Engineering Commons^™

The Plastics Crisis: Responsible Recycling In Civil Engineering And Infrastructure, Jason Howell Stewart

Theses and Dissertations

A global plastics crisis exists with around 400 million metric tons (MMT) of plastics production and 350 MMT of plastics waste generated annually around the globe. Plastics are durable and essentially non-biodegradable, so they accumulate in both terrestrial and marine environments as pollution and within landfills without breaking down over time. Plastics are ubiquitous in 21st-century society and culture, comprising essential elements in most industries including packaging, transportation, electrical/electronics, and building/construction. The role of civil engineering and infrastructure in addressing the plastics crisis was specifically explored. Responsible plastics recycling yields products with improved engineering properties, performance characteristics, marketability, and/or manufacturing …

Physics-Based And Data-Driven Constitutive Modeling Of Unsaturated Soils Under Multi-Physics Loading Conditions, Mohsen Ajdari

Theses and Dissertations

Understanding the behavior of unsaturated soils under multi-physics loading is crucial for addressing several challenges related to emerging geo-energy technologies, climate change, and geohazard mitigation. The main objective of this research is to enhance the state of the art for modeling unsaturated soils under multi-physics loading conditions through physics-based and data-driven approaches. Toward this objective, this dissertation is divided into two distinct yet interrelated parts. In the first part (Chapters 2, 3, and 4), thermodynamic principles are employed to develop new constitutive functions to describe soil suction and stress-dilatancy of unsaturated soils under temperature-dependent conditions. Building upon the insights gained …

Training Machine Learning Algorithms For The Transient Startup Of A Long-Life Modular Microreactor, Ahmad N. Shaheen

Nuclear Engineering ETDs

There is an increasing interest in developing and deploying small modular nuclear reactors (SMRs) and micro modular reactors (MMRs). They could be operated with minimal on-site personnel or remotely with a high degree of autonomy. This can be enabled through the use and application of Artificial Intelligence (AL) and Machine Learning (ML) algorithms and methods. The objective of the present work is to train machine learning algorithms for remote control mimicking the transient startup of the Very-Small, Long-LIfe, Modular (VSLLIM) microreactor. This walk-away safe microreactor design and a fully integrated transient model have been developed at the University of New …

Predicting Vegetation Override Force For Off-Road Autonomy, Marc Nicholas Moore

Theses and Dissertations

Vegetation override is an important aspect of off-road ground vehicle mobility. An autonomous ground vehicle’s (AGV) perception system must distinguish between vegetation that can be easily driven through from vegetation that cannot. Predicting the resistance of vegetation could allow path- planning systems to make this distinction. However, despite its importance, direct measurement of vegetation resistance is rare, as most studies use indirect proprioceptive data, such as inertial measurements, as proxies for override force. Notably, there is a lack of empirical data on the override resistance of small stems (< 2.5 cm) and clusters of vegetation on medium-sized (approx. 1000kg) vehicles. To address this gap, a comprehensive dataset of override measurements was collected for clumps of small vegetation relevant to intermediate-sized AGVs navigating off-road terrain. This dataset includes over 70 recordings using the Robot Operating System (ROS) during controlled driving experiments through small trees, grasses, and bushes. The collected data includes light detection and ranging (LiDAR) scans, imagery, force measurements from integrated load cells, and simultaneous localization and mapping (SLAM) information. A key contribution of this research is the development and calibration of a custom push bar system equipped with load cells to directly measure override forces. These measurements are compared to empirical models previously developed by the U.S. Army Corps of Engineers for larger single-stem vegetation. A preprocessing pipeline was developed to automatically extract and label LiDAR and camera data according to these force measurements. This self-labeled dataset was then used to train machine learning models that predict override resistance of vegetation from LiDAR and camera scans alone. This research characterizes the relationship between override forces and the observable features of vegetation as measured by LiDAR and camera sensors. Deep learning models were developed and trained to predict override forces based on different input modalities and features derived from point clouds and images. The performance of these models was compared across various input features to investigate how deep learning can create a generalizable and accurate force prediction system.

