bluuebunny/crossref_metadata_2025 huggingface dataset:
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

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

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

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

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

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

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

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

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

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

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

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

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

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.
The Effect of Packing Fraction on the Thermal Performance of Shell-and-Tube-Based Latent Heat Energy Storage Systems
Authors: Soanker Abhinay , Oztekin Alparslan
Published: February 2024

This study examines the effect of packing fraction on shell- and tube-based latent heat energy storage units. To determine the performance of these systems, a three-dimensional transient numerical analysis has been carried out using Ansys, Fluent. This study address flow, heat transfer, melting, and solidification processes. The K-Omega SST model has accounted for turbulent flow regimes in the heat transfer fluid (HTF) and the phase-changing material (PCM). The HTF’s inlet temperature was set at 495K during the charging cycle, while it was set at 285K during the discharging cycle. A velocity boundary condition has been applied at the HTF inlet, with a Reynolds number of 5,000 considered. Furthermore, a symmetric boundary condition has been applied at the outer boundaries of the PCM to reduce the size of the shell and tube system.

The packing fraction values of 0.1, 0.2, 0.3, and 0.4 were considered while maintaining a constant volume of PCM across all cases. The performance characteristics, such as melting and solidification rates, total energy stored and discharged, and average PCM temperature, were analyzed. Although all four cases stored similar amounts of energy, the packing fraction 0.3 exhibited slightly higher thermal energy absorption at the end of the charging cycle, about 8.2% more than the 0.1 packing fraction. The packing fraction 0.4 demonstrated the fastest melting and solidification rates and the highest energy absorption and discharge rates at any given time. Meanwhile, the packing fraction 0.1 had a lower energy absorption rate but remained more consistent throughout the charging cycle when compared to higher packing cases.
Hollow Fiber Vacuum Membrane Distillation Modules With Cross-Flow and Parallel Flow Arrangements
Authors: Caspar Justin , Xue Guanyang , Asiri Mohammed , Oztekin Alparslan
Published: February 2024

2D Large Eddy Simulations (LES) were run to characterize the effect of a cross-flow configuration versus the same cross-section in parallel flow for hollow fibers with a packing fraction of 50%, Reynolds number 500, for vacuum membrane distillation modules. The enhanced nature of vortex shedding and flow separation was able to effectively mitigate temperature polarization in cross-flow in both the axial and radial directions. The flow remained attached to the fibers in the parallel configuration, leading to thick thermal and concentration boundary layers corresponding to high polarization. In the parallel configuration, there was 2% radial distribution in the flux, showing a near-uniform boundary layer thickness. In the cross-flow configuration, the radial distribution varied in time based on the transient nature of vortex shedding. The shedding mitigated radial temperature polarization by reducing the boundary layer thickness and mixing more thermal energy that would normally exit the module via the bulk solution back into the zone near the membrane, improving axial polarization. For a module length of 40mm, corresponding to 30 rows of packed fibers, there was a 50% improvement in the flux performance switching from parallel to cross-flow.
Design Optimization of Additively Manufactured Components Using Simulation-Based Analysis of Infill Structures
Authors: Asami Karim , Roth Sebastian , Krukenberg Michel , Emmelmann Claus
Published: February 2024

Additive manufacturing (AM) has revolutionized the manufacturing industry, allowing the production of complex, lightweight components with specific properties. This has created opportunities for customized parts with optimized performance and cost-efficiency compared to traditional manufacturing.

Infill structures are used to fill the voids inside the component during layer-by-layer manufacturing. These structures, such as grids and honeycombs, optimize mechanical properties, reduce weight, and save production time. However, investigating the mechanical properties of components with different infill structures is typically done experimentally, which is time-consuming and expensive.

This paper proposes a simulation-based approach to investigate the influence of infill structure parameters on the mechanical properties of components made from AISI 316L stainless steel. Two-dimensional grid and honeycomb infill structures are studied, considering infill degree, cell wall thickness and spatial orientation relative to the load direction. The study employs a parametric design approach to generate different infill structures for simulation and validation.

