Engineering Commons^™

Fixture Design For Parasitic Capacitances Of Mosfets For Emi Applications, Anfeng Huang, Hanyu Zhang, Li Du, Cheung Wei Lam, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

Due to the fast-switching nature of modern power converters, up to hundreds of MHz of common-mode noise can easily be generated. The characterization of switching components, e.g., Si MOSFETs, is essential for noise reduction. However, limited by the bandwidth of instruments, the voltage-dependent capacitances of high voltage MOSFETs are typically characterized at approximately 1 MHz, which is insufficient for EMI applications. In this paper, the measurement method and the test fixtures are presented. The measurement bandwidth is pushed to 30 MHz and higher, and frequency-dependent capacitances of a MOSFET are observed through measurements.

Generation Expansion Planning Considering Discrete Storage Model And Renewable Energy Uncertainty: A Bi-Interval Optimization Approach, Siyuan Wang, Guangchao Geng, Qy Jiang, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

Both discrete storage model (DSM) and continuous storage model (CSM) have been used in the power system planning literature. In this work, we conduct a sizing-error analysis for the use of CSM in generation expansion planning (GEP), which shows more reasonable storage sizing decisions are offered by the DSM in comparison to the CSM. However, when the DSM is considered in the context of interval optimization, the discrete status variables in mutually exclusive constraints and the strong temporal coupling in state-of-charge (SOC) constraints create significant challenges. To tackle this, a tailored interval optimization approach is proposed to consider both DSM …

I2Mtc 2021 Special Issue In Ieee Transactions On Instrumentation And Measurement, Pawel Niewczas, Kristen M. Donnell, Melanie Ooi

Electrical and Computer Engineering Faculty Research & Creative Works

No abstract provided.

An Energy-Efficient Internet Of Things Relaying System For Delay-Constrained Applications, Abdullah M. Almasoud, Ahmad Alsharoa, Daji Qiao, Ahmed E. Kamal

Electrical and Computer Engineering Faculty Research & Creative Works

The emerging Internet-of-things (IoT) systems contain a large number of small wireless devices with limited energy, communication, and computational capabilities. In such systems, a helping station located between the IoT devices and backhaul servers can be deployed to broadcast the IoT devices to the backhaul networks. This paper investigates a hybrid energy-efficient framework using multiple energy harvested relays with data buffering capabilities. The relays are powered by a hybrid energy supply consisting of a traditional electric grid and renewable energy grid. We propose an energy efficient novel approach aiming to support the wireless uplink transmission from IoT devices to backhaul …

Concurrent Learning-Based Neuro-Adaptive Robust Tracking Control Of Wheeled Mobile Robot: An Event-Triggered Design, Krishanu Nath, Manas Kumar Bera, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, an event-based neuro-adaptive robust tracking controller for a perturbed and networked differential drive mobile robot (DMR) is designed with concurrent learning. A radial basis function neural network, which approximates an unknown perturbation, is used to design an adaptive sliding mode controller (SMC). The RBFNN weights and SMC parameters are estimated online using an adaptive tuning law to ensure performance with reduced chattering. To improve the convergence of RBFNN weight estimation error, a concurrent learning-based adaptive law is derived, which uses measured online and recorded data. Further, a suitable triggering condition is designed to achieve a reduced number …

An Interleaved High Step-Up Dc-Dc Converter With Built-In Transformer-Based Voltage Multiplier For Dc Microgrid Applications, Ramin Rahimi, Saeed Habibi, Mehdi Ferdowsi, Pourya Shamsi

Electrical and Computer Engineering Faculty Research & Creative Works

This paper proposes a high step-up DC-DC converter with a built-in transformer (BIT)-based voltage multiplier (VM) that is suitable for integrating low-voltage renewable energy sources into a DC microgrid. A three-winding BIT is combined with the switched-capacitor (SC) cells to extend the voltage gain and reduce the voltage stress on the switches. The current-falling rates of the diodes are controlled by the leakage inductances of the BIT, alleviating the reverse-recovery problem of the diodes. The operating modes and steady-state analysis are presented. Additionally, the validity of the proposed converter is confirmed by the simulation and experimental results of a 400 …

