Doctor of Philosophy (PhD), Wright State University, 2023, Environmental Sciences PhD

Successful crop production relies on soils with balanced physical, chemical and biological properties. Demand for greater crop yields has led to the breakdown of soil properties through detrimental agricultural practices. To combat soil degradation, farmers employ field management practices including cover crop application, crop rotation strategies and organic soil amendment addition. These practices, used independently or in combination, can improve soil stability, increase soil nutrient content and functions of beneficial soil microbiota while increasing crop yield. Despite showing promise as an organic soil amendment, dredged sediments are still not well understood, due in part to the fresh or weathered conditions dredged sediments can be applied. Specifically, there is currently no research combining dredged sediments with cover crops, comparing different dredged sediments conditions in a single study or evaluating dredged sediment condition coupled with cropping strategies. To address these knowledge gaps, my dissertation evaluates changes in soil properties and crop responses when dredged sediments are coupled with these practices. I evaluated changes in dredged sediment property responses and corn production following winter rye cover crop application compared to a fallow season in a field experiment where I found cover crop application increased corn yields compared to a fallow season. These differences were driven by microbial-associated nutrient mineralization. Additionally, I quantified soil property and corn responses to different application ratios of fresh and weathered dredged sediments in a greenhouse experiment and determined applications of dredged sediments calculated based on the nutrient recovery ratio are not sufficient to provide benefits to agricultural soils. However, in 100% applications, weathered dredged sediments were more beneficial to corn growth than agricultural soils, while fresh dredged sediments proved detrimental to corn growth. (open full item for complete abstract)

Committee: Megan Rúa Ph.D. (Committee Chair); Silvia Newell Ph.D. (Committee Member); Louise Stevenson Ph.D. (Committee Member); Katie Hossler Ph.D. (Committee Member); Zheng Xu Ph.D. (Committee Member) Subjects: Environmental Science

Doctor of Philosophy, University of Akron, 2013, Civil Engineering

With the implementation of load and resistance factor design (LRFD) by the U.S. Federal Highway Administration, the design of deep foundations is migrating from Level I (e.g., allowable stress design) codes to Level II codes (e.g., LRFD). Nevertheless, there are still unsolved issues regarding the implementation of load and resistance factor design. For example, there is no generally accepted guidance on the statistical characterization of soil properties. Moreover, the serviceability limit check in LRFD is still deterministic. No uncertainties arising in soil properties, loads and design criteria are taken into account in the implementation of LRFD. In current practice, the load factors and resistances are taken as unity, and deterministic models are applied to evaluate the displacements of geotechnical structures. In order to address the aforementioned issues of LRFD, there is a need for a computational method for conducting reliability analysis and computational tools for statistically characterizing the variability of soil properties. The objectives of this research are: 1) to develop a mathematically sound computational tool for conducting reliability analysis for deep foundations; and 2) to develop the associated computational method that can be used to determine the variability model of a soil property. To achieve consistency between the strength limit check and the serviceability limit check of the LRFD framework, performance-based design methodology is developed for deep foundation design. In the proposed methodology, the design criteria are defined in terms of the displacements of the structure that are induced by external loads. If the displacements are within the specified design criteria, the design is considered satisfactory. Otherwise, failure is said to occur. In order to calculate the probability of failure, Monte Carlo simulation is employed. In Monte Carlo simulation, the variability of the random variables that are involved in the reliability a (open full item for complete abstract)

Committee: Robert Liang Dr. (Advisor); Lan Zhang Dr. (Committee Member); Qindan Huang Dr. (Committee Member); Xiaosheng Gao Dr. (Committee Member); Chien-Chung Chan Dr. (Committee Member) Subjects: Civil Engineering; Statistics