Engineering Commons^™

Sustainability In The Cruising Industry: Innovations In Air Quality, Energy Efficiency, And Waste Management, Fikret Durmus, Mi Ran Kim

ICHRIE Research Reports

The cruise industry, a cornerstone of the global hospitality and tourism sector, faces increasing scrutiny over its environmental impact. As passenger numbers grow, so does the industry's responsibility to adopt sustainable practices. This report examines key innovations in air quality management, energy efficiency, and waste management, highlighting the industry's transition from historically high emissions and waste production to advanced sustainability initiatives. Key focus areas include evolving maritime regulations, adopting cleaner propulsion technologies, integrating energy-efficient solutions, and improving waste treatment practices. Findings indicate that industry leaders are investing in liquefied natural gas engines, exhaust gas cleaning systems, and onshore power supply …

Exploring The Limits Of Multimodal Foundation Models For Visual Temporal Reasoning And Gesture Recognition Tasks, Ziyao Shangguan

Computer Science Theses

Multimodal foundation models (MFMs) have demonstrated impressive capabilities in static vision-language tasks such as image captioning, video summarization, and cross modal retrieval. However, their ability to reason over time—especially in gesture-rich video inputs—remains limited. This thesis investigates the temporal reasoning capabilities of MFMs in the context of gesture understanding, a critical component for enabling more expressive human-robot interaction. Through a preliminary study, we show that prompting-based strategies offer only marginal improvements in temporal reasoning, despite producing accurate frame-by-frame descriptions.

To more rigorously evaluate these limitations, we introduce TOMATO, a benchmark designed to assess visual …

An Artificial Neural Network-Based Battery Management System For Lifepo4 Batteries, Roger Painter, Ranganathan Parthasarathy, Lin Li, Irucka Embry, Lonnie Sharpe, S. Keith Hargrove

Civil and Architectural Engineering Faculty Research

We present a reduced-order battery management system (BMS) for lithium-ion cells in electric and hybrid vehicles that couples a physics-based single-particle model (SPM) derived from the Cahn–Hilliard phase-field formulation with a lumped heat-transfer model. A three-dimensional COMSOL® 5.0 simulation of a LiFePO4 particle produced voltage and temperature data across ambient temperatures (253–298 K) and discharge rates (1 C–20.5 C). Principal component analysis (PCA) reduced this dataset to five latent variables, which we then mapped to experimental voltage–temperature profiles of an A123 Systems 26650 2.3 Ah cell using a self-normalizing neural network (SNN). The resulting ROM achieves real-time prediction accuracy comparable …

Bounding Case Requirements For Power Grid Protection Against High-Altitude Electromagnetic Pulses, Connor A. Lehman, Darrell Robinette, Wayne Weaver, David G. Wilson

Michigan Tech Publications

Securing the power grid is of extreme concern to many nations as power infrastructure has become integral to modern life and society. A high-altitude electromagnetic pulse (HEMP) is generated by a nuclear detonation high in the atmosphere, producing a powerful electromagnetic field that can damage or destroy electronic devices over a wide area. Protecting against HEMP attacks (insults) requires knowledge of the problem’s bounds before the problem can be appropriately solved. This paper presents a collection of analyses to determine the basic requirements for controller placements on a power grid. Two primary analyses are conducted. The first is an inverted …

Extreme Bandgap Polarization Doped Algan Layers On Bulk Aln For Pn-Diodes With An 8.5 Mv Cm−1 Breakdown Field And Forward Current Density Exceeding 20 Ka Cm−2, Tariq Jamil, Abdullah Al Mamun Mazumder, Muhammad Ali, Mafruda Rahman, Kenneth Stephenson, Grigory Simin, Asif Khan

Faculty Publications

In this paper we present a study of distribution polarization doped Al_xGa_1−xN layers and their use in quasi-vertical configuration pn-diodes which exhibited a high breakdown field of ∼8.5 MV cm⁻¹ and a large forward current density (∼23 kA cm⁻²). We also establish their potential use in UVC light emitters by studying the optical emission from a quantum well inserted at the distribution polarization doped pn-junction interface.

