bluuebunny/crossref_metadata_2025_split huggingface dataset:
Design and Development of a Novel Soft Gripper Manipulated by a Robotic Arm
Authors: Cianciotto Bryce , Price Derek , Spencer Logan , Garcia Martin , Tekes Ayse 
Published: January 2022

Abstract
This study presents the design and development of a tendon-driven soft gripper manipulated by a 4 DOF robotic arm. The proposed robotic arm and gripper explore new areas focusing on increasing the grasping performance of the gripper as well as the workspace. The gripper is designed with 3 fingers and driven by tendons using two servo motors. The tension of the strings is adjusted using a pulley mechanism and a string. The opening and grasping of the soft gripper are accomplished by each motor. The wide opening allows the gripper to grasp larger objects. The parallel robotic arm motion is actuated using 4 motors. These motors are mounted on a spherical shoulder plate with attached circular plates with angled axles are. The axles are angled so that their axes of rotation converge to the center point of the shoulder plate. The vertical and lateral motion of the robotic arm is controlled by the series of radial linkages connected to the motors, with a parallel linkage attached to the radial linkages to actuate the forearm of the mechanism. The robotic arm is 3D printed in polylactic acid (PLA) and the monolithic soft gripper is 3D printed in thermoplastic polyurethane (TPU). The gripping force applied by the gripper is obtained using flexible sensors attached to the tip of the 3 fingers. The finite element analysis is performed in SoldWorks and the link lengths are optimized to trace the desired workspace. The mechanism is tested for its grasping and lifting of various objects showing promising superiorities in terms of its grasping capabilities mimicking the human hand. If the robotic arm is mounted on a moving platform, then it can serve as an assistive robot for the elderly.
Experimental Characterization of Hygrothermal Aging: Competition Between Thermo-Oxidation and Hydrolysis Phenomena
Authors: Shaafaey Mamoon , Bahrololoumi Amir , Alazhary Sharif , Mohammadi Hamid , Dargazany Roozbeh 
Published: January 2022

Abstract
In this work, we have presented a comparison between effects of accelerated thermo-oxidative, hydrolytic and hygrothermal aging on the mechanical and chemical properties of a polyurethane based (PUB) adhesive. The adhesive is a flexible adhesive which is extensively used in automobile industry as a glass sealant. During service life it gets exposed to the hygrothermal environment and the integrity of matrix interface is most vulnerable. This study focuses on weighing and comparing effects of different aging environments on material behavior; and it shows that hygrothermal aging environment results as a competition between two sub-aging phenomena i.e., thermo-oxidation and hydrolytic aging. Samples were exposed to 0%RH, 80%RH and submerged condition in distilled water. Uni-axial tensile tests, and cross-link density analysis by swelling test were carried out on as-received and aged samples. The aging process was conducted at three different temperatures (60°C, 80°C and 95°C) and for four different exposure durations of 1, 10, 30, and 90 days. This work confirms that the effect of hygrothermal aging is a result of competition between thermo-oxidation and hydrolytic aging environments. The total mechanical and environmental damage incurred by specimens is a collaborative effect of all exposure environments involved i.e., aging time, temperature, oxygen, water and humidity. The results are in agreement with the chemical test outcomes as well.
Probing the Role of Venting and Evaporative Cooling in Thermal Runaway for Small Format Li-Ion Cells
Authors: Parhizi Mohammad , Crompton K. R. , Ostanek Jason 
Published: January 2022

Abstract
In the present study, a lumped capacitance, 0-D model was developed for simulating thermal runaway of Li-ion battery cells. The model accounts for multi-mode heat transfer, physics associated with gas generation, evaporation of liquid electrolyte, and venting of gases out of the cell during thermal runaway. The model was exercised for two different cases of oven test and external heater. It was found that the role of evaporative cooling changes depending on the state of the decomposition reactions at the time of vent-activation. For oven tests with low temperature and for external heating at slow rates, the energy budget is delicately balanced between decomposition reactions and heat exchange with the surroundings. In these scenarios, the evaporative cooling has a significant effect, and the characteristic temperature decrease after venting is observed. Under faster heating scenarios, vent activation occurs at a time when the decomposition reactions are underway. The evaporative cooling effect is less significant in these scenarios, and the temperature vs. time signature does not show the characteristic temperature decrease. The model presented in this work provides a useful tool for parameter identification, sensitivity analysis, and probing the effects of gas generation, evaporation, and venting.
A New Approach to Develop an Intelligent Robotic Gripper Using Virtual Tools Implementing IIoT and ML Technologies
Authors: Guerra-Zubiaga David , Block Logan , Ricketts Adam , Faile Jacob , Dickson Charlie 
Published: January 2022

