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Articles 4141 - 4170 of 8619
Full-Text Articles in Engineering
Predicting Strut Geometry Of Pcl And Dmso2 Biocomposites From Nozzle To Deposition In Bio-Scaffold 3d Printing, Jae-Won Jang, Kyung-Eun Min, Jun-Hee Park, Cheolhee Kim, Sung Yi
Predicting Strut Geometry Of Pcl And Dmso2 Biocomposites From Nozzle To Deposition In Bio-Scaffold 3d Printing, Jae-Won Jang, Kyung-Eun Min, Jun-Hee Park, Cheolhee Kim, Sung Yi
Mechanical and Materials Engineering Faculty Publications and Presentations
The field of tissue engineering increasingly demands accurate predictive models to optimize the 3D printing process of bio-scaffolds. This study presents a unified numerical model that predicts extrusion velocity and strut diameter based on printing conditions and the material properties of polycaprolactone (PCL) and dimethyl sulfone (DMSO2) composites. The extrusion velocity was simulated using Navier–Stokes equations, while the strut diameter was calculated via a surface energy model. For PCL, the extrusion velocity showed a temperature coefficient of 23.3%/°C and a pressure coefficient of 19.1% per 100 kPa; the strut diameter exhibited a temperature coefficient of 21.6%/°C and a pressure coefficient …
The Hecks Angels: A Look At The City Of New York's Electric Motorcycle Community, Mckenzie A. Corey
The Hecks Angels: A Look At The City Of New York's Electric Motorcycle Community, Mckenzie A. Corey
Capstones
Motorcycles are a common mode of transportation globally, but within the U.S., they tend to imply a certain demeanor—maybe someone who's brash or a risk taker. I mean, it makes sense. You've got to be a bit daring to ride off into the sunset on something that screams when it shifts gears and begs to be revved at a red light. But in New York City electric motorcycle enthusiasts appear to have slapped a fresh coat of paint on the old concept of what it means to live a life on two wheels.
Finite Volume Incompressible Lattice Boltzmann Framework For Non-Newtonian Flow Simulations In Complex Geometries, Akshay Dongre, John Ryan Murdock, Song Lin Yang
Finite Volume Incompressible Lattice Boltzmann Framework For Non-Newtonian Flow Simulations In Complex Geometries, Akshay Dongre, John Ryan Murdock, Song Lin Yang
Michigan Tech Publications
Arterial diseases are a leading cause of morbidity worldwide, necessitating the development of robust simulation tools to understand their progression mechanisms. In this study, we present a finite volume solver based on the incompressible lattice Boltzmann method (iLBM) to model complex cardiovascular flows. Standard LBM suffers from compressibility errors and is constrained to uniform Cartesian meshes, limiting its applicability to realistic vascular geometries. To address these issues, we developed an incompressible LBM scheme that recovers the incompressible Navier–Stokes equations (NSEs) and integrated it into a finite volume (FV) framework to handle unstructured meshes while retaining the simplicity of the LBM …
Hierarchical Optimal Scheduling Of Integrated Energy System With Electric Vehicles Based On Empc, Miaomiao Ma, Zijuan Long, Zhiwei Ren, Yongqiang Cheng
Hierarchical Optimal Scheduling Of Integrated Energy System With Electric Vehicles Based On Empc, Miaomiao Ma, Zijuan Long, Zhiwei Ren, Yongqiang Cheng
Journal of System Simulation
Abstract: A hierarchical real-time optimization (HRTO) based on economic model predictive control is designed to address the issues of randomness and uncertainty of renewable energy and demand-side in integrated energy systems (IES) with electric vehicles. The optimization problem of the entire system is divided into three sub-problems: day-ahead rolling optimization, real-time rolling optimization, and tracking control. The day-ahead optimization strategy based on economic model predictive control is constructed to ensure that the operational units can meet users' demands. The optimal steady-state operating points of the entire IES are obtained through the real-time optimization layer. The tracking model predictive controller is …
Method For Dynamic Coalition Formation Of Wargame Agent For Force Cooperation, Changhua Yao, Shanning Bi, Rufei Ma, Xiaohan Yu, Jiaqiang Li, Jinli Chen
Method For Dynamic Coalition Formation Of Wargame Agent For Force Cooperation, Changhua Yao, Shanning Bi, Rufei Ma, Xiaohan Yu, Jiaqiang Li, Jinli Chen
Journal of System Simulation
Abstract: Regarding the issue of cooperative task alliance formation and adjustment in multi-agent dynamic confrontation scenarios at the tactical level, this method comprehensively considers factors such as target value, task allocation, and operator characteristics, as well as the benefits and costs of executing different types of tasks. we propose a targeted force coordination adjustment for dynamic task alliance formation based on behavioral constraints. The “MiaoSuan-Wise Winning Instant Strategy Human-Computer Confrontation Platform” of Chinese Academy of Sciences (CAS) is used as an experimental platform to conduct confrontation experiments. The experiment demonstrates that the proposed method improves the dynamic coordination ability of …
Research On Decision-Making Of Autonomous Driving In Highway Environment Based On Knowledge And Large Language Model, Xiang Wang, Guozhen Tan
Research On Decision-Making Of Autonomous Driving In Highway Environment Based On Knowledge And Large Language Model, Xiang Wang, Guozhen Tan
Journal of System Simulation
Abstract: Aiming at the lack of continuous learning and interpretability of current autonomous driving system, a decision model with cognition, generalization and learning ability is proposed. The model utilizes large language model (LLM) and attention mechanisms to understand and explain driving scenes. the system can accumulate and learn from driving experiences, continuously improving its decisionmaking ability. In a simulation environment, the closed-loop test decision model is applied in high-speed scenarios.The simulation results show that the success rate of the knowledge-driven model is 7% and 4% higher than those of the rule-based and data-driven methods. Additionally, the model exhibits generalization and …
