This dissertation focuses on examining the relationship between antecedent soil moisture and summer precipitation in the U.S. Great Plains (GP). The influence of Nino sea surface temperatures (SSTs) on summer precipitation has also been investigated to compare their relative contributions to those from local moisture recycling. Both observational data and model simulations have been used to investigate how and why soil moisture can affect subsequent summer precipitation in the GP. Observational analysis indicates that spring (May 1st) soil moisture is significantly correlated with summer precipitation only during periods when Nino SSTs are not strongly correlated with summer precipitation (e.g. 1925-1936). During periods when Nino SSTs are strongly correlated with summer precipitation (e.g. 1940-1970), spring soil moisture is not a good predictor of summer precipitation in the GP. The periods of strong correlation between Nino SSTs and summer precipitation are associated with strong SST persistence. This study suggests that both local soil moisture and remote SST anomalies (deviation from SST climatology) influence summer precipitation in the GP. The soil moisture anomalies are of greatest importance during years when Nino SST persistence is low. Model results have demonstrated that there are significant differences in precipitation response to soil moisture anomalies depending on their sign (+/-), timing and persistence. The influence of dry soil moisture anomalies on subsequent precipitation tends to last longer than wet soil moisture anomalies when initialized on May 1st. Dry soils can influence summer precipitation in the subsequent 2-3 months. However, the precipitation response to wet soil moisture anomalies is faster and greater in magnitude than the response to dry soil moisture anomalies. Persistent soil moisture anomalies that are sustained for an entire month produced larger precipitation changes than soil moisture anomalies only applied on the first day of the month. It appears that the length of soil moisture memory also depends on the sign of soil moisture anomaly. The results of this study may be model-dependent due to the significant inter-model variations in land surface parameterizations. This may restrict the potential for drawing general conclusions.

Sandwich composites with polymer foam core are currently used in load-bearing components in buildings and naval structures due to their high strength to weight and stiffness to weight ratios, excellent thermal insulation, and ease of manufacturing. During their service time, sandwich composites are exposed to various external mechanical and hygro-thermal stimuli. It is known that the constituent properties of the sandwich composites are greatly influenced by the temperature and moisture fields. For example extreme temperature changes and humid environmental conditions can significantly degrade the stiffness and strength of the polymer foam core. This study analyzes the effect of moisture diffusion on the deformation of viscoelastic sandwich composites, which are composed of orthotropic fiber-reinforced laminated skins and viscoelastic polymeric foam core. It is assumed that the elastic and time-dependent (transient) moduli at any particular location in the foam core depend on the moisture concentration at that location. Sequentially coupled analyses of moisture diffusion and deformation are performed to predict overall performance of the studied viscoelastic sandwich systems. A time and moisture dependent constitutive model is used for the polymer foam core. A time-integration algorithm is developed to link this constitutive model to finite element (FE) analyses framework. The overall time-dependent responses of the sandwich composites subject to moisture diffusion are analyzed using 2D plane strain and 3D continuum elements. A 23% increase in the transverse deformation of the viscoelastic sandwich beam is observed due to the moisture degradation. Experimental data and analytical models available in the literature are used to verify the results obtained from the FE code. Parametric studies on the effects of different diffusivity ratios of skin and core materials on stress, strain and displacement fields have been analyzed. At the initial times the effect of moisture on the field variables is found to be most pronounced in the case with the highest diffusivity ratio. Contributions of moisture dependent elastic and the time-dependent moduli to the overall stress, strain and displacement field have been studied. The structural analysis of the sandwich composite under combined moisture diffusion and mechanical loading for two kinds of problems using FE method is performed to complete the study.

The deleterious effect of moisture on the structural integrity of asphalt mixtures has been recognized as one of the main causes of early deterioration of asphalt pavements. This phenomenon, usually referred to as moisture damage, is defined as the progressive loss of structural integrity of the mixture that is primarily caused by the presence of moisture in liquid or vapor state. Moisture damage is associated with the development of different physical, mechanical, and chemical processes occurring within the microstructure of the mixture at different intensities and rates. Although there have been important advancements in identifying and characterizing this phenomenon, there is still a lack of understanding of the damage mechanisms occurring at the microscopic level. This situation has motivated the research work reported in this dissertation. The main objective of this dissertation is to formulate and apply a numerical micromechanical model of moisture-induced damage in asphalt mixtures. The model focuses on coupling the effects of moisture diffusion—one of the three main modes of moisture transport within asphalt mixtures—with the mechanical performance of the microstructure. Specifically, the model aims to account for the effect of moisture diffusion on the degradation of the viscoelastic bulk matrix of the mixture (i.e., cohesive degradation) and on the gradual deterioration of the adhesive bonds between the aggregates and the asphalt matrix (i.e., adhesive degradation). The micromechanical model was applied to study the role of some physical and mechanical properties of the constitutive phases of the mixtures on the susceptibility of the mixture to moisture damage. The results from this analysis suggest that the diffusion coefficients of the asphalt matrix and aggregates, as well as the bond strength of the aggregate-matrix interface, have the most influence on the moisture susceptibility of the mixtures. The micromechanical model was further used to investigate the influence of the void phase of asphalt mixtures on the generation of moisture-related deterioration processes. Two different probabilistic-based approaches were used to accomplish this objective. In the first approach, a volumetric distribution of air voids sizes measured using X-Ray Computed Tomography in a dense-graded asphalt mixture was used to generate probable void structures in a microstructure of an asphalt mixture. In the second approach, a stochastic modeling technique based on random field theory was used to generate probable air voids distributions of the mixture. In this second approach, the influence of the air voids was accounted for by making the physical and mechanical properties of the asphalt matrix dependent on probable voids distributions. Although both approaches take into consideration the characteristics of the air void phase on the mechanical response of the mixtures subjected to moist environments, the former explicitly introduces the air phase within the microstructure while the latter indirectly includes its effects by modifying the material properties of the bulk matrix. The results from these simulations demonstrated that the amount, variability and location of air voids are decisive in determining the moisture-dependent performance of asphalt mixtures. The results from this dissertation provide new information on the kinetics of moisture damage mechanisms in asphalt mixtures. In particular, the results obtained from applying the micromechanical model permitted identification of the relative influence of the characteristics of the constitutive phases of a mixture on its moisture-related mechanical performance. This information can be used as part of design methodologies of asphalt mixtures, and/or as an input in life-cycle analysis models and maintenance programs of road infrastructure.

