Digital Commons Network^™

Prediction Of Surfactant Performance From Surfactant Huff-Puff In Carbonate Reservoirs Using A Data-Driven Approach And Desktop Application Development, Y. Yao, Mingzhen Wei, Y. Cui, M. Ali, J. Leng, Y. Qiu

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Surfactants have been widely used to alter the wettability of carbonate rocks from oil-wetness to water-wetness and enhanced oil recovery. One of primary methods implemented in filed applications for enhanced oil recovery is surfactant huff-puff. Currently, a large number of surfactant treatments are conducted in laboratories prior to field applications to optimize the design of surfactant huff-puff, test the performance of surfactants, and minimize failure risk. This process is time-consuming since a treatment could last from several days to more than 300 days. Moreover, a fraction of treatments could not improve oil recovery as reported in the literature. In this …

Descriptive Statistical Analysis Of Experimental Data For Wettability Alteration With Smart Water Flooding In Carbonate Reservoirs, Muhammad Ali Buriro, Mingzhen Wei, Baojun Bai, Ya Yao

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Smart water flooding is a promising eco-friendly method for enhancing oil recovery in carbonate reservoirs. The optimal salinity and ionic composition of the injected water play a critical role in the success of this method. This study advances the field by employing machine learning and data analytics to streamline the determination of these critical parameters, which are traditionally reliant on time-intensive laboratory work. The primary objectives are to utilize data analytics to examine how smart water flooding influences wettability modification, identify key parameter ranges that notably alter the contact angle, and formulate guidelines and screening criteria for successful lab design. …

Lessons Learned From Laboratory Study And Field Application Of Re-Crosslinkable Preformed Particle Gels Rppg For Conformance Control In Mature Oilfields With Conduits/Fractures/Fracture-Like Channels, Baojun Bai, Thomas P. Schuman, David Smith, Tao Song

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

This Paper Surveys the Role of Re-Crosslink able Preformed Particle Gels (RPPG) in Addressing Conformance Challenges within Mature Oilfields. Despite Widespread Preformed Particle Gel (PPG) Application in 15,000+ Wells, their Limitations in Sealing Fractures and Conduits Prevalent in Mature Reservoirs Have Driven the Development of RPPG Formulations. Synthesized in Various Sizes from Micrometer to Millimeter Levels, These Environmentally Friendly RPPGs Are Tailored for Diverse Reservoir Conditions. Findings Showcase the Successful Laboratory-Scale Creation and Upscaling of RPPG Products, Offering Adaptability to Temperatures from 20 to 175°C, Customizable Sizes, Swelling Ratios (5 to 40 Times), and Re-Crosslinking Times Spanning Minutes to Days. …

Pattern Recognition For Wettability Alteration With Surfactants In Carbonate Reservoirs By Using Machine Learning, Y. Yao, Mingzhen Wei, M. Ali, Y. Qiu, Y. Cui, J. Leng

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Surfactants Are Widely Applied Agents to Interact with the Adsorbates on Carbonate Rock Surface, Which Could Alter Wettability from Oil-Wetness to Water-Wetness and Thus Enhance Oil Recovery. Surfactant Huff-Puff is Often Conducted to Achieve Wettability Alteration and Has Been Applied under Various Conditions. Currently, Many Investigations Have Been Reported to Apply Conventional Data Analysis Methods to Analyze Different Sets of Surfactant Huff-Puff Projects. Yet the Application of Machine Learning Algorithms to Reveal the Inherent Patterns is Rarely Reported. in This Study, We Integrate Principal Component Analysis (PCA) with Hierarchical Clustering Algorithm (HCA) to Uncover the Hidden Patterns Embedded in Global …

Radiofrequency Interference Detection Using Lstmand Statistical Analysis Discriminator, Luke Smith

Masters Theses

"Wireless devices are becoming increasingly pervasive across all aspects of society. Examples of such devices include radios, routers, mobile phones, tablets, and more. As the number of radio frequency (RF) devices continues to rise, so does the amount of interference and noise increase. This is why an efficient approach to interference detection is explored. Most research within this area has been done strictly within the frequency domain as viewing a signal within this domain provides many insights into what makes the signal. This has, however, led to the time domain being underutilized for this area of research.

