All ETDs from UAB

Advisory Committee Chair

Nasim Uddin

Advisory Committee Members

Jason Kirby

Christopher Waldron

Ian Hosch

Ashraf Al-Hamdan

Document Type


Date of Award


Degree Name by School

Doctor of Philosophy (PhD) School of Engineering


The use of heavy vehicles is the backbone of freight shipment and the corner stone of economic success in the United States. National projections predict that freight shipments will double in the next ten years. This increase in freight demand must be accommodated by increasing the number of trucks, increasing the weight of trucks, or both. It is quite obvious that increasing the number of heavy vehicles or the weight of heavy vehicles will inversely affect the bridge lifespan. Thus, congestion problem due to increased number of heavy vehicles must be addressed. Moreover, additional repetitive loading may cause fatigue cracking in these bridge superstructures and limit their service lives. The useful life of highway bridge superstructures is directly affected by trucks' configurations (e.g. gross vehicle weight, axle weight, and axle spacing), as well as the damages that occur in the bridge deck and in the main superstructure elements. Also, the damage magnitude depends on the construction material and the structure's components. Additionally, to maintain the bridge functionality, accelerated maintenance actions increases the associated bridge costs. In this dissertation, the weigh-in-motion (WIM) and bridge WIM (BWIM) recorded data were used to identify the main characteristics that widely affect the bridge's lifespan and cause serious fatigue stress problems due to the most prevalent trucks passing over the bridge. These characteristics include the configurations of the representative heavy vehicle, gross vehicle weight (GVW), axle weight (AW), axle spacing, and the characteristics of the bridge population sensitive to load effect and fatigue. Characteristics of typical trucks were synthesized and processed from acquired data. The total numbers of trucks with different axle configurations were recorded monthly during a certain period. Histograms of the percentage distribution of truck traffic classified by the number of axles in both directions were developed. The results showed that the most prevalent trucks were two-axle and five-axle. The gross vehicle weight data of these trucks was processed by a MATLAB program to predict the Generalized Extreme Value (GEV) of the GVW over a 1000 year return-period using the Extreme Value Theory (EVT). Accordingly, the axle's weights were calculated. In the same way, the axle's weights data were processed to estimate the extreme axle weights and, as well, the corresponding GVW. Characterizing the bridge population sensitive to load effect and fatigue was done based on a static and dynamic analysis of the estimated characterized truck, proposed 97-kip truck, and the current rating 80-kip truck, as well as the most frequent GVW. According to the recorded WIM data of two- and five-axle trucks, histograms were built to detect the most frequent GVW. Steel and concrete girder bridges of different spans were modeled by two filed-verified different computer programs, a commercial program (CSiBridge) and AASHTOWare program (Virtis), in addition to a limited case using LS-DYNA. The results provided the most critical sections and rating factors of girders in different bridges' span lengths under selective heavy truck presence. Maintaining both the safety and serviceability of deteriorating highway bridge networks necessitates suitable bridge maintenance system (BMS) tools that can maximize cost effectiveness. Numerous experiments have been conducted to detect the long-term mechanical properties of the epoxy resin materials used in one of the most common techniques in strengthening and maintenance, namely, Fiber Reinforced Polymers (FRP) strengthening. Furthermore, Finite Element Analysis (FEA) models were developed, using the ANSYS software, to simulate the unstrengthened and FRP strengthened bridges with the original and aged properties of construction and retrofitting materials. These models were used to develop the bridge performance chart for the capacity of the bridge, with and without strengthening interventions, as a BMS tool. Increased freight demand may adversely affect the bridge's life-span. There were two different scenarios that may be applied when a current traffic situation changes. These scenarios either change the traffic (doubling the number of heavy vehicles) or change the traffic load (increase the heavy vehicle weight limit). Bridge analysis for the bridge's remaining life was done for both these scenarios. The synthesized recorded WIM data, along with the results of different specialized softwares (CSiBridge and Virtis), were used to calculate the total lifespan of steel bridges (steel component and concrete deck) following the AASHTO fatigue calculation procedures. The data compared the effect of heavier trucks to the effect of doubling the number of heavy vehicles under the present limits of the bridge's service life. The total number of maintenance periods was directly affected by the estimated service life of the bridge. The bridge cost and the whole life cost is directly impacted upon by the changing of the current traffic situation. Increasing the number and/or weight of heavy vehicles impacts cost. These costs are calculated using an NCHRP project program. Cost impact associated with different possible remedy actions was calculated. This cost impact was used to calculate the bridge's cost over the span of planning period (PP) of interest. Finally, as the research covers various aspects, starting with the vehicle characterization thru characterizing bridge population; providing the FE modeling approach of unstrengthened and FRP strengthened bridges, and ending with the investigation of the effect of increasing traffic and/or traffic loads on bridges' lifespan and the associated cost impact during a planning period of interest; it may be considered as a decision-making tool for departments of transportation (DOTs). These tools included a BMS, with the PP cost, for the current and future traffic situations, along with different remedy actions and cost impacts.

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