bluuebunny/crossref_metadata_2025 huggingface dataset:
A Framework for In-Situ Vision Based Detection of Part Features and its Single Layer Verification for Additive Manufacturing
Authors: Saini Tushar , Shiakolas Panos S.
Published: February 2024

Additive manufacturing (AM) is a layer-by-layer manufacturing process that has become a popular technique to produce complex components with high precision and accuracy. The presence of internal defects and geometrical issues in a layer can significantly affect the quality of a 3D-printed part. In this research, we propose an in-situ framework that offers a systematic approach for detecting features on a layer-by-layer basis during the manufacturing process and compare them with the as-designed ones. A single high-resolution camera controlled by a Raspberry Pi is used. The acquired images are processed by a computer vision algorithm implemented in the Python programming language. The framework uses techniques such as image segmentation and edge detection to analyze and extract internal features at each printed layer. Subsequently, the identified features are compared with the as-designed ones based on the generated GCODE. The proposed framework is evaluated on a single-layer; a 20mm square shaped test sample with different distinct shaped internal features. These features are automatically compared to the as-designed model to assess and highlight any differences between them. Initial results show that the proposed framework is highly effective in detecting sub-millimeter errors between the as-designed and printed in-layer features and alerting the operator in real-time of any differences outside an acceptable error level. These differences could be employed to decide whether to continue printing, attempt repairs or abort the fabrication thus improving quality control and reduce waste. The developed system is a cost-effective solution that can be easily integrated into existing additive manufacturing systems.
A Deep Learning-Based Method for Early Crack Diagnosis in Non-Standard Spur Gear Pairs
Authors: Kalay Onur Can , Karpat Fatih , Karpat Esin , Dirik Ahmet Emir , Ekwaro-Osire Stephen
Published: February 2024

Gears are the key components of modern industry and have been widely employed in the automotive, wind turbine, and aviation fields. From the engineering point of view, an intelligent method that can automatically extract fault features from the vibration signals would be precious since failing in early diagnosis of root cracks may result in a tooth broken rapidly. In this regard, deep learning (DL) is increasingly popular in achieving early fault diagnostics tasks in geared systems with the wide availability of sensors and ever-increasing computation power. With this in mind, the asymmetric tooth concept offers higher load-carrying capacity, long fatigue propagation life, and the ability to lessen vibration and noise than the standard (symmetric) involute profile spur gears. From this standpoint, this study aims to determine the tooth root crack and its degree for both symmetric (20°/20°) and asymmetric (20°/30°) involute spur gears with a DL-based approach using vibration data. To this end, the single tooth stiffness values of the designed gears were obtained with ANSYS software for healthy and cracked gears (50%–100%), and then the time-varying mesh stiffness was calculated. Besides, a six-degree-of-freedom dynamic model was developed by deriving the equations of motion of a one-stage spur gear transmission. The vibration responses were collected for the healthy state, 50%, and 100% crack degrees for symmetric and asymmetric tooth profiles. Three different signal-to-noise ratios were considered to complicate the early crack diagnosis task and evaluate its influence on the DL algorithm’s classification performance. The obtained findings were then evaluated and interpreted in time and frequency domains. To this end, the Fourier transform was applied to the simulated time-sequence acceleration data in the time domain. As a supplementary finding, the present research also benefited from three statistical indicators, namely, (1) root mean square, (2) kurtosis, and (3) crest factor, to investigate whether the configuration of tooth profiles would provide an advantage in detecting tooth-root cracks. The present study also evaluated the influence of residual signals on the proposed DL-based method’s classification accuracy and further expanded the scope of research work. The findings indicated that the overall classification accuracy could be improved by 5.1% using asymmetric (20°/30°) gearing.
A Slicing Method for Spherical Additive Manufacturing
Authors: Kim Christopher D. , DeVries Levi D. , Kutzer Michael D. M.
Published: February 2024

