Engineering Commons^™

Analysis Of Shallow Water Underwater Noise From Marine Pile Driving Using Computational Fluid Dynamics And Empirical Data Fitting, Moses Bosco

UNF Graduate Theses and Dissertations

There has been a growing concern in recent years about the effects of anthropogenic noise due to pile driving on underwater wildlife. Current guidelines for mitigating hydroacoustic effects associated with these geotechnical events are based upon a relatively simple transmission loss formulation known as the Practical Spreading Loss Model (PSLM). This model is easy to implement, but it may produce overly conservative results. Sound data during pile drives from several sites in Florida showed much higher sound attenuation than predicted by the PSLM. The first part of this study focused on explaining this discrepancy using computational fluid dynamics. Specifically, synthetic …

A Kinetic Evaluation For Phenothiazine Base Copolymers, Fatih Dogan

Materials Science and Engineering Faculty Research & Creative Works

In here, the non-isothermal decomposition kinetics of co-polymers-based phenothiazine was present-ed. For this, firstly, 3, 7-di-2-thienyl-10H-phenothiazine (TF) was prepared via an optimized Suzu-ki–Miyaura cross-coupling reaction. After monomer (TF) characterization, the copolymerization re-actions with EDOT and thiophene were performed by the electrochemical technique. The molecular masses of the co-polymers were found by gel permeation chromatography (GPC) analysis. Thermal characterizations of the resulting polymers were conducted by thermogravimetric analyses. The thermal decomposition kinetics of the resulting polymers was also performed. For this, the kinetic methods (Tang, FWO, KAS, Kissinger, and Friedman) based on the multiple heating rates were used. Several kinetic parameters …

Mental Health And The Covid-19 Pandemic: Analysis Of Twitter Discourse, Omar El-Gayar, Abdullah Wahbeh, Tareq Nasralah, Ahmed El Noshokaty, Mohammad A. Al-Ramahi

Computer Information Systems Faculty Publications (Archived)

This study analyzed Twitter discourse to understand the association of the COVID-19 pandemic with mental health. The study compared tweets’ volume over time, tweets’ volume per mental health category, emotions, and the top hashtags on mental health before and after November 2019, the month on which the first COVID-19 case was reported. We analyzed a total of 273 million English tweets on mental health collected from 56 million unique users. Results and analysis showed a significant shift in trend for the volume of tweets on mental health over time. There was also a notable increase in the volume of tweets …

Insuring The 'Uninsurable': Catastrophe Bonds, Pandemics, And Risk Securitization, Steven L. Schwarcz

Faculty Scholarship

In principle, governments could protect against the potential economic devastation of future pandemics by requiring businesses to insure against pandemic-related risks. In practice, though, insurers do not currently offer pandemic insurance. Although they may well be able to obtain sufficient actuarial data to set pandemic underwriting standards and rate tables, insurers are concerned that they lack sufficient capacity, as an industry, to cover those risks, which are likely to occur worldwide and to be highly correlated. Pandemics therefore are in the class of risks, like war, terrorism, and riots, that are deemed “uninsurable,” at least by private markets. This Article …

General Brochure, University Of North Dakota. Energy And Environmental Research Center

EERC Brochures and Fact Sheets

Highlights the Energy & Environmental Research Center’s employment, various resources for energy, fuel testing, technology development, and facilities. [This item is an outdated or superseded version and retained for historical purposes only. It may no longer reflect current information, policies, or practices.]

Novel Machine Learning And Wearable Sensor Based Solutions For Smart Healthcare Monitoring, Rajdeep Kumar Nath

Theses and Dissertations--Electrical and Computer Engineering

The advent of IoT has enabled the design of connected and integrated smart health monitoring systems. These health monitoring systems can be utilized for monitoring the mental and physical wellbeing of a person. Stress, anxiety, and hypertension are the major elements responsible for the plethora of physical and mental illnesses. In this context, the older population demands special attention because of the several age-related complications that exacerbate the effects of stress, anxiety, and hypertension. Monitoring stress, anxiety, and blood pressure regularly can prevent long-term damage by initiating necessary intervention or clinical treatment beforehand. This will improve the quality of life …

Development Of A Hybrid-Electric Aircraft Propulsion System Based On Silicon Carbide Triple Active Bridge Multiport Power Converter, Cole M. Ivey

