Digital Commons Network^™

Dealuminated Metakaolin In Supplementary Cementitious Material And Alkali-Activated Systems: A Review, Amany G. Micheal Prof., Mostafa Adel Elsebaei Eng., Maria Mavroulidou Prof., Maria Centeno Assoc. Prof., Rabee Shamass Senior Lec., Ottavia Rispolio Mrs.

Architectural Engineering

This paper presents a comprehensive review of dealuminated metakaolin (DK), a hazardous industrial by-product generated by the aluminium sulphate (alum) industry and evaluates its potential as a component in cementitious systems for the partial or full replacement of Portland cement (PC). Positioned within the context of waste valorisation in concrete, the review aims to establish a critical understanding of DK formation, properties, and reactivity, particularly its pozzolanic potential, to assess its suitability for use as a supplementary cementitious material (SCM), or as a precursor in alkali-activated cement (AAC) systems for concrete. A systematic methodology is used to extract and synthesise …

Ev Charging Management In A Real-Time Optimization Framework Considering Operational Constraints, Hilmi Cihan Güldorum, Ayşe Kübra Erenoğlu, İbrahim Şengör, Barry P. Hayes, Ozan Erdinç

Department of Computer Science Publications

The electrification of transportation plays a central role in the decarbonization of energy systems. Although electric vehicles (EVs) are expected to reduce energy related emissions, the increasing demand imposed by large scale EV adoption presents serious challenges for distribution systems (DSs), which were not originally designed to accommodate such loads. This study proposes a mixed integer quadratically constrained programming (MIQCP) framework to optimize the operation of an EV parking lot (EVPL) under DS constraints. The model compares three widely adopted objective functions: minimization of active power loss, charging cost, and uncontrolled charging impact, which is represented by minimizing the total …

Development Of A Machine Learning Framework For An Irrigation Decision Support System, Eric Wilkening, Derek M. Heeren, Yeyin Shi, Laila A. Puntel, Guillermo R. Balboa, Abia Katimbo, Kuan Zhang, Precious Nneka Amori, Bruno Lena

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Currently used irrigation scheduling techniques often require significant human intervention and are time consuming, particularly for variable rate irrigation. This research aimed to develop a conceptual framework that incorporates disparate data sources leveraging both mechanistic and machine learning (ML) approaches. The overarching objective is to utilize the growing availability of data and technology to manage irrigation more precisely, which will minimize negative impacts of irrigation on our water resources. An initial irrigation machine learning model was proposed and tested in this study as a key component of an edge-cloud computing and federated learning decision-making framework. The specific objectives were (1) …

Curved Confinement Directs Anchoring-Mediated Structural Transitions In Highly Chiral Liquid Crystal Shells, Sepideh Norouzi, Jeremy Money, Stiven Villada-Gil, José Martínez-Gonález, Monirosadat Sadati

Faculty Publications

Cholesteric liquid crystals (CLCs) confined in curved geometries exhibit a rich spectrum of defectmediated morphologies governed by the interplay between chirality, curvature, surface anchoring, and confinement. This study systematically investigates structural transitions in highly chiral CLC shells under asymmetric anchoring conditions, focusing on the effects of shell thickness and curvature on pitch axis reorientation and defect formation. Utilizing microfluidic techniques, we generate core–shell droplets with independently tunable anchoring at inner and outer aqueous interfaces. Transitioning from planar–planar to planar-homeotropic boundary conditions via surfactant-mediated modulation induces profound reorganizations in the director field, giving rise to focal conic domains (FCDs), stripe patterns, …

A Study On The Propagation And Exploitation Of Structured Light In Underwater Turbulence, Jaxon P. Wiley

All Dissertations

The development and optimization of optical systems will play a pivotal role in the continued exploration and exploitation of the world’s underwater environments. These systems offer advantages in many sectors, and includes applications in areas such as high-speed communication, advanced sensing and imaging, and environmental characterization and monitoring. Underwater environments offer a plethora of challenges, however, and mitigating these obstacles remains an arduous task. In this work, the inherent advantages of structured light are leveraged to optimize optical system performance through non-ideal underwater conditions. Additionally, fundamental relationships between the generation of specified structured modes and their interactions with complex environments …

Multiple View Neural Regression Of A Facial Shape Model, Xiang Li

All Dissertations

Creating re-topologized 3D facial meshes is a critical step in high-quality facial animation pipelines, yet it remains a labor-intensive and time-consuming task. Traditional approaches typically rely on multiview stereo reconstruction and specialized photometric environments to acquire accurate geometric and reflectance data under controlled conditions. This dissertation presents work toward more efficient capture of production-ready meshes including (1) developmental aspects of VarIS, a custom-designed light sphere capable of capturing high-resolution stereo geometry and reflectance maps—including diffuse, specular, and normal components under programmable illumination; (2) a study of the effects of camera parameters on automatic 2D and 3D landmarking methods, (3) methods …

