bluuebunny/crossref_metadata_2025_split huggingface dataset:
Innovative Food Packaging System Design
Authors: Pinuelas Jake , Foust Emine 
Published: January 2025

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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.