There are over 250,000 reinforced concrete bridges in the U.S. many of which do not have a load rating on record nor the plans required to perform the calculations. The U.S. Army owns and maintains hundreds of these bridges throughout the U.S. This dissertation describes the development of multiple regression models to estimate the load rating of reinforced concrete bridges. An exploratory data analysis of the 2017 NBI data was performed for the selection of a representative data sample. The data was found to have multiple errors and required significant processing in order to extract a reliable sample for modeling. After processing, a data sample of 31,112 bridges remained, providing sufficient sample for model training and testing. A six-variable model (Model A) was determined to provide the best performance while maintaining a desired low level of complexity. The model was tested by comparing the percentage of cases that fell within its 95% prediction interval, which resulted in 94.9% of the real values falling within the prediction interval. Given the concerns that arose of the quality of the 2017 NBI data during its exploration, as built-drawings from 50 slab bridges throughout the U.S. were collected. With these drawings a new data sample was generated by calculating the load rating of each bridge. Availability of the as-built drawings provided the opportunity to investigate other variables not available in the 2017 NBI, most notably the slab thickness. This data sample was significantly smaller than the previous one, therefore a repeated 10old cross-validation approach was taken to evaluate model performance. It was determined that a five-variable model (Model B) provided the best trade-off between complexity and performance. Model B performed significantly better than Model A due to the inclusion of the slab thickness variable. The models presented in this dissertation provide a valuable tool for reinforced concrete bridge owners tasked with the assigning a load rating when no structural plans are available helping.

No description available.

No description available.

No description available.

No description available.

No description available.

No description available.

For nearly half a century, institutions of higher education have implemented bridge programs in order to increase the retention and graduation rates of at-risk students (Pascarella & Terenzini, 2005). In fact, summer bridge programs (SBPs), which typically occur prior to a student's freshman fall term, are among the oldest strategies used to improve college retention rates (Garcia, 1991). Surprisingly, even though SBPs are widely acknowledged by both students and program administrators to be beneficial, there is very little empirical evidence assessing their effectiveness (Garcia, 1991; Kluepfel,1994; Pascarella & Terenzini; Rita and Bacote,1997; Ackerman 1990; Gandara & Maxwell-Jolly, 1999). This study, therefore, used a mixed methods approach to investigate the various adjustment issues of participants versus non-participants in a summer bridge program for engineering students at a predominantly White institution (PWI) in the mid-southeastern region of the United States. Specifically, the Academic, Social, Personal-Emotional, and Goal Commitment/Institutional Attachment subscales of the Student Adaptation to College Questionnaire (SACQ) were utilized (Baker & Siryk, 1999) for this purpose. One important finding that the SACQ revealed was that the personal-emotional scale was significant for gender since scores for men were higher than for females. The Summer Bridge Inventory (SBI) that was employed in this research also revealed that summer bridge participants and the director of support programs shared similar opinions about the strengths and weaknesses of the program and its related activities. In conclusion, college administrators and directors of summer support programs should carefully assess programmatic outcomes to ensure that their institutions' SBPs provided the needed supports that will enhance the retention and graduation rates of at-risk students in engineering. / Ph. D.

State Departments of Transportation (DOT's) have established Bridge Management Systems (BMS) with procedures to aid in estimating service lives of bridge components and elements. Service life estimates, together with cost information, are used to develop life-cycle costs of bridges. These estimates are necessary to prioritize and optimize bridge improvement programs within budgetary constraints. Several factors, including age, traffic, and environment have been identified in current BMS literature as being directly responsible for the deterioration of bridge components or elements. However, no formal methodology exists to determine the effects of the environment. Estimating bridge elements service lives, without considering the effect of environmental factors, could potentially lead to biased estimates. A methodology is proposed using statistical analysis to determine the effects of environmental regions on service life estimates of steel girder bridge component (concrete deck) and element/protective system (girder paint) using bridge inspection field data collected by bridge inspectors. Further, existing deterioration models are incapable of using the non-numeric element level inspection data, which most state DOT's have been collecting for nearly thirty years per Federal Highway Administration guidelines. The data format used were the numerical condition appraisal scale (9 through 0) for concrete deck component, and the letter condition appraisal (G-F-P-C) for steel girder paint element. The methodology proposed an environmental classification system for use in BMS programs. In addition, least squares mean and corresponding standard errors and also means and corresponding standard deviations of service lives at the component and element/protective system levels were estimated. The steel girder paint estimated service lives can be used in scheduling maintenance, repair and rehabilitation operations, and also in life-cycle costs analysis at the project and network levels. Because of limitations in the concrete deck data sets, the estimated concrete deck service lives are not true estimates of their service lives but do reflect the influence of environmental exposure characteristics on their performance. / Ph. D.

This thesis investigates the repair of impact-damaged prestressed concrete bridge girders with strand splices and fabric-reinforced cementitious matrix systems, specifically for repair of structural damage to the underside of an overpass bridge girder due to an overheight vehicle collision. Collision damage to bridges can range from minor to catastrophic, potentially requiring repair or replacement of a bridge girder. This thesis investigates the performance of two different types of repair methods for flexural applications: strand splice repair, which is a traditional repair method that is often utilized, and fabric-reinforced cementitious matrix repair, which is a relatively new repair method. The overarching goal of this project was to provide guidance for assessment and potential repair of impact-damaged girders. Prestressed concrete girders were tested to failure in flexure in this research. After a control test to establish a baseline for comparison, five tests were performed involving damaging a girder, repairing it using one of the repair methods, and testing it to failure. These tests showed that both strand splice repairs and fabric-reinforced cementitious matrix repairs can adequately restore the strength of an impact-damaged girder when up to 10% of the prestressing strands are severed. Combined repairs can also be a viable option if more than 10% of the prestressing strands are severed, though as the damage gets more severe, girder replacement becomes a more attractive option. / Master of Science