bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development of an Autonomous Robotic Snowplow for Residential Use
Authors: Suer Alexander , Yang Xun , Yang Rui , You Xuzhen , Zhang Zhihao , Dong Janet 
Published: February 2024

Abstract
Shoveling driveways and sidewalks on a cold snow day is a very physically demanding task often leading to a wide variety of health issues and injuries for those who shovel or plow the snow. This paper describes the development of a domestic autonomous snowplow, including the design and building of the mechanical structure and drive system, the strategies and algorithms to achieve autonomy, including path planning and position locating, and the analysis and control for expected performance. The robotic snowplow is designed to be able to clear 3–5 inches of snow and operate at 4 mph while lasting up to 4 hours per charge. The snowplow is fully battery-powered, which requires nearly zero maintenance compared to its gasoline counterparts. This also brings benefits such as high reliability, low running cost, zero-emission, and low noise. It is expected that such a snowplow will benefit small homeowners by increasing the quality of their life and reducing the risk of injuries and health issues.
Investigation of Mixtures of Temperature Fields on Micro-Fin Enhanced Surfaces Using Large Eddy Simulations
Authors: Li Puxuan , Alrifaai Hatim , Eckels Steven 
Published: February 2024

Abstract
Internally enhanced surfaces such as micro-fins are an important class of heat transfer enhancement in commercial applications such as air conditioners and refrigerators. In our previous studies, it was found that flow structures affected heat transfer and drag forces on micro-fin enhanced surfaces significantly. The current paper is a continuous study to explore the relationships between flow structures and temperature fields. Several problems about the relationships were discussed and solved. First, the study discussed the factors affecting the mixtures of temperature fields. Second, the paper determined how flow structures affected the mixtures of temperature fields and enhanced heat transfer on micro-fin enhanced surfaces. We utilized a large eddy simulation (LES) with a localized, dynamic kinetic energy, subgrid-scale model (LDKM) to predict turbulent flow structures. The numerical simulation included both heat conduction in the metal structure and heat convection on the solid-fluid interface. The Q criterion was applied to identify turbulent flow structures. The accuracy of the numerical model was verified by a Particle-image Velocimetry (PIV) system and a Planar Laser Induced Fluorescence technique (PLIF). Three cases were investigated in this study representing three different Reynolds numbers.
Shielding of Spacecraft and Satellites From Micrometeorites and Space Debris
Authors: Thakkar Nishant , Piovesan Davide 
Published: February 2024

Abstract
Astronauts and spacecraft have had frequent run-ins with micrometeorites and other orbital debris. Moreover, hypervelocity impacts by micrometeoroids and orbital debris are significant hazards for spacecraft and satellites. Thermal protection and hypervelocity impact protection can be combined in a multi-layer insulation blanket. Materials like Kevlar, Twaron, and other aramid materials are used as fabric layers in the space shields. Other potential materials are Ultra High Molecular Weight Polyethylene (UHMWPE) or Dyneema and ceramic-based structures can be used as well. These materials, when used in layers can provide a good amount of protection from micrometeorites and space/orbital debris. This review paper focuses on impact testing and material characteristics done in previous studies regarding materials like Kevlar, Dyneema, and Ceramic materials. MMOD shielding capability is influenced by both, configuration, and material selection. Composites and materials with a high strength-to-weight ratio are used in the shields. Several layers like disrupt layer, standoff layer, and stopper layer are used to shield the spacecraft depending on the properties of the material used. The risk and probability of penetration due to hypervelocity impacts remain a big threat to space missions. The review also discusses experiments done on current systems related to MMOD shielding.
Development of Portable Ground Control Station for Real-Time Data Monitoring of an Unmanned Surface Vessel
Authors: Kotian Rakshith , Umesh Pruthviraj , Gangadharan K. V. , Shetty Devdas 
Published: February 2024

Abstract
This paper presents a portable ground control station for unmanned surface vessels (USVs) that can operate autonomously or remotely without crew onboard. USVs equipped with various sensors, propulsion systems, and communication equipment perform a wide range of tasks, including scientific research, environmental monitoring, and maritime security. The Ground Control Station (GCS) is essential to the operation of a USV, enabling remote control and monitoring of the vehicle, allowing it to operate autonomously or semi-autonomously. A portable GCS allows the operator to bring the system to remote or difficult-to-access locations, enabling the USV to operate in a wider range of environments and conditions. The paper describes the hardware architecture of the system, with an emphasis on navigational sensors for guidance and control. The hardware components include controllers, communication equipment, and sensors such as GPS, and sonar. These sensors provide the USV with real-time information about its position, velocity, and environment, enabling informed navigation and control decisions. The software includes control algorithms, user interfaces, and data processing tools that allow the operator to control and monitor the USV’s operations. The user-friendly software interfaces and clear feedback make it easy for the operator to manage the USV’s movements and data collection. Overall, the paper provides insights into the design and implementation of a system for controlling USVs, focusing on hardware, User interface and, and Mission planning.
Robot-Based Adaptive Training of a Repetitive Motion Shows the Potential to Outperform Transient, Passive and Active Learning
Authors: Zhang Danqing , Weaver Jonathan M. 
Published: February 2024

