Date of Award:

2013

Document Type:

Thesis

Degree Name:

Master of Science (MS)

Department:

Civil and Environmental Engineering

Advisor/Chair:

Paul J. Barr

Abstract

As part of the Long Term Bridge Performance (LTBP) Program, a single-span, prestressed, integral abutment concrete girder pilot bridge near Perry, Utah was instrumented with different sensors at various locations onto the bridge for long-term monitoring and periodic testing. One of the periodic tests conducted on this bridge was a live-load test. The live-load test included driving trucks across the bridge, as well as parking trucks along different lanes of the bridge, and measuring the deflection and strain. The data collected from these tests was used to create and calibrate a computer model of the bridge. The model was afforded the same dimensions and characteristics as the actual bridge, and then the boundary conditions (how the bridge is being supported) were altered until the model data and the live-load data matched. Live-load distribution factors and load ratings were then obtained using this calibrated model and compared to the AASHTO LRFD Bridge Design Specifications. The results indicated that in all cases, the AASHTO LRFD Specification distribution factors were conservative by between 55% to 78% due to neglecting to take the bridge fixity (bridge supports) into account in the distribution factor equations. The actual fixity of the bridge was determined to be 94%.
Subsequently, a variable study was conducted by creating new models based on the original bridge for changes in span length, deck thickness, edge distance, skew (angle of distortion of the bridge), and fixity to see how each variable would affect the bridge. Distribution factors were then calculated for each case and compared with the distribution factors obtained from the AASHTO LRFD Specifications for each case. The results showed that the variables with the largest influence on the bridge were the change in fixity and the change in skew. Both parameters provided ranges between 10% non- conservative and 56% conservative. The parameter with the least amount of influence was the deck thickness providing a range between 4% non-conservative and 19% non- conservative. Depending on which variable was increased, both increases and decreases in conservatism were exhibited in the study.