Advancing Life Cycle Assessment For Environmental Sustainability Of Carbon Fiber-Reinforced Polymer Composites (Cfrps)), Hao Chen

All Dissertations

Carbon fiber-reinforced polymer composites (CFRPs) have emerged as promising materials, particularly for lightweight applications, with the potential to reduce environmental impacts across multiple sectors, including automotive, aerospace, and renewable energy. However, fully realizing their sustainability potential requires a more comprehensive and context-specific understanding of their environmental performance throughout the entire life cycle—from raw material production to end-of-life management.

This dissertation advances life cycle assessment (LCA) practices for CFRPs by addressing key challenges across multiple phases of the CFRP life cycle. First, I conducted a critical review and meta-analysis of carbon fiber manufacturing, revealing substantial variability in reported data on energy …

Effects Of Lossy Compression Data On Machine Learning Models, Max H. Faykus Iii

All Dissertations

Machine learning is a fundamental tool that is incorporated in every field across academia and other industries. Due to the large amount of data needed for training machine learning models, lossy compression plays a crucial role in storing data. Machine learning involves the use of algorithms and models to learn patterns in data. This allows the AI to make decisions without specific programming. On the other hand, compression utilizes encoding and decoding techniques to reduce the size of files. Compression is either lossy or lossless, lossy causes a loss of data while lossless preserves the data. This dissertation will explore …

Studies On The Effects Of Operator Fatigue On Performance, Trust, And Workload Demand In Human-In-The-Loop Ai-Enabled Drone Systems, Snowil Lopes

All Dissertations

Civil infrastructure must be regularly inspected to ensure its safety and reliability. Traditionally, risk engineers performed these inspections manually and in person. However, with the introduction of drones equipped with artificial intelligence (AI), inspections of civil infrastructure can now be conducted remotely. These AI-enabled drones capture and analyze images, helping engineers monitor large and complex structures from a distance. However, working with integrated systems consisting of multiple drones, especially those with varying levels of reliability, can be challenging. Operators must divide their attention, determine how much to trust each drone, and manage mental workload, which can affect their performance. Another …

Impact Of Biodegradation On The Mechanical And Fatigue Properties Of 3d-Printed Pla Bone Scaffolds, Hamed Bakhtiari, Alireza Nouri, Muhammad Aamir, Mohadeseh Najafi, Majid Tolouei-Rad

Research outputs 2022 to 2026

A proper degradation rate of bone scaffolds ensures optimal mechanical support and effective tissue regeneration. The present study examines the degradation effects of simulated body fluids (SBF) on the compressive and fatigue strength of 3D-printed PLA bone scaffolds. Scaffolds with varying surface-to-volume (S/V) ratios and identical porosity (60 %) were immersed in Hanks' solution for a maximum period of 30 days. Static and dynamic compression tests were performed at different immersion times to assess how S/V ratio influences the degradation process. CT images showed that scaffold pore structure remained interconnected after biodegradation, with no significant change in strut thickness or …

The Influence Of Surface Textural Properties And Adsorption Temperature On H2 Adsorption And Storage Performance Of Mil-88b(Fe) Mofs, Tawanda Matamba, Samira Sadeghi, Hussein Rasool Abid, Masoumeh Zargar, Alireza Keshavarz, Stefan Iglauer

Research outputs 2022 to 2026

To advance the establishment of a stable H2 economy we need to solve the issue regarding its storage. The physicochemical properties of Metal Organic Frameworks (MOFs) make them suitable for H2 storage. Therefore, here, we synthesized two Iron-based MOFs (12-MIL-88 B(Fe), 24-MIL-88 B(Fe) at different reaction times (12 h and 24 h), to investigate the relationship between adsorption temperature and pressure with the material's surface textural properties towards H2 storage (at 30 °C, 0 °C, −78.5 °C, and −196.15 °C and from vacuum pressure to 55 bar). Results showed that at 30 °C and 0 °C adsorption temperature, H2 adsorption …

Advancement Of Biocarbon Materials In Sustainable Thermal And Electrochemical Energy Storage With Future Outlooks, Md Shahriar Mohtasim, Barun K. Das

