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Articles 25321 - 25350 of 196022

Full-Text Articles in Engineering

Carbohydrates Generated Via Hot Water As Catalyst For Co2 Reduction Reaction, Yang Yang, Heng Zhong, Jiong Cheng, Yun Hang Hu, Richard Lee Smith Jr, Fangming Jin Sep 2023

Carbohydrates Generated Via Hot Water As Catalyst For Co2 Reduction Reaction, Yang Yang, Heng Zhong, Jiong Cheng, Yun Hang Hu, Richard Lee Smith Jr, Fangming Jin

Michigan Tech Publications

Combining terrestrial biomass with submarine-type hydrothermal environments for CO2 reduction is a possible approach for realizing new energies while achieving sustainable circulation of carbon. Herein, carbohydrateenabled CO2 reduction based on NaHCO3 conversion to formate revealed that hydrothermal environments facilitated direct hydrogen transfer from carbohydrates (glucose, cellulose) to CO2/NaHCO3 with hot water (250–300 °C, 5–20 MPa) acting as homogeneous catalyst in absence of any conventional catalysts giving CO2/ NaHCO3 reduction efficiencies as high as 76% for cellulose. Time-resolved operando hydrothermal DRIFTS spectra of glycolaldehyde in hot water (250 °C, autogenous pressure) verified that water catalyzed NaHCO3 reduction by converting the -CHO …

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In Situ Monitoring Of The Hydration Of Calcium Silicate Minerals In Cement With A Remote Fiber-Optic Raman Probe, Bohong Zhang, Wenyu Liao, Hongyan Ma, Jie Huang Sep 2023

In Situ Monitoring Of The Hydration Of Calcium Silicate Minerals In Cement With A Remote Fiber-Optic Raman Probe, Bohong Zhang, Wenyu Liao, Hongyan Ma, Jie Huang

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

This study utilized a novel in situ fiber-optic Raman probe to continuously monitor the hydration progress of tricalcium silicate (C3S) and dicalcium silicate (C2S) without the need for sampling, from early hydration stage to later stages, and from fresh to hardened states of paste samples. By virtue of the remarkable ability of this technique in characterizing either dry or wet and crystalline or amorphous samples, the hydration processes of C3S and C2S pastes with different water-to-solid (w/s) ratios could be monitored from the start of the hydration reaction. The main hydration products, …

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Data-Driven Analysis Of Construction Bidding Stage-Related Causes Of Disputes, Muaz O. Ahmed, Islam H. El-Adaway Sep 2023

Data-Driven Analysis Of Construction Bidding Stage-Related Causes Of Disputes, Muaz O. Ahmed, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Construction bidding is a complex process that involves several potential risks and uncertainties for all the stakeholders involved. Such complexities, risks, and uncertainties, if uncontrolled, can lead to the rise of claims, conflicts, and disputes during the course of a project. Even though a substantial amount of knowledge has been acquired about construction disputes and their causation, there is a lack of research that examines the causes of disputes associated with the bidding phase of projects. This study addresses this knowledge gap within the context of infrastructure projects. In investigating and analyzing the causation of disputes related to the bidding …

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Degredation Of Organic Pollutants In Flocculated Liquid Digestate Using Photocatalytic Titanate Nanofibers: Mechanism And Response Surface Optimization, Yiting Xiao, Yang Tian, Yuanhang Zhan, Jun Zhu Sep 2023

Degredation Of Organic Pollutants In Flocculated Liquid Digestate Using Photocatalytic Titanate Nanofibers: Mechanism And Response Surface Optimization, Yiting Xiao, Yang Tian, Yuanhang Zhan, Jun Zhu