Identification Of Volatile Organic Liquids By Combining An Array Of Fiber-Optic Sensors And Machine Learning, Wassana Naku, Anand K. Nambisan, Muhammad Roman, Chen Zhu, Rex E. Gerald, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

In This Paper, We Report an Array of Fiber-Optic Sensors based on the Fabry-Perot Interference Principle and Machine Learning-Based Analyses for Identifying Volatile Organic Liquids (VOLs). Three Optical Fiber Tip Sensors with Different Surfaces Were Included in the Array of Sensors to Improve the Accuracy for Identifying Liquids: An Intrinsic (Unmodified) Flat Cleaved End face, a Hydrophobic-Coated End face, and a Hydrophilic-Coated End face. the Time-Transient Responses of Evaporating Droplets from the Optical Fiber Tip Sensors Were Monitored and Collected Following the Controlled Immersion Tests of 11 Different Organic Liquids. a Continuous Wavelet Transform Was Used to Convert the Time-Transient …

Particle Swarm Optimization For Critical Experiment Design, Cole Michael Kostelac

Masters Theses

“Critical experiments are used by nuclear data evaluators and criticality safety engineers to validate nuclear data and computational methods. Many of these experiments are designed to maximize the sensitivity to a certain nuclide-reaction pair in an energy range of interest. Traditionally, a parameter sweep is conducted over a set of experimental variables to find a configuration that is critical and maximally sensitive. As additional variables are added, the total number of configurations increases exponentially and quickly becomes prohibitively computationally expensive to calculate, especially using Monte Carlo methods.

This work presents the development of a particle swarm optimization algorithm to design …

Automatic Sparse Esm Scan Using Gaussian Process Regression, Jiangshuai Li

Masters Theses

“Emission source microscopy (ESM) technique can be utilized for localization of electromagnetic interference sources in complex and large systems. In this work a Gaussian process regression (GPR) method is applied in real-time to select sampling points for the sparse ESM imaging using a motorized scanner. The Gaussian process regression is used to estimate the complex amplitude of the scanned field and its uncertainty allowing to select the most relevant areas for scanning. Compared with the randomly selected samples the proposed method allows to reduce the number of samples needed to achieve a certain dynamic range of the image, reducing the …

Guiding A Human Follower With Interaction Forces: Implications On Physical Human-Robot Interaction, George L. Holmes, Keyri Moreno Bonnett, Amy Costa, Devin Michael Burns, Yun Seong Song

Psychological Science Faculty Research & Creative Works

This work challenges the common assumption in physical human-robot interaction (pHRI) that the movement intention of a human user can be simply modeled with dynamic equations relating forces to movements, regardless of the user. Studies in physical human-human interaction (pHHI) suggest that interaction forces carry sophisticated information that reveals motor skills and roles in the partnership and even promotes adaptation and motor learning. In this view, simple force-displacement equations often used in pHRI studies may not be sufficient. To test this, this work measured and analyzed the interaction forces (F) between two humans as the leader guided the blindfolded follower …

Pulsed-Active Microwave Thermography, Logan M. Wilcox, Mathias Bonmarin, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Active microwave thermography (AMT) is a thermographic nondestructive testing and evaluation technique that utilizes an electromagnetic-based excitation with a subsequent infrared measurement of the surface thermal profile of the material or structure of interest. AMT has been successfully applied to several aerospace and civil infrastructure applications. This work seeks to expand the performance of AMT by incorporating a signal processing technique common to traditional (flash-lamp) thermography, referred to as pulsed thermography (PT). PT operates on the premise of a pulsed excitation, as opposed to a constant or step excitation (ST) over a given time-period that is typical to traditional active …

Self-Vernier Effect-Assisted Optical Fiber Sensor Based On Microwave Photonics And Its Machine Learning Analysis, Chen Zhu, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Optical Vernier Effect Has Been Recently Demonstrated as a Tool to Enhance the Sensitivity of Optical Fiber Interferometric Sensors and Has Become a Hot Topic in the Last Few Years. the Generation of the Vernier Effect Relies on the Superposition of Interferograms of Two Interferometers (A Sensing One and a Reference One) with Marginally Different Optical Path Differences (OPDs), Where an Amplitude Modulation-Like Signal is Sustained in the Output Spectrum. the Vernier Modulation Envelope Exhibits Significantly Magnified Sensitivity in Response to External Perturbations, compared to the Individual Sensing Interferometer, Providing a New Route to New Generations of Ultra-Sensitive Optical Fiber …