Theses and Dissertations--Electrical and Computer Engineering

Constrained by the low energy density of Lithium-ion batteries with all-electric aircraft propulsion, hybrid-electric aircraft propulsion drive becomes one of the most promising technologies in aviation electrification, especially for wide-body airplanes. In this thesis, a three-port triple active bridge (TAB) DC-DC converter is developed to manage the power flow between the turbo generator, battery, and the propulsion motor. The TAB converter is modeled based on the emerging Silicon Carbide (SiC) Metal-Oxide-Semiconductor Field Effect Transistor (MOSFET) modules operating at high switching frequency, so the size of the magnetic transformer can be significantly reduced. Different operation modes of this hybrid-electric propulsion drive …

Re-Designing Main Memory Subsystems With Emerging Monolithic 3d (M3d) Integration And Phase Change Memory Technologies, Chao-Hsuan Huang

Theses and Dissertations--Electrical and Computer Engineering

Over the past two decades, Dynamic Random-Access Memory (DRAM) has emerged as the dominant technology for implementing the main memory subsystems of all types of computing systems. However, inferring from several recent trends, computer architects in both the industry and academia have widely accepted that the density (memory capacity per chip area) and latency of DRAM based main memory subsystems cannot sufficiently scale in the future to meet the requirements of future data-centric workloads related to Artificial Intelligence (AI), Big Data, and Internet-of-Things (IoT). In fact, the achievable density and access latency in main memory subsystems presents a very fundamental …

Special Power Electronics Converters And Machine Drives With Wide Band-Gap Devices, Yibin Zhang

Theses and Dissertations--Electrical and Computer Engineering

Power electronic converters play a key role in power generation, storage, and consumption. The major portion of power losses in the converters is dissipated in the semiconductor switching devices. In recent years, new power semiconductors based on wide band-gap (WBG) devices have been increasingly developed and employed in terms of promising merits including the lower on-state resistance, lower turn-on/off energy, higher capable switching frequency, higher temperature tolerance than conventional Si devices. However, WBG devices also brought new challenges including lower fault tolerance, higher system cost, gate driver challenges, and high dv/dt and resulting increased bearing current in electric machines.

This …

Dual-Functional Phosphorene Nanocomposite Membranes For The Treatment Of Perfluorinated Water: An Investigation Of Perfluorooctanoic Acid Removal Via Filtration Combined With Ultraviolet Irradiation Or Oxygenation, Joyner Eke, Lillian Banks, M. Abdul Mottaleb, Andrew J. Morris, Olga V. Tsyusko, Isabel C. Escobar

Internal Medicine Faculty Publications

Nanomaterials with tunable properties show promise because of their size-dependent electronic structure and controllable physical properties. The purpose of this research was to develop and validate environmentally safe nanomaterial-based approach for treatment of drinking water including removal and degradation of per- and polyfluorinated chemicals (PFAS). PFAS are surfactant chemicals with broad uses that are now recognized as contaminants with a significant risk to human health. They are commonly used in household and industrial products. They are extremely persistent in the environment because they possess both hydrophobic fluorine-saturated carbon chains and hydrophilic functional groups, along with being oleophobic. Traditional drinking water …

Data-Driven Discovery Of Material States In Composites Under Fatigue Loads, Muthu Ram Prabhu Elenchezhian, Vamsee Vadlamudi, Rassel Raihan, Kenneth Reifsnider

Institute of Predictive Performance Methodologies (IPPM-UTARI)-Archive

Our community has a widespread knowledge on the damage tolerance and durability of the composites, developed over the past few decades by various experimental and computational efforts. Several methods have been used to understand the damage behavior and henceforth predict the material states such as residual strength (damage tolerance) and life (durability) of these material systems. Electrochemical Impedance Spectroscopy (EIS) and Broadband Dielectric Spectroscopy (BbDS) are such methods, which have been proven to identify the damage states in composites. Our previous work using BbDS method has proven to serve as precursor to identify the damage levels, indicating the beginning of …

Ordinary Differential Equations With Machine Learning For Prediction Of Smart Composite Fracture Toughness, Relebohile George Qhobosheane, Muthu Ram Prabhu Elenchezhian, Vamsee Vadlamudi, Kenneth Reifsnider, Rassel Raihan

Institute of Predictive Performance Methodologies (IPPM-UTARI)-Archive

This work in on the development of an ordinary differential equation (ODE) model coupled with statistical methods for the prediction of fracture toughness of a magnetostrictive, piezoelectric smart self-sensing Fiber Reinforced Polymer (FRP) composite. The smart composite with sensing properties encompasses Terfenol-D alloy nanoparticles and Single Walled Carbon NanoTubes (SWCNT). To explore various configurations the of nanoparticle constituents’ effect on fracture toughness within the FRP composite, the ODE model developed within a finite element analysis (FEA) environment is considered to attain fracture observations across the solution space. The acquired FEA data is then used to feed the machine-learning (ML) algorithms …

