Engineering Commons^™

Transient Response Of Esd Protection Devices For A High-Speed I/O Interface, Jianchi Zhou, Yang Xu, Sergej Bub, Steffen Holland, Javad Soleiman Meiguni, David Pommerenke, Daryl G. Beetner

Electrical and Computer Engineering Faculty Research & Creative Works

System-efficient electrostatic discharge (ESD) design (SEED) models of a diode and transient voltage suppressor (TVS) were developed to study their transient response in a high-speed input/output interface. Previously reported SEED models were improved to strengthen their convergence stability and facilitate accurate predictions over a wide range of conditions. These improvements were required to accurately capture the race conditions between the TVS and on-chip diode, where the diode's turn on may prevent turn on of the TVS. Simulations and measurements were performed to demonstrate the impact of the ESD pulse's rise time on race conditions. During a race, results showed the …

Towards A Low-Cost Solution For Gait Analysis Using Millimeter Wave Sensor And Machine Learning, Mubarak A. Alanazi, Abdullah K. Alhazmi, Osama Alsattam, Kara Gnau, Meghan Brown, Shannon Thiel, Kurt Jackson, Vamsy P. Chodavarapu

Electrical and Computer Engineering Faculty Publications

Human Activity Recognition (HAR) that includes gait analysis may be useful for various rehabilitation and telemonitoring applications. Current gait analysis methods, such as wearables or cameras, have privacy and operational constraints, especially when used with older adults. Millimeter-Wave (MMW) radar is a promising solution for gait applications because of its low-cost, better privacy, and resilience to ambient light and climate conditions. This paper presents a novel human gait analysis method that combines the micro-Doppler spectrogram and skeletal pose estimation using MMW radar for HAR. In our approach, we used the Texas Instruments IWR6843ISK-ODS MMW radar to obtain the micro-Doppler spectrogram …

Development Of Smart Wearable Sensory Systems On Flexible And Fabric Platforms For Health Monitoring Applications, Simin Masihi

Dissertations

Wearable sensing technology has recently received an increased attention in both research and commercialization phases and has moved from a vision of science fiction to reality with a wide variety of applications. This incredible growth can be attributed to several factors, such as affordability and ergonomics provided by advances in flexible electronics. The other factors that realized wearable sensing technology include a critical need for more accessible health care services experienced during the recent COVID pandemic, integration to the Internet of Things (IoT), and a growing consumer desire for health awareness. This dissertation presents the fulfillment of three main projects …

Peridynamic Modeling Of Crack Propagation In Brittle Materials With Electromechanical Coupling, Semsi Coskun

Dissertations

The bond-based peridynamics (BB-PD) is a widely used peridynamic model in the literature. Despite Poisson's ratio restriction, it still serves as a powerful tool to solve challenging engineering problems with a relatively cheap computational cost. Consider the Poisson ratio of the material does not deviate from the ones that BB-PD can model. In that case, it becomes advantageous to use the BB-PD compared to other PD models in terms of computational cost and simplicity. However, the BB-PD suffers from the so-called surface or skin effect where the material response at boundaries becomes softer than the bulk material points. As a …

Multi-Technique Characterization Of Superconducting Materials For Particle Accelerator Applications, Junki Makita

Physics Theses & Dissertations

We investigated the performance limitations of superconducting radio-frequency (SRF) cavities and materials using multiple experimental techniques. In particular, this study focuses on understanding the surface properties of nitrogen-doped Nb cavities and superconducting thin films with higher T_c such as Nb₃Sn. The main goal of this work is to use different techniques to better understand each aspect of the complex loss mechanism in superconductors to further improve the already highly efficient SRF cavities.

Nitrogen doping applied to a Nb SRF cavity significantly improves the quality factor Q₀ compared to a conventional Nb cavity, at an expense of …

Design, Synthesis And Characterization Of Triazole Based Glycoconjugates And 4,6-Acetal Protected D-Glucosamine Derivatives As Low Molecular Weight Gelators, Pooja Sharma

Chemistry & Biochemistry Theses & Dissertations

Low molecular weight gelators (LMWGs) are small molecules that can form gels in either organic solvents or water in their pure form or as mixtures. LMWGs self-assemble through noncovalent interactions such as hydrogen bonding, halogen bonding, van der Waals interactions and hydrophobic forces in solvents. They have shown great potential in biomedical industry, catalysis and environmental remediation to name a few. Moreover, the formation of metallogels can be used for detection of various ions as well as catalysis, which adds a new dimension to their applications. Among many classes of LMWGs based on the type of functional groups used, carbohydrate …

