Identification Of Thruster Faults In Underwater Vehicles By Using Custom Encodings In Spiking Neural Networks,
2026
Louisiana State University and Agricultural and Mechanical College
Identification Of Thruster Faults In Underwater Vehicles By Using Custom Encodings In Spiking Neural Networks, Donovan Gegg
LSU Master's Theses
Autonomous Underwater Vehicles (AUVs) are untethered robotic platforms used for tasks such as seafloor mapping, infrastructure inspection, and environmental monitoring. Recent technological advances have produced smaller, more affordable platforms, broadening access to research teams and small companies alike. This miniaturization comes at the cost of them handling drawbacks associated with a more compact machine such as reduced battery capacity as well as limited processing and sensing capabilities. These constraints make small-sized marine vehicle’s reliability critical as they can cause malfunctions, making the loss of a vehicle more likely. Actuator faults are particularly consequential as unintended and unstable control in an …
Experimental Study Of Dimpled Serpentine Reactors For Hydrogen Production Via Methanol Steam Reforming,
2026
Mechanical Power Engineering Department, Faculty of Engineering, Mansoura University, Mansoura, Egypt
Experimental Study Of Dimpled Serpentine Reactors For Hydrogen Production Via Methanol Steam Reforming, Mohamed I. Zeid, Mahmoud A. Shouman, Osama Abdelrehim, Ahmed M. Hamed
Mansoura Engineering Journal
Hydrogen is widely regarded as a clean energy carrier, with methanol steam reforming (MSR) emerging as a promising route for portable and on-board applications due to its favorable operating conditions and high hydrogen yield. Reactor geometry plays a decisive role in hydrogen productivity, pressure drop, and energy efficiency, yet the balance among these factors remains insufficiently addressed. In this study, three serpentine aluminum microreactors: a plain serpentine reactor (PSR), a rhombusdimple reactor (RDR), and a hemispherical-dimple reactor (HDR) were fabricated and coated with a copper (II) oxide, zinc oxide, aluminum oxide (CuO/ZnO/Al₂O₃) catalyst to experimentally investigate the effect of dimple …
Task-Based Analysis Of Augmented Reality In Collaborative Robotic Programming For Manufacturing Assembly,
2026
Michigan Technological University
Task-Based Analysis Of Augmented Reality In Collaborative Robotic Programming For Manufacturing Assembly, Medhavi Kamran, Snehesh Shrestha, Vinh Nguyen
Michigan Tech Publications
Augmented Reality (AR) is often promoted as a solution to the cognitive and physical demands of traditional Teach Pendant (TP) programming for collaborative robots. Although prior work has suggested advantages of the AR interface, many evaluations have been limited in scope and may not fully represent the complexities of real-world manufacturing tasks. This study compares the performance of an AR interface to that of a standard TP interface for manufacturing assembly tasks of varying difficulty. In a between-groups study, one group of operators completed standardized assembly tasks using the TP interface, while a separate group used the AR interface instead. …
Layer-Wise Printing Parameter Optimization For Laser Powder Bed Fusion,
2026
University of Missouri
Layer-Wise Printing Parameter Optimization For Laser Powder Bed Fusion, Chaoran Dou, Rongxuan Wang, Raghav Gnanasambandam, Jianzhi Li, Zhenyu James Kong
Manufacturing & Industrial Engineering Faculty Publications
Additive manufacturing (AM) is a transformative technology that enables the fabrication of complex geometries layer by layer. However, metal parts produced via AM processes such as laser powder bed fusion (LPBF) are prone to various defects, including porosity and deformation. These defects often result from suboptimal printing parameter settings. Traditional approaches typically aim to reduce defects by optimizing a fixed set of parameters for the entire part. However, such methods do not account for layer-wise variations in printing conditions caused by changes in geometry, heat transfer, and re-heating effects. While optimizing parameters for each layer could improve part quality, it …