Utilizing Pupper, A Social Robot Dog, To Increase Happiness And Improve Mood In Pediatric Patients Of A Cardiac Step-Down Unit, Angela Feng Wu

Master's Projects and Capstones

Objective The usage of social robots in pediatrics is an emerging field of study. Preliminary research shows that they are effective at improving the psychosocial well-being of pediatric patients. This quality improvement project focuses on Pupper, a newly developed quadruped social robot dog, and its ability in improving mood and happiness in pediatric patients of a cardiac step-down unit. Aim The aim of this project is to increase average mood scores of pediatric cardiac patients aged 3-25 years by 50% from their baseline of 3.75 to 5.63 on a six-point scale within a one-month time frame. Methods Before intervention and …

A Case Against Exclusive Reliance On Volumetric Mixture Characterization For Future Asphalt Pavements And The Advancement Of A Viable Alternative, Jonathan Randy Easterling

Theses and Dissertations

Volumetric properties have been the cornerstone of asphalt mixture design and control dating back to the early 20th century. However, social and economic drivers have caused the asphalt industry to make changes in materials and processes used to produce mixtures that have stretched the limits of volumetric centric methodologies. The primary objectives of this dissertation were to present an extensive case on how volumetrics is limited in their ability to characterize asphalt mixtures and to advance the body of knowledge of a viable alternative. State agency specifications were examined and found that Departments of Transportation (DOTs) were using asphalt volumetric …

Lignin Cationization For The Removal Of Phosphates And Nitrates From Effluents Of Wastewater Treatment Plants, Fannyuy V. Kewir

LSU Master's Theses

The removal of phosphates and nitrates from wastewater treatment plant (WWTP) effluents is important for preventing pollution of receiving waters. In this study, we chemically modified alkaline lignin (aLN) with quaternary ammonium groups to obtain biodegradable cationic lignin (cLN). We characterized the cLN and tested its efficacy for removing phosphates and nitrates in a lab setting and on field-collected WWTP samples. Adsorption isotherm and kinetic studies were performed in aqueous media, and the effects of several variables (contact time, pH, initial concentration, and adsorbent dose) were investigated. The Langmuir isotherm described phosphate and nitrate adsorption well, with R2 values of …

Enhanced Intellectual Property Protection Mechanisms Towards Collaborative Data Sharing In Metal-Based Additive Manufacturing, Durant Hayes Fullington

Theses and Dissertations

This dissertation aims to develop effective methodologies towards enhanced intellectual property protections for data sharing frameworks in metal-based additive manufacturing (AM). Currently, many small-to-medium sized manufacturers face data availability challenges due to the prohibitive high cost to collect, process, and analyze large amounts of process-related data for AM. Because these manufactures rely heavily on small-scale data, it can be difficult for them to effectively train complex machine learning (ML) algorithms, which are commonly used for AM process monitoring. One popular solution is to develop collaborative data sharing frameworks, where multiple independent AM users can share their data to increase the …

Assessing Plate Load Testing And Modulus Of Subgrade Reaction Determination For Pavements, Jami Lynn Rushing

Theses and Dissertations

This thesis aims to: 1) determine the effect of plate size on the modulus of subgrade reaction (k), 2) investigate the differences between the ASTM D1196-21 and CRD-C 655-95 plate load test methods, and 3) develop new effective k curves. 150 plate load tests were executed on three subgrade materials under varying base course thicknesses. Plate load testing was designed to evaluate various plate sizes and testing standards (e.g., the military standard – CRD-C 655-96 and the ASTM standard – ASTM D1196-21). By performing plate load tests on varying base course thicknesses, newly developed effective k curves were developed from …

On Topological Measures And Network Vulnerability Patterns: A Review And Comparative Analysis, Saviz Saei

Theses and Dissertations

Despite much hope for climate change to slow down or even reverse, younger generations face a future overshadowed by extreme events. The indisputable reality is that unless the United Nations establishes comprehensive and sustained climate justice policies, children today will experience five times more extreme events than those that took place a century ago. On Monday, July 3rd of 2023, an unprecedented peak in global temperatures was documented, marking the highest global temperature ever recorded, as the U.S. National Centers for Environmental Prediction reported. These increasing temperatures indicate the ongoing and intensifying phenomenon of climate change, which amplifies the frequency …

Investigation Of Coupled Fluid-Structure Interactions In Supersonic Flows, Seshendra Palakurthy

Theses and Dissertations

The skin panels used in high-speed flights are exposed to various types of loads, such as inertial, elastic, and aerodynamic loads. In addition, oblique shock impingement can cause flow separation and unsteady aerodynamic loading, which can reduce vehicle performance and result in acoustic noise and viscous heating. These loads, when combined, can result in a complex dynamic response, such as flutter. Flutter is characterized by sustained unsteadiness or structural vibrations. Although flutter might not be immediately harmful, it can lead to fatigue failure of the structural components. A vast amount of literature already exists on the panel flutter induced by …

Study The Effects Of Temperature On Laser Cladding Process With Two Different Geometries Using Comsol Multiphysics, Luban Hamdy Hameed Al-Qudsy

