Electrical and Computer Engineering Commons^™

Calving As A Source Of Acute And Persistent Kinetic Energy To Enhance Submarine Melting Of Tidewater Glaciers, M. F. Shaya, J. D. Nash, E. C. Pettit, J. M. Amundson, R. H. Jackson, D. A. Sutherland, Dylan Winters

Electrical and Computer Engineering Faculty Publications and Presentations

Calving icebergs at tidewater glaciers release large amounts of potential energy. This energy—in principle—could be a source for submarine melting, which scales with near‐terminus water temperature and velocity. Because near‐terminus currents are challenging to observe or predict, submarine melt remains a key uncertainty in projecting tidewater glacier retreat and sea level rise. Here, we study one submarine calving event at Xeitl Sít’ (LeConte Glacier), Alaska, to explore the effect of calving on ice melt, using a suite of autonomously deployed instruments beneath, around, and downstream of the calving iceberg. Our measurements captured flows exceeding 5 m/s and demonstrate how potential …

Performance Analysis Of Power System Dynamic Stability Of The Nigerian 330kv Transmission Network, Charles Evuarherhe Ikeyin, Benjamin Olabisi Akinloye

Al-Bahir

Nigeria's power sector faces persistent challenges, including dynamic instability, poor voltage regulation, and frequent grid collapses, primarily driven by reactive power deficits and transmission distances exceeding 200 km in northern regions. To bridge critical research gaps, this study employs a rigorous, multi-method approach through comprehensive EMTP-RV (Electromagnetic Transients Program) analysis of Nigeria’s 330kV 52-bus grid, PV curve-based vulnerability indexing to identify cascade-critical buses, and a novel Cost-benefit Pareto framework for optimal capacitor placement. Methodology was validated against IEEE (Institute of Electrical and Electronics Engineers) 14-bus benchmarks. Validated against IEEE 14-bus benchmarks, simulations revealed severe voltage instability in northern …

Resilience Oriented Distribution System Service Restoration Considering Overhead Power Lines Affected By Hurricanes, Kehkashan Fatima, Hussain Shareef, Flavio Costa

Michigan Tech Publications

In recent years, there has been an increase in the frequency of severe weather events (like hurricanes). These events are responsible for most power outages in power distribution systems (PDSs). Particularly susceptible to storms are overhead PDSs. In this study, the dynamic Bayesian network (DBN)-based failure model was developed for different hurricane scenarios to predict the line failure of overhead lines. Based on the outcomes of the DBN model, a service restoration model was formulated to maximize restored loads and minimize power losses using Particle Swarm Optimization (PSO)-based distributed generation (DG) integration and system reconfiguration. Three different case studies based …

Non-Invasive Way For Detection Of Neonatal Jaundice Using Gbr, Priti V. Bhagat, Mukesh Raghuwanshi, Ashutosh D. Bagde

Chulalongkorn Medical Journal

Background: Neonatal jaundice is a common condition in newborns due to excess levels of bilirubin. The traditional method for bilirubin testing is invasive, i.e., through blood tests only, which is painful to infants. Therefore, this study uses machine learning algorithms to develop a non-invasive way to detect neonatal jaundice.

Objectives: Design a computer-aided support system to detect neonatal jaundice using machine learning algorithm.

Methods: The gradient-boosting regression model is used to predict the bilirubin level. Gradient Boosting is a robust boosting algorithm that combines several weak learners into strong learners, in which each new model is trained to minimize the …

Trustworthy Navigation With Variational Policy In Deep Reinforcement Learning, Karla Bockrath, Liam Ernst, Rohaan Nadeem, Bryan Joseph Pedraza, Dimah Dera

Electrical and Computer Engineering Faculty Publications

Introduction: Developing a reliable and trustworthy navigation policy in deep reinforcement learning (DRL) for mobile robots is extremely challenging, particularly in real-world, highly dynamic environments. Particularly, exploring and navigating unknown environments without prior knowledge, while avoiding obstacles and collisions, is very cumbersome for mobile robots.

