Remote Sensing Techniques for Highway Retaining Walls
Detroit, Michigan, USA
Retaining walls are a critical component of highway systems with most states having thousands of miles of walls in their networks. Structural monitoring using remote sensing techniques can quantitatively assess the performance of retaining walls in service and can offer the data needed to perform risk assessments and prioritize infrastructure investments.
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Principal Investigators
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Co-Principal Investigators
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Other Contributors
Kidus Admassu, M.Sc.
MDOT
Metrics
Funding Source
MDOT
About the Project
Highways consists of a large number of civil engineered structures that are vital to their safe and efficient operations including bridges, culverts, retaining walls, among others.
In particular, retaining walls are an important part of highway systems with most states having thousands of miles of walls in their networks. For instance, earth and service road retaining structures were popularly constructed along many freeway corridors in the metropolitan Detroit region in Michigan since the early 1960’s. To date, highway managers have focused on the health and upkeep of bridges in their networks but recent federal directives is requiring the adoption of risk management strategies for all highway structures including retaining walls. In this regard, many highway managers are struggling with how to make asset management decisions regarding retaining walls given their large inventories of walls and their complex soil-structure behavior. Structural monitoring offers one possible approach to quantitatively assessing the performance of retaining walls in service and offering the data needed to perform risk assessment decisions.
In Michigan, the major types of retaining walls employed to support service roads, overpasses and earth structures along major highway corridors include: cantilever reinforced concrete walls, concrete walls supported by caisson tiebacks, mechanically stabilized earth (MSE) walls, sheet pile walls and soldier pile walls. Ten site visits (selected from a list of 74 potential retaining wall sites presented by MDOT) were conducted May through October 2017. Of the ten selected locations, two of the ten walls have been identified as potentially showing some structural distress to warrant instrumentation. The two walls identified include a caisson supported RC wall along M-10 near Schaefer Highway and a cantilever RC wall along I-696 at Central Park Boulevard supporting W Eleven Mile Road on the south side of I-696.
In this study, two retaining wall structures in the metropolitan Detroit region are studied using a wireless monitoring system permanently installed. One wall is a traditional cantilever retaining wall while the second is a tie-back wall type. The monitoring systems consist of three major types of sensing transducer: inclinometers, strain gauges and thermistors. These transducers were interfaced to a wireless sensing node termed Urbano which has been designed for long-term unattended operations in infrastructure monitoring applications. It is designed with a cellular modem which utilizes cellular communication to push data to the Internet. Long-term tilt and strain response of the wall is used to identify soil loads on the backwall and to validate performance features of the walls. Using the measured performance of the walls, wall demand and capacity are estimated to assess the risk of failure of each wall monitored. The monitoring strategies for both walls considered sensing transducer types to assess the mechanical behavior of the wall and environmental factors driving wall behavior. The intention of the sensors selected is to provide valuable data from which the load demand and structural capacity of the walls can be evaluated or estimated for risk assessment.
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Learn MoreJerome Lynch PhD
Principal Investigator
Co-Founder
Donald Malloure Department Chair, Department of Civil and Environmental Engineering
Professor of Civil and Environmental Engineering
Professor of Electrical Engineering and Computer Science
Jerome P. Lynch, Ph.D. has been a member of the faculty at the University of Michigan since 2003. He was formerly the Donald Malloure Department Chair of Civil and Environmental Engineering. He was formerly a Professor of Civil and Environmental Engineering and a Professor of Electrical Engineering and Computer Science. In addition to his work as the Director of the U-M Urban Collaboratory Initiative, he is also the Director of the Laboratory for Intelligent Systems Technology (LIST). Dr. Lynch is now with Duke University.
Dr. Lynch’s work focuses on the boundary between traditional civil engineering and related engineering disciplines (such as electrical engineering, computing science, and material science), converting infrastructure systems into more intelligent and reactive systems through the integration of sensing, computing, and actuation technologies. These cyber-physcial systems (CPS) greatly enhance performance while rendering them more resilient against natural and man-made hazards.
Dr. Lynch completed his graduate studies at Stanford University where he received his Ph.D. in Civil and Environmental Engineering in 2002, M.S. in Civil and Environmental Engineering in 1998, and M.S. in Electrical Engineering in 2003. Prior to attending Stanford, Dr. Lynch received his B.E. in Civil and Environmental Engineering from the Cooper Union in New York City. He has co-authored one book and over 200 articles in peer reviewed journal and conferences. Dr. Lynch has been awarded the 2005 ONR Young Investigator Award, 2009 NSF CAREER Award, 2009 Presidential Early Career Award for Scientists and Engineers (PECASE), 2012 ASCE EMI Leonardo da Vinci Award and 2014 ASCE Huber Award.
Recent Projects
Adda Athanasopoulos-Zekkos PhD, MSc
Co-Principal Investigator
Associate Professor
Dr. Adda Athanasopoulos-Zekkos holds a joint BS/MSc in Civil Engineering from the University of Patras, Greece (2003), and received her MSc (2004) and PhD (2008) Degrees in Geotechnical Engineering from the University of California, Berkeley. In 2004 she received the National Science Foundation Graduate Research Fellowship for her PhD research. She joined the Civil and Environmental Engineering Department at the University of Michigan, Ann Arbor in 2008 as an Assistant Professor, and is now an Associate Professor since 2015.
She has received the NSF CAREER award (2013), the 2014 Faculty Excellence Award by the CEE Dept at the Univ. of Michigan, the 2015 ASCE Arthur Casagrande Award and the 2015 ASCE Thomas Middlebrooks Award, and more recently the 2016 Chi Epsilon (XE) Outstanding Teaching Award.
Her research focuses on soil liquefaction, seismic slope stability, and flood protection systems and soil structures under extreme loading like hurricanes and earthquakes and new technologies and methodologies to design, monitor and reinforce them. Her work recently has focused on investigating the dynamic response of gravelly soils by integrating unique laboratory testing and advanced field testing, as well as Discrete Element Method numerical modeling.
Recent Projects
Dimitrios Zekkos PhD, MS
Co-Principal Investigator
Dimitrios Zekkos, PhD, PE, is an Associate Professor in the Civil and Environmental Engineering Department of the University of Michigan. His research interests are in the nexus of geotechnical engineering, natural hazards, and informatics. Dr. Zekkos received his undergraduate degree from the University of Patras in Greece, and a MSCE and PhD Degree in Geoengineering from the University of California at Berkeley. Prior to joining the University of Michigan in 2008, he worked for Geosyntec Consultants in the San Francisco Bay Area. He has published more than 100 publications in refereed journals and conferences, and has been recognized with several awards including the Middlebrooks Award, Casagrande Award and Collingwood Prize by the American Society of Civil Engineers (ASCE), and the Outstanding Innovator Award by the International Society for Soil Mechanics and Geotechnical Engineering. He is the CEO of ARGO-E LLC, a startup based in Ann Arbor with a focus on informatics in civil engineering.