bluuebunny/crossref_metadata_2025 huggingface dataset:
Classification of Damage State in Carbon Fiber Reinforced Composites Using Transfer Learning
Authors: Dabetwar Shweta , Jones Hannah
Published: January 2025

In recent years, composite materials have been implemented in many applications starting from micro-level to large-scale structures. With the increase in applications, the need to understand their behavior under various stress conditions has also increased. Composite materials undergo sudden damage which can lead to catastrophes. In order to avoid sudden catastrophes creating a framework that can effectively use the non-destructive inspection data and to identify the damage accurately is significantly important. In this study, a public dataset of carbon fiber-reinforced polymer composite which contains the Lamb wave signals of composite specimens was used. Deep learning can use the data and make the identification of damage levels but the selection of the correct algorithm is very difficult. Thus, a comparative study of multiple algorithms including transfer learning is presented in this paper to assess the performance of transfer learning models against a general deep learning model. In this study, the signals were converted into images and multiple transfer learning algorithms such as VGG16 and incpetionV3 were implemented and compared. A comparison of transfer learning vs regular CNN algorithm was also performed. A sensitivity analysis based on the number of epochs was also performed. It was concluded that sensitivity analysis is significantly important to provide optimum values of hyperparameters to achieve the highest performance of each algorithm. It was observed that pre-trained weights provided better performance than the non-pre-trained weights.
Shaping the Future of Engineering Education: Exploring Trends and Insights in ASME-IMECE Engineering Education Conference Papers, 2012-2023
Authors: Alves Anabela C. , Kumpaty Subha , Shimek Gary , Alves Diogo M. , Leão Celina P.
Published: January 2025

The Engineering Education (EE) track in the International Mechanical Engineering Congress and Exposition (IMECE) conference of the American Society of Mechanical Engineering (ASME) has been publishing papers related to Engineering Education learning methodologies, methods, labs, tools, and competencies in all fields of engineering since 1999. Despite evolving trends, the overarching goal of the papers remains constant: to enhance student learning experiences through active learning methodologies and innovative approaches that empower students to take ownership of their learning journey. In this paper, an overview is presented of publications in the EE track spanning the past twelve years (2012–2023). An analysis was conducted to address quantitative and qualitative aspects of over 500 papers. As an initial step, this project features the results of bibliometric analyses. A large language model (LLM)-enabled platform was used to efficiently extract key points, trends, and outcomes from each title, abstract, and keywords of each conference paper. This approach enabled the development of insights into the evolving landscape of EE research. The primary goal of this analysis was to uncover and elucidate emerging trends in the field of EE, thereby offering valuable insights that can shape the future research agenda. Beyond this scholarly exploration, the authors aspire to actively promote the work of the numerous researchers whose papers have been published. Moreover, they aim to inspire others within the academic community to contribute to the discourse by sharing their research through publication. An important finding is that papers during the study period from 2012 through 2023 are associated with a movement from traditional engineering education topics (e.g., mechanical engineering and design) to engineering education and high-tech impacts (e.g., machine learning, augmented reality).
Modal Excitation Analysis for Interior and Surface-Breaking Cracks in Two-Dimensional Half Plane Using Boundary Element and Perturbation Methods
Authors: Maruyama Taizo , Sugita Naohiro
Published: January 2025

This paper presents a perturbation analysis of the excitation problem for an open domain. As a fundamental study, it addresses wave scattering by a crack in a two-dimensional domain to avoid fictitious eigenfrequency issues, which are encountered in a boundary integral equation. The system comprises a homogeneous, isotropic, and linearly elastic half plane containing interior and surface-breaking cracks. The modal amplitude is approximated using the perturbation method with the Taylor expansion around the complex-valued eigenfrequency for the open domain. The eigenfrequency problem for an open domain is solved using boundary element method and Sakurai-Sugiura method, which is one of the nonlinear eigensolvers. Several numerical results demonstrate that the proposed perturbation method approximately evaluates the modal amplitude due to real-valued frequency excitation.
Linear Quadrature Method of Moments for Solving the PDF Model Equation for Turbulent Reactive Flows
Authors: Wang Yunchu , Wang Yize , Yuan Li
Published: January 2025

Quadrature-based moment methods (QBMMs) are an alternative approach for the numerical solution of the probability density function (PDF) model equation for turbulent combustion. In this work, we propose a new QBMM called Linear Quadrature Method Of Moments (LQMOM) for the univariate PDF case. We use a set of predefined quadrature nodes and weights in the sample space to establish linear equations for the PDF values at the nodes in the moment inversion. The LQMOM is more economic than the original QMOM which needs to solve nonlinear equations in the moment inversion. However, the LQMOM may return negative PDF values for a non-smooth PDF. So we construct the LQMOM-QMOM hybrid algorithm. Further, we develop the linear Conditional Quadrature Method Of Moments (LCQMOM) and a simplified version (LCQMOM-S) for the multivariate PDF case by referring to the main idea of the original CQMOM. The LQMOM-QMOM hybrid algorithm is tested in a plug-flow reactor example, and the LQMOM(-S)-CQMOM hybrid algorithms in conjunction with a LES method are tested in two compressible turbulent reactive flow examples. The numerical results show that the hybrid algorithms can reduce 20–35% computational cost compared with the respective QMOM and CQMOM.
Vat Photopolymerization 3d Printing of Multifunctional Contact Lenses for Ocular Applications
Authors: Hisham Muhammed , Lee Sungmun , Butt Haider
Published: January 2025