Biological and Agricultural Engineering Faculty Publications and Presentations

Titanate nanofibers (TNFs) were synthesized using a hydrothermal method and were employed for the first time in this study to photocatalytically degrade organic pollutants found in flocculated liquid digestate of poultry litter. The photocatalytic performance of TNFs, with a bandgap of 3.16 eV, was tested based on degradation of organic pollutants and removal of color. Five combinations of pollutant concentration and pH were examined (0.2 to 1.3 g·L−1 at pH 4 to 10). Central composite design (CCD) and response surface methodology (RSM) were applied in order to optimize the removal rates of volatile fatty acids (VFA) and chemical oxygen …

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Alkaline Pretreatment And Air Mixing For Improvement Of Methane Production From Anaerobic Co-Digestion Of Poultry Litter With Wheat Straw, Yuanhang Zhan, Jun Zhu, Yiting Xiao, Leland C. Schrader Sep 2023

Alkaline Pretreatment And Air Mixing For Improvement Of Methane Production From Anaerobic Co-Digestion Of Poultry Litter With Wheat Straw, Yuanhang Zhan, Jun Zhu, Yiting Xiao, Leland C. Schrader

Biological and Agricultural Engineering Faculty Publications and Presentations

Alkaline pretreatment (AL) and air mixing (air) both have the potential to improve anaerobic co-digestion (Co-AD) of poultry litter with wheat straw for methane production. In this study, the effects of the combination of AL (pH 12 for 12 h) and air mixing (12 mL·d−1) on the Co-AD process were investigated. The substrate hydrolysis was enhanced by AL, with soluble chemical oxygen demand increased by 4.59 times and volatile fatty acids increased by 5.04 times. The cumulative methane yield in the group of Co-AD by AL integrated with air (Co-(AL + air)), being 287 mL·(g VSadded) …

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Membrane Functionalization Approaches Toward Per- And Polyfluoroalkyl Substances And Selected Metal Ion Separations, Francisco Cecil Léniz-Pizarro, Holly E. Rudel, Nicolas J. Briot, Julie B. Zimmerman, Dibakar Bhattacharyya Sep 2023

Membrane Functionalization Approaches Toward Per- And Polyfluoroalkyl Substances And Selected Metal Ion Separations, Francisco Cecil Léniz-Pizarro, Holly E. Rudel, Nicolas J. Briot, Julie B. Zimmerman, Dibakar Bhattacharyya

UK CARES Faculty Publications

Adsorption and ion exchange technologies are two of the most widely used approaches to separate pollutants from water; however, their intrinsic diffusion limitations continue to be a challenge. Pore functionalized membranes are a promising technology that can help overcome these challenges, but the extents of their competitive benefits and broad applicability have not been systematically evaluated. Herein, three types of adsorptive/ion exchange (IX) polymers containing strong/weak acid, strong base, and iron-chitosan complex groups were synthesized in the pores and partially on the surface of microfiltration (MF) membranes and tested for the removal of organic and inorganic cations and anions from …

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Pattern-Of-Life Modeling With Automatic Dependent Surveillance-Broadcast (Ads-B), Sarah J. Bolton Sep 2023

Pattern-Of-Life Modeling With Automatic Dependent Surveillance-Broadcast (Ads-B), Sarah J. Bolton

Theses and Dissertations

This dissertation and research were sponsored by the Air Force Research Laboratory Layered Sensing Exploitation Branch (AFRL/RYA) to investigate the utility of using the data found within aircraft secondary radar to make predictions about aircraft characteristics and intent. The research focuses on making predictions on aircraft characteristics using only the kinetic data within one type of secondary radar, Automatic Dependent Surveillance-Broadcast (ADS-B), as a surrogate for primary radar. The results from this research provide a means to reduce the reliance on a type of aircraft tracking that is vulnerable to cyber attack and other integrity concerns.

