bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improving the Long-Term Durability of Polymers Used in Biomedical Applications
Authors: Hossain Mohammad , Madasani Ravi Chandra 
Published: February 2024

Abstract
Hydrophobic surfaces can improve the long-term mechanical response of polymers by delaying their degradation caused by moisture absorption over time. This improvement in long-term mechanical performance can significantly increase the lifespan of polymers used in various biomedical applications, such as total joint replacement prostheses applications. Although a number of surface modification techniques have been developed over the years, such as introduction of various textures on the surface; their specific influences on hydrophobicity enhancement as well as long-term mechanical performance are yet to be fully understood. In this study, surface textures, with variation in type and geometry, are introduced on model Ultrahigh Molecular Weight Polyethylene (UHMWPE) and High Density Polyethylene (HDPE) surfaces to study the effect of surface modification on hydrophobicity and long-term mechanical performance under environmental conditions. The results show that introduction of surface textures significantly improves the hydrophobicity of model polymers. Texture length or diameter significantly affects the improvement in hydrophobicity. However, texture spacing does not have significant influence on the improvement in hydrophobicity. How this improvement in hydrophobicity facilitates improving the long-term mechanical performance under environmental conditions is investigated. The study provides useful guidelines to improve the long-term mechanical response of polymers for various applications, including biomedical applications.
A Deep Learning System to Quantify and Predict the Chewing Process of Foods
Authors: Ren Shiyi , Chen Bangxiang , Dhupia Jaspreet Singh , Stommel Martin , Xu Weiliang 
Published: February 2024

Abstract
The real-time assessment and prognostication of food texture during mastication are paramount for comprehending and emulating the chewing process, bearing significant ramifications for the food industry. This study unveils a deep learning-oriented recognition framework utilizing Mask R-CNN to analyze food texture throughout the mastication process. We create an extensive food bolus image compendium and train a deep learning model proficient in texture discrimination and processing parameter estimation. A vision system, incorporating an Intel RealSense D435i camera, is harnessed to capture high-resolution images of the food bolus. The dataset encompasses images of masticated peanut samples, with the number of chews varying from 1 to 12 cycles. Although the model’s predictions occasionally diverge from the actual data points, with a maximum discrepancy of ±2 chewing instances chews except for predicting peanuts chewed 11 cycles, the proposed system lays the groundwork for real-time evaluation and prediction of food texture during mastication. Future inquiries could concentrate on ameliorating the model’s precision, broadening its applicability to diverse food categories, and refining the training dataset. This investigation holds the potential to influence the advancement of delectable and nourishing food products, bestowing benefits upon both the food industry and consumers.
Characterizing High-Speed Impact Behavior of UHMWPE Through Molecular Dynamics Simulation
Authors: Guo Guodong , Alam Shah 
Published: February 2024

Abstract
In this paper, a study on the ballistic impact behavior of the ultra-high-molecular-weight-polyethylene (UHWMPE) microstructure through molecular dynamics simulations is presented. Unlike most of the existing works, of which the focus has been on the ballistic impact resistance of amorphous polyethylene, our research studied mechanical properties of both crystal and amorphous structure of the fibril which together constitute the shish-kebab structure of the UHMWPE macro-fibril. In the numerical model, a spherical diamond block that represents a rigid projectile is used to impact a polyethylene block. Two different types of potential energy functions are compared to investigate the energy dissipation mechanisms in tensile simulation. The first type of potential energy function is the polymer consistent force field (PCFF) based on CFF91 (consistent force field) with additional parameters specified for polymer materials. The second type of potential function used is the AIREBO (Adaptive Intermolecular Reactive Empirical Bond Order) potential. The presented MD simulations were conducted by the open-source MD code Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS).
Modeling Heat and Mass Transfer in Metal Hydride-Based Hydrogen Storage Systems Using the Finite Volume Method
Authors: Hasnain Muhammad , Khan Shehzad , Ezazi M. Amin , Sezer Hayri 
Published: February 2024

Abstract
Integrated hydrogen systems need technology to store hydrogen (H2) for many applications. Conventionally, hydrogen can be kept either in the gaseous state (under 500–700 bars) or as a liquid at cryogenic temperature (almost 20 K). Alternatively, metal hydrides (MH)-based storage of hydrogen is currently the state-of-the-art approach to storing hydrogen that offers both safety and higher storage efficiency. However, the main challenge in the MH is the low thermal conductivity that limits the heat transfer during the exothermic adsorption and endothermic desorption processes. This ultimately leads to slow reaction rates and ultimately to higher charging and discharging durations. To improve the performance of MH-based hydrogen storage systems, it is crucial to optimize the heat and mass transfer mechanisms within the MH bed. This work is an attempt to model the heat and mass transfer phenomena during the adsorption process of hydrogen. The governing equations are discretized based on Finite Volume Method and Euler’s implicit method is used for time integration. This method offers a robust and customizable numerical approach that can examine the performance of a broad range of metal hydrides and system configurations for varying environmental conditions. This will enable the modeling and optimization of heat and mass transfers, aimed at reducing the charging and discharging times of these systems. The analyzed parameters include temperature, equilibrium pressure, and average reacted fraction of hydrogen during the adsorption process. The reacted fraction profile from the inhouse developed 2D axis symmetrical model is validated with the experimental data reported in the literature.
Effect of Impactor Diameter on the Residual Properties of Impact Damaged Composite Panels
Authors: Sreenath A. M. , Prakash Raghu V. 
Published: February 2024