Methods: This study introduces a novel trustworthy navigation framework that utilizes variational policy learning to quantify uncertainty in the estimation of the robot’s action, localization, and map representation. Trust-Nav employs the Bayesian variational approximation of the posterior distribution over the policy-based neural network’s parameters. Policy-based and value-based learning are combined to guide the robot’s actions …

Authenticating Electronic Devices Via Multi Tone Analysis, Carl Bohman Jr., Aaron Jennings, Christian Eakins, Mark B. Skouson, Richard Ott, Jamin Mccue

AFIT Patents

Methods and systems for authenticating electronic devices via multi tone analysis. A method for authenticating a device under test (DUT) of a type of DUT includes imparting voltage tones to the DUT. The voltage tones are proximate a frequency of interest that is associated with the type of DUT. Using a measurement response of the DUT to the voltage tones, an electronic signature of the DUT is determined. The DUT is determined to be authentic when the electronic signature of the DUT substantially matches an electronic signature of an authority DUT of the type of DUT.

Investigating The Harmonic Content Of A Pwm Inverter With Varying Modulation Index, Peter Makolo

Tanzania Journal of Engineering and Technology (TJET)

Photovoltaic energy is a clean and endless vital renewable energy. In order to generate electricity from solar energy an inverter is required to transform the direct current into alternating current. Also, with the emerging of new ultra-high voltage direct current transmission technology, the rectification and inverters play a great role. Most three-phase two-level inverters draw harmonics that cause heat dissipation, waveform distortions hence affect the electrical loads. Knowing that Total Harmonic Distortion content of voltage source inverter is important and must be within the allowable range. Several schemes are suggested to mitigate the distortion in order to produce as much …

Techno-Economic Analysis Of Hybrid Pv-Wind-Diesel Generator Swarm Grid For Rural Electrification In Tanzania, Ibrahim Mwammenywa

Tanzania Journal of Engineering and Technology (TJET)

Remote, rural, and off-grid communities, particularly in Sub-Saharan Africa (SSA), face significant challenges in securing reliable and affordable electricity. While solutions such as solar home systems (SHSs) and diesel generators (DGs) have been adopted by some individuals, their deployment is often not optimized to meet the full load demand. This study addresses this challenge by proposing a hybrid swarm grid (HSG) design that integrates photovoltaic (PV), wind energy, and diesel generators (DGs). Utilizing MATLAB/Simulink and HOMER, the HSG is modeled and optimized for a typical SSA village, incorporating real-world variables such as load demand profiles, solar irradiance, and wind patterns. …

Maximum Likelihood Symbol Timing Algorithm Based On Cyclic Prefix For Ofdm Systems, Kwame S. Ibwe

Tanzania Journal of Engineering and Technology (TJET)

In this paper, a blind symbol synchronization algorithm is presented for orthogonal frequency-division multiplexing (OFDM) systems, and a timing function based on the redundancy of the cyclic prefix (CP) is introduced. The existing algorithms rely on the prior knowledge of the channel energy distribution i.e. channel power profile. In practical environment the channel power profile is unknown to the receiver and its statistics are expected to be highly changing. Nevertheless, the use of pilot symbols in channel profile estimation reduces efficiency as data subcarriers are used to carry pilots instead of payload. In this paper a timing function that accounts …

Optimal Location And Sizing Of Facts Devices To Improve Voltage Profiles On A 132 Kv Mwanza-Musoma-Nyamongo Transmission Line, Peter Makolo

Tanzania Journal of Engineering and Technology (TJET)

Recently, utility companies have desired to supply quality, stable and reliable power to customers, and ensure they meet the demand. Flexible AC Transmission Systems (FACTS) dynamic compensator devices such as Static Synchronous Compensator (STATCOM), Static VAr Compensator (SVC) and Unified Power Flow Controller (UPFC) are an impeccable choice, however, cost is one of the limiting factors following these technologies. In addition, using FACTS devices in the system requires a detailed steady state, dynamic and optimisation analysis to effectively meet the purpose and ensure reduced cost. This paper proposes using an optimised FACTS device to improve voltage profile, power transfer, system …