Impact Of Glass Powder As A Sustainable Material On The Workability, Strength, And Durability Properties In High-Performance Basalt Fiber Reinforced Concrete: A Statistical Analysis,
2026
Department of Civil Engineering, College of Engineering, Bisha University, P.O. Box 67711, Bisha 61361, Saudi Arabia
Impact Of Glass Powder As A Sustainable Material On The Workability, Strength, And Durability Properties In High-Performance Basalt Fiber Reinforced Concrete: A Statistical Analysis, Ahmed Fathi Mohamed Salih
Journal of Sustainable Construction Materials and Technologies
The global construction sector is increasingly challenged to balance environmental sustainability with the growing demand for durable, high-performance materials. As cement production continues to be a major source of anthropogenic CO2 emissions, the incorporation of alternative, low-impact binders has become a key strategy for reducing the environmental footprint of concrete. In this context, glass powder (GP)—a finely ground industrial by-product rich in amorphous silica—has emerged as a promising partial replacement for Portland cement. Its pozzolanic reactivity contributes to improved hydration and matrix densification, while its use also supports circular economy principles by diverting waste glass from landfills. At the same …
Roadmap: Integrating Artificial Intelligence In Structural Health Monitoring Systems,
2026
University of South Carolina
Roadmap: Integrating Artificial Intelligence In Structural Health Monitoring Systems, Simon Laflamme, Erik Blasch, Flippo Ubertini, Zheng Liu, John Wertz, Christine Knott, Matthew Cherry, Eric Lindgren, Fu-Kuo Chang, Amrita Kumar, Jack Poole, Keith Worden, Austin Downey, Jie Wei, Patrick F. Musgrave, Adrian S. Wong, Guiseppe Quaranta, Marco Martino Rosso, Giuseppe Carlo Marano, Yu Chen, Et. Al.
Faculty Publications
Advances in computing and machine learning (ML) methods have led to a rapid rise in artificial intelligence (AI) research and applications in many fields. AI research benefitted from advances in computation hardware, collection and distribution of large data sets, and proliferation of software techniques. AI techniques include ML for provable results, deep learning for data exploration, reinforcement learning for control, and active learning for adaptive systems. Likewise, AI algorithms can handle large amounts of data, construct unknown representations, and provide a direct link between data and classification for decision making. These unmatched capabilities have been seen as a path to …
An Ambient Acoustic Ice-Fracturing Dataset Taken In Shallow Freshwater,
2026
Pennsylvania State University
An Ambient Acoustic Ice-Fracturing Dataset Taken In Shallow Freshwater, John Case, Andrew Barnard, Daniel Brown
Michigan Tech Publications
This paper describes an acoustic dataset collected on a frozen shallow freshwater lake between February and March of 2024. This collection took place over one full week on Portage Lake in the Upper Peninsula of Michigan, USA. The first sub-dataset consists of ambient ice and environmental noises collected by an array of hydrophones, microphones and geophones placed below, above and on the ice respectively. The second sub-dataset consists of instrumented force hammer impacts at a series of locations on the the ice with the corresponding response at each acoustic sensor. All acoustic data were recorded at a sample rate f …
Towards Sustainable Energy Storage: Evaluating The Performance Of Three Polymer Electrolytes For Zinc-Ion Batteries,
