bluuebunny/crossref_metadata_2025 huggingface dataset:
Developing Online Learning Modules on Systems Concepts for First Year Mechanical Engineering Students
Authors: Bedillion Mark , Muci-Kúchler Karim , Emami Anahita , Kojtek Lynn , Pottmeyer Laura , Birrenkott Cassandra
Published: January 2025

Mechanical engineers develop complex products consisting of multiple interacting subsystems, and product complexity has grown over time as sensing and communication elements have become ubiquitous. Developing these products requires engineers to take a holistic system-level view of the product and its context. Infusing systems thinking and systems engineering skills into the mechanical engineering undergraduate curriculum better prepares graduates to work on these complex systems. This paper describes the development of online learning modules for first-year mechanical engineering students that introduce the product development process while presenting fundamental systems concepts. The development of the online modules features a partnership between faculty, learning engineers, and student testers to convert materials previously presented in class into self-contained learning modules. These modules are designed to be suitable for a flipped classroom approach that allows using classroom time for “hands-on” activities based on the topics covered in the modules. The article describes the process to develop the online modules and the best practices learned for content conversion from classroom to online, embedded assessment, and protocols for student feedback, but does not include assessment results from a classroom implementation. The modules described in the paper are scheduled to be deployed in three institutions in the fall of 2024.
Conceptual Study of Cryogenic Carbon Capture in a Swirl Flow System
Authors: Kurian Emel V. , Sandilya Pavitra
Published: January 2025

Cryogenic carbon capture (CCC) involves the use of subzero temperatures to separate carbon dioxide from a gas mixture like flue gas, natural gas, etc. The separation may be achieved by desublimation, liquefaction, distillation, and/or hydrate formation. In all these methods, the efficacy of carbon capture depends primarily on mass transfer between two phases (gas-solid or vapor-liquid); however, due to the evolution of heat during the phase change, it is essential to ensure an effective way of removing this heat. Therefore, in designing a device for CCC, one has to consider both the mass and the heat transfer aspects to arrive at an optimal design.

There are a few studies reported on the desublimation-based CCC, and they have focused on the development of an efficient cooling system to enhance the rate of desublimation. In this context, we explored the efficacy of a swirl flow device to further improve carbon capture efficiency by increasing the mass and heat transfer coefficients. In this paper, we developed a lumped parameter model for a swirl flow and an axial flow in a tube. The carbon capture efficiency of both the systems are compared for varying composition and mass flow rates. In every scenario, swirl flow showed an enhanced carbon capture rate. The results showed that using a swirl flow device for desublimation-based cryogenic carbon capture can significantly reduce the equipment size, capital, and operating costs.
Implementing Ant-Gaiting-Based Biomimetic Locomotion for a Damaged Hexapod Robot
Authors: Marks William , Ackerman Matthew , Rahman Kaushik , Kim Dal Hyung
Published: January 2025

In this paper, we present biomimetic gait patterns for both undamaged and damaged hexapod robots, mimicking the locomotion of intact and amputated fire ants. We observed the gait patterns of intact and injured ants using a locomotion compensator and implemented a machine-learning image processing algorithm to accurately identify and track their movements. We modeled the locomotion using a Central Pattern Generator (CPG) with model parameters such as gait frequency, duty factor, and phase, leading to the derivation of one gait pattern for the 6-leg configuration and two major patterns for the 5-leg model. Furthermore, we designed and developed a biomimetic hexapod robot based on the dimensions of fire ants, controlling it using the derived motion patterns. The damaged hexapod robot demonstrated stable walking using these biomimetic gaits experimentally.
A Hyper Physics-Informed Neural Network for Predicting Heat Transfer Patterns During the Curing Process in Aerospace Composite Manufacturing
Authors: Deodhar Anirudh , Ramezankhani Milad , Parekh Rishi , Birru Dagnachew
Published: January 2025

The importance of fast and accurate process simulation is crucial in various manufacturing settings to enable both design experimentation and real-time monitoring and control. Traditional numerical simulations, however, are often too slow and computationally demanding for real-time applications. Physics-Informed Neural Networks (PINN) offer a promising alternative but struggle with dynamic prediction and generalization due to the need for retraining with any change in system configurations. To overcome this, Hypernetwork-based PINN (HyperPINN) has been developed. HyperPINN utilizes a secondary neural network to generate necessary weights for the primary PINN network based on input system configurations, thus avoiding retraining for different conditions. This paper showcases the use of HyperPINN in simulating the heat transfer patterns of a curing process for aerospace-grade composites. The process involves modeling transient heat transfer in a one-dimensional composite part. The Hypernetwork and the primary PINN are jointly trained across various system configurations, allowing the Hypernetwork to dynamically adjust PINN parameters as per the current conditions while maintaining adherence to physical laws. The zero-shot capability, along with near real-time inference and accuracy comparable to conventional simulations, makes HyperPINN ideal for digital twins, design optimization, and real-time process control. Additionally, the model can be adapted for other transient physical processes in manufacturing and process industries.
Preparation of a 3-D Printable Radiopaque Composite Using Zirconium Oxide Composite
Authors: Piatt Sophia , Tiari Saeed , Mihaly Holly , Chen Longyan
Published: January 2025