This paper provides a simulation-based methodology for varying and evaluating design parameters for AM processes using grid and honeycomb infill structures. The findings can be used to optimize lightweight component design for specific applications, improving performance and cost-efficiency. The study contributes to the field of Design for Additive Manufacturing (DfAM).
A Computational Study on Adaptive Multiobjective Optimization of Blowout Preventer Valve System
Authors: Song Fei , Caekebeke Laurent , Jagadesan Prabhu , Li Ke
Published: February 2024

A blowout preventer (BOP) is a large valve that acts as a critical well control unit against oil, gas, and water overflow and well blowout. The BOP valve body assembly contains the main pressure-containing parts. For example, in deepwater or coiled tubing drilling operations for oil and gas, the BOP can be subjected to sustained high pressure cycles. These cycles may cause the concentration of stresses in some regions, which could result in cracks or fatigue damage. Once the BOP fails during the emergency shut-in process, a blowout accident can occur, which may lead to casualties and major economic losses. To ensure the structural integrity under service loads, the BOP valve body should be designed to fulfill the stress requirements as defined by the American Petroleum Institute (API) Specification 16A, 17G and ASME (American Society of Mechanical Engineers) Boiler and Pressure Vessel Code Section VIII, Division 2. It is necessary to ensure that the BOP valve can safely withstand the working pressure. However, overengineering the BOP design is undesirable as well in terms of value engineering because it wastes both time and money. Therefore, there is a strong need to efficiently explore the full design space and identify the optimal solution that results in a compromise between the competing objectives under the constraints for the BOP valve design.

In this paper, a methodology is presented for integrating computer-aided design (CAD) nonlinear finite element analysis (FEA), and optimization package to enable adaptive multiobjective optimization and virtual verification and validation (V&V) for the BOP valve system. The BOP valve assembly is parameterized before being imported into an FEA solver. The FEA workflow is automated such that once a set of geometric parameters are given, the preprocessing, solving, and postprocessing steps can be completed automatically. Based on the automated FEA workflow with advanced optimizer (adaptive metamodel of optimal prognosis (AMOP) in Ansys™ OptiSLang), the BOP valve body design space is efficiently explored. The Pareto-optimal design points with respect to two completing design objectives on structural integrity and weight reduction are discovered. This process had never been done in the past. The optimal design set recommended from the optimization algorithm is finally sent to the three-dimensional nonlinear FEA solver for virtual V&V per the API Spec and ASME code compliance. The automated design optimization approach demonstrated in this paper could considerably enhance the product performance and reliability and, in the meantime, minimize product development cost.
Intelligent Facade Innovation (IFI): Using IIoT, Digital Twin, and Next-Gen Architecture Designs
Authors: Salamaga Diana , Guerra-Zubiaga David A. , Voicu Razvan Cristian
Published: February 2024

This paper explores a new methodology for integrating Internet of Things (IoT) on smart facades and implementing the digital twin concept in kinetic facades to advance the field of intelligent buildings and sustainable lean architecture. Advancements in climate-responsive building skins and analysis of the automatically adjustable kinetic facade with real-time solar tracking devices, temperature, humidity, occupancy, and air quality sensors are discussed in this article. While several papers have explored the implementation of Industry 4.0 trends on intelligent buildings, limited research has been conducted on the integration of IoT on smart facades and the implementation of digital twin concept. This research project aims to fill this gap by investigating the value of integrating IoT on smart facades and implementing the digital twin concept on kinetic facades. This research project contributes to the ongoing efforts to create a more sustainable and efficient built environment. This research will be valuable to researchers, architects, and engineers interested in advancing the field of next-generation architecture designs and principles.
Unmanned Aerial Vehicles (UAVs) in Smart Factories: Exploring the Potential for Energy Savings Through Wireless Communication Technologies
Authors: Hantouli Fadi , Guerra-Zubiaga David A. , Esmaeili Amin , Chakravarty Sumit , Perry LaShaundra , Forsberg Paul , Richards Gershom
Published: February 2024