2026
University of South Carolina
Towards Sustainable Energy Storage: Evaluating The Performance Of Three Polymer Electrolytes For Zinc-Ion Batteries, Roya Rajabi, Shichen Sun, Buke Sun, Jamil A. Khan, Kevin Huang
Faculty Publications
Polymer electrolytes have been explored as an alternative to conventional aqueous electrolytes in zinc-ion batteries, particularly for flexible and wearable applications. Despite the increasing interest in polymer electrolyte-based zinc-ion batteries (ZIBs), their development is still in its early stages due to various challenges. In this study, we investigated three promising polymer electrolytes: CSAM (carboxyl methyl chitosan with acrylamide monomer), PAM (polyacrylamide monomer hydrogel electrolyte), and p-PBI (phosphate-doped polybenzimidazole solid electrolyte) with Zn(ClO4)2 and Zn(OTf)2, as electrolytes for zinc-ion batteries. The p-PBI solid electrolyte showed high mechanical stability and improved resistance to short-circuiting during cycling. The …
Towards Sustainable Energy Storage: Evaluating The Performance Of Three Polymer Electrolytes For Zinc-Ion Batteries,
2026
University of South Carolina
Towards Sustainable Energy Storage: Evaluating The Performance Of Three Polymer Electrolytes For Zinc-Ion Batteries, Roya Rajabi, Shichen Sun, Buke Wu, Jamil A. Khan, Kevin Huang
Faculty Publications
Polymer electrolytes have been explored as an alternative to conventional aqueous electrolytes in zinc-ion batteries, particularly for flexible and wearable applications. Despite the increasing interest in polymer electrolyte-based zinc-ion batteries (ZIBs), their development is still in its early stages due to various challenges. In this study, we investigated three promising polymer electrolytes: CSAM (carboxyl methyl chitosan with acrylamide monomer), PAM (polyacrylamide monomer hydrogel electrolyte), and p-PBI (phosphate-doped polybenzimidazole solid electrolyte) with Zn(ClO4)2 and Zn(OTf)2, as electrolytes for zinc-ion batteries. The p-PBI solid electrolyte showed high mechanical stability and improved resistance to short-circuiting during cycling. The presence of carboxyl groups in …
Reinforcement Learning For Imbalanced Data In Robotic Anomaly Detection Within Autonomous Manufacturing,
2026
The University of Texas Rio Grande Valley
Reinforcement Learning For Imbalanced Data In Robotic Anomaly Detection Within Autonomous Manufacturing, Salma Messaoudi, Ahmed Bendaouia, El Hassan Abdelwahed, Mohammed Ameksa, Hajar Mousannif, Jianzhi Li
Manufacturing & Industrial Engineering Faculty Publications
Ensuring reliable anomaly detection in industrial robots is critical for safe and autonomous manufacturing operations. However, it remains challenging due to temporal dependencies and class imbalance in sensor data. This study presents a reinforcement learning approach using Deep Q-Network (DQN) enhanced with Long Short-Term Memory (LSTM) and Gradient Boosting Machine (GBM) for robust anomaly detection in robotic systems. The proposed framework integrates an LSTM into the DQN policy to capture temporal patterns. It also introduces a novel GBM-based reward mechanism that mitigates class imbalance by applying SMOTE (Synthetic Minority Over-sampling Technique) after removing temporal dependencies. Experimental results demonstrate that this …
Supporting Data For Novel Approach For Quantifying The Impact Of Coherent Structures On The Turbulent Kinetic Energy Decay Rate,
2026
Utah State University
Supporting Data For Novel Approach For Quantifying The Impact Of Coherent Structures On The Turbulent Kinetic Energy Decay Rate, Tim Berk, Ankit Gautam
Browse all Datasets
This project investigates the influence of coherent structures on the decay of turbulent kinetic energy (TKE). The work was conducted as part of the PhD research in Mechanical Engineering by Ankit Gautam at Utah State University.
