bluuebunny/crossref_metadata_2025_split huggingface dataset:
Role of Secondary Ions on the i-v Characteristics of Oxyfuel Flame Subject to an Electric Field
Authors: Untaroiu Alexandrina , Rahman S. M. Mahbobur , Martin Christopher R. 
Published: February 2023

Abstract
Recent use of ion currents as a sensing strategy in the mechanized oxyfuel cutting process motivated a series of studies which revealed that the steel work piece contributes secondary ions in addition to the primary ions classically identified in the oxyfuel flame. In this work, we present a computational model that has linked carbon-related chemi-ions as a source of secondary ions in preheating stage of oxyfuel cutting process subject to electric bias voltages. The flames' response to the electric field at different positive and negative polarities manifested a better understanding of the physical behavior of current-voltage (i-v) relationship. While copper surface exhibits stable and repeatable i-v characteristics, sporadically enhanced current was observed in positive saturation regime for steel surface, and this is believed to be due to the presence of secondary chemi-ions. To this extent, a source term of gaseous carbon has been assigned to mimic the ‘work surface’ reactions. The hypothesis is that since carbon is an important element, it will be diffusing out of the steel surface and evaporate into the flame.
Design and Development of a Spherical 5-Bar Thumb Exoskeleton Mechanism for Poststroke Rehabilitation
Authors: Ketkar Vishwanath D. , Wolbrecht Eric T. , Perry Joel C. , Farrens Andria 
Published: February 2023

AbstractThis paper presents the kinematic design and development of a two degree-of-freedom (2DOF) spherical 5-bar thumb exoskeleton to augment the finger individuating grasp exercise robot (FINGER) rehabilitation robot, which assists the index and middle fingers individually in naturalistic grasping. The thumb module expands the capabilities of FINGER, allowing for broader proprioceptive training and assessment of hand function. The design process started by digitizing thumb-grasping motions to the index and the middle fingers separately, recorded from multiple healthy subjects utilizing a motion capture system. Fitting spheres to trajectory data of each subject allowed normalization of all subjects' data to a common center and radius. A two-revolute joint serial-chain mechanism was synthesized (intermediate optimization step) to reach the normalized trajectories. Next, the two resulting grasping trajectories were spatially sampled as targets for the 2DOF spherical 5-bar synthesis. Optimization of the spherical 5-bar included symmetry constraints and cost-function penalties for poor manipulability. The resulting exoskeleton assists both flexion/extension and abduction/adduction of the thumb enabling a wide range of motions. Consistent with FINGER, the parallel structure of the spherical 5-bar places the actuators at the base of the module, allowing for desirable characteristics, including high backdrivability, high controllable bandwidth, and low mechanical impedance. The mechanical design was developed from the kinematic solution, including an adjustable thumb cuff to accommodate different hand sizes. Fit and function of the device were tested on multiple subjects, including survivors of stroke. A proportional-derivative force controller with gravity and friction compensation was implemented to reduce resistance to motion during subject testing.
A Curved Compliant Differential Mechanism With Neutral Stability
Authors: Mak Robin , Amoozandeh Nobaveh Ali , Radaelli Giuseppe , Herder Just L. 
Published: February 2023