Multiagent Copilot In Industrial Ai Applications, Chathurangi Shyalika, Renjith Prasad, Utkarshani Jaimini, Cory Henson, Fadi El Kalach, Amit Sheth

Publications

In the era of smart automation and digital transformation, achieving efficiency, precision, and adaptability is essential for industries to remain competitive. Sectors, including manufacturing, supply chain and logistics, healthcare, finance, and retail, face significant challenges in deploying Artificial Intelligence (AI) solutions tailored to their unique needs, particularly in critical, resource-constrained applications. According to Gartner’s 2024 Hype Cycle for Artificial Intelligence, composite AI, which integrates techniques like machine learning, knowledge graphs, and rule-based systems, is becoming foundational for industries, enhancing predictions, decisions, and scalability across complex environments.

The complexity of real-world systems requires Industrial AI solutions to be customizable to business …

Development And Evaluation Of A Simple Human Body Link Model Considering The Degrees-Of-Freedom Of Shoulders, Mizuki Takeda, Yuki Saito, Kaiji Sato

Progress in Scale Modeling, an International Journal

Modeling of the human body is widely utilized in the field of human–robot interaction, warranting the development of a simple model to measure and recognize the human body movements. To this end, a two-dimensional (2D) human body link model in the sagittal plane has been used to represent the human body with rotating joints and links connecting these joints. The joint positions can be determined by using the coordinates of a limited number of points on the links and estimated using a few sensor outputs when the links are of constant length. However, models with constant link lengths may result …

A Review Of Direct Ink Writing Of Polymer Derived Ceramics, Victoria Bishop, Saket Chand Mathur, Nhu Nguyen, Bhisham Sharma, Mary Drouin, Bin Li, Cheol Park, Wei Wei

Michigan Tech Publications

With the growing demand for materials capable of withstanding extreme temperatures and pressures, ceramic components with exceptional corrosion resistance and reliable mechanical properties have experienced a significant surge in demand. However, traditional ceramic forming methods involve high-temperatures and energy-intensive processes that often struggle to produce complex parts or composites efficiently. Polymer-Derived Ceramics (PDCs) offer a transformative solution by using polymeric precursors that can be converted into a wide variety of silicon-based and non-silicon-based ceramics through heat treatment. The polymeric nature of PDC precursors enables the fabrication of geometrically intricate components using conventional polymer-forming techniques at significantly lower processing temperatures. Furthermore, …

Meshlet Rendering Using D3d12 Mesh Shading Pipeline, Anishva Bardhan

Programming Theses and Dissertations

Modern video games must render scenes with increasingly complex geometry. Technologies like Nanite in Unreal Engine 5 enable the handling of scenes with significantly higher object and triangle counts than ever before. This project draws inspiration from Nanite by operating on triangle clusters, allowing artists to focus solely on creating high-poly meshes. The primary objective is to implement fine-grained culling techniques on meshlets, combined with efficient meshlet instancing, to reduce render time and memory usage.

Meshlet instancing plays a crucial role in optimizing rendering performance by allowing multiple objects sharing the same geometry to be rendered efficiently. Instead of duplicating …

3d Multi-Threaded Ai Navigation With Pathfinding And Obstacle Avoidance, Jabari Belgrave

Programming Theses and Dissertations

In this thesis, I developed a 3D multi-threaded AI navigation system using my own custom-built C++ game engine. The system combines triangle-based A* pathfinding with real-time obstacle avoidance using a set of velocity-obstacle algorithms. It is designed to support large numbers of agents navigating complex environments while avoiding collisions. I created two main simulation modes: Navigation Mode, which integrates A* with ORCA to handle large-scale pathfinding and movement, and Obstacle Avoidance Mode, which allows direct comparison between VO, RVO, HRVO, and ORCA in a controlled test setting.

The terrain is procedurally generated using Perlin noise, and this terrain data is …

Molecular Dynamics Study Of Phase Change And Interfacial Behavior In Nanoconfined Argon, Ying-Chu Chen

Mechanical Engineering Research Theses and Dissertations

As electronic devices continue to reduce in size, effective thermal management becomes increasingly critical. Thin-film evaporation offers a promising solution due to its high heat flux capacity and passive nature. However, the applicability of continuum theory to thin-film evaporation becomes uncertain at the nanoscale. This work presents a two-phase Molecular Dynamics(MD) study of liquid argon confined within two parallel platinum walls, focusing on both equilibrium and non-equilibrium phase change behavior under nanoscale confinement.