Joint dislocations are sustained frequently in the sports world, especially in contact sports. Athletic trainers and students in training must use joint simulation models to retain the skills to treat joint dislocations effectively. However, commercially available joint simulation models for athletic training are rare and often costly. The three-dimensional (3D)-printed patient-specific models with anatomical fidelity enable learners to practice before further medical intervention. However, one major limitation is that the polymers (such as PLA and ABS) are not visible under X-ray imaging, the most common non-invasive clinical diagnosis and assessment method for joint dislocation injuries.

In this study, a 3D printable radiopaque polymer composite was prepared by blending radiopaque zirconia particles with fine polylactic acid (PLA) particles under different weight ratios. The polymer composites were extruded to prepare filament through a filament extruder under various extruding conditions. The mechanical properties of the filaments were evaluated through tensile testing, using an MTI-10K machine. The results showed that the PLA mixed with up to 2.5% zirconia filament can improve the mechanical strength up to 1.2-fold. However, as more zirconia was added the material became more brittle. It is anticipated that the current PLA-Zr composite could provide an affordable and convenient solution for fabricating medical training models.
Computational and Experimental Calibration of Material Model for Blast-Resistant Laminated Glass Systems
Authors: Salim Hani , Elbelbisi Ahmed , Knight Jonathan , Chen Zhen , Elemam Hesham , Bowman Andrew , Kantrales George
Published: January 2025

This study employs a combined computational and experimental approach to adjust material model parameters for a blast-resistant curtain wall system. The focus lies on understanding the material’s behavior after reaching its peak strength. This enables an unbiased assessment of energy dissipation at the system level through finite element analysis. Experimental tests were conducted on the polymeric interlayer material SentryGlas®, commonly used in laminated glass for blast-resistant curtain walls. Digital image correlation was utilized to analyze strain distribution within the material. A finite element computational model was created using Ansys LS-DYNA software and validated against experimental results. The initial findings indicate the capability of finite element modeling to qualitatively predict the post-peak behavior of SentryGlas® as an interlayer in blast-resistant curtain wall systems.
Improving Indoor Air Quality and Ventilation in Government School Classrooms: A Mechanical Engineering Extension Service
Authors: Galindo Ronald M.
Published: January 2025

This paper investigates the indoor air quality (IAQ) and ventilation conditions in classrooms of a three-storey government school building in an urban setting, focusing on implications for student well-being and academic performance. Conducted as a mechanical engineering extension service, the research employed a comprehensive approach, utilizing measurements of temperature, relative humidity, sound, and light levels with a digital environment multimeter. Additionally, physical attributes such as total occupants, floor area, windows, doors, lights, and fans were recorded to provide a complete understanding of the indoor environment. The guidelines from the Department of Labor and Employment (DOLE) were incorporated to ensure compliance and alignment with regulatory standards. Interviews with teachers and students further enriched the data, showing light on the practical implications of IAQ on attendance, comfort, and performance in the classroom. Moreover, informative sessions on psychrometrics and IAQ awareness were conducted to address students’ queries and foster understanding regarding indoor environmental factors. The research findings revealed significant disparities in IAQ and ventilation across different floors of the school building. Ground floor classrooms exhibited compromised ventilation rates due to an obstructive elevated concrete fence, affecting indoor temperature and humidity levels and occupant comfort. Recommendations include strategic modifications to the building’s infrastructure and educational initiatives to improve IAQ and ventilation, ensuring a conducive learning environment.
A Framework for Digital Twin Development in Manufacturing
Authors: Stefanone Alessandro , Rossoni Marco , Colombo Giorgio
Published: January 2025

This study explores the application of Digital Twin technology in industrial manufacturing, focusing on the integration of OPC UA communication protocol for data exchange between physical machines and their virtual counterparts. The treatise presents a comprehensive framework for developing and deploying Digital Twins in a manufacturing setting. Through the implementation of this framework, significant challenges encountered in Digital Twin development are addressed, including the intricate process of extracting data from OPC UA servers, the necessity for standardized methodologies for descriptive-based Digital Twins, as well as limitations imposed by the frequency of API calls for data retrieval and the complexities associated with managing large and intricate systems. Furthermore, promising avenues for future exploration are proposed, such as the advancement of open-source OPC UA servers and the emergence of web-based Digital Twins as accessible and collaborative platforms for industrial applications. A case study involving a CNC machining center demonstrates the practical utility of the developed framework for monitoring and diagnostics of industrial processes.
Ultrasonic Vibration-Assisted Scratching Process of Sapphire: Effects of Feeding Speed
Authors: Ansary Shah Rumman , Kabir Sarower , Cong Weilong
Published: January 2025

