Automated Ice Inference and Monitoring on the Veterans’ Glass City Skyway Bridge
Publication: Journal of Bridge Engineering
Volume 17, Issue 6
Abstract
Under certain weather conditions, the Veterans’ Glass City Skyway (VGCS) Bridge in Toledo, Ohio, accumulates ice on the stay sheaths in such a way that has led to large fragments falling into traffic lanes. To aid the Ohio Department of Transportation (ODOT) in their response to this, an automatic inference and monitoring system was implemented. This system utilizes existing weather station measurement data to infer possible events, alerting officials and providing tools to further assess the situation. The development of the decision, the algorithm, and implementation process are presented. The system was implemented in January 2011, and it warned of and monitored an icing event that occurred February 20–24, 2011. Ice fell shortly after the system indicated conditions were met for icefall. ODOT personnel used the ice inference system to assist them in managing the response to the icing event.
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Acknowledgments
This project was sponsored and supported by the Ohio Department of Transportation. The authors gratefully acknowledge their financial support. The authors thank Kathleen Jones and Charles Ryerson of the U.S. Army Cold Regions Research and Engineering Laboratory for the extensive analysis and support developing the criteria that led to development of such a successful first phase of the project. The authors also thank Mike Madry and Jeff Baker (both now retired from ODOT) for their assistance in defining criteria for the ice inference analysis and Joshua Belknap and Ali Arbabzadegan of the University of Toledo for their assistance in documenting the icing events.
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Copyright
© 2012 American Society of Civil Engineers.
History
Received: May 27, 2011
Accepted: Jan 3, 2012
Published online: Jan 5, 2012
Published in print: Nov 1, 2012
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