Engineering Commons^™

Oxygen Fugacity Of Global Ocean Island Basalts, Lori N. Willhite, Ricardo Arevalo, Philip Piccoli, John C. Lassiter, Devin Rand, Matthew G. Jackson, James M.D. Day, Robert W. Nicklas, Marek Locmelis, Thomas J. Ireland, Igor S. Puchtel

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Mantle plumes contain heterogenous chemical components and sample variable depths of the mantle, enabling glimpses into the compositional structure of Earth's interior. In this study, we evaluated ocean island basalts (OIB) from nine plume locations to provide a global and systematic assessment of the relationship between fO₂ and He-Sr-Nd-Pb-W-Os isotopic compositions. Ocean island basalts from the Pacific (Austral Islands, Hawaii, Mangaia, Samoa, Pitcairn), Atlantic (Azores, Canary Islands, St. Helena), and Indian Oceans (La Réunion) reveal that fO₂ in OIB is heterogeneous both within and among hotspots. Taken together with previous studies, global OIB have elevated and heterogenous fO …

Evaluation Of Novel Preformed Particle Gel System For Conformance Control In Mature Oil Reservoirs, Abdulaziz Almakimi, Ahmed Ben Ali, Ibnelwaleed A. Hussein, Baojun Bai

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

To address challenges associated with excessive water production in mature oil reservoirs, this study introduces a carboxymethyl cellulose (CMC)-based material as a novel preformed particle gel (PPG) designed to plug excessive water pathways and redistribute the subsequent injected water toward unswept zones. Through microwave-assisted grafting copolymerization of CMC with acrylamide (AM), we successfully generated multi-sized dry particles within the range of 250–800 µm. Comprehensive analyses, including Fourier-transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM), have confirmed the chemical composition and morphology of the resulting carboxymethyl cellulose-grafted crosslinked polyacrylamide (CMC/PAMBA). Swelling kinetics and rheology tests were conducted to confirm the …

Mantle Flow And Olivine Fabric Transition In The Myanmar Continental Subduction Zone, Enbo Fan, Yinshuang Ai, Stephen S. Gao, Yumei He, Kelly H. Liu, Mingming Jiang, Guangbing Hou, Shun Yang, Chit Thet Mon, Myo Thant, Kyaing Sein

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

One of the Major Advances in Mineral Physics and Seismology is the Realization that Different Olivine Fabric Types Are Functions of Temperature, Shear Stress, and Water Content in Oceanic Subducting Systems. the Distribution of Different Olivine Fabric Types and Geodynamic Processes in the Mantle Wedge above a Subducting Continental Slab Remain Poorly Understood. Here, based on Splitting Analysis of Shear Waves Recorded by 46 Stations Recently Deployed in Central Myanmar, We Reveal Trench-Perpendicular Fast Orientations between the 80 and 100 Km Slab Contours Sandwiched between Trench-Parallel Fast Orientations from the Mantle Wedge Tip to the Backarc. the Dramatic Change in …

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. …

Electromagnetic Near-Field Scanning With A Spatially Sparse Sampling Strategy Utilizing Kriging-Dmd, Yanming Zhang, Steven Gao, Lijun Jiang

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

This paper proposes a hybrid method for time-resolved electromagnetic near-field scanning, merging model-based (Gaussian processes regression model, a.k.a. Kriging method) and data-driven (dynamic mode decomposition) techniques. Specifically, Latin hypercube sampling enables spatially sparse measurements, followed by dynamic mode decomposition to analyze resulting sparse spatial-temporal data, extracting frequency information and sparse dynamic modes. The Kriging method is then employed for full-state reconstruction. The proposed approach is evaluated using crossed dipole antennas. Results indicate that, even with a spatial subsampling factor of 130, achieving a fully reconstructed field distribution suitable for engineering applications with frequency information extraction is feasible. This hybrid framework …

Improving Insar Accuracy For Slow Deformation And Change Detection With Lidar And Gps, Yusupujiang Aimaiti, Vasit Sagan, Cagri Gul, Jeremy Maurer, Jackson D. Cothren, Carla Klehm, Elizabeth A. Koenig, Nathan Scott