AbstractDifferential mechanisms are remarkable mechanical elements that are widely utilized in various systems; nevertheless, conventional differential mechanisms are heavy and difficult to use in applications with limited design space. This paper presents a curved differential mechanism that utilizes a lightweight, compliant structure. This mechanism acquires its differential characteristic by having a high rotational stiffness when the mechanism is symmetrically actuated on two sides, while having a low rotational stiffness when actuated only on one side. To make the mechanism neutrally stable, the intrinsic elastic strain energy required for deformation of the compliant differential is compensated for by the reintroduction of potential energy, which is provided by two preloaded springs. The rotational stiffness of the one-sided actuation of the compliant differential mechanism around the neutral position is hypothesized to be adjustable by changing the preload of the springs. The stiffness can be positive, zero, or negative, indicating that the mechanism can be neutral or bistable. This hypothesis is investigated using a simulated model in Ansys Parametric Design Language (APDL) using optimized parameters to achieve the desired stiffness for the mechanism. The simulated model is validated using an experimental setup for both the one-sided and symmetrical actuation stages. The experimental results showed a high correlation with the simulation results. The mechanism with optimized dimensions and preload demonstrated neutral stability over a 16deg range. Bistability was discovered for preloads greater than the optimized preload. At θ = 0, a linear relationship was discovered between the spring preload and the rotational stiffness of the mechanism. Furthermore, an output/input kinematic performance of 0.97 was found for the simulated results and 0.95 for the experimental results.
A Rational Approach to Meshing Cerebral Venous Geometries for High-Fidelity Computational Fluid Dynamics
Authors: Haley Anna L. , Sidora Gurnish , Cancelliere Nicole M. , Pereira Vitor M. , Steinman David A. 
Published: February 2023

AbstractComputational fluid dynamics (CFD) of cerebral venous flows has become popular owing to the possibility of using local hemodynamics and hemoacoustics to help diagnose and plan treatments for venous diseases of the brain. Lumen geometries in low-pressure cerebral veins are different from those in cerebral arteries, often exhibiting fenestrations and flattened or triangular cross section, in addition to constrictions and expansions. These can challenge conventional size-based volume meshing strategies, and the ability to resolve nonlaminar flows. Here we present a novel strategy leveraging estimation of length scales that could be present if flow were to become transitional or turbulent. Starting from the lumen geometry and flow rate boundary conditions, centerlines are used to determine local hydraulic diameters and cross-sectional mean velocities, from which flow length scales are approximated using conventional definitions of local Kolmogorov and Taylor microscales. By inspection of these scales, a user specifies minimum and maximum mesh edge lengths, which are then distributed along the model in proportion to the approximated local Taylor length scales. We demonstrate in three representative cases that this strategy avoids some of the pitfalls of conventional size-based strategies. An exemplary CFD mesh-refinement study shows convergence of high-frequency flow instabilities even starting from relatively coarse edge lengths near the lower bounds of the approximated Taylor length scales. Rational consideration of the length scales in a possibly nonlaminar flow may thus provide a useful and replicable baseline for denovo meshing of complicated or unfamiliar venous lumen geometries.
Design and Analysis of Multifidelity Finite Element Simulations
Authors: Shaowu Yuchi Henry , Roshan Joseph V. , Jeff Wu C. F. 
Published: February 2023

Abstract
The numerical accuracy of finite element analysis (FEA) depends on the number of finite elements used in the discretization of the space, which can be varied using the mesh size. The larger the number of elements, the more accurate the results are. However, the computational cost increases with the number of elements. In current practice, the experimenter chooses a mesh size that is expected to produce a reasonably accurate result, and for which the computer simulation can be completed in a reasonable amount of time. Improvements to this approach have been proposed using multifidelity modeling by choosing two or three mesh sizes. However, mesh size is a continuous parameter, and therefore, multifidelity simulations can be performed easily by choosing a different value for the mesh size for each of the simulations. In this article, we develop a method to optimally find the mesh sizes for each simulation and satisfy the same time constraints as a single or a double mesh size experiment. A range of different mesh sizes used in the proposed method allows one to fit multifidelity models more reliably and predict the outcome when meshes approach infinitesimally small, which is impossible to achieve in actual simulations. We illustrate our approach using an analytical function and a cantilever beam finite element analysis experiment.
New Design for Implementation of 2-Degree-of-Freedom Planar Parallel Robot for Use in Creating an Infinite 3D Printer
Authors: De La Melena Miguel , Duan Shawn 
Published: February 2023

