Engineering Commons^™

Use Of Digital Twins To Mitigate Communication Failures In Microgrids, Andrew Eggebeen

Theses and Dissertations

This work investigates digital twin (DT) applications for electric power system (EPS) resilience. A novel DT architecture is proposed consisting of a physical twin, a virtual twin, an intelligent agent, and data communications. Requirements for the virtual twin are identified. Guidelines are provided for generating, capturing, and storing data to train the intelligent agent. The relationship between the DT development process and an existing controller hardware-in-the-loop (CHIL) process is discussed. To demonstrate the proposed DT architecture and development process, a DT for a battery energy storage system (BESS) is created based on the simulation of an industrial nanogrid. The creation …

A Design Strategy To Improve Machine Learning Resiliency Of Physically Unclonable Functions Using Modulus Process, Yuqiu Jiang

Theses and Dissertations

Physically unclonable functions (PUFs) are hardware security primitives that utilize non-reproducible manufacturing variations to provide device-specific challenge-response pairs (CRPs). Such primitives are desirable for applications such as communication and intellectual property protection. PUFs have been gaining considerable interest from both the academic and industrial communities because of their simplicity and stability. However, many recent studies have exposed PUFs to machine-learning (ML) modeling attacks. To improve the resilience of a system to general ML attacks instead of a specific ML technique, a common solution is to improve the complexity of the system. Structures, such as XOR-PUFs, can significantly increase the nonlinearity …

Methodology For Designing Assistive Robots For Activities Of Daily Living Assistance, Javier Dario Sanjuan De Caro

Theses and Dissertations

The growing prevalence of Upper or Lower Extremities Dysfunctions (ULED), often linked to central nervous disorders such as stroke, Spinal Cord Injury (SCI), and Multiple Sclerosis (MS), underscores the urgent need for innovative support solutions. Over 5.35 million Americans currently live with ULED, a situation that places a significant socioeconomic burden on families and society. Despite invaluable support from caregivers and family members, the need for more scalable, practical solutions persists.

Wheelchair-mounted assistive robots emerge as a promising alternative in this context. These devices, offering continuous and reliable assistance, significantly alleviate caregiver fatigue and enhance the independence and quality of …

Utilizing Fluorescent Nanoscale Particles To Create A Map Of The Electric Double Layer, Quintus Owen

Theses and Dissertations

The interactions between charged particles in solution and an applied electric field follow several models, most notably the Gouy-Chapman-Stern model, for the establishment of an electric double layer along the electrode, but these models make several assumptions of ionic concentrations and an infinite bulk solution. As more scientific progress is made for the finite and single molecule reactions inside microfluidic cells, the limitations of the models become more extreme. Thus, creating an accurate map of the precise response of charged nanoparticles in an electric field becomes increasingly vital. Another compounding factor is Brownian motion’s inverse relationship with size: large easily …

Image-Based Cancer Diagnosis Using Novel Deep Neural Networks, Hosein Barzekar

Theses and Dissertations

Cancer is the major cause of death in many nations. This serious illness can only be effectivelytreated if it is diagnosed early. In contrast, biomedical imaging presents challenges to both clinical institutions and researchers. Physiological anomalies are often characterized by modest modifications in individual cells or tissues, making them difficult to detect visually. Physiological anomalies are often characterized by slight abnormalities in individual cells or tissues, making them difficult to detect visually. Traditionally, anomalies are diagnosed by radiologists and pathologists with extensive training. This procedure, however, demands the participation of professionals and incurs a substantial expense, making the classification of …

Use Of Machine Learning And Natural Language Processing To Enhance Traffic Safety Analysis, Md Abu Sayed

Theses and Dissertations

Despite significant advances in vehicle technologies, safety data collection and analysis, and engineering advancements, tens of thousands of Americans die every year in motor vehicle crashes. Alarmingly, the trend of fatal and serious injury crashes appears to be heading in the wrong direction. In 2021, the actual rate of fatalities exceeded the predicted rate. This worrisome trend prompts and necessitates the development of advanced and holistic approaches to determining the causes of a crash (particularly fatal and major injuries). These approaches range from analyzing problems from multiple perspectives, utilizing available data sources, and employing the most suitable tools and technologies …