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Interferometric Synthetic Aperture Radar (InSAR) uses two or more SAR images over the same region for mapping ground surface displacements through time. InSAR displacements are relative to a reference point due to the 2π phase ambiguity that from unwrapping, and as a result ground control points (GCPs) are often used to calibrate the displacement model and obtain absolute measurements. Errors in InSAR time-series are typically measured with respect to the reference point, but absolute errors are not currently well constrained. To develop absolute error models for InSAR, we generate Sentinel-1 InSAR time-series for Belleville, Illinois and compare time-series with Global …

Kiloton Class Isru Systems For Lo2/Lch4 Propellant Production On The Mars Surface, Steven R. Oleson, Elizabeth Turnbull, Julie Kleinhenz, Wesley Johnson, Ryan Grotenrath, Nicholas Uguccini, Benjamin Abshire, Lee Mason, Thomas Packard, Anthony Colozza, John Z. Gyekenyesi, James Fittje, Stephen Hoffman, Leslie S. Gertsch

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

As part of the 2023 strategic analysis cycle to explore the trade space, the NASA Mars Architecture Team wanted to explore what it takes to produce in situ on Mars many hundreds of tons of propellants for a large all-chemical transportation system. The conceptual operations and design of the LO₂/LCH₄ in situ resource utilization (ISRU) water acquisition, propellant production and liquification system was assigned to the NASA Compass concurrent engineering team with support from various NASA ISRU, cryogenic fluid management, and surface power experts. The conceptual point design examined one case producing 300 t of LO_{2 …}

Bioprinting With Adipose Stem Cells And Hydrogel Modified With Bioactive Glass, Krishna C.R. Kolan, Apurv Saxena, Bradley A. Bromet, Lesa B. Steen, August T. Bindbeutel, Julie A. Semon, Delbert E. Day, Ming C. Leu

Biological Sciences Faculty Research & Creative Works

Bioprinting research is focused on utilizing growth factors and multiple cell types to create clinically relevant three-dimensional (3D) tissue models using hydrogels. Rheological and biological challenges are two main factors that limit the creation of extrudable bioactive hydrogels. In this study, we investigate incorporation of fast dissolving and bioactive borate glass in different weight to volume percentages (0.075 to 0.6%) to alginate-gelatin (1:1) hydrogel to improve rheological properties and enable bioprinting with bioactive glass. The addition of glass improved the stiffness of the hydrogel. Human adipose-derived mesenchymal stem cells (ASCs) were uniformly mixed in this bioink at 1 x 106 …

Borate-Based Bioactive Glasses Properties: Clinical And Biomedical Applications, Sarah Fakher, David J. Westenberg

Biological Sciences Faculty Research & Creative Works

Borate bioactive glasses (BBGs) constitute the recently produced bioactive glasses (BGs) in the domain of bioactive materials, offering enhanced functionalities over conventional silicate and phosphate BGs. This advancement is primarily characterized by BBGs' rapid yet controllable degradation rates, superior bioactivity, and the ability to swiftly form a hydroxyapatite layer (HAP) upon interaction with physiological fluids. A distinguishing feature of BBGs lies in their customizability; doping with therapeutic metal ions tailors their bioactivity towards specific physiological responses, including promoting angiogenesis, antibacterial activity, and osteogenesis. This versatility of BBGs' applications extends to bone regeneration, wound healing, drug delivery systems, and potentially nerve …

Learning Social Fairness Preferences From Non-Expert Stakeholder Opinions In Kidney Placement, Mukund Telukunta, Sukruth Rao, Gabriella Stickney, Venkata Sriram Siddardh Nadendla, Casey I. Canfield

Computer Science Faculty Research & Creative Works

Modern kidney placement incorporates several intelligent recommendation systems which exhibit social discrimination due to biases inherited from training data. Although initial attempts were made in the literature to study algorithmic fairness in kidney placement, these methods replace true outcomes with surgeons' decisions due to the long delays involved in recording such outcomes reliably. However, the replacement of true outcomes with surgeons' decisions disregards expert stakeholders' biases as well as social opinions of other stakeholders who do not possess medical expertise. This paper alleviates the latter concern and designs a novel fairness feedback survey to evaluate an acceptance rate predictor (ARP) …

Observability-Aware Path Planning For Autonomous Navigation, Raymond Brink Neistat