Effects Of Surface Characteristics On Mechanical And Dielectric Properties Of Adhesively Bonded Carbon Fiber Composites, Minhazur Rahman, Gayathri Kola, Monjur Morshed Rabby, Muthu Ram Prabhu Elenchezhian, Relebohile George Qhobosheane, Vamsee Vadlamudi

Institute of Predictive Performance Methodologies (IPPM-UTARI)-Archive

The rapid rise of fiber reinforced composite usage in aircraft, spacecraft and automobile industries made the proper comprehension of repair and joining of these materials a crucial aspect. Adhesive bonding is one of the most advantageous and desirable joining and repair technique for fiber reinforced composites. However, the heterogeneity of fiber reinforced composites and the complex interfacial nature of the adhesive bonds, makes most non-destructive evaluation and assessment techniques ineffective to assess the state of the bond. Different manufacturing and surface preparation techniques impart different surface characteristics to the adherends, hence proper understanding of the state of bonds is dependent …

The Theory And Design Of Class E Power Amplifiers For Impulse Excitation In Nuclear Magnetic Resonance, Owen D. Riemer

Browse all Theses and Dissertations

A new method for analyzing the effectiveness of NMR impulse power amplifiers was developed using a classical linear systems approach to NMR. The method demonstrates a way to compare NMR power amplifiers and outputs. Thermodynamic calculations and the harmonic content of NMR amplifiers is presented to provide a complete description of the NMR power amplifier design problem. A design procedure for class E NMR power amplifiers with a pi-impedance matching network is outlined for matching the amplifier to the transmitter coil. The thesis concludes with the presentation of a 53 MHz power amplifier developed with the procedure. The complete amplifier …

Multi-Label Classification On Locally-Linear Data: Application To Chemical Toxicity Prediction, Xiu Huan Yap

Browse all Theses and Dissertations

Computational models may assist in identification and prioritization of large chemical libraries. Recent experimental and data curation efforts, such as from the Tox21 consortium, have contributed towards toxicological datasets of increasing numbers of chemicals and toxicity endpoints, creating a golden opportunity for the exploration of multi-label learning and deep learning approaches in this thesis. Multi-label classification (MLC) methods may improve model predictivity by accounting for label dependence. However, current measures of label dependence, such as correlation coefficient, are inappropriate for datasets with extreme class imbalance, often seen in toxicological datasets. In this thesis, we propose a novel label dependence measure …

Edge Processing Of Image For Uas Sense And Avoidance, Christopher J. Rave

Browse all Theses and Dissertations

Today there is a large market for Unmanned Aerial Systems. Although most current systems are remotely piloted by operators on the ground, increasingly, many of these systems will use some sort of automatic flight controller to help mitigate new challenges, due to their deployment at growing scale. These challenges include, but are not limited to, shortage of FAA-certified UAS pilots, transmission bandwidth and delay constraints and cyber security threats associated with wireless networking, profitability of operations constrained by energy capacity and efficiency and air dynamics planning, and etc. In order to address these rising challenges, this thesis is a part …

Arise - Augmented Reality In Surgery And Education, Sadan Suneesh Menon

Browse all Theses and Dissertations

Human errors in healthcare can be fatal. Proper physical assessment of patients to avoid such errors is of paramount importance. Incorrect or insufficient assessment of the patient can cause treatment delays that may lead to negative outcomes. In this dissertation we introduce innovative technology to assist surgeons in patient assessment as well as during the training of nurses in order to enhance learning. Technological advancements have made it possible to visualize overlays of computer-generated 3D models on real-world surfaces. This technology is called augmented reality. Using Steady State Topography (SST) brain imaging to examine the brain activity of people who …

Leveraging Sequential Nature Of Conversations For Intent Classification, Shree Gotteti

Browse all Theses and Dissertations

Conversations are more than just a sequence of text, it is where two or more participants interact in order to achieve their goals. Conversation Understanding (CU) requires all participants to understand each others intent. In the past decade, CU has been extended from automated human-human text processing to build automated conversational agents for human-machine interactions. Despite their popularity, these automated conversational agents (like Siri, Alexa, etc) can't handle more than one or two utterances, and they don't recognize conversations as intents. The development of approaches that extract intents behind an utterance is essential for the advancements of Question Answering (QA) …

Carbon Nanotube-Coated Scaffolds For Tissue Engineering Applications, Soham Dipakbhai Parikh