There is a recent surge in interest in sapphire due to its distinctive physical and chemical properties, coupled with widely recognized, highly productive, and economical crystal growth techniques. The low fracture toughness and high hardness value of sapphire makes it a very challenging material to be machined. Scratching test using a single diamond abrasive grain is a great way to understand the material removal mechanism and deformation characteristics of sapphire-like brittle materials. This test result can also be used to simulate and predict sapphire’s cutting force and material removal mechanism during other multi-abrasive machining processes like grinding and lapping. Experimental investigations have shown that vertical ultrasonic vibration-assisted scratching can improve the cutting forces, scratch quality, and material removal characteristics of sapphire wafers compared to conventional scratching. However, the effect of different feeding speeds on the scratching process of sapphire wafers has not been studied yet. To address this research gap, this experimental study examines how both feeding speed and ultrasonic vibration impact vertical cutting force, scratch quality, and the material removal mechanism of sapphire wafers. We have tested four distinct feeding speeds, spanning from extremely slow (0.1 mm/s) to moderately fast (100 mm/s). We have analyzed the cutting force data and observed the scratch-induced microscopic features and thus got some insight into the deformation patterns attributed to the surface morphologies of sapphire. This experimental investigation validates that higher feeding speed with ultrasonic vibration can lead to better scratch quality with reduced microcrack formation.
Photopatternable Flexible Electromagnetic Polyimide/Cobalt Iron Oxide Composite Films for MEMS Applications
Authors: Akram Fazli , Guler Zeynel , Adaval Akanksha , Janardhana Ranjith D. , Jackson Nathan
Published: January 2025

Piezoelectric composite films are progressively pursued for Micro-electromechanical systems (MEMS) applications due to their adaptable nature. HD-4100 polyimide, renowned for its thermal resilience, mechanical robustness, and photopatternability, emerges as a promising matrix material for MEMS composites. Polyimides provide fundamental insulation and structural support across numerous industries, including MEMS. The addition of CoFe2O4 (CFO) nanoparticles to HD-4100 matrices has potential to enhance their magnetic characteristics. This study investigates the manufacturing of HD-4100/CFO composites through spin coating and photolithography techniques. The investigation aims to enhance the resolution of HD-4100 composite thin-films containing 5 wt.% CFO nanoparticles under different UV exposure intensities (UVexp = 160–400 mJ/cm2) and developer time (DT = 1 and 2 min). Results demonstrate resolutions of features with < 20 μm were achieved. Furthermore, a magnetic response of 52 Gauss signifies notable enhancement as pristine polyimide has 0 Gauss response. These perceptions pointed out the potential role of enhancing the performance of HD-4100/CFO composite thin-films across diverse technological domains. Examining the skilled balance between chemical processing technique and optical precision, this research catalyzes advanced technological innovation. The outcomes contribute substantially to the continual advancement and integration of MEMS technology into various applications, promising the development of high-performance devices with enhanced functionality and reliability.
Thermal and Optical Analysis of a Light Engine With Multi Color and Ultraviolet Light Emitting Diodes
Authors: Islam Md Shafiqul , Arik Mehmet
Published: January 2025

Light Emitting diodes have been of interest for general lighting applications over the last two decades due to energy savings, color quality and long lifetime. Moreover, due to unique features such as multi color and compactness, human centric lighting and agricultural applications started being more popular than ever. In this study, thermal and optical analysis have been performed computationally with a view to developing a multi color LED light engine. The incorporation of ultraviolet (UV) LED chips makes it unique in many ways. For the application, the primary focus of this light engine is agricultural applications, especially animal or bird lighting. Hence, a mixture of red (R). green (G), blue (B), white (W) LED chips along with UV chips are required for providing a wide range of spectrum and to prevent or control diseases in some cases. Thermal investigation shows that the chip spacing affects the junction temperature of the LED package, and 1 mm wider chip spacing can reduce the temperature by 0.65% based on numerical models. Another model consisting of hexagonal chips shows higher performance. The reduction of junction temperature for this honeycomb approach is around 1.5% for 1 mm wider spacing. The diameter of the board also affects the maximum junction temperature and results showed that a 40 mm board can reduce temperature by 0.35% compared to a 35 mm board. Apart from thermal analysis, optical investigation has also been carried out. Since the current model is a miniature LED light engine, a detector of smaller area can capture the optical properties better than a large detector. A 10 ft × 10 ft plane provides better incoherent illuminance than larger detectors in this study. The value of luminance in angle space is also found to be larger for the smaller detector. From Speos simulation, 1931 CIE color coordinates have been obtained for R, G, B and RGBW LED chip combinations.
Innovative Food Packaging System Design
Authors: Pinuelas Jake , Foust Emine
Published: January 2025

