The objective of this Faculty Early Career Development (CAREER) program award is to develop new and improved structural health monitoring (SHM) methods for damage diagnosis and prognosis (estimating the remaining useful life) of structures. In the latest report card for America's infrastructure, the American Society of Civil Engineers described U.S. Infrastructure as poorly maintained, unable to meet current and future demands, and, in some cases, unsafe. Expanding and improving SHM for damage assessment and maintenance is essential for establishing sustainable and resilient civil infrastructure systems and ensuring they can meet the needs of future users. The critical information obtained from SHM provides a basis for optimum allocation of financial resources towards the maintenance, rehabilitation and strengthening of the infrastructure. The new methodology will also allow rapid assessment of structures after an earthquake. This CAREER project will integrate research and education by inspiring graduate, undergraduate and K-12 students to take on the infrastructure challenges through highlighting current research needs and opportunities in the field of SHM. The project will impact students at the undergraduate and graduate levels through SHM-related involvement in the research. Outreach to K-12 students will be achieved by creating a LEGO-based summer experience related to SHM as well as helping teachers bring engineering topics to classrooms.
The research will focus on developing a new methodology for vibration-based SHM, based on probabilistic calibration of nonlinear finite element models of structures using their measured nonlinear response to moderate to large amplitude excitations such as earthquakes. In this method, time-varying short-time modal parameters and/or nonlinear normal modes of a structure will be identified from measured input-output nonlinear data. These identified features will then be used to estimate parameters of a nonlinear model of the structure through deterministic and probabilistic (Bayesian) model updating schemes. Finally, the performance of this method will be evaluated using numerically simulated data as well as available experimental data. The educational component of this project will be performed through K-12 outreach, undergraduate student education, graduate student education, and evaluation of outcomes of these educational goals.