The rise of Industry 4.0 and the increased use of intelligent technologies in factories has resulted in better automation and improved efficiency. Smart factories are using Unmanned Aerial Vehicles (UAVs) to achieve energy-saving objectives, but the potential of UAVs for energy savings has not been fully explored. This paper seeks to fill this gap by introducing the next generation of wireless communication technology that will be available for UAVs in smart factories. Data transmission is a critical component of smart factories, and it is essential that the wireless technology used for data transmission is reliable and flexible, so that data can be transmitted without disruption. In this article, we visualized a scenario using UAVs to inspect machine conditions in a smart factory through data collected from the UAVs and transmitted wirelessly to a station for further analysis. We discussed the importance of wireless technology in this application and compared the reliability and flexibility of a 6G network with a 5G network. We also examined how deep learning techniques can be used to improve the transmission of data further. The goal is to maximize the efficiency of the smart factory and ensure that data is transmitted.
An Adaptive Path Planning Approach for Digital Twin-Enabled Robot Arm Based on Inverse Kinematics and Deep Reinforcement Learning
Authors: Zhou Qi , Li Sikai , Qu Jingbo , Wu Jin , Xu Haomiao , Bi Youyi
Published: February 2024

Efficient path planning methods for robot arms are crucial to ensure the quality and safety of their completing various tasks. Compared to traditional manual instruction, Reinforcement Learning (RL) based path planning methods show better adaptability for complex working scenarios. However, the training of RL is usually time-consuming with limited success rate. To tackle this problem, we propose an adaptive path planning approach for robot arm based on Inverse Kinematics (IK) and Deep Reinforcement Learning (DRL) in a pick-and-place context. A judgement mechanism is developed to adaptively select IK or RL based method according to the results of early-stage collision detection. We separate the pick and place task into three sequential curriculums (approaching, grabbing and placing) with modified reward functions to speed up the training process and achieve a higher success rate. The proposed approach is validated with a physical robot arm supported by a high-fidelity digital twin model. The experiment results show that our proposed approach outperforms traditional RL based method with improved training speed and guaranteed performance in collision avoidance and path accuracy. This work contributes to the practical deployment of RL based path planning method for digital twin-enabled robot arm in smart manufacturing.
Simulation and Validation of Material Handling and Packaging Processes Using Vision-Guided Virtual and Physical Robots
Authors: Mascaro Seth , Mueninghoff Alexander , Chauhan Vedang , Guerra-Zubiaga David A.
Published: February 2024

Due to a shortage of labor, there has been a significant increase in the demand for automation and robotics in recent times. Industry 4.0 is heavily reliant on utilizing these robots to automate various processes in manufacturing to improve efficiency and reduce costs. The goal of this research is to implement automated product handling and packing using both virtual and physical robots and evaluate the performance of the system. The principal scope of this work is to automate the product handling and packaging process for a pharmaceutical company that produces pipets, thereby reducing labor expenses and enhancing operational efficiency. Additionally, this technology has the potential to transform the manufacturing industry by decreasing the need for human labor, improving product quality, and minimizing the risk of errors or contamination. The novelty of this research lies in the utilization of ROBOGUIDE simulation software to create and optimize a virtual workcell, along with a machine vision inspection system that identifies and locates products. The physical workcell is then constructed based on the simulation data, and the performance of the robot is validated using the results obtained from the physical robot. The robots’ performances are reported in terms of the cycle time and vision classification scores. Implementing automated product handling and packaging using virtual and physical robots is a promising technology that can enhance the efficiency, quality, and cost-effectiveness of the manufacturing industry.
Cryogenic Analysis Measuring Thermal Expansion Coefficient of Silicon Nitride and Sapphire via the Strain Gauge Method and Computational System Coupling
Authors: Lovelace Kirsten , Davis Ruth , Smith Sonya T.
Published: February 2024

Microchip reliability issues can be caused by mismatches in coefficients of thermal expansion (CTE) which can be mitigated by selecting materials with lower thermal expansion values. The strain gauge method was utilized to develop a simple thermal expansion measurement system. The objective of this research is to evaluate the coefficient of thermal expansion of sapphire and silicon nitride within the cryogenic temperature range of 299 K-4 K, as alternative options for substrate and printed circuit board (PCB) materials within integrated circuitry. This research focuses on validating experimental results with computational modeling at the liquid nitrogen temperature range of 77K and a brief overview of the mean CTE data at 4K.
Computational Verification of Analytical Modal Analysis Solution of Non-Symmetric 3RPR Parallel Kinematics Manipulator
Authors: Rosyid Abdur , El-Khasawneh Bashar , Alazzam Anas
Published: February 2024