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Atmospheric Propagation Of Qubits: Laboratory Experiments To Field Demonstrations, Keith A. Wyman Sep 2023

Atmospheric Propagation Of Qubits: Laboratory Experiments To Field Demonstrations, Keith A. Wyman

Theses and Dissertations

Free-space quantum networks can enable global-scale quantum communication via satellite-based nodes and quantum ground transceivers. To enable building of robust global quantum networks, it is critical to learn how the state of the qubit is transformed while propagating through the atmosphere. With such an overarching goal, we built a laboratory based atmospheric turbulence simulator (ATS) to characterize the effects of atmospheric turbulence on an entangled pair of photons as a function of statistical quantities such as the Fried parameter or scintillation index for long-distance communication. Specifically, the changes in the statistical properties associated with a quantum source was investigated using …

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Analysis Of Coronal Magnetic Field Parameters During X- And M-Class Solar Flares, Seth H. Garland Sep 2023

Analysis Of Coronal Magnetic Field Parameters During X- And M-Class Solar Flares, Seth H. Garland

Theses and Dissertations

Using Non-Linear Force Free Field (NLFFF) extrapolation, 3D magnetic fields were modeled from the 12-minute cadence Helioseismic and Magnetic Imager (HMI) photospheric vector magnetograms, spanning a time period of one hour before through one hour after the start of 18 X-class flares and 12 M-class flares. Several magnetic field parameters were calculated from the modeled fields directly – as well as from the power spectrum of surface maps generated by summing the fields along the vertical axis – for two different regions: areas with photospheric Bz ≥ 300 G (Active Region – AR) and areas above the photosphere with the …

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Brdf Measurements And Physical Optics Modeling Applied To Anisotropic Satellite Solar Cells, Madilynn E. Compean Sep 2023

Brdf Measurements And Physical Optics Modeling Applied To Anisotropic Satellite Solar Cells, Madilynn E. Compean

Theses and Dissertations

Light curve analysis is often used to discern information about satellites in geosynchronous orbits, and since solar panels comprise relatively large surface areas, their reflected energy can contribute greatly to observed light curves. Data was collected using a space qualified solar cell interrogated by a green HeNe laser. The data validated certain aspects from previous work, but also identified multi-slit behavior, showed that the specular term was a second diffraction pattern, and diagnosed the out-of-plane diffraction curvature as the conical diffraction phenomenon. Two physical-optics-based models were developed to incorporate these new features and better predict solar cell BRDF solely from …

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Quantifying Atmospheric Turbulence Effects On Image Quality Using A Deconvolution Algorithm, Ahmad M. Almalki Sep 2023

Quantifying Atmospheric Turbulence Effects On Image Quality Using A Deconvolution Algorithm, Ahmad M. Almalki

Theses and Dissertations

Imaging through turbulence is affected by several factors including imaging system specifications, imaging system setup and more importantly the atmospheric turbulence as it is uncontrollable. One important parameter which is used to quantify the atmospheric turbulence severity is the atmospheric coherence diameter (��0 ), known as Fried's parameter. This thesis explores ways to characterize the atmospheric turbulence effects on image quality using simulated and laboratory generated turbulence where ��0 is estimated using a maximum a posteriori (MAP) estimator and frequency domain analysis algorithms. Furthermore, image quality metrics such as Peak Signal to Noise Ratio (PSNR), Structural Similarity (SSIM) …

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Evaluating The Chief Of Staff Of The Air Force 2016 Initiative To Revitalize The Squadron: A Thematic Content Analysis Of Appreciative Inquiry Mechanisms, John M. Huntz Sep 2023

Evaluating The Chief Of Staff Of The Air Force 2016 Initiative To Revitalize The Squadron: A Thematic Content Analysis Of Appreciative Inquiry Mechanisms, John M. Huntz

Theses and Dissertations

A thorough thematic analysis and literature review were undertaken to understand better the integration of AI mechanisms within the Revitalize the Squadron initiative. To facilitate the initiative's implementation, the aim is to provide commanders with practical instances, dimensions, findings, and results. Throughout the coding process, instances of AI’s mechanisms were discovered in the literature. The link between PE and HQR boosted the overall vitality within the squadron, where vitality was determined to be the goal. AI, as a whole, was not found in the literature, but the analysis determined that the Revitalize the Squadron initiative was “Appreciative” in nature.