Smart contact lenses offer unique opportunities as personalized, non-invasive devices that simultaneously perform a wide range of functions. However, the actual production of smart contact lenses is rather challenging. Herein, two vat photopolymerization 3D printing techniques are presented for producing multimaterial and multifunctional contact lenses. In the first technique, a contact lens is 3D printed with hollow channels, which are later filled with resin containing different dyes or drugs. In the second method, functionalized structures are directly 3D printed on top of a commercial contact lens. Atto dyes enable red-green and blue-yellow color vision correction. Photochromic dye enables UV monitoring, warning the wearer in case of UV hazards. Multifunctional contact lenses which can perform ocular health monitoring can also be produced through these techniques. Drug delivery is explored from drug-loaded structures added on the contact lens. Herbal eye drops and phenol red were utilized for studying drug release. The dyes and drugs are incorporated into hydroxyethyl methacrylate and polyethylene glycol diacrylate (HEMA:PEGDA) hydrogels. Drug release rate can be varied by varying the drug loading or the hydrogel composition. The multifunctional contact lenses displayed excellent optical and material properties. Drug loaded structures are printed as peripheral structures that do not hinder vision. These multifunctional contact lenses can enable simultaneous color vision correction, health monitoring and drug delivery without disturbing the daily routine of the wearer. The study demonstrates the potential of vat photopolymerization 3D printing for cost-effective production of multifunctional contact lenses.
Vibration Control Coupler Design for Robot Learning From Human Polishing
Authors: Yang Jiaqi , Reyes Ashley , Shanks Jack , Dey Rohit , Chernjavsky Patrick , Zheng Yihao
Published: January 2025

Polishing is a finishing process using abrasive tools to improve workpiece surface quality and geometric tolerance. Polishing has been primarily performed manually, despite recent advances in automation and robotics in manufacturing. Manual polishing is troubled by quality control, workforce training, and occupational hazards. Robotic implementation may enhance polishing quality, efficiency, and safety. Robotic polishing of complex geometries is challenged by trajectory planning, force control, and general adaptability. Robot learning from human could potentially address these challenges to handle complex geometries. To learn from human polishing, the compliance and structure differences between robotic and human arms could be an obstacle. In this study, we aim to design a coupler, connecting the polishing tool to the robot end effector, to bring the polishing vibration of the robotic system close to that of the manual polishing. To evaluate the coupler vibration control performance, the polishing vibrations characterized by, a triaxial piezoelectric accelerometer and polishing forces measured by a 6-axis force/torque sensor were compared in three cases: robotic polishing with the coupler (RP_c), robotic polishing without the coupler (RP_o), and the manual polishing (MP), under three normal polishing forces of 10, 20, and 30 N with low, medium, and high pneumatic power settings. The human arm and the proposed coupler suppressed the higher dominating frequencies excited by the sander vibration in RP_o and reduced the magnitude of the dominating frequencies The results demonstrated that the robotic system with the coupler could achieve a similar polishing vibration as manual polishing, which could bring down the barrier to future robot learning from human polishing.
Design of Experiments Informed Investigation of Magnetic Field Assisted Nickel Electroplating on Copper
Authors: Balsamy Kamaraj Abishek , Merugu Saketh , Mahajan Chaitanya , Gupta Anju
Published: January 2025

This study investigates the synergistic effects of electrolyte flow velocity and magnetic fields on the surface quality of nickel electroplated onto copper substrates. Nickel coatings protect copper from oxidation and fouling, prolonging component life. An electroplating apparatus with a Watts bath and copper electrode was used to compare three deposition methods: static bath, flowing electrolyte, and flowing electrolyte under a magnetic field. Our investigation indicates a direct relationship between current density and deposition thickness, with thicker deposits at lower flow speeds and narrower electrode gaps, suggesting gas bubble effects. Applying a perpendicular magnetic field generally increased current density and thickness, except at the highest flow rate and widest gap. Design of Experiments analysis revealed the magnetic field homogeneously improved surface roughness uniformity compared to other variables. Lower current densities yielded smoother surfaces. Magnetic field exposure enhanced wettability, indicating increased surface energy that can be attributed to ion alignment during deposition. These findings demonstrate magnetic fields can manipulate the wetting behavior of electroplated surfaces, with potential applications in immersion cooling of microelectronics. Additionally, controlling wettability through magnetic field-assisted electroplating offers opportunities to tailor surface properties for specific applications.
Experimental Investigation on the Transcritical Dynamic Characteristics of Water Wall for a Supercritical CFB Boiler
Authors: Yang Dong , Du Xiaocheng , Guo Zerui , An Ning , Han Lei , Wei Ziyu
Published: January 2025

