SHAREOK Repository
Not a member yet
49261 research outputs found
Sort by
Non-Terminal Hydrometeor Fall Speed Effects on Modeled Rain Processes
Get PDFRecent observational studies have shown hydrometeors exhibit non-terminal fall speeds. The goal of this study is to understand how these non-terminal fall speeds affect the collision, coalescence and breakup of raindrops in a Lagrangian cloud model called the Cloud Particle Model (CPM). The observational studies identified three important characteristics of the non-terminal fall speeds; 1) hydrometeor fall speeds have some variance around the expected terminal velocity; 2) hydrometeors have a tendency for large particles (D >1.5 mm) to display sub-terminal fall speeds and small particles (D < 0.5 mm) to display super-terminal fall speeds; 3) hydrometeors have the tendency for large particles to have narrower fall speed distributions than small particles. The CPM is a Lagrangian model that uses the method of limited volume (MLV) to maintain computational feasibility rather than the super droplet method commonly used in Lagrangian models. The MLV samples a fixed number of nearby particles at each time step to calculate collisional interactions rather than combine multiple particles of the same size into super droplets. This makes the CPM more sensitive to random fluctuations than the super droplet method, a desirable feature for studying random variation in fall speeds.
The first sensitivity study, varying the width of the fall speed distribution, showed that there was a critical width of the velocity variations, which if not exceeded, resulted in approached equilibrium distributions that were statistically indistinguishable from the equilibrium distributions approached using the deterministic terminal velocities. The exact value of this critical standard deviation depends strongly on the assumed initial distribution. The second sensitivity test, adding a bias term, showed the bias had a greater impact on the number concentration of large particles in the approached equilibrium distribution than the did random noise term, which means the bias has a big impact on higher moments of the size distribution like radar reflectivity and rain rate. The last sensitivity study, which scaled the variance of large particles, found that the scaling term had a very small effect on any moment of the approached equilibrium distribution, including the number concentration (7% change between scaling terms, and 18% change between bias terms) and rain rate (1.3% change between scaling terms and 5% change between bias terms), which lessens the impact of the term compared to the other two terms
Biomedical Engineering Lab Manual, Volume 2
No full textThe lab manual was written as the second installment that coincides with two lab courses taught at the University of Oklahoma (BME3171, BME3181). These courses are designed to provide Biomedical Engineering students with lab skills and experience in biomedical engineering research and clinical techniques. This manual is used with BME3181 Biomedical Engineering Lab 2 and the following wet lab topics are covered in this lab manual; bioimaging, cell culture, tissue engineering, live-dead and DNA assays.Supported in part by the University of Oklahoma Library's Alternative Textbook GrantVolume 1 of this lab manual is available at: https://shareok.org/handle/11244/33884
The Design and Adaptation of an Experimental Test Setup to Characterize Metal Spring Energized Seals
Get PDFFluid sealing technology is critical to the performance and longevity of equipment in a variety of industries. They prevent harmful fluids from being released into the environment, especially in the case of the oil and gas industry who commonly work with corrosive or toxic materials. Seals prevent harmful debris from entering internal areas of equipment which could damage internal components. It is important to test seals to better understand their level of performance for specific applications. The best method for characterizing seals based on their pressure limitations, fluid compatibility, or durability during dynamic sealing is to inspect them on a test stand. Typically, these tests stands are specific to each application and therefore are costly and time consuming to develop. To help save on project costs, an adaptation to an existing test system can be undertaken in order to test new or existing designs or apply new parameters.
This thesis presents the design approach enabled to adapt an existing test stand to characterize the performance of metal spring energized (MSE) seals under linear reciprocating motion. The test stand was adapted to meet new mechanical and data system requirements which were not capable of being met by the previous iteration.