In the first phase, Equilibrium Molecular Dynamics (EMD) simulations investigate the influence of channel height (4, 8, and 16 nm) and wall-fluid interaction strength on bulk and …

Load Forecasting And Modeling For Power System, Han Guo

Electrical Engineering Theses and Dissertations

Accurate load forecasting and modeling play a pivotal role in ensuring the stability, reliability, and economic efficiency of modern power systems. With the increasing integration of renewable energy sources, distributed energy resources, and demand-side management strategies, power systems are becoming more dynamic and complex, making traditional load forecasting methods inadequate. This dissertation introduces two novel approaches to address the challenges associated with day-ahead load forecasting and load modeling.

First, a Diffusion Model-Based Probabilistic Day-Ahead Load Forecasting (PDALF) Framework is proposed to enhance the accuracy and robustness of load forecasting. By employing a conditional denoising diffusion probabilistic model (DDPM), the framework, …

A Highly Sensitive Electrochemical Immunosensor For Cortisol Detection, Pritu Sarkar, Ali Ashraf, Ahmed Hasnain Jalal, Fahmida Alam, Nazmul Islam

Mechanical Engineering Faculty Publications

In this research, an interdigitated gear-shaped working electrode is presented for cortisol sensing. Overall, the sensor was designed in a three-electrode system and was fabricated using direct laser scribing. A synthesized conductive ink based on graphene and polyaniline was further employed to enhance the electrochemical performance of the sensor. Scanning electron microscopy (SEM) and Fourier transform infrared (FTIR) spectroscopy were employed for physicochemical characterization of the laser-induced graphene (LIG) sensor. Cortisol, a biomarker essential in detecting stress, was detected both in phosphate-buffered saline (PBS, pH = 7.4) and human serum within a linear range of 100 ng/mL to 100 µg/mL. …

Effect Of Using Machine Learning To Improve Active Suspension Control For Vehicle Stability, David A. Butz

Masters Theses

This study demonstrates that it is possible to use road surface classification as a means of informing active suspension systems in order to limit their activity. An approach was taken to improve the response of an active suspension control system by classifying road surfaces in near real time. A control system model was developed to represent a full-body vehicle, and an AI was used to analyze road vibration noise. The model was adapted to allow the AI to select from multiple control signals based on the AI’s analysis of road vibration noise. The objective of the study was to demonstrate …

Design Of A Subthreshold Cmos Inverter-Based Amplifier For Low-Noise And Low-Power Applications, Landon Alexander Schmucker

Electrical and Computer Engineering ETDs

Amplification is a fundamental function in most analog circuits. There is a fast-growing demand for low-power, low-noise, and high-gain amplifiers. Modern semiconductor processes are increasingly optimized for digital applications, which has introduced new challenges in analog design. To address these challenges, analog designers have investigated replacing conventional analog circuits with digital implementations. One promising application is the typical CMOS inverter as an amplifier.

This research presents a CMOS inverter-based amplifier with feedback designed to achieve low power consumption, low input noise, and high gain. Unlike typical CMOS inverter-based amplifiers, this topology has two distinctive features: (1) it uses a MOSFET …

Machine Learning-Driven Optimization Of Piezoelectric Energy Harvesters For Low-Frequency Applications, Kyrillos Selim, Login Moustafa, Sameh O. Abdellatif

Electrical Engineering

To enhance energy harvesting efficiency, this paper explores the optimization of a cantilever-based piezoelectric energy harvester by integrating advanced machine learning (ML) methodologies. Leveraging a meticulously trained model on data sourced from a sophisticated two-dimension (2D) COMSOL Multiphysics numerical simulation, the study focuses on the critical input parameters, particularly the dimensions of the piezoelectric thin film. Through extensive simulations, the analysis delves into power density extraction and resonance frequency for various configurations. The culmination of rigorous simulations and analysis has led to the identification of an optimal design configuration for the cantilever piezoelectric energy harvester, characterized by a length of …

06.16.2025 Ored Connect, Liz Williamson

ORED Newsletter

Email address Matters with SPAN and ARC Forms

Participant Support Costs training for PIs available in Blackboard

Aerial Robotic Studies Of Volcanic Co2 Emissions, John Ericksen

Computer Science ETDs

Volcanic systems are inherently complex, involving dynamic interactions among magma flow, gas emissions, and atmospheric dispersion. This dissertation focuses on developing and analyzing autonomous UAS algorithms for efficiently surveying volcanic CO2 plumes, introducing several novel methods: the LoCUS algorithm, a swarm coordination and self-healing algorithm that supports gradient-based plume tracking, a transect-based technique that employs a 2D Gaussian fit to calculate CO2 plume flux, and the Sketch algorithm for rapid plume boundary tracing. By treating multiple UAS as a single scientific instrument, these methods leverage swarm algorithms to use in-situ data in ways impossible with individual drones. Validated through simulations …

