All ETDs from UAB

Advisory Committee Chair

Nasim Uddin

Advisory Committee Members

Virginia P Sisiopiku

Talat Salama

Jason T Kirby

Kirby Z Al-Hamdan

Document Type


Date of Award


Degree Name by School

Doctor of Philosophy (PhD) School of Engineering


In the U.S., 40% of the bridges are considered defective and are eligible candidates for retrofit and replacement. Without interrupting the traffic and employing pre-weighed vehicles for the load testing, live load model is established and applied for the soft loading test with the application of the latest commercial bridge weigh-in-motion (BWIM) system. Field testing of three simple supported slab-girder concrete bridges on highway I-59, I-459 and I-78 is implemented to test and evaluate the BWIM system. In addition, field testing on highway I-78 is employed for enforcement screening with the comparison of the results acquired from the bending plate WIM (BPWIM) system. Analysis of three fielding tests demonstrates that the latest commercial BWIM system can not provide sufficient accuracy in axle weight identification in this type of bridge in the U.S. In order to improve the accuracy to an acceptable level for enforcement and safety assessment of existing bridges, two algorithms are proposed for the identification of axle weights and gross vehicle weight (GVW) of moving heavy vehicles. The first proposed algorithm is the modification of Moses' algorithm, which is currently employed in the commercial BWIM systems. Here the transverse behavior of the bridge is taken into account in the algorithm with the consideration of transverse load distribution of each girder to obtain influence line (IL) of each girder. Taking the calculated ILs as references, the axle weights are then calculated. The mathematical equations are derived to calculate ILs and axle weights, and the algorithms are implemented by the computer program written by the author in MATLAB. The second proposed algorithm applies dynamic programming method together with first-order Tikhonov regularization technique in the moving force identification (MFI) theory. The algorithm is based on sophisticated finite element (FE) model of the bridge. The FE model of the bridge is developed, and the proposed MFI algorithm is implemented using a computer program written in MATLAB. Based on the analysis of test results on bridge I-78, both algorithms significantly improved the accuracy of the identified axle weights in comparison with that from the commercial BWIM system.

Included in

Engineering Commons



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