Adoption Of Agrivoltaics In Developing Countries: A Review On Challenges, Opportunities And Future Prospects, Abdi J. Athumani, Pater Makolo

Tanzania Journal of Engineering and Technology (TJET)

This paper provides a review of agrivoltaics technology and how it has been applicable in developing countries, including African countries. Agrivoltaics, the integration of agricultural production with photovoltaic energy generation, offers promising solutions to water- energy-food nexus in developing countries. This technology offers the dual benefit of increasing agricultural productivity while generating clean energy, which is very important for regions facing frequent electricity shortages and declining agricultural yields due to climate change. However, despite its potential, the adoption of agrivoltaics in developing nations remains limited in comparison to developed countries due to financial, technical and policy constraints. This paper explores …

Towards Autonomous Energy Management: Machine Learning For Effective Auditing And Optimization, Sameh O. Abdellatif, Sherif Ashraf, Mira Mohsen

Electrical Engineering

This study presents a fully automated procedure for energy management and auditing, applicable to a diverse range of residential and commercial loads, leveraging machine learning techniques across three key phases: load classification, benchmarking, and smart monitoring. The model effectively categorizes energy loads based on consumption patterns, establishes performance benchmarks through historical data analysis, and employs real-time monitoring to identify inefficiencies and predict future energy usage. Evaluating the model through four distinct case studies demonstrates its capability to optimize energy consumption in a techno-economic manner, achieving significant energy savings of 34.73 MWh/year for essential loads in Egypt, 215.67 MWh/year for HVAC …

Developing A Low-Temperature Pathway For The Synthesis Of Two-Dimensional Ws2 Nanosheets, Akhil Potdar

Holster Scholar Projects

Since their discovery in 2004, two-dimensional (2D) materials have attracted great attention due to their unique mechanical, electrical, and chemical properties. However, their integration into devices is limited by the high temperatures required for crystalline growth, which prevents the use of flexible and biocompatible substrates like polymers for biomedical and next-generation electronic devices. This project aims to therefore develop a low-temperature synthesis process for two-dimensional tungsten disulfide (WS₂), a material particularly promising due to its tunable bandgap and biocompatibility. We propose that by first depositing an intermediate tungsten oxide film (WOx) via Hollow Cathode Plasma-Assisted Atomic Layer Deposition (HCP-ALD) and …

Foundations For Multi-Bit-Per-Cell Phase Change Memory Modeling Gst Crossbar Arrays, Sashah Wilson-Thompson

Holster Scholar Projects

This project builds a simulation foundation for selective cell heating in a phase-change memory (PCM) crossbar using Ge2Sb2Te5 (GST) as the active material. Using COMSOL Multiphysics® a 3D modeling software, couples Electric Currents, Electric Circuits, Heat Transfer in Solids, and Electromagnetic Heating for the simulation. A parameterized Tungsten (W)/GST-Amorphous/GST-Crystalline(phases) /W embedded in Silica Dioxide (SiO2) and surrounded in Silica Nitride (Si3N4) is validated at the single-cell level and scaled to small GST crossbars A terminal voltage (V_active/V_inactive, or 0 V if unselected) is applied through MOSFET and diode selector elements at the ends of each word line and bit line. …

Ai-Powered Accessibility Tracker For Inclusive Public Spaces, Yenny Ma, Kevin Beltran

College of Engineering Summer Undergraduate Research Program

This research project will develop and evaluate a smartphone-based, AI-powered system to crowdsource and analyze accessibility features and barriers in public spaces. Using computer vision and geospatial mapping, the system will identify and categorize issues such as uneven sidewalks, missing or inadequate curb ramps, damaged tactile paving, obstructive overhangs, and the absence of visual or auditory wayfinding cues. The overarching goal is to generate a dynamic, real-time accessibility map that empowers individuals with diverse mobility, sensory, and cognitive needs to navigate public spaces more safely and confidently. The project will integrate technologies and methods from applied machine learning, mobile computer …

