bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimizing Cold Spraying Parameters of Metallic Coatings Deposited Onto Polymer Substrate
Authors: Abubakar Abba Abdulhamid , Arif Abul Fazal M. , Al-Athel Khaled S. , Akhtar Syed Sohail , Ankah Nestor , Sorour Ahmad A.
Published: January 2025

Polymer-based composites offer several advantages, such as high strength-to-weight ratio, exceptional corrosion resistance, and tailored mechanical properties. However, they may also have limitations, such as poor surface finish, low thermal conductivity, and limited wear resistance especially when fabricated through 3D printing technologies. Therefore, through surface metallization, cold spray can overcome these limitations by depositing metallic composite coatings onto polymer-based components. This study investigates the optimization of cold spraying parameters to achieve effective polymer metallization via cold spraying of anti-bacterial coating onto PEEK. A combination of Cu and Al2O3 particles is used in the feedstock to effectively metallize PEEK. The cold spray parameters (such as gas temperature, particle velocity, powder feed rate, scan speed, step size, spray path pattern, and spray distance) are optimized to achieve high-quality metallic coatings using computational fluid dynamics (CFD) simulations that investigate particle flow dynamics. Finite element and smooth particle hydrodynamics simulations are used in a hybrid computational technique to evaluate the impact characteristics of the deposited particles. The optimized parameters are used to make coating samples and evaluate their microstructure, phase composition, and mechanical properties using various analytical tools. A gas pressure of 6 bar and a temperature of 400 °C were identified as optimized conditions for metallizing PEEK. Dendritic Cu particles resulted in shallower penetration depth and less PEEK erosion compared to spherical Cu particles. A dense and defect-free Cu-Al2O3 coating layer with a thickness of ∼ 290 μm. The presence of Al2O3 particles enhanced interfacial bonding and hardness of the coating layer. The results demonstrate ways of achieving effective metallization of polymers through precise control of cold spraying parameters.
Droplet Combustion Behaviors of Liquid Fuel Doped With Carbon Dots
Authors: Parveg A. S. M. Sazzad , Ratner Albert
Published: January 2025

Nanofuels, incorporating sub-micron particles to enhance combustion and reduce emissions, hold promise in various industries. While metal-nanoparticle-based nanofuels offer benefits, concerns over environmental and health impacts drive exploration of safer alternatives such as carbon nanoparticles. Carbon dots (CDs), with their nanoscale dimensions and biocompatibility, emerge as potential candidates for improving combustion efficiency, particularly in liquid fuels. This study investigates the combustion characteristics of liquid fuel doped with gel-like carbon dots (G-CDs) at the droplet scale to understand their impact on combustion behavior. n-Dodecane is chosen as the representative liquid fuel due to its resemblance to real-life multicomponent fuels, allowing for the isolation of the impact of multicomponent fuels and accurate assessment of G-CDs’ role. Sorbitan monooleate (Span 80) is selected as the surfactant for effectively dispersing G-CDs into the liquid phase. Nanofuels with G-CDs concentrations ranging from 0.01% to 1.00% are prepared for droplet combustion experiments. Additionally, droplet combustion dynamics of Dodecane with surfactants at concentrations of 0.05%, 0.50%, and 2.50% w/w are examined to understand surfactant effects on combustion. Experimental setups utilize suspended isolated single droplets for detailed examination under normal gravity and standard atmospheric conditions (∼25°C, 1 atm). Key droplet combustion characteristics analyzed include combustion rate, pre-ignition time, and droplet dynamics. Findings reveal that surfactant concentrations up to 0.50% w/w minimally affect base fuel combustion dynamics. At higher concentrations (2.50% w/w), pre-ignition time increases by approximately 9.00%, indicating a threshold for surfactant influence. G-CDs show significant enhancements in combustion dynamics at concentrations ≤ 0.10% w/w, with combustion rate augmentations ranging from 4.00% to 16.00%, and improvements in pre-ignition time ranging from 7.00% to 10.00%. The highest enhancement in combustion rate, observed at 0.10% w/w G-CDs concentration, reaches 16.46%, while a decrease of about 5.63% is noted at 1.00% w/w G-CDs concentration. Pre-ignition time experiences its highest decrease of approximately 10.19% at 0.10% w/w G-CDs concentration, contrasting with a 9.63% increase at 1.00% w/w G-CDs concentration. These findings suggest concentration-dependent effects of G-CDs on liquid fuel combustion behavior. In conclusion, this study provides insights into the combustion dynamics of liquid fuels doped with G-CDs, highlighting their potential as additives for enhancing combustion efficiency and reducing emissions in liquid fuel systems.
Investigating the Effects of Spray Nozzle Clogging in Continuous Casting of Steel
Authors: Meng Dianzhi , Nandipati Sai Bhuvanesh , Silaen Armin , Zhou Chenn
Published: January 2025