The modal analysis of parallel kinematics manipulators is more complicated than that of serial kinematics manipulators due to the closed kinematic chains of the former. Using commercial finite element software, modal analysis of the manipulator should be typically set up for every single posture. Using commercial software for dynamic stiffness optimization is also less convenient than using an analytical formulation. This paper presents a verification of a proposed analytical solution by comparing it to the finite element solution. Two examples of 3RPR planar parallel kinematics manipulator were presented in the comparison. Similar to the analytical model, the finite element model uses beams to represent the manipulators’ links. First, the comparison between the analytical and finite element models was made to the individual links of the manipulator. Subsequently, the comparison was made to the assembled manipulator. Different ratios of the moving platform stiffness to the leg stiffness were used to investigate the dynamic behavior of the mechanism. It is shown that the derived analytical model for the modal analysis matches quite well with the finite element models. Furthermore, an example of dynamic stiffness optimization using the verified analytical solution was presented.
Development of an Elaborated Fuel Cell Stack Model for Drone Fuel Cell System With Liquid Cooling
Authors: Woo Jongbin , Kim Younghyeon , Yu Sangseok
Published: February 2024

Recently, the drone is tried to employ in the logistics industry that is known as cargo drone. Since a cargo drones requires high power density to allow large payload, hydrogen fuel cell is considered as power propulsion system for cargo drone. Typically, the fuel cell system of small drone is equipped with air cooled fuel cell system but the large payload of cargo drone requires liquid cooling fuel cell system. Since the high power density of cargo drone allows more weight for payload, the fuel cell should be operated with higher current density at the take-off. Those conditions result in serious amount of heat generation that should be maintained at reasonable set value for extended durability and high performance. Even though the liquid cooling of the fuel cells is very effective for controlling heat generation, the liquid cooling requires complicated system with heavy weight. Nonetheless, it is necessary to equip liquid cooling system as the system power requirement is large enough.

This study developed a 20kWe polymer electrolyte membrane fuel cell system model through AMESet, a model development program, and the cooling system was developed as a water cooling system in consideration of the heat generation of the stack. The cooling system consists of a water pump, a cooling fan, a radiator, and a three-way valve, and the optimal cooling strategy is derived by comparing the temperature control performance of the fuel cell system with the parasitic energy of the cooling system.
Optimization of the Design and Operation of Multi-Energy Systems Integrated With Energy Networks: Retrofit Design Problem
Authors: Dal Cin Enrico , Carraro Gianluca , Lazzaretto Andrea , Tsatsaronis George
Published: February 2024

In the literature there is a lack of tools able to optimize contextually the design and operation of a multi-energy system in its entirety, meaning with this both i) the number, type and size of the energy conversion and storage plants supplying the system, and ii) the geometry and capacity of the distribution networks delivering energy to the end users. Moreover, rarely the retrofit design problem is considered, meaning with “retrofit design” the addition of new capacity to components initially available in existing systems. Here, a general method is proposed to simultaneously optimize the retrofit design and operation of a multi-energy system and associated energy networks. The goal consists in finding the additional capacity to be added to already available components — energy conversion and storage plants, energy networks — and the new components to be installed, in order to comply with given reduction targets in carbon emissions, while keeping the life-cycle cost of the system at a minimum. A district composed of commercial and residential buildings operating in a microgrid is considered as a case study. Heat can be provided to the end users via a district heating network, while electricity can be either generated on site or imported from the national power grid. Results of the retrofit design problem show a contextual reduction of 35% in CO2 emission and 20% in life cycle cost with respect to the original system configuration.
Dynamic Modelling and Experimental Validation of Reaction Forces in Crane Structures
Authors: Rykkje Thorstein , Bakketun Ringheim Alexander , Willis Lundgaard Jonathan , Mezher Kenan , Øvsthus Knut , Impelluso Thomas
Published: February 2024