Thermal Management And Lubrication Characteristics Of Tungsten Disulfide (Ws2) Vegetable-Based Nanolubricants,
2026
The University of Texas Rio Grande Valley
Thermal Management And Lubrication Characteristics Of Tungsten Disulfide (Ws2) Vegetable-Based Nanolubricants, Jaime Taha-Tijerina, Dyana De Leon-Elizondo, Jade Mendieta, Leonardo Taha-Soto
Informatics and Engineering Systems Faculty Publications
Recent innovations with the aid of nanotechnology are more frequently seen in the industrial sectors. Lubricants are a high-end commodity resource used in many manufacturing processes; unfortunately, most of these lubricants are petroleum-based, which come with certain drawbacks, such as environmental aspects, handling issues and high costs. With the incorporation of nanostructures within fluids and lubricants, novel material alternatives are replacing conventional lubrication systems, maintaining the required thermophysical and tribological characteristics. This research provides an analysis of vegetable lubricant, castor oil (CO), and the effects of the incorporation of WS2 nanofiller at diverse filler fractions. A TEMPOS thermal analyzer device …
Decentralized Q-Learning Supervisory Control For Coordinated Multi-Loop Tuning In Pump Stations,
2026
Michigan Technological University
Decentralized Q-Learning Supervisory Control For Coordinated Multi-Loop Tuning In Pump Stations, David Brattley, Wayne Weaver
Michigan Tech Publications
This paper introduces a reinforced learning-based supervisory control architecture that oversees multiple Recursive Least Squares (RLS) based self-tuning pump controllers and determines when each loop is permitted to adapt its gains. The supervisor learns adaptation policies that minimize interaction between loops while preserving responsiveness to changing hydraulic conditions. A two-loop pump station simulation is used to evaluate performance under product changes and transient flow disturbances. The results show that the supervisory layer reduces the number of simultaneous adaptation events by over 70%, leading to a 32% lower pressure-tracking error and 45% fewer gain-induced oscillations compared to conventional independent adaptive control. …
Multimodal Thermal And Mechanical Characterization Of Cryopreservation Effects In Biological Cells,
2026
Louisiana State University and Agricultural and Mechanical College
Multimodal Thermal And Mechanical Characterization Of Cryopreservation Effects In Biological Cells, Subhrajyoti Sourav Kumar Kundu
LSU Master's Theses
Cryopreservation is critical for long-term storage of cells, tissues, organs, and reproductive cells in medicine, biotechnology, and conservation. However, its success is limited by ice formation and cryoinjury, prompting extensive research into analytical tools for understanding and improving cryopreservation outcomes. We outline the principles of each technique and how they are used to detect key thermal and physical events such as ice nucleation, vitrification, devitrification, and cryoinjury. DSC enables quantitative thermal characterization including critical cooling/warming rates (ranging from 1-200°C/min for various systems) and glass transition temperatures. Cryomicroscopy provides direct real time visualization of ice crystal dynamics, distinguishing intracellular versus extracellular …
Acoustic Levitation At Sub-Atmospheric Pressures And Reduced Temperatures: An Approach To Study Ice Crystal And Hypersonic Shockwave Interaction,
2026
University of North Dakota
Acoustic Levitation At Sub-Atmospheric Pressures And Reduced Temperatures: An Approach To Study Ice Crystal And Hypersonic Shockwave Interaction, Imteaz Osmani, David J. Delene, Hallie Boyer Chelmo
Graduate Research Achievement Day Posters
Micrometer-sized atmospheric ice crystals are commonly observed in high-altitude clouds. Inside clouds, they attach in different orientations, producing varied geometries, yet their formation mechanisms remain poorly understood. Their behavior under shock wave conditions remains underexplored due to lack of laboratory techniques capable of producing atmospherically realistic ice in controlled conditions. No experimental data and laboratory techniques exist to date on the interaction between atmospheric ice crystal aggregates and hypersonic shockwaves. To explore realistic atmospheric ice crystals’ thermodynamic and mechanical changes in hypersonic environments, we investigate the formation and behavior of ice crystal aggregates using acoustic levitation that avoids physical contact …
Influence Of Pulse Width On Energy Deposition And Temperature In Nanosecond-Pulsed Discharges,
2026
University of South Carolina
Influence Of Pulse Width On Energy Deposition And Temperature In Nanosecond-Pulsed Discharges, Christopher B. Reuter, Joshua B. Sinrud, Tanvir I. Farouk, Nicholas S. Dewey, Dmitri Kaganovich