Open Access Master's Theses

Terrain-Aided Navigation (TAN) is a popular method of localization for GPS-denied vehicles, particularly in the marine domain. There are many ways to perform TAN in a marine setting, such as Bathymetric SLAM (BSLAM) and Bayesian Filtering with the aid of an a priori map. These techniques have been studied extensively, but show an overall lack of rigorous observability analyses. Without nonlinear observability analyses, TAN practitioners do not have an analytical indicator to know which areas of terrain will provide opportunities for the best localization performance. This thesis reviews current developments in the endeavors of nonlinear observability analyses as well as …

Developing Smart Textiles Encapsulated With Single Walled Carbon Nanotubes For Biomedical Applications, Devleena Chowdhury

Open Access Master's Theses

This thesis investigates the creation of core-shell nanofibers for enhanced wound healing applications using a variety of polymer combinations. Chronic wounds are a major worry in the biomedical sector, and researchers are looking at new materials to help the healing process. The PVDF/PVA core-shell structure with single-walled carbon nanotubes (SWCNTs) was chosen due to its balanced mechanical strength, high biocompatibility, and DNA-SWCNT complex stability. PVDF is a preferred shell material due to its biocompatibility and water solubility, making it excellent for wound dressings, implanted scaffolds, and sensors that monitor healing.

The study focuses on improving the electrospinning method to produce …

Rf And Mechanical Design Of A 915 Mhz Srf Cavity For Conduction-Cooled Cryomodules, G. Ciovati, A. Castilla-Loeza, G. Cheng, J. Henry, J. Rathke, J. Vennekate, K. Harding, T. Schultheiss, J. Lewis

Physics Faculty Publications

Conduction-cooled SRF niobium cavities are being developed for use in compact, continuous-wave electron linear accelerators for a variety of industrial applications. A 915 MHz two-cell cavity has been designed to achieve an energy gain of 3.5 MeV. The design of the cell shape aims at minimizing the peak surface magnetic field. Field flatness is achieved by adjusting the length of the outer end half-cells. The higher-order mode analysis shows that absorbers are not required for a moderate beam current of 5 mA. One of the beam tubes has two side-ports for insertion of coaxial fundamental power couplers. The mechanical design …

The Discharge-Induced Polarity-Dependent Propagation Characteristics Of A Strong Shock Wave, Anna Markhotok

Physics Faculty Publications

The specifics of a shock wave propagation down a positive column of a DC discharge in molecular chemically inert gases has been investigated. It was shown that axial gradients caused by the imbalance in the charged particle momentum transfer to the gas molecules can be a reason for the shock velocity dependence on the electric field direction. In pure nitrogen gas, the calculated shock velocity difference of up to 13.5% is in good agreement with the 12% value obtained in the experiment. A returning gas flow organizing in the discharge as a possible mechanism for an extended shock structure and …

Particle Accelerator Spin-Transparent Storage Rings For Beyond State-Of-The-Art Science, R. Suleiman, Y. Derbenev, M. Grau, V. Morozov

Physics Faculty Publications

We will describe spin-transparent storage rings that exhibit spin-coherence times of several hours and store a large number of particles and their use in novel applications. For example, these rings can be used to directly measure the electric dipole moment of the electron, relevant to CP violation and matter-antimatter asymmetry in the universe, and to search for dark energy and ultra-light dark matter*. These rings can also serve as a compelling platform for quantum computing. In this presentation, we will describe how spin-transparent rings can be used in conjunction with ion traps to enhance scalability and increase quantum coherence times …

Deep-Learning Approaches To Predict Remaining Useful Life Of Hard Disks, Rohan Mohapatra

Master's Projects

On a daily basis, data centers process huge volumes of data using inexpensive hard disks. Data stored in these disks serve a range of critical functional needs from financial, and healthcare to aerospace. As such, premature disk failure and consequent loss of data can be catastrophic. To mitigate the risk of failures, cloud storage providers perform condition-based monitoring and replace hard disks before they fail. By estimating the remaining useful life (RUL) of hard disk drives, one can predict the time-to-failure of a particular device and replace it at the right time, ensuring maximum utilization whilst reducing operational costs. We …

