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Articles 1 - 30 of 52
Full-Text Articles in Physical Sciences and Mathematics
Development Of A Computer Model To Simulate Battery Performance For Use In Renewable Energy Simulations, Arjun Sundararajan
Development Of A Computer Model To Simulate Battery Performance For Use In Renewable Energy Simulations, Arjun Sundararajan
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Renewable and clean energy has been the driving force behind the booming storage industry. The need for producing energy from clean and quickly replenishable energy sources has never been as high as it is now. However, renewable energy only supplies a little over a quarter of the world’s electricity needs and much less of the world’s total energy requirements. One reason is the intermittent nature of renewable energy. Inexpensive and convenient storage technologies are required to solve this issue. It is believed that batteries offer the most viable solution to conquer the problem of renewable energy intermittency. To aid the …
Analysis Of Amur Honeysuckle Stem Density As A Function Of Spatial Clustering, Horizontal Distance From Streams, Trails, And Elevation In Riparian Forests, Greene County, Ohio, Greg Michael Grierson Jr.
Analysis Of Amur Honeysuckle Stem Density As A Function Of Spatial Clustering, Horizontal Distance From Streams, Trails, And Elevation In Riparian Forests, Greene County, Ohio, Greg Michael Grierson Jr.
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The non-native invasive shrub Amur honeysuckle, Lonicera maackii (Rupr.) Herder (Gorchov and Trisel, 2003), is one of the most prolific invasive plant species across Midwestern and Northeastern landscapes of the United States. The locations of 2,095 individual Amur honeysuckle stems were geolocated using handheld GPS units in the understory of mixed growth forests at two study sites located approximately 5 km apart in northwestern Greene County, OH. Each site has undergone different levels of anthropogenic disturbance through time. The stem position data was used to measure the spatial clumping distribution and the density of Amur honeysuckle. The spatial clumping of …
Human-Ai Teaming For Dynamic Interpersonal Skill Training, Xavian Alexander Ogletree
Human-Ai Teaming For Dynamic Interpersonal Skill Training, Xavian Alexander Ogletree
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In almost every field, there is a need for strong interpersonal skills. This is especially true in fields such as medicine, psychology, and education. For instance, healthcare providers need to show understanding and compassion for LGBTQ+ and BIPOC (Black, Indigenous, and People of Color), or individuals with unique developmental or mental health needs. Improving interpersonal skills often requires first-person experience with expert evaluation and guidance to achieve proficiency. However, due to limited availability of assessment capabilities, professional standardized patients and instructional experts, students and professionals currently have inadequate opportunities for expert-guided training sessions. Therefore, this research aims to demonstrate leveraging …
The Formation Of Prenucleation Clusters For Calcium Fluoride, Taylor M. Muterspaw
The Formation Of Prenucleation Clusters For Calcium Fluoride, Taylor M. Muterspaw
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There have been limited studies on the analysis of the nucleation and precipitation behind calcium fluoride. Earlier studies support a nucleation mechanism in agreement to classical nucleation theory (CNT) in which a surface nucleation mechanism is required for calcium fluoride. This experiment devised using the ISE method to calcium fluoride to find evidence of a nucleation mechanism like that of calcium carbonate (prenucleation cluster pathway). The potential and pH were recorded versus time and the potential data was converted to nCa2+ data of free calcium ions. It was determined that there was evidence of a similar nucleation mechanism for calcium …
Power Scaling Of Ice Floe Sizes In The Weddell Sea, Southern Ocean, Tristan J. Coffey
Power Scaling Of Ice Floe Sizes In The Weddell Sea, Southern Ocean, Tristan J. Coffey
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The cumulative number versus floe area distribution of seasonal ice floes from four satellite images covering the Summer season (November - February) in the Weddell Sea Antarctica during the summer breakup and melting is fit by two scale-invariant power scaling regimes for the floe areas ranging from 7 to 20 x 108 m2. Scaling exponents, β, for larger floe areas range from -1.5 to -1.7 with an average of -1.6 for floe areas ranging from 6 x 106 to 55 x 107 m2. Scaling exponents, β, for smaller floe areas range from -0.8 to -0.9 with an average of -0.85 …