When the boiler load varies, the operational parameters in the water wall will change, this process is called as dynamic process. Dynamic process presents unique flow and heat transfer phenomena within the water wall. To investigate the process, the research was conducted in a vertical upward smooth tube for a supercritical circulating fluidized bed (CFB) boiler. Experiments were conducted to explore the dynamic characteristics during transcritical pressure process. The results indicate that as system pressure decreases from 23 MPa to 21 MPa, the mass flux within the tube increases sharply, and the outlet fluid temperature decreases. Concurrently, a rapid rise in wall temperature was observed. As the inlet mass flux increases, the wall temperature eventually returns to the normal value. The dynamic heat transfer coefficients were calculated throughout the transcritical pressure process, revealing stages of heat transfer deterioration, subcooled boiling, and single-phase water heat transfer. In addition, experiments and numerical simulations were carried out to explore the dynamic characteristics at supercritical pressure. The dynamic response curves during the step process of heat flux and inlet enthalpy under supercritical pressure conditions were obtained. As the inlet enthalpy decreases, the system mass flux increases, and as the heat flux increases, the system mass flux decreases. And there is no rise in wall temperature during the dynamic response at supercritical pressure.
Development of an Instrumented RC Car to Enhance Understanding of Steering Characteristics in a Vehicle Dynamics Course
Authors: Weaver Jonathan M. , Henri Christine R.
Published: January 2025

An instrumented RC car has been developed to enrich the learning experience of students taking a university course in vehicle dynamics. The involved course focuses on modeling and analysis of the dynamics of vehicles, focusing particularly on four-wheeled motor vehicles. The structure of the vehicle dynamics course is fairly traditional, with classroom lectures, homework assignments, and five quizzes. Historically, the course lacked much interaction with hardware to illustrate the principles being taught, except for some simple demonstrations. The course does include some hands-on demonstrations such as the effect of front vs rear wheel lockup and trailer instability, using toy cars and RC cars, respectively. Students also do some physical tests with cardboard models to understand cg location and static stability on a grade. Students experiment with the basics of understeer vs oversteer by running an RC car and wrapping either the front or rear tires with duct tape to modify the front or rear cornering stiffnesses, observing how the steering characteristics change in each case. In order to further enhance the hands-on aspects of the course, an RC car was instrumented with an onboard Arduino-based data collection and logging system. The system includes an optical counter to measure the vehicle speed (via driveshaft speed), a tri-axis accelerometer to measure all three principal accelerations (although the one of interest in this work is the vehicle’s lateral acceleration), and the steering servo position (indicative of steering angle). The system also includes an LCD display to show the system status and an SD card writer to allow the captured data to be written for subsequent analysis. During the most recent offering of the course, the instrumented RC car was used to demonstrate a constant steering angle handling test for the vehicle configured to exhibit understeer (US) (the behavior of the vehicle in its stock configuration) and oversteer (OS) (achieved by adding duct tape to the rear tires to increase the rear slip angle relative to the front slip angle, although the vehicle still exhibited US at low speeds before transitioning to OS at higher speeds). The students took part in the car’s operation and subsequent analysis of the data. For each handling configuration, they made a plot of the radius of curvature (computed from the speed and lateral acceleration) vs. lateral acceleration. The students observe that, as expected, the plot for the vehicle exhibiting US shows a negative slope, and the plot for the vehicle exhibiting OS shows a positive slope at higher speeds, after initially showing a negative slope at lower speeds. The paper discusses some background, instrumenting of the RC car, data collection, and data analysis. Additional demonstrations are planned for future offerings of the course, including a constant radius test and a constant speed test.
Integrated Product and Process Design for Robotic Additive Manufacturing
Authors: Pini Fabio , Dalpadulo Enrico , Leali Francesco
Published: January 2025

Robotic Additive Manufacturing is an emerging trend thanks to effective advances compared to traditional machines based on Cartesian movements. Reduction of the volume of supports and the related “staircase effect” increased inaccuracy and surface roughness, large printing volumes, more flexibility on the printing strategy, and use of multiple materials are just some of the potential benefits returned by robotic additive manufacturing. Nevertheless, the selection of suitable strategies, planning of the printing trajectories and definition of the related code to drive the robot movements are still managed by different digital tools that make it challenging to identify the optimal process. This work describes a Design for Robotic Additive Manufacturing approach to support the development of the printing process driven by complex machines such as robotic arms. Based on an available computer-aided design platform, the digital replica of the robotic system is recreated, and additive process alternatives are applied to simulate the fabrication of an automotive part. A first assessment of the design integration by the approach suggested is evaluated by the simulation of fuse material deposition for a simplified version of the selected use case.
Heat Transfer in Tightly Packed Cylinder Arrays
Authors: Kovachev Martin , Sexsmith Cameron , Ricklick Mark
Published: January 2025