To explore the …

The Graduation Walk: Pareto Optimization Of Degree Paths, Arianna Gail Sy Chaves

Masters Theses

"A student’s academic history, course availability at their institution, and the overall degree of difficulty of the schedule for each semester are all critical factors in their academic success and experience. This thesis proposes an advanced recommendation algorithm that considers these real and conflicting factors that are involved in identifying a prudent degree path - a semester-by-semester course schedule to graduation - for each student. The original contribution of this work is the use of weighted-sum multi-objective constraint programming to minimize an increased number of optimization criteria and identify Pareto-optimal degree paths to be recommended to the student. The conflicting …

Computational Fluid Dynamics Analysis Of Thermal-Hydraulic Phenomena In Nuclear Reactor Systems, Mehedi Hasan Tusar

Masters Theses

"A computational analysis of thermal-hydraulic processes in nuclear reactor systems is performed, leveraging Computational Fluid Dynamics (CFD) to advance the design and ensure the safety of nuclear reactors. Divided into two primary sections, the initial part examines thermal-hydraulic behavior in the Replacement Research Reactor (RRR) operating at 20 megawatts and evaluates potential enhancements for the Missouri University of Science and Technology Reactor (MSTR) to operate at an increased capacity of 2 megawatts from the existing 0.2 megawatts. Detailed simulations reveal insights into flow characteristics, temperature distributions, and pressure drops, highlighting the effective use of realistic and porous media modeling techniques …

Iterative Power Flow Control Architecture For Dc-Ac-Ac Triple Active Bridge Converters: Design, Simulation, And Hardware Testing, Jonathan Henri Saelens

Masters Theses

Driven by widespread electrification and escalating energy demands, efficient and cost-effective converter systems are necessary to maintain and improve our nation's electrical grid. Facilitating this necessity are power electronic converters in applications such as smart grids, renewable energy integration, and electric vehicles. Guided by the demand for improved converter topologies and conversion efficiency, much research has been conducted on varying designs, development, and control implementations. One such topology gaining significant research attention is the triple active bridge (TAB) converter. The TAB is a three-port power converter enabling both bidirectional power flow on each port and galvanic isolation for safety and …

Time Series Anomaly Detection Using Generative Adversarial Networks, Shyam Sundar Saravanan

Masters Theses

"Anomaly detection is widely used in network intrusion detection, autonomous driving, medical diagnosis, credit card frauds, etc. However, several key challenges remain open, such as lack of ground truth labels, presence of complex temporal patterns, and generalizing over different datasets. In this work, we propose TSI-GAN, an unsupervised anomaly detection model for time-series that can learn complex temporal patterns automatically and generalize well, i.e., no need for choosing dataset-specific parameters, making statistical assumptions about underlying data, or changing model architectures. To achieve these goals, we convert each input time-series into a sequence of 2D images using two encoding techniques with …

A Binary Integer Linear Programming Model For Optimizing Underground Stope Layout, Theophilus Mensah

Masters Theses

"Underground mine planning engineers face significant challenges when determining what geometry provides the most profitable and safe stope for extraction. Several techniques and optimization algorithms have been developed in recent years, but most fail to find optimal solutions because they are heuristic or LP-based without efficient geometric constraints. This thesis work proposes a two-dimensional binary linear programming (BILP) model for determining the optimal combination of blocks in a stope that maximizes the economic value of the layout of stopes for a sublevel deposit. The work draws from Queyranne and Wolsey’s (2017 & 2018) formulations of tight constraints for bounded up/down …

The Deep Bsde Method, Daniel Kovach

Masters Theses

"The curse of dimensionality is the non-linear growth in computing time as the dimension of a problem increases. Using the Deep Backwards Stochastic Differential Equation (Deep BSDE) method developed in [HJE18], I approximate the solution at an initial time to a one-dimensional diffusion equation. Although we only approximate a one-dimensional equation, this method extends well to higher dimensions because it overcomes the curse of dimensionality by evaluating the given partial differential equation along "random characteristics''. In addition to the implementation, I also present most of the mathematical theory needed to understand this method"-- Abstract, p. iii

Open-Ended Hollow Coaxial Cable Resonance Sensing Via Permittivity Fluctuations For Applications To Exhaled Breath Health Monitoring, Peter Henry Holtmann

