生提供高级培训。这两个机构的内部计划将被用来招收代表人数不足的背景的学生参与这一研究项目。为了在今后的研究和实践中得到更广泛的应用，项目成果将通过为正式课程、会议报告和期刊出版物开发的演示模块向更广泛的技术界传播。这项研究将被整合到调查人员正在进行的涉及小学生、初中生和高中生的外展活动中，让他们接触到涉及不确定性的结构动力学和工程设计问题。