Abstract
Carbon fiber reinforced polymer (CFRP), is widely used as a structural material in high-performance applications. Even though CFRP has very high strength in the fiber direction, the material response to in-plane impact damage is weak. The post impact residual strength — also referred to as Compression strength after Impact (CAI) — of the damaged composites panels are commonly correlated with the kinetic energy of the impactor. The shape of the impactor also affects the damage patterns, and hence the residual strength. The effect of radius of the impactor on residual strength and residual stiffness CFRP laminates is studied. Low velocity impact with same initial kinetic energy and different impactor diameters simulated using dynamic explicit finite element analysis. Neither the delamination patterns nor the residual strength properties show any clear correlation with the impactor diameter. The energy absorbed during the impact was found to be a direct measure to estimate residual mechanical properties.
A Futuristic Approach to Micro-Milling With Linear Motion Compliant Mechanism Based Platforms
Authors: Tanksale Abhijit Anandrao , Bafna Ratnesh , Gandhi Prasanna 
Published: February 2024

Abstract
Miniaturization of components in various industries is increasing tremendously, leading to the high demand for different microfabrication techniques. Micro-milling is one of the prominent material removal-based techniques. Most current micro-milling motion platforms are linear guideways with ballscrews as they offer low friction or air bearings with magnetic actuation. With ball screw drives, friction cannot be entirely eliminated, and positioning within a few microns or in the sub-micron range is quite challenging. Although air-bearing magnetic actuation platforms can give positioning accuracies in the sub-micron range, they often turn out to be a highly expensive alternative. The present paper explores an alternative approach with compliant mechanism-based motion control platform for micro-milling. Compliant mechanisms obtain their entire motion through the elastic deformation of flexible beams and do not have any kinematic joints, which results in frictionless, backlash-free motion with the ability to position in the submicron range. The designed micromotion platform is integrated with a commercial Galil motion control board to operate with NC codes. Further, a few basic geometries, microchannels and a complex shape have been micro-milled on brass workpieces using the proposed compliant mechanism-based micro-milling machine. Overall, the basic capabilities of the compliant motion platforms for micro-milling have been established. More research in this direction is required to unfold the new doorways for complaint-based motion stages in machining platforms.
Effect of Layering Sequence on the Characteristics of Wire Arc Additive Manufactured Parts
Authors: Cheepu Muralimohan , Shanmugam Ragavanantham , Vinayagam Mohanavel , Dennison Seth 
Published: February 2024

Abstract
Wire arc additive manufacturing (WAAM) is gaining popularity among other additive manufacturing processes for the manufacture of large-scale components. The microstructural evolution of the solidification process in WAAM depends on the amount of heat input and the layering sequence. To examine the effect of layering sequences on the development of grain growth, microstructure, and mechanical properties, Inconel 825 alloy was deposited in various sequences for layering by WAAM using GMAW in this work. Several layering sequences were developed to prevent columnar grain production from oscillation beads and many passes in a single layer. The single direction of heat conduction promotes the growth of grains in that direction from bottom to top by linking grains at fusion boundaries. At the fusion border between the previously solidified bead and liquid metal, nucleation and epitaxial grain growth likely to develop. Hence, the transverse columnar grains are determined by the grain size of the previous layer. Traditional stacking sequence in one direction yields columnar grains, however zigzag layering sequence refined the grain growth. The zigzag layering sequence mostly disrupted the direction of heat conduction and grain development. The smaller size of fragmented grains improves the isotropic characteristics. The anisotropic behavior of additively manufactured deposits has been shown to depend on grain growth direction and size, which are affected by the layering sequence. Hardness and tensile strength of WAAM deposits with zig-zag layering sequence were found to be superior to standard layering sequence methods. Moreover, the zigzag layering sequence improves the resolution of deposited walls having a linear shape.
Enhancing the Performance Measures of Electrical Discharge Machining Using Additive Manufactured Copper Tool Electrode on Drilling Titanium Alloy Specimens
Authors: Shanmugam Ragavanantham , Thangaraj Muthuramalingam , Thangamani Geethapriyan , Ramoni Monsuru 
Published: February 2024