Cylindrical arrays with a cross flow are commonly used for heat transfer augmentation within an internal channel. In most applications, the cylinders have a spacing of over 2 diameters (2D) between their center points in both the lateral and downstream directions. One option for battery thermal management in hybrid/electric aviation is to use cylindrical batteries packed in arrays with an applied cross flow. In the context of aviation, it is always important to maximize space and weight savings. Tightly packing these cylinder arrays with a spacing of under 2D in both directions would save on both of these. A variety of cases are computationally modeled to develop a relationship between changing spacings and their influence on the heat transfer on the cylinders. Results show that when looking at tightly packed spacings and matching the defined Reynolds number, heat transfer effectiveness stays roughly the same until extremely tightly packed cases. Since the spacings get tighter and the flow area gets smaller, this means the amount of heat transfer per a given area increases and so there some heat transfer benefit to packing the batteries tighter in addition to weight and spacing savings. This trend peaks at a spacing of 1.25D before dropping off.
Stabilization and Control of Crates for Offshore Cranes
Authors: Rykkje Thorstein R. , Venge Mats , Pedersen Sjurd Sandvik , Wiers Henrik , Impelluso Thomas
Published: January 2025

The loading of crates onto ships poses inherent dangers stemming from uncontrolled swinging motions. This paper proposes the application of gyroscopic stabilization to enhance safety protocols. First, this study explores the dangers associated with conventional crate loading methods. Then this paper explores the potential of gyroscopic technology to reduce the swinging motion of loaded crates. By resisting changes in orientation, gyroscopes have demonstrated efficacy in stabilizing objects in motion. This research further explores how gyroscopic mechanisms could be employed to facilitate controlled rotational movements of cargo, enabling precise manipulation for optimal stacking and alignment. Such advancements would represent a significant leap from traditional manual or impact-based methods, enhancing safety and operational efficiency in complex loading scenarios. The Moving Frame Method (MFM) was chosen as the foundation for the analysis. The MFM is an approach to machine dynamics. Founded on Lie Group Theory and associated algebra, Cartan’s notion of moving reference frames, and a compact notation, the MFM simplifies single and multi-body dynamics. This paper presents the analysis and simulation and discusses how the MFM empowers student exploration of advanced research and development. Ultimately, however, the project is one of design. This paper reports on various design possibilities that were considered prior to commencement of the analysis, simulation, and construction. This research contributes to the ongoing discourse on maritime cargo safety by providing a comprehensive analysis of the dangers associated with conventional loading practices, emphasizing the urgent need for improved safety measures, and proposing gyroscopic stabilization as a practical and effective solution. The findings underscore the potential of gyroscopic technology to revolutionize cargo loading procedures, fostering safer and more efficient cargo handling.
Blood Warming Device for Austere Location Blood Transfusion
Authors: Christopher Jason D. , Anderson Michael L. , Lee Matthew , Pinsenschaum Lydia , Henry Dylan , O’Bannon MeiLi , Brinkman Jared
Published: January 2025

The Air Force Special Operations Command (AFSOC) identified a need for a more effective fluid warmer in austere operational environments, including the back of vehicles, helicopters, or airplanes. Current technologies for portable fluid warmers often do not provide an adequate flow rate or do not heat the fluid to adequate temperatures when used in field settings. Consequences of insufficient blood warming can cause hypovolemic or hypothermic shock in the patient. The product was designed to take low temperature blood (approximately 4°C) and heat it to 37°C at a desired flow rate of 200 mL/min or greater. Such a design could be used in other austere environments as well as in developing nations, remote locations around the globe, or even one day in space. This paper covers the project scope, background research, existing products, concept development, prototyping, and testing. Preliminary results indicate it is possible to heat blood to the desired temperature, however the device as built was not able to achieve such warming, thus improvements for the future are provided.
A Comparative Analysis of Lane Keeping Assist and Lane Departure Warning Systems on Curved and Straight Roadways
Authors: Harrington Shawn , Takbhate Shubham Ramraja
Published: January 2025