Fabrication using additive manufacturing (AM) or 3D printing technology is ubiquitous across a growing number of disciplines. Despite a wide variety of AM methods ranging from extrusion of polymers to laser sintering of metals, the use of flat layers or “slices “ is common practice for deposition planning and execution. While effective, observations of other well-understood fabrication methods and testing conducted on AM prints reveal the importance of print fiber arrangement; otherwise known as grain orientation. By expanding AM capabilities to allow for fabrication using alternate grain orientations, AM workpieces see an improvement in anisotropy, surface finish, and physical properties. This paper presents a new approach to AM based on conformal layering that produces spherically wrapped grain.
Complex Dynamic Phenomena in Circular Cylindrical Shells
Authors: Pellicano Francesco , Iarriccio Giovanni , Zippo Antonio
Published: February 2024

In this paper the achievements of an intense experimental champaign, regarding shell nonlinear dynamics with and without fluid interaction, with thermal effects, subjected to harmonic or random excitations, is presented. Extreme thermal conditions, and high thermal gradients across the thickness of the shell cause important effects on the shell dynamics: a test setup has been developed to perform tests in climate chamber, in order to investigate the dynamics under different conditions, both for empty and a fluid-filled shells as well as for Newtonian and non-Newtonian (dilatant) fluids.

The response is strongly non-linear due to the couplings between fluid-structure-shaker which lead to a complex dynamic scenario. In the case of harmonic excitation, experiments show the onset of complex dynamics: subharmonic and quasiperiodic responses, Chaos. In the case of high-energy random excitation a synchronicity phenomenon was detected for particular thermal and loading conditions: a severe transfer of energy from a broadband excitation to almost harmonic response is experimentally observed; energy transfer to low frequencies was observed as well.
Enhancing Thermal Comfort and Air Quality in a Classroom Using Air Filtration Boxes
Authors: Kokash Hussein , Khanafer Khalil , Burzo Mihai G.
Published: February 2024

This study presents a numerical simulation of a classroom’s indoor environment using Fluent Ansys to investigate the effectiveness of air filtration boxes in maintaining good indoor air quality (IAQ) and thermal comfort while reducing the spread of airborne particles. The simulation examines the distribution of aerosol particles released by occupants, the airflow patterns, and the concentration of pollutants in a typical classroom with a ventilation system consisting of supply and return air diffusers and air filtration boxes. The results demonstrate that the placement and location of the air filtration boxes significantly impact IAQ and thermal comfort, and the proposed template can guide researchers in optimizing ventilation strategies. More specifically, our results show that more filtration boxes are not always better or desirable. As few as two filtration boxes placed strategically in the classroom can be as effective as using more boxes. The study highlights the importance of maintaining good IAQ and thermal comfort in classrooms, especially during the COVID-19 pandemic. The use of air filtration boxes is a cost-effective and easy-to-install solution that can help filter out pollutants and reduce the spread of airborne virus particles. The findings of this study can contribute to creating safer and healthier indoor environments in classrooms and have implications for the health and productivity of occupants.
Developing a Modular Control Moment Gyroscope for Planetary Rover Mobility
Authors: Han Fang , Wiles Jeremy , Brawley Aidan , Sanderson Oliver , Burke Stephen , Radhakrishnan Pradeep
Published: February 2024

A control moment gyroscope (CMG) is a torque actuator typically used for spacecraft attitude control, but other applications of CMGs are seldom seen in practice. The goals of this project were to design, manufacture, and analyze a modular CMG for use in any application. The developed prototype consisted of a turned brass flywheel suspended in a servo-powered, aluminum gimbal structure and was able to produce a nominal output torque of up to 6 Nm. A microcontroller was used to simulate CMG dynamics, control the motors, and calculate performance metrics. Quantitative analyses were conducted for the behaviors of the motors, dynamic disturbances in the system, and stresses in the structure. To further validate the design, its output torque performance was evaluated against a theoretical CMG model developed in Simulink. Subsequently, to exemplify the prototype’s modularity, its use on planetary rovers for rollover prevention, rollover recovery, and entrapment recovery was substantiated through computer simulations. Rollover recovery was also physically demonstrated. These applications aimed to address NASA’s Space Technology Grand Challenge of “All Access Mobility,” which identifies the need for next-generation rovers to safely traverse any terrain type.
Improved Non-Contact Ultrasonic High-Speed Structural Condition Monitoring of Rails Using a Controlled Acoustic Source and Random Wheel Generated Excitations
Authors: Datta Diptojit , Hosseinzadeh Ali Zare , Batista Izabela , Lanza di Scalea Francesco
Published: February 2024

