Department of Civil, Environmental and Ocean Engineering

Jon Miller, a research associate professor in the Department of Civil, Environmental and Ocean Engineering, was awarded the Robert G. Dean Coastal Academic Award at the 2023 American Shore and Beach Preservation Association (ASBPA) National Coastal Conference held in Providence, Rhode Island, in October 2023.

Named after the internationally recognized coastal engineer and scientist, the award “is presented in recognition of an academic who has made significant contributions furthering the community’s understanding of coastal science or engineering and in fostering young coastal scientists or engineers,” according to ASBPA.

A member of the Davidson Lab, Miller’s research focuses on the impact of coastal hazards on developed shorelines. His Coastal Engineering Research Group uses a mix of numerical modeling and field data collection to evaluate the impact of human interventions on the resilience of built and natural systems.

Said Miller of the award, “I don’t think words can express the honor that I feel in receiving an award named after my mentor and one of the greatest coastal engineers and human beings that I’ve ever encountered.” Miller worked with Dean while a graduate student at the University of Florida.

Miller was nominated by Davidson Lab Senior Research Engineer Laura Kerr, with a number of Miller’s former students also contributing to the nomination letter. Established in 1926, ASBPA was established to preserve, protect and enhance American coastal systems through research and public policy.

Department of Civil, Environmental, and Ocean Engineering Assistant Professor Yi Bao has been awarded a $420,000 U.S. Department of Transportation grant to develop a dual-purpose, low-cost robot for pipe inspection and cleaning tasks for operation in hazardous liquid pipelines. North Dakota State University serves as prime.

Titled “Dual Purpose PIG for Cleaning and Internal Integrity Assessment for Hazardous Liquid Pipelines,” the project will leverage advanced deep learning and computer vision techniques to develop the inspection tasks.

The mechanical behaviors of the robot will be studied and optimized to achieve high robustness and service life for the cleaning tasks.

Associate Professor Marouane Temimi and Assistant Professor Kaijian Liu in the Department of Civil, Environmental and Ocean Engineering recently received a $870,614 grant from the United States Geological Survey (USGS) for their project, “Leveraging USGS Hydrologic Imagery Visualization and Information System (HIVIS) for an Operational Monitoring of Streamflow using Computer Vision.” The project seeks to develop a computer-vision based system that leverages artificial intelligence and an existing network of USGS HIVIS cameras to automatically measure streamflow and water levels and determine river flow conditions on U.S. waterways.

Temimi and Liu's method consists of acquiring the real-time feed from cameras deployed and maintained by USGS of U.S. waterways, performing an automated segmentation of the received image frames, detecting changes between these images, and inferring water level, water velocity and streamflow values using a combination of machine learning and fluid velocity measurement methods.

The resulting system will run automatically and continuously, allowing for accurate monitoring of U.S. waterways in real-time. Such automatic extraction and processing of visual information would benefit entities like the U.S. National Oceanic and Atmospheric Administration’s National Weather Service in determining current water conditions and developing forecasts of future conditions.

Kaijian Liu and Yi Bao, both assistant professors in the Department of Civil, Environmental and Ocean Engineering, were recently awarded a $693,989 grant from the National Science Foundation (NSF) for their project, “Mutualistic Cyber-Physical Interaction for Self-Adaptive Multi-Damage Monitoring of Civil Infrastructure.” In collaboration with researchers from the University of Illinois at Urbana-Champaign, the three-year project received $1,199,988 in total funding through the NSF Cyber-Physical Systems program.

Cyber-physical systems are networked systems in which sensors and other computer technologies interact with and respond to a physical environment. Liu and Bao’s project will develop improved CPS system methods using deep learning in which sensors are capable of seeking out and targeting civil infrastructure damage based on system predictions, allowing for a single type of sensor to monitor multiple types of damage. The team’s solution will also develop reconfigurable sensing methods for optimizing sensor monitoring and edge cloud computing methods for efficient damage information extraction from raw sensing signals.

This system will improve the cost-effectiveness of multi-damage infrastructure monitoring by reducing the types and number of sensors needed, while maximizing the timeliness and accuracy of damage assessment and prediction at the same time.