Effects of Wingwall Configurations on the Behavior of Integral Abutment Bridges

This research includes parametric studies performed with the use of three-dimensional nonlinear finite element models in order to investigate the effects of cantilever wingwall configurations on the behavior of integral abutment bridges located on straight alignment and zero skew. The parametric studies include all three types of cantilever wingwalls; inline, flared, and U-shaped wingwalls. Bridges analyzed vary in length from 100 to 1200 feet. Soil-structure and soil-pile interaction are included in the analysis. Loadings include dead load in combination with temperature loads in both rising and falling temperatures. Plasticity in the integral abutment piles is investigated by means of nonlinear plasticity models. Cracking in the abutments and stresses in the reinforcing steel are investigated by means of nonlinear concrete models. The effects of wingwall configurations are assessed in terms of stresses in the integral abutment piles, cracking in the abutment walls, stresses in the reinforcing steel of abutment walls, and axial forces induced in the steel girders. The models developed are analyzed for three types of soil behind the abutments and wingwalls; dense sand, medium dense sand, and loose sand. In addition, the models consider both the case of presence and absence of predrilled holes at the top nine feet of piles. The soil around the piles below the predrilled holes consists of very stiff clay. The results indicate that for the stresses in the piles, the critical load is temperature contraction and the most critical parameter is the use of predrilled holes. However, for both the stresses in the reinforcing steel and the axial forces induced in the girders, the critical load is temperature expansion and the critical parameter is the bridge length. In addition, the results indicate that the use of cantilever wingwalls in integral abutment bridges results in an increase in the magnitude of axial forces in the steel girders during temperature expansion and generation of pile plasticity at shorter bridge lengths compared to bridges built without cantilever wingwalls.

Development and Application of Predictive Models for Survival, Growth, and Death of Enteric Pathogens in Leafy Greens Supply Chain

Leafy greens are essential part of a healthy diet. Because of their health benefits, production and consumption of leafy greens has increased considerably in the U.S. in the last few decades. However, leafy greens are also associated with a large number of foodborne disease outbreaks in the last few years. The overall goal of this dissertation was to use the current knowledge of predictive models and available data to understand the growth, survival, and death of enteric pathogens in leafy greens at pre- and post-harvest levels. Temperature plays a major role in the growth and death of bacteria in foods. A growth-death model was developed for Salmonella and Listeria monocytogenes in leafy greens for varying temperature conditions typically encountered during supply chain. The developed growth-death models were validated using experimental dynamic time-temperature profiles available in the literature. Furthermore, these growth-death models for Salmonella and Listeria monocytogenes and a similar model for E. coli O157:H7 were used to predict the growth of these pathogens in leafy greens during transportation without temperature control. Refrigeration of leafy greens meets the purposes of increasing their shelf-life and mitigating the bacterial growth, but at the same time, storage of foods at lower temperature increases the storage cost. Nonlinear programming was used to optimize the storage temperature of leafy greens during supply chain while minimizing the storage cost and maintaining the desired levels of sensory quality and microbial safety. Most of the outbreaks associated with consumption of leafy greens contaminated with E. coli O157:H7 have occurred during July-November in the U.S. A dynamic system model consisting of subsystems and inputs (soil, irrigation, cattle, wildlife, and rainfall) simulating a farm in a major leafy greens producing area in California was developed. The model was simulated incorporating the events of planting, irrigation, harvesting, ground preparation for the new crop, contamination of soil and plants, and survival of E. coli O157:H7. The predictions of this system model are in agreement with the seasonality of outbreaks. This dissertation utilized the growth, survival, and death models of enteric pathogens in leafy greens during production and supply chain.