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.