Internal defects in rails are a major contributing factor in train derailment related accidents. A non-contact ultrasonic passive rail defect detection system is currently being developed at the Experimental Mechanics, NDE, and SHM Laboratory at the University of California San Diego. This technique has the potential to operate at high speeds and can be mounted on a regular train, thereby facilitating continuous condition monitoring of rails. This paper presents an improved version of the ultrasonic non-contact passive rail defect detection system with the introduction of a non-contact active acoustic source. The previous version of the system utilized air-coupled capacitive ultrasonic transducers in receiving-only mode to passively extract an impulse response function of a rail segment using rail-wheel interaction as the random source of excitation. The use of an active and controlled non-contact acoustic source is proposed for the improved system that aims to enhance the signal-to-noise ratio at the transducer array independent of variabilities of the wheel-induced excitation. Tests were conducted with various types of non-contact sources and source operating parameters to optimize the improved system. Results from field tests conducted by mounting the system on a train with testing speeds of 25 mph, 33 mph and 40 mph are presented.
Importance of Data Scaling for Various Machine Learning Models: A Case Study Based on Ionic Liquids for Processing Extra-Terrestrial Regolith
Authors: Rexhepi Fatlum , Banerjee Soumik
Published: February 2024

Lunar regolith is primarily composed of silicates and metal oxides, which are excellent in situ resources for metals as well as oxygen. Developing a technology for extracting metals from regolith would enable additive manufacturing of components for sustainable space exploration. Solvent-based digestion of regolith using Ionic Liquids (ILs) is a promising technique. Since experimental work on ILs is very expensive, this work is focused on leveraging Machine Learning (ML) algorithms to build statistical models to predict solubility. While prior effort employed optimal ML algorithm to predict solubility parameter for ILs, which is a descriptor of the solubility process, the selection of specific algorithms and pre-processing of data was not reported. To carefully study model selection, three different algorithms were tested. Emphasis was placed on preprocessing, where the importance of data scaling was analyzed. Finally, hyperparameter tuning was investigated within the range of the given search space. This analysis showed that when data preprocessing is done correctly models are not sensitive to different combinations of hyperparameters.
Parametric Study on the Nanoparticle Focusing in Thermophoresis Microfluidic Devices
Authors: Xue Guanyang , Caspar Justin , Cheng Xuanhong , Oztekin Alparslan
Published: February 2024

Three-dimensional computational fluid dynamics simulations were run to simulate the nanoparticle concentrating in thermophoresis microfluidic devices. Thermophoresis is a phenomenon where particles are driven by a temperature gradient. The microfluidic device utilizes thermophoretic force by applying 10 K temperature difference across the channel. The artificial transverse flow induced by slanted grooves is combined with the thermophoresis to concentrate nanoparticles. Following the experimental research, this study revisited the theory by applying the concept of circulation to evaluate the intensity of the transverse flow. Apart from the original experimental setup with 175 μm groove spacing, 25 μm and 75 μm setups were also simulated as comparison. The comparison shows that the peak circulation has no correlation between different groove spacing. The mass concentration accumulation was analyzed, and smaller spacing resulted in less fluctuation and more effective particle focusing. The averaged mass concentration from the outlet was processed, and in the best scenario, the 25 μm spacing design achieved 68% more concentration than the original 175 μm spacing design from the experiment.
Comparison of Biodiesel/Glycerin Separation by Gravitational Settling and Electrostatic Coagulation
Authors: Igbax Saanyol Ityokumbul , Swartling Daniel , Ahmed ElSawy , Idem Stephen
Published: February 2024

