bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improving Road Safety With Human-In-The-Loop Bayesian Optimization Using Driver Vision Obstruction Simulations
Authors: Firouzi M. Amin , Jetton Cole , Bhaskaran Vignesh , Hoyle Christopher , Demirel H. Onan 
Published: January 2025

Abstract
It is important to improve driver visibility to reduce the incidence of vehicle-related accidents. One necessary area of improvement is to reduce the vision obstruction created by the A-pillar, which is the forwardmost support structure that obscures the driver’s vision. This can be done by creating holes through the A-pillar; however, designing and testing these configurations is time-consuming and computationally expensive. There is a need for a method to guide the design of these problems — one that considers the expensiveness of simulations and allows engineers to find creative solutions in an efficient manner. This paper proposes a novel methodology that uses batch Bayesian optimization to guide the design of these A-pillars. In it, designers are presented with multiple design targets and design targets to meet those specifications. Each design is then tested using high-fidelity simulations to capture the visibility of a potential accident target. The method then creates surrogate models of the visibility and feasibility of the design targets. We propose using batch Bayesian optimization to find new design targets that are better than before. We successfully demonstrated this method in a scenario where the A-pillar obstructs the view of a bicycle. This study shows how Bayesian optimization can work in conjunction with creative solutions and driver vision simulations to improve designs and lead to solutions that reduce the potential for accidents.
Novel Tubular Auxetic Metamaterial for Energy Absorption Applications
Authors: H. ZainElabdeen Ibrahim , Umer Rehan , Cantwell Wesley , Khan Kamran A. 
Published: January 2025

Abstract
This study introduces a novel layered re-entrant tubular structure manufactured through fused deposition modeling (FDM) aimed at enhancing energy absorption capabilities in demanding engineering applications. Quasi-static compression tests were conducted to evaluate the structure’s mechanical properties and energy absorption, compared with traditional auxetic design. While elastic modulus and compressive strength were comparable to conventional auxetic models, our findings demonstrate an 85% increase in specific energy absorption in the new design, attributed to enhanced deformation mode enabled by the layering technique. These results underscore the potential of advanced layering methods to significantly improve the performance of auxetic structures in various engineering applications.
Advancing Autonomous Robotics: Integrating Mecanum Wheels, LiDAR, and SLAM for Enhanced Mobility and Navigation Through Student Involvement
Authors: Chiou Richard Y. , Vasudevan Nijanthan , Senthilvel Kavitha Arjuna Karthikeyan , Tseng Tzu-Liang (Bill) 
Published: January 2025

Abstract
This study unveils an advanced autonomous mobile robot (AMR) designed as a practical educational module for students, featuring Mecanum wheels, LiDAR, and integrated through a comprehensive SLAM algorithm, all within the framework of the Robot Operating System (ROS). The AMR’s use of Mecanum wheels affords it unparalleled agility and the capability to maneuver omnidirectionally in intricate settings. LiDAR technology enhances the robot’s ability to generate detailed spatial maps, crucial for real-time navigation and obstacle avoidance. Through experimental validation in a controlled laboratory environment, the AMR demonstrated superior navigational accuracy and adaptability to evolving conditions. This hands-on educational approach not only underlines the robot’s effectiveness in navigating real-world challenges but also positions it as an adaptable solution for future automation tasks, emphasizing the potential for its application across a broad spectrum of industrial and commercial fields.
Investigating the Design and Locations of Inlet and Exhaust Diffusers and Airflow Patterns and Airborne Contaminants in Surgical Settings
Authors: Burzo Mihai G. , Kokash Hussein , Khanafer Khalil 
Published: January 2025

Abstract
Maintaining air quality and thermal comfort in operating rooms (ORs) is crucial for the health, safety and well-being of patients and medical staff. During surgical procedures, various gases are emitted, including volatile organic compounds (VOCs) from disinfectants, anesthetic gases, pathogens, and smoke from high-frequency electric knives. This surgical smoke, laden with harmful particles, is often termed a “silent killer”, posing a significant contamination risk. Ventilation systems are crucial for maintaining a comfortable thermal environment and regulating airborne particle concentrations within prescribed limits critical for sterile conditions in ORs. We aim to comprehensively assess airflow dynamics, temperature distribution and contaminant distribution in typical ORs using numerical analysis. We proposed new air diffuser arrangements and a corresponding optimization framework to effectively control airborne contaminants, ensuring high standards of indoor air quality and thermal comfort during surgical procedures. Two airflow configurations were considered: Modified Laminar Airflow (M-LAF) and Coanda diffuser layouts. It was found that the M-LAF, with adjusted inlet velocities at the diffuser corners, enhances airflow uniformity around medical personnel and patients, outperforming traditional setups. Our results show a reduction in Air Diffusion Performance Index (ADPI) of 75.6%, 35.6%, and 83.3% between M-LAF and LAF at 0.15 m/s, 0.5 m/s, and 0.75 m/s, respectively. However, it also indicates an increase in Local Air Change Index (LACI) of 50.2% at 0.15 m/s and 172.5% at 0.75 m/s, while LACI decreases by 72.5% between LAF and M-LAF at 0.5 m/s. Particle simulations confirm that the M-LAF better disperses smoke particles, suggesting lower contamination risks during surgery. The Coanda diffuser layout also improves airflow and temperature distribution, ensuring better thermal comfort and is expected to offer improved energy savings. ADPI for Coanda diffuser was found to increase by 88% compared with LAF. Its design effectively removes airborne particles by directing them to exit diffusers, decreasing the concentration near staff. Altogether, the research indicates that these designs could substantially improve ventilation in healthcare settings, boosting both thermal comfort and air quality in ORs.
Investigation of Thermal Conductivity of Partial Periodic Si/Ge Superlattice in Si Nanowire
Authors: Rafi Kamrul Hasan , Mojumder Azmir Hasan , Morshed A. K. M. Monjur , Paul Titan C. 
Published: January 2025