Abstract
Industrial manufacturing companies face the challenge of adapting to increasingly complex demands, especially with the influx of online ordering. One case of this is in the underperformance of end-effectors, limiting the adaptability of robotic arms in manufacturing functionality. To create proper gripper adaptability, intelligent gripper design is required to improve the sensibility and processing capability of the end-effectors. This will allow for grippers to perform effective decision-making and optimize production. This paper suggests a methodology that includes a step-by-step design process for an intelligent gripper and discusses how to develop intelligence utilizing key components of Industry 4.0 (Internet of Things, machine learning, and cloud manufacturing). This method was analyzed in a case study of a low-level intelligent vacuum gripper design. The methodology will be beneficial to intelligent gripper design from multiple levels of intelligence, creating a guide for engineers to follow to effectively design intelligent gripper solutions for their systems.
Resilient Cyber-Manufacturing Systems Under Cyber Attacks
Authors: Espinoza-Zelaya Carlos , Moon Young 
Published: January 2022

Abstract
The concept of cyber-manufacturing systems (CMS) is at the nexus of manufacturing advances by an interdisciplinary effort from engineering, computer science, and information science fields. Future manufacturing will increasingly be characterized by complex, networked cyber-physical systems that may be instantiated in one physical location but distributed across many. However, this vision of an interconnected manufacturing environment ushers in the challenge of new security threats to production systems that still contain traditional closed legacy components.
How to address the system failures caused by cyber-attacks remains one of the main success factors in the widespread adoption of CMS. The aim of this research is to investigate the resilience of such a system in the face of cyber-attacks. In general, “resilience” refers to the ability of an entity to withstand unforeseen environmental perturbations or disturbances while continuing performing its intended functions successfully. A resilient CMS is a manufacturing system capable of detecting, withstanding, and recovering from failures while still fulfilling its expected levels of service with acceptable levels of security, integrity, and profitability. Particularly, the resilience from failures caused by cyber-attacks is the focus of the research. A resiliency measure, evaluation of system impacts, and selection algorithm of resilient mechanisms have been explored.
Microwave Synthesis of Plant-Based Supercapacitor Electrodes for Flexible Electronics
Authors: Mehta Siddhi , Jha Swarn , Stewart Weston , Liang Hong 
Published: January 2022

Abstract
Renewable energy and environmental preservation are two grand challenges in our society today. To address these two challenges, there is an increasing demand for energy storage devices made of green and biodegradable materials. State-of-the-art plant-based electrodes have problems of poor electrochemical performance, low reliability, and high manufacturing cost that pose major limitations in their use in flexible supercapacitors. In this research, a novel microwave irradiation synthesis is used to produce a high-performing electro-active lignin-based biomaterial. MnO2 particles are deposited on these lignin-based materials to impart pseudo-capacitance property. These electro-active materials were coated on an Al substrate and used as an anode with an AC-based cathode. A quasi-solid-state supercapacitor was assembled using a polymer-based gel electrolyte of PVA/H3PO4. SEM was performed to study morphology, porosity, and polydispersity of the lignin-based matrix. Cyclic voltammetry (CV) was employed to study the polarization resistance of the system. The cyclic charge-discharge (CCD) was performed to observe cyclic performance. The assembled supercapacitor exhibited a specific capacitance of 26 mF/g after 500 cycles with capacitance retention of ∼87% at 0.1 A/g. This work provides new insights into the synthesis of low-cost and scalable plant-based flexible supercapacitors.
Thermodynamic Performance Study of Diesel-Fueled SOFC Power Generation System
Authors: Wang Heng , Zhao Hongbin 
Published: January 2022

Abstract
In this paper, the diesel-fueled CLHG-SOFC system is proposed, which can separate CO2 without energy consumption while achieving efficient power, and only H2 enters the anode, which can effectively avoid the problem of carbon deposition. Meanwhile, the SOFC system of diesel autothermal reforming and steam reforming is also established. Under the condition of ensuring the same input parameters of the three systems, the variable working condition analysis and exergy analysis are carried out, and the curves of the performance parameters of the three systems with the change of fuel flow and the exergy destruction diagram of each component are obtained. In addition, the results of the three systems are compared. The results show that although the power of diesel steam reforming SOFC is the highest, the total power efficiency of the system is not the highest because it needs electric heating. Diesel autothermal reforming SOFC has the highest total power efficiency and exergy efficiency. CLHG-SOFC system has the lowest efficiency, but it can recover CO2 and avoid carbon deposition in SOFC, which is not available in the other two systems. The research results not only provide theoretical basis and scientific support for the design of SOFC power generation system based on diesel fuel, but also provide a new scheme for energy saving optimization of power generation system.
Computational Fluid Dynamics Turbulence and Wake Study of a Utility-Scale Rotating Three-Blade Horizontal Axis Wind Turbine
Authors: Al-Qarishey Hussein , Fletcher Robert W. , Alkareem Elaf Abd 
Published: January 2022