There are currently two main types of machinery used for harvesting cotton in the United States, cotton pickers and cotton strippers with or without field cleaners. These different machine types package seed cotton with varying amounts of burrs, sticks, and leaves. Harvested cotton is placed in modules for storage prior to ginning. Recent developments in the industry include on-board module builders that package seed cotton as they harvest. This leads to three methods of storage: 1) traditional seed cotton modules, 2) half-modules, and 3) round modules utilized by harvesters with on-board module builders; all of these have different levels of packaging density. Cotton is harvested under widely varying conditions throughout the country and the moisture content of seed cotton at the point of containerization can be an important factor in the final quality of the crop. Seed cotton is being stored for increasing periods of time before being processed by cotton gins. The number of cotton gins in the U.S. has decreased while the production of cotton has increased. All cotton is harvested as it matures and the harvesting rate greatly exceeds the ginning rate. As a consequence of fewer gins, increased harvesting rates and increased quantities of cotton, the storage time of seed cotton prior to ginning has increased. It is hypothesized that the impact of varying densities, varying trash contents, and increased storage times prior to ginning is impacting the quality of the cotton lint and seed. The goal of this research is to quantify the impacts of these factors. The purpose of this research is to evaluate the effects of packaging seed cotton from any of the three different harvesting methods into varying types of storage as a function of differing moisture content and increased storage time. Results are indicated in terms of quality of both the fiber and the seed of ginned samples, as well as how the quality changes affect the value of the processed cotton. Samples of seed cotton are sealed in plastic containers for up to three months at varying levels of moisture, density, and trash content. Temperature and oxygen levels are monitored during storage. Samples are ginned and cottonseed and fiber are analyzed. The results of this research indicate that density does not affect the final quality of the lint and seed harvested. Increased moisture contents have a negative effect on both the quality and the value of the seed cotton, and this effect becomes more pronounced as the length of storage increases.

Thesis (Ph.D.) -- University of Texas at Arlington, 2009.

Thesis (M.S.)--Ohio State University, 1955. / Includes bibliographical references (leaves 41-42). Available online via OhioLINK's ETD Center

Thesis (Ph. D.)--University of Oklahoma, 1999. / Includes bibliographical references (leaves 184-194).

From June to August 2011, Texas experienced the hottest summer ever recorded in the history of the United States, and the state suffered a water shortage that made its vulnerability to drought painfully plain. This disaster sparked new interest in methods of defining drought severity, especially with regard to the variation of soil moisture levels. This thesis assesses the suitability of information from the North American Land Data Assimilation System (NLDAS), an assemblage of land surface models forced with observations data, for quantifying soil moisture levels in Texas. The potential for combining NLDAS data with the Soil Survey Geographic (SSURGO) Database’s available water capacity data is explored. It is discovered that because NLDAS is a hydrological model and SSURGO an agricultural dataset, they employ different definitions of soil moisture storage. Moreover, the temporal variation of soil moisture levels in the SSURGO polygons cannot be inferred from NLDAS data due to the vastly different spatial scales of the two datasets. A relative measure of soil saturation from 0–100% is developed instead and determined to be a more useful indicator of drought than the soil moisture level itself. Calculated solely from NLDAS data, it is used to map the severity of drought in Texas, with the results displayed at the county scale. The temporal variation in soil moisture storage across the state is compared with variations in the gravity anomaly measured by NASA’s Gravity Recovery and Climate Experiment (GRACE) satellites and variations in Texas surface water reservoir levels, both of which are physical measurements of water storage changes. This analysis suggests that the NLDAS data, which is derived from a land surface model, accurately describes subsurface moisture variations. Also, the GRACE gravity anomaly data reveals that during the 2011 drought, the total water storage in Texas was approximately 100 cubic kilometers less than normal. NLDAS data indicates that more than 50% of this deficit was due to losses from the top one meter of the state’s soils. / text

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published_or_final_version / Civil Engineering / Master / Master of Philosophy