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Connecticut’s Expanding Long-Term Bridge Monitoring Project

Connecticut’s Expanding Long-Term Bridge Monitoring Project. Adam Scianna Research Assistant Richard Christenson Assistant Professor John DeWolf Emeritus Professor University of Connecticut. Outline. Introduction Bridge Monitoring Systems Monitored Bridges Conclusions. Outline.

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Connecticut’s Expanding Long-Term Bridge Monitoring Project

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  1. Connecticut’s Expanding Long-Term Bridge Monitoring Project Adam Scianna Research Assistant Richard Christenson Assistant Professor John DeWolf Emeritus Professor University of Connecticut

  2. Outline Introduction Bridge Monitoring Systems Monitored Bridges Conclusions

  3. Outline Introduction Bridge Monitoring Systems Monitored Bridges Conclusions

  4. ASCE Report Card Usually built for 50 years, average age of a bridge in the U.S. is 43 years old. According to the U.S. Department of Transportation, 600,905 (26.9%) bridges are rated structurally deficient or functionally obsolete. http://www.infrastructurereportcard.org/fact-sheet/bridges • Truck miles traveled doubled over last 20 years. • Of 3 trillion + VMT, 223 billion are from trucks.

  5. Connecticut’s Long-Term Bridge Monitoring Project In 1994, the Connecticut Department of Transportation (ConnDOT) and the University of Connecticut (UConn) started monitoring bridges on a long-term basis. Initiated to develop tools and techniques to quantitatively evaluate highway bridges in Connecticut. To fill the need in bridge monitoring to examine the application of structural health monitoring techniques to actual in-service bridge structures. Currently monitoring 6 bridges on a long-term basis. All bridges in the process of being updated with current technologies.

  6. Outline Introduction Bridge Monitoring Systems Monitored Bridges Conclusions

  7. Outline Introduction Bridge Monitoring Systems Monitored Bridges Conclusions

  8. Monitoring System Overview Demonstrate how long-term bridge monitoring systems can be used to evaluate the in-service behavior of bridges. Develop techniques for long-term structural health monitoring for different types of bridges. Used to track the response changes that could occur in a bridge over its lifespan indicative of structural damage. Identify environmental variability in the bridge dynamics and response. Intended to complement the biennial bridge inspections by ConnDOT.

  9. Monitoring System General Configurations Sensor technologies include accelerometers, strain gauges, temperature transducers, tilt meters, and displacement transducers. Temperature and tilt are collected at regular 10 minute intervals which is consistent with expected variations. Temperature data allows for analysis of temporal thermal gradients. Tilt and displacement data provide information on bridge geometry. Acceleration and strain are collected using a trigger approach. FFTs are calculated from acceleration records and are used to estimate the lower natural frequencies of the bridges. Maximum strains and distributions of strains can be used to detect changes in the structural system.

  10. Outline Introduction Bridge Monitoring Systems Monitored Bridges Conclusions

  11. Outline Introduction Bridge Monitoring Systems Monitored Bridges Conclusions

  12. Monitored Bridges in Connecticut Hartford East Hartford Danbury Cromwell New London New Haven Old Saybrook Bridgeport INTERSTATE INTERSTATE INTERSTATE INTERSTATE INTERSTATE INTERSTATE INTERSTATE INTERSTATE INTERSTATE INTERSTATE 291 384 691 395 91 91 84 95 95 84

  13. Bigfoot Bridge

  14. Bigfoot Bridge

  15. Bigfoot Bridge • Carries 3 lanes of traffic from I-384W to I-84W in East Hartford. • 3 span, 5 cell, curved cast in place concrete box girder bridge with two, single integral columns. • Cracking was discovered around the interior column-superstructure interfaces during an inspection. • 12 Temperature sensors, 6 Tilt sensors, 6 accelerometers.

  16. Bigfoot Bridge • Since 1999, many studies have been done with the bridge data including: • Lengyel and DeWolf (2003) used frequency domain plots to generate histograms which identified a total of 7 natural frequencies between 1 and 7 Hz. • Fu and DeWolf (2004) demonstrated that the cracking in the interior support columns and box girders is a result of differential temperatures due to the sun and that it is not due to live loads. • Liu and DeWolf (2006) used the data to show how modal information is influenced by temperature. • Olund and DeWolf (2007) established a basis for BHM for this bridge. • BHM will statistically evaluate: (1) the lower natural frequencies; (2) spectral acceleration levels associated with the natural frequencies; (3) diagonal terms of the sensitivity coefficient matrices for the natural frequencies; and (4) tilt values

  17. Cromwell Bridge • Carries 3 lanes of traffic over the Mattabesset River on I-91S • Three simple spans of eight W36 x 194’s with a composite concrete deck • 20 uniaxial, quarter bridge strain gages • Read at 50Hz, recorded when prescribed value is obtained