The secondary cooling zone of continuous casting is typically equipped with air-mist nozzles. Nozzle clogging, however, poses a significant industry challenge, impacting cooling efficiency and, consequently, product quality.

This study aims to explore the effects of nozzle clogging on heat transfer behavior during continuous casting. An integrated three-dimensional CFD model, incorporating the actual nozzle layout of a full-scale continuous caster is used to explore the effects of nozzle clogging on the cooling process. The enthalpy-porosity method is employed to model the solidification process. The cooling provide by the air-mist nozzles on the slab surface is defined using HTC correlation.

This study explores the relationship between nozzle clogging and its effects on slab surface temperature, cooling rates, and metallurgical length (ML) in continuous casting. It finds that clogs can raise surface temperature by up to 100 K and slightly increase ML, with more clogs leading to longer ML. Clogs near the meniscus are especially influential, emphasizing the role of early cooling in solidification. Even a single clog can cause up to a 3.2% increase in ML, highlighting the significant impact of nozzle clogging on the casting process.
Optimizing Lithium-Based Battery Cooling: A Numerical Simulation of Phase Change Materials Partially Filled With Metal Foam Based Liquid Cooling Technique
Authors: Arumugam Aanandsundar , Buonomo Bernardo , Nardini Sergio , Manca Oronzio
Published: January 2025

Focusing on thermal management within electric vehicles, this research focuses on the key challenges surrounding the effective control of rechargeable electric battery temperatures. Employing a three-dimensional cylindrical model of a lithium manganese oxide single battery module, this numerical study explores the various thermal control cooling mechanisms involved during the discharge process. The control techniques involve the application of phase change material (PCM) which are associated with metal foams of different porosity and pore densities. The module is placed alongside convective channels through which cooling liquid is allowed to pass through. The metal foams which are embedded with the PCMs, are varied both in geometry as well as configuration. The model is assumed to be adiabatic in nature and implemented using finite volume technique. The internal resistance of the module is estimated using the Generalized Reduced Gradient algorithm (GRG) for two specific C-rates of 0.5C and 1C respectively during the process of discharge. The model assumes three configurations based on the dimensions of the battery and four different pore densities. The study compares the temperature distribution on the battery and the PCM along with the liquid fraction during the process of thermal cooling for the different cases.
Comparison of Dominant vs Non-Dominant Achilles Tendon Stiffness and the Effect of Fatigue
Authors: Salman Muhammad , Butler Carolyn , Salman Fatima , Shah Iti , Housen Nahtecia
Published: January 2025