Impulse, Fall 2025, Jill Fier, Sierra Brown, Jerome J. Lohr College Of Engineering

Impulse (Jerome J. Lohr College of Engineering Publication)

2 | Faculty News
3 | SDSU Vet Hua to Head Civil Engineering
6 | Ad Lunam — To the Moon
10 | Building A Safety Culture
11 | Department News
12 | Surface Mount Technology Kickoff
14 | Construction Management Student, Volleyball Player Building Success Piece by Piece
16 | Student Awards, Honors
18 | Student Competition Results
20 | NASA Win Opens Doors for New Product Development Order
22 | SDSU Engineering Student Tabbed as Noblereach Fellow
26 | Knabach Award Recipient from Apprentice Lineman to Company President
28 | Metzger Create Faculty Endowment for SDSU Engineering
30 …

Inductorless Cascaded Low-Power Dc-Dc Converter: Optimizing Performance Metrics Through Machine Learning Techniques, Ahmed Khaled, Sameh O. Abdellatif

Electrical Engineering

This study presents a groundbreaking methodology for optimizing the operational efficiency of a three-stage boost DC-DC cascaded converter through the application of a Random Forest(RF) machine learning algorithm. A novel figure of merit is meticulously formulated to quantitatively evaluate the converter’s performance, focusing on critical metrics such as power conversion efficiency, output DC ripple levels, and response time. The Random Forest model is trained on a comprehensive dataset encompassing a wide range of resistive and capacitive design parameters, with the figure of merit serving as the output indicator. Rigorous simulations and analyses demonstrate that the integration of LM741 operational amplifiers …

Research On The Construction Of Domain Knowledge Graph For Assisted Decision Making And Its Scenario-Oriented Application, Hao Xu, Linlin Ge, Yan Zhang, Sanhong Deng

Journal of Scientific Information Research

[Purpose/significance] This research constructed a domain knowledge graph and its scenario-oriented application framework for decision support at four levels: the data foundation layer, the key technology layer, the domain knowledge graph construction layer, and the scenario-oriented application layer. This framework aims to provide systematic support for knowledge discovery.

[Method/process] Based on the construction of a domain knowledge graph and its scenario-oriented application framework for decision support, this research focuses on the improvement of models and performance evaluation for fine-grained entity and relationship extraction at the discourse level within texts. The optimal model is selected to construct a domain knowledge graph. …

High Torque Density Dual-Stator Vernier Motors With Flux Concentrating Rotors, Esmaeil Mohammadi, Ali Mohammadi, Mohammad Amin Jalali Kondelaji, Pedram Asef, Ion G. Boldea, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

Axial Flux Permanent Magnet (AFPM) machines are increasingly being studied for low-speed, direct-drive applications due to their compact structure and high torque output. This study proposes two novel dual-stator AFPM vernier machine topologies: a spoke-type rotor configuration and a back-to-back Halbach array rotor. Both designs employ dual outer stators with 12 double-layer concentrated windings, and high-polarity rotor configurations to enhance flux concentration. A three-dimensional finite element model, which was previously validated by a laboratory prototype motor was utilized to evaluate the electromagnetic characteristics of the proposed topologies. These characteristics include torque density, airgap flux distribution, and harmonic content. Comparative results …

Multi-Phase Wireless Power Transfer With High Power Density Inductive Coils For Electric Drone Charging, Lucas A. Gastineau, Donovin D. Lewis, Omer Onar, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