Every industry, including food storage and delivery, should continue to innovate to increase efficiency, reduce risks, and improve customer experiences. The goals of this undergraduate research project are to improve the food packaging system for group serving packages, reduce waste, and improve safety. The current method for transporting all fluid-containing foods in large quantities, such as vegetables, is packaging them in metal cans. There are several different sizes of cans commonly used in the food packaging industry. The standard sizes vary between #1 and #10. For example, #2 cans, also referred to as standard soup cans, can hold approximately 20 ounces while #10 cans can hold close to 109 ounces of fluid. In this study, the focus is on improving group serving packages that currently use #10 metal cans. The main advantages of these cans are their long shelf-life, durability, simplicity, and low cost. On the other hand, the #10 cans have several drawbacks, including being heavy, bulky, and difficult to open without the proper tools. In addition, there is carbon dioxide production in every step of the food packaging and delivery process including the production of cans, processing, and even the recycling process. Inefficiencies during any of these stages result in more pollution than is necessary to transport the food. To address these issues, this study aims to develop an innovative group serving packages that can replace the #10 cans. This paper includes the design process followed to generate alternative ideas along with computational fluid dynamics analysis of the #10 metal cans.
Multi-Disciplinary Analysis and Optimization of Micro-Channel Evaporators
Authors: Ramakrishnan Vignesh , Mohammad Arif , Hicken Jason , Mishra Sandipan , Narayan Shankar
Published: January 2025

Efficient thermal management is necessary to dissipate high heat fluxes in applications ranging from cooling power electronics to nuclear reactors. For these applications, micro-channel evaporators using liquid-vapor phase change offer a compact solution that achieves remarkable heat transfer. However, the optimal geometry for a thermal management system is often unclear, especially when dry-out of the evaporators is a concern. This motivates the development of a design-optimization framework that can help inform the design of heat sinks with micro-channel evaporators. In this work, we present a strategy to numerically solve the coupled heat-sink and micro-channel evaporator heat-transfer problem using the PyMFEM finite element package. By parameterizing the path of the evaporators using b-spline control points and leveraging NASA’s OpenMDAO framework, we have also performed a gradient-based design optimization study to find the optimal trajectories of the micro-channel evaporators within the heat sink for achieving the most efficient thermal management solution.
A Comparative Investigation on the Mechanical Properties of WC-17Co Additively Manufactured by Cold Spray (CS) and High Velocity Air Fuel (HVAF) Technologies
Authors: Smith David , Grabowski Theresa , Thorpe Joncy , Azarmi Fardad , McDonnell Martin
Published: January 2025

Thermal spraying technologies encompass a well-known group of coating deposition methods, but they have also been recently utilized as near-net-shape forming processes. Tungsten Carbide Cobalt (WC-Co) is one of the commonly used materials for applications when high strength at elevated temperatures is required for industrial components. With the introduction of high-pressure cold spray (CS), deposition of ceramics and hard particles such as WC-Co has also become possible using this spraying technology. High Velocity Air Fuel (HVAF) is also a relatively new flame spraying technology for deposition of refractory materials. The novelty of this study is the application of CS and HVAF in the deposition of WC-Co coatings to examine and compare their general mechanical properties. Both samples showed very little porosity and minimal microcracking within their microstructure. However according to energy dispersive spectroscopy (EDS) results, the CS sample contained a reduced WC content due to carbide rebound during the deposition process. The HVAF sample exhibited higher hardness and lower wear rate, which could be attributed to its higher carbide content compared to the CS sample. The stronger bonding and adhesion between splats and deposited layers in HVAF resulted in higher bending stiffness and elastic modulus. The aforementioned tensile mechanical properties were also determined using an emerging numerical simulation method, Object Oriented Finite Element Analysis (OOF). In this method, actual microstructural images are subjected to finite element analysis in order to simulate experimental tests. Results obtained from both FEA studies are in good agreement with experimental elastic moduli results, and have the potential to reduce or eliminate costly and time-consuming mechanical testing in the future.
Investigation of Nonlinear Phenomena in Electrically Coupled Mechanical Oscillators With Applications in Electrostatic Energy Harvesting of Low Frequency Vibrations
Authors: Galarza Matthew G. , Borca-Tasciuc Diana-Andra
Published: January 2025

With the proliferation of Internet of Things (IoT) devices, the demand for sustainable, wireless power sources has gained significant interest. Electrostatic energy harvesters (e-VEHs) present a promising sustainable alternative to traditional battery technology due to their compatibility with silicon-based technologies and potential for on-chip integration. However, existing e-VEHs exhibit modest power levels, necessitating further enhancement. While various optimization techniques have been explored, a comprehensive understanding of the fundamental nonlinear dynamics of these devices remains lacking. This study addresses this gap by conducting a theoretical investigation into the nonlinear behavior of mechanical oscillators coupled with electrical circuits, the basic building blocks of e-VEHs. Special attention is given to bifurcation phenomena, particularly at low frequencies, an excitation range where most e-VEHs operate poorly. This, however, it could be beneficial as it was found trigger frequency-up conversion. Additionally, analysis of dynamic regions revealed the conditions ideal for maximizing output efficiency.
Multi Input Single Output Structural Health Monitoring of Space Vehicles Using the Electromechanical Impedance Method
Authors: Nwokocha Funmilola , Zagrai Andrei , Hunter David
Published: January 2025

The significance of structural health monitoring has increased in recent times as it aids in reduction of failures thereby reducing costs and enhancing structural safety. To achieve this in space structures, thin piezoelectric wafer active sensors are used to measure the electromechanical impedance of a structure. These sensors are bonded to the surface of the structure they are monitoring, and the local dynamic signature of the structure is taken as a baseline, which is then compared with its signatures at different conditions. A notable difference between these signatures could indicate the influence of environmental effects or damage.