Cyber Deception For Critical Infrastructure Resiliency, Md Ali Reza Al Amin

Computational Modeling & Simulation Engineering Theses & Dissertations

The high connectivity of modern cyber networks and devices has brought many improvements to the functionality and efficiency of networked systems. Unfortunately, these benefits have come with many new entry points for attackers, making systems much more vulnerable to intrusions. Thus, it is critically important to protect cyber infrastructure against cyber attacks. The static nature of cyber infrastructure leads to adversaries performing reconnaissance activities and identifying potential threats. Threats related to software vulnerabilities can be mitigated upon discovering a vulnerability and-, developing and releasing a patch to remove the vulnerability. Unfortunately, the period between discovering a vulnerability and applying a …

Evaluation Of Generative Models For Predicting Microstructure Geometries In Laser Powder Bed Fusion Additive Manufacturing, Andy Ramlatchan

Computer Science Theses & Dissertations

In-situ process monitoring for metals additive manufacturing is paramount to the successful build of an object for application in extreme or high stress environments. In selective laser melting additive manufacturing, the process by which a laser melts metal powder during the build will dictate the internal microstructure of that object once the metal cools and solidifies. The difficulty lies in that obtaining enough variety of data to quantify the internal microstructures for the evaluation of its physical properties is problematic, as the laser passes at high speeds over powder grains at a micrometer scale. Imaging the process in-situ is complex …

Utilization Of Finite Element Analysis Techniques For Adolescent Idiopathic Scoliosis Surgical Planning, Michael A. Polanco

Mechanical & Aerospace Engineering Theses & Dissertations

Adolescent Idiopathic Scoliosis, a three-dimensional deformity of the thoracolumbar spine, affects approximately 1-3% of patients ages 10-18. Surgical correction and treatment of the spinal column is a costly and high-risk task that is consistently complicated by factors such as patient-specific spinal deformities, curve flexibility, and surgeon experience. The following dissertation utilizes finite element analysis to develop a cost-effective, building-block approach by which surgical procedures and kinematic evaluations may be investigated. All studies conducted are based off a volumetric, thoracolumbar finite element (FE) model developed from computer-aided design (CAD) anatomy whose components are kinematically validated with in-vitro data. Spinal ligament stiffness …

Applied Deep Learning: Case Studies In Computer Vision And Natural Language Processing, Md Reshad Ul Hoque

Electrical & Computer Engineering Theses & Dissertations

Deep learning has proved to be successful for many computer vision and natural language processing applications. In this dissertation, three studies have been conducted to show the efficacy of deep learning models for computer vision and natural language processing. In the first study, an efficient deep learning model was proposed for seagrass scar detection in multispectral images which produced robust, accurate scars mappings. In the second study, an arithmetic deep learning model was developed to fuse multi-spectral images collected at different times with different resolutions to generate high-resolution images for downstream tasks including change detection, object detection, and land cover …

Development Of High Quantum Efficiency Strained Superlattice Spin Polarized Photocathodes Via Metal Organic Chemical Vapor Deposition, Benjamin Belfore

Electrical & Computer Engineering Theses & Dissertations

Spin polarized photocathodes are necessary to examine parity violations and other fundamental phenomena in the field of high energy physics. To create these devices, expensive and complicated growth processes are necessary. While integral to accelerator physics, spin polarized electrons could have other exciting applications in materials science and other fields of physics. In order to explore these other applications feasibly, the relative supply of spin polarized photocathodes with a high rate of both polarization and photoemission needs to be increased. One such way to increase this supply is to develop the means to grow them faster and at a larger …

A Quality Systems Economic-Risk Design Theoretical Framework, Abdallah S. Thefeid

Engineering Management & Systems Engineering Theses & Dissertations

Quality systems, including control charts theory and sampling plans, have become essential tools to develop business processes. Since 1928, research has been conducted in developing the economic-risk designs for specific types of control charts or sampling plans. However, there has been no theoretical or applied research attempts to combine these related theories into a synthesized theoretical framework of quality systems economic-risk design. This research proposes to develop a theoretical framework of quality systems economic-risk design from qualitative research synthesis of the economic-risk design of sampling plan models and control charts models. This theoretical framework will be useful in guiding future …

Emotion Detection Using An Ensemble Model Trained With Physiological Signals And Inferred Arousal-Valence States, Matthew Nathanael Gray

Electrical & Computer Engineering Theses & Dissertations

Affective computing is an exciting and transformative field that is gaining in popularity among psychologists, statisticians, and computer scientists. The ability of a machine to infer human emotion and mood, i.e. affective states, has the potential to greatly improve human-machine interaction in our increasingly digital world. In this work, an ensemble model methodology for detecting human emotions across multiple subjects is outlined. The Continuously Annotated Signals of Emotion (CASE) dataset, which is a dataset of physiological signals labeled with discrete emotions from video stimuli as well as subject-reported continuous emotions, arousal and valence, from the circumplex model, is used for …