Zookeeper Through The Ages: A Comparative Performance Analysis Of Evolutionary Versions, Ashish Khanchandani

Master's Projects

The rise in the need for scalable, fault-tolerant, and high-performance systems is the primary factor driving the developments in distributed computing. However, the proliferation of distributed computing creates significant difficulties. In an internet- scale setting where errors and network delays are frequent, coordinating distributed applications presents difficulties that ZooKeeper attempts to solve. It ensures several crucial characteristics that guarantee reliability and consistency. However, performance and latency play a huge part when it comes to dealing with systems built for handling very high loads. ZooKeeper has very low latency for read-heavy workloads, making it suitable for real-time applications. These factors contribute …

Integrating Chatgpt With A-Frame For User-Driven 3d Modeling, Ivan Hernandez

Master's Projects

ChatGPT is a large language model that is capable of creating conversational text and functional code that can be integrated into various technologies, including computer graphics software. Currently, 3D modeling applications can be relatively difficult for novices to learn and understand due to the overwhelming amount of graphical user interfaces. However, we can remedy this issue by leveraging ChatGPT’s conversational language capabilities. Our project described in this report integrates ChatGPT with A-Frame, an online framework for developing virtual reality experiences, to create an immersive and user-friendly 3D modeling environment where users can create and modify 3D models through natural language …

Noteblocklib: A Library For Physics- And Animation-Driven Virtual Midi Instruments For Use In Video Games, Kevin Rotunni

Master's Projects

To better capture the relationship between the performer of a piece of music and the music itself in a video game context, I have designed NoteBlockLib, a system by which MIDI instructions are generated and processed in real time based on the motion and collision data of in-game objects. Ultimately, the movement of instruments made using this system would be driven by the animations of a character in the game. This system would thus allow the player character to interact with the performer in the game without sacrificing the relationship between the performer’s actions and the resulting music or to …

Gradual Typing For Information Flow Control In Typescript Using Es Lint, Ashish Agarwal

Master's Projects

Current state-of-the-art systems tackle data security threats by incorporating information flow control (IFC) to ensure that a piece of information reaches only its intended recipient. However, most IFC implementations introduce a custom language built on top of a well-known language. Adaptations of such languages are limited due to limited support and updates, along with difficulty in learning new syntaxes. Implementations without a custom language offer incomplete IFC support. We present a comprehensive framework by leveraging Typescript, in conjunction with ESLint and NodeJS, aiming to resolve some of the limitations of IFC and intending to facilitate acceptance by a wide range …

Adversarial Attacks And Defense Mechanisms In Multivariate Time-Series Forecasting For Applications In Smart And Connected Infrastructures, Pooja Krishan

Master's Projects

The advent of deep learning models has revolutionized the industry over the past decade, leading to the widespread proliferation of smart devices and infrastructures. They play a crucial role in safety-critical applications like self-driving cars and medical image analysis, sustainable technologies like power consumption prediction, and in health monitoring tools to replace industrial equipment like hard disk drives, semiconductor chips, and lithium-ion batteries. But these indispensable deep learning models can be easily fooled to give incorrect predictions with utmost conviction, leading to catastrophic failures in applications where safety is of utmost importance, and resulting in the wastage of resources in …

A Two-Stage Machine Learning Approach For Fake News Detection And News Article Categorization, Snegdha Adusumilli

Master's Projects

This project employs machine learning techniques to develop a sequential model for detecting and categorizing fake news, aiming to mitigate its proliferation in today's digital landscape. The model operates in two phases: in the first phase, the classification algorithms like Naïve Bayes, XGBoost and Random Forest are used to distinguish between true and false news stories and in the second phase the capabilities of Naïve Bayes, XGBoost, Random Forest, and the Transformer-based BERT (Bidirectional Encoder Representations from Transformers) model are leveraged to further categorize the news into specific topics.