  18. Cromwell Bridge

  19. Cromwell Bridge • Since 2004, many studies have been done with the bridge data including: • The initial monitoring data was used to determine load histories, the distribution of the loads to the eight girders, and the behavior of the composite action of the bridge deck and girders (Chakraborty and DeWolf 2006, Cardini and DeWolf 2008). • The study has shown that the live load stresses per girder are smaller than those used in the AASHTO (2004) design code. • The data also showed that the bridge is fully composite, as designed. • Cardini and DeWolf (2008) established the basis for BHM of this bridge, using the strain data. • The BHM is based on a statistical comparison of (1) the distribution factors involving how the truck loads are being distributed to the different girders in the first span; (2) the peak strains in the steel girders; and (3) the neutral axis locations, determined on a continuous basis. 

  20. Flyover Bridge

  21. Flyover Bridge • One lane of traffic from I-84E to I-91N. • Dual steel tub-girder with composite concrete deck. • Three sets of three continuous spans, each simply supported. • 8 Temperature sensors and 6 tilt meters recorded at ten minute intervals. • 8 Accelerometers recorded at 90.91Hz for 30 seconds when excitation becomes larger than prescribed value.

  22. Flyover Bridge

  23. Flyover Bridge • Since 2001, many studies have been done with the bridge data including: • Virkler and DeWolf (2005) used the field data along with an extensive finite element model to evaluate the global deformations. • Concluded column cracking due to temperature variations in bridge. • Olund and DeWolf (2007) have recommended structural health monitoring to statistically evaluate the following items : • Lowest natural frequencies that occur on a regular basis. • Acceleration levels associated with the natural frequencies, based on the FFTs. • Diagonal terms of the sensitivity coefficient matrices for the natural frequencies. (Fu and DeWolf 2001) • Tilt meter values. • Scianna and Christenson (2009) used historical bridge data from the Flyover Bridge to verify a different statistical method of BHM

  24. Gold Star Bridge • Originally constructed in 1944 • Steel Truss with Suspended Center Span • 5 lanes on I-95N over Thames River

  25. Gold Star Bridge

  26. Gold Star Bridge • 12 wireless, self contained solar-powered sensors: • 4 Accelerometers • 8 Strain Gages • Solar panels individually provide power for: • Daytime observation • Recharge batteries for overnight observation • Permanent power supply necessary due to access limitations

  27. Gold Star Bridge

  28. Gold Star Bridge • Bridge has been monitored since 2007. • Currently, data is collected two minutes every hour. • This information is stored directly onto the sensor and is downloaded daily. • Study of the bridge is for BHM purposes however a part of the research is to also evaluate the feasibility of the solar-powered wireless monitoring system. • Olund (2008) recommended a set of BHM parameters for this bridge. • Peak strains or strain ranges where a change would show a change in the hanger • Strain ratios to evaluate the truss behavior • Natural frequencies, primarily local due to the limited number of accelerometers, to determine changes in effective stiffness • Sensitivity coefficients which Fu and DeWolf (2001) showed to be effective in a steel box-girder bridge.

  29. Sikorsky Bridge

  30. Sikorsky Bridge Continuous steel multi-girder bridge with composite concrete deck. Carries Connecticut Route 15 over the Housatonic River between Stratford and Milford, Connecticut. Connecticut Route 15 is a limited access highway prohibiting access by commercial vehicles. • Monitoring began in 2007. • Newest bridge in project. • 4 LVDTs to measure expansion joint movement. • 22 accelerometers • 6 tilt-meters • 16 strain gauges

  31. Sikorsky Bridge Trivedi (2009) used Sikorsky Bridge data to propose a data qualification method for the Connecticut Bridge Monitoring Network. Trivedi demonstrated a need for data qualification by observing aliasing and low signal-to-noise ratios.

  32. Outline Introduction Bridge Monitoring Systems Monitored Bridges Conclusions

  33. Outline Introduction Bridge Monitoring Systems Monitored Bridges Conclusions

  34. Conclusions • Major accomplishments from these bridge monitoring systems are: • Showing the viability of placing monitoring systems on a bridge for multi-year monitoring. • Using data to characterize each bridge, providing additional information on how bridges behave. • Using the field data to calibrate finite element models which have then been used to better define the bridge’s behavior. • Showing how deformations resulting from temperature changes have led to cracking in either the bridge or supporting columns • Developing techniques to reduce the extensive amount of data collected to data that can be used to both characterize the bridge behavior and to use for long-term structural health evaluation • Implementing a solar-power wireless BHM system has been show to be possible. • Identifying the need for data qualification for all the bridges in the Connecticut Bridge Monitoring Network and for anyone doing BHM has been demonstrated.

  35. Acknowledgements • Materials and Research Division of the Connecticut Department of Transportation • Federal Highway Administration • Connecticut Transportation Institute at University of Connecticut • NEESit • Open Source Data Turbine Initiative

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