Comparative testing was conducted to evaluate the performance of Lane Keeping Assist (LKAS) and Lane Departure Warning (LDW) systems across three different vehicles, including a 2016 Ford F-150, 2014 Subaru Forester, and the Mobileye 6 series integrated and installed into a 2013 Mitsubishi Lancer. The LKAS and LDW systems were tested on both a curved rural roadway at approximately 40 miles per hour (mph) and a straight rural roadway at approximately 55–60 mph in Pennsylvania. Whenever possible, the vehicle’s Controller Area Network (CAN) bus data was analyzed using Vehicle Spy (VSPY) hardware and software and integrated with a VBOX 3i RTK DGPS data acquisition system. A road-facing nadir GoPro Hero8 action camera was synced with the VBOX data acquisition system and was mounted above the vehicle’s left front wheel to monitor testing. The video obtained from the GoPro Hero8 was compared with the data acquired from the CAN bus, instrument cluster, and/or driver interface to compare the performance of the LKAS/LDW systems on the Ford, Subaru, and Mitsubishi on both curved and straight roadways at different speeds.
Thermal Stresses Analysis of Thermoelectric Materials Based on Turbojet Engine
Authors: Aljaghtham Mutabe
Published: January 2025

Thermoelectrical generators (TEGs) require high-temperature differences across thermoelectrical (TE) materials to generate high TE output power. However, the increasing thermal gradient causes thermal stresses on TE materials, which might lead to thermal fatigue. In this study, finite element method-based simulation is presented to quantify the Von Mises stresses on annular TE legs attached to the exhaust pipe of the turbojet engine. The thermal stresses build up on TE elements as the heat transfer coefficient of hot gas flow increases. Therefore, the cascade TEG system is designed to overcome high temperatures that are subjected to TE legs. Besides the cascaded TE model, the unileg (n-n or p-p) cascade TEGs system is also designed to alleviate high thermal stress exposed on the TE materials. Silicon germanium is selected as TE material around the exhaust pipe, and skutterudite is chosen next to the cold side. The design of geometry parameters of annular TE modules is also optimized to decrease stresses. At a heat transfer coefficient of 50 W/m2.K, the results showed that the Von Mises stresses of silicon germanium and skutterudite are reduced by 22% and 15%, respectively, when the unileg TE cascade is used compared to an uncouple (conventional) TE cascade system.
CCD IK Implementation in Unity for Finding the Angles of Industrial Robots’ Links
Authors: Nutonen Karle , Kuts Vladimir , Otto Tauno
Published: January 2025

The nature of the industry has undergone significant development over the past decade, moving towards digital production influenced by the concept of Industry 4.0. This development has been facilitated by the easy accessibility and relatively simple implementability of various technologies. Nearly all manufacturing processes are now robotized to increase and enhance productivity and quality. However, the process of robotization is complex, requiring consideration of various predetermined aspects, particularly concerning safety from a human perspective, where the process must be safe for humans. Nowadays, it is possible to employ simulation environments with digital avatars, providing a highly accurate digital replica of the real environment, taking into account various real-life physical dimensions. A major bottleneck in the design of the robotization process is achieving precise and realistic movement using inverse kinematics functionality. Analytical approaches are commonly used, necessitating the creation of specific mathematical formulas for each industrial robot model. They are applicable only when working with the given robot or similar industrial robots. This paper focuses on the CCD IK (Cycling Coordinate Descent Inverse Kinematics) implementation. This implementation aims to determine the correct angles of the robot’s joints based on the end-effector’s position in Cartesian space, also considering the end-effector’s rotation.
Investigating the Impact of Origami Structures on Side Collisions: Scaling and Material Optimization for Enhanced Safety in Electric Vehicles
Authors: Dang Aaron , Park Yong Seok
Published: January 2025

This paper investigates the impact of origami structures on side collisions, with a focus on mitigating crash energy and intrusion. We specifically chose an existing electric vehicle due to the inherent risk of fires resulting from cell punctures caused by collisions, leading to internal short circuits. The fire from a crash can then propagate across the battery pack which poses a significant danger. To achieve our objectives, we modified the side structure of a 2014–2016 Tesla Model S P85D battery with origami designs and varied parameters such as size (scaling) and materials. All models were created in Solidworks while results were obtained using the ANSYS software (2023), following a validation process. To examine the influence of materials on the origami structure, we conducted tests using three different materials: Aluminum, Magnesium, and Acrylonitrile Butadiene Styrene (ABS). Preliminary tests indicate that reducing the scale of the origami structure by 55% yields the lowest von-mises stress while scaling it up 10% provides the least total deformation. Furthermore, comparisons at 10% scale concluded that ABS exhibited the least total deformation and von-mises stress. Results from the side structure tests concluded that ABS experienced the least von-mises stress while aluminum performed the best in terms of total deformation. In addition, analysis linking material density to the model’s mass concluded that ABS reduces the kinetic energy and intrusion the most during a collision.
Multiscale Quasi-Static Finite Element Analysis of Commercial Lithium Primary Batteries
Authors: Knee Wesley , Ginga Nicholas J.
Published: January 2025