Collaborative Robotics Strategies For Handling Non-Repetitive Micro-Drilling Tasks Characterized By Low Structural Mechanical Impedance, Xiangyu Wang

Mechanical & Aerospace Engineering Theses & Dissertations

Mechanical micro-drilling finds widespread use in diverse applications ranging from advanced manufacturing to medical surgery. This dissertation aims to develop techniques that allow programming of robots to perform effective micro-drilling tasks. Accomplishing this goal is faced with several challenges. Micro-drills suffer from frequent breakage caused from variations in drill process parameters. Micro-drilling tasks afford extremely low feed rates and almost zero tolerance for any feed rate variations. The accompanying robot programming task is made difficult as mathematical models that capture the micro-drilling process complexities and sensitive variations in micro-drill parameters are highly difficult to obtain. Therefore, an experimental approach is …

The Relationship Between Cerebrovascular Reactivity And Cerebral Oxygenation During Hemodialysis, W. T. Richerson, Brian D. Schmit, D. F. Wolfgram

Biomedical Engineering Faculty Research and Publications

Significance Statement

Patients with ESKD have a high burden of ischemic brain lesions related to decline in cerebral blood flow during hemodialysis. Preliminary studies in patients on hemodialysis noted impairment in cerebrovascular reactivity, a mechanism that regulates cerebral perfusion. We found that lower cerebrovascular reactivity was associated with greater decrease in cerebral oxygen saturation during hemodialysis, particularly when accounting for changes in systemic BP. These results suggest that testing cerebrovascular reactivity could be relevant to characterizing risk of cerebral ischemia during hemodialysis and the potential sequelae of brain injury and cognitive impairment over time.

Background

Patients with kidney failure treated …

Fluorescein Clearance Kinetics In Blood And Bile Indicates Hepatic Ischemia-Reperfusion Injury In Rats, Joohyun Kim, Yongquiang Yang, Seung-Keun Hong, Jacek Zielonka, Ranjan K. Dash, Said H. Audi, Suresh N. Kumar, Amit Joshi, Michael W. Zimmerman, Johnny C. Hong

Biomedical Engineering Faculty Research and Publications

Quantitative measurement of the degree of hepatic ischemia-reperfusion injury (IRI) is crucial for developing therapeutic strategies for its treatment. We hypothesized that clearance of fluorescent dye through bile metabolism may reflect the degree of hepatic IRI. In this study, we investigated sodium fluorescein clearance kinetics in blood and bile for quantifying the degree of hepatic IRI. Warm ischemia times (WITs) of 0, 30, or 60 min followed by 1 h or 4 h of reperfusion, were applied to the median and lateral lobes of the liver in Sprague-Dawley rats. Subsequently, 2 mg/kg of sodium fluorescein was injected intravenously, and blood …

A Comparison Of Uniaxial Compressive Response And Inelastic Deformation Mechanisms In Freeze Cast Alumina-Epoxy Composites Without And With Rigid Confinement, Tareq Aljuhari

Mechanical & Aerospace Engineering Theses & Dissertations

Cellular ceramics have an array of improved mechanical properties that make them incredibly desired for different applications such as armor systems, aircraft structures, automobiles bumpers, and biomedical implants. It is also desirable that porous architecture could be shaped into bulk complicated shapes and easy to scale-up with low manufacturing cost. Despite several efficient techniques to fabricate cellular ceramics, some limitations are preventing us from meeting the high demand of the after mentioned applications. For that, freeze casting, also called ice-templating, is technique of solidifying an aqueous ceramic suspension under the effect of unidirectional temperature gradient. In this study, Ice-templated porous …

Engineering Of Ideal Systems For The Study And Direction Of Stem Cell Asymmetrical Division And Fate Determination, Martina Zamponi

Biomedical Engineering Theses & Dissertations

The cellular microenvironment varies significantly across tissues, and it is constituted by both resident cells and the macromolecules they are exposed to. Cues that the cells receive from the microenvironment, as well as the signaling transmitted to it, affect their physiology and behavior. This notion is valid in the context of stem cells, which are susceptible to biochemical and biomechanical signaling exchanged with the microenvironment, and which plays a fundamental role in establishing fate determination and cell differentiation events. The definition of the molecular mechanisms that drive stem cell asymmetrical division, and how these are modulated by microenvironmental signaling, is …