AUIQ Technical Engineering Science

Due to the advancement of laser material processing and the high-demand of high-quality processing, COMSOL Multiphyiscs emerges as a powerful solution to the problem, offering multiple simulation in virtual environment with both 2D and 3D geometries. In this work, we aim to study the effects of thermal properties on the laser cladding using both 2D and 3D geometries with Nickle and Copper as promising candidates for rapid processing of materials. The work was done on a personal computer using commercially-available package of COMSOL Multiphysics 5.0. Results shows a notable increment of heat affected zone when the laser power increased. Additionally, …

Disturbance Observer-Based Control Schemes For Off-Grid Renewable Energy-Based Distributed Generation Systems Feeding Unbalanced And Nonlinear Loads, Samantha Sasi Stephen

Thesis/ Dissertation Defenses

This thesis addresses two critical issues in Renewable Energy-based Distributed Generation (REDG) systems that operate autonomously to supply unbalanced and nonlinear loads. The first issue concerns voltage regulation in grid-forming three-phase Pulse Width Modulation Voltage Source Inverters (PWM VSIs), which convert DC power generated by Distributed Generators (DGs) into three-phase AC power. These inverters often face challenges when feeding unbalanced and nonlinear loads, leading to poor voltage quality. To address this, a voltage controller was developed for grid-forming three-phase PWM VSIs to deliver symmetrical and high-quality voltage to such loads. The proposed controller integrates a Disturbance Observer (DO) into a …

Jovial Family Farm Facilitates Intergenerational Learning Opportunities Through Urban Farming, Maera Williams

Purdue Journal of Service-Learning and International Engagement

Maera Williams is a sophomore in Environmental and Ecological Engineering at Purdue University. She joined the Engineering Projects in Community Service (EPICS) Urban Farming team as a freshman and now serves as project manager of ten undergraduate students collaborating with Jovial Family Farm to design and develop three indoor hydroponics systems for a laboratory space on their property in Broad Ripple, IN. Jovial Family Farm is a nonprofit organization founded by Drs. Bobbie and Brian Jellison with the mission to provide senior citizens, their families, and their communities with meaningful engagement opportunities on an intergenerational scale through urban agricultural activities. …

Direct Methanol Fuel Cells Using Pure Methanol, Ryan Spragg

McKelvey School of Engineering Graduate Student Theses & Dissertations

Fuel cell technology has attained significant appeal as a form of renewable energy in recent years due to its diverse applications, various fuel types, and lower greenhouse gas emissions. Of the various fuel cell types, direct methanol fuel cells (DMFCs) hold a set of distinct advantages for stationary and small portable applications. These advantages include faster refueling compared to battery charging, high gravimetric energy density, and ease of production and use compared to hydrogen. However, the DMFC has numerous technical hurdles that prevent its widespread adoption into the commercial market. Namely, the slow reaction kinetics in the anode and the …

Optimized Fabrication Of Dendritic Mesoporous Silica Nanoparticles As Efficient Delivery System For Cancer Immunotherapy, Varsha Godakhindi, Mostafa Yazdimamaghani, Sudip Kumar Dam, Farzana Ferdous, Andrew Z. Wang, Mubin Tarannum, Jonathan Serody, Juan L. Vivero-Escoto

Chemical and Biochemical Engineering Faculty Research & Creative Works

In the past decade, cancer immunotherapy has revolutionized the field of oncology. Major immunotherapy approaches such as immune checkpoint inhibitors, cancer vaccines, adoptive cell therapy, cytokines, and immunomodulators have shown great promise in preclinical and clinical settings. Among them, immunomodulatory agents including cancer vaccines are particularly appealing; however, they face limitations, notably the absence of efficient and precise targeted delivery of immune-modulatory agents to specific immune cells and the potential for off-target toxicity. Nanomaterials can play a pivotal role in addressing targeting and other challenges in cancer immunotherapy. Dendritic mesoporous silica nanoparticles (DMSNs) can enhance the efficacy of cancer vaccines …

Performance Evaluation Of Routing Protocols And Ml-Based Enhancements For Uav-Assisted Post-Disaster Communication Networks, Prachi Choudhary

Doctoral Dissertations and Master's Theses

During natural disasters, the existing communication systems collapse, and the disaster-affected areas become disconnected without any means of exchanging information. The collapse of existing communication networks poses challenges for First-Responders (FRs) in locating survivors during Search and Rescue (SAR) operations and for survivors to communicate for emergency aid. To alleviate post-disaster consequences and save lives, Uncrewed Air Vehicles (UAVs), commonly known as drones, can be employed to establish adaptable and reliable emergency communication networks. UAVs offer portability and rapid deployment, making them effective in crises. This thesis presents two main contributions: 1) Evaluation and Comparison of Routing Protocol Performance: The …