This paper presents a first-phase project toward designing a digital twin for a smart crane on a ship. Digital twin technologies create a virtual model of a physical system to simulate its behavior and aid in its operation. The long-term goal of this project is to integrate the finite element method, the multi-body dynamics method, artificial intelligence, and 3D visualization for the creation of digital twins. The short-term objective of this first phase, and the focus of this paper, is to use the moving frame method (MFM) in dynamics as a foundation for such an integration. The MFM relies on Lie group theory (distilled to the simplicity of matrix algebra) and Cartan’s notion of Moving Frames. A compact notation simplifies the kinematics. In addition to the underlying method, this paper presents a systematic and coherent way to create the frame connection matrices for multi-bodies. Then, with an appropriate restriction on the variation of the angular velocity, the MFM extracts the equations of motion using the Principle of Virtual Work. These are solved using an adaptive Runge-Kutta-4. Following this, the paper presents a systematic way to isolate each body in the linked system and solve for all contact forces (the latter in preparation for the deployment of the finite element method). The solution of the system drives a software simulation of the crane’s motion using WebGL and ThreeJS. Finally, the method and analysis is validated. A crane scale model was constructed using 3D-printed parts and electric motors for motion. Load cells were integrated into the base to measure the reaction forces. This paper reports on the first phase.
Evaluation of Fracture and Fatigue Properties of Graphene Oxide by Atomic Force Microscope and Molecular Dynamics Simulation
Authors: Sakuma Shunsuke , Nakao Yusuke , Tanaka Tomoyasu , Yonezu Akio
Published: February 2024

Graphene is a typical two-dimensional material and is expected to be a next-generation material for structural and functional applications, including weight reduction and miniaturization of high-tech structures and devices. However, graphene is difficult to be synthesized in large quantities, and its practical application has not been well advanced because graphene is very sensitive to defects, and defects significantly decreases its strength and fatigue life. Therefore, we focused on graphene oxide (GO), in which functional groups such as hydroxy and epoxy groups are bonded to graphene. Since GO can be synthesized in large quantities and is endowed with ductile behavior, it is expected to be used in various applications such as supercapacitors and conductive high-strength composite materials. Since these devices are subjected to repeated loading and deformation in the process of use, it is very important to know the fracture and fatigue properties of GO. However, there are very few studies on the fracture and fatigue properties of GO. Therefore, this study evaluated the fracture and fatigue properties of GO using Atomic Force Microscope (AFM) experiments and molecular dynamics, and investigated the mechanisms of fracture and fatigue damage.
Thermal Behavior of PCMs During Phase Transitions With Phase Change Hysteresis: Experimental Setup Development and Problems of Model Validation
Authors: Zálešák Martin , Charvát Pavel , Klimeš Lubomír , Pech Ondřej , Bouchal Patrik
Published: February 2024

Various models and approaches for phase transitions of phase change materials (PCMs) have been proposed in recent years. However, many of these models lack validation with experimental data, particularly the models for phase change hysteresis (PCH) and incomplete (partial) phase transitions. To address this issue, an experimental setup was designed, assembled and tested for potential validation of numerical models. The experiments involve monitoring of the heat flux and the temperature distribution in a PCM contained in a rectangular cavity with a heated/cooled wall. Peltier cells are used to introduce positive or negative heat flux - heating and cooling of the PCM. The first sets of experiments were conducted with the RT35HC paraffin-based PCM. The ultimate goal of the experiments is to provide experimental data for solving inverse heat transfer problems, specifically the identification of the relationships between the enthalpy and temperature during complete and incomplete phase transitions of a PCM. The results suggest that in order to properly account for the influence of natural convection in liquid PCM, a more appropriate experimental setup that avoids its effects or a more suitable modelling approach is required.
Mechanical Characterization of Yucca Plant for Potential Biomimetic Applications
Authors: Shaw Rickelle , Robertson Kyle , Vargas-Silva Gustavo , Mixon Daryl , Jawaharlal Mariappan
Published: February 2024

Hesperoyucca Whipplei (HW), commonly known as the chaparral yucca, is a species of yucca native to the southwestern United States, particularly California and Arizona. This plant has adapted to thrive in dry, arid conditions, making it an interesting subject for studying the mechanical properties of its physical structures.

Research has shown that the chaparral yucca has distinctive physical and structural characteristics that allow it to withstand external forces and environmental stresses. For example, the yucca’s leaves and stems are composed of fibrous tissue that provides both stiffness and flexibility, allowing them to bend and resist breaking under wind and other physical stresses.

For this paper, experiments were performed to establish the mechanical properties of HW with a focus on understanding its distinctive physical and structural characteristics. Tensile tests were conducted on different components of the plant, including whole leaf samples, fiber bundles, braided fibers, and single fibers. Similarly, the outer bark of the stalks underwent 3-point bending testing. Studying the mechanical properties of HW can provide valuable insights into the plant’s adaptation to its environment and inspire new innovations in materials science and engineering.