Masters Theses

"We report a pre-diagnostics breath analyzer based on the open-ended hollow coaxial cable resonator (OE-HCCR) to achieve real-time differentiation of healthy and compromised lung function through electromagnetic analysis of exhaled breath matter. A two-phase amplification scheme of electromagnetic signatures metered via the S11 phase curve offers high sensitivity to permittivity fluctuations in exposed airflow. The mathematical model of the breath analyzer is explained, followed by experimental validation of numerical findings from previous work. The collection of breath transient signals is performed through monitoring the reflected power magnitude and phase of the scattering parameter (S11) at the resonance frequency. Material fluctuations …

Fiber Assisted Re-Assembly Preformed Particle Gel For Conformance Control, Zhe Sun

Masters Theses

"In Enhanced Oil Recovery technology today, gel treatments have been implemented as a cost-effective method to improve the oil sweep efficiency in reservoirs by plugging the high permeability zones. This study presents a novel gel composition to be used in conformance control in order to improve oil recovery for mature oilfields.

The product is a fiber-assist re-assembly preformed particle gel which could be generalized to the preformed particle gels (PPG). The product developed in this study could be injected into the reservoir act as a conformance control agent by plugging water thief zones and channels in the beginning process. Due …

Investigation Of The Relationships Between Hydraulic, Physical, And Biological Soil Parameters At A Vineyard In Saint James, Missouri, Lyndsey Bennett

Masters Theses

"Soil is a living, dynamic system that performs vital functions such as crop production, organic matter decomposition, and the flow and transport of water. Given the pressures of food and in some locales water security, climate change, and sustainability, farmers, scientists, and other related specialists and stakeholders must have access to understandable soil health indicators as well as the soil hydraulic function parameters to maximize crop growth while maintaining soil health. Although biological and physical soil parameters are different, we aim to evaluate their relationship at the field scale. Hydraulic conductivity in the vadose zone may be especially important, as …

Monitoring And Control Of Coal Dust Exposure Using Low-Cost Pm Sensors And Computational Fluid Dynamics, Nana Kobina Amoako Amoah

Doctoral Dissertations

"Overexposure to respirable coal mine dust has been linked to causing serious health problems including coal workers pneumoconiosis (CWP) and chronic massive fibrosis. The prevalence of these health problems has been on the increase since the 2000s due to increased exposure levels with roof bolter operators having the highest exposure levels. The currently used PDM3700 is too expensive, heavy and bulky which limits their use only for regulatory monitoring failing to measure miners’ personal exposure levels. Also, since roof bolter operators are more prone to elevated coal dust levels, the canopy air curtain (CAC) was developed to protect then high …

Modeling And Analysis Of Dc-Dc Converters For Power Distribution Networks Design, Junho Joo

Doctoral Dissertations

"Accurate modeling of power distribution networks (PDN) including voltage regulator module (VRM) is critical for high-performance digital systems including low- to high-power applications such as laptops and mobile platforms. As a consolidated end-to-end power source, PDN can be divided into several parts: the VRM to regulate the external voltage source, printed circuit board (PCB) PDN, package PDN, and on-chip PDN. A transient current drawn from the on-die circuitry will produce an instantaneous voltage drop at the bump. The time domain behavior of such a drop and the subsequent recovery is called voltage droop which is strongly associated with the VRM …

Solar Enhanced Oxygen Evolution Reaction With Transition Metal Telluride, Harish Singh, Taishi Higuchi-Roos, Fabrice Roncoroni, David Prendergast, Manashi Nath

Chemistry Faculty Research & Creative Works

The Photo-Enhanced Electrocatalytic Method of Oxygen Evolution Reaction (OER) Shows Promise for Enhancing the Effectiveness of Clear Energy Generation through Water Splitting by using Renewable and Sustainable Source of Energy. However, Despite Benefits of Photo electrocatalytic (PEC) Water Splitting, its Uses Are Constrained by its Low Efficiency as a Result of Charge Carrier Recombination, a Large overpotential, and Sluggish Reaction Kinetics. Here, We Illustrate that Nickel Telluride (NiTe) Synthesized by Hydrothermal Methods Can Function as an Extremely Effective Photo-Coupled Electrochemical Oxygen Evolution Reaction (POER) Catalyst. in This Study, NiTe Was Synthesized by Hydrothermal Method at 145°C within Just an Hour …

Reflections On Linear B, (Part 1): An Egyptian Hieroglyphic Component, Gerald Leonard Cohen

Arts, Languages and Philosophy Faculty Research & Creative Works

No abstract provided.

