Development and validation of a sensor-based health monitoring model for the Parkview Bridge deck.

Details

• Creators:
  Abudayyeh, Osama ; Aktan, Haluk ; Abdel-Qader, Ikhlas ; Attanayake, Upul
• Corporate Creators:
  Western Michigan University. College of Engineering and Applied Sciences
• Corporate Contributors:
  Michigan. Dept. of Transportation
• Subject/TRT Terms:
  • Detection and identification technologies
  • Sensors
  • Structural health monitoring
  • Bridge construction
  • Wire
  • Measuring instruments
  • Testing equipment
  • Bridge decks
  • Panels
  • Stresses
  More +
• Publication/ Report Number:
  RC-1564
• Resource Type:
  Tech Report
• Geographical Coverage:
  Michigan
• Edition:
  Final report; 2010-2012.
• Corporate Publisher:
  Western Michigan University. College of Engineering and Applied Sciences
• Abstract:
  Accelerated bridge construction (ABC) using full-depth precast deck panels is an innovative technique that brings all ; the benefits listed under ABC to full fruition. However, this technique needs to be evaluated and the performance of ; the bridge needs to be monitored. Sensor networks, also known as health monitoring systems, can aid in the ; determination of the true reliability and performance of a structure by developing models that predict structure ; behavior and component interaction. The continuous monitoring of bridge deck health can provide certain stress ; signatures at the onset of deterioration. The signatures are vital to identify type of distress and to initiate corrective ; measures immediately; as a result, bridge service life increases and eliminates costly repairs This project focused on ; the continuous monitoring and evaluation of the structural behavior of the Parkview Bridge full-depth deck panels ; under loads using the sensor network installed. Special attention was placed on the durability performance of the ; connections between precast components. However, after careful evaluation of the designs and construction process, ; it was identified that the transverse joints between deck panels are the weakest links, in terms of durability, in the ; system. ; Analysis of sensor data and load test data showed that the live load effect on the bridge is negligible. The ; dominant load is the thermal. Using three years of data from the sensors, stress envelopes were developed. These ; envelopes serve as the basis for identifying the onset of bridge deterioration. A detailed finite element model was ; developed, and the model was first calibrated using load test data. However, due to the dominance of thermal loads, it ; was required to calibrate the model using stresses developed in the structural system due to thermal loads. This was a ; great challenge due to a lack of sensors along depth of the bridge superstructure cross-section. A few models were ; identified that are capable of representing the thermal gradient profile from 12 p.m. to 6 p.m. in a summer day. The ; FE model was calibrated using sensor data and the thermal gradient profile of the specific duration. Construction ; process simulation with the calibrated model shows that all the joints between the panels are in compression, as ; expected at the design. Stress signatures were developed simulating the debonding of a transverse joint between ; panels. The signatures show a distinct pattern than what is observed from a bridge without distress. Hence, the onset ; of deterioration can be identified from the sensor data to make necessary maintenance decisions. The proposed ; signatures are applicable only during noon to 6 p.m. on a summer day, and development of deterioration models for ; the rest of the time requires development of new thermal models. Further, the stresses vary drastically following ; onset of joint deterioration; hence, identification of exact physical location of the sensors is required for fine-tuning ; the models.
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• Format:
  PDF
• Funding:
  109028
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/24421/dot_24421_DS1.pdf
• File Type:
  [PDF - 4.50 MB]
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha-512:66a2bf162b4290f49100f689d078cc134b84ac284efc1a89e36e6b3f5b2c9edaa99c1fb175ffb64db9ffafcc1ad5895e653bdfa960096510d0a1081000af9b8d