Abstract
Non-equilibrium molecular dynamics simulation (NEMD) is used to look at the thermal conductivity (TC) of partial periodic Si/Ge superlattice nanowires (SLNW). Compared to bulk Si, Si nanowire has lower thermal conductivity. Doping of Ge atoms as periodic bands lower the thermal conductivity of the system from both Si and Ge systems of the same dimension respectively. To comprehend the relationship between thermal conductivity and the position of the superlattice structure, the thermal conductivity for two partial Si/Ge superlattice layers put in various places has been examined. The SL band’s midway location is where thermal conductivity is at its lowest. In accordance with where the Si/Ge bands are located, thermal conductivity needs to be examined. As the band’s location gradually changed from being close to the heat sink to the heat source, thermal conductivity gradually decreased. Thermal conductivity can be reduced by 30%–40%, depending on where the band is located. The activation of phonons of various energies at various places and the phonon scattering at the Si/Ge contact are what cause these effects of the SL structure in the Si nanowire. The Vibrational Density of States (VDOS) analysis of the phonon at various frequencies explains these phonon behaviors, which in turn explains the various thermal conductivity results for various systems in this study. According to the findings, there is a practical and efficient technique to lower the thermal conductivity of semiconductor materials for a variety of thermoelectric applications.
Distributed Hyperdimensional Computing for Real-Time Data Aggregation and Interpretable Quality Monitoring in Manufacturing
Authors: Chen Zhiling , Hoang Danny , Chen Ruimin , Imani Farhad 
Published: January 2025

Abstract
The integration of diverse sensors in manufacturing processes offers enhanced potential for real-time quality assurance through the collection of complementary data. However, the limited interpretability of current machine learning models often hampers the effective discrimination of each sensor’s unique contributions, primarily due to the complexity of decoding the interdependencies among various signals. This paper proposes a novel computational framework, Distributed Hyperdimensional Computing (DHDC), which is designed to leverage efficient cognitive operations, such as binding and bundling, for interpretable learning across multi-level sensor data. DHDC operates by encoding and aggregating data systematically across a distributed architecture, thereby enhancing transparency in computational efficiency. Our real-world experimental results on the 5-axis machining for the fabrication of the counterbore hole feature demonstrate that the framework not only effectively characterizes the impact of individual sensors but also achieves a high degree of predictive accuracy, as evidenced by an F1 score of 90.4 ± 0.013%. The proposed framework holds the potential for interpretable and scalable quality control in distributed additive and subtractive manufacturing.
Spatial Variation of Heat Transfer of a Fluidic Oscillator Jet Impinging on a Flat Surface
Authors: Gomes Rita C. S. , Barbosa Flavia V. , Constantino Erany , Teixeira Senhorinha C. F. , Teixeira José C. F. 
Published: January 2025

Abstract
Fluidic oscillators are non-moving devices that generate a periodic oscillating jet. The most common configuration is the Double Feedback Loop oscillator in which the Coanda effect of a fluid interaction with a curved surface generates two periodic feedback fluxes that produce a sweeping jet. In heat transfer applications, their performance compares with impinging jets, although for low Reynolds numbers they appear to be more effective.
The present work investigates the spatial variation of the convective heat transfer coefficient produced by a fluidic oscillator over a flat surface. The experimental set up consists of an oscillator made up of Plexiglas with an outlet orifice with a hydraulic diameter of 9.7 mm. The target plate, located 6 diameters downstream, contains five OMEGA® HFS4 thin-film heat flux sensors heat flux sensors, mounted flush to the surface. The flow field was measured by means of a two color, two component, LDA system, operating in backscatter mode. The experiments were carried out with air at flow rates of 4.5 up to 30.5 L/min over a surface, at a constant temperature of 120 °C.
The results show that the heat transfer coefficient profile evolves from a single peak centered around the stagnation point at low Reynolds numbers to a double peak profile at higher Reynolds numbers which suggests a more uniform heat dissipation rate over the surface when compared with an impinging jet.
Distributed Real-Time Soil Saturation Assessment in Levees Using a Network of Wireless Sensor Packages With Conductivity Probes
Authors: Chowdhury Puja , Crews James , Mokhtar Ayman , Oruganti Sai Durga Rithvik , Wyk Ryan Van , Downey Austin R. J. , Flemming Malichi , Bakos Jason D. , Imran Jasim , Khan Sadik 
Published: January 2025