The Achilles tendon plays a crucial role in various movements such as walking, running, and jumping. It’s stiffness is an important factor in determining overall function and performance. A comparison between dominant and non-dominant Achilles tendon stiffness is studied using a shear wave elastography method. Wave speed changes between different levels of contraction can be precisely detected. Tendon load can be monitored using shear wave elastography using surface mounted accelerometers. The dominant side typically refers to the limb that is used more frequently or is stronger in activities such as kicking a ball (for example, the right leg for a right-handed person). We also investigated the effect of doing the fatigue exercise on the Achilles tendon after a fatigue exercise of stair climbing, and then checked the stiffness of the tendon again using shear wave elastography. Five healthy subjects, including males and females, with ages ranging from 20 to 50 years old, were taken as subjects to find the differences in their tendon. In individuals who engage in asymmetrical activities or sports, the dominant Achilles tendon may experience greater loading and stress compared to the non-dominant side. Asymmetrical activities refer to tasks or movements that are primarily performed using one side of the body over the other. These activities involve a preference or dominance of one limb or side of the body, resulting in unequal use or loading between the left and right sides. As a result of increased use and loading, the dominant Achilles tendon may exhibit higher stiffness compared to the non-dominant side. Dominant Achilles tendon may provide better support and stability during activities that heavily involve the dominant limb. The non-dominant side typically refers to the limb that is used less frequently or is weaker in asymmetrical activities. The non-dominant Achilles tendon may experience less loading and stress compared to the dominant side, particularly in activities where the dominant limb takes precedence. It’s essential to note that the difference in stiffness between the dominant and non-dominant Achilles tendons may vary among individuals based on factors such as activity level, training history, and any asymmetries in biomechanics or muscle strength. Additionally, any significant difference in stiffness between the two sides may have implications for injury risk and performance, highlighting the importance of addressing asymmetries through appropriate training and rehabilitation strategies.
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

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

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

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

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

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

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

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

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

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

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

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

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.
Fracture Analysis of Additive Friction-Stir Deposited Non-Ferrous and Ferrous Alloys
Authors: Alam Chowdhury Sadid , Abid Abyaz , Ahmed Radif Uddin , Rahman M. Shafiqur
Published: January 2025

In the dynamic field of metal 3D printing, solid-state additive manufacturing (AM) techniques like Additive Friction Stir Deposition (AFSD) are revolutionizing the production and repair of critical parts in various industries due to their efficiency, environmental benefits, and enhanced material properties. AFSD stands out by enabling the creation of high-strength, fully dense non-ferrous and ferrous alloys that exhibit superior mechanical characteristics. This study offers a detailed examination of the fatigue crack growth and fracture behaviors of non-ferrous (AA6061-T6) and ferrous (4340 steel) alloy specimens processed through AFSD. Employing numerical methods, the mixed-mode fracture properties and propagation of cracks in the structures are evaluated. The model involves modified compact tension specimens (MCTS) subjected to tensile loads to analyze fatigue crack propagation and determine Paris Law constants. The study utilizes ANSYS software’s Separating Morphing Adaptive Remeshing Technology (SMART) tool to predict crack trajectories and fatigue growth under constant amplitude loading. Results from the numerical models, showing stress intensity factors, crack extension, and stress deformation, are compared with analytical outcomes to validate the precision of the models in simulating the mechanical integrity of AFSD-produced parts. Additionally, a comparative analysis of the mechanical properties between traditionally produced alloys and those manufactured via AFSD highlights significant improvements, thereby confirming the potential of AFSD for high-strength structural and repair applications with both ferrous and non-ferrous alloys.
Real-Time Bayesian Estimation of Drilling Tool Lateral Motion by Fusing Physics With Sensor Data
Authors: Song Fei , Shi Kevin , Li Ke , Mahjoub Amine , Ossia Sepand , Loretz Ives , Serafim Robson
Published: January 2025

The performance and health of logging while drilling (LWD) tools can be significantly impacted by the drilling dynamics of the bottomhole assembly (BHA). With drilling dynamics becoming increasingly harsh, BHA whirl is one of the undesired motions the tool can face during drilling operations, where the BHA follows an eccentric rotation about a point along the wellbore other than the geometric center. For example, parasitic motion that causes a plethora of distortions to the echo train, at times manifesting as erratic noise or a complete loss of cohesion has been a measurement quality concern for LWD tools. Advanced motion sensors can be installed only at discrete and limited locations of various LWD tools. If we simply take the sensor measurements as the dynamic states at locations away from the sensors, risks associated with tremendous uncertainty can be present in decision making. The farther away from the sensors, the more uncertain the dynamic states will become. Therefore, robust inference of the motion states at the LWD measurement sensor of interest with motion sensors at discrete locations is critical for risk flagging and quality assurance of LWD answer products.