Functionalizing Polyethersulfone Membranes: Using Nmr To Avoid Pitfalls When Using Uv-Induced Polymerization To 'Graft From' Surfaces, Priyanka Suresh, Megan M. Sibley, Amy C. Che, Christine E. Duval
Functionalizing Polyethersulfone Membranes: Using Nmr To Avoid Pitfalls When Using Uv-Induced Polymerization To 'Graft From' Surfaces, Priyanka Suresh, Megan M. Sibley, Amy C. Che, Christine E. Duval
Faculty Scholarship
For nearly 30 years, UV-induced free radical polymerization has been used to modify the surface chemistry of polyethersulfone (PES) membranes, films, and coatings. The initial mechanism for the grafting process was introduced in the 1990s and supported without direct evidence of covalent bond formation. Since then, claims of ‘grafting from’ membranes in the literature rely on similar evidence using a combination of gravimetry, attenuated total reflectance infrared spectroscopy, contact angle goniometry, water sorption, and/or water permeance. While these techniques provide evidence of the presence of a polymer coating, they do not provide direct evidence of covalent bond formation between the …
Sustainability In The Cruising Industry: Innovations In Air Quality, Energy Efficiency, And Waste Management, Fikret Durmus, Mi Ran Kim
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
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
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 …
Multiagent Copilot In Industrial Ai Applications, Chathurangi Shyalika, Renjith Prasad, Utkarshani Jaimini, Cory Henson, Fadi El Kalach, Amit Sheth
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 …
Bounding Case Requirements For Power Grid Protection Against High-Altitude Electromagnetic Pulses, Connor A. Lehman, Darrell Robinette, Wayne Weaver, David G. Wilson
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
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 AlxGa1−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.
Development And Evaluation Of A Simple Human Body Link Model Considering The Degrees-Of-Freedom Of Shoulders, Mizuki Takeda, Yuki Saito, Kaiji Sato
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
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, …
The Rapid Detection Of Foreign Fibers In Seed Cotton Based On Hyperspectral Band Selection And A Lightweight Neural Network, Yeqi Fei, Zhenye Li, Dongyi Wang, Chao Ni
The Rapid Detection Of Foreign Fibers In Seed Cotton Based On Hyperspectral Band Selection And A Lightweight Neural Network, Yeqi Fei, Zhenye Li, Dongyi Wang, Chao Ni
Biological and Agricultural Engineering Faculty Publications and Presentations
Contamination with foreign fibers-such as mulch films and polypropylene strands-during cotton harvesting and processing severely compromises fiber quality. The traditional detection methods often fail to identify fine impurities under visible light, while full-spectrum hyperspectral imaging (HSI) techniques-despite their effectiveness-tend to be prohibitively expensive and computationally intensive. Specifically, the vast amount of redundant spectral information in full-spectrum HSI escalates both the system's costs and processing challenges. To address these challenges, this study presents an intelligent detection framework that integrates optimized spectral band selection with a lightweight neural network. A novel hybrid Harris Hawks-Whale Optimization Operator (HWOO) is employed to isolate 12 …
Meshlet Rendering Using D3d12 Mesh Shading Pipeline, Anishva Bardhan
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
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
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
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
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
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 …
Machine Learning-Driven Optimization Of Piezoelectric Energy Harvesters For Low-Frequency Applications, Kyrillos Selim, Login Moustafa, Sameh O. Abdellatif
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 …
Enhancing Water Supply Resilience & Sustainability: Potential Solutions To Address Water Scarcity In Bogotá, Colombia, Sophia Alvarez Wong
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 …
Wildfire Hydrologic Impacts, Kathleen E. Inman
Wildfire Hydrologic Impacts, Kathleen E. Inman
Theses and Dissertations
Wildfires are essential processes for certain ecosystems but are increasing in severity and occurrence. These increases are negatively changing hydrology. Anticipating the hydrologic changes is necessary for management of effected watersheds, infrastructure, and downstream users. This study hypothesized land cover changes post-fire would increase water temperature and discharge in burned watersheds located in the Willamette Basin. This study (1) evaluated the change in estimated curve numbers (CN) from land cover pre-fire and post-fire to assess expected runoff impacts in watersheds, and (2) identified the significance of actual water temperature and discharge changes using non-parametric statistical analysis. An unburned watershed and …
Advancing Wood Chip Moisture Content Prediction Using Advanced Generative Ai Techniques, Daniel Esteban Marulanda
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 …
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 …
06.16.2025 Ored Connect, Liz Williamson
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
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 …
Development Of Non-Precious Iron-Cobalt Alloy Catalyst For Electrocatalytic Reaction, Harsh Panchal
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 …