The innovative multi input single output (MISO) method of measuring impedance was suggested in this contribution. Thin piezoelectric sensors are installed on a structure and are simultaneously excited acting as actuators while one of the sensors is used to measure the response to the excitation. The measured impedance of the structure can be used to determine the health of the structure being monitored. A mathematical description of the technique is included to reveal the underlying principles of the MISO method. The results of laboratory experimental studies that support the application of the method to space structures are discussed.

A new miniaturized hardware was designed and developed to implement the MISO approach. This hardware incorporates a set of impedance measurement chips and microcontrollers, enabling independent multi-channel structural impedance measurements. The hardware has a data storage capacity using an SD card and can transmit the measured data directly to a satellite communication system on Earth.

An experiment was conducted with the aim of measuring the electromechanical impedance of a fixed panel as a part of a 6U CubeSat. The purpose of the experiment is to monitor the condition of a satellite in a laboratory setting as well as in space.
Impact of High-Strain and Deformation on Heat Pipe Capillary Flow Geometries
Authors: Harry Sayyada , Sinift Bryce , Smith Wyatt , MajidiRad AmirHossein , Oshman Christopher
Published: January 2025

Stretchable electronics and robotics are developing fields that will require significant thermal management strategies. Flexible thermal materials and devices have already been developed by several research groups. Previous studies show flexible heat pipes are a practical solution to cool systems with unique geometries. Therapeutic hypothermia (TH) is an immediate application for stretchable heat pipes, given that precise heat deposition or extraction has been shown to save lives. Hypoxic Ischemic Encephalopathy (HIE), where an infant’s brain experiences a decrease in blood flow, is an example of a condition that is treated with TH. This research aims to use Finite Element Analysis (FEA) and experimental studies, to analyze stress-strain deformation of Polydimethylsiloxane (PDMS), a stretchable material. A prototype was created; this prototype was used to collect data on grove geometry and strain. ANSYS results show variations of wicking structures were oriented either parallel or perpendicular which resulted the parallel model having a maximum shear elastic strain of 0.69884 m/m and the perpendicular model maximum shear elastic strain of 1.1097 m/m. Due to the high strain tolerance and reasonable capillary pumping pressure of 293 Pa in 500 μm wide grooves, Initial PDMS models and experiments show promising effectiveness for stretchable heat pipes. Beyond TH, stretchable heat pipes have potential applications in military and athletic wearable systems, as well as the growing field of wearable electronics.
Hands-On Learning for Enhanced Thermodynamics Education With Refrigeration System Analysis
Authors: Guo Qi , Everage Daxton , Zhang Qinhe
Published: January 2025

Thermodynamics is a fundamental subject in engineering education, yet it often poses challenges for students due to its abstract nature and complex concepts. One particularly difficult topic within thermodynamics is refrigeration cycles, which require a deep understanding of thermodynamic principles and their practical applications. This paper explores the implementation and impact of hands-on refrigeration labs in an engineering curriculum to enhance students’ understanding of thermodynamics, specifically focusing on refrigeration systems.

The hands-on labs utilize a refrigeration cycle hands-on trainer, providing students with practical experience in measuring temperature and pressure, analyzing heat transfer and thermodynamic work with enthalpy and entropy data, computing refrigerant mass flow rate and Coefficient of Performance (COP), and applying thermodynamic principles to real-world scenarios. By conducting these labs, students not only deepen their theoretical knowledge but also develop critical skills such as problem-solving, critical thinking, and practical application of engineering principles.

The hands-on refrigeration labs demonstrate the effectiveness of experiential learning methodologies in enhancing students’ understanding of thermodynamics. Through the lab activities, many students expressed that the labs significantly improved their understanding of refrigeration systems and their ability to apply thermodynamic concepts in engineering practice. This experiential learning approach bridges the gap between theory and practice, preparing students for future engineering challenges and enhancing their readiness for the workforce.
Unveiling the Kinetics of Accelerated Degradation in Polymer Electrolyte Fuel Cells
Authors: Ordónez-Saca Brayan , Santana-Villamar Jordy , Andersson Martin , Espinoza-Andaluz Mayken
Published: January 2025