Effect Of Cloud Cover On Optimum Orientations Of Fixed Solar Panels For Maximum Yearly Energy Collection, Prethew Prasad
Effect Of Cloud Cover On Optimum Orientations Of Fixed Solar Panels For Maximum Yearly Energy Collection, Prethew Prasad
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The amount of cloud cover present in the sky is a significant factor when determining the solar radiation impinging on a solar panel. The optimum tilt required to achieve maximum energy impingement on a surface is also influenced by the amount of cloud cover. This work presents a method for determining the optimum tilt angle for a fixed solar panel when a set amount of cloud cover is present in the sky. Fixed tilt angles that have the most incident solar energy over the course of a year as a function of cloud cover, latitude, and azimuthal angle orientation are …
Sediment Nutrient Dynamics In Fondriest Agricultural Settling Pond, Marie Grace Bezold
Sediment Nutrient Dynamics In Fondriest Agricultural Settling Pond, Marie Grace Bezold
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Excess loading of nitrogen (N) and phosphorus (P) is a serious global problem and has numerous negative impacts on water quality of aquatic ecosystems including eutrophication, harmful algal blooms, and hypoxia. Anthropogenic activities (such as the Haber-Bosch process, burning of fossil fuels, sewage treatment, and manure reuse) have led to excess N loading to aquatic systems. Sediment N dynamics were examined from Oct 2019 – Oct 2020 in an agricultural settling pond connected to a constructed wetland adjacent to an agricultural field. Intact sediment cores were amended with 15N for continuous-flow incubations to measure denitrification and N fixation rates, as …
Content Adaption And Design In Mobile Learning Of Wind Instruments, Neha Priyadarshani
Content Adaption And Design In Mobile Learning Of Wind Instruments, Neha Priyadarshani
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People in today's world seek things that are simple to use. Learning is one of the most crucial aspects of the ongoing digital transformation. Everything is now accessible with a single click on mobile devices, making access to instructional materials faster, easier, and more comfortable. It takes time and effort to build abilities and become an expert in the fields of learning, training, and teaching; and music learning demands a great deal of both practice and mentoring. Initially, music teachers and band directors must maintain a steady attention and devote a significant amount of time to manually teaching materials. This …
Goal Management In Multi-Agent Systems, Venkatsampath Raja Gogineni
Goal Management In Multi-Agent Systems, Venkatsampath Raja Gogineni
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Autonomous agents in a multi-agent system coordinate to achieve their goals. However, in a partially observable world, current multi-agent systems are often less effective in achieving their goals. In much part, this limitation is due to an agent's lack of reasoning about other agents and their mental states. Another factor is the agent's inability to share required knowledge with other agents and the lack of explanations in justifying the reasons behind the goal. This research addresses these problems by presenting a general approach for agent goal management in unexpected situations. In this approach, an agent applies three main concepts: goal …
Utilizing Rotational Energy In Wind Turbine Blades With The Flywheel Mechanism And Predicting The Power Output By Neural Networking, Anamika Mishra
Utilizing Rotational Energy In Wind Turbine Blades With The Flywheel Mechanism And Predicting The Power Output By Neural Networking, Anamika Mishra
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As we expand and innovate for better and safer living, there will always be a need for new energy sources. By replacing fossil fuels, renewable energy is becoming a viable option for primary power generation. That is why researchers are turning their attention to renewable energy sources and ways of making the most of them. WIND ENERGY is a promising renewable and clean energy source harvested from the wind which is plentiful on the planet. We already have the technology to harvest it, but the efficiency and power output are not optimal. In this thesis, to enhance the energy harvesting …
Applying Cognitive Measures In Counterfactual Prediction, Lori A. Mahoney
Applying Cognitive Measures In Counterfactual Prediction, Lori A. Mahoney