Abstract
Wind turbines deployed in utility scale wind farms can help to meet future energy demands and reduce carbon dioxide emissions by reducing energy needs from fossil fuels. Wind turbines, however, produce downstream wakes and turbulence. In wind farms such turbulence can negatively impact power production of downstream turbines. It is critical, therefore, to understand this downstream turbulence, but this is challenging. Wind farm layouts are costly and mandate advanced analysis and sophisticated simulations be done to define a wind farm configuration long-before its construction. This is usually done using high-speed computers, and even super computers, to simulate and analyze downstream conditions. In this work the successful deployment of Computational Fluid Dynamics (CFD) using a desktop workstation to study downstream turbulence and wakes of a single utility-scale, rotational three-blade horizontal axis wind turbine (HAWT) are presented. A three-dimensional flow field assuming incompressible flow and unsteady state SST k-ω (two equation) turbulence model was constructed using an unstructured grid around an operational typical utility size HAWT with a rotor hub elevation of 80 meters and a blade length of 40 meters rotating at 18 RPMs. Various wind velocities of up to 25 meters per second providing pressures and velocities were successfully studied.
Standardizing the Process Information for Machining Operations Through Self-Contained Structures
Authors: Asghar Eram , Tolio Tullio , Ratti Andrea 
Published: January 2022

Abstract
A mechanical product is manufactured through multiple processes and procedures. The process information is coded in a part program, and a large amount of unstructured information comes from the shop floor. This results in the loss of logic formulated for the creation of a code. Moreover, it is impossible to track the modifications carried out during these processes. Thus, the unavailability of appropriate and standard knowledge of part processing leads to the situation where the information must be recreated every time a similar part is manufactured, hence, increasing the process planning time. One solution is to divide it into two steps: first, by fetching the information and coding it in a standardized structure; second saving it in a suitable form, facilitating in improving the efficiency and effectiveness of process design for available parts as well as anticipating the new parts. This was achieved by using the previous information related to the process combined with the one obtained from the shop floor. The proposed work concerns capturing the unstructured information from the existing part programs and regaining it using process simulation (VERICUT). Through the extraction of theoretical and graphical geometric data, the interactions between the operations were analyzed. The operational knowledge in this work includes: origin, feed-rate, rotating speed of the tool, rapid movement, cutting tool, material knowledge, and some geometric information of the process. The proposed approach based on simulations and mathematical programming logic is a way to improve flexibility at process and system level by formalizing the available operational knowledge. To illustrate the applicability of the proposed approach, a case study was carried out on a real industrial part program.
Investigating the Effects of Branching on the Constraint-Embedded Swept Profile Calculations
Authors: Aras Eyyup 
Published: January 2022

Abstract
One of the most significant issues investigated in the CAD/CAM developments is the swept envelope formation by a moving tool. There is many attempts to get envelopes, based on the evaluation of tangency constraint. The core operation of this method is to pick the input values one at a time and consider the solutions of constraint for various dependent values at a particular time instance. Such a pathway causes excessive computational effort and time that must be spent to implement the tangency constraint. Recently some research [15,17] has been conducted to completely eliminate the need for evaluating tangency-constraint. In these techniques in order to obtain a closed-form representation of the envelope, the tangency constraint is written explicitly in terms of the dependent variable then it is embedded into the tool surface equation. While these sound straight forward, there are some important inevitable consequences of these restructurings. In the new form, there are no restrictions on the domains of the input variables. On the other hand, for the form-cutting tools the whole set of input values need to be partitioned into a number of disjoint ordered-subsets for which correspondence check between domain and eliminated variables must be performed. The computational cost associated with this type of calculation can become impractical when looking at all the benefits we get from eliminating the tangency-constraint evaluation. To overcome this issue, in this paper first, we introduce a powerful test that takes the domain restrictions into account. Later, using this test we will systematically investigate the distribution patterns of swept profiles. Finally, we present algorithms for forming the domains of closed forms under different motion kinematics.
Studying the Superfluid Transformation in Helium 4 Through the Partition Function and Entropic Behavior
Authors: Domenikos G-R. , Rogdakis E. , Koronaki I. 
Published: January 2022

