Abbett Distinguished Seminar Series

Structural health monitoring (SHM) is a critical means of assessing the performance of aging civil infrastructure. Earlier studies used heavy dynamic shakers to assess the dynamics of structures, which are unwieldy and reliance has been shifted to ambient vibration of structures to extract dynamic features. This study introduces a “virtual shaker” concept that effectively replaces the physical shaker and provides all the desired features for SHM. Examples are provided along with an App that facilitates the use of this concept to identify dynamic features. A traditional structural health monitoring (SHM) operation requires a wired system, which is often termed “hub and spoke” because the sensors are located throughout the structure and then wired to a central data acquisition server. To avoid issues associated with long cables, a unique prototype system in SHM, SmartSync, an “IoT”, with “edge computing,” which utilizes the building's existing Internet backbone as a system of “virtual” instrumentation cables and limited computations at the sensor location has been developed. Since the system is modular and largely “plug-and-play”, the units can be rapidly deployed at any location with access to power and an Internet connection and has been implemented in the Burj Khalifa, the tallest building in the world. For rural footbridges remotely located, the citizen sensing approach has been used to monitor their response in storms and to identify their dynamic feature. An example from Nicaragua will be presented. In an age of unprecedented sensing technology that allows for greater volumes of climate and infrastructure-related data to be collected and analyzed places a new demand. This proliferation of data has led to building data-driven models to better assess our infrastructure and implement solutions oriented towards sustainability and resiliency. The seminar will address new developments in system identification involving non-stationary observations and their real-time monitoring. Machine learning is becoming ubiquitous in this context and is enabling data-to-model and automated feature extraction from SHM observations. The use of various machine learning schemes embedded with Hilbert, Wavelet and Shapelet transforms will be presented with examples from Burj Khalifa, Sutong Yangtze River Bridge and the European Union’s surface wind monitoring in the Port of Genoa, Italy.

The proportion of urban population in the world is expected to increase from 54% currently to 70% by 2050. A majority of Americans also reside in urban regions - according to the 2010 census 80% of Americans reside in urban areas. Given the large number of urban citizens in the world (and US) it is imperative that we identify solutions to improve the quality of life for urban residents and economic vitality of our cities. Studies to address and fulfill the needs of envisioned future smart city infrastructure should successfully integrate a range of engineering, humanities and sociological fields such as emerging communication technologies, Internet of Things (IoT), cyber security, cloud computing, intelligent transportation, infrastructure monitoring, analyzing tourism, theorizing structures of government and bureaucracy, project financing, public policy development and implementation. In this talk, we will first three overarching themes: (1) technologically advanced infrastructure with sensing and communication capability, (2) urban operations and services improved with better decisions using multilayered “big data”, and (3) utilization of technology for social, public policy, planning and governance to improve urban quality of life. Next, we will present a sampling of relevant U.S. research and education achievements in structural control and monitoring as compiled by U.S. Panel that are envisioned as concepts for smart cities. Finally, we will present our recent work at UCF CITRS in the area of structural health monitoring where novel technologies such as computer vision, deep learning have been developed for our existing and next generation of smart city infrastructure.

This presentation describes key research works on expansive soils, the methods employed to characterize them, and fallacies in the current characterization of expansive soils. Novel swell characterization models that account for hydro, chemical, and mechanical behaviors of soils are introduced and used in various case studies to improve expansive soil stabilization practices. An innovative design method for successful stabilization of expansive soil is introduced in one case study which incorporated both basic clay mineralogy and unsaturated soil behaviors, as well as performance-based durability studies. Sulfate soil stabilization works on medium-to-high sulfate soils are presented in another case study. The last case study involving steep earthen embankment built with expansive clayey soils and experiencing recurring surficial slope failures and maintenance issues is presented along with forensic studies explaining the causes of slope failures. All case studies reveal the need for understanding of soil chemistry, including clay mineralogy and sulfate screening studies, to improve the current field stabilization and infrastructure design on expansive soils. The last section of the talk focuses on recent innovations for better health monitoring and management of civil infrastructure built on expansive soils using unmanned aerial vehicle (UAV) platforms and visualization tools, which will be valuable in validating the application of new materials in infrastructure design and construction processes as well as for health monitoring and asset management practices.

The study of community resilience requires modeling of each sector across a community, but the sectors must interact, often representing contributions from different scientific disciplines. This type of complex modeling requires the analyst to not only have an understanding of disciplines outside of engineering but to actively work and engage with key experts in sociology/planning and economics. This presentation will begin with an overview of the Center for Risk-Based Community Resilience Planning’s approach to merge engineering, social science/planning, and economics to form the Interdependent Networked Community Resilience Modeling Environment (IN-CORE). This includes learning from an interdisciplinary longitudinal field study beginning in 2016 to present for flooding in Lumberton, NC, including challenges posed by a second hurricane and the pandemic on data collection and interpretation. The presentation will close with an illustrative example application of a community planning for tornado hazard and an example of resilience-informed policy guidance.

Asphalt pavements covers over 93 percent of the paved roads in the United States. The use of recycled asphalt into pavement maintenance and construction has been a common practice. However the lack of understanding of the interaction between recycled and virgin asphalt poses a change on the efficient use of recycled asphalt, and often causes pavement premature failures. The present study addressed some fundamental aspects associated with the beneficial use of recycled asphalt into asphalt paving mixtures: 1) how much recycled asphalt can be mobilized into a uniform asphalt coating in the mixture? and 2) will the mobilized old asphalt co-mingle with virgin asphalt to form a homogeneous material? Analytical chemical procedure and fluorescence microscopy (FM), and molecular dynamics simulation have been utilized for the analyses. The results have provided better understandings on the homogenization process between the recycled and virgin asphalt; thus provide better guidance to efficient use of recycled asphalt pavements.