Faculty Publications
Nanosecond-pulsed discharges are a promising method to enhance combustion but can generate significant levels of electromagnetic interference (EMI). Modifying the discharge pulse width is an unexplored option to reduce EMI, but few studies have examined how changing the pulse width affects discharge parameters such as energy and temperature. This study addresses this issue by systematically investigating how the pulse width affects the energy per pulse, breakdown time, rotational temperature, and vibrational temperature in air across different frequencies, flow velocities, and gap distances in a plasma-assisted flow tube. It is observed that the pulse width has a substantial impact on the …
Investigation Of Material Properties Of Thermoplastic And Thermoset Polymer Materials At Cryogenic Temperatures Using Molecular Dynamics,
2026
Michigan Technological University
Investigation Of Material Properties Of Thermoplastic And Thermoset Polymer Materials At Cryogenic Temperatures Using Molecular Dynamics, Swapnil S. Bamane, Sagar Patil, Khatereh Kashmari, Benjamin D. Jensen, Brett A. Bednarcyk, Evan J. Pineda, Jeffery Hinkley, Ozgur Keles, Jin Ho Kang, Gregory Odegard
Michigan Tech Publications
Cryogenic fluids, such as liquid hydrogen and liquid oxygen, are critical for space operations as rocket fuel and life support. The fluids need to be contained in tanks that can withstand the effects of cyclic thermal and pressure loading throughout their lifecycle. Polymer matrix composites (PMCs) are prime candidates for these tanks because of their low mass, which is important for fuel savings. Although advanced PMC systems have been developed for a wide range of engineering applications, insight is still needed to identify optimal polymer matrix materials for cryogenic structural applications. The objective of this study is to use molecular …
Elevating The Underrepresented And Marginalized Using Experiences In Stem (Lumens): A Stem Diversity And Inclusion Initiative,
2026
North Carolina Agricultural and Technical State University
Elevating The Underrepresented And Marginalized Using Experiences In Stem (Lumens): A Stem Diversity And Inclusion Initiative, Robert Cobb Jr, Paula E. Faulkner, Deiadra Modlin, Obinna Chiekezi, Victoria Cobbold, Madison Beaudoin
Journal of Research Initiatives
The study offered a 5-week summer immersion program to address the shortage of students from underrepresented populations enrolling in degree programs and seeking careers in science, technology, engineering, and mathematics (STEM). The study also addressed the importance of offering summer immersion programs to close the achievement gap. A quantitative descriptive design was used to gather data from participants related to STEM lessons during the program. Gender, grade level, and race served as the demographic variables. The study included 21 secondary students in grades 9–12. Pre- and post-tests assessed participants' knowledge gain regarding STEM lessons. Data analyzed with SPSS version 29 …
Design And Development Of A 12-Degree-Of-Freedom Quadruped Robot,
2026
California Polytechnic State University, San Luis Obispo
Design And Development Of A 12-Degree-Of-Freedom Quadruped Robot, Kai De La Cruz
Master's Theses
This thesis presents the design, analysis, and experimental validation of a 12-degree-of-freedom (DOF) quadruped robot developed as a research platform for legged locomotion and control. The system builds upon the Cal Poly Legged Robotics Group’s prior 8-DOF quadruped, addressing key limitations in manipulability, load distribution, and mechanical robustness by introducing a 3-DOF leg architecture.
The mechanical design emphasizes lightweight construction, structural integrity, and modularity to support future research extensions. Static and dynamic loading models were developed to inform component sizing and material selection. A carbon-fiber chassis and redesigned leg assemblies were fabricated and validated through finite element analysis and physical …
Portable Ice Cube Maker,
2026
California Polytechnic State University, San Luis Obispo
Portable Ice Cube Maker, Ayden Ziegler, Emiliano Hansen, Wyatt Engdahl, Dane Hansen
Mechanical Engineering
This Final Design Report outlines the senior design project undertaken by a team of mechanical engineering students at California Polytechnic State University, San Luis Obispo, for the development of a portable backpacking ice cube maker. The project aims to design, build, and test a lightweight, compact device that produces ice cubes for backpackers in remote outdoor environments. The goal is to create a functional prototype that is durable, user-friendly, and suitable for backcountry use. This document details background research, project objectives, and project plan, and current design status.