Browse all Theses and Dissertations

Carbon Nanotubes (CNTs) have beneficial properties for cell scaffolding, which has translated into effective growth of bone, muscle, and cardiac cells. However, loose carbon nanotubes can cause in vivo toxicity. To reduce this risk, our team has developed biomimetic scaffolds with multiscale hierarchy where carpet-like CNT arrays are covalently bonded to larger biocompatible substrates. In this study, we have tested such scaffolds in two distinct types of biomedical applications involving glioblastoma and keratinocyte cells. The growth of glioblastoma (GBM) cells on our CNT-coated biomimetic scaffolds was evaluated to check their suitability as a potential chemotherapy-loaded implant for GBM patient treatment. …

Evaluation Of Murrell’S Ekf-Based Attitude Estimation Algorithm For Exploiting Multiple Attitude Sensor Configurations, Sharanabasaweshwara Asundi, Norman Fitz-Coy, Haniph Latchman

Mechanical & Aerospace Engineering Faculty Publications

Pico- and nano-satellites, due to their form factor and size, are limited in accommodating multiple or redundant attitude sensors. For such satellites, Murrell's implementation of the extended Kalman filter (EKF) can be exploited to accommodate multiple sensor configurations from a set of non redundant attitude sensors. The paper describes such an implementation involving a sun sensor suite and a magnetometer as attitude sensors. The implementation exploits Murrell's EKF to enable three sensor configurations, which can be operationally commanded, for satellite attitude estimation. Among the three attitude estimation schemes, (i) sun sensor suite and magnetometer, (ii) magnetic field vector and its …

Simulation For Cybersecurity: State Of The Art And Future Directions, Hamdi Kavak, Jose J. Padilla, Daniele Vernon-Bido, Saikou Y. Diallo, Ross Gore, Sachin Shetty

VMASC Publications

In this article, we provide an introduction to simulation for cybersecurity and focus on three themes: (1) an overview of the cybersecurity domain; (2) a summary of notable simulation research efforts for cybersecurity; and (3) a proposed way forward on how simulations could broaden cybersecurity efforts. The overview of cybersecurity provides readers with a foundational perspective of cybersecurity in the light of targets, threats, and preventive measures. The simulation research section details the current role that simulation plays in cybersecurity, which mainly falls on representative environment building; test, evaluate, and explore; training and exercises; risk analysis and assessment; and humans …

Internet-Of-Things Devices In Support Of The Development Of Echoic Skills Among Children With Autism Spectrum Disorder, Krzysztof J. Rechowicz, John B. Stull, Michelle M. Hascall, Saikou Y. Diallo, Kevin J. O'Brien

VMASC Publications

A significant therapeutic challenge for people with disabilities is the development of verbal and echoic skills. Digital voice assistants (DVAs), such as Amazon’s Alexa, provide networked intelligence to billions of Internet-of-Things devices and have the potential to offer opportunities to people, such as those diagnosed with autism spectrum disorder (ASD), to advance these necessary skills. Voice interfaces can enable children with ASD to practice such skills at home; however, it remains unclear whether DVAs can be as proficient as therapists in recognizing utterances by a developing speaker. We developed an Alexa-based skill called ASPECT to measure how well the DVA …

Methods For Weighting Decisions To Assist Modelers And Decision Analysts: A Review Of Ratio Assignment And Approximate Techniques, Barry Ezell, Christopher J. Lynch, Patrick T. Hester

VMASC Publications

Computational models and simulations often involve representations of decision-making processes. Numerous methods exist for representing decision-making at varied resolution levels based on the objectives of the simulation and the desired level of fidelity for validation. Decision making relies on the type of decision and the criteria that is appropriate for making the decision; therefore, decision makers can reach unique decisions that meet their own needs given the same information. Accounting for personalized weighting scales can help to reflect a more realistic state for a modeled system. To this end, this article reviews and summarizes eight multi-criteria decision analysis (MCDA) techniques …

Fuzzy Cognitive Map-Based Knowledge Representation Of Hazardous Industrial Operations, Francesco Longo, Antonio Padovano, Letizia Nicoletti, Caterina Fusto, Mohaiad Elbasheer, Rafael Diaz

VMASC Publications

Hazardous industrial operations are highly stochastic, still human-dependent, and risky. Operators working in such an environment must understand the complex interrelation between several factors contributing to safe and effective operations. Therefore, being able to predict the effects of their actions on provoking or mitigating possible accidents is crucial. This study aims to utilize fuzzy cognitive maps (FCM) to model the expert’s reasoning about occupational health and safety (OHS) in confined space. This knowledge is used by operators to build their mental models. The developed FCM displays all the possible incidents of a confined space and links these incidents with all …

