Engineering Commons^™

Interaction Of Particles With Plasma And Shock Produced By Pulsed Spark Discharge, Shomik Mukhopadhyay

Dissertations

Interactions of powders with high-temperature plasma and shockwaves occur in diverse scenarios, such as nuclear blasts, accidental industrial dust explosions, solid propellant combustion in explosive charges and when removing contaminants from surfaces. Electrostatic Discharge (ESD), known for generating shock and plasma, is a promising lab-scale technique for simulating these interactions. Studies with ESD involved placing powders near a spark-producing gap between electrodes and observing mechanical and chemical processes like particle motion and ignition. A limited range of spark conditions and material properties have been tested, which facilitated the development and validation of preliminary computational models describing this system. Significant gaps …

Machine Learning-Based Design Of Doppler Tolerant Radar, Kyle Peter Wensell

Dissertations

In this work, machine learning theory is applied to the design of a radar detector in order to train a machine learning-based detector that is robust against Doppler shifts. The radar system is designed to work with data that would be otherwise intractable to conventional optimal detector design, such as transmitted noise waveforms and the effects of one-bit quantization at the receiver. The detection performance of the one-bit receiver is shown to match the performance of the derived square-law sign correlator detector. The resulting learning-based detector also introduces Doppler tolerance to the system, which allows for the successful detection of …

Decentralized Control Of Renewable Generation Systems, Milad Shojaee

Dissertations

As the global community struggles with the escalating challenges of climate change and environmental degradation, the transition to renewable energy sources has emerged as a paramount solution. Harnessing energy from renewable sources such as solar, wind, and hydro power not only alleviates the adverse effects of conventional fossil fuel energy sources, but also establishes a foundation for a sustainable and resilient future. Microgrids have been utilized as a feasible platform to integrate renewable energy sources into the electrical power generation networks. They include one or more generation units connected to nearby users, and are able to operate in both grid-connected …

Information Theoretic Bounds For Capacity And Bayesian Risk, Ian Zieder

Dissertations

In this dissertation, the problem of finding lower error bounds on the minimum mean-squared error (MMSE) and the maximum capacity achieving distribution for a specific channel is addressed. Presented are two parts, a new lower bound on the MMSE and upper and lower bounds on the capacity achieving distribution for a Binomial noise channel. The new lower bound on the MMSE is achieved via use of the Poincare inequality. It is compared to the performance of the well known Ziv-Zakai error bound. The second part considers a binomial noise channel and is concerned with the properties of the capacity-achieving distribution. …

A Molecular Dynamics Study On The Destruction Mechanism Of Per And Polyfluoroalkyl Substances Due To Ultrasound Technology, Bruno Bezerra De Souza

Dissertations

Per- and polyfluoroalkyl substances (PFAS) are a group of stable synthetic chemicals that are highly persistent and harmful pollutants to the environment and human health. PFAS have caused a strong public and regulatory response due to their ubiquitous presence in the environment and toxicity to humans. The application of ultrasound is one of the most effective treatment technologies for the mineralization of PFAS in contaminated water. However, this technology is treated as a black box causing the inability to be optimized. Therefore, there is a pressing need to investigate the intricate dynamics of PFAS degradation under ultrasound to unlock its …

Graph-Based Modeling And Optimization Of Wpt Systems For Evs, Matthew J. Hansen, Greg Droge, Abhilash Kamineni

Electrical and Computer Engineering Student Research

A model of a system of wireless power transfer (WPT) pads is developed, where each WPT pad is modeled as a node and the coupling between pads is modeled as graph edges. This modeling approach is generalized to admit primary, secondary, and booster coils, where power can flow among the pads and a pad can fill multiple roles. An excitation in one pad induces voltage and current in all neighboring pads, causing each pad to act as both a booster coil and either a transmitter or a receiver. Power flow through the entire system can be modeled with the graph …

Molecular-To-Continuum Scale Modeling Of Aerosols: Atmospheric Application And Beyond, Ella Ivanova

Dissertations

Aerosol modeling is critical for various applications, such as climate forecasting, air quality, and human health impact assessment. During their lifetime, aerosols undergo a complex evolution, usually divided into several stages — formation, processing, transport, and removal — that occur on different scales. Thus, the choice of modeling methods depends on the stage considered. For example, certain stages of particle formation may require nano-scale modeling while aerosol-cloud interactions span from microscale to mesoscale. This study examines the modeling of aerosol behavior over a wide range of scales, from nano to microscale, with implications to mesoscale.