This paper compares the use of electrostatic coagulation and gravitational settling for efficient separation of biodiesel and its by-product glycerin, which were produced using raw materials such as waste vegetable oil and virgin canola oil. Titrations were performed to determine the free fatty acid (FFA) percentage and the optimal amount of catalyst to be used. The tests utilized an oil to methanol volume ratio of 6:1. Separation by gravity allowed each fluid to settle into different layers based on their respective densities. To reduce the separation time and improve the quality of biodiesel, the use of high voltage separation was investigated. A circuit rated at 1.5 kV and 1.5A was designed and constructed to impose a DC voltage potential across the biodiesel/glycerin mixture. The separation process was deemed to be complete when the electrical resistance across the load approached an asymptotic limiting value. In every instance the required time to achieve complete separation was recorded. For select cases considered in this paper, it was determined that use of electrostatic coagulation yielded significant reductions in the time required to fully separate the biodiesel and glycerin, as compared to gravitational settling.
Influence of Bondline Thickness on the Performance of Adhesive Joints Under Ballistic Peel Impact
Authors: Demir Gizem Derya , Yildiz Salih , Gursel Ali , Ikikardaslar Kerim Tuna , Delale Feridun
Published: February 2024

As structural adhesive technology advances, adhesive joints provide attractive advantages over conventional fastening methods. Since welding, riveting, and bolting may cause nonuniform stress distribution across the joint, and in many cases cannot be used to bond dissimilar materials such as composites to metals, adhesive joining may be considered as an alternative joining method. It is well known that the geometry of adhesive joints as well as their material properties and the adhesive thickness may affect their performance. In this study, an adhesive joint consisting of an aluminum back plate and a patch bonded by an epoxy is employed to investigate the influence of the bond thickness on the performance of adhesive joints under predominantly Mode I ballistic impact. A pressure gas gun is used for the dynamic test. High speed camera (Phantom V710) was used to record specimen behavior under ballistic peel impact tests. Frame rate of the high-speed camera to capture impacts was kept at 120,000 per second. The effect of bondline thicknesses (i.e., 0.005” (0.127 mm), 0.01” (0.254 mm), 0.015” (0.381 mm) on the adhesive joint performance were investigated. The results indicate that the adhesive joint with 0.01” mm bondline thickness performs better than those with 0.005” and 0.015” adhesive thickness. In addition to the experimental work, Finite Element Analysis is carried out to determine the mechanical properties of the joints by an inverse problem-solving technique.
Impact of Channel Shape and Process Parameters on Fluid Flow in Internal Channels of Material Extrusion Parts
Authors: Van Domelen Ryan , Wentz John , Shepard Thomas
Published: February 2024

The use of additive manufacturing (AM) techniques allows for the construction of internal flow conduits whose cross-sectional geometries can vary from the traditional circular, square, or rectangular passages made using more traditional manufacturing processes. These internal channels have seen use in conformal cooling of molds and other fluid transport processes that take advantage of the ability to generate internal features previously unable to be fabricated. In the creation of these channels some AM processes also run into issue through the requirement of support structures that must then be removed in post processing. While many experimental studies have shown the feasibility of fabricating and using these channels, there has been less study into the fluid dynamics at play within the channels that are a function of the AM process parameters. The impact of layer thickness, build orientation, and even channel shape is of interest to the design of parts that take advantage of the new capabilities. By modifying the cross-sectional shape, the velocity gradients and thus frictional pressure losses will also be modified, in addition to affecting support structure requirements in fabrication. This creates an opportunity for interesting research relating to cross-sectional shapes that may reduce energy losses within a pipe system as compared to a circular cross section. In material extrusion AM, print parameters such as layer height and print orientation relative to flow orientation can also impact the wall friction. In this study a variety of material extrusion pipes were printed in order to experimentally study the effect of cross-sectional shape (circle, diamond, teardrop), print layer thickness and hydraulic diameter on the pressure drop through the pipe with horizontal full-developed turbulent flows. The hydraulic diameters studied for each shape are 3.5 mm and 5 mm while the print layer thickness of 0.127 mm and 0.33 mm were used. Reynolds numbers ranged from 9200–61,300 with a test fluid of water. The results demonstrate a significant effect of channel shape with the diamond and circle profiles resulting in the lowest and highest pressure drops respectively for a given flow rate. As the desired internal channel shapes are a function of ability to fabricate overhanging shapes with and without support material, these results provide valuable insight to designers who desire to both reduce internal pressure drops and fabricate parts with internal channels in AM. This is specifically valuable as most processes are able to fabricate a diamond shape without support structure necessary, eliminating the need for support removal steps.
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