The polymer electrolyte fuel cells are electrochemical devices that can produce electricity, water, and heat through chemical reactions of hydrogen and oxygen. This manuscript focuses on one detailed state of degradation, called as Membrane Chemical Stability and Metrics. The Accelerated Stress Test under study was standardized by the Department of Energy. Recent advancements in the study of degradation are related to achieving three important objectives: increasing system specific power, reducing system cost, and improving system durability to make fuel cell technology more commercially accessible. The manuscript briefly introduces the Proton Exchange Membrane fuel cells, passing through the mention of the targets proposed by 2025 by the Department of Energy. Next, also addresses the latest advancements and evidence of degradation factors in the main layers of fuel cells, including the Perfluorosulfonic Acid Membrane, the Catalyst Layer, and the Gas Diffusion Layer. Finally, it includes a brief analysis of external factors such as temperature, relative humidity, and the stoichiometry ratio’s influence on understanding the impact on fuel cell performance.
Homogenization of Different Material Groups at High Filler Fractions Using a New Weighted Approach
Authors: Kabir Mobashar , Pervez Tasneem , Al-Jahwari Farooq K. S. , Qamar Sayyad Zahid
Published: January 2025

A new and simple weighted homogenization approach is used to calculate effective properties of different composite material groups. The approach is built upon the principle that a given composite of material-1 and material-2 may be considered to be a mixture of two different cases. This includes the case where material-2 acts as the reinforcing filler in a binding matrix of material-1. And the reverse case where material-1 acts as a filler embedded in a supporting matrix of material-2. The proportions of each of the cases at given constituent volume fraction is defined using the concept of weight functions. Two such functions are considered, one that is independent of the material properties of the constituents and the other that considers the effect of difference in constituent properties. The effective properties calculated using this approach are compared with experimental data from literature and the Mori-Tanaka homogenization model widely used by researchers. It was found that the weighted homogenization approach yields accurate effective properties at high filler fractions, especially when large differences exist between constituent modulus of elasticity. Furthermore, results showed that the weighted approach is well suited for application in the homogenization and analysis of functionally graded structures that exhibit a gradual change in their filler-matrix compositions along one or more directions.
Power System Analysis of Solar and Hydrogen Fuel Cell Powered EVTOL UAV
Authors: Almesafri Nouf , Alhammadi Majed , Zafar Sayem , Santos Gustavo
Published: January 2025

The interest in electric Vertical Take-off and Landing (eVTOL) Unmanned Aerial Vehicles (UAVs) has increased with the introduction of Advanced Air Mobility (UAM) vehicles. This configuration, reliant on multiple lifting motors for vertical flight and a forward flight motor for horizontal flight, necessitates a well-designed power and propulsion system. This study explores a propulsion system combining photovoltaic (PV) panels with a hydrogen fuel cell for eVTOL UAVs. Fuel cell integration is studied to enhance the vertical flight time in which fuel cell is used to power the vertical flight motors. The PV panels are studied to be integrated with forward flight motor to analyze the improvement in forward flight time. This hybrid system aims to extend flight endurance and operational capabilities by harnessing solar and hydrogen energy. The study looks at the integration of these technologies, aiming to address typical energy limitations of batteries and enhance UAV performance regarding endurance, payload capacity, and hover time. These enhancements added to the system achieved an extended hover time of 35 minutes and 55 minutes for 3.5L and 5L hydrogen cylinders, respectively. It also allowed the eVTOL UAV to conduct 4 to 6 take-off/landing cycles, improving the UAV’s operational capability.
Physics Informed Deep Neural Networks for Strength Evaluation Based on Shakedown Analysis
Authors: Huang Songhua , Chen Min , Lim Eng Gee , Liu Zhiyuan
Published: January 2025

In the field of structural engineering and materials science, particularly in aerospace engineering, optimizing structural design for strength while minimizing material usage presents a complex challenge, especially under variable loading conditions. The current research for the first time introduces an approach to strength evaluation through the innovative application of Physics Informed Neural Networks (PINNs) in shakedown analysis. This paper presents a novel methodology that combines the principles of physics-informed machine learning with shakedown analysis’s rigorous demands. Shakedown analysis offers a sophisticated framework for determining the safe load-bearing capacity of structures beyond the conventional elastic limit but within the plastic threshold, without the need to consider the history of loading conditions. This methodology enables engineers to design lighter, more material-efficient structures by safely harnessing the structure’s capacity to withstand loads without reaching failure. Our approach leverages the concept of Physics Informed Neural Networks (PINNs), which integrates differential equations governing physical laws directly into the learning process of deep neural networks. PINNs are further advanced by incorporating self-equilibrating stress field relations, essential for shakedown analysis. This integration enables to accurately predict the shakedown limit strength, crucial for determining a structure’s ability to endure repeated loading without failure. By adding these relations to the mechanical equilibrium equation and constitutive equations within the neural network architecture, it is now offer a comprehensive modeling capability, extending their application to more complex scenarios in solid mechanics, including accurate shakedown limit predictions. The proposed methodology introduces key innovations by extending PINNs to nonlinear problems for complex elastoplastic behavior through shakedown analysis and proposing a multi-network PINN model for more accurate structural response representation. To validate our approach, we employ synthetic data derived from analytical and numerical reference solutions, focusing on convergence behavior and accuracy. Our research highlights the robustness of PINNs in handling sparse data and extrapolating across a wide range of parameters, a critical aspect in the context of shakedown analysis where the design space is vast and complex. This ability to predict accurately under previously unseen conditions not only underscores the potential of PINNs in surrogate modeling but also in the further sensitivity analysis, providing a powerful tool for engineers to explore and optimize structural designs efficiently. Furthermore, the technique is used to determine the shakedown strength for a manned airtight module.
Data-Driven Functional Modeling of Corroded Bolted Joints: A Framework for Remanufacturing
Authors: Afifi Nehal , Kaiser Jan-Philipp , Wettstein Andreas , Lanza Gisela , Matthiesen Sven
Published: January 2025