This dissertation focuses on two …

Microplastic Abundance And Removal In Stormwater Using Green Infrastructure, Meghana Parameswarappa Jayalakshmamma

Dissertations

Microplastics (MPs) are increasingly recognized as a pervasive environmental contaminant, conveying other contaminants, accumulating in aquatic organisms, and posing ecological risks. The existing research has primarily focused on MPs in wastewater treatment plant effluents in surface waters. However, the role of stormwater systems in MP transport has been less explored. Given the rise in MPs from urban sources, stormwater runoff from urban areas may serve as a critical conduit for transporting land-based MPs into aquatic environments. Green infrastructures (GIs) have been recognized for mitigating flooding and improving water quality from minor storms by trapping stormwater pollutants. Yet, the capability of …

Reproducible Fluid Structure Interaction For Complex Flows In Engineered Systems, Allen Prasad Varghese

Dissertations

This dissertation focuses on the application of numerical models to study Fluid Structure Interaction (FSI) in the industrial context. The emphasis is on a series of case studies belonging to practical applications in design and manufacturing and that are solved by a synergistic use of theoretical and computational models. The first study looks into the hydrodynamic actions experienced by vibrating slender structures immersed in viscous fluids near the free surface. This study case is relevant to applications such as, for example, marine propulsion, micro-electro-mechanical systems, and atomic force microscopy. The hydrodynamic problem is governed by three parameters, namely the frequency, …

Development Of Super Hydrophobic Membranes And Their Applications, Sumona Paul

Dissertations

Effective liquid phase separation is vital across industries, especially in aviation, chemicals, fuels, and textiles. Membrane technology offers advantages over traditional methods like distillation, with low energy consumption and protection for heat-sensitive molecules. Membrane performance is assessed based on factors such as materials, surface modification, and interactions. This research targets superhydrophobic membranes for liquid-liquid filtration and antiwetting omniphobic membranes for membrane distillation, focusing on properties like contact angle and thermal resistance.

This study presents a highly hydrophobic membrane achieved by immobilizing carbon nanotubes (CNTs) onto a PTFE microfiltration membrane. It's designed for dewatering organic-water mixtures with trace water content via …

Application Of Secant Span In Medical Diagnosis, R. Narmadhagnanam, A. Edward Samuel

Neutrosophic Systems with Applications

Many common and specific characteristics engrave most diseases. Water-borne diseases differ slightly in their characteristics. Erroneous diagnoses can be attributed to shared characteristics. Current approaches tend to rely on imprecise diagnoses and lack robust techniques for differentiating between characteristics. Every illness also presents with specific symptoms. To assist doctors in approaching a likely diagnosis, the suggested method is successful in determining the connection between a class of sickness and the people with a specific pathology to the indications. Among n-valued interval neutrosophic sets, a secant span is proposed in this paper and a few of its attributes are talked about …

Rough Fermatean Neutrosophic Sets And Its Applications In Medical Diagnosis, P. Dhanalakshmi

Neutrosophic Systems with Applications

This paper introduces the concept of rough fermatean neutrosophic sets and investigates their properties. Additionally, a cosine similarity measure between these sets is proposed. By applying this measure to a medical diagnosis example, the paper illustrates how the method can be used in practical situations, highlighting its effectiveness in complex decision-making scenarios. This innovation holds promise for improving decision-making processes, especially in critical areas like medical diagnosis, where making accurate assessments amidst uncertainty is crucial.