In this paper, we present a Bayesian data assimilation method that fuses physics with sensor data for inferring the dynamic states at points of interest on the BHA with proper uncertainty quantification. A 4.75 inch-LWD tool has been used as a use case, where the dynamic states at the LWD measurement sensor can be predicted in real time with the measurements at the motion sensor as the required inputs. This was achieved with a developed transfer function that utilizes unscented Kalman filtering technique. The robustness of the transfer function was evaluated with synthetic data obtained from drilling dynamics and finite element analysis (FEA) simulations for various BHA configurations and drilling conditions. It was found that the prediction by the transfer function agrees favorably well with the true states of motion at the LWD measurement sensor. The developed transfer function method was further assessed with experimental roll test data, which is considered as close to drilling conditions. The prediction by the transfer function was found consistently close to the ground truth at various rotation speeds.
Towards Zero Defects Manufacturing: Metrological Automatic Recognition of Elementary Functional Geometries
Authors: Costa Carlos Alberto , Mendonça João Pedro
Published: January 2025

This article addresses the growing demand for efficient and high-quality manufacturing processes, highlighting the importance of the “Zero Defects Manufacturing” concept. It is explained how a standard tool such as a Coordinate Measuring Machine (CMM) — a current and standard method for dimensional inspection — contributes to ensure product quality in such and more rigorous procedure. Subsequently, the paper explains and compare the automatic recognition of Elementary Functional Geometries with the standard method, exploring differences and analyzing the advantages of automatic recognition in terms of efficiency and precision. The article then emphasizes the importance of recognizing elementary geometries and their tolerancing, including the recognition of flat, spherical, cylindrical, and conical surfaces. The primary focus of the work is to adapt partial derivatives to the equations of Gaussian and mean curvatures, highlighting their potential as tools for automatic geometric shape recognition. The article concludes by presenting decision criteria for different elementary geometries, emphasizing their relevance for implementing an automatic recognition algorithm for these geometries.
Chat GPT Inclusive Student Active Teaching for Engineering Education
Authors: Tyagi Pawan , Alshweiki Ali
Published: January 2025

ChatGPT assistive tools can dramatically enhance or limit the intellectual growth of engineering students based on how they are utilized. The utilization of ChatGPT in the assignments given generally after the instructor-focused lectures-based courses is considered a challenge; it is extremely difficult and burdensome to separate students’ original work from the copy-pasted portion of the ChaTGPT-like resources. Here, we present a case study of how ChatGPT was utilized to enhance student mastery of the course content when applied in Student Presentation-based Effective Teaching (SPET), a method invented and advanced by the author. Under this approach, students are allowed to use ChatGPT or any AI resource along with the suggested textbook to prepare answers to the assignments/questions regarding the upcoming discussion topics. Students generally get the assignment 7–15 days prior to the discussion date to do self-study and independently answer the questions. In addition, students are expected to work in groups of 3–5 students to prepare a group presentation for class discussion. Each group member answers the same questions individually before working in the group to develop a threshold level of content mastery and familiarity with the concepts to be discussed. Students are required to submit individual and group presentations by the discussion date in the scheduled class. Students are provided instructions about the rubric that will be used for evaluating the student’s mastery and efforts. Generally, 30% marks are assigned to the level of completion of the assigned questions, 20% grade for the quality of presentation, and 30% grade is assigned for the quality of presentation and demonstrating mastery by giving examples and analogies. 20% marks are assigned for answering the questions or “what if” scenario. The SPET approach allowed us to gauge individual students’ concept mastery levels, mainly via their in-class presentations. This paper discusses insights into the usage permitting the use of ChatGPT in the context of several topics ranging from mental resilience to innovating novel engineering design using the principle of fluid flow and heat transfer.
Developing Carbon Fibre Composite Current Collectors for Structural Battery Applications
Authors: Raju Karthikayen , Dong Sihan , Tay Tong-Earn
Published: January 2025

Structural batteries can perform structural load bearing functions in addition to electrochemical storage. Current collectors that can bear load in addition to their essential function to gather electric current generated by the battery’s electrochemical reactions and convey it to the external circuit can be beneficial in structural battery design.