Abstract
This study explores the relationship between humans and robots from the perspective of autonomy, introducing a novel concept for teaching humans new, repetitive motions to develop their muscle memory. The research builds on the authors’ previous work by moving beyond the use of a dynamically autonomous robot (Type X robot) for transient training, a progressive robotic-assisted training approach where robot assistance is strong at first but fades over time. Instead, we propose a new concept of adaptive training, where the compensation of robotic assistance is real-time evaluated and multi-factor based. In this work, an additional subject was tested using the adaptive training approach. The initial test result suggests the potential for adaptive training to outperform transient training.
An Assessment of Vehicle Electrification Within the United States Army
Authors: Langone Gregory A. , Kass Kyle J. , Lozano Noah A. , Budoff Paul F. , West Benjamin S. , Lueders Jacob T. , Levine Charles R. , Van Poppel Bret P. , Davidson F. Todd 
Published: February 2024

Abstract
The United States Army is currently undergoing an initiative to modernize its installations and vehicles to reduce logistical demand, mitigate the effects of climate change, and improve the resilience of Army infrastructure. Published in 2022, the Army Climate Strategy (ACS) [1] provides a timeline for the widespread electrification of both tactical and non-tactical vehicle fleets throughout the next thirty years. The implementation of electric vehicles (EVs) in Army tactical and non-tactical operations requires proactive design solutions for energy and logistics systems to maintain capabilities and responsibly manage costs through this transition. This paper responds to three questions that arise in this modernization process. First, a framework for prioritization of which vehicles to replace with EVs is developed by inspecting lifecycle cost and carbon footprint. Second, a simulation tool is developed to suggest the number, type, and location of chargers to support the non-tactical EV fleet on an Army installation. Finally, energy production and conversion pathways are inspected for their viability, cost, and carbon footprint to identify the most advantageous paradigms for fueling tactical vehicles. The summative response to these three topics expands the base of knowledge informing Army vehicle infrastructure modernization.
Continuously Variable Heterogeneous Density 3D Map Generation for Ubiquitous Drones
Authors: Tatoglu Akin , McClurkin Emma , Vaka Mohit Sai , Kelly Rasheed , Diehl Edward , Sohn Kiwon , Altuger-Genc Gonca 
Published: February 2024

Abstract
The goal of this project is to develop a dependable and effective LiDAR scanner for autonomous quadcopters to map the landscape. The LiDAR sensor enables scanning of the ground, locating obstructions, and determining secure landing areas. For secure navigation in uncharted territory, the system creates a 3D point cloud map. By scanning at the precise target angle, the control system makes sure that accurate data gathering is accomplished. The control system’s servo is controlled by the IMU, allowing the LiDAR sensor to adapt in response to quadcopter motion. With an effective range of 100 meters, the terrain scanner is essential for selecting a secure landing spot for cargo delivery. The operating code of the gadget enables interoperability with more potent LiDAR units for prolonged use. The LiDAR terrain scanner has both physical and financial capabilities. The strategy attempts to deliver technologies at the intermediate level with easily controllable design complexity. The system is tested in an outdoor environment with variable density scans. Sparse and dense maps are compared for lane segmentation purposes.
Effect of Internal Structure on Warpage in a Large-Scale Additive Manufacturing Process With Bio-Derived Composites
Authors: Jo Eonyeon , Copenhaver Katie , Pokkalla Deepak Kumar , Smith Tyler , Vaidya Uday , Kunc Vlastimil , Ozcan Soydan , Kim Seokpum 
Published: February 2024