Neural Network Attitude Control System Design For The Wallops Arc-Second Pointer, Pavel Galchenko, Henry J. Pernicka

Mechanical and Aerospace Engineering Faculty Research & Creative Works

No abstract provided.

Bulk Nanostructured Steels For Nuclear Reactor And Extreme Environment Applications, Maalavan Arivu

Doctoral Dissertations

"Candidate accident tolerant FeCrAl fuel (ATF) claddings for light water reactors (LWRs) need to be thinner than current Zircaloys owing to higher neutronic penalty, demanding an improvement in strength. Therefore, equal channel angular pressing (ECAP), and high-pressure torsion (HPT) were used to produce bulk ultra-fine grained and nanocrystalline Kanthal-D [KD; Fe-21Cr-5Al-0.026C (wt.%) alloy] which resulted in an improvement in strength of up to 3 times their nominal strength from grain boundary strengthening, and dislocation strengthening. Dynamic recovery was promoted due to ECAP at 520 oC rendering it with a large area fraction of less mobile low angle grain boundaries (LAGBs) …

A Three-Dimensional Fully Coupled Hydro-Mechanical Elasto-Plastic Model For Unsaturated Soils With Consideration Of Hysteresis Behavior, Beshoy Sami Moussa Riad

Doctoral Dissertations

"Unsaturated soils are often used as a construction material in transportation infrastructures; in which it is subjected to cyclic traffic loadings and/or seasonal wetting-drying cycles. While mechanical hysteresis is a common feature of soils in general, hydraulic hysteresis is associated with unsaturated soils. Most existing constitutive models paid limited attention to the mechanical and hydraulic hysteresis behavior of unsaturated soils. This research presents a three-dimensional model for unsaturated soils and a chemo mechanical model for saturated soils. The unsaturated soils’ model has the following characteristic features: (a) the hydraulic and mechanical behaviors are fully coupled under 3D conditions; (b) it …

Corrosion Resistance Performance Investigation Of Mild Steel Bar Coated With Magnesium Phosphate Cement Paste, Fan Zhang

Doctoral Dissertations

"In this research study, the anti-corrosion mechanism of reinforcement embedded in magnesium potassium phosphate cement (MKPC) is explored. In addition, one type of additives, metakaolin, and one type of retarder, boric acid, are employed in MKPC to modify its properties in order to further investigate corrosion resistance and to achieve mass-production coating reinforcement at the work site. This coating method may be practical for some underwater construction and some traditional reinforcement concrete structures to reduce the reinforcement corrosion rate and to eventually extend service life in both repair and new construction applications.

By comparing the electrochemical properties of bare ribbed …

Signal Integrity Analysis And Electromagnetic Inteference Modeling For Autonomous Vehicles, Yuandong Guo

Doctoral Dissertations

"An autonomous vehicle (AV) may employ various sensors to detect the environment, and the hardware for self-driving should be able to process large volume of sensor data and make real-time decisions. For signal integrity (SI), both the bandwidths and data rates of the high-speed channels should meet the requirements. The electromagnetic interference (EMI) noise may become a major concern with the ever-increasing number of electric modules. This research focuses on both SI analysis and EMI modeling for AVs. The first topic is accurate and broadband three-phase motor modeling. The novel modeling methodology for a typical three-phase motor is presented, using …

Computational Fluid Dynamics Techniques For Multiphase Flow Systems, Jose Sebastian Uribe Lopez

Doctoral Dissertations

"Mathematical modelling of multiphase flow systems has been a major and persistent challenge over the last decades. Vast attempts to obtain predictive models can be found reported in literature, where major advances can be recognized in recent years, paired to enhancements in computer science and engineering. Notwithstanding, universally valid models with a mechanistic development are far from being achieved. The current status of modelling any multiphase flow system relies on the model order reduction of purely theoretical models. Such reductions and simplifications become the source of deviations in the predictions of the experimentally measured parameters and will constrain the applicability …