Abstract
On this paper the authors study the behavior of Superfluid Helium 4 near and below the Lambda line deriving its partition function. The partition function is split into an interacting and a non-interacting/ideal part. Hence, the models about the Bose-Einstein Condensation of an ideal Bose-Gas are applied to the non-interacting/ideal part and then the results compared to the full superfluid, described by the quasiparticle approach. The transition from the Bose-Einstein to the Maxwell-Boltzmann statistics in the non-interacting part is exhibited extremely near the lambda transition of the actual superfluid Helium, hinting the effect of superfluidity in the ideal part of the system. Thus, the complete statistical model is now designed and calibrated by the known experimental data for its interacting part. With this model, since it is a theoretical method based on the partition function and entropy, not on the energy values of the quasiparticles, there is no theoretical limit to the lowest temperatures it can possibly describe. This entropic approach when extended well below the lambda-line, going near absolute zero, predicts the existence of an interatomic potential even at absolute zero, something that has been known to be the case for superfluid Helium. Overall, it seems that by the calculation of the authors the behaviors of superfluidity can also be observed and derived by studying the macroscopic variables, being the partition function and entropy in this way, thus offering a view of the superfluidity of the system through a different more macroscopical scope.
Continuous Equation of State and Thermodynamic Maps for Cryogenic Helium 4
Authors: Domenikos G-R. , Rogdakis E. , Koronaki I. 
Published: January 2022

Abstract
On this paper the authors present a unified EOS for Helium 4 below its liquidation and towards absolute zero. While such EOS’s exist in the literature, they are divided to different region depending on temperatures and pressures, but in this work an overall equation has been created using all the available data and different methods. Thus, the provided equations offer a solid point of reference for any cryogenic engineering applications as they cover to a very high accuracy all the known data and combine them in a ready to use form for any application. Additionally, because of the availability and continuity of the equations covering the entire Fluid, Superfluid and Lambda spectrum thermodynamic maps can now be created for both Helium 4, giving the tools to directly study thermodynamic cycles on maps as done in higher temperatures. The equations that describe the thermodynamic characteristics are offered in two different forms, one of high accuracy with large number of terms, and one with lesser but adequate accuracy with less terms to be used for quicker calculations. Overall, this set of equations can be used to describe the working medium in any cryogenic application using Helium 4 without the need to differentiate one’s models and equations depending on the temperature and pressure regions, meaning that the same model can be used to describe even different phases of Helium 4 in the same application.
KrakenBox: Deep Learning-Based Error Detector for Industrial Cyber-Physical Systems
Authors: Ding Sheng , Morozov Andrey , Fabarisov Tagir , Vock Silvia 
Published: January 2022

Abstract
Online error detection helps to reduce the risk of failure of safety-critical systems. However, due to the increasing complexity of modern Cyber-Physical Systems and the sophisticated interaction of their heterogeneous components, it becomes harder to apply traditional error detection methods. Nowadays, the popularity of Deep Learning-based error detection snowballs. DL-based methods achieved significant progress along with better results. This paper introduces the KrakenBox, a deep learning-based error detector for industrial Cyber-Physical Systems (CPS). It provides conceptual and technical details of the KrakenBox hardware, software, and a case study. The KrakenBox hardware is based on NVIDIA Jetson AGX Xavier, designed to empower the deep learning-based application and the extended alarm module. The KrakenBox software consists of several programs capable of collecting, processing, storing, and analyzing time-series data. The KrakenBox can be connected to the networked automation system either via Ethernet or wirelessly. The paper presents the KrakenBox architecture and results of experiments that allow the evaluation of the error detection performance for varying error magnitude. The results of these experiments demonstrate that the KrakenBox is able to improve the safety of a networked automation system.
Efficient Joining Sequence Variation Analysis of Stochastic Batch Assemblies
Authors: Sadeghi Tabar Roham , Lindkvist Lars , Wärmefjord Kristina , Söderberg Rikard 
Published: January 2022

Abstract
Geometric variation causes functional and aesthetic problems in the assemblies. The challenge is predicting the moments of the distribution of geometric deviations of assemblies to evaluate compliance with the set requirements. Variation analysis of non-rigid sheet metal assemblies with respect to the geometric quality is traditionally performed using Method of Influence Coefficient (MIC), based on Finite Element Method (FEM). The joining operation is one of the most crucial steps in the assembly process, imposing forces on the parts and causes bending and deformation during the assembly, consequently contributing considerably to the final geometric outcome of the assembly. To model the behavior of the assembly realistically and achieve accurate simulation results, considering the sequence of joining is essential. In a digital twin of the assembly process, where the scanned geometry of parts are available and the assembly parameters are optimized for a batch of fabricated components, joining sequences need to be provided for the optimal geometric outcome of the batch of assemblies. The sequence optimization of the joining processes is a time-consuming combinatorial problem to solve. Variation analysis of non-rigid assemblies with stochastic part inputs, including optimal joining sequences, requires an extensive amount of computational effort. More efficient approaches for evaluating assembly geometric variation are desired. In this paper, a computationally efficient approach is proposed for geometric variation analysis and optimization of non-rigid assemblies with stochastic part inputs with respect to the joining sequences. A clustering approach is proposed categorizing the incoming parts based on the part variation. Sequence optimization is performed, and geometric variation is analyzed for each cluster. The results show that the proposed method drastically reduces the computation time needed for sequence optimization compared to individualized optimization for each assembly.