12.02.2024 Orsp Connect, Liz Williamson

ORED Newsletter

Email Address Matters

All of Us Researcher Symposium

Welcome Anya Goldman

Leveraging Machine Learning For Defect Detection In Irrigation Concrete Canal Lining In Egypt: Advancing Construction Quality And Efficiency, Mohamed Nabawy

Civil Engineering

Abstract:

Defects during the construction phase of projects pose significant challenges, particularly in terms of

safety, cost overruns, delays, and labor inefficiencies. In irrigation concrete canal lining construction

with mega investments, early detection of defects is critical to ensuring quality and project success.

This study explores the application of machine learning (ML) for onsite defect detection, focusing

on the development and deployment of an object detection mobile application specifically tailored

for identifying visible defects in concrete canal lining construction. Leveraging the machine learning

capabilities of Microsoft Azure, a custom object detection model was trained and validated to

recognize defects such …

Ge/Sige Quantum Wells: Material For The Post-Moore Era, Troy Alexander Hutchins-Delgado

Optical Science and Engineering ETDs

This dissertation demonstrates high-quality germanium quantum wells on a 200 mm silicon wafer platform, enabling novel device possibilities. Partnering with a commercial silicon-germanium epitaxy supplier, we obtained shallow, undoped germanium quantum wells with high-crystalline quality, confirmed through x-ray diffraction, secondary ion mass spectroscopy, high-resolution scanning transmission electron microscopy, and energy dispersive x-ray spectroscopy. Hall bar devices fabricated on single quantum wells revealed that surface preparation can tune transport properties while maintaining peak mobilities around 10⁵ cm²V⁻¹s⁻¹. Manganese-germanide spintronic contacts were integrated via solid-state reaction, with contact quality assessed through Schottky diodes, transfer length …

Custom Cathode Optimization For Electropolishing Additively Manufactured 316l Stainless Steel, Kasandra Escarcega Herrera

Mechanical Engineering ETDs

Laser powder bed fusion (LPBF) has become increasingly popular for its ability to rapidly manufacture complex metallic parts. However, the surface properties of as-built LPBF parts may degrade overall performance due to tortuous surface features. Consequently, post-processing like electropolishing (EP) to reduce the surface asperities is often needed for LPBF parts to perform as expected. Utilizing experimental and computational approaches, this project aims to more uniformly EP complex shaped parts made from LPBF 316L. For the experimental approach, parts with a three-dimensional T-shape were printed out of 316L stainless steel and EP using an acidic-based and a polyethylene glycol/NaCl-based electrolyte. …

Predictive Modeling And Sustainability Assessment Of Hydrothermal Liquefaction Of Seaweeds: A Techno-Economic And Life Cycle Analysis Approach, Micheal O. Asama

Mechanical Engineering Theses

This study presents comprehensive predictive models and an economic and environmental assessment of HTL for converting macroalgae into biofuels and valuable co-products. Predictive models were developed based on experimental kinetic data to simulate batch HTL of brown seaweed, capturing the yields of biocrude, gas, biochar, and water-soluble compounds as functions of key process variables, including temperature, time, pressure, and water-to-biomass ratio. Analysis of Variance (ANOVA) confirmed that temperature and residence time significantly affect biocrude yield, with an optimal yield of 23% achieved at 283°C, 200 bar, 54 minutes, and a 10:1 water-to-biomass ratio. The model’s predictive accuracy was validated with …

Data Intensive Method For Processing Defect Detection And Mitigation For Composites, Deepak Kumar

Doctoral Dissertations and Master's Theses

Composite manufacturing without processing defects is a crucial step in satisfying the production, performance, and quality requirements of composite materials in various industries. Autoclave processing enables manufacturing of high-quality composite parts with excellent mechanical properties, whereas additive manufacturing (AM) offers adaptability to complex designs and streamlined processes. However, each method presents unique challenges; despite the benefits, autoclave processes can still result in processing defects, and AM is particularly susceptible to processing anomalies owing to the novelty of the process. Ensuring the quality and reliability of composite manufacturing is essential to fully capitalize on the advantages offered by both techniques. Artificial …

Highly Porous Nanocarriers For Osmolyte Delivery And Drought Mitigation In Wheat And Ryegrass, David Britt

Funded Research Records

No abstract provided.