Project Wars: A Serious Game To Teach Decision Making In Project Execution, Cecil Eng Huang Chua, Veda C. Storey, Linda Wallace

Business and Information Technology Faculty Research & Creative Works

Project execution (i.e., the production, delivery, and deployment of an information system project's outputs) is a difficult concept to teach effectively because of the many real-time decision-making variables facing a project manager. This paper introduces Project Wars, a web-based serious game designed to teach the project execution concepts of deferral of gratification, organizational mindfulness, and discipline in the face of adversity. Project Wars serves as both a platform to instill these concepts and as a basis for discussions on other critical concepts. The latter includes project team management and control, project leadership, the relationship between productivity, slack, and overtime, and …

Shedding Light On Software Engineering-Specific Metaphors And Idioms, Mia Mohammad Imran, Preetha Chatterjee, Kostadin Damevski

Computer Science Faculty Research & Creative Works

Use of figurative language, such as metaphors and idioms, is common in our daily-life communications, and it can also be found in Software Engineering (SE) channels, such as comments on GitHub. Automatically interpreting figurative language is a challenging task, even with modern Large Language Models (LLMs), as it often involves subtle nuances. This is particularly true in the SE domain, where figurative language is frequently used to convey technical concepts, often bearing developer affect (e.g., 'spaghetti code). Surprisingly, there is a lack of studies on how figurative language in SE communications impacts the performance of automatic tools that focus on …

Uncovering The Causes Of Emotions In Software Developer Communication Using Zero-Shot Llms, Mia Mohammad Imran, Preetha Chatterjee, Kostadin Damevski

Computer Science Faculty Research & Creative Works

Understanding and identifying the causes behind developers' emotions (e.g., Frustration caused by 'delays in merging pull requests') can be crucial towards finding solutions to problems and fostering collaboration in open-source communities. Effectively identifying such information in the high volume of communications across the different project channels, such as chats, emails, and issue comments, requires automated recognition of emotions and their causes. To enable this automation, large-scale software engineering-specific datasets that can be used to train accurate machine learning models are required. However, such datasets are expensive to create with the variety and informal nature of software projects' communication channels. In …

Trusted Digital Twin Network For Intelligent Vehicles, Asad Malik, Ayan Roy, Sanjay Madria

Computer Science Faculty Research & Creative Works

Vehicle-to-vehicle (V2V) infrastructure facilitates wireless communication among vehicles within close proximity. This allows sharing of contextual information such as speed, location, direction, traffic, route closures, human behavior mental conditions to improve traffic flow, reduce collisions, and enhance safety on the road. However, the assumption of honest peers along with the over-reliability on the information shared in the network can pose a serious threat to human safety. A digital twin is a concept that enables a system to develop a virtual environment that mimics the real-life scenario for any situation. The availability of powerful computing equipment inside vehicles can be leveraged …

Analyzing Real-Time Insect Detection In Smart Connected Farms, Ashish Gupta, Vishesh Kumar Tanwar, Amit Nath Jha, Sajal K. Das

Computer Science Faculty Research & Creative Works

With a vision of smart connected farms, this research proposes an insect detection framework (InsDet) to identify the most harmful corn crop insect, known as corn rootworm beetle. InsDet employs an object detection model with varying sizes to localize the insects in sticky-trap images.

Achieving Efficient And Privacy-Preserving Reverse Skyline Query Over Single Cloud, Yubo Peng, Xiong Li, Ke Gu, Jinjun Chen, Sajal K. Das, Xiaosong Zhang

Computer Science Faculty Research & Creative Works

Reverse skyline query (RSQ) has been widely used in practice since it can pick out the data of interest to the query vector. To save storage resources and facilitate service provision, data owners usually outsource data to the cloud for RSQ services, which poses huge challenges to data security and privacy protection. Existing privacy-preserving RSQ schemes are either based on a two-cloud model or cannot fully protect privacy. To this end, we propose an efficient privacy-preserving reverse skyline query scheme over a single cloud (ePRSQ). Specifically, we first design a privacy-preserving inner product's sign determination scheme (PIPSD), which can determine …

Enhancing Group-Wise Consistency In 3-Hinge Gyrus Matching Via Anatomical Embedding And Structural Connectivity Optimization, Chao Cao, Xiaowei Yu, Lu Zhang, Tong Chen, Yanjun Lyu, Tianming Liu, Dajiang Zhu