Enhancing Water Supply Resilience & Sustainability: Potential Solutions To Address Water Scarcity In Bogotá, Colombia, Sophia Alvarez Wong

Master's Projects and Capstones

Municipal water utilities are in urgent need of adapting to the intensifying impacts of climate change and population growth—key drivers of urban water scarcity worldwide. In rapidly expanding cities like Bogota, Colombia, these pressures have contributed to a severe water crisis driven by prolonged droughts, ecosystem degradation, increasing water demands, and overdependence on limited water sources. This study explores potential adaptation and management strategies that utilities can implement to sustainably strengthen supply system resilience and enhance water security, in the context of low- to middle-income regions. A series of comparative and case study analyses were conducted to assess the feasibility …

Who Owns The Wind: The Absence Of Community Wind Farms In California, Sky Berry-Weiss

Master's Projects and Capstones

Community ownership structures for wind farms have been around for decades, particularly in European countries, due to high socioeconomic benefits. Given these significant benefits, one might expect community wind to thrive in the United States—especially in a state like California, which prides itself on progressive climate policy and renewable energy leadership. Yet utility-scale community wind remains largely absent from research on California’s energy system, raising questions about its existence in the state. To pinpoint how many utility-scale community owned wind farms are in California, this study surveys every operational wind turbine in the state. After classifying each wind farm by …

Advancing Wood Chip Moisture Content Prediction Using Advanced Generative Ai Techniques, Daniel Esteban Marulanda

Theses and Dissertations

In this study we propose a deep learning method to optimize the classification of wood chip moisture content levels using the Vision Transformer and then ultimately increase the classification performance by creating synthetic images using the diffusion transformer model. In the first chapter of our study, we complete a detailed explanation of how the moisture content levels of 10 different wood chips were gathered ranging from 2 to 50$\%$. This chapter serves as a foundation for subsequent sections, illustrating the challenges associated with the current data collection process, which is both time-consuming and inefficient. Accurately determining moisture content for wood …

An Overview Of Global Navigation Satellite System Reflectometry In Coastal Wetlands, Luke Andrew Redwine

Theses and Dissertations

With rising global temperatures, increasing sea levels, and the accelerated erosion of coastal wetlands, efficient methods for monitoring this vulnerable ecosystem are crucial. Traditional approaches, such as manual surveys, are labor-intensive, hazardous, and invasive to the environment they are attempting to protect, while current remote sensing methods are cost prohibitive and rely on irregular data collection techniques. To address these challenges, a scalable solution is needed for reliable and frequent data collection. This study explores the use of GNSS Reflectometry (GNSS-R) combined with unmanned aerial vehicles (UAVs) to monitor the shifting topology in wetlands with minimal human invasion. By leveraging …

An Updated Viscoplastic Self-Consistent Model To Capture The Effects Of Residual Stress, Microstructural Heterogeneity, And Precipitation In Cold-Sprayed Aluminum Alloys, Aulora Williams

Theses and Dissertations

Cold spray additively manufactured (CSAM) aluminum alloys exhibit heterogenous microstructures and mechanical properties, primarily due to high dislocation densities, sub-grain structures, and variation in inter-particle (intersplat) bonding arising from high-velocity particle impacts. Thermal post-processing has been shown to enhance intersplat bonding, reduce high residual stress concentrations, and lower dislocation densities, thereby improving the overall mechanical properties. Building on previous advancements with a mean-field viscoplastic self-consistent (VPSC) model, integrating intersplat boundary terms, Hall-Petch relations, and physically informed residual stress parameters, the current work extends the model to include precipitates and their effects. Observations of CSAM aluminum 7050 alloy indicate precipitate congregation …

Development Of Non-Precious Iron-Cobalt Alloy Catalyst For Electrocatalytic Reaction, Harsh Panchal

Electronic Theses & Dissertations

The development of a FeCo alloy catalyst with tunable Fe/Co ratios is examined to improve electrocatalytic performance in reactions like the oxygen evolution reaction (OER), hydrogen evolution reaction (HER), and oxygen reduction reaction (ORR). Many energy conversion devices, such as fuel cells, metal-air batteries, and water-splitting systems, depend on these interactions to function. These technologies have huge potential to meet the increasing need for hydrogen production and renewable energy sources worldwide, which are critical to attaining a sustainable energy future. When compared with noble metal-based catalysts, the FeCo alloy catalyst shows much higher catalytic activity, according to previous studies. Hydrothermal …