The objective of this work is to fabricate current collectors and to improve both the mechanical and electrical performance of these to make them both structurally and electrically functional, so that they can be used as structural battery current collectors. The composite current collectors after fabrication are tested in tension to measure the tensile modulus and tensile strength. The electrical performance is evaluated by measuring the resistance of the current collectors along different directions such as along the axis of the fibres and across the thickness of the composites. The measurement of resistance is carried out with a test set-up which eliminates the effect of contact resistance in the measurements by applying pressure during resistance measurements.

The current collectors’ tensile properties and resistivities are compared with one another. Coin cells are assembled with some of the better performing current collectors as a demonstration. The work is concluded with considerations for potential future directions.
Solar Recycling of Aluminum Cans
Authors: Tastet Collin , Alsayyed Basel
Published: January 2025

Planet Earth receives about twelve hours of sunlight per day on average, but global warming poses a serious threat to its climate and ecosystems. One of the main causes of global warming is the emission of greenhouse gases, which trap heat in the atmosphere. Recycling is one of the many actions that can help reduce greenhouse gas emissions and conserve natural resources. Examining the case of Jackson County, NC, where the solid waste and recycling department manages the collection and transportation of recyclable materials from the surrounding area. The transfer station in Jackson County oversees the collection of various recyclable resources, such as paper, cans, and aluminum. These materials are sorted and distributed by Curbside Management, a company based in Woodfin, NC. This transfer station handles about 1,400 tons of paper, 700 tons of cans, and 35 tons of aluminum per year. The cost of transporting these materials to the sorting facility is about $660 per load. Aluminum accounts for approximately 5% of the total recyclable materials, but it has a high market value of $1,231 per ton. According to the American Chemical Society, “Aluminum recycling is profitable because extracting this metal from aluminum ore is expensive, it pollutes the environment, and it consumes a significant amount of energy” [1]. Therefore, recycling aluminum not only saves money, but also reduces environmental impact and energy consumption. However, recycling aluminum is not without its challenges. For instance, Jackson County’s transfer station uses diesel trucks and electric lifts to store and collect recyclable goods. These vehicles and equipment consume fossil fuels and electricity, which generate greenhouse gas emissions and contribute to global warming. Thus, the question arises: how can we achieve zero emissions recycling? This paper hopes to expose the environmental and economic benefits of recycling aluminum and the challenges and opportunities for achieving zero-emission recycling. In addition, the paper will explore some practical solutions, modernizing the method of recycling aluminum cans and recovering their material using simple equipment that uses the sun’s energy to melt a material, instead of using electricity or other traditional sources that uses fossil fuel. This scope aims to investigate environmentally friendly recycling with zero carbon footprint, improving recycling efficiency, and implementing sustainable manufacturing techniques.
Mechanical Engineering Curriculum Modifications and Adaptions to Address Climate Mitigation and Changes in the Energy Mix
Authors: Zenouzi Mansour , Kowalski Gregory J. , Metghalchi Hameed
Published: January 2025

The world needs to reduce carbon emissions to combat climate change. Electrification of building and transportation, data centers that are being built to support commerce and enabling artificial intelligence (AI) necessitates innovative energy solutions to reduce greenhouse gas emissions because of global warming. Decarbonization of the economy, shifting to electricity produced with low-carbon energy sources and building up adequate capacity of renewable energy will take time and will require the discovery of new clean energy sources and innovative technologies to replace the traditional fossil fuel combustion driven power cycles. It is imperative that academic institutions design appropriate curricula that prepare students to tackle the complex energy-related problems faced by society. Students need to understand existing technologies, such as cogeneration or combined heat and power (CHP), which reduces energy consumption, and it can be integrated with renewable energy sources. Weatherization of buildings, which consume more than 40% of the energy in the United States, is necessary to reduce energy consumption; however, many mechanical engineering programs are not offering HVAC as a required or even as an elective course. Curricula should include such topics as: energy storage technologies, e.g., batteries, green hydrogen-generation, power transmission, electrochemistry and membrane technologies that are needed for innovative new power generation technologies such as fuel cells (FC) and salinity gradient energy (SGE) generation.