The methodology encompasses several key steps: data acquisition, preprocessing, feature extraction, …

Echo: A Browser Extension That Runs Experimental Javascript, Prayuj Pillai

Master's Projects

Narcissus is a JavaScript interpreter written in JavaScript. While it is a good engine for experimenting with JavaScript’s design, it does not integrate easily into the browser. This project introduces ‘‘Echo’’, a browser add-on designed to execute Narcissus JavaScript files and scripts within web browsers. The project explores the performance of the Narcissus interpreter against native browser JavaScript engines and benchmarks the results, showcasing the trade-offs in running an experimental engine—the Narcissus interpreter—on the browser versus native JavaScript. Additionally, as a proof of concept, we implement taint tracking, a capability meant to boost security by preventing sensitive data from being …

Mitigating The Risk Of Reentrancy Attack In Smart Contract Development, Eric Ngo

Master's Projects

Smart contracts, while revolutionizing the blockchain with their immutable nature, are prone to attacks such the reentrancy attack. This attack allows malicious adversaries to repeately enter a contract before previous executions are completed. SpartanScript, a custom dialect of Scheme, is a way for developers to write and develop contracts in an experimental blockchain environment like SpartanGold. Compared to cryptocurrencies that use a virtual machine to run on the blockchain, SpartanScript utilizes a simplified interpreter for rapid prototyping. However, SpartanScript does not have a way to detect and warn developers of reentrancy vulnerabilities. Hence, there is a need to implement reliable …

Secured Data Storage Management With Deduplication In Cloud Computing, Ganesh Regoti

Master's Projects

In the cloud era, cloud storage has become a major service and the security of data and user privacy algorithms are becoming of great importance. This way, we make sure that the encrypted data is kept in the cloud storage. But, the challenges follow: First, storing encrypted data may result in ineffective utilization of cloud resources as in the provision of encrypted data, redundancy cannot be provided. Access control to the encrypted data is difficult as the underlying data is hidden and there is no metric with which the decision to share among users can be easily taken. Deduplication is …

Enhancing Environmental Health And Safety: Fine-Tuning Large Language Models For Domain-Specific Applications, Mohammad Adil Ansari

Master's Projects

This study aims to simplify Environmental Health and Safety (EHS) by leveraging the power of Large Language Models (LLMs). In this research, we focus on fine-tuning three LLMs — LLaMA, Mistral, and Falcon — using PEFT techniques such as QLoRA and SFT, to address domain-specific needs such as safety compliance, incident reporting, and knowledge dissemination. Our research methodology involves fine-tuning each LLM model on a custom dataset compiled from various regulatory agencies, supplemented by targeted web scraping and manual collection of questionnaires to capture and enrich the models with the latest regulations and guidelines. This study aims to compare the …

Resume Content Generation Using Llama 2 With Adapters, Navaneeth Sai Nidadavolu

Master's Projects

The primary objective of this project is to optimize the Llama language model to generate customized resumes containing domain-specific job descriptions and maintain the linguistic capabilities of the large language model. Building upon the prior research by Sumed Kale on Job Tailored Resume content generation using GPT-2, where he employed full fine-tuning of the model and demonstrated the capability of LLMs to generate resume content, it is evident that while effective, full fine-tuning has its limitations. Primarily, it is computationally expensive, which can pose constraints, especially for large models. Additionally, during the fine-tuning process, there is a risk of losing …

Domain Expert Bot, Amrutha Dondemadahalli Ramegowda

Master's Projects

The fast growth of artificial intelligence in human-computer interaction has been aided significantly by the introduction of conversational AI systems. This project presents a Domain Expert Bot, a multi-domain conversational bot built with advanced NLP techniques incorporated through Sentence-BERT and MapReduce to allow the bot to analyze and comprehend challenging user queries on various topics. The bot can converse on different subjects ranging from technology topics to healthcare, environment, politics, and casual discussions. It excels in understanding deep language contexts and efficiently processes large datasets, ensuring prompt and accurate responses. Furthermore, it uses advanced ranking algorithms to perform real- time …

Instagram Data Analysis Using Machine Learning, Lakshmi Prasanna Gorrepati

Master's Projects

With enormous amount of social media content, we can draw valuable insights. In this paper, we apply different Machine Learning and Deep Learning techniques on Instagram data to determine the techniques that work well to discover the engagement class of a social media post. Out of all the social media platforms, Instagram is growing rapidly not just in the number of users but also in terms of Advertisement and marketing surpassing YouTube’s advertisement revenue. The end goal of this paper is to propose a technique to predict the engagement class. We applied Random Forest (RF), Stacking Classifier, Extreme Gradient Boost …