Throughout the design and construction of the test stand, the following research objectives were achieved. The changes which needed to occur with the previous system were identified. New requirements were created, and the setup was adapted to meet them through the design and implementation of new components with a focus on minimal change to reduce project costs. Lastly, the adaptation to the setup was validated using data collected from initial tests showing proper function and its ability to meet system requirements
UCO Academic Calendar 2023-24
No full textNoAnnual publication of the University of Central Oklahoma's academic calendar with the official semester schedule, break times, and office closures for the designated school year along with a tentative calendar for the following school year. The calendar is prepared by the University Registrar who submits the calendar to the state regents for approval. This version of the calendar is published each summer by University Communications and distributed to campus offices
Methodology comparison using occupancy modeling for six species of rails native to the Texas Gulf Coast
No full textRails are a group of marsh birds which are traditionally difficult to monitor due to low and variable detection estimates. Many species of rail in the United States are experiencing population declines and are species of special conservation concern with added state and federal protection. However, the secrecy of rails creates inefficient and expensive survey conditions that hinder the ability to conserve and monitor populations. Black Rails, for example, are federally listed as Threatened but have very low detection probabilities that require extensive revisits to locations. Determining survey methodology that would maximize the detection probabilities for rails would minimize long-term monitoring costs by reducing the amount of field hours required to revisit survey areas.From February-July of 2022, I utilized four survey methods (autonomous recording units, call-playback, forward-looking-infrared camera equipped drone, and trail cameras) to monitor six species of rail (King Rail [Rallus elegans], Clapper Rail [R. crepitans], Virginia Rail [R. limicola], Sora [Porzana carolina], Eastern Black Rail [Laterallus jamaicensis] and Yellow Rail [Coturnicops noveboracensis]) that winter and/or breed on the Texas Gulf Coast. Vegetation sampling conducted from June-July was used to determine the influence of micro-habitat features on the occupancy of the six target rail species to calculate occupancy estimates for each survey site. Using occupancy modeling I calculated and compared detection estimates generated for each survey method in order to determine the methods which maximized detection probability at a species level. Advanced cluster analyses were trained, developed, and then subsequently used to sort out known vocalizations of each study species to reduce the required time spent sorting acoustic data. Additionally, I conducted a general cost analysis of the three most common survey techniques (call-playback, passive acoustic monitoring, and passive visual monitoring survey methods) to assess the expenses generated for theoretical long-term survey implementation. Average above-ground biomass was a significant factor influencing occupancy for both Black Rail as well as Yellow Rail. Black rail detection probability (p ̂) was highest in the spring/summer using autonomous recording units (p ̂=0.279) and was low in the winter using call-playback (p ̂=0.041). Yellow Rail detection probability was highest with winter call-playback (p ̂=0.043). King/Clapper rail detection probability was influenced strongly by wind speed in the winter and water levels in the spring/summer and standing water levels influenced both winter and spring/summer occupancy. Call-playback had the highest detection probability in winter for King/Clapper Rail (p ̂=0.733) and Virginia Rail (p ̂=0.326) and autonomous recording units were best in the spring/summer for King/Clapper Rail (p ̂=0.706) and Sora (p ̂=0.474). Drone thermal imaging work revealed the possibility of finding rails as small as Black Rail and Yellow Rail, as 27 total rail detections included 12 Black/Yellow Rails, 12 Sora, 1 Virginia, and 2 King/Clappers. Behavioral response to the drone of targeted rails was minimal, with preliminary data showing 81% of birds exhibiting no visual response to the drone although behavioral intensity would increase with increased duration of hovering over individuals. Our Gaussian kernel regression results revealed that wind speed (p=0.04) and percent cloud cover (p=0.01) influenced the number of rails detected on a given survey. By establishing the methods that display the highest detection probabilities for each species, we were able to weigh the monetary cost of the methods against the potential loss/gain of detection probability. Passive acoustic monitoring reduced costs for multiple species including Black Rail, Sora, and King/Clapper Rail, as this method is far cheaper annually than traditional call-playback methods and maintains adequate detection probabilities for these species. Monitoring for Black Rail, Sora, and King/Clapper Rail may be more attainable for agencies with limited funding or resources. The potential of using drone thermal imagery also may further reduce costs while maintaining adequate detection probability for these secretive species. Future research should focus on estimating the detection probability using drone thermal imaging for each of these species, especially the smallest and most difficult to detect such as Black and Yellow Rail
An Exploration of the Influence of Rural Teachers' Curriculum Beliefs and Rural Contexts on Instructional Practices
Get PDFThis holistic single-case study explored how rural teachers’ curriculum beliefs and rural contexts influence their instructional practices. Two teachers from a rural elementary school participated in the study. Data sources include survey, interview transcripts, and field notes. Thematic analysis, constant comparative method, and content analysis were used to analyze data in this study. The themes include adverse aspects of teaching in rural schools, Scholar Academic orientation in curriculum beliefs and instructional practices, and reliance on academic standards. The findings suggest inconsistencies between rural teachers’ curriculum beliefs and instructional practices. In addition, findings indicate that the teacher participants’ views of rural contexts tend to be deficit-oriented and that rural teachers’ instructional practices center on standardized curriculum and state academic standards. This study contributes to research in rural education by highlighting the complexity of curriculum beliefs and instructional practices of rural elementary teachers
Application of in situ CO2 enhanced oil recovery in liquid-rich shale and low-temperature reservoirs
Get PDFThe injection of CO2 presents significant potential for enhancing oil production while minimizing environmental impact by storing CO2 within the oil reservoir. However, the realization of this potential is hindered by factors such as limited inexpensive CO2 sources, lack of infrastructure for CO2 transportation, early gas breakthrough, gravity segregation, viscous fingering, low solubility of CO2 in water, and asphaltene deposition, among others. To address these challenges, alternative methods to deliver CO2 to the target oil reservoir through in-situ generation of CO2 are explored. Specifically, we used aqueous solutions of urea as the CO2 gas generating agent due to its low cost, availability, ease of handling, high solubility in aqueous solutions, tolerance to high salinity conditions and high yield of CO2.