Research outputs 2022 to 2026

Biocarbon exhibits significant potential in thermal and electrochemical energy storage owing to its higher surface area, flexible porosity, and superior thermal stability, facilitating effective energy absorption, storage, and conversion. Additionally, its sustainable and cost-effective nature, derived from renewable biomass, aligns with the growing demand for eco-friendly solutions. There is not enough review work that offers comprehensive details on the unique properties of biocarbon (both animal and plant-derived), synthesis and characterization methods, the root level mechanism of biocarbon's interaction with phase change materials (PCMs) matrix, the generalization of thermal and electrochemical regulation with an emphasis on the benefits to the environment …

Development And Application Of Novel Apparatus For Ocean Spray In Turbulent Atmospheres, Alicyn S. Koldewyn

All Graduate Reports and Creative Projects, Fall 2023 to Present

Ocean spray droplets can have significant effects including reducing surface heating from the sun, degrading air quality, and intensifying tropical cyclones. However, quantifying these effects has been challenging due to the multiscale, chaotic nature of wave breaking and turbulent flow. This research presents the development of a novel apparatus designed to combine bubble column droplet generation with synthetic jet actuators for turbulence generation. The purpose is to demonstrate reliable bubble formation and droplet generation, air turbulence effect on droplet dynamics, and quantitative measurement and analysis of these effects. The primary goals of the apparatus include optical accessibility for high-resolution imaging, …

Effective Transformer Networks For Undersampled Magnetic Resonance Image Reconstruction, Tahsin Rahman

Open Access Theses & Dissertations

The proliferation of data-driven tools for solving problems in every possible domain, coupled with rapid advances in computing technology, has led to an arms race of AI development and application research in industry and academia. One field of research that stands to gain immeasurably from this revolution is medical imaging. It is a critical part of modern diagnostics, and advancements in this area can directly benefit the average person by making healthcare more accessible, accurate, and affordable. Breakthroughs in mainstream image processing and computer vision have long fueled development in medical imaging, and it is now common to see cutting …

Model-Based Systems Engineering For Aerospace Applications: Strategic Requirements Prioritization In Complex Adaptive Systems And Digital Integration, Iqtiar Md Siddique

Open Access Theses & Dissertations

Ineffective systems engineering practices continue to jeopardize aerospace missions, resulting in multi-billion-dollar losses, delays, and fragmented development outcomes. As complexity intensifies and timelines shrink, conventional document-based methods increasingly fail to support early validation, cross-domain traceability, and synchronized tool usage. This research presents an integrated approach that addresses three critical gaps: synchronizing executable and traceable MBSE models across structural, behavioral, and requirements domains; applying scalable requirements prioritization techniques tailored for Complex Adaptive Systems; and establishing automated simulation feedback loops through digital toolchain integration. Central to this strategy is the Digital Trinity, which connects system models, simulations, and lifecycle data through a …

Digital Twin For Real-Time Monitoring And Control Of Conveyor Systems Using Flexsim, Ai And Plc Integration, Jose Francisco Arvizu Astorga

Open Access Theses & Dissertations

Modern manufacturing is making significant advancements by innovating and automating most processes. However, a major challenge remains: systems are constantly evolving and becoming more complex to analyze. Fortunately, a powerful tool can help, Digital Twin (DT) technology. This technology enables the analysis and optimization of processes like never before. A Digital Twin is a real-time virtual model of a physical system that continuously up dates with live data. One of its greatest features is the ability to create infinite scenarios, allowing hundreds of configurations to be tested virtually, risk-free, and without making any real-world changes that could disrupt ongoing operations. …

Decoding Anisotropic Porous Medium: A Synergy Of Lattice Boltzmann Modelling And Operator Learning To Predict Permeability As A Function Of Orientation, Soumya Shouvik Bhattacharjee

Open Access Theses & Dissertations

Understanding the directional properties of porous media is essential for accurately predicting flow behavior, reactive transport, and fluid-solid interactions in systems ranging from geothermal reservoirs to energy storage devices and biological tissues. Directional variations in permeability - reflecting a medium's response to flow at different angular orientations - are particularly important for complex, inherently anisotropic geometries. In this study, we employ a Lattice Boltzmann (LBM) model to calculate directional permeabilities from porous media images subjected to varying flow inlet angles. Three classes of porous media were investigated: (1) synthetic media with circular grains, serving as isotropic baselines; (2) synthetic media …

Thermal Inkjet Bioprinting Of Human Fibroblasts Into Stem Cell Environment Leads To Stem-Like Gene And Protein Expression And Changes In Hippo Pathway Effectors Yap/Taz, Patricia Ablanedo Morales