Novel Ferromagnetic Materials With Improved Mechanical Performance, Wesley Alexander Everhart

Doctoral Dissertations

"The ductility of intermetallics has long been a hindrance to their broad adaptation despite a significant range of properties such as magnetic, half-metallic, and shape memory behavior. The lack of a general theory for the ductility of intermetallics along with the lack of prior art that experimentally measured mechanical properties drives the need for significant investment in many of these novel magnetic materials in order to even understand, let alone correct, poor ductility.

This dissertation includes work that explored the effect of vanadium content and quenching rate on the microstructure and ductility of Fe-Co alloys. Results indicated that a martensitic …

Multifunctional Behaviors Of Two-Dimensional Materials And Their Composites, Yanxiao Li

Doctoral Dissertations

"Two-dimensional (2D) materials, including graphene, transition metal carbides or nitrides (TMC/Ns), have rich surface chemistry, superb electrical and mechanical properties. These unique properties make them ideal for multifunctional devices. Among them, we focused on graphene and TMC/Ns (i.e., MXenes), as well as their composites. Unlike the well-known graphene, MXenes, are relatively new and typically synthesized by the selective etching of the “A” layers from the layered carbides and /or nitrides known as MAX phases, which introduce MXenes with rich terminal groups (e.g. -O-, -OH, -F).

During my Ph.D. study, firstly, the adhesive and frictional behaviors, which are related to successful …

Influences Of The Internal Residual On Combustion Instabilities In The Misfire And Partial Burn Regimes Of A Dilute Spark-Ignition Engine, Rachel Inez Stiffler

Doctoral Dissertations

"Dilution in spark-ignition (SI) engines can improve fuel consumption and reduce emissions; however, increased levels of dilution either from excess oxidizer or exhaust gas recirculation (EGR) causes combustion to become more strained and cycle-to-cycle variations increase. At high levels of dilution incomplete combustion events (i.e. misfires and partial burns) start to occur, which cause combustion instabilities and eventually a dilute limit is reached. It is known the combustion instabilities seen are primarily due to the feed-forward mechanism present in the residual gases, but it is still unknown what about the residual is influencing the dynamics under high levels of dilution …

Theoretical And Experimental Application Of Neural Networks In Spaceflight Control Systems, Pavel Galchenko

Doctoral Dissertations

“Spaceflight systems can enable advanced mission concepts that can help expand our understanding of the universe. To achieve the objectives of these missions, spaceflight systems typically leverage guidance and control systems to maintain some desired path and/or orientation of their scientific instrumentation. A deep understanding of the natural dynamics of the environment in which these spaceflight systems operate is required to design control systems capable of achieving the desired scientific objectives. However, mitigating strategies are critically important when these dynamics are unknown or poorly understood and/or modelled. This research introduces two neural network methodologies to control the translation and rotation …

A Variable Node Optimization Model For Byzantine Fault Tolerant Systems, Ian Robert Fulton

Masters Theses

“Byzantine Fault Tolerance (BFT) has been a major subject of study over the last two decades with increasing societal dependance on secure, correct, and reliable computer systems and online services. This research presents a model for high-level optimization of emerging systems that rely on these BFT algorithms and use a variable numbers of decision nodes. The model highlights the relationship between the security of a system and its efficiency. Two experiments were performed to determine system performance by varying the number of compromised nodes, decision nodes, and total nodes. They examine the probability that a transaction will be compromised based …

State Level Trends In Renewable Energy Procurement Via Solar Installation Versus Green Electricity, Eric Michael Hanson

Masters Theses

“In the past 5 years, consumer options for procuring renewable energy have increased, ranging from rooftop solar installation to utility green pricing to Community Choice Aggregation. These options vary in terms of costs and benefits to the consumer as well as grid integration implications. However, little is known regarding how the presence of a wide range of options for utility-scale renewable procurement affects demand for distributed residential solar installations. In theory, there are three possible relationships, (1) positive correlation, where utility-scale and distributed resources complement each other to increase overall production, (2) negative correlation, where utility-scale and distributed resources are …