Abstract
Levees play a critical role in safeguarding communities and assets from flooding, acting as essential defenses against the devastating impacts of inundation. Yet, earthen levees are prone to breaches, especially in the face of swift floodwaters. Distributed low-cost sensor networks offer the potential to generate spatial maps illustrating soil moisture levels. Long-term monitoring of these spatial maps could identify vulnerable zones in the levee while providing an understanding of how climate change affects levee stability. This study presents an investigation into spatial monitoring of soil saturation in levees using a wireless network of UAV-deployable sensing spike packages. The goal of this paper is to demonstrate the use of these sensors for assessing soil conductivity levels in sand-filled embankments. The obtained soil conductivity levels are crucial for determining soil saturation. The developed sensing spikes consist of a spike that penetrates the ground and measures conductivity between two electrically conductive contacts. The sensing spike consists of microprocessors for edge computing, and wireless data communication systems that report data to a way station in real-time. To validate the efficacy of the developed sensors, a flume test is developed as a replica of a levee and monitored under controlled water flow conditions. The analysis of data at different times revealed the progression of moisture throughout the earthen embankment. Initially, the soil is almost dry. As the controlled water flow proceeds, the soil becomes partially saturated, with the final stage showing a dominant presence of saturated soil. The collected data sampled at the measurement points is expanded to a continuous moisture profile using kriging. Gaussian kriging, also known as ordinary kriging, is one of the commonly used variants of the kriging method. In Gaussian kriging, the estimation of values at unsampled locations is based on a linear combination of nearby data points, with weights determined by their spatial relationships. The Gaussian assumption implies that the errors in the estimation process follow a normal distribution. The extended knowledge about saturation levels obtained through kriging can lead to insights for predicting vulnerable areas and preempting potential failures. Overall, this study paves the way for further development of a wireless network of sensing spike packages as a UAV-deployable system for levee health assessment and improved infrastructure management.
Effects of Biodegradable Aerogel Insulation in High-Powered Rocketry
Authors: Purdy Ellyssa , Thota Jagadeep , Islam Mohammad Rasedul , Staker Jacob , Tovar Andres , Siegel Amanda 
Published: January 2025

Abstract
Current flight configurations of high-powered rockets require lightweight materials to protect payloads and flight avionics. These rockets contain single-use parts comprised of nylon, polystyrene, and other non-biodegradable materials that harm soils and ecosystems upon disposal. This study determines the efficiency of flight avionics within high-powered rockets when enclosed by a biodegradable and compostable aerogel composite utilized for insulating applications. In pursuit of maximizing flight duration, the rocket undergoes optimization procedures. This involves utilizing computer-aided design (CAD) modeling techniques coupled with numerical flight simulation and graphical programs. These modeling and analysis methods allow the systematic exploration of flight configurations to ultimately enhance flight performance and the design of propulsion and recovery systems. During flight, the Internal Data Acquisition System (IDAS) will monitor the pressure, temperature, and humidity within the avionics bay, while the flight avionics will record the external counterparts. The findings of the experiment are dependent on the degrees of variation observed in comparisons between predicted and actual flight performance as well as internal and external parameter datasets. Proportional degrees of variation indicate that optimization of aerogel composite properties promotes enhancements in flight avionics performance. Alternatively, the degrees of variation possess an inversely proportional relationship. On the one hand, minimal environmental variation effectively maintains flight avionics but functions solely as a water barrier between the payload and environment. On the other hand, excessive variation adversely impacts flight avionics but provides stable internal conditions for payloads. An optimal balance is achieved when the efficiency of flight avionics controls is maintained while protecting the payload from environmental variance. The impact of the aerogel composite on flight avionics efficiency highlights the benefits biodegradable and compostable aerogel materials have in the aerospace industry, mitigating the harmful effects of current single-use, non-biodegradable plastics.
Commercial Hydrogen Vehicle Power Distribution Simulation Using Fuzzy Control
Authors: Han Jaesu , Yu Sangseok 
Published: January 2025