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Advances In Quaternion-Valued Neural Networks, Jeremiah P. Bill Sep 2023

Advances In Quaternion-Valued Neural Networks, Jeremiah P. Bill

Theses and Dissertations

This dissertation investigates the construction, optimization, and application of quaternion neural networks (QNNs) to Department of Defense (DoD) related problem sets. QNNs are a type of neural network wherein the weights, biases, and input values are all represented as quaternion numbers. This work provides a critical evaluation of the myriad different quaternion backpropagation derivations that exist in the literature, testing the performance of each on a range of regression problem sets. The optimization dynamics of QNNs are explored, presenting visualizations of QNN loss surfaces and a novel method for assessing the “smoothness” of these loss surfaces. Finally, this dissertation presents …

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Test Problem Generation And Metaheuristic Selection For The Multidemand Multidimensional Knapsack Problem, Matthew E. Scherer Sep 2023

Test Problem Generation And Metaheuristic Selection For The Multidemand Multidimensional Knapsack Problem, Matthew E. Scherer

Theses and Dissertations

This work focuses on instance generation methods for the multi-demand multidimensional knapsack problem (MDMKP). Specifically, instance space analysis (ISA) is used to characterize the landscape of existing instances and validate the novelty of new instances generated with a novel problem generation method, the primal problem instance generator (PPIG). The instance generator is capable of producing feasible, diverse, and challenging instances by directly controlling the problem features. PPIG contributes to the previous collections of instances and is validated through instance space analysis. The research presents an in-depth empirical evaluation of existing solution procedures for the MDMKP. The portfolio of metaheuristics examined …

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Improving Deep Reinforcement Learning Methodology For Autonomous Defense And Escort Of Military High-Value Assets, Joseph Liles Iv Sep 2023

Improving Deep Reinforcement Learning Methodology For Autonomous Defense And Escort Of Military High-Value Assets, Joseph Liles Iv

Theses and Dissertations

This dissertation explores the application of machine learning to the control of autonomous unmanned combat aerial vehicles (AUCAVs). In particular, this research applies deep reinforcement learning methodologies to a defensive air combat scenario wherein a fleet of AUCAVs protects a military high-value asset (HVA). A collection of air battle management scenarios along with an original simulation environment and a set of designed computational experiments support the approximation of high-quality decision policies by employing Markov decision processes, approximate dynamic programming algorithms, and deep neural networks for value function approximation.

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Network Vulnerability Identification For The Material Routing Problem, Carson G. Long Sep 2023

Network Vulnerability Identification For The Material Routing Problem, Carson G. Long

Theses and Dissertations

This dissertation considers the importance of identifying spatiotemporal vulnerabilities in ground distribution networks and uses operations research methods to formulate models that allow military logistic planners to implement prevention and mitigation measures regarding the routing of personnel, equipment, and supplies in contested Areas of Responsibility (AOR). For optimization models relating to identifying spatiotemporal network vulnerabilities in distribution networks, this work leverages game theory, mixed-integer programming, multi-objective optimization, and metaheuristics to inform mitigation measures for shipment routing. This research has three related components: the first component develops a multi-objective mathematical program to identify spatiotemporal vulnerabilities via myopic heuristic identification, in combination …

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Analysis Of Traffic Crash Data In Kentucky 2018-2022, Paul Ross, Eric Green, Christopher Blackden, Christopher Van Dyke Sep 2023

Analysis Of Traffic Crash Data In Kentucky 2018-2022, Paul Ross, Eric Green, Christopher Blackden, Christopher Van Dyke

