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

我国日益老化的基础设施构成了重大的工程和公共政策挑战，特别是考虑到预计的财政资源将不足以支付必要的结构系统维修和更换资金，以遏制基础设施的恶化。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寿命和设计荷载之后继续使用。因此，必须寻求新的具有成本效益的解决办法，以确保这类系统的结构完整性，特别是在遭受地震和强风等自然灾害时。配备智能减震系统的结构系统，其性能可以适应不断变化的环境，是一种很有前途的解决方案。该奖项支持基础研究，使设计方法能够结合可控阻尼器的耗散和非线性特性，从而以更低的成本实现性能更高的智能阻尼器设计。这将使可控阻尼器成为解决基础设施老化困境的现实方法，从而使美国社会受益。这项研究涉及结构力学、控制论和计算科学等学科。这个多学科和多机构的项目将有助于扩大学生的参与，这些学生来自传统上在工程研究中代表性较低的群体，并将对本科生和研究生的工程教育产生积极影响。混合模型预测控制可以影响可控阻尼能力的显著进步，以减少结构响应并提高结构安全性。阻尼器的设计将包括阻尼器的物理耗散限制，通过使用混合系统模型来捕捉开关切换和非线性或约束动态系统的模型预测控制。虽然这种方法在可控减振设计方面的前景已经确立，但在更广泛地实施之前，必须克服几个障碍。使用一套桥梁和建筑试验台结构系统和几个模型的可控减震装置，本项目将研究基于学习的方法和并行计算技术。其结果将减少在实际结构模型应用中反复求解高阶混合整数-二次规划问题所产生的通常令人望而却步的计算费用。关键的数值和实验室实验将验证这些非线性可控减振方法的有效性，并确定所产生的设计对结构模型、传感器噪声和硬件限制中的不确定性和误差具有鲁棒性，这些限制对实施构成挑战。

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.