Open Access Theses & Dissertations

Thermal inkjet bioprinting (TIB) has emerged as a powerful tool with many potential applications, such as organ regeneration, drug testing, and cell differentiation, among others. Despite the forces and stress that cells are subjected to during the printing process, there is little research that investigates in detail the combined effects of the TIB process and the surrounding environment on cells. Furthermore, a cell's biological environment greatly influences its behavior. Therefore, understanding the effects of bioprinting on cells in a particular environment at a genetic level can provide clues regarding changes in cell characteristics. Bioprinting could potentially be used as a …

Application Of Distributed Fiber Optic Sensing (Dfos) For Monitoring Asphalt Pavement Strains Under Accelerated Loading Conditions, Sebastian Morales

Open Access Theses & Dissertations

This thesis presents a study on the application of Distributed Fiber Optic Sensing (DFOS) technology for detecting pavement's strain response with high spatial resolution. Using a Rayleigh-based optical frequency domain reflectometry (OFDR) system, DFOS sensors were calibrated and embedded in full-scale asphalt slabs subjected to accelerated loading using a Model Mobile Load Simulator 3 (MMLS3). Calibration of the DFOS sensors was conducted using a three-point bending flexural test with known load conditions and reference strain gauges to validate theoretical and numerical models. The results demonstrate DFOS's capability to detect pavement response under static and dynamic loading, as well as changes …

Effects Of Environmental Stressors On Human Tissue-On-A-Chip Platforms, Andie Padilla

Open Access Theses & Dissertations

As space exploration begins to extend beyond low earth orbit, it has become increasingly critical to understand the interaction of the extreme environment of space flight with human systems. While it is known that space-travel induces a vast array of complications to cardiac, neural, musculoskeletal, and immune systems, the mechanisms by which these complications occur are poorly understood. Current research to study the effects of microgravity and radiation are limited to ground simulations, which rarely account for the multifactorial stressors experienced during spaceflight, or long duration studies aboard the International Space Station. Similarly, traditional two-dimensional (2D) models lack the ability …

Cellular And Noncellular Influences On Lipid Nanoparticle Tropism In The Liver, Mario Yomir Mata Corral

Open Access Theses & Dissertations

Hepatocellular carcinoma (HCC) is currently ranked as the second leading cause of cancer-related mortality worldwide, causing more than 700,000 deaths a year. The liver is important in blood filtration and metabolism, and for this reason is a prime target for drug delivery, with lipid nanoparticles (LNPs) showing promise as carriers due to their natural hepatic tropism. However, LNP efficacy is decreased in HCC due to the limited understanding of liver physiology in cancerous environments. This project proposes to address this gap by using a tissue-clearing technique known as CLARITY along with a chemically tagged LNP for comprehensive visualization of LNPs …

Elucidation Of Nano-Mechanical Property Evolution Of 3d-Printed Zirconia, Diana Hazel Leyva Marquez

Open Access Theses & Dissertations

This dissertation presents an in-depth look at the mechanical behavior, size changes, and process improvement of ceramic and polymer materials made with additive manufacturing (AM). The work consists of four separate but related studies, each tackling important challenges in fabrication, characterization, and predictive modeling. Chapter 1 examines the nano-mechanical property changes of 3D-printed zirconia made using digital light processing (DLP). By employing nanoindentation and scanning electron microscopy (SEM), the effects of print orientation and sintering on hardness, elastic modulus, and microstructure are revealed. The results indicate that 0°-oriented sintered samples have up to 140% higher hardness compared to preconditioned samples, …

Evaluation Of Salt-Free Electrodialysis Metathesis For High Recovery Inland Desalination Brine Management, Tayia Oddonetto

Open Access Theses & Dissertations

Salt-Free Electrodialysis Metathesis (SF-EDM) is an emerging electro-driven membrane technology designed to minimize brine discharge while enabling selective ion separation and resource recovery. This dissertation presents an evaluation of SF-EDM, spanning bench-scale studies with synthetic brine from the Brackish Groundwater National Desalination Research Facility in Alamogordo, NM, real reverse osmosis (RO) brines from the Kay Bailey Hutchinson Desalination Plant in El Paso, TX, and finally a weeklong pilot demonstration at the Yuma Desalting Plant in Yuma, AZ. Bench-scale experiments established process feasibility and performance trends, while pilot results revealed the value of pre-treatment and system configuration. SF-EDM demonstrated high hydraulic …

A Digital Engineering Framework For Ai-Driven Trade-Off Evaluation And Predictive Component Classification, Alejandro Silva Au