Kentucky Transportation Center Research Report

This report documents analysis of traffic crash data in Kentucky. A primary objective of this study was to determine average crash statistics for Kentucky highways. Where used, rates were calculated for various highway types and for counties and cities. Difference criteria were used for exposure. Average and critical numbers, SPFs, and crash rates were calculated for various highway types in rural and urban areas. These metrics rely on crashes identified on highways where Annual Average Daily Traffic (AADT) volumes were available. Data in this report may be used to help identify problem areas. The other primary objective of this study …

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Grasp Solution Approach For The E-Waste Collection Problem, Aldy Gunawan, Dang Viet Anh Nguyen, Pham Kien Minh Nguyen, Pieter Vansteenwegen Sep 2023

Grasp Solution Approach For The E-Waste Collection Problem, Aldy Gunawan, Dang Viet Anh Nguyen, Pham Kien Minh Nguyen, Pieter Vansteenwegen

Research Collection School Of Computing and Information Systems

The digital economy has brought significant advancements in electronic devices, increasing convenience and comfort in people’s lives. However, this progress has also led to a shorter life cycle for these devices due to rapid advancements in hardware and software technology. As a result, e-waste collection and recycling have become vital for protecting the environment and people’s health. From the operations research perspective, the e-waste collection problem can be modeled as the Heterogeneous Vehicle Routing Problem with Multiple Time Windows (HVRP-MTW). This study proposes a metaheuristic based on the Greedy Randomized Adaptive Search Procedure complemented by Path Relinking (GRASP-PR) to solve …

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2023 Safety Belt Usage Survey In Kentucky, Erin Lammers-Staats, Derek S. Young, Kenneth R. Agent, Aidan Elias Sep 2023

2023 Safety Belt Usage Survey In Kentucky, Erin Lammers-Staats, Derek S. Young, Kenneth R. Agent, Aidan Elias

Kentucky Transportation Center Research Report

Data and results of a statewide observational survey used to establish the statewide usage rate for safety belts in Kentucky.

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Evaluation Of Durable Pavement Striping, William Staats, Erin Lammers-Staats Sep 2023

Evaluation Of Durable Pavement Striping, William Staats, Erin Lammers-Staats

Kentucky Transportation Center Research Report

Roadway pavement markings, colloquially referred to as “striping”, can be made of various combinations of paint and reflective beads. In the interest of aligning Kentucky with the state-of-the-art durable pavement marking practices of other states, the Kentucky Transportation Cabinet (KYTC) developed a research study aimed at improving pavement marking specifications and practices. This study reviewed current practices, identified potential improvements, and performed a systematic evaluation in a controlled environment on both asphalt and concrete roads. The state evaluated high-build waterborne paint, extruded and spray thermoplastic, polyurea, and preformed plastic tape, as well as several bead packages including M247, Missouri blend, …

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Inspection Training Course On Bridge Preventive Maintenance Activities, Danny Wells, Sudhir Palle Sep 2023

Inspection Training Course On Bridge Preventive Maintenance Activities, Danny Wells, Sudhir Palle

Kentucky Transportation Center Research Report

Despite over 30 percent of bridges in the United States having exceeded their 50-year design lives, most state departments of transportation (DOTs) lack the funding needed to replace bridges on a large scale. In response, agencies have increasingly turned to bridge preventive maintenance activities to prolong bridge service lives. These activities provide a safe and cost-effective way to slow the rate at which structures deteriorate, mitigate the effects of aging, and improve bridge functional condition. The Kentucky Transportation Cabinet (KYTC) has become increasingly reliant on preventive maintenance to preserve and extend the service lives of its steel and concrete bridges. …

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Computation Of High-Order Sensitivities Of Model Responses To Model Parameters—I: Underlying Motivation And Current Methods, Dan Gabriel Cacuci Sep 2023

Computation Of High-Order Sensitivities Of Model Responses To Model Parameters—I: Underlying Motivation And Current Methods, Dan Gabriel Cacuci