Human Factors, Ergonomics And Industry 4.0 In The Oil & Gas Industry: A Bibliometric Analysis, Francesco Longo, Antonio Padovano, Lucia Gazzaneo, Jessica Frangella, Rafael Diaz

VMASC Publications

Over the last few years, the Human Factors and Ergonomics (HF/E) discipline has significantly benefited from new human-centric engineered digital solutions of the 4.0 industrial age. Technologies are creating new socio-technical interactions between human and machine that minimize the risk of design-induced human errors and have largely contributed to remarkable improvements in terms of process safety, productivity, quality, and workers’ well-being. However, despite the Oil&Gas (O&G) sector is one of the most hazardous environments where human error can have severe consequences, Industry 4.0 aspects are still scarcely integrated with HF/E. This paper calls for a holistic understanding of the changing …

Developing An Artificial Intelligence Framework To Assess Shipbuilding And Repair Sub-Tier Supply Chains Risk, Rafael Diaz, Katherine Smith, Beatriz Acero, Francesco Longo, Antonio Padovano

VMASC Publications

The defense shipbuilding and repair industry is a labor-intensive sector that can be characterized by low-product volumes and high investments in which a large number of shared resources, technology, suppliers, and processes asynchronously converge into large construction projects. It is mainly organized by the execution of a complex combination of sequential and overlapping stages. While entities engaged in this large-scale endeavor are often knowledgeable about their first-tier suppliers, they usually do not have insight into the lower tiers suppliers. A sizable part of any supply chain disruption is attributable to instabilities in sub-tier suppliers. This research note conceptually delineates a …

Digital Twins For Manufacturing And Logistics Systems: Is Simulation Practice Ready?, Francesco Longo, Antonio Padovano, Letizia Nicoletti, Mohaiad Elbasheer, Rafael Diaz

VMASC Publications

This article provides a theoretical contribution to the state-of-the-art of digital twins for manufacturing and logistics systems. The primary goal of this paper is to draw attention to the gap between the theoretical framework of digital twins in manufacturing and supply chain and their practical implementation from a simulation modeling point of view. Therefore, highlighting the recent innovations in the simulation practice that could provide the basis for digital twins with high levels of data integration, automation, and smart capabilities. This study follows a comparative approach to analyzing theoretical and technical readiness for developing digital twins with high fidelity and …

Influence Of The Inherent Safety Principles On Quantitative Risk In Process Industry: Application Of Genetic Algorithm Process Optimization (Gapo), Mehdi Jahangiri, Abolfazl Moghadasi, Mojtaba Kamalinia, Farid Sadeghianjahromi, Sean Banaee

Community & Environmental Health Faculty Publications

Inherent safety (IS) refers to a set of measures that enhance the safety level of processes and equipment, rendering additional equipment and/or add-ons. The early design phase of processes is suited best for implementation of IS strategies as some of such strategies either are impossible to be implemented at the operation phase or substantially increase costs. The purpose of this study is to present a new approach called genetic algorithm process optimization (GAPO), by which processes can be made inherently safer even at the operation phase. This study simulates the IS principle, assessing its impact on quantitative risk and the …

Hidden Markov Model And Cyber Deception For The Prevention Of Adversarial Lateral Movement, Md Ali Reza Al Amin, Sachin Shetty, Laurent Njilla, Deepak K. Tosh, Charles Kamhoua

Computational Modeling & Simulation Engineering Faculty Publications

Advanced persistent threats (APTs) have emerged as multi-stage attacks that have targeted nation-states and their associated entities, including private and corporate sectors. Cyber deception has emerged as a defense approach to secure our cyber infrastructure from APTs. Practical deployment of cyber deception relies on defenders' ability to place decoy nodes along the APT path optimally. This paper presents a cyber deception approach focused on predicting the most likely sequence of attack paths and deploying decoy nodes along the predicted path. Our proposed approach combines reactive (graph analysis) and proactive (cyber deception technology) defense to thwart the adversaries' lateral movement. The …

Modeling And Simulation Of Cascading Failures In Transportation Systems During Hurricane Evacuations, Yuan Zhu, Kaan Ozbay, Hong Yang, Fan Zuo, Di Sha

Computational Modeling & Simulation Engineering Faculty Publications

Effective and timely evacuation is critical in alleviating the impact of hurricanes. As such, evacuation models are often sought to support the preparedness of evacuations. One important task in the modeling process is to evaluate exogenous factors that cause transportation system capacity loss during evacuation. Typical factors include direct damage to the roadway network due to storm surge and cascading impacts because of other facilities failures. For example, power outage can lead to signal failure and subway suspension. This paper aims to develop a macroscopic simulation-based approach to study the capacity loss of the roadway network in evacuation due to …