Enhancement Of Energy Efficiency For Thermal Energy And Biomass Driven Applications, Osama Mansour Selim Elsayed

Theses and Dissertations

The importance of gas turbine blades is to convert the thermal energy into shaft work output, which makes the turbine blades are one of the critical components of the gas turbines. Besides the mechanical stresses caused by the centrifugal force and the fluid forces, the thermal stresses arise because of the temperature gradient within the blade materials. This paper aims to have a uniform circumferential temperature field at the combustor exit, consequently reducing the thermal stresses caused by the non-uniform temperature distribution along the turbine blade. The validation of the simulation results with the experiments showed an acceptable agreement with …

Study Of The Chemical Fabrication Process Of Nsom Probes And The Modification Of The Probe Surface, Muhammad Nazmul Hussain

Theses and Dissertations

Near-field scanning optical microscopy (NSOM) merges scanning probe technology with the power of high-resolution optical microscopy and provides a natural view into the nanoworld. NSOM requires tapered probes with subwavelength optical apertures and wide cone angles to efficiently channel the illumination light to the tip apex so that it can acquire optical images beyond the diffraction limit. Tapered probes with a range of cone angles can be fabricated through chemical etching of optical fibers using hydrofluoric acid (HF) by varying the etching time. Apart from their use for NSOM imaging, such optical probes can also be transformed into nanosensors by …

Development Of A Novel Telemanipulation Framework For Human-Robot Collaboration Using Ptc Thingworx And Vuforia Studio, Preet Parag Modi

Theses and Dissertations

Significant advancements in contemporary telehealth care applications are enforcing the demand for effective and intuitive telerehabilitation tools. The current techniques for observing live process parameters of robots frequently require complex and inefficient methods, which fundamentally limits the human administrator's ability to settle on the most educated decisions possible. Telemanipulation can minimize the distance and costs in varieties of robot applications, including industry for object manipulation and robot-aided rehabilitation. This research aims to develop a novel telemanipulation framework to deliver robot-assisted rehabilitation using PTC ThingWorx’s Industrial Internet of Things (IIoT), and Vuforia Studio’s Augmented Reality (AR) platforms. This communication architecture is …

Advanced Analytics In Smart Manufacturing: Anomaly Detection Using Machine Learning Algorithms And Parallel Machine Scheduling Using A Genetic Algorithm, Meiling He

Theses and Dissertations

Industry 4.0 offers great opportunities to utilize advanced data processing tools by generating Big Data from a more connected and efficient data collection system. Making good use of data processing technologies, such as machine learning and optimization algorithms, will significantly contribute to better quality control, automation, and job scheduling in Smart Manufacturing. This research aims to develop a new machine learning algorithm for solving highly imbalanced data processing problems, implement both supervised and unsupervised machine learning auto-selection frameworks for detecting anomalies in smart manufacturing, and develop a genetic algorithm for optimizing job schedules on unrelated parallel machines. This research also …

A Deep Recurrent Neural Network With Iterative Optimization For Inverse Image Processing Applications, Masaki Ikuta

Theses and Dissertations

Many algorithms and methods have been proposed for inverse image processing applications, such as super-resolution, image de-noising, and image reconstruction, particularly with the recent surge of interest in machine learning and deep learning methods.

As for Computed Tomography (CT) image reconstruction, the most recently proposed methods are limited to image domain processing, where deep learning is used to learn the mapping between a true image data set and a noisy image data set in the image domain. While deep learning-based methods can produce higher quality images than conventional model-based algorithms, these methods have a limitation. Deep learning-based methods used in …

Functional Material Systems For Stimuli-Responsive Interference Coloration, Milad Momtaz

Theses and Dissertations

Part I: Responsive Interference Coloration (RIC) Systems for High-Performance Humidity Sensing

High-humidity conditions (85−100% relative humidity) have a variety of effects on many aspects of our daily lives. In spite of significant progress in the development of structural coloration-based humidity sensors, enhancing the sensitivity and visual humidity resolution of these sensors at high-humidity environment remains a big challenge. In this work, high-performance colorimetric humidity sensors based on environment-friendly konjac glucomannan (KGM) are introduced. These sensors are fabricated via thin-film interference and prepared using a simple, affordable, and scalable method. An effective approach is shown for markedly improving the sensitivity and …