Bilayer Asymmetric-Based Metal-Organic Frameworks Membrane For Blue Energy Conversion, Rockson Kwesi Tonnah, Milton Chai, Mohammad Khedri, Milad Razbin, Reza Maleki, Amir Razmjou, Mohsen Asadnia

Research outputs 2022 to 2026

The conversion of Gibbs free energy at the interface of solutions with salinity gradients into electrical energy is essentially a means of mitigating environmental pollution and bolstering the availability of new energy sources to enhance the renewable energy portfolio. However, a three-dimensional (3D) sub-nanofluidic membrane with high ion conductivity and selectivity for a reverse electrodialysis (RED) based osmotic energy conversion in both aqueous and organic solutions remains largely unexplored. Herein, we engineered a bilayer metal organic frameworks (MOFs) membrane with polystyrene sulfonated angstrom-size channels in UiO-66-NH2 base layer and isoreticular MIL-88B membrane as the top layer to enhance permselectivity and …

Drainage Area Limitations Of Single Watershed, Peak Flow Estimates From Nrcs Methods, Timothy Alexander Maughan

Theses and Dissertations

Most roadway design sections of state Departments of Transportation predict peak flow for culvert design using Natural Resources Conservation Service (NRCS) TR-20 methodology. Even though the approach is more than 50 years old, there is no clear guideline for how large a single watershed drainage area may be while remaining appropriate for predicting peak discharge with this method. Our objective is to identify the drainage area where TR-20 peak flow predictions significantly deviate from flow frequency predictions. We aim to recommend to the Nebraska Department of Transportation (NDOT) a range of basin drainage areas appropriate for predicting peak flow using …

Traveling-Wave Vibration Control And Comparison Of Individuals With Insomnia And Good Sleepers Using Eeg Spectral Power And Sample Entropy, Joseph T. Lecheminant

Theses and Dissertations

This thesis explores the intersection of whole-body vibration (WBV) and neurophysiological analysis to improve sleep quality and understanding of insomnia. The work is divided into two primary areas: the development of a novel traveling-wave vibration system for sleep enhancement and the analysis of electroencephalography (EEG) metrics in individuals with insomnia versus good sleepers. A vibrating sleep system capable of generating programmable traveling-wave patterns is designed and prototyped. Through iterative development and user trials, the system enables highly controlled mechanical stimulation in the form of traveling-wave vibration. Key advancements include independent amplitude and speed modulation and customizable wave patterns. Simple wave …

An Experimental Investigation Of Signal Processing Techniques For Vibration-Based Structural Health Monitoring In Residential Buildings Subjected To Base Excitation, Fedaa Ali

Electrical Engineering Theses

Coastal regions, particularly in the southeastern United States, are consistently confronted with the ongoing threat of hurricane-induced damage to their buildings. Consequently, there is a pressing need to concentrate efforts on the evaluation and prediction of structural integrity and reliability in such environments. This is paramount for minimizing losses and enhancing public safety in the face of these challenging climatic conditions. Current structural health monitoring systems are typically customized for specific buildings, rendering them excessively expensive and impractical for residential structures. This research presents a comprehensive study of signal processing techniques and damage detection for an economical yet efficient structural …

Cellular Air Quality Sensors With Lora Backchannel A Robust Sensor Suited For Remote Deployment In Harsh Environments, Joseph R. Miera

Theses and Dissertations

Air quality significantly impacts health and overall quality of life, making its measurement essential. However, most affordable air quality devices are designed only for use within WiFi range and cannot handle extreme temperatures, limiting their usefulness for people in remote or extreme environments, such as regions with harsh winter climates. This limitation is concerning, as winter often brings worse air quality due to temperature inversions that trap pollutants and increase fuel burning for heating. Inversion is a problem as close to home as Utah Valley, and as far away as Ulaanbaatar, Mongolia. Most low-cost air quality sensors are not built …

Etherealbreathing: A Holographic Biofeedback Game To Support Relaxation In Autistic Children, Arturo Morales Téllez, Isabel López Hurtado, Franceli L. Cibrian, Monica Tentori

Engineering Faculty Articles and Research

Biofeedback training for box breathing is becoming increasingly accessible due to advancements in consumer-grade breathing sensors. However, there is limited research on their design and applications for specialized populations. This study evaluates a novel biofeedback holographic game, EtherealBreathing, designed to support autistic children. In EtherealBreathing, children practice box breathing to collect virtual elements to maintain the Earth's balance, using a wearable sensor to measure chest expansion for breath detection. A deployment study with 20 autistic children revealed that EtherealBreathing effectively promotes box breathing, leading to better health-related outcomes, such as lowering participants’ heart and respiratory rates than traditional practices. Biofeedback …