Abstract
Extrusion-based large-format additive manufacturing (LFAM) often results in unintended deformation and failures due to thermal residual stress between layers. This LFAM involves a hot molten polymer deposited on a previously deposited and cooled layer, generating a temperature mismatch between the layers. The temperature discrepancy causes a thermal contraction mismatch, generating thermal residual stress. Due to the residual stress, printed structures experience warpage and delamination Therefore, understanding the heat distribution behavior is essential to preventing undesired deformation and failures. The goal of this study is to investigate the effect of infill patterns on heat distribution and deformation in an LFAM system. Wood fiber-reinforced polylactic acid was used as a sustainable and low-cost reinforcement material. A numerical model was developed to predict the temperature and deformation field with thermo-mechanical properties, which were measured by a dynamic mechanical analysis and a thermal expansion test. Simulations were performed on a box geometry with three different infill patterns. The simulation model was verified with temperature data gathered from an infrared camera. The results show good agreement between predicted and measured temperature profiles. The developed simulation model was applied to a roof tray with different infill patterns for a case study. We found that the different thermal mass distributions resulting from the various infill patterns affected the heat distribution and deformation. These findings contribute to a better understanding of the thermal and mechanical behavior of LFAM.
A Comparison of the Designs of Shell-Type and Core-Type Solid State Transformers With Convex Optimization
Authors: Lambada Puneeth Raj , Wang Xin 
Published: February 2024

Abstract
This paper presents a computer-aided minimum mass design of both shell and core type medium frequency single phase solid state transformers using split winding and Litz wires. The aim of the study is to compare the performance of these two designs in terms of their mass and efficiency. The design process involves modeling the transformers using geometric programming, which allows for a global optimum solution to be found for a given set of constraints. The models are optimized for minimum mass while maintaining a fixed power rating and voltage level. The study finds that the core type transformer has a lower mass than the shell type transformer. However, the shell type transformer has a higher efficiency than the core type transformer. The use of split winding and Litz wires in both designs significantly improves the efficiency and reduces the mass of the transformers. The paper concludes that the choice between a shell type and core type transformer ultimately depends on the specific requirements of the application, as each design has its own advantages and disadvantages. However, the use of split winding and Litz wires is recommended in both designs to improve efficiency and reduce mass. Overall, this study provides valuable insights into the design of medium frequency single phase solid state transformers, and the use of computer-aided design methods to optimize their performance.
Analysis of 100kW Fuel Cell Electric Vehicle System Component Characteristics in Case of Sudden Load Change Using Modeling
Authors: Kim Younghyeon , Yu Sangseok 
Published: February 2024

Abstract
A fuel cell hybrid electric vehicle (FCHEV) that combines multiple energy sources can compensate for the shortcomings of a pure fuel cell vehicle. Nevertheless, multiple energy sources increase the complexity of power system operating modes. Therefore, research to increase the efficiency and durability of FCHEVs has become one of the key technologies. In order to solve the problem of vehicle efficiency and durability, it is necessary to analyze the characteristics of each part at the vehicle system level, establish a control strategy suitable for the system characteristics, and conduct research on improving the efficiency of element parts.
In this study, a nonlinear dynamics model of a fuel cell system for a 100kW vehicle was developed and the characteristics of the parts according to each load change were confirmed. The system is largely composed of six parts: air supply system, hydrogen supply system, stack, battery, thermal management system, and power system. The characteristics of the system model were analyzed in low-load, medium-load, and high-load sections according to the speed profile, and the characteristics of each part were identified in the section where the load rapidly changed. It was confirmed that the temperature fluctuation range of the stack was the largest in the section where the load changed rapidly, and overshoot and undershoot occurred for up to 5 seconds when the load changed. Afterward, it was confirmed that the values in each part reached a normal state within 10 seconds. In addition, it was confirmed that in the case of the motor rpm in the rapidly changing section with high load, the output was lower than the actual parameter output by about 50 rpm for about 5 seconds and then gradually reached a steady state.
Lunar Dust Tolerance and Mitigation of Space Suits Through Nano Fabricated Electrostatic Cleaning
Authors: Harrigan Voss , Carter Korey , Gilmore Marcus , Xu Jiajun 
Published: February 2024

Abstract
In efforts to support the Artemis mission which seeks to return to the lunar surface, this research seeks to tackle one of the biggest issues faced on the lunar surface. Lunar soil is a hazardous threat to both spacesuit functionality and astronaut health. Due to characteristics such as being electrostatically charged, jagged edged and extremely fine in composition (&gt; 10 microns). For the past three years the research focus has been experimenting with previously established electrostatic cleaning systems that were not able to achieve 100% cleaning efficiency. Removing soil particles smaller than 10 microns became a main concern as they were the most difficult to remove. Previous iterations were able to achieve up to 98% cleaning efficiency and building upon this success the research developed new methods of transmitting an electrostatic field by using thin films which are more beneficial to spacesuit fabric. The system during certain test pushed the limits by achieving a cleaning efficiency of 99.5%. This study discusses the process of using systems engineering to successfully take the system from inception to completion. This process illustrates the project progress during major reviews such as System requirements review, preliminary design review and critical design review. Also, the schedule and budget concept of operations and system hierarchy is discussed as it progressed throughout the project. Various trade studies, reliability and safety of the project is also examined in this study. The system is finally built and tested to display its feasibility and efficiency to match that which was envisioned during the inception of the project.
Energy and Exergy Analysis of Coiled-Tube Heat Exchanger Operated With Al2O3 Nanofluid
Authors: Jassim Esam I. , Jasem Bashar 
Published: February 2024

