Mechanical and Civil Engineering Seminar
Tackling Infrastructure Resiliency through Structural Modeling and Mechanics
The issues facing our nation's aging infrastructure are numerous, well documented, and only growing with time. However, we also find ourselves living in an age of unprecedented sensing technology that allows for greater volumes of data to be collected and analyzed than ever before. This proliferation of data has allowed the civil engineering community to build highly complex models to better assess our infrastructure and implement solutions oriented towards sustainability and resiliency, ideas that show great promise for both addressing these underlying issues and building better cities of tomorrow. Resiliency, specifically, addresses how a given structure or system absorbs a disturbance and maintains its basic function and capacity, a topic of ever-increasing importance given the recent spate of extreme weather events and the relative volatility of modern geopolitics. Resiliency is also directly related to problems in mechanics, as absorbing disturbances and maintaining capacity are clearly linked to concepts of energy dissipation and deformation.
1. In this talk, I will explore how structural models built from sensing data and applications of mechanics principals work together to tackle challenges of infrastructure resiliency. In particular, I will focus on two specific applications: accurately evaluating energy dissipation in long-span bridges and modeling the behavior of seismic protective devices in a complex isolated structure. Energy dissipation in a linear structural response is directly related to damping, and is profoundly important to a structure's response to extreme loads from natural hazards and excessive vibrations that can culminate in fatigue failure; however, the accuracy and reliability of conventional damping estimates may suffer when a structure is excited by non-uniform or narrow-band input, as is typical with loads induced by vehicular traffic and large trains travelling over long-span bridges. This talk will demonstrate that the nature of traffic loading introduces significant error in conventional damping estimates that cannot be easily resolved, but new methods that account for these error sources are proposed to overcome these challenges in identification
2. Another challenge is the development of accurate computational models for the seismic protective systems that are utilized in structures to mitigate the potentially disastrous effects of earthquakes. Because it is often infeasible or too costly to test every scenario in a laboratory setting, it is necessary to create models that capture the salient features of the seismic protective devices; however, the creation and selection of such models represents a formidable task as many seismic protective devices exhibit high degrees of nonlinear behavior when the structure is excited by large earthquakes. Various strategies of parameter identification and model selection that account for the nonlinear behavior of seismic protective systems are discussed through both experimental and computational studies.
This talk will conclude with a few brief examples of how tools developed for assessing and analyzing resilient infrastructure can be applied to other fields, such as materials science and biomechanics, to study similarly pressing problems.
Dr. Patrick Brewick earned his B.S. (2009) in Civil Engineering from the University of Notre Dame and M.S. (2010) and Ph.D. (2014) in Civil Engineering and Engineering Mechanics from Columbia University. After his Ph.D., Dr. Brewick was a Viterbi Postdoctoral Fellow at the University of Southern California in the Sonny Astani Department of Civil and Environmental Engineering. Dr. Brewick is currently a Research Scientist in the Materials Science and Technology Division of the U.S. Naval Research Laboratory. Dr. Brewick's research focuses on exploring the connections between data analytics, modeling, and mechanics and tackling the challenge of turning measurements into useful models that accurately reflect the behavior and characteristics of the physical system.