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Counterfactual reasoning can be used in task-switching scenarios, such as design and planning tasks, to learn from past behavior, predict future performance, and customize interventions leading to enhanced performance. Previous research has focused on external factors and personality traits; there is a lack of research exploring how the decision-making process relates to both task-switching and counterfactual predictions. The purpose of this dissertation is to describe and explain individual differences in task-switching strategy and cognitive processes using machine learning techniques and linear ballistic accumulator (LBA) models, respectively, and apply those results in counterfactual models to predict behavior. Applying machine learning techniques …
Texture-Driven Image Clustering In Laser Powder Bed Fusion, Alexander H. Groeger
Texture-Driven Image Clustering In Laser Powder Bed Fusion, Alexander H. Groeger
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The additive manufacturing (AM) field is striving to identify anomalies in laser powder bed fusion (LPBF) using multi-sensor in-process monitoring paired with machine learning (ML). In-process monitoring can reveal the presence of anomalies but creating a ML classifier requires labeled data. The present work approaches this problem by printing hundreds of Inconel-718 coupons with different processing parameters to capture a wide range of process monitoring imagery with multiple sensor types. Afterwards, the process monitoring images are encoded into feature vectors and clustered to isolate groups in each sensor modality. Four texture representations were learned by training two convolutional neural network …
Finite Different Time-Domain Simulation Of Terahertz Waves Propagation Through Unmagnetized Plasma, Aditha Srikantha Senarath
Finite Different Time-Domain Simulation Of Terahertz Waves Propagation Through Unmagnetized Plasma, Aditha Srikantha Senarath
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In order to support ongoing terahertz time-domain spectroscopic experiments involving plasma characterization, it is beneficial to simulate the interaction of THz pulses with varying plasma configurations. In this approach, a 1-D Finite Difference Time Domain (FDTD) model was constructed to simulate the interaction of terahertz radiation with a plasma medium. In order to incorporate the plasma properties into the simulation, a Z-transformation was applied. This model is capable of simulating the following properties of plasmas including electron density, collision frequency, and the interaction length of the plasma medium. The simulated model was characterized using terahertz time-domain spectroscopy. The effects of …
Investigation Into The Source Of Contamination Of Surface Waters Flowing Through The Wright State University Woods, Nnadozie Kennedy Okeke
Investigation Into The Source Of Contamination Of Surface Waters Flowing Through The Wright State University Woods, Nnadozie Kennedy Okeke
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This investigative research was carried out with the purpose of determining the source of contaminants present in the surface waters flowing through the Wright State University woods. Five sample sites going from upstream to downstream namely; Inflow to Nutter Center Pond (INNCP), Nutter Center Pond (NCP), Outfall 21 (OTF 21), Burley, and Outfall 15 (OTF 15), were sampled over a time period spanning from June 2020 to January 2021. Samples collected were analyzed for Escherichia coli (E. coli) using 3M™ Petrifilm™ E. coli/Coliform Count (EC) plates, select anions (Phosphate PO43-, Nitrate NO3-, Sulfate SO42-, Fluoride F- and Chloride Cl-) using …
Edge Processing Of Image For Uas Sense And Avoidance, Christopher J. Rave
Edge Processing Of Image For Uas Sense And Avoidance, Christopher J. Rave
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Today there is a large market for Unmanned Aerial Systems. Although most current systems are remotely piloted by operators on the ground, increasingly, many of these systems will use some sort of automatic flight controller to help mitigate new challenges, due to their deployment at growing scale. These challenges include, but are not limited to, shortage of FAA-certified UAS pilots, transmission bandwidth and delay constraints and cyber security threats associated with wireless networking, profitability of operations constrained by energy capacity and efficiency and air dynamics planning, and etc. In order to address these rising challenges, this thesis is a part …
Cytoviva Hyperspectral Imaging For Comparing The Uptake And Transformation Of Agnps And Ag+ In Mitochondria, Kristina Steingass
Cytoviva Hyperspectral Imaging For Comparing The Uptake And Transformation Of Agnps And Ag+ In Mitochondria, Kristina Steingass