Abstract
Since electrical discharge machining (EDM) is utilised in numerous manufacturing industries, it is crucial to optimise the process mechanism to the greatest extent feasible. Incorporating additively manufactured tool electrodes into a process can effectively improve quality standards. In the present study, an effort was made to enhance the performance parameters of the EDM process with an additive manufacturing copper tool electrode when machining titanium (Ti-6Al-4V) specimens. The effect of input parameters such as gap voltage, peak current, and duty factor on performance indicators such as material removal rate and overcut has been evaluated. It was discovered that additively manufactured electrodes for tools could effectively enhance quality measures. Taguchi-DEAR analysis determined the optimal arrangement of input factors in the EDM process to be 80v (Vg), 6A (Ip), and 80 (DF) with an error accuracy of 1.6%.
Valuation and Cost Optimization of the Proton Exchange Membrane Water Electrolyzer Technologies Considering the Degradation Phenomena
Authors: Mohammadi Efat , Headley Alexander John 
Published: February 2024

Abstract
Polymer electrolyte membrane water electrolyzers (PEMWEs) have gained significant attention in the energy storing industry due to their suitable dynamic response to fluctuations. To minimize the overall hydrogen production cost over the life of the system, it is important to consider both the electricity pricing tariffs and the health of the system. The weakest component of a PEMWE for long term performance is the membrane which thins during operation and eventually no longer separates the reactants appropriately. Reported mechanisms of membrane thinning are conflicting with a wide range of failure rates, operating hours before failure, and differing estimates of efficiency impacts. Some degradation studies report significant reductions in ohmic losses as membranes thin leading to improved overall efficiency, while others predict increasing activation losses leading to declining efficiency over the life of the system. These conflicting reports make projecting long-term costs of PEMWE hydrogen production difficult at present. To provide a comprehensive valuation of hydrogen production cost, an optimal valuation algorithm for behind-the-meter hydrogen production is presented through a case study of hydrogen production at the Natural Energy Laboratory of the Hawaii Authority (NELHA). We include consideration of the various degradation mechanisms reported in literature to highlight which effects will be most important to understand for production planning. This is compared to estimations of production costs ignoring degradation, to highlight the impact of system degradation on long-term planning. Further, this paper suggests analyses to estimate renewable penetration levels for which PEMWE hydrogen production may be cost competitive with other fuel sources given the current membrane replacement costs.
Spike Analysis of the Neural Activities Across the Rats’ Auditory Brain Structure
Authors: Meeker Alexis , Van Gampelaere Jensen , Zhu Linda , Luo Hao , Zhang Jinsheng 
Published: February 2024

Abstract
Tinnitus has been a health condition that affects a large population. Clinical diagnosis and treatment have been developed for tinnitus for years. However, there are still limitations because researchers have yet to find an underlying mechanism for how it develops in the brain structure. Abnormal neural interactions among the brain areas are considered to play an important role in tinnitus generation. From bottom to top, researchers have been working on the analysis of neural activities in the auditory brain structures, including the dorsal cochlear nucleus (DCN), inferior colliculus (IC), and auditory cortex (AC), to seek a better understanding of the information flow among these areas, especially in comparison of both health and tinnitus conditions. In the project, a collection of multiple animals’ neural activities from DCN, IC, and AC, on conditions of before and after noise exposure and before and after Auditory Cortex Electrical Stimulation (ACES) were processed and analyzed. These conditions in rats were used to estimate healthy animals, noise-trauma-induced tinnitus, and after ACES treatment. The signal processing algorithms started with the raw measurement data and focused on the local field potentials (LFPs) and spikes in the time domain. First, conventional ways of evaluation were applied to the signals. Based on the signals of each channel inserted in the different structures, the firing rate was calculated by counting the total number of spikes for the given period of time in each channel. Meanwhile, the Hilbert transform was used to obtain the phase-frequency information. Phase-phase correlation analysis was applied to test any relations between channels, especially for those from different auditory brain structures. Second, the shape of spikes was investigated to find the changes in neural activities in auditory brain areas under various conditions, therefore determining if tinnitus-related abnormal neural activities have a specialized pattern. In this procedure, spikes above the threshold were extracted with the rectangular window on the time domain. Spike shapes were quantified in terms of amplitude and width of peak and compared across channels. Averaged spike shapes from different areas/channels were plotted synchronized for comparison. The above-mentioned information could present the difference in neural activities among the DCN, IC, and AC in the auditory pathway. Last, the time difference of arrival of spikes among areas was calculated to help further understand the information transfer in the auditory pathway. This was a preliminary test to see if it could help observe abnormal time delays in tinnitus conditions compared to healthy ones. All the above numerical analysis results were summarized in plots and color maps and also used to compare animal conditions and discussed.
Model-Based Visual Control for Robotic Manipulators Using Udwadia Kalaba Formulation
Authors: Morgan Edward , Ard William , Barbalata Corina 
Published: February 2024