Transport, Photoluminescence & Photoconduction Characteristics Of Free Standing Two-Dimensional Γ-Alumina & Titanium Superlattice Doped Two-Dimensional Γ-Alumina Grown By Graphene-Assisted Atomic Layer Deposition, Elaheh Kheirandish

Theses and Dissertations

This study presents a facile high-yield bottom-up fabrication, morphology, crystallographic and optoelectronic characterization of free-standing quasi-2D γ-alumina, a non van der Waals 2D material. The synthesis comprises a multi-cycle atomic layer deposition (ALD) of amorphous alumina on a porous interconnected graphene foam as a growth scaffold and removed next by annealing and sintering the alumina/graphene/alumina sandwich at ~ 800 °C in air . The crystallographic and structural characteristics of the formed non-van der Waals quasi 2D γ-alumina were studied by X-ray diffraction (XRD), selected area electron diffraction (SAED), and high-resolution transmission electron microscopy (HRTEM). This analysis revealed the synthesized 2D …

Development Of A 7 Dof Exoskeleton Robot For Rehabilitation Of Lower Extremity, Sk Hasan

Theses and Dissertations

The World Health Organization reports that worldwide about 1 billion people have some form ofdisability. Of these, 110-190 million people have significant difficulties in functioning (mainly upper and lower extremity disability) independently. The major causes of human lower extremity disability include stroke, trauma, spinal cord injuries, and muscular dystrophy. Every 40 seconds, someone in the United States has a stroke. A statistic shows that approximately 65% of post-stroke patients suffer lower extremity impairment. Rehabilitation programs are the main method to promote functional recovery in disabled individuals. The conventional therapeutic approach requires a long commitment from a therapist or a clinician. …

Theoretical And Computational Modeling Of Contaminant Removal In Porous Water Filters, Aman Raizada

Theses and Dissertations

Contaminant transport in porous media is a well-researched problem across many scientific and engineering disciplines, including soil sciences, groundwater hydrology, chemical engineering, and environmental engineering. In this thesis, we attempt to tackle this multiscale transport problem using the upscaling approach, which leads to the development of macroscale models while considering a porous medium as an averaged continuum system.

First, we describe a volume averaging-based method for estimating flow permeability in porous media. This numerical method overcomes several challenges faced during the application of traditional permeability estimation techniques, and is able to accurately provide the complete permeability tensor of a porous …

Medical Image Segmentation Using Machine Learning, Masoud Khani

Theses and Dissertations

Image segmentation is the most crucial step in image processing and analysis. It can divide an image into meaningfully descriptive components or pathological structures. The result of the image division helps analyze images and classify objects. Therefore, getting the most accurate segmented image is essential, especially in medical images. Segmentation methods can be divided into three categories: manual, semiautomatic, and automatic. Manual is the most general and straightforward approach. Manual segmentation is not only time-consuming but also is imprecise. However, automatic image segmentation techniques, such as thresholding and edge detection, are not accurate in the presence of artifacts like noise …

Wound Image Classification Using Deep Convolutional Neural Networks, Behrouz Rostami

Theses and Dissertations

Artificial Intelligence (AI) includes subfields like Machine Learning (ML) and DeepLearning (DL) and discusses intelligent systems that mimic human behaviors. ML has been used in a wide range of fields. Particularly in the healthcare domain, medical images often need to be carefully processed via such operations as classification and segmentation. Unlike traditional ML methods, DL algorithms are based on deep neural networks that are trained on a large amount of labeled data to extract features without human intervention. DL algorithms have become popular and powerful in classifying and segmenting medical images in recent years. In this thesis, we shall study …

Design Of A Novel Manual And Automated Penetration Testing Framework For Connected Industrial Control Systems (Ics), Rafat Elsharef