Computer Science Faculty Research & Creative Works

Recently, a novel cortical folding pattern known as the 3-hinge gyrus (3HG) has been identified. 3HGs are defined as the convergence of the gyri coming from three distinct directions on gyral crests. In contrast to cortical regions, 3HGs are defined at a finer scale and they widely exist across different individuals, representing both commonalities and individualities of cortical folding patterns. It is important to note that 3HGs are identified in individual spaces, lacking natural cross-subject correspondences. To address this issue, we have developed a learning-based method to encode anatomical features of 3HGs into a set of embedding vectors that can …

Core-Periphery Multi-Modality Feature Alignment For Zero-Shot Medical Image Analysis, Xiaowei Yu, Lu Zhang, Zihao Wu, Dajiang Zhu

Computer Science Faculty Research & Creative Works

Multi-modality learning, exemplified by the language-image pair pre-trained CLIP model, has demonstrated remarkable performance in enhancing zero-shot capabilities and has gained significant attention recently. However, simply applying language-image pre-trained CLIP to medical image analysis encounters substantial domain shifts, resulting in severe performance degradation due to inherent disparities between natural (non-medical) and medical image characteristics. To address this challenge and uphold or even enhance CLIP's zero-shot capability in medical image analysis, we develop a novel approach, Core-Periphery feature alignment for CLIP (CP-CLIP), to model medical images and corresponding clinical text jointly. To achieve this, we design an auxiliary neural network whose …

Investigating Price Fluctuation Transmission Among Construction Materials, Mohamad Abdul Nabi, Islam H. El-Adaway, Rayan H. Assaad

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Generally, Fluctuation In One Material's Price Can Cause A Series Of Chain Reactions In The Supply Chain System, Known As Price Fluctuation Transmission, As All Materials Are Interconnected And Interrelated. None Of The Previous Studies Have Investigated Price Fluctuation Transmission Among All Construction Materials. This Paper Aims To Fill This Gap In Knowledge. The Authors Collected Producer Price Index (PPI) Data For 16 Construction Materials, Modeled The Relationship Between Each Pair Of Materials Using Vector Autoregression Technique, And Validated The Causality Using Granger Causality Test. Network Analysis Was Performed To Identify The Price Fluctuation Transmission Capacity, Susceptibility, And Intermediatory Capacity …

Rapid Control Prototyping Platform For Grid Connected Electrical Energy Conversion Systems, Shruti Pandey, Noah Damron, Michael Mcintyre

Electrical and Computer Engineering Faculty Research & Creative Works

Electrical Energy Conversion Systems (EECSs) are extensively utilized in contemporary stand-alone systems to supply power to isolated loads. They are also integrated into distributed generation systems, micro grids, and smart grids. In each of these contexts, it is essential to conduct efficient energy management procedures to optimize the electrical energy systems output and ensure the effective and high-quality delivery of electric energy to consumers. To create the energy management system for such a system, careful consideration must be given to the configuration of the power conversion and conditioning system, as well as the specific hardware devices that make up this …

Ai Trustworthy: Ethical Challenges And Strategies, Jian Liu, Iwan Sandjaja, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

This paper explores the pivotal role of trust in the widespread application of Artificial Intelligence (AI) across various domains. We review AI applications in sectors like energy, healthcare, and autonomous vehicles and discuss the crisis of human trust they face. This paper introduces a novel framework that delineates the relationship between AI transparency and user trust, highlighting specific industry applications. Through a systematic review of recent literature, we first delve into factors such as emotional response, acceptance, transparency, accuracy, and interpretability that shape human trust in AI. We then underscore the necessity of ethical AI practices and highlight the importance …

Empowering Urban Traffic Management: Elevated 3d Lidar For Data Collection And Advanced Object Detection Analysis, Nawfal Guefrachi, Hakim Ghazzai, Ahmad Alsharoa

Electrical and Computer Engineering Faculty Research & Creative Works

The 3D object detection capabilities in urban environments have been enormously improved by recent developments in Light Detection and Range (LiDAR) technology. This paper presents a novel framework that transforms the detection and analysis of 3D objects in traffic scenarios by utilizing the power of elevated LiDAR sensors. We are presenting our methodology's remarkable capacity to collect complex 3D point cloud data, which allows us to accurately and in detail capture the dynamics of urban traffic. Due to the limitation in obtaining real-world traffic datasets, we utilize the simulator to generate 3D point cloud for specific scenarios. To support our …