Open Access Theses & Dissertations

This thesis introduces a digital engineering tool designed to help engineers make smarter decisions when choosing actuators. At its core, the system brings together machine learning (specifically XGBoost) and a decision-making method called Multi-Utility Attribute Theory (MUAT). The goal is to support engineers in picking components based on what really matters for their designs, whether that's speed, cost, durability, or any other performance factor. What makes this tool stand out is its user-friendly interface that lets people interact with the system directly. It takes a set of actuator performance data, classifies each one into a relevant use category, and then …

Laser Scan Path Design For Controlled Microstructure In Additive Manufacturing With Integrated Reduced-Order Phase-Field Modeling And Deep Reinforcement Learning, Augustine Twumasi

Open Access Theses & Dissertations

Laser Powder Bed Fusion (L-PBF) is a well-established additive manufacturing technique for fabricating intricate metal components with exceptional precision. A significant challenge in L-PBF is the formation of complex microstructures that influence final material properties. We propose a physics-guided, machine learning-aided approach to optimize scan paths for desired microstructure outcomes, such as equiaxed grains. We employed a phase-field method (PFM) to model the evolution of the crystalline grain structure. To reduce computational costs, we trained a surrogate machine learning model, a 3D U-Net convolutional neural network, using single-track phase-field simulations with varying laser powers to predict crystalline grain orientations based …

Multi-Material Cell Clipping On The Gpu, Melanie Cassidy Walsmith

Open Access Theses & Dissertations

The process of clipping a multi-material cell finds diverse applications across fields such as numerical simulations and computer graphics visualization. Computational fluid dynamics problem often combines multiple materials with different physical properties. The interfaces between those materials may be a part of the solution and evolve in time and can be non-aligned with the mesh. When volume conservation is crucial, interface reconstruction methods are used to approximate such material interfaces. They involve multiple steps, one of which is the process known as clipping. Clipping consists of intersecting and cutting a given cell with a material interface (represented by a line …

Seismic Performance Assessment Of Fatigue-Damaged Cantilever Overhead Sign Structures Using Near-Field Ground Motions, Yeasin Ahmed

Open Access Theses & Dissertations

Cantilever overhead sign support (COSS) structures are one of the most common features of transportation systems, providing navigational information to motorists. The slender geometry, lightweight design, and welded connection at the base make COSS structure susceptible to fatigue cracking under long term cyclic loading from wind-induced galloping, truck-induced gust pressure and so on. COSS structures are traditionally designed considering nominal wind conditions. However, rising incidents of seismic activity in regions like Dallas-Fort Worth related to industrial injection wells in the Permian Basin have created a serious concern regarding the seismic performance of potentially fatigued-damaged COSS structure. The interaction between already …

Modeling And Characterization Of Additively Manufactured Barium Titanate Ceramic, Luz Irene Bugarin

Open Access Theses & Dissertations

This dissertation investigates the influence of geometric design on the mechanical properties of BTO structures fabricated via 3D printing. Using finite element modeling (FEM), we simulate mechanical stress responses across a range of architected designs. Results reveal that specific design strategies can significantly enhance performance by promoting favorable stress distributions. This work highlights the critical role of structural design in optimizing functional ceramics and provides a computational framework for the design of next-generation piezoelectric devices.

Technology-Enabled Foreign Object (Fo) Prevention, Christopher Lee Colaw

Open Access Theses & Dissertations

The aviation industry incurs $14 billion per year in cost due to Foreign Object (FO) damage and the prevention and resolution techniques associated with foreign object debris. While aircraft loss, material scrap and rework contribute to that cost impact, a traditional approach to aircraft design and manufacturing which is based on human performance is also a significant driver. Failure modes and effects analysis of human based aircraft manufacturing reveals that two of the largest risks are associated with unknown potential for FO creation and the inability to recall or objectively provide evidence of FO conformity for cases of inquiry, learning, …

Mechanical Characterization Of M Plane (10-10) And C Plane (0001) Gallium Nitride Semiconductors Via Spherical Nanoindentation, Daniela Alejandra Duarte

Open Access Theses & Dissertations

Gallium nitride's (GaN) mechanical characterization is essential for evaluating its performance and long-term dependability, especially when subjected to mechanical stress and irradiation. The design and optimization of GaN-based devices, which are extensively employed in high-power electronics and optoelectronics, depend on an understanding of these characteristics. Mechanical characterization allows for the evaluation of key characteristics, including stress distributions, representing the spatial variation of internal stresses under applied loading, and pop-in events, which correspond to abrupt displacements associated with the onset of dislocation nucleation and slip. These features are essential for understanding the anisotropic (direction-dependent) response of the material to external forces …