Abstract
The purpose of this research is to experimentally evaluate the degree of enhancement in the heat transfer and entropy generation when nanoparticles mix with ordinary water. Several concentrations of Al2O3 nanoparticles at various flowrates are investigated to assess the enhancement in the exchanger’s (NTU) and efficiency. Results illustrate that the existence of nanoparticles enhances exchanger performance up to 27% and such enhancement is supplemented with the increase in the flow rate of the nanofluid. Furthermore, it is shown that adding more Al2O3 additive improves the energy exchange between the two fluids. Irreversibility due to thermal source is found to be decreased with the increase in the volume concentration of the nanofluid. In contrast, frictional source augments by 27% when 0.5% of Al2O3 is employed. However, the total irreversibility decreases by 47%. Such reduction fosters the exergy efficiency by 53% at volume concentration of 0.5% and nanofluid Reynolds number of 270.
Development of a Bio-Chair Using Electromygraphic Actuation for Rehabilitation Excercises
Authors: Bellannagari Pranav , Zaidi Sohail H. , Viswanathan Vimal 
Published: February 2024

Abstract
Traditional rehabilitation exercises are required for patients who have partially lost their mobility and intend to regain it to walk freely without any external assistance. Selective exoskeleton devices are commercially availble that rely on mechanical systems to conduct such rehabilitation exercises. Such devices are expensive and are not suitable for patients who are unable to stand. In the current work, a commercially available wheelchair is modified to incorporate new features of the proposed bio-chair. In order to operate the leg supporting plates, several components, including ball-screw mechanical actuators, motors, and L-shaped power transmitting shafts, were conceived and built. Ball screw mechanical actuators and motor holders were made via 3D printing. The angular motion of the leg supporting plates was used to calibrate the linear movement of the ball-screw nut. To determine the motors that are most suitable for operation by providing enough torque, basic calculations were performed. A unique feature of the bio-chair is that it enables the user to use his leg muscle’s power to trigger the bio-chair operation to conduct rehabilitation exercises to regain his/her mobility. The final design is fabricated and tested in this work. Initial operation results are included.
A Fully-Dense Deep Neural Network Method for the Inverse Transient Heat Transfer Problem
Authors: Bazgir Adib , Zhang Yuwen 
Published: February 2024

Abstract
It is necessary to estimate the temperature field accurately during manufacturing and heat treatment processes to perform an effective manufacturing procedure. Under some situations, the front surface temperature can be determined indirectly by the solution of an inverse heat conduction problem (IHCP) based on the transient temperature or heat flux measurements taken at the back surface. This study investigates the capability of a Deep Neural Network (DNN) approach for predicting the front surface temperature and heat flux from the measured back surface parameters. At the early stage, the back surface temperature and heat flux are determined using a direct Python script code. Then, the inverse solution is applied with the help of the fully dense DNN approach. To prevent overfit and non-generalization issues, the regularization and dropout techniques are embedded into the neural network framework. The results reveal that the DNN approach provides more accurate prediction compared to previous mathematical frameworks such as Conjugate Gradient Method (CGM). Moreover, the model is tested by noisy data (from 1% to 10%) causing instabilities in the recovered front surface conditions. Despite of the niose presence, the model can overcome this difficulty and is able to predict the desired parameters with a good accordance.
Leveraging Probabilistic Risk Assessment and Machine Learning for Safety and Cost Optimization in HAZMAT Transportation
Authors: Prins Molly , O’Connell Thomas M. , Earthperson Arjun , Alzahrani Yahya A. , Diaconeasa Mihai A. 
Published: February 2024

Abstract
Transportation systems play a pivotal role in modern society, but they are not without inherent risks and inefficiencies. This paper explores the integration of Probabilistic Risk Assessment (PRA) and Machine Learning (ML) techniques to enhance safety and cost optimization in hazardous materials (HAZMAT) transportation. Traditional PRA methods, while robust, are limited by the quality and quantity of data available for analysis. ML techniques can address these limitations by analyzing large datasets, identifying patterns, and making accurate predictions. The integration of ML techniques into PRA can enhance data analysis, prediction capabilities, routing decisions, resource allocation, and decision-making processes in HAZMAT transportation. This paper presents a comprehensive literature review on PRA and ML within the transportation industry, discusses the potential benefits of integrating these approaches, examines the challenges associated with transportation accident data, and suggests areas for further research and improvements in HAZMAT transportation safety analysis.