Faculty Publications

The mathematical/computational model of a physical system comprises parameters and independent and dependent variables. Since the physical system is seldom known precisely and since the model’s parameters stem from experimental procedures that are also subject to uncertainties, the results predicted by a computational model are imperfect. Quantifying the reliability and accuracy of results produced by a model (called “model responses”) requires the availability of sensitivities (i.e., functional partial derivatives) of model responses with respect to model parameters. This work reviews the basic motivations for computing high-order sensitivities and illustrates their importance by means of an OECD/NEA reactor physics benchmark, which …

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Computation Of High-Order Sensitivities Of Model Responses To Model Parameters—Ii: Introducing The Second-Order Adjoint Sensitivity Analysis Methodology For Computing Response Sensitivities To Functions/Features Of Parameters, Dan Gabriel Cacuci Sep 2023

Computation Of High-Order Sensitivities Of Model Responses To Model Parameters—Ii: Introducing The Second-Order Adjoint Sensitivity Analysis Methodology For Computing Response Sensitivities To Functions/Features Of Parameters, Dan Gabriel Cacuci

Faculty Publications

This work introduces a new methodology, which generalizes the extant second-order adjoint sensitivity analysis methodology for computing sensitivities of model responses to primary model parameters. This new methodology enables the computation, with unparalleled efficiency, of second-order sensitivities of responses to functions of uncertain model parameters, including uncertain boundaries and internal interfaces, for linear and/or nonlinear models. Such functions of primary model parameters customarily describe characteristic “features” of the system under consideration, including correlations modeling material properties, flow regimes, etc. The number of such “feature” functions is considerably smaller than the total number of primary model parameters. By enabling the computations …

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Qc-Odkla: Quantized And Communication-Censored Online Decentralized Kernel Learning Via Linearized Admm, Ping Xu, Yue Wang, Xiang Chen, Zhi Tian Sep 2023

Qc-Odkla: Quantized And Communication-Censored Online Decentralized Kernel Learning Via Linearized Admm, Ping Xu, Yue Wang, Xiang Chen, Zhi Tian

Electrical and Computer Engineering Faculty Publications

This article focuses on online kernel learning over a decentralized network. Each agent in the network receives online streaming data and collaboratively learns a globally optimal nonlinear prediction function in the reproducing kernel Hilbert space (RKHS). To overcome the curse of dimensionality issue in traditional online kernel learning, we utilize random feature (RF) mapping to convert the nonparametric kernel learning problem into a fixed-length parametric one in the RF space. We then propose a novel learning framework, named online decentralized kernel learning via linearized ADMM (ODKLA), to efficiently solve the online decentralized kernel learning problem. To enhance communication efficiency, we …

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Sensitivity Analysis Of The Ideal Ct Test Using The Distinct Element Method, Shadi Saadeh, Maria El Asmar Sep 2023

Sensitivity Analysis Of The Ideal Ct Test Using The Distinct Element Method, Shadi Saadeh, Maria El Asmar

Mineta Transportation Institute

Cracking is a primary mode of failure for asphalt concrete (AC), resulting in road damage and deterioration, and leading to an increase in road hazards and fatalities. Studying the fracture behavior of AC is an effective way to learn how to best enhance their cracking resistance. To do this, the indirect tensile cracking laboratory test (IDEAL-CT) was developed and used to assess the AC cracking behavior by defining a unique index that allows the ranking of different mixes’ cracking resistance. The sensitivity of the test results to the test parameters is needed to monitor the test’s performance. Several parameters impact …

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Experimental Data Supporting Co2 Enhanced Oil Recovery And Storage Potential In The Bakken Petroleum System (Bps), University Of North Dakota. Energy And Environmental Research Center Sep 2023

Experimental Data Supporting Co2 Enhanced Oil Recovery And Storage Potential In The Bakken Petroleum System (Bps), University Of North Dakota. Energy And Environmental Research Center

EERC Brochures and Fact Sheets

Fact sheet on CO2 enhanced oil recovery (EOR) in the Bakken petroleum system. Highlights experimental data concerning CO2’s role in oil recovery in the region.