Machine Learning Based Analysis Of Civil Infrastructure In The Presence Of Sparse Data, Megan Butcher

Doctoral Dissertations and Master's Theses

The high computational cost of estimating engineering demand parameters (EDPs) via finite element (FE) models, which incorporate uncertainties in earthquake events and material properties, limits the application of the Performance-Based Earthquake Engineering (PBEE) framework. Previous efforts to replace FE models with surrogate models have typically focused only on building parameters, necessitating re-training for new, unseen earthquakes. This paper introduces a machine learning-based surrogate model framework that addresses both earthquake and material parameter uncertainties to predict responses for unseen seismic events. Earthquakes are characterized by their projections on an orthonormal basis, computed using Singular Value Decomposition (SVD) of a representative ground …

Consequences Of Spatial Heterogeneity For Turbulent Wake Development, Ryan Scott

Dissertations and Theses

Spatial heterogeneity is an fundamental property of natural systems. In fluid dynamics subtle variations in fluid motion give rise to chaotic turbulent flows. When a fluid passes an object it retains an imprint of the object as a momentum deficit known as a wake. The resulting spatial structure of the wake is intrinsically linked to the object responsible for its creation. The coupling between geometric complexity in wake producing entities and turbulent wake evolution is considered in terms of spatial heterogeneity from individual wakes through turbulent canopy flows. First a novel Lacunarity-based method is developed for quantifying spatial heterogeneity in …

Effect Of Antioxidant Additives And Recycling Agents On Performance Of Asphalt Binders And Mixtures, Phase I, Nitish R. Bastola, Mahdieh Khedmati, Hamzeh Haghshenas, Jamilla Teixeira

Nebraska Department of Transportation: Research Reports

The use of reclaimed asphalt pavement (RAP) in asphalt mixtures has notably increased in recent times. Nevertheless, the inherent stiff and aged characteristics of RAP materials have consistently raised concerns regarding cracking performance. The use of recycling agents (RAs) has gained popularity in recent years since they can effectively modify the engineering properties of the aged asphalt binder. Besides that, the combination of RA with antioxidant (AO) additives has shown promise in enhancing the long-term performance of RAP mixtures. This research aims to investigate the effect of various RAs and one AO additive on performance of asphalt binders and high-RAP …

Development Of The Nebraska Department Of Transportation Winter Severity Index – Phase Ii, Mark Anderson, Curtis L. Walker, Thomas Kauzlarich

Nebraska Department of Transportation: Research Reports

For the Nebraska Department of Transportation (NDOT), the Nebraska Winter Severity Index (NEWINS) provided an independent framework to calculate a winter season’s severity by categorizing individual winter storms. However, one of the greatest limitations of NEWINS is that it is not predictive. Thus, this study builds on the previously developed NEWINS by creating a predictive winter storm severity index known as NEWINS-Predictive (NEWINS-P). The quantitative precipitation forecast, snow accumulation, ice accumulation, and surface wind speed parameters from the National Digital Forecast Database (NDFD) are used to develop the five components composing the NEWINS-P framework. These components consist of snow severity …

Integrating Edge-Intelligence In Auv For Real-Time Fish Hotspot Identification And Fish Species Classification, U. Sowmmiya, J. Preetha Roselyn, Prabha Sundaravadivel

Electrical Engineering Faculty Publications and Presentations

Enhancing the livelihood environment for fishermen's communities with the rapid technological growth is essential in the marine sector. Among the various issues in the fishing industry, fishing zone identification and fish catch detection play a significant role in the fishing community. In this work, the automated prediction of potential fishing zones and classification of fish species in an aquatic environment through machine learning algorithms is developed and implemented. A prototype of the boat structure is designed and developed with lightweight wooden material encompassing all necessary sensors and cameras. The functions of the unmanned boat (FishID-AUV) are based on the user's …

Rough Fermatean Neutrosophic Sets And Its Applications In Medical Diagnosis, P. Dhanalakshmi

Neutrosophic Systems with Applications

This paper introduces the concept of rough fermatean neutrosophic sets and investigates their properties. Additionally, a cosine similarity measure between these sets is proposed. By applying this measure to a medical diagnosis example, the paper illustrates how the method can be used in practical situations, highlighting its effectiveness in complex decision-making scenarios. This innovation holds promise for improving decision-making processes, especially in critical areas like medical diagnosis, where making accurate assessments amidst uncertainty is crucial.