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Nanomaterials have attracted significant attention in the last decade, with applications in everyday products. Amongst all known nanomaterials in use, silver is the leading metal, present in 531 different types of products, owing to their unique optical, electrical, antimicrobial, and thermal properties. Though silver nanoparticles (AgNPs) come in contact regularly with the general population, there is little known about their toxicity mechanism due to limited techniques for thorough analysis. CytoViva Hyperspectral Imaging (HSI) shows potential for filling these gaps. In this study, borohydride-capped AgNPs with an approximate diameter of 10 nm were synthesized using the modified Creighton method and characterized …
Analysis Of Classifier Weaknesses Based On Patterns And Corrective Methods, Nicholas Skapura
Analysis Of Classifier Weaknesses Based On Patterns And Corrective Methods, Nicholas Skapura
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Classification is an important branch of machine learning that impacts many areas of modern life. Many classification algorithms (classifiers for short) have been developed. They have highly different levels of sophistication and classification accuracy. Classification problems often have highly different levels of hardness and complexity. Practitioners of classification modeling need better understanding of those algorithms in order to select the optimal algorithm for given classification problems. Researchers of classification need new insight on how given classifiers are weak and how they can be improved by correcting their classification errors. This dissertation introduces new tools and concepts to analyze classifier weakness …
Computer Modeling Of Solar Thermal System With Underground Storage Tank For Space Heating, Mohammad Yousef Mousa Naser
Computer Modeling Of Solar Thermal System With Underground Storage Tank For Space Heating, Mohammad Yousef Mousa Naser
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Space heating is required in almost every dwelling across the country for different periods of time. The thermal energy needed to meet a heating demand can be supplied using different conventional and/or renewable technologies. Solar energy is one example of a renewable resource that can be used for supplying heating needs. It can be utilized either by using photovoltaic panels to generate electricity, that in turn can be used to operate heaters, or by using solar thermal panels. Solar thermal panels obtain higher operating efficiencies than photovoltaic panels, but solar energy for heating purposes suffers from a mismatch between supply …
Structural Analysis And Link Prediction Algorithm Comparison For A Local Scientific Collaboration Network, Denys Guriev
Structural Analysis And Link Prediction Algorithm Comparison For A Local Scientific Collaboration Network, Denys Guriev
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Scientific collaboration between researchers is very common and much influential and ground-breaking research is performed by teams comprised of scientist from different fields and organizations. In this thesis, we analyze and model a small scientific collaboration network limited to two organizations: Wright State University and the Air Force Research Laboratory. Research paper co-authorship is used for establishing the network structure. We analyze several network properties and compare them to past results from analysis of larger and more diverse collaboration networks. We show that the two-organization network we explored exhibits properties similar to those of larger networks. Guided by advances in …
Recommending Collaborations Using Link Prediction, Nikhil Chennupati
Recommending Collaborations Using Link Prediction, Nikhil Chennupati
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Link prediction in the domain of scientific collaborative networks refers to exploring and determining whether a connection between two entities in an academic network may emerge in the future. This study aims to analyze the relevance of academic collaborations and identify the factors that drive co-author relationships in a heterogeneous bibliographic network. Using topological, semantic, and graph representation learning techniques, we measure the authors' similarities w.r.t their structural and publication data to identify the reasons that promote co-authorships. Experimental results show that the proposed approach successfully infer the co-author links by identifying authors with similar research interests. Such a system …
A Rebellion Framework With Learning For Goal-Driven Autonomy, Zahiduddin Mohammad
A Rebellion Framework With Learning For Goal-Driven Autonomy, Zahiduddin Mohammad