Accurate mechanical models of lithium batteries are important during their development to create safe and reliable designs, but computational challenges exist for models that include the entire battery geometry. The large overall diameter of batteries combined with contrastingly thin internal layers of anode, cathode, and separator films make exact finite element models computationally difficult. An existing method to simplify the battery geometry and improve computation times uses representative volume elements (RVE’s) for the thin internal layers. The use of RVE’s in battery models can provide accurate solutions of the overall mechanical deformation of batteries but lacks details regarding the mechanical behavior of the individual internal layers. In this study, the use of RVE’s is combined with a global-local finite element modeling approach in order to perform mechanical analysis on the entire battery while also providing detailed mechanical behavior of the individual layers. This modeling approach is demonstrated by subjecting cylindrical lithium primary cells to quasi-static compressive loading between parallel plates. This was performed using off-the-shelf consumer grade lithium primary batteries including a cylindrical AAA lithium primary battery and a 3V cylindrical subcomponent cell from a 9V lithium primary battery. In this study the global-local modeling approach utilizing RVE’s is developed including the mechanical properties for the RVE, global model geometry, and local model geometry. The RVE mechanical properties and overall global-local modeling approach using RVE’s developed here was also applied to an 18650 lithium battery form factor for validation and agrees with published results for the battery’s mechanical behavior.
Comparative Analysis of Stresses and Deformation of a Common Construction Helmet With and Without a Deformation Zone Using Finite Element Analysis
Authors: Hand Bryson , Schonning Alexandra , Bevill Grant , Simsiriwong Jutima
Published: January 2025

Construction helmets are one of the most common forms of personal protection utilized in the workforce. Within industries that they are required, construction helmets are commonly referred to as “hard hats.” The purpose of a construction helmet is to mitigate impact forces and repel objects away from the head. Furthermore, they are designed to reduce the risk of concussion, Traumatic Brain Injury (TBI.) and other forms of head injury.

The goal of this project is to test whether a deformation zone should be included in future construction helmet designs. Deformation zones are used as a method to absorb impact energy through intentionally deforming, thereby reducing the impact energy absorbed by the body. Deformation zones have been adopted into other forms of personal protective equipment such as sport helmets and bicycle helmets, which have seen positive results in impact testing. This project utilizes the MSA V-Gard Type 1, Class E helmet, which is commonly used in the workforce. The MSA V-Gard helmet is ideal for this project due to the ridge at the top of the helmet shell which allows for a deformation zone to be integrated into the helmet design. Two models were created: One model consists of the scanned helmet without a deformation zone, the second model consists of the scanned model with a deformation zone. The goal of this study is to determine whether the addition of a deformation zone to a construction helmet model will help to mitigate impact forces. The results from static loading of the two models show that the helmet with a deformation zone had greater displacement than that of the model without a deformation zone. This validates the need for future dynamic impact testing to determine whether this displacement of the helmet with a deformation zone will absorb more energy than the helmet model without a deformation zone. The implication of this study, as well as future studies, is that construction helmet designs that incorporate a deformation zone could improve the safety of the construction industry. The comparative analysis of the two helmet models focuses only on the effect of the geometric design of the two helmet shell models, not the effect of the webbing/suspension system.
Comparative Analysis of Wind Energy Harvesting Performance Using Multi-Stage Savonius Turbines With Non-Contact Magnetic Excitation
Authors: Alhumaid Saleh
Published: January 2025

Small-scale energy harvesting technologies, particularly piezoelectric transducers, offer promising avenues for generating power from environmental sources. However, current research is mainly centered on optimizing piezoelectric materials and deformation mechanisms, neglecting the critical role of rotor blade design. A deeper investigation is presented here to improve rotor blade performance in increasing wind energy harvesting efficiency, especially at low wind speeds. This study presents an innovative wind energy harvester design featuring concentric rings with piezoelectric benders and strategically positioned magnetic plates. Experimental validation demonstrates successful power generation, with an average output of 524 microwatts. The optimized configuration utilizes piezoelectric benders with a diameter of 35 mm and a 6.5 mm distance between magnets, with Neodymium Magnets N42 employed as permanent materials. Notably, the prototype exhibits resilience and robustness, performing well under sustained wind speeds without damage. Comparative analysis of harvester performance using single and multi-stage Savonius turbines highlights the optimized configuration’s efficiency. Comprehensive laboratory investigations validate the rotor blade design’s efficacy, showcasing its potential to enhance small wind energy harvesting systems. By bridging current research gaps and showcasing promising experimental results, this work contributes to advancing sustainable energy solutions across various applications.
Comparative Analysis of Mechanical Behavior and Material Modeling in Additively Manufactured PEEK With Diamond TPMS Lattice Structures
Authors: Gide Kunal Manoj , Bagheri Shaghayegh
Published: January 2025

