Collaborative Research: Optimal Design of Smart Damping for Structural Systems to Mitigate the Impacts of Natural Hazards

合作研究：结构系统智能阻尼的优化设计，以减轻自然灾害的影响

• 批准号: 1436018
• 负责人: Erik Johnson
• 金额: $ 20.61万
• 依托单位: University of Southern California
• 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: 2014-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1436018&HistoricalAwards=false
• 关键词: Collaborative; Research; Optimal; Design; Smart; Collaborative; Research; Optimal; Design; Smart

Our nation's aging infrastructure presents a significant engineering and public policy challenge, particularly given that projected financial resources will not be adequate to fund the requisite structural system repairs and replacements to stem this infrastructure deterioration. The inevitable result is that buildings, bridges, roads, tunnels and other structural systems will frequently remain in service past their initial design lifetimes and design loads. Consequently, novel cost-effective solutions must be pursued to ensure the structural integrity of such systems, particularly when subjected to natural hazards such as earthquakes and strong winds. Structural systems equipped with smart damping systems, whose properties can be adapted to their changing environments, are one promising solution. This award supports fundamental research to enable design methods to incorporate dissipative and nonlinear nature of controllable dampers yielding smart damper designs with increasing performance at reduced cost. This will benefit the U.S. society by making controllable dampers a realistic approach for addressing the dilemma of aging infrastructure. The research involves disciplines of structural mechanics, control theory and computational science. This multi-disciplinary and multi-institutional project will help broaden participation by students from groups traditionally underrepresented in engineering research and will positively impact engineering education at both the undergraduate and graduate levels.Hybrid Model Predictive Control can affect a significant advancement in controllable damping capabilities to reduce structural response and improve structural safety. The damper design will incorporate the physical dissipative limitations of the dampers through the use of hybrid system models to capture the on-off switching and to model predictive control for nonlinear or constrained dynamical systems. While the promise of this approach for controllable damping design has been established, several barriers must be overcome before wider implementation is possible. Using a set of bridge and building testbed structural systems and several models of controllable damping devices, this project will investigate learning-based methods and parallel computing techniques. The result will reduce the often prohibitive computational expense of repeatedly solving the high-order mixed integer-quadratic programming problems that arise from application to realistic structure models. Critical numerical and laboratory experiments will validate the efficacy of these nonlinear controllable damping approaches and establish that the resulting designs are robust to uncertainties and errors in the structural model, sensor noise and hardware limitations that challenge implementation.

我们国家的老化基础设施提出了重大的工程和公共政策挑战，特别是考虑到预计的财务资源将不足以资助必要的结构系统维修和更换，以阻止这种基础设施降低。不可避免的结果是，建筑物，桥梁，道路，隧道和其他结构系统将经常在其初始设计的生命寿命和设计负载之后保留。因此，必须采用新颖的成本效益解决方案，以确保此类系统的结构完整性，尤其是在遭受天然危害（例如地震和强风）时。配备智能阻尼系统的结构系统可以适应其不断变化的环境，是一个有前途的解决方案。该奖项支持基本研究，以使设计方法能够结合可控阻尼器的耗散性和非线性性质，从而以降低的成本效果提高智能阻尼器设计。这将通过使可控制的阻尼成为解决衰老基础设施困境的现实方法，从而使美国社会受益。该研究涉及结构力学，控制理论和计算科学的学科。这个多学科和多机构的项目将有助于扩大传统上代表性不足的团体的学生参与工程研究，并将对本科和研究生级别的工程教育产生积极影响。Hybrid模型预测控制可能会影响可控湿能力的重大进步，从而减少结构响应并提高结构安全。 阻尼器设计将通过使用混合系统模型来捕获开关开关并建模非线性或约束动力学系统的预测控制，从而结合阻尼器的物理耗散局限性。尽管已经建立了这种方法对可控阻尼设计的承诺，但必须在更广泛的实施之前克服几个障碍。该项目使用一组桥梁和建筑测试台结构系统以及几种可控阻尼设备的模型，将研究基于学习的方法和并行计算技术。结果将减少反复解决高阶混合整数 - 季度编程问题的经常刺激的计算费用，这些编程是由应用到现实结构模型引起的。关键的数值和实验室实验将验证这些非线性可控阻尼方法的功效，并确定所得设计的设计对结构模型，传感器噪声和硬件限制的不确定性和错误具有牢固性，从而挑战了实施。