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

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

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

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

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

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

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

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

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

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

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 (> 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

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

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

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

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.
Plasma Liquid Gas (PLG) Systems, Establishing a Plasma Dielectric Barrier Discharge-Mode With Liquid Electrodes for Energy Conversion
Authors: Wright Kamau , Patton J. P. , Potamianos Christos , Cui Juntao , Arsenlis Nikolas , Kim Daniel , Klahr Jordan
Published: February 2024

The present work explores the use and improvement of a novel plasma reactor, called a Plasma Liquid Gas (PLG) system. This reactor can utilize at least one liquid electrode to support plasma discharges in a gas. The safe operation of the PLG system is demonstrated at atmospheric pressure in a Dielectric Barrier Discharge (DBD) mode. DBD mode is further explored in and out of the presence of liquid electrodes, using a dielectric material (quartz). Results are presented for experiments with a 1/8” dielectric, a gas-filled gap of 2–3 mm, and a range of voltages, currents, and frequencies, first classified qualitatively and then supported by current-voltage profiles. Quantitative results are presented comparing the discharge with one liquid electrode to the discharge with both metal electrodes. Results indicate which combination of operating parameters were conducive to establishing stable plasmas in air, although key future applications for this work are in the plasma-induced decomposition of carbon dioxide (CO2). Investigations on the impact of liquid electrodes in plasma systems developed to treat gases represents a new experimental approach that will advance understanding of multiphase reactions with plasmas, and inform energy storage, and conversion of substances into value-add chemicals, with environmental benefits.
A Point-Of-Care Device Integrating Sample Preparation With Isothermal Amplification for Detection of Mayaro Virus
Authors: Alipanah Morteza , Lednicky John A. , Morris J. Glenn , Fan Z. Hugh
Published: February 2024

Mayaro virus (MAYV) is an emerging mosquito-borne alphavirus that causes clinical symptoms similar to those caused by Chikungunya virus (CHIKV), Dengue virus (DENV), and Zika virus (ZIKV). To differentiate MAYV from these viruses diagnostically, we have developed the first reverse-transcription loop-mediated isothermal amplification (RT-LAMP) assay for detection of MAYV. We designed six LAMP primers targeting MAYV’s non-structural protein (NS1) gene and determined the visual limit of detection of at least 10 viral genome equivalents (GEs) per reaction. The assay was specific for MAYV, without cross-reactions with CHIKV, DENV, or ZIKV. A 30 min. RT-LAMP assay was integrated with valve-enabled sample preparation device wherein virus lysis and RNA enrichment/purification were carried out on the spot, without requiring pipetting. Colorimetric detection was achieved by naked eye or a smartphone. The functions of our platform were demonstrated using purified RNA and cultured viruses for their potential usage. We have used the device for detection of cultured MAYV in 50 min.
Teaching Engineering Courses in the Digital Transformation Era
Authors: Rodriguez-Paz Miguel X. , Gonzalez-Mendivil Jorge A. , Zamora-Hernandez Israel
Published: February 2024

In this paper we present a teaching model for Engineering couses, particularly courses of Applied Mechanics for the new generation of Engineering Programs. After the online terms due to the global pandemic, students and their professors returned to campuses and some lessons learned during that period were positive ones and students keep on demanding new models of teaching making use of the latest technologies. The use of digital media has become widely accepted by both, faculty members and students and most lectures are now recorded and students are used to have such material available on the same day of the class session. We present the students perceptions of what the new generation of Engineering courses should have in order to be attractive to students, help them develop some digital transformation competencies and, mainly, help them perform their best in courses that could be difficult, such as the Applied Mechanics courses. A total of 350 students were surveyed in the last four years, even prior to the pandemic to get their perceptions and their ideas on what an ideal Engineering course should contain, taking into account the era in which we are living, with particular focus on Digital Transformation Competencies and the use of new Artificial Intelligence tools such as ChatGPT®. We present a model that has been successfully implemented in our university and we think that Engineering educators worldwide can benefit from our experience and the recommendations our students provided.