This study examines architectured lattices’ mechanical and morphological characteristics, leveraging additive manufacturing advancements and assessing various finite element analysis (FEA) models commonly used to predict their mechanical behavior. Various FEA material models, such as Arruda Boyce (AB), Yeoh Hyperelastic (YH), and Johnson Cook (JC), are compared to address limitations of classical models with respect to experimental verification under uniaxial compression testing of AM polyether ether ketone (PEEK) lattice samples. The study examines PEEK lattices with 50% porosity, produced via fused filament fabrication (FFF) employing triply periodic minimal surface (TPMS) structures, highlighting diamond unit cell geometry. The data for the material model was calibrated using Mcalibration software. Employing nTopology software for modeling and Abaqus Standard 2023, for computational analysis, lattice structures undergo simulation under uniaxial compression. The study primarily examines elastic and yielding regions. Upon comparing computational results of each model with experimentally obtained mechanical properties, it became evident that AB model was the most accurate in predicting mechanical properties of diamond-based lattices. This research contributes to the proper selection of a material model for predicting the mechanical properties of TPMS-based lattices, thereby advancing the understanding of lattice structures’ mechanics and offering crucial insights for future innovations in advanced materials science.
Enhancing Defective Casting Classification in Manufacturing Using Deep Learning: A Case Study With VGG16
Authors: Gurupatham Sathish , Palreddy Chandana , Vijayakumar Harshith , Loignon Tyler
Published: January 2025

In the manufacturing industry, the detection of defective products, such as castings, is crucial for ensuring product quality and preventing potential safety hazards. Deep learning techniques, particularly convolutional neural networks (CNNs), have emerged as powerful tools for automating the detection and classification of defects in manufacturing processes. This study explores the application of deep learning, specifically utilizing the VGG16 model, for classifying defective castings from normal castings in the manufacturing field.

The dataset comprises a collection of images depicting both normal and defective castings. Initially, the VGG16 model was trained on a dataset consisting of 4100 training images, 1200 validation images, and 500 testing images. The model achieved a moderate accuracy of approximately 60% on the testing set, indicating its ability to classify defective castings to some extent. However, the model’s performance in terms of precision, recall, and F1 score was suboptimal.

To enhance the model’s performance, several strategies were employed. First, the VGG16 layers were fine-tuned by selectively unfreezing and training certain layers of the pre-trained model. This process allowed the model to adapt more effectively to the nuances of the specific dataset. Additionally, regularization techniques, such as dropout and L2 regularization, were incorporated to prevent overfitting and improve generalization performance.

Moreover, the learning rate of the model was adjusted, and different values were experimented with to optimize its performance. Learning rate schedules and adaptive optimizers, such as the Adam optimizer, were utilized to dynamically adjust the learning rate during training.

Furthermore, the training dataset was augmented by applying various data augmentation techniques, such as rotation, flipping, and zooming, to increase the diversity of the images. By balancing the dataset to include an equal number of training, validation, and testing images, consisting of 4100, 1200, and 500 samples respectively, a significant improvement in the model’s performance was observed.

After implementing these enhancements, the model achieved impressive results, with an accuracy of 89.6%, precision of 91.4%, recall of 89.6%, and F1 score of 89.5% on the testing set. These findings underscore the effectiveness of deep learning approaches, particularly when combined with fine-tuning, regularization, and data augmentation techniques, in accurately detecting and classifying defective castings in the manufacturing industry. Such advancements have the potential to streamline quality control processes, reduce production costs, and enhance overall product reliability and safety in manufacturing operations.
Enhancing Degradation Models of Mechanical Systems Through Uncertainty Quantification
Authors: Ajayi David Omodolapo , Ekwaro-Osire Stephen , Gandur Nazir Laureano , Lopez-Salazar Camilo
Published: January 2025

Over the years, various techniques have been developed to construct remaining useful life (RUL) models for reliability analysis based on run-to-failure experiments for rolling element bearings. The naturally produced experimental data from open-source repositories, XJTU-SY and PRONOSTIA ball-bearing datasets, were used in this study. The PRONOSTIA dataset has no records for its location of damage, and knowledge of the bearings’ damaged components will benefit studies requiring it. Both datasets are testaments to fault commencement and complete failure occurring at different times for identical bearings running under the same operational conditions. Hence, a bearing will have multiple points where incipient fault points (IFs) and end-of-life points (EOLs) could occur. Thus, attributing all this information to a singular degradation model is essential. This study answers the research question: Can quantification of uncertainty enhance degradation models for rolling element bearings? The objectives of this paper are to (1) identify the unknown damage locations, (2) quantify the uncertainty of the IFs and EOLs, and (3) determine the degradation model considering uncertainty. Due to limited data from both datasets, the study employs the maximum entropy principle (MaxEnt) to define uncertainty for both the IFs and EOLs. This is achieved by plotting probability density functions (PDFs) such that both the IFs and EOLs transcend as random variables (RV) instead of deterministic parameters. MaxEnt is further used to construct a degradation model by connecting the PDF, cumulative distribution function, and reliability model. An approach based on uncertainty quantification was proposed to determine a degradation model of ball bearings. The approach is shown to be generalizable to other engineering systems.
Analysis of Convection Heat Transfer on a Plate With Porous Media
Authors: Khoso Abdul Qadeer , Fareedi Atiq Ur Rehman , Khan Hurmat , Buonomo Bernardo , Manca Oronzio , Nardini Sergio
Published: January 2025

