CDS&E: Theoretical Foundation and Computational Tools for Complex Nonlinear Stochastic Dynamical Engineering Systems - A New Paradigm

CDS

• 批准号: 1403844
• 负责人: Achintya Haldar
• 金额: $ 38.75万
• 依托单位: University of Arizona
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-06-15 至 2019-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1403844&HistoricalAwards=false
• 关键词: CDS& Theoretical; Foundation; Computational; Tools

Engineered structures excited by dynamic loadings, including natural events like earthquakes, cause enormous damage in terms of loss of life, property damage, and lost economic activity. Because of the unpredictability of these events, the excitation time histories cannot be known in advance. The cost of designing structures against such excitation is enormous, and there is considerable room for improvement in the current state of knowledge in predicting the response of structures under these conditions. This study will provide a theoretical foundation and computational tools to analyze structures, and thus to improve the efficiency and overall safety of engineering designs. The impact of the study is expected to be multi-disciplinary in nature. However, the immediate major beneficiary will be the engineering profession interested in designing seismic damage-tolerant and risk-consistent structures. Since the underlying risk cannot completely be eliminated, it needs to be managed and the study will provide the necessary tools. This multi-disciplinary approach will help broaden the participation of underrepresented groups in research and will impact engineering education. A multi-disciplinary transformational theoretical concept will address the knowledge gap mentioned above. Instead of using the classical random vibration approach, the uncertain dynamic loadings will be applied in the time domain and will explicitly incorporate information on major sources of nonlinearity, improved modeling and several recently introduced energy dissipation features, and associated uncertainties, as the stochastic system goes through several phases just before failure. Some of the basic challenges are the understanding of input uncertainties, propagating them in large nonlinear dynamic systems from the parameter to the system level satisfying the underlying physics, obtaining reliable probabilistic response characteristics/metrics/statistics, and validating them using limited data. The research objectives will be achieved by taking into account sensitivity analysis, model reduction techniques, intelligent sampling schemes, and several advanced factorial schemes producing a beneficial compounding effect to obtain efficiency without sacrificing accuracy. They will be implemented in a multi-scale environment exploiting state-of-the-art computational power. The formulation will extract stochastic dynamical behavior using only tens of intelligent analyses instead of thousands of simulation-based analyses. Essentially, this is intelligent multiple deterministic analyses. The overall effort will effectively integrate education, outreach, research, and training.

受动态载荷激励的工程结构，包括地震等自然事件，会造成巨大的生命损失，财产损失和经济活动损失。 由于这些事件的不可预测性，激发时程不能提前知道。针对这种激励设计结构的成本是巨大的，并且在预测结构在这些条件下的响应方面，在当前的知识状态中有相当大的改进空间。本研究将为结构分析提供理论基础和计算工具，从而提高工程设计的效率和整体安全性。研究的影响预计将是多学科性质的。然而，直接的主要受益者将是对设计地震损伤容限和风险一致的结构感兴趣的工程专业。 由于潜在风险无法完全消除，因此需要对其进行管理，研究将提供必要的工具。这种多学科方法将有助于扩大代表性不足的群体在研究中的参与，并将影响工程教育。一个多学科的转型理论概念将解决上述知识差距。而不是使用经典的随机振动的方法，不确定的动态载荷将被应用在时域，并将明确纳入信息的主要来源的非线性，改进的建模和最近推出的几个能量耗散功能，以及相关的不确定性，随机系统通过几个阶段之前失败。一些基本的挑战是输入不确定性的理解，传播他们在大型非线性动态系统从参数到系统级满足底层物理，获得可靠的概率响应特性/度量/统计，并验证他们使用有限的数据。研究目标将通过考虑敏感性分析，模型简化技术，智能抽样计划，和几个先进的阶乘计划产生有益的复合效应，以获得效率，而不牺牲精度来实现。它们将在利用最先进的计算能力的多尺度环境中实现。该公式将仅使用数十个智能分析而不是数千个基于模拟的分析来提取随机动力学行为。从本质上讲，这是智能的多重确定性分析。总体努力将有效地整合教育、外联、研究和培训。