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Modeling an autonomous agent that decides for itself what actions to take to achieve its goals is a central objective of artificial intelligence. There are various approaches used to build autonomous agents including neural networks, state machines, utility functions, learning agents, and cognitive architectures. In this thesis, we focus on cognitive architectures. Our approach uses specific knowledge of the world, the goals they pursue, and the actions being performed. Most agents do what they are told (i.e., achieve the goals given to them by a human), but a genuinely autonomous agent does more. It can formulate its own goal or …
Adaptive Two-Stage Edge-Centric Architecture For Deeply-Learned Embedded Real-Time Target Classification In Aerospace Sense-And-Avoidance Applications, Nicholas A. Speranza
Adaptive Two-Stage Edge-Centric Architecture For Deeply-Learned Embedded Real-Time Target Classification In Aerospace Sense-And-Avoidance Applications, Nicholas A. Speranza
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With the growing number of Unmanned Aircraft Systems, current network-centric architectures present limitations in meeting real-time and time-critical requirements. Current methods utilizing centralized off-platform processing have inherent energy inefficiencies, scalability challenges, performance concerns, and cyber vulnerabilities. In this dissertation, an adaptive, two-stage, energy-efficient, edge-centric architecture is proposed to address these limitations. A novel, edge-centric Sense-and-Avoidance architecture framework is presented, and a corresponding prototype is developed using commercial hardware to validate the proposed architecture. Instead of a network-centric approach, processing is distributed at the logical edge of the sensors, and organized as Detection and Classification Subsystems. Classical machine vision algorithms are …
Partial Facial Re-Imaging Using Generative Adversarial Networks, Derek Desentz
Partial Facial Re-Imaging Using Generative Adversarial Networks, Derek Desentz
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Existing facial recognition software relies heavily on using neural networks to extract key facial features to accurately classify known individuals. Some of these key features include the shape, size, and distance between an individual’s eyes, nose, and mouth. When these key features cannot be extracted due to facial coverings, existing applications become inaccurate and unreliable. The accuracy and reliability of these technologies are growing concerns as the facial recognition market continues to grow at an exponential rate. In this thesis, we have developed a web-based application service that is able to take in a partially covered face image and generate …
Diversity And Function Of Algal Biofilms In The Laurentian Great Lakes, Leon R. Katona
Diversity And Function Of Algal Biofilms In The Laurentian Great Lakes, Leon R. Katona
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Attached algae are ubiquitous components of lake benthic habitats wherever sufficient light reaches submerged surfaces. Attached algae interact with heterotrophic bacteria and fungi to form complex biofilms (“periphyton”) that provide a nutritious food source for consumers and influence biogeochemical cycling by regulating redox potential at the sediment-water interface. Despite their ecological importance, there are limited data on the role of periphyton in the Laurentian Great Lakes. I quantified wave exposure and light availability in rocky nearshore habitats in Lake Erie and Lake Huron. Periphyton biomass and productivity in nearshore Lake Erie was very high while algal biomass and productivity in …
Sediment-Water Fluxes Of Phosphorus And Trace Metals In The Maumee River, Northwest Ohio, Emily L. Holliday
Sediment-Water Fluxes Of Phosphorus And Trace Metals In The Maumee River, Northwest Ohio, Emily L. Holliday
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Excess phosphorus (P) and nitrogen (N) in the western basin of Lake Erie drive annual cyanobacteria blooms and associated hypoxia events. The Maumee River inputs ~5% of the water load into the western basin and ~50% of annual P loadings. I quantified seasonal variability of net P and metals fluxes from sediments in the Maumee River at four stations from Defiance, Ohio, to Maumee Bay. Upriver sediments were, on average, a total and filtered P sink throughout the year (−19 ± 7 and −6 ± 3, respectively; all fluxes represent `net flux’ reported in µmol m−2 h−1). At the river …
Benzotriazole And Tolytriazole Analysis In Select Surface Waters Near Wilmington Air Park, Lee A. Raska
Benzotriazole And Tolytriazole Analysis In Select Surface Waters Near Wilmington Air Park, Lee A. Raska