This dissertation comprises of two major topics. The first topic focused on the development of effective in-situ CO2 enhanced oil recovery (ICE) formulations for liquid-rich shale reservoirs while the second topic focused on the application of ICE in low-temperature reservoirs. The first study was conducted in two phases. In the first phase we used dodecane as the oil phase, while crude oil was used in the second phase. We study the synergistic effects of coupling urea with a thermally stable anionic surfactant to further improve oil recovery performance from low-permeability shale formations. We designed the oil recovery experimental procedures to simulate the huff-n-puff technique. Imbibition tests were carried out with oil-saturated Woodford outcrop shale cores for different soaking periods. To assess recovery performance and mechanisms, tests were conducted with four different formulations: brine only, urea in brine, thermostable anionic surfactant in brine, and a blend of urea and surfactant in brine. Surfactant stability at the test temperature was investigated. Furthermore, interfacial tension (IFT) and wettability alteration tests were conducted to understand their effect on total recovery. In addition, the oil recovery experiments were tested at below and above MMP conditions to help decipher the principal recovery mechanism. Results revealed that the selected enhanced oil recovery (EOR) recipes are stable at reservoir conditions and compatible with the oil samples. There was no significant difference in oil recovery when the test pressure was below or above MMP, which suggests that the oil recovery process involved immiscible CO2 mechanism. Furthermore, we observed that both IFT reduction and wettability alteration play critical roles in improving oil recovery. For the tests performed with dodecane-saturated shale cores, combining the surfactant with urea did not have any synergistic benefits. This was attributed to the strong water wetness of the dodecane-saturated shale core samples. Moreover, the urea-only case could recover up to 24% of the original oil in place (OOIP) compared to about 6% for the brine-only case, 21% for the surfactant-only case and 22% for the ternary urea/surfactant/brine mixture. For the tests performed with crude oil-saturated shale cores, aging the shale cores in crude oil changed the wettability of the cores from water-wet to oil-wet. We observed a favorable synergistic effect when we combined the surfactant with urea, leading to higher oil recovery after a 14-day soaking period. The oil recovered in the case of 14-days soaking time for the brine only, binary brine/urea, binary brine/surfactant, and ternary urea/surfactant/brine mixture was 7%, 9%, 5%, and 18% of the OOIP, respectively.
The second topic of this research focused on the application of ICE in low-temperature reservoirs. We used a naturally occurring enzyme (urease) to catalyze the generation of in-situ CO2 under low-temperature reservoir conditions. This study was conducted in two phases. The first phase was conducted with highly purified commercially available urease and deionized (DI) water was used as the aqueous phase, while the second phase was conducted with crude urease extracts from jack beans and artificial sea water (ASW) was used as the aqueous phase. We conducted batch tests to study the kinetics of the urease-catalyzed hydrolysis of urea at different temperatures and concentrations of urea and urease. Adsorption tests were conducted to study the adsorption of the enzyme on porous media. The extent of wettability alteration and the recovery mechanism for different lithologies was determined through core sample imbibition experiments and contact angle measurements. One-dimensional sand pack flowthrough experiments were conducted with different lithologies at 50 °C in the first phase and at 50 and 70 °C in the second phase, to evaluate the tertiary oil recovery potential of low-temperature ICE using the modified formulations. From the experimental results, urease-catalyzed urea hydrolysis is proven to be effective in generating CO2 at the test temperatures with urea conversion rate of up to 95 % at 50 °C for the crude urease extracts. The adsorption tests show that urease was significantly adsorbed on limestone surfaces while the adsorption on sandstone was insignificant. Imbibition tests of this improved formulation with various porous media show distinct wettability reversal trends towards a more water-wet state post-imbibition. For the tests with highly purified urease and DI water, the tertiary oil recovery was up to 31.3 % for sandstone at 50 °C. Meanwhile, for the tests with jack bean extracts and ASW, the tertiary oil recovery was up to 28.0 % for limestone at 50 °C. These results were better than the corresponding high temperature (120 °C) cases. Moreover, the tertiary oil recovery for the limestone and sandstone tests were lower at 70 °C compared to 50 °C. This was attributed to the higher solubility of CO2 in oil at lower temperatures. Overall, the simplicity of the technique used to produce the crude urease extract from jack beans will significantly reduce the cost of enzyme-catalyzed low-temperature ICE, thus overcoming a major barrier and enabling practical applications in the oilfield
Kidney OCT 3D images classification using machine learning
Get PDFThe goal of this research is to make a classification program for 3D images by using a CNN model. The images to classify are kidney images that have 3 different classes: Pelvis, Medulla and Cortex.