Abstract
3D printing is a rapidly growing and evolving field filled with a diverse array of printers capable of printing an equally as diverse amount of material. A new type of material extrusion 3D printer was recently developed and features the capabilities of printing infinitely long objects due to design decision of angling the XY plane and incorporating a rotating bed. The innovative design for the infinite 3D printer features a 2-DoF planar parallel manipulator (PPM) that will control the hot-end motion in the XY plane. This innovative design will greatly reduce the mass of moving parts in comparison to other infinite 3D printers. This reduction of weight will reduce inertia and allow for this new printer to achieve higher accelerations. In addition to the development of the new 3D printer, this paper presents a kinematic and dynamic model of the angled PPM, a finite element analysis of the critical components of the PPM, and an optimization approach to determine arm length of the PPM. The dynamic model simulation was developed in MATLAB and the results were compared with field data collected to verify the model. A meta-heuristic optimization was performed to optimize arm length of the connectors while maximizing the dynamic performance of the PPM with consideration of the usable workspace. The results of these examinations yield a validated mechanism that will be suitable for the development of a new type of infinite 3D printer.
How Do Maintenance Personnel Perceive Occupational Safety and Health (OSH) Risks During Major Overhauls, Outages, Shutdowns or Turnarounds (MoOSTs)? An Examination of the Nigerian Cement Industry
Authors: Yunusa-Kaltungo Akilu , Jungudo Rukaiyatu Mohammed , Ray Srija , Sokunbi Idowu 
Published: February 2023

Abstract
Asset management activities such as periodic overhauls are crucial for ensuring asset integrity and workplace safety. However, lessons learned from previous major industrial accidents across various high-risks industries have indicated that the perception of occupational safety and health (OSH) risks of maintenance personnel during major overhauls, outages, shutdowns and turnarounds (MoOSTs) are common denominators and precursors to several accidents. This is typically owing to several factors especially the fusion of all classes of routine maintenance tasks on enormous scales and the integration of a very diverse workforce (client, regulators, original equipment manufacturers, and various contracting firms) that possess very different safety cultures, which in turn compound overall risk profiles of job sites and the likelihood of accidents. Therefore, developing a good understanding of the risks perceptions and attitudes of MoOSTs workers towards can help improve overall OSH performance. Although several studies have investigated the subject of safety culture and climate in the context of projects especially engineering, procurement and construction (EPCs), however, studies and use cases on MoOSTs are significantly underrepresented, despite their impacts on costs, employment and wellbeing. This study therefore aims to advocate a safety culture that would boost OSH performance during MoOSTs through the development and deployment of safety climate questionnaire survey to MoOSTs workers of leading cement manufacturing operations in Nigeria. The study revealed “training and learning from incidents”, “commitment of senior management towards ensuring safety and its protocol deployment process”, and “effectiveness of incident reporting systems during MoOSTs” as the three main underlying safety climate factors.
CFD Study of the Influence of SARS-CoV-2 Deposition on Human Lung Dynamic: A Comparison Between Healthy and Diseased Condition
Authors: Carotenuto Carlo , Scurani Letizia , Fontanili Luca , Montorsi Luca , Milani Massimo 
Published: February 2023

Abstract
This paper presents a numerical approach to analyze the influence of SARS-CoV-2 deposition on human lung dynamics under real conditions. A comparison is made between a healthy and a diseased lung. A multiphase three-dimensional computational fluid dynamics (CFD) study is performed for the dispersion of covid-19 virus particles throughout the alveolar tree. Then, fully coupled fluid-structure interaction (FSI) is used to evaluate the expansion properties of the alveolar wall. The mesh morphing technique with solid displacement characteristics is used to obtain a realistic wall displacement during the inspiratory and expiratory phases corresponding to the expansion and retraction of the alveolar sac, respectively. These phases are studied under steady-state conditions. The main objective of this study is to evaluate how particle deposition alters the displacement of alveoli exposed to a Sars-Cov-2 and to compare the obtained simulation results with the healthy case. The novelty of this analysis is that it examines where the virus is most deposited and how the presence of Sars-Cov-2 can affect the mechanical properties of the alveolar sac and worsen the respiratory capacity of a sick person at an advanced stage of infection.
Spontaneous Enlargement of Receptor Clusters in Response to Pulling Traction
Authors: Sarvestani Alireza S. , Moorthy Arsha 
Published: February 2023