Challenges Of Modeling Rainfall Triggered Landslides In A Data-Sparse Region: A Case Study From The Western Ghats, India, C. L. Vishnu, T. Oommen, Snehamoy Chatterjee, K. S. Sajinkumar

Michigan Tech Publications, Part 1

Accurate rainfall estimates are required to forecast the spatio-temporal distribution of rain-triggered landslides. In this study, a comparison between rain gauge and satellite rainfall data for assessing landslide distribution in a data-sparse region, the mountainous district of Idukki, along the Western Ghats of southwestern India, is carried out. Global Precipitation Mission Integrated Multi-satellitE Retrievals for GPM-Late (GPM IMERG-L) rainfall products were compared with rain gauge measurements, and it was found that the satellite rainfall observations were underpredicting the actual rainfall. A conditional merging algorithm was applied to develop a product that combines the accuracy of rain gauges and the spatial …

Superhard Single-Phase (Ti,Cr)B2 Ceramics, Lun Feng, William Fahrenholtz, Gregory E. Hilmas, Laura Silvestroni

Materials Science and Engineering Faculty Research & Creative Works

A nominally pure and dense (Ti0.9Cr0.1)B2 ceramic was produced by spark plasma sintering of powders synthesized by boro/carbothermal reduction of oxides. The synthesized powders were a single phase and had an average particle of 0.4 ± 0.1 μm and an oxygen content of 1.2 wt%. Average Vickers hardness values of the resulting ceramics increased from 25.9 ± 0.8 GPa at a load of 9.81 N, to 46.3 ± 0.8 GPa at a load of 0.49 N. Compared to the nominally pure TiB2 ceramic obtained under the same processing conditions, the (Ti0.9Cr0.1)B2 ceramic had higher values under the same load due …

Modeling, Estimation, And Optimal Control Of Lithium-Ion Battery At Cell And System Level, Hamidreza Mirzaei

All Dissertations

Lithium-ion batteries (LIBs) have been regarded as a crucial technology for electrifying a variety of applications, ranging from powering computers, phones, and hybrid electric vehicles (HEVs) to being a critical part of the modern centralized and distributed power grids. Battery systems performance is governed by embedded battery management systems (BMSs). The BMS includes battery state estimation algorithms and control rules, and it acts as the brain of battery-powered systems. The purpose of this research is to address unresolved difficulties associated with control algorithms in BMSs at all levels, from single battery cells to battery packs in hybrid electric vehicles (HEVs).\\ …

Design And Operations Of A New Facility In A Next Generation Logistic System Based On Horizontal Collaboration, Dilhani Marasinghe

All Dissertations

The growing amount of freight combined with systemic inefficiencies are stressing current logistic systems. Including horizontal collaboration in the future could provide significant help but this strategy will require several new types of facilities. The most flexible type of horizontal collaboration, however, required freight routing decisions to be made dynamically, in real time, and based on last minute information. This research explores one new facility type operating in this environment that handles a high throughput of pallets or pallet-like containers. A key design feature is how much storage these facilities should have to better coordinate outbound loads. The approach taken …

Evaluation Of Fresh And Hardened Properties Of 3d-Printed Engineered Cementitious Composites (Ecc) Designed For Sustainable And Resilient Infrastructure Systems, Maryam Hojati, Muhammad Saeed Zafar, Amir Bakhshi

Data

3D concrete printing is a cutting-edge construction technique that has the potential to revolutionize the construction industry due to cost-saving in terms of labor and formwork costs, efficiency in construction, lower safety-related risks, and a higher degree of automation. However, several issues still make its adoption relatively slower on a large scale. Engineered cementitious composites (ECC), a class of ultra-high-strength concrete, can be a potential solution to some problems, such as reinforcement and durability. The preliminary phase of a Tran SET project focused on the design of 3D printable ECC, considering the concrete mix design proportions and their potential effects …

Evaluation Of Fresh And Hardened Properties Of 3d-Printed Engineered Cementitious Composites (Ecc) Designed For Sustainable And Resilient Infrastructure Systems, Maryam Hojati, Muhammad Saeed Zafar, Amir Bakhshi

Publications

3D concrete printing is a cutting-edge construction technique that has the potential to revolutionize the construction industry due to cost-saving in terms of labor and formwork costs, efficiency in construction, lower safety-related risks, and a higher degree of automation. However, several issues still make its adoption relatively slower on a large scale. Engineered cementitious composites (ECC), a class of ultra-high-strength concrete, can be a potential solution to some problems, such as reinforcement and durability. The preliminary phase of a Tran SET project focused on the design of 3D printable ECC, considering the concrete mix design proportions and their potential effects …