The circular economy, emphasizing resource efficiency and sustainability, highlights remanufacturing as a key aspect. However, ensuring the quality and reliability of remanufactured products is challenging due to uncertainties from prior product usage, especially for bolted joints affected by corrosion. Current methodologies, including analytical, numerical, and empirical models, often fail to meet accuracy and computation time criteria. Addressing this research gap, this paper presents a data-driven framework that couples empirical methods with artificial intelligence techniques to develop a predictive functional model. This model aims to accurately predict key variables such as load-bearing capacity and thread friction coefficient for the remanufactured bolted joints. The proposed framework comprises three main components: development of a test rig and experimental analysis, identification of key variables, and development of a predictive model. The model is based on empirical data from various Design of Experiments (DoE) tests and is refined using machine learning techniques. By embracing a data-driven approach, this research seeks to fill the gaps left by existing modeling techniques, enhancing the reliability of modeling techniques for corroded bolted joints. This framework contributes to the circular economy, product quality, reliability, and sustainability and can eventually be applied beyond bolted joints, addressing uncertainty across various products.
Digital Twin Enabled Layout Optimization Framework for Photogrammetry Cameras in Reconfigurable Robotic Work Cells
Authors: Pandurevic Stevan , Wang Zi , Sanderson David , Ratchev Svetan
Published: January 2025

Photogrammetry systems are extensively used in industrial manufacturing as an assistance measurement tool. Their non-contact nature and rapid data acquisition allow for high-precision feedback, playing a crucial role in various applications such as quality control and process inspection. However, the dynamic nature of modern manufacturing environments poses significant challenges for traditional static layouts of photogrammetry systems. Manufacturers are under pressure to improve production efficiency, shorten product lifecycles, and increase product variety, necessitating a shift towards reconfigurable manufacturing systems. To address this challenge, this paper proposes a digital twin based optimization framework that enables the exploration of reconfigurable work cells within a three-dimensional domain — a crucial gap in current research. The framework utilizes a virtual representation of the work cell constructed in Process Simulate, allowing for the learning and exploration of the work cell within a three-dimensional domain. The methodology involves defining a visibility parameter that quantifies how much the target object can be seen by the cameras. This parameter is determined by comparing point clouds generated from camera snapshots with a complete point cloud of the target object generated from a CAD model. To optimize camera positions and maximize visibility, an objective function is defined based on the degrees of freedom of the entire system. Initial numerical optimization using a grid search approach achieves a visibility of 96% within two hours. However, the time requirement for this approach renders it unfeasible for reconfigurable manufacturing systems. To address this limitation, heuristic optimization techniques, including Simulated Annealing, Genetic Algorithm, and Bayesian Optimization, are employed, reducing the time taken to find optimal solutions to under five minutes each while maintaining high visibility results of around 90%. These findings demonstrate the efficacy of the digital twin based optimization framework in addressing the challenges of photogrammetry systems in dynamic manufacturing environments. By leveraging heuristic optimization techniques, manufacturers can efficiently adjust camera positions to maximize visibility, thereby enhancing production efficiency and quality control processes. Future research directions may involve further refinement of optimization algorithms and their application to different manufacturing scenarios, ultimately advancing the field of reconfigurable manufacturing systems.
Contaminant Dispersion: Modeling Indoor and Outdoor Airflow Through a Ventilated Building
Authors: Eckstein Adam , Gilliard Joshua , Lee Alyssa , Banko Andrew , Fobar Dave
Published: January 2025