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Previous investigations into the presence of benzotriazole (BTZ) and corresponding analogs done in early 2019 found elevated levels near the Wilmington Air Park in Wilmington, Ohio. The analogs detected were 4-methyl-1H-benzotriazole and 5-methyl-1H-benzotriazole: known together as tolytriazole (TTZ). BTZ and TTZ are emerging environmental contaminants of concern that are often found in aircraft de-icing solutions, anti-icing solutions and detergents. The Wilmington Air Park has two facilities used to pre-treat runoff water before its subsequent release into surrounding streams. Three sites were chosen: Lytle Creek, Indian Run, and Cowan Creek. For the 2019 and 2019/2020 investigative projects, Cowan Creek was designated …
Deep Learning For Compressive Sar Imaging With Train-Test Discrepancy, Morgan R. Mccamey
Deep Learning For Compressive Sar Imaging With Train-Test Discrepancy, Morgan R. Mccamey
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We consider the problem of compressive synthetic aperture radar (SAR) imaging with the goal of reconstructing SAR imagery in the presence of under sampled phase history. While this problem is typically considered in compressive sensing (CS) literature, we consider a variety of deep learning approaches where a deep neural network (DNN) is trained to form SAR imagery from limited data. At the cost of computationally intensive offline training, on-line test-time DNN-SAR has demonstrated orders of magnitude faster reconstruction than standard CS algorithms. A limitation of the DNN approach is that any change to the operating conditions necessitates a costly retraining …
Mathematical Formula Recognition And Automatic Detection And Translation Of Algorithmic Components Into Stochastic Petri Nets In Scientific Documents, Elisavet Elli Kostalia
Mathematical Formula Recognition And Automatic Detection And Translation Of Algorithmic Components Into Stochastic Petri Nets In Scientific Documents, Elisavet Elli Kostalia
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A great percentage of documents in scientific and engineering disciplines include mathematical formulas and/or algorithms. Exploring the mathematical formulas in the technical documents, we focused on the mathematical operations associations, their syntactical correctness, and the association of these components into attributed graphs and Stochastic Petri Nets (SPN). We also introduce a formal language to generate mathematical formulas and evaluate their syntactical correctness. The main contribution of this work focuses on the automatic segmentation of mathematical documents for the parsing and analysis of detected algorithmic components. To achieve this, we present a synergy of methods, such as string parsing according to …
Evaluating The Performance Of Using Speaker Diarization For Speech Separation Of In-Person Role-Play Dialogues, Raveendra Medaramitta
Evaluating The Performance Of Using Speaker Diarization For Speech Separation Of In-Person Role-Play Dialogues, Raveendra Medaramitta
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Development of professional communication skills, such as motivational interviewing, often requires experiential learning through expert instructor-guided role-plays between the trainee and a standard patient/actor. Due to the growing demand for such skills in practices, e.g., for health care providers in the management of mental health challenges, chronic conditions, substance misuse disorders, etc., there is an urgent need to improve the efficacy and scalability of such role-play based experiential learning, which are often bottlenecked by the time-consuming performance assessment process. WSU is developing ReadMI (Real-time Assessment of Dialogue in Motivational Interviewing) to address this challenge, a mobile AI solution aiming to …
Grain-Size And Permeability Of Sediments Within The Hyporheic Zone At The Theis Environmental Monitoring And Modeling Site, Great Miami River And Buried Valley Aquifer, Southwest Ohio, Usa, Timothy Wayne Cornett
Grain-Size And Permeability Of Sediments Within The Hyporheic Zone At The Theis Environmental Monitoring And Modeling Site, Great Miami River And Buried Valley Aquifer, Southwest Ohio, Usa, Timothy Wayne Cornett
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The Theis Environmental Monitoring and Modeling Site is a field research facility, located on the Great Miami River in southwest Ohio, dedicated to the study of hyporheic zone processes. The site is underlain by an aquifer on the order of 21 meters thick, comprised of fluvial deposits. The permeability of the aquifer sediments was quantified both from one large scale hydraulic test (~100 m radial distance) and from grain-size analysis of 119 small-scale core samples (~20 cm length each). The permeability determined from the large-scale hydraulic test is 98.9 Darcies. The test also gave a value for specific yield of …