Theses and Dissertations

This research presents the design of new framework—a manually executed and an automated penetration testing process for Connected Industrial Control Systems (ICS). Both frameworks were built using open-source security software and ICS equipment currently used in critical infrastructure, manufacturing companies, and other institutions in the United States and around the world. Existing penetration testing frameworks have largely been focused on manual testing and are specific to Information Technology (IT). In addition, a new severity scoring system framework, called Common Vulnerability Scoring System for Industrial Control Systems (CVSS-ICS), was recommended for calculating the severity score in Industrial Control Systems (ICS).The broader …

A Simulation Framework For Traffic Safety With Connected Vehicles And V2x Technologies, Md Abu Sayed

Theses and Dissertations

With the advancement in automobile technologies, existing research shows that connected vehicle (CV) technologies can provide better traffic safety through Surrogate Safety Measure (SSM). CV technologies involves two network systems: traffic network and wireless communication network. We found that the research in the wireless communication network for CV did not interact properly with the research in SSM in transportation network, and vice versa. Though various SSM has been proposed in previous studies, a few of them have been tested in simulation software in limited extent. On the other hand, A large body of researchers proposed various communication architecture for CV …

Development Of Novel Compound Controllers To Reduce Chattering Of Sliding Mode Control, Mehran Rahmani

Theses and Dissertations

The robotics and dynamic systems constantly encountered with disturbances such as micro electro mechanical systems (MEMS) gyroscope under disturbances result in mechanical coupling terms between two axes, friction forces in exoskeleton robot joints, and unmodelled dynamics of robot manipulator. Sliding mode control (SMC) is a robust controller. The main drawback of the sliding mode controller is that it produces high-frequency control signals, which leads to chattering. The research objective is to reduce chattering, improve robustness, and increase trajectory tracking of SMC. In this research, we developed controllers for three different dynamic systems: (i) MEMS, (ii) an Exoskeleton type robot, and …

Application Of Deep Learning For Imaging-Based Stream Gaging, Ryan Lee Vanden Boomen

Theses and Dissertations

In the field of water resources management, one vital instrument utilized is the stream gage. Stream gages monitor and record flow and water height within some water body. The United States Geological Survey maintains a network of stream gages at many locations across the country. Many of these sites are also equipped with webcams monitoring the state of the water body at the moment of measurement. Previous studies have outlined methods to approximate stream gage data remotely with limitations such as the requirement of detailed depth information for each site. This study seeks to create a process for training a …

Numerical And Experimental Investigation Of Aeration Self Mixing By Using Pulsating And Continuous Air Flow, Ahmed Ali Alkhafaji

Theses and Dissertations

Wastewater treatment is considered one of the most common forms of pollution control in the united states. Considered as an integral part of the wastewater treatment, the aeration process is the most energy-consuming process among all the processes that take place in any wastewater treatment plant. According to the United States Environmental Protection Agency (EPA), a wastewater treatment plant is expected to remove at least 85% of the suspended solids and dissolved organic compounds from the wastewater before discharging it to a river or a lake. The normal operation of the aeration process is by compressing air continuously to basin …

Developing Highly Reversible Li Metal Anode With Mossy/Dendritic Li Suppression In High Energy Density Batteries, Xi Chen

Theses and Dissertations

Lithium-ion battery technology has wide impact on our daily life. However, most of the commercial batteries with limited energy density are unable to meet the growing demand of electrical vehicles, portable electronic devices and other energy storage systems. Therefore, the development of new electrode materials with high energy density and reliable performance has become a critical mission for researchers. Particularly replacing graphite anode with Li metal is one of most viable approaches to break the limitation of energy density in batteries. Metallic lithium is one of the most promising anode materials, which has a high theoretical specific capacity of 3860 …

Sustainability In Construction: Using Lean Management Principles To Reduce Waste, Matthew Waite

Theses and Dissertations

The construction industry is facing many challenges. There are growing consumer demands for sustainable building. The construction industry generates a significant portion of the waste going into landfills. The construction industry has failed to keep pace with productivity in the manufacturing industry. Through adoption of Lean management principles, the construction industry can become more sustainable while increasing productivity. The literature was evaluated for three concepts: Lean management principles interaction with sustainability, the current state of sustainability in the construction industry, and the current state of Lean management principles in the construction industry. Lean management philosophies interactions with sustainability has been …

