CAREER: Structural Health Monitoring, Diagnosis and Prognosis of Minimally Instrumented Structural Systems

这个教师早期职业发展（CAREER）计划奖将开创一个新的框架，以评估建筑物和桥梁的最低仪表结构系统的安全性。 研究的最终目标是预测仪器结构的剩余寿命与知识的状态的损伤，材料退化，并纳入不确定性的加载环境。这项工作将集中在两种类型的负载，丰富的土木工程和共享许多共同的特点与其他系统在机械/生物医学和航空航天应用。该项目将调查：（i）地震荷载引起的建筑结构的低周疲劳破坏和（ii）交通荷载引起的桥梁的高周疲劳。建筑物和桥梁的结构系统是大的，复杂的，并且只能用相对于自由度总数相对较少的传感器来测量。监控这些系统的运行安全性是一项重大的工程挑战。在这个项目中开发的计算方法将使早期损伤诊断和未来的寿命预测的结构系统使用最少的仪器。该项目将整合多学科研究、教育，并扩大工程和数学领域代表性不足的群体的参与。该项目的研究探讨了一种新的框架，用于对遭受疲劳等累积损伤的结构进行结构健康监测。该项目偏离了将损伤识别为模型参数变化的常规方法。相反，这个项目将研究一个新的框架，结合概率损伤力学和动态状态估计。将开发一种新的算法，该算法将能够最佳地结合多尺度有限元模型的预测能力与传感器测量的预测能力，以重建结构的完整动态响应。重建的响应允许评估整个结构的累积疲劳损伤状态，从而在达到临界水平之前预测潜在的损伤。一旦确定了结构的损伤状态及其不确定性，就可以预测结构的未来状况，从而进行概率损伤预测。该研究涉及计算算法的开发，实验室实验和现场验证使用真实的数据，从最低限度的仪表操作桥梁和建筑结构。

This Faculty Early Career Development (CAREER) Program award will pioneer a novel framework to assess the safety of minimally instrumented structural systems of buildings and bridges. The ultimate goal of the research is to predict remaining life of instrumented structures with knowledge of the state of damage, of material degradation and incorporating uncertainties in the loading environment. The work will focus on two types of loading that abound in civil engineering and that share many common characteristics with other systems in mechanical/bio-medical and aerospace applications. The project will investigate: (i) seismic load induced low-cycle fatigue damage in building structures and (ii) traffic load induced high-cycle fatigue in bridges. The structural systems of buildings and bridges are large, complex and can only be instrumented with a relatively small number of sensors in relation to the total number of degrees-of-freedom. Monitoring the operational safety of these systems is a significant engineering challenge. The computational methods developed in this project will enable early damage diagnosis and future life prognosis of structural systems using minimal instrumentation. This project will integrate multi-disciplinary research, education, and broadens the participation of underrepresented groups in engineering and mathematics.The research in this project investigates a new framework for structural health monitoring of structures subjected to cumulative damage such as fatigue. This project deviates from the conventional approach of identifying damage as changes in model parameters. Instead, this project will investigate a novel framework that combines probabilistic damage mechanics and dynamic state estimation. A new algorithm will be developed which will be capable of optimally combining the predictive capabilities of multi-scale finite element models with that of sensor measurements to reconstruct the complete dynamic response of a structure. The reconstructed response allows assessment of the state of cumulative fatigue damage throughout the structure, thus anticipating potential damage before it reaches a critical level. Once the state of damage together with its uncertainty is determined, the condition of the structure can be projected into the future in order to perform probabilistic damage prognosis. The research involves development of computational algorithms, laboratory experiments and field validation using real data from minimally instrumented operational bridge and building structures.