Understanding turbulent mixing of contaminants within and around buildings in urban environments is essential to a wide variety of engineering, public health, and natural applications. For example, air pollution in urban centers has been linked to an increased severity of asthma symptoms. Furthermore, recommendations for populations to shelter in place or evacuate in case of a hazardous chemical release depend on accurate predictions of outdoor and indoor contaminant concentrations. Thus, a detailed understanding of how airborne contaminants move around and through ventilated buildings is indispensable. A great deal is known about internal mixing and external flow around a building separately. However, fewer studies explore the coupling between indoor and outdoor dispersion. This work examines the temporal dynamics of contaminant mixing within and around a small-scale ventilated building. Experiments are conducted in a water channel with a passive, fluorescent dye to model the full-scale contaminant release equivalent. Using Planar Laser-Induced Fluorescence (PLIF), this study investigates the mixing dynamics of the dye as it passes over, through, and around the small-scale building. Additionally, Magnetic Resonance Velocimetry (MRV) is used to measure the three-dimensional (3D) velocity field within and surrounding the small-scale building. Integral quantities of interest are post-processed from the data, such as the concentration time series within the building for a transient release. This provides the residence time of the contaminant within the building and is used to deduce the ventilation rate from a mass balance. The desired end state for this study is the ability to correctly design small-scale building models for use with advanced diagnostics to obtain detailed measurements of the dispersion physics, and to interpret these results to gain inferences about real world events.
Virtual Optimization to Engineer Stents With Minimized Recoil and Restenosis Through FEA
Authors: Shrivastava Rajiv , Ponappa K. , Kinare Amit Bhanudas , Tandon Puneet
Published: January 2025

Cardiovascular disease (CVD) is the leading cause of death worldwide. It comprises coronary heart disease (CHD) and coronary artery disease (CAD), with CAD serving as a primary cause of death. Sufficient treatments, such as percutaneous coronary intervention (PCI), are essential for controlling CAD and thwarting the widespread danger of cardiovascular illness. PCI is a highly effective procedure performed by accessing the internal organs via a needle puncture to treat CAD by a crucial step of implanting a stent to restore the blood flow to blocked areas. Over the last forty years, improvements in PCI technique, together with the design and construction of stent scaffold, have addressed pathophysiologic concerns associated with therapy, leading to better clinical outcomes. Due to their suitable mechanical properties for cardiovascular stents, 316L Stainless Steel and Cobalt-Chromium alloy have been chosen in this study. Based on parameters linked to recoil and restenosis, the performance of two distinct balloon-expandable stent designs is compared. The study’s conclusions include lower recoil rates for 316L SS and Co-Cr alloy, at 1.6% and 4.2%, respectively, and no evidence of Type-I mechanical restenosis in either stent. This study has the potential to spur substantial advancement in the field of interventional cardiology by reducing the rate of recoil and restenosis.
Short-Term Time Series Energy Forecasting for Smart Buildings Using Machine Learning Models
Authors: Chikte Rufaidah , Mathew Ansu , Ramachandran Balaji , Almaeeni Khuloud , Aljasmi Nawal , Vandavasi Jayakumar
Published: January 2025

Short-term energy forecast models that predict energy demand within 1 hour to 1 week ahead have gained popularity due to their effectiveness in residential buildings. This paper compares short-term time series energy forecasts for smart buildings using multiple machine learning models such as statistical, decision-tree-based, and gradient-boosting methods. The data is collected from two energy meters deployed within an IoT laboratory, measuring the energy consumption of the laboratory’s constituents at 15-minute intervals. The energy meters can measure up to 6 three-phase circuits and 18 single-phase circuits. A weather station also provides temperature, humidity, and air quality data. These datasets are combined, processed, and analyzed for their temporal behavior. The data is then inputted into the ML models for training and testing, forecasting the energy demands for the next day and 1-week time horizon. Each ML model is hyperparameter-tuned and cross-validated to fit the nature of the dataset better. The performance of the ML models for the different time horizons is evaluated using performance metrics such as RMSE, accuracy, and MAPE. Accurate energy forecasting will implement better energy management systems through reduced production and operational costs, better power output scheduling, and improved user comfort.
Dynamic Forces Measurements Along an Egg Shaped Damaged Ball Bearing
Authors: Stanley Daniel , Kimani Peter , Ranbhise Siddhant , Azzouz Salim
Published: January 2025

This experimental project investigates the generation of dynamic forces produced from a ball that runs along the edge of a damaged and deformed outer-race of a ball bearing. To simulate this effect, a ball has been made to rotate at a certain speed through the inside of an egg-shaped trackway to illustrate and determine numerically the dynamic forces produced by such damage on a single-row deep-grove ball bearing. To propel the ball through the trackway, four electromagnets have been placed on specific locations along the trackway, allowing the ball to continue rotating so long as electricity is provided to the electromagnetic coils. The trackway and electromagnetic coil holders are 3-D printed using a polyester clear resin. The equation of motion of the system in a free frictionless circling ball state along the path, has been determined using the Lagrange equations. To simulate the motion of the ball, the trackway has been designed symmetrically, both in shape and center of mass. While this project is still a continuing project and not yet completed, it is envisioned that the dynamic forces would be studied as a function of the voltage applied to the coils circuits upon completion. This active device will be used to demonstrate the dynamic forces produced by a damaged ball bearing in a lab setting in the machine elements design course and for senior mechanical engineering working on their capstone project.