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Optimizing Mn-Al Permanent Magnet Performance Through Control Of The Phase Transformation, Ternary Element Addition, And Advanced Processing, Thomas R. Keller Sep 2023

Optimizing Mn-Al Permanent Magnet Performance Through Control Of The Phase Transformation, Ternary Element Addition, And Advanced Processing, Thomas R. Keller

Dartmouth College Ph.D Dissertations

The growing need for electrical power in machines and vehicles brings with it a growing need for critical materials. The current high-performance permanent magnets (PMs) based on rare-earth (RE) elements Nd and Sm cannot escape the problem of raw material cost, geographic scarcity in the earth’s crust, and lack of circular global supply chains. This poses a problem of industrial ecology: can PMs be made from inexpensive, more abundant materials while still meeting sufficient performance criteria? PMs based on the magnetic τ phase of Mn-Al offer a possible alternative to REPMs. However, years of innovation have not yet achieved real-world …

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Guar-Based Injectable Hydrogel For Drug Delivery And In Vitro Bone Cell Growth, Humandra Poudel, Ambar R. Rangumagar, Pooja Singh, Adeolu Oluremi, Nawab Ali, Fumiya Watanabe, Joseph Batta-Mpouma, Jin-Woo Kim, Ahona Ghosh, Anindya Ghosh Sep 2023

Guar-Based Injectable Hydrogel For Drug Delivery And In Vitro Bone Cell Growth, Humandra Poudel, Ambar R. Rangumagar, Pooja Singh, Adeolu Oluremi, Nawab Ali, Fumiya Watanabe, Joseph Batta-Mpouma, Jin-Woo Kim, Ahona Ghosh, Anindya Ghosh

Chemistry & Biochemistry Faculty Publications and Presentations

Injectable hydrogels offer numerous advantages in various areas, which include tissue engineering and drug delivery because of their unique properties such as tunability, excellent carrier properties, and biocompatibility. These hydrogels can be administered with minimal invasiveness. In this study, we synthesized an injectable hydrogel by rehydrating lyophilized mixtures of guar adamantane (Guar-ADI) and poly-β-cyclodextrin (p-βCD) in a solution of phosphate-buffered saline (PBS) maintained at pH 7.4. The hydrogel was formed via host-guest interaction between modified guar (Guar-ADI), obtained by reacting guar gum with 1-adamantyl isocyanate (ADI) and p-βCD. Comprehensive characterization of all synthesized materials, including the hydrogel, was performed using …

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Modeling Yield Strength Of Austenitic Stainless Steel Welds Using Multiple Regression Analysis And Machine Learning, Sukil Park, Myeonghwan Choi, Dongyoon Kim, Cheolhee Kim, Namhyun Kang Sep 2023

Modeling Yield Strength Of Austenitic Stainless Steel Welds Using Multiple Regression Analysis And Machine Learning, Sukil Park, Myeonghwan Choi, Dongyoon Kim, Cheolhee Kim, Namhyun Kang

Mechanical and Materials Engineering Faculty Publications and Presentations

Designing welding filler metals with low cracking susceptibility and high strength is essential in welding low-temperature base metals, such as austenitic stainless steel, which is widely utilized for various applications. A strength model for weld metals using austenitic stainless steel consumables has not yet been developed. In this study, such a model was successfully developed. Two types of models were developed and analyzed: conventional multiple regression and machinelearning- based models. The input variables for these models were the chemical composition and heat input per unit length. Multiple regression analysis utilized five statistically significant input variables at a significance level of …

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Me-Em Enewsbrief, June 2023, Department Of Mechanical Engineering-Engineering Mechanics, Michigan Technological University Sep 2023

Me-Em Enewsbrief, June 2023, Department Of Mechanical Engineering-Engineering Mechanics, Michigan Technological University

Department of Mechanical and Aerospace Engineering eNewsBrief

No abstract provided.

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