Zinc Plating From Alkaline Non-Cyanide Bath, Abdul J. Mohammed

Masters Theses

“Alkaline non-cyanide zinc plating baths are preferred when trying to avoid the toxicity of cyanide baths or corrosivity of acid baths. Without additives, alkaline zincate baths produce powdery non-adherent deposits which have no use in commercial plating. Additives must be added at optimum concentrations to produce adherent, bright and uniform zinc deposits. In this study electrochemical tests were used to determine effects of additives on cathodic polarization, throwing power and morphology of deposits. Current density distribution in a unique bath of 37.5 g L^-1 Zn and 210 g L^-1 NaOH was modelled using COMSOL and validated two plating …

Study Of Contamination Resulting From Historical Mining Within The Old Lead Belt: Mineral Fork Watershed, 2021-2022, Tessa Nicole Mortensen

Masters Theses

“The Old Lead Belt in Missouri has been mined extensively over the past two hundred years, and with historical mining practices often not meeting modern environmental protection standards many areas have significant soil and water contamination as a result. This study focuses on the Mineral Fork River’s watershed in Washington County, Missouri, which includes portions of four separate Superfund sites. In this study, we exam the impact of historical mining on the health of alluvial systems, as evaluated by lead, zinc, and barium (barite) concentrations in the suspended and sediments within tributaries of the Mineral Fork River system. To relate …

Characterization Of Cermet Fuel For Nuclear Thermal Propulsion (Ntp), James Floyd Mudd

Masters Theses

“A manned flight to Mars is met with many technical challenges, not the least of which is the development of propulsion technology capable of moving a transit vehicle from Earth orbit to Mars orbit. NASA is investigating Nuclear Thermal Propulsion (NTP) as a way of reducing flight time and providing the option for a mid-mission abort. NTP, which uses a high temperature nuclear reactor to heat a propellant, requires advanced fuel materials capable of withstanding temperatures well in excess of 2000 K. Among the fuel options are ceramic metal (cermet) composites composed of refractory metals and Ultra-High Temperature Ceramics (UHTCs). …

Industry 4.0 Remanufacturing: A Novel Approach Towards Smart Remanufacturing, Prashansa Ragampeta

Masters Theses

“Smart remanufacturing has become more popular in recent years as a result of its multiple benefits and the growing need for society to encourage a circular economy that leads to sustainability. One of the most common end-of-life (EoL) choices that can lead to a circular economy is remanufacturing. As a result, at the end-of-life stage of a product, it is critical to prioritize this choice over other accessible options because it is the only recovery option that retains the same quality as a new product. This work focuses on the numerous technologies that can aid in the improvement of smart …

A Convolutional Neural Network (Cnn) For Defect Detection Of Additively Manufactured Parts, Musarrat Farzana Rahman

Masters Theses

“Additive manufacturing (AM) is a layer-by-layer deposition process to fabricate parts with complex geometries. The formation of defects within AM components is a major concern for critical structural and cyclic loading applications. Understanding the mechanisms of defect formation and identifying the defects play an important role in improving the product lifecycle. The convolutional neural network (CNN) has been demonstrated to be an effective deep learning tool for automated detection of defects for both conventional and AM processes. A network with optimized parameters including proper data processing and sampling can improve the performance of the architecture. In this study, for the …

Optimization And Modeling Of Esd Protection Devices, Li Shen

Masters Theses

“Transient voltage suppressors (TVS) are used to protect ICs (integrated circuits) against overvoltage, ESD (Electrostatic Discharge), inductive load switching, and even lightning strikes. In this research, a transient behavior model framework for ESD protection devices is used for modelling four different types of TVS (non-snapback, snapback, spark gap like device and varistor). The System-Efficient ESD Design (SEED) methodology is utilized to strengthen the trust in the model framework by efficient simulation of ESD interaction of the off-chip ESD protection devices with the IC ESD protection device and associated measurement data.

Improvements in the TVS transient response, accounting for conductivity modulation, …