Application Of Secant Span In Medical Diagnosis, R. Narmadhagnanam, A. Edward Samuel

Neutrosophic Systems with Applications

Many common and specific characteristics engrave most diseases. Water-borne diseases differ slightly in their characteristics. Erroneous diagnoses can be attributed to shared characteristics. Current approaches tend to rely on imprecise diagnoses and lack robust techniques for differentiating between characteristics. Every illness also presents with specific symptoms. To assist doctors in approaching a likely diagnosis, the suggested method is successful in determining the connection between a class of sickness and the people with a specific pathology to the indications. Among n-valued interval neutrosophic sets, a secant span is proposed in this paper and a few of its attributes are talked about …

Methodology For Developing Biodegradable Polymer Blends And Composites For Agriculture, Fangzhong Xing

Theses

The use of polyethylene (PE) films to improve soil conditions and to increase crop yield has produced microplastics that are harmful to our ecosystem. The overall objective of this thesis is to develop an effective biodegradable polymer/composite to replace PE, and hence, to reduce microplastic pollution. The focus of this research is to develop a systematic protocol for assessing the suitability of the biodegradable films based on industry standards in agriculture. For this purpose, a range of biodegradable polymer blends are prepared using polylactic acid (PLA) and polybutylene adipate-co-terephthalate (PBAT) with varying PLA to PBAT ratios. Solvent casting combined with …

Neural Operator For Accelerating Coronal Magnetic Field Computations In Bifrost Mhd Model, Yutao Du

Theses

The application of the Tensorized Fourier Neural Operator (TFNO) to significantly enhance the computational efficiency of coronal magnetic field calculations within the Bifrost Magnetohydrodynamics (MHD) model is introduced in this study. Leveraging simulated data from the European Sunrise Science Data Center, the TFNO? an extension of the Fourier Neural Operator (FNO) that incorporates tensor decomposition for improved handling of high-dimensional data?is employed to solve time-varying partial differential equations (PDEs) over a 3D domain. The performance of the TFNO is compared with traditional machine learning methods, including Vision Transformer and CNN-RNN (encoder-decoder) architectures, to demonstrate its accuracy, computational efficiency, and scalability. …

Marking Estimation In Petri Nets Using Dynamic Mode Decomposition, Aditya Kale

Theses

Petri Nets (PNs) are a well-established framework for modeling and analyzing complex systems with interacting, concurrent processes. This thesis extends traditional Petri Net methodologies by integrating Dynamic Mode Decomposition (DMD), a technique originally developed for fluid dynamics, to analyze Continuous Petri Nets (CPNs). By applying DMD to CPN marking evolution, this research constructs a reduced-order model that captures its dynamics through dynamic modes and eigenvalues, enabling prediction of future markings without detailed knowledge of transition firings or underlying deterministic models. The principal contribution of this research is extending the kit of tools available for analysis of CPN dynamics, providing insights …

Effects Of Exoskeletal-Assisted Walking Rehabilitation On Gait Of Patients Post Stroke, Archisha Kanchan

Theses

Stroke can have detrimental effects on one's body. Its symptoms can range from lightheadedness to blurred vision to body paralysis. One of the more common effects of stroke is difficulty walking where many of the patients who have suffered from stroke are unable to ambulate fully. To mitigate gait difficulties, patients typically follow through with various kinds of physical therapy to help with their gait movements. Recently, robotic exoskeleton (RE) walking therapy has been used as a more innovative approach to gait rehabilitation, in conjunction with other physical therapy session techniques. However, studies involving RE therapy within the stroke population …

The Next Strike: Pioneering Forward-Thinking Attack Techniques With Rowhammer In Dram Technologies, Nakul Kochar

Theses

In the realm of DRAM technologies this study investigates RowHammer vulnerabilities in DDR4 DRAM memory across various manufacturers, employing advanced multi-sided fault injection techniques to impose attack strategies directly on physical memory rows. Our novel approach, diverging from traditional victim-focused methods, involves strategically allocating virtual memory rows to their physical counterparts for more potent attacks. These attacks, exploiting the inherent weaknesses in DRAM design, are capable of inducing bit flips in a controlled manner to undermine system integrity. We employed a strategy that compromised system integrity through a nuanced approach of targeting rows situated at a distance of two rows …

Targeted Drug Delivery: Investigating Protein Corona Behavior, Atharva Markale

Theses

Due to high specificity and less toxicity, nanoparticles have become promising for targeted drug delivery against cancer, although they face challenges when they enter the bloodstream, making their behavior unpredictable. The deposition of proteins on nanoparticles, the protein corona, changes their biosignature, affecting their circulation, drug release potency, targeting ability, and immunogenicity. The continuous exchange of protein layers on a nanoscale is complex to analyze.