Wireless charging of unmanned ground vehicles and aircraft has been proposed to increase charging reliability and security, allow for autonomous functionality, and either reduce battery size or increase continuous flight time. This paper proposes a three-phase Litz wire primary and a two-phase PCB secondary for high secondary-side power density considering misalignment tolerances, surface and volumetric power density, and coil sizing. Electromagnetic 3D finite element analysis (FEA) simulations are conducted to study variation in mutual inductance and coupling coefficient with different secondary coil sizes and number of turns, horizontal and vertical misalignment between the primary and secondary, and a combination of …

Nonlinear Design Scaling Of Electric Machines Based On Hybrid De And Meta-Modeling Application To Synchronous Motors With Combined Pm Stator And Reluctance Rotor Excitation, Oluwaseun A. Badewa, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

This paper presents an innovative method for nonlinear scaling of electric machines by integrating machine learning (ML)-based meta-modeling with a differential evolution (DE) algorithm. The technique is applied to high-performance combined-excitation synchronous electric motors which exhibit highly nonlinear characteristics, making performance scaling challenging. The proposed approach employs an ML meta-model trained on data obtained from finite element analysis (FEA), utilizing an experimentally validated model for nonlinear scaling and performance prediction at different power ratings. The accuracy of the meta-model in capturing the nonlinear relationships between design parameters and motor performance is first assessed using metrics such as R-squared (R2) and …

Multi Electric Machines With Series And Parallel Electromechanical Combinations For Aircraft, David R. Stewart, Donovin D. Lewis, Matin Vatani, Diego A. Lopez-Guerrero, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

High-performance electric propulsion systems require fault tolerant, power dense, electric machines capable of maintaining high efficiency across a dynamic range of operation. To address these inherently conflicting requirements, multi-motor architectures employing electromechanically coupled modular configurations have been proposed to enhance system efficiency, fault tolerance, and redundancy. This paper investigates four mechanically coupled configurations for a coreless axial flux permanent magnet (CAFPM) motor unit integrating series, parallel, and hybrid architectures with differential and gearbox coupling. Performance and optimal sizing for motors in each configuration are determined through 3D finite element analysis (FEA). To assess fault tolerance and system redundancy, Markov chain …

Design Optimization And Scaling Of Coreless Afpm Machines Using Hybrid Fea-Based Differential Evolution And Machine Learning, Matin Vatani, David R. Stewart, Donovin D. Lewis, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

This paper presents a machine learning (ML) based design framework for the fast and accurate optimization of coreless axial flux permanent magnet (AFPM) machines. Although the absence of magnetic cores eliminates material nonlinearity, the design process remains highly nonlinear due to the complex influence of geometric parameters. To overcome the computational challenges of finite element analysis (FEA)-based optimization, a series of multi-objective differential evolution (MODE) optimizations were conducted across various machine sizes at constant power output. The resulting design data was used to train an artificial neural network (ANN), enabling rapid prediction of machine performance without the need for repeated …

Coreless Axial Flux Permanent Magnet Machines With Concentrated Coils And Various Pole/Coil Combinations, Matin Vatani, Spencer M. Goode-Kulchar, John F. Eastham, Xiaoze Pei, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

This paper comprehensively analyzes coreless stator axial flux permanent magnet (AFPM) machines by investigating rotor magnetic fields, stator winding factors, and 2D/3D finite element analysis (FEA) simulations. The torque production theory in coreless AFPM machines is studied with detailed derivations for flux density and current density. The impact of rotor permanent magnet (PM) width is examined for both surface-mounted and Halbach array configurations, followed by a discussion of its influence on the air-gap harmonic spectrum. The effect of stator coil side width is analyzed through a detailed winding factor study across various pole-to-coil ratios and a discussion on the trade-off …

Voltage And Reactive Power Combined Control Of Utility Devices And Smart Inverters On A Distribution Grid With Solar Pv, Steven B. Poore, Rosemary E. Alden, Evan S. Jones, Thomas Morstyn, Aron Patrick, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