The use of porous media for the purpose of heat transfer is gaining ground these days. It also gives an opportunity to combine impinging jet flows (IJF) with porous media for the purpose of heat transfer enhancement. This paper presents the experimental and numerical study of the analyses of heat transfer on the plate with diverse nozzle to plate distance or channel height (H) in the presence of the porous media placed over the heated plate using IJF. IJF works by throwing the pressurized fluid from the nozzle exit and pounding on the heated plate after passing through the metal foam (MF) in our case. This passage of fluid from the MF extracts heat within the MF and cools down the heated plate. The repeated experiments have been performed with various variables under consideration mainly: diversity of metal foam in terms of PPI and various channel height to jet diameter ratio and diverse fluid flow. The outcome of the experimental study suggests that generally MF of 20 PPI with H/Dj ratio 8.57 has a greater value of Nusselt number (Nu) on the given Reynolds number (Re) in turbulent case while in laminar case MF of 10 PPI has greater value of Nu. The results are different when the H/Dj ratio changes. The crux of this study describes the suitable configuration of MF at specific H/Dj ratio for greater heat transfer. The results could assist in designing a suitable heat exchanger for application.
Environmental Impact and Techniques for the Reuse and Disposal of Automotive Batteries
Authors: Capata Roberto , Calabria Alfonso
Published: January 2025

Lithium batteries represent the best solution for storing electrical energy; they are now an integral part of electronic devices (laptops and smartphones) and electric vehicles. Their reuse (Second Life) has taken hold for some time now: at the end of their initial operating life cycle, they can be used for other purposes. As far as recycling is concerned, several studies and research have focused on recycling methods. There are over 300 studies on various recycling methods and techniques, of which more than 75% are concerned with metallurgical processes, and about 70% are about metallurgical processes. The results show that all the materials that make up the battery, including lithium, can be recycled. In this paper, the authors want to analyze the state of the art of reuse and recycling, detect any critical issues of the process in its entirety, and — where possible — proceed to its optimization. The recycling and reuse of batteries constitute a new economic and industrial flow; batteries represent virtual mines from which to extract materials not present in the national territory. The production of batteries constitutes the most significant environmental impact of the same technique, and their reuse is beneficial for reducing emissions. Nevertheless, there is a need for standardization of disassembly methods on a large scale, which could be ensured by the increase in the market but requires constant research.
Enhancing Tubular Structure Integrity Assessment: A Machine Learning-Integrated Failure Assessment Diagram Approach
Authors: Elkhodbia Mohamed , Negi Alok , Barsoum Imad , AlFantazi Akram
Published: January 2025

Failure Assessment Diagrams (FADs) are a cornerstone of structural integrity analysis, but their complexity can limit their adoption in certain engineering contexts. This study introduces a novel machine learning approach designed to make FAD analysis more accessible and computationally efficient. The method leverages artificial neural networks (ANNs) trained on FAD models derived from rigorously calculated numerical contour integrals. Finite Element Analysis (FEA) was used to generate the FAD envelopes that is used to train the ANNs. The resultant ANNs demonstrate several capabilities: generating precise FAD envelopes, predicting limit loads, and incorporating the effects of residual stress via the Φ parameter. This work highlights the potential of ANN-based FADs as a powerful and adaptable tool, streamlining complex structural integrity evaluations without sacrificing accuracy.
Anatomical Data Acquisition Protocol Using Low-Cost 3D Scanners for Project Zule: 3d-Printed Breast Prostheses for Women Undergoing Mastectomy
Authors: Helguero Carlos G. , Cansing Jose , Maldonado Fausto A. , Saldarriaga Carlos , Amaya-Rivas Jorge L.
Published: January 2025

Inspired by the Zule Project, which aims to assist underprivileged women in developing countries who have undergone mastectomies and seek affordable, personalized breast prostheses with additive manufacturing, this study establishes a data acquisition protocol for 3D scanning. This non-invasive technique captures patient anatomy to generate a digital representation of the body surface. The primary objective is to quantify breast volume, morphology, and bilateral symmetry, under normal brassiere pressure, for subsequent prosthesis fabrication using additive manufacturing (AM) technology. To develop the data acquisition protocol, a standardized marker system was employed. This system incorporates a global reference marker and localized markers consistently positioned on each patient. Healthy volunteers participated in the study, undergoing bra and bra-free scans using a low-cost 3D scanner. Subsequent image processing utilized computer-aided design (CAD) software. Leveraging the global marker, corresponding anatomical landmarks were identified and processed through a custom code to quantify positional variations between the two named scenarios.