Alternative Supplementary Cementitious Materials In Ultra-High Performance Concrete, Craig Newtson, Seyedsaleh Mousavinezhad, Gregory J, Gonzales, William K. Toledo, Judit M. Garcia

Data

Ultra-high performance concrete (UHPC) is an emerging material with remarkable mechanical and durability properties that contains large amounts of cementitious materials. Silica fume is a main supplementary cementitious material (SCM) in UHPC, however, it is more expensive than cement and other SCMs, so it is often substituted with inexpensive class F fly ash. Unfortunately, future availability of fly ash is uncertain as the energy industry moves toward renewable energy. Fly ash shortages create an urgent need to find cost-effective and environmentally-friendly alternatives for fly ash. This study investigated replacing cement, fly ash, and silica fume in UHPC mixtures with ground …

Effectiveness Assessment Of E-Ticketing Technology In Construction Of Transportation Projects, Sharareh Kermanshachi, Karthik Subramanya

Data

The construction of highway infrastructure has devoted significant resources towards e-Construction to reduce the paperwork and automate the tasks in daily operations. Electronic Ticketing (e-Ticketing) is one such component of e-Construction that aids in the digital transfer of material tickets such as asphalt and concrete which accounts for more than fifty per cent of construction costs. Despite the benefits of e-Ticketing, many state departments and agencies are unwilling to transition into this technology. No studies have identified the cause of the delay in the implementation process, developed a framework to comprehend the platform's full potential, quantified savings, and suggested strategies …

Development Of A Machine Learning-Based Model To Determine The Optimum And Safe Restriping Timing Of Thermoplastic Pavement Markings In Hot And Humid Climates, Momen R. Mousa, Marwa Hassan

Publications

Due to limited budget, most transportation agencies restripe their thermoplastic pavement markings based on a fixed schedule or based on visual inspection instead of monitoring the retroreflectivity and restriping when the retroreflectivity drops below a pre-determined threshold. These strategies are questionable in terms of efficiency and economy. Therefore, previous studies proposed degradation models to predict the retroreflectivity of thermoplastic markings based on key variables. Yet, most of these studies reported low R² (as low as 0.1), which placed little confidence in these models. Therefore, the objective of this study was to evaluate and predict the field performance of thermoplastics …

Development Of A Machine Learning-Based Model To Determine The Optimum And Safe Restriping Timing Of Thermoplastic Pavement Markings In Hot And Humid Climates, Momen R. Mousa, Marwa Hassan

Data

Due to limited budget, most transportation agencies restripe their thermoplastic pavement markings based on a fixed schedule or based on visual inspection instead of monitoring the retroreflectivity and restriping when the retroreflectivity drops below a pre-determined threshold. These strategies are questionable in terms of efficiency and economy. Therefore, previous studies proposed degradation models to predict the retroreflectivity of thermoplastic markings based on key variables. Yet, most of these studies reported low R² (as low as 0.1), which placed little confidence in these models. Therefore, the objective of this study was to evaluate and predict the field performance of thermoplastics …

Alternative Supplementary Cementitious Materials In Ultra-High Performance Concrete, Craig Newtson, Seyedsaleh Mousavinezhad, Gregory J. Gonzales, William K. Toledo, Judit M. Garcia

Publications

Ultra-high performance concrete (UHPC) is an emerging material with remarkable mechanical and durability properties that contains large amounts of cementitious materials. Silica fume is a main supplementary cementitious material (SCM) in UHPC, however, it is more expensive than cement and other SCMs, so it is often substituted with inexpensive class F fly ash. Unfortunately, future availability of fly ash is uncertain as the energy industry moves toward renewable energy. Fly ash shortages create an urgent need to find cost-effective and environmentally-friendly alternatives for fly ash. This study investigated replacing cement, fly ash, and silica fume in UHPC mixtures with ground …

A Deep Learning Tool For The Assessment Of Pavement Smoothness And Aggregate Segregation During Construction, Mostafa Elseifi, Ramchandra Paudel, Md Tanvir Ahmed Sarkar, Hossam Abohamer, Nirmal Dhakal

Data

Pavement construction monitoring and quality assurance (QA) practices are mostly based on costly, discrete, and destructive methods. Most quality assurance programs are based on pavement construction procedures encompassing in-situ coring for layer thickness determination, density measurements, laboratory testing to measure volumetric properties, and smoothness measurements in case of the availability of a profiler. The main objective of this study was to develop a machine learning-based classifier for predicting pavement roughness and aggregate segregation based on digital image analysis, image recognition, and deep learning machine models. The developed Convolution Neural Networks (CNN) models were trained, tested, and validated using 600-pavement surface …