Zn–Assisted Synthesis Of M (Mn/Fe/Co/Ni)-N-C Catalysts For Multifunctional Electrochemical Activity, Kemila A. Chaudhary

Electronic Theses & Dissertations

The design and development of atomically dispersed M-N-C catalysts (metal (M) supported on an nitrogen-carbon (NC) matrix with high multifunctional electrocatalytic performance is desirable but proved to be very challenging. Herein, we synthesized M-N-C catalysts (M = Fe, Co, Mn, and Ni) using Zn-assisted high temperature treatment and characterized using various techniques. The prepared catalysts were tested for their electrocatalytic performance towards oxygen and hydrogen evolution reaction (OER and HER) as well as oxygen reduction reaction (ORR) in alkaline media. The results indicated that Mn-N-C catalyst showed higher performance towards both the ORR (E_1/2 = 0.90 V) and …

A Rapid Artificial Neural Network Interatomic Potential For Bismuth, Lee Michael Mayfield Jr.

Theses and Dissertations

To study molecular dynamics in bismuth, Quantum Espresso was used to create a density functional theory (DFT) database which was then used as the input for rapid artificial neural network (RANN). The RANN interatomic potential that was developed using this database was then validated. Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) was used to create simulations and gather data using the RANN potential. The properties of bismuth, including elastic constants, melting points, and volume change, were calculated and compared to DFT and experimentally observed data. The RANN potential coincided well with these values. The RANN potential shows good predictive capabilities for …

The Importance Of Community: An Investigation Of Stress, Coping, And The Value Of Social Support For First Responders, Brian Reid

Theses and Dissertations

People are designed to be in community with others, to work together and share the load and weight of life. First responders are a community that has not emphasized the importance of social support to mitigate and buffer against the stress inherent in their jobs. This study investigates the sources of stress, coping methods, and social support of first responders. Results from the first study show the impact of workplace and family stress on the first responder is impactful from the beginning. The secondary study finds that adaptive coping methods are the preferred method to cope with stress and that …

Enhancing Profitability In The Air Transport Industry Through Improved Air Passenger Forecasting: A Comparative Analysis Of Arima, Holt-Winters And Lstm Time Series Forecasting Techniques, Megan Skowronek

Theses and Dissertations

Predicting air passenger volumes is crucial for airports and airlines seeking to reduce costs and enhance profitability. Accurate forecasting enables better planning and efficiency improvements within the air transport industry. This study applies LSTM, ARIMA and HW to U.S. air passenger datasets. Each analysis shows a methodology for predicting air passenger volumes across airports, airlines and across airports and airlines simultaneously. ARIMA was found to have limited applicability, since only a subset of the datasets was stationary. LSTM and HW were applicable to all airlines and ARIMA was applicable to no airlines. LSTM had less error compared to HW at …

Adaptive Multi-Sensor Fusion For Robust Autonomous Perception In Unstructured Environments, Samantha S. Carley

Theses and Dissertations

Autonomous vehicles commonly employ multiple sensors to perceive their surroundings. Coupling these sensors would ideally improve perception compared to using a single sensor. An autonomous system can be equipped with object localization and classification, often performed using a visual camera to understand a scene intelligently. Object detection and classification can also be applied to LiDAR and infrared (IR) sensors to further enhance scene awareness of the autonomous system. Herein, sensor-level, decision-level, and feature-level fusion are explored to assess their impact on perception and mitigate sensor disagreements. Specifically, the fusing of RGB, LiDAR, and IR sensor data to improve object classification …

The Role Of K-12 Educators In Shaping Stem Pathways: Examining Social Capital And Self-Efficacy In Stem Education, Holly Trisch

Theses and Dissertations

This dissertation examines the impact of K-12 educators on students’ pathways in STEM (Science, Technology, Engineering, and Mathematics) by focusing on two main factors: the social capital of K-12 and elementary school teachers and the self-efficacy of preservice teachers in STEM education instruction. The first study investigates the social capital of first year engineering students, emphasizing the relationships and resources they gained during their K-12 education that influenced their decision to major in engineering. A quantitative study using survey data collected from first-year undergraduate engineering students indicates that K-12 educators play a crucial role by providing mentorship and resources that …