With adoption of distributed energy resources (DERs) expected in future grids, voltage regulation methods need to be reevaluated and improved to ensure their effectiveness under the high volatility of renewable generation. A multi-timescale cluster-based method is proposed to optimize and disperse operation of voltage controlling utility devices including capacitor banks (CBs) and load tap changers (LTCs) while allowing faster response time with customer-owned smart inverters (SIs) in-between switching operations. The proposed method is tested on a digital twin (DT) of a very large utility distribution grid with 2,018 nodes and 8.65MW peak load to evaluate its effectiveness in future grid …

Torque-Speed Characteristic Estimation Based On Gaussian Processes And Adaptive Sampling Strategy For Permanent Magnet Synchronous Machines, Marcelo D. Silva, Pedram Asef, Oluwaseun A. Badewa, Rosemary E. Alden, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

Internal Permanent Magnet Synchronous Machines (IPMs) are widely used and typically optimized to meet specific performance requirements. Parameters such as base speed, maximum torque, and maximum speed commonly define the torque- speed characteristic of a given design. This study introduces a novel machine learning approach for statistically estimating the torque-speed characteristics of IPMs using Gaussian Process Regression (GPR), which models predictions as random variables. By leveraging uncertainty quantification, the study explores sampling strategies that enable the construction of a high-precision meta-model with minimal error and uncertainty. The proposed adaptive sampling strategy, combined with GPR, accurately estimates torque-speed characteristics and associated …

Degradation Minimization Of Utility-Scale Li-Ion Bess Through Operational Optimization Employing An Equivalent Circuit Model, Kwabena A. Kyeremeh, Grant M. Fischer, Donovin D. Lewis, Aron Patrick, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

The increasing deployment of utility-scale battery energy storage systems (BESS) necessitates effective strategies for supporting grid services while minimizing degradation that may compromise system longevity. High charge/discharge rates (C-rate) and imbalanced operation of multi-unit BESS configurations may accelerate degradation. This paper proposes a degradation-aware operational optimization based on Model Predictive Control (MPC) for coordinating multiple BESS units under physical and operational constraints. The multi-objective optimization model imposes penalties on C-rate magnitude, operational state-of-charge (SoC) disparity, and battery internal resistance modeled using an equivalent circuit model. A case study conducted for a fleet of BESS units over a one-week load profile …

Csc36000 - Modern Distributed Computing Assignment, Saptarashmi Bandyopadhyay

Open Educational Resources

This assignment covers standard performance metrics for Distributed Systems and the basics of Multiprocessing for CSC36000 - Modern Distributed Computing at the City College of New York CUNY. It is an interactive coding assignment intended to be executed in a Python notebook.

Safety-Critical Formation Control Of Non-Holonomic Multi-Robot Systems In Communication-Limited Environments, Logan Beard

College of Engineering Summer Undergraduate Research Program

This project explores advanced methodologies for distributed planning, formation control, and coordination in heterogenous multi-agent robotic systems consisting of small mobile robots and nano unmanned aerial vehicles (UAVs). Leveraging decentralized control theories and optimization techniques, the research aims to develop robust algorithms for real-time collaborative task execution, efficient formation maintenance, and adaptive coordination strategies. Python and ROS will be used extensively to simulate, validate, and experimentally deploy distributed robotics algorithms. The student researcher significantly contributes to the theoretical and practical advancement of multi-agent system technologies.

Eggbeater Antenna Design 915 Mhz, Anshul Deshmukh

College of Engineering Summer Undergraduate Research Program

The Sal-E cube sat mission that is planned for launch in 2026 includes a 902-928 MHz receiving module called the Space Quacker Advanced Development (SQUAD) module. The SQUAD module uses the LoRa modulation format for unlicensed uplink to the satellite using the 902-928 MHz Industrial, Scientific, and Medical (ISM) band. The goal of the SQUAD module is to demonstrate the link robustness of the LoRa communication standard to a low earth orbit (LEO) satellite using this ISM band. To demonstrate this communication link, a 902-928 MHz uplink ground station needs to be established at Cal Poly. The goal of this …