Abstract
This work presents the development of a model-based visual control strategy for robotic manipulators performing target tracking. The proposed approach leverages fiducial-based techniques for target identification with the Udwadia-Kalaba (UK) formulation for constrained robotic motion control. Using Baumgarte’s approach leads to a model-based visual control strategy capable of stable behavior when discontinuities are present in the desired trajectory that the robot has to follow, as well as when there are uncertainties in the dynamic model of the system. The control strategy is tested in simulation with a 4-DOF Reach Alpha 5 manipulator using real-world visual target tracking. The qualitative and quantitative evaluation of the strategy shows its capabilities in accurately tracking the desired trajectories.
Computational Fluid Dynamics Study of the Performance of Solar Air Heater
Authors: Ames Kieran , McCarthy Chris , Clark Ian , Weathers Justin , Mastrandrea Kyle , Tudor Timothy , Etesami Faryar , Zhu Xiaowei 
Published: February 2024

Abstract
As part of the ongoing efforts to promote accessible and sustainable green energy, renewable sources have become increasingly prevalent in both commercial and residential settings. Solar energy represents a promising form of residential power generation. Where photovoltaic (PV) solar panels address the search for renewable energy sources through the conversion of solar radiation into electricity, solar air heaters (SAH) can approach the problem from a different direction: reducing the heating demand on a building by directly heating air using solar radiation, thereby reducing electrical energy usage. In this research, we employ computational fluid dynamics analysis to determine the preferential design of SAHs. Our focus lies in the internal geometry of the SAH, where heat exchange occurs between the hot panel and cold air flowing over it. By using Solidworks as the design and simulation tool, we first design SAHs with varying internal geometries. Then the simulations are conducted to explore the effects of the internal geometry on the flow and heat transfer characteristics. Further analysis shows that the preferred design of a SAH could be achieved by combining modifications to the collector and implementing structural variations. An efficiency improvement of nearly 470% was found to be achievable in the models tested. This research offers guidance for future optimization of the internal design of next-generation SAHs and further promotes sustainable building practices.
Development of an Articulating Robot Arm Kit As an Educational Tool for Middle School Students
Authors: Herath Ramitha , Balko Kyle , Pottmeyer Benjamin , Williams John-Paul , Dong Janet 
Published: February 2024

Abstract
This paper describes the design and build of a working prototype of an industrial robot arm kit. The kit is intended to be used by middle school students as an educational tool or an inspiration for them to pursue engineering fields, specifically robotics, and automation. With the end users in mind, the robot arm is designed to be highly modular, engaging, easy to assemble and control, and inexpensive. The robot arm itself is classified or designed as an articulating arm robot. It consists of seven modules with five degrees of freedom. The seven modules are a base assembly, a lower arm, an upper arm, a controller, and three interchangeable end effectors. Three interchangeable end effectors are a pen holder, a circular two-jaw gripper, and a camera, which enable the robot arm to draw on paper with a pen, move an object from one location to another, and capture images of an object. Realizing that most children are more willing to learn about a subject or object if they interact with it, the robot arm has been set up with several coded presets to illustrate its performance capabilities, interactions with users, and manual control buttons on the controller.
IR Sensor Modeling in Unreal Engine for Autonomous Vehicle Applications
Authors: Vemulapalli Sri Sai Teja , Rahi Adibuzzaman , Mullins Spencer Dean , Wasfy Hatem , El-Mounayri Hazim , Anwar Sohel 
Published: February 2024

Abstract
As autonomous vehicle technologies continue to advance in the automotive industry, sensors such as Infra-Red (IR) cameras are becoming increasingly crucial during night-time and low visibility scenarios. However, developing and validating object detection and recognition algorithms with these sensors can be expensive and time-consuming. Therefore, simulation of autonomous vehicles with appropriate sensor models provides an efficient and cost-effective way of testing and validating such algorithms. The use of virtual environments for developing and validating sensor models offers experimentation with various scenarios that may be cost-prohibitive or impossible to recreate in a physical environment including different weather conditions, lighting conditions, and other environmental factors that may affect the performance of the sensor. In this paper, we present a novel IR sensor model that approximates the output of an actual IR camera. The model utilizes Unreal Engine’s Custom Stencil and Post-Processing Materials to assign greyscale color values based on the object’s temperature property and an assigned temperature range for the camera. The IR sensor model outputs are compared with the outputs of an actual IR camera under similar conditions. The results show that the proposed IR camera model captures the basic features of an IR camera very well. However, further improvements to this innovative IR camera model is needed to capture additional features of an IR camera such as the rejection of non-thermal IR reflections, creation of a reflection buffer for real-time implementations, etc.