Abstract
Proton exchange membrane fuel cell (PEMFC) are gaining attention in various power industries due to their high efficiency, eco-friendly nature, and stability. In the automotive industry, they are favored for their low operating temperature and suitability for frequent start-stop cycles, leading to significant research and development. However, challenges such as a lack of historical data and high confidentiality hinder progress in hydrogen mobility research. One major issue is the power distribution between the fuel cell and battery, impacting vehicle-level efficiency and durability.
Hydrogen vehicles require sophisticated management strategies to maintain battery State of charge (SoC) in a high-efficiency range while avoiding rapid durability degradation of fuel cells at high voltages. Studies by Jahromi, Pei, and Yue have explored vehicle-level hydrogen mobility but lack focus on power distribution control systems. Effective control systems are crucial for balancing efficiency and durability.
This study developed a simulation model of hydrogen mobility with fuel cells and batteries, employing a fuzzy control-based power distribution strategy. Specifications for fuel cell, battery, and motor models were based on previous studies. An EMS was used to manage power distribution, and fuzzy controllers ensured smooth transitions between current control levels, enhancing performance and fuel cell durability.
A Comparative Classification Study on the Use of Audible Acoustic Emission Signals for Surface Roughness Condition Monitoring in Shoulder Milling of Steel
Authors: Banerjee Amit , Abu-Mahfouz Issam , Rahman Esfakur Ahm 
Published: January 2025

Abstract
Despite the current advances in additive manufacturing, subtractive manufacturing methods such as machining still account for the major share of modern manufacturing. Surface roughness of a machined product is a crucial parameter that impacts the functionality, assembly, and service life of the product. Surface finish texture of machined components is too complex for accurate prediction when using analytical or computer simulation techniques. This is because there are numerous parameters relating to the material of the workpiece, cutting tool, and machining process conditions. Therefore, machine learning (ML) techniques are becoming more popular in creating model-based methods that are capable of providing more reliable real-time surface quality prediction. The aim of this study is to develop ML models to predict the surface roughness in shoulder milling of steel parts using audible acoustic emission data produced during machining. Microphones are used to pick up acoustic data that is highly correlated to acoustic waves produced by the machining process. These sound measuring devices are non-invasive and can be easily integrated within the machining envelope without disrupting or stopping the machining process. Features are then extracted from the acoustic data that include averaged wavelet decomposition quantities, statistical quantities, and filtered time signatures of the sound waves. These are then (1) used to training classifiers using important features or a combination of features that have highly corelated to surface finish, and (2) develop a learning model to use these features to predict the surface roughness in shoulder milling. In this study, we use a variety of dimensionality reduction algorithms in the training phase. In the learning model, we use classification algorithms and develop suitable classifiers. The overall objective is to develop a reliable and robust predictive tool with potential for practical implementation in a real-time industrial machine tool installation for process monitoring.
Investigating the Effect of Single-Phase Liquid Immersion Cooling on TG-400 Substrate Core’s Thermomechanical Characteristics
Authors: Suthar Rohit , Bansode Pratik , Tirupati Venkatachalam Venkateshwar Vishnu , Ede Naga Tejesh , Lakshminarayana Akshay , Bhandari Rabin , Sivakumar Akiilessh , Agonafer Dereje 
Published: January 2025

Abstract
The exponential increase in server power density and heat generation within data centers due to the processing and storage of massive data volumes has led to a significant focus on efficient cooling technologies. Conventional air-cooled data centers allocate a substantial portion of energy towards cooling information technology equipment (ITE), necessitating alternative cooling solutions. Single-phase liquid immersion cooling (SP-LIC) has emerged as a promising approach, offering enhanced thermal mass and efficient heat dissipation, particularly suitable for hyper-scale, edge, and modular data center applications.
This study investigates the impact of single-phase liquid immersion cooling fluids on the thermomechanical properties of the TG-400 substrate core, a vital component in electronic packaging. Our previous study focused on a different substrate core material, I-Speed, and now extends the analysis to TG-400. The key properties under scrutiny include the Elastic Modulus (E) and Glass Transition Temperature (Tg), critical for mechanical design and reliability assessment of electronic packages.
The research involves subjecting the TG-400 substrate core to thermal aging in various immersion cooling fluids, including synthetic hydrocarbon fluid (EC100) and Polyalphaolefin 6 (PAO 6), alongside exposure to ambient air. Aging occurs at two distinct temperatures, 85°C and 125°C, for 720 hours each. The study evaluates changes in complex modulus pre- and post-aging, providing insights into the material’s behavior under different thermal conditions and immersion cooling environments.
Furthermore, this research contributes to understanding the reliability and failure mechanisms associated with immersion cooling technologies, essential for advancing efficient and sustainable data center cooling strategies. By examining both the Elastic Modulus and Glass Transition Temperature of the TG-400 substrate core, this study enhances our knowledge of material compatibility and performance in immersive cooling settings, aiding in the development of robust electronic packaging designs for modern data center infrastructures.