To do so, a data preprocessing was needed. The data preprocessing went through two big steps: cropping the 3D images to have smaller image volume and rotating the images to get a data enrichment.
\bigskip
After that data preprocessing, the next step is to build a model that can achieve a better accuracy than 2D models that were used previously
Study On The Use Of Facemask Fibers For Soil Reinforcement
Get PDFThis study investigated the potential application of facemask materials as a sustainable solution for soil reinforcement, with a focus on assessing the influence of facemask fiber attributes on the geotechnical properties of Fiber-Reinforced Soils (FRS). After conducting interface shear tests and tensile strength tests on facemask materials, CUIC triaxial tests were performed on a raw soil and corresponding FRS specimens, incorporating various facemask fiber configurations and geotextile materials for comparison purposes. Results of study indicate that the inclusion of facemask fibers can indeed influence the magnitudes of FRS cohesion and friction angle relative to raw soil values, leading to an increase in the soil shear strength. Specimens with 2.5 x 51 mm-long fibers at a concentration of 1.2 kg/m3 led to the greatest strength increase measured in this study, with a total shear strength increase of 39.7%. This performance was followed by that of 5.1 mm-wide and 51 mm-long fibers at 0.8 kg/m3, resulting in a 31.3% improvement in shear strength. Proper addition of facemask fibers with even spread and random orientation in the soil consistently led to increased shear strength in FRS specimens. This increase was evident not only in the overall toughness of the specimens but also in the effective friction angle, showing an improvement of up to 18%. However, it was observed that effective cohesion remained practically unchanged or, in some cases, decreased by as much as 82%. Additionally, the findings indicate that thinner fibers tend to be more effective in the reinforcement process, and the optimal concentration of facemask fibers is closely associated with their aspect ratio
Transmission electron microscopy of metallic nanoparticles extracted from soils dated to the Younger Dryas; persistence and generation during chemical digestion
No full textImpact events are associated with nanodiamonds. Often found within meteorites, or produced from the interaction with earth’s environment, they can be found across sedimentary layers that record impact events. Acid digestion is typically used to separate nanodiamonds from these sedimentary layers, methods vary from group to group as do their results. As one example, Bement et al. (2014) found nanoparticles consistent with n-diamond in sediments dated to the Younger Drays boundary (YDB) in Bull Creek, OK. This is just one of 22 sites and counting that have identified nanodiamonds within YDB soils globally, suggesting a potential impact layer. Identifying nanodiamonds from heterogeneous geomaterials presents a number of challenges, including possible misidentification via Transmission Electron Microscopy (TEM) due to similarities with copper nanoparticles. For example, Bement et al. (2014) used copper TEM sample support grids, which leads to background signal contamination when using X-ray analysis (EDXA). Additionally, copper and n-diamond have d-spacings that differ by less than 1% making electron diffraction (SAED) an unreliable tool to characterize them (Daulton et al., 2017). In this study, we sought to provide additional evidence on the characterization of nanoparticles found in Bull Creek, OK. Using TEM and wet chemical analysis, we examine the potential for the destruction, production, and perseverance of metallic nanoparticles during the soil digestion process. Through this study we found that copper nanoparticles persisted throughout soil digestion methods and gold nanoparticles were generated during chemical digestion and altered under the electron beam in the TEM. We found that gold grids produced an abundance of nanoparticles when exposed to an acidic dichromate digestion matrix compared to other types of metallic grids (molybdenum and nickel). In comparison, molybdenum grids were destroyed by the matrix and nickel grids appeared unchanged, without nanoparticle deposition. Although we cannot rule out copper or diamond due to the abundance of gold nanoparticles across our sample grids, we have demonstrated the complex interactions between metallic nanoparticles and chemical digestion methods