Nanoparticle tracking analysis (NTA) is a method to characterize nanoparticles in blood plasma by combining principles of light scattering microscopy and Brownian motion. In this work, time-dependent experiments with plasma were conducted to analyze the …

Electrochemical Nitrate Reduction To Ammonia On Cu Based Nanoparticles Using Quantum Mechanical Simulations, Kathan Bhavin Shukla

Theses

Nitrate reduction to ammonia (NRA) is critical for environmental remediation and energy conservation, as it can remove harmful nitrate (NO₃^-) from water sources while producing usable ammonia (NH₃). Cu represents one of the most promising non-noble-metal NRA electrocatalysts. However, the intrinsic catalytic activity of Cu facets and their influence under different pH conditions remain unclear, particularly in the presence of ions commonly found in wastewater such as Cl^-, Na⁺, Mg²⁺, and Ca²⁺. Using density functional theory (DFT) calculations, we evaluated the nitrate reduction to ammonia (NRA) pathways …

Strawberry Nectar Preservation Through Innovative Techniques And Energy Evaluation For High-Pressure Processing, Caterina Scaioli

Theses

Strawberries are universally adored by people of all ages, owing to their richness in vitamins, nutrients, and antioxidants, offering myriad health benefits, including combating free radicals. However, despite their popularity, strawberry juices or nectars are not commonly found in markets due to their delicate structure, which makes them prone to rapid deterioration of their prized qualities and vibrant red color. In the food industry, preventing browning and nutrient deterioration are often the primary challenges faced when processing red juices. Traditional preservation methods, such as pasteurization, are inadequate in maintaining their freshness. The focus of this study is to explore alternative …

Monetary Condition Index And Its Relation With Other Macroeconomic Variables: An Empirical Study In Selected Mena Countries, Jinan Jihad Kassem

BAU Journal - Creative Sustainable Development

This article aims to construct a monetary condition index (MCI) for five countries in the MENA region, namely Algeria, Bahrain, Egypt, Jordan, and Morocco, in order to interpret the stance of monetary policy in these countries. A broad MCI has been constructed by combining two transmission channels of monetary policy, the real interest rate and the real effective exchange rate, along with bank credit to the private sector. These three indicators of the monetary conditions are collected for these countries over the period 1995–2020 for all countries except for Bahrain, which has data from 1995 to 2015. Principal component analysis …

Examining Elevation Opening Ratio And Space Proportions In Lebanese Schools, Chirine Traboulsi, Mary Felix

BAU Journal - Creative Sustainable Development

The academic performance and outcomes of students are significantly impacted by the architecture of educational institutions. When designing learning spaces, two important considerations are the size of the room and the elevation opening percentage that describe how much daylight enters the space through windows. Previous studies showed that these factors have an important effect on student learning performance. This study explores the link between elevation opening percentage and space proportions in educational institutions. In order to assess daylight dispersal in a classroom in Lebanon that faced north—the direction required for the nation's best solar exposure—a quantitative approach utilizing modelling software …

Business Process Anomaly Detection And Root Cause Analysis Using Blstm-Vae With Attention, Yasser Ismail, Eman El-Aziz, Radwa Fathalla, Mohamed Shaheen

Faculty Publications

Detecting anomalous executions in business process data is crucial for safeguarding the efficiency and success of an organization. Unsupervised approaches are commonly used for business process anomaly detection because of the scarcity of labeled anomaly data. However, these approaches often encounter a notable decline in performance because they lack prior knowledge about the anomalies. Additionally, most of them do not perform root cause analysis on the detected anomalies. This study proposes a variational autoencoder-based approach to overcome the performance limitations of existing unsupervised methods and determine the root causes of the detected anomalies. The learning of the variational autoencoder from …