Intelligent Therapeutic Robot: Design, Development, And Control, Asif Al Zubayer Swapnil

Theses and Dissertations

This research contributes to developing an Intelligent Therapeutic Robot (iTbot) designed to provide therapy to patients with upper limb impairment due to stroke, injury, and other trauma. This robot aims to implement robotic rehabilitation based on principles of motor rehabilitation and Neuroplasticity. The iTbot, as developed in this research, can provide end-effector type rehabilitation exercises in various configurations, including motion in the vertical and horizontal plane. It can provide passive, active, and active-assisted rehabilitation therapies to patients with limited upper limb mobility.

The iTbot has been designed with simplicity in mind with a minimum viability approach. With a minimum amount …

Characterization Of Fiber Bragg Grating Based, Geometry-Dependent, Magnetostrictive Composite Sensors, Edward Lynch

Theses and Dissertations

Optical sensors based on geometry dependent magnetostrictive composite, having potential applications in current sensing and magnetic field sensing are modeled and evaluated experimentally with an emphasis on their thermal immunity from thermal disturbances. Two sensor geometries composed of a fiber Bragg grating (FBG) embedded in a shaped Terfenol-D/epoxy composite material, which were previously prototyped and tested for magnetic field response, were investigated. When sensing magnetic fields or currents, the primary function of the magnetostrictive composite geometry is to modulate the magnetic flux such that a magnetostrictive strain gradient is induced on the embedded FBG. Simulations and thermal experiments reveal the …

Detection Of Stealthy False Data Injection Attacks Against State Estimation In Electric Power Grids Using Deep Learning Techniques, Qingyu Ge

Theses and Dissertations

Since communication technologies are being integrated into smart grid, its vulnerability to false data injection is increasing. State estimation is a critical component which is used for monitoring the operation of power grid. However, a tailored attack could circumvent bad data detection of the state estimation, thus disturb the stability of the grid. Such attacks are called stealthy false data injection attacks (FDIAs). This thesis proposed a prediction-based detector using deep learning techniques to detect injected measurements. The proposed detector adopts both Convolutional Neural Networks and Recurrent Neural Networks, making full use of the spatial-temporal correlations in the measurement data. …

Development Of An Advanced Zinc Air Flow Battery System (Phase 2), Jingyu Si

Theses and Dissertations

A zinc-air battery is the promising energy storage technology for large-scale energy storage applications due to its low cost, environmental friendliness, and high energy density. However, the electrically rechargeable zinc−air batteries suffer from poor energy efficiency and cycle life because of critical problems such as passivation, dendrite growth, and hydrogen evolution reaction. The proliferation of zinc−air batteries is limited.

The zinc-air flow battery combines the advantages of both a zinc-air battery and a redox flow battery. This combination permits the zinc-air flow battery to compete with the current leading battery technologies in the marketplace. A rechargeable Zn-air flow battery with …

Reevaluating Order Fulfillment Decisions For E-Tailers Under True Simulated Operating Conditions, Amir H. Kalantari

Theses and Dissertations

This dissertation makes both a methodological and an applied contribution. From a methodological standpoint, this is among the very first works in the literature to explore the concepts of true simulated operating conditions and fully embedded decision-making algorithms. We illustrate the effectiveness of these concepts by applying them to an online retailer (i.e. e-tailer) order fulfillment decision making process.

Online shopping has completely transformed retail markets in recent years. For customers, it provides convenience, visibility and choice, and for retailers it provides market expansion opportunities, operational cost reduction, and many other advantages. There are fundamental differences between the supply chain …

Computational Materials Science And Engineering: Model Development And Case Study, Yihan Xu

Theses and Dissertations

This study presents three tailored models for popular problems in energy storage and biological materials which demonstrate the application of computational materials science in material system development in these fields. The modeling methods can be extended for solving similar practical problems and applications.

In the first application, the thermo-mechanical stress concentrated region in planar sodium sulfur (NaS) cells with large diameter and different container materials has been estimated as well as the shear and normal stresses in these regions have been quantified using finite-element analysis (FEA) computation technique. It is demonstrated that the primary failure mechanism in the planar NaS …