Abstract
Most adherent cells are capable of sensing the external forces and probing the mechanical properties of their surroundings. These are classical hallmarks of what is termed mechanotransduction. Mechanotransduction is generally attributed to the sensory functions of focal adhesion (FA) proteins upon activation by mechanical stimuli. A striking feature of cell mechanosensing is the growth of FAs in response to increased cytoskeletal or extracellular tension. Despite growing knowledge about the molecular structures of cell focal adhesions, it has remained elusive as to how these anchorage points grow and how their sensory function operates. The aim of this contribution is to show that force-dependent enlargement of FAs could be driven by spontaneous clustering of transmembrane receptors, independent from active sensory mechanisms. The elasticity of bonds is the key regulator of this process. The mechanical work associated with the cytoskeletal tension alters the free energy landscape and facilitates the recruitment of free receptors to establish new bonds with ligands. Therefore, mechanotransduction could be the manifestation of a thermodynamic process in cell FAs to achieve the state of minimum free energy, independent from the sensory function of molecular sensors in FAs, as postulated in available models.
A Model-Based Approach for Integrated Variation Management
Authors: Horber Dennis , Götz Stefan , Schleich Benjamin , Wartzack Sandro 
Published: February 2023

Abstract
Variation management is a responsible task for product developers, which have to balance the ever-increasing quality demands and cost pressures, while considering the product design as well as the manufacturing and assembly process. These aspects have a direct impact on its subsequent success in the market. Therefore, a large number of different activities of variation management are necessary. In this area, a wide variety of mostly document-centered methods support product developers, which have individual interfaces. Thus, it is currently not possible to map the entire variation management process in a single model. Especially with regard to the increasing availability of large amounts of data, the potential of an integrated variation management cannot be exploited efficiently. For this reason, this paper presents a novel model-based approach for the development of a combined system and tolerancing model. This model contains the processes and activities of integrated variation management and links them with further system models and the corresponding data. The presented approach is a superordinate model for variation management as well as its processes and provides the modeling of individual views of different stakeholders. In addition, process- and program-specific solutions can be integrated into the model, which enables a cross-linking of the data beyond their interfaces. In this paper, the approach is realized using the systems modeling language (SysML).
Modelling of Surface Roughness in CO2 Laser Ablation of Aluminium-Coated Polymethyl Methacrylate (PMMA) Using Adaptive Neuro-Fuzzy Inference System (ANFIS)
Authors: Okello Job Lazarus , El-Bab Ahmed M. R. Fath , Yoshino Masahiko , El-Hofy Hassan A. , Hassan Mohsen A. 
Published: February 2023

Abstract
High surface roughness hinders the flow of fluids in microchannels leading to low accuracy and poor-quality products. In this work, the adaptive neuro-fuzzy inference system (ANFIS) was used to examine surface roughness in CO2 laser fabrication of microchannels on polymethyl methacrylate (PMMA). The PMMA substrates were coated with a 500 nm layer of 99.95% pure aluminium. The inputs were speed (10, 15, and 20 mm/s), power (1.5, 3.0, and 4.5 W), and pulse rate (800, 900, and 1000 pules per inch) while the output was surface roughness. A 3-level full factorial design of experiments was used, and 27 experiments were conducted. Using the gaussian membership function (gaussmf), the ANFIS model was developed using the ANFIS toolbox in MATLAB R2022a. Analysis of variance was performed to examine the significance of the inputs. Power is the most significant followed by speed and pulse rate. The mean relative error (MRE), mean absolute error (MAE), and the correlation coefficient (R) were used to examine the accuracy and viability of the model. MRE, MAE, and R were found to be 0.257, 0.899, and 0.9957 (R2 = 0.9914) respectively. The root mean square error (RMSE) was 0.0022 and 3.6099 for the training data and checking data respectively. Hence, the developed model can predict the values of the average surface roughness with high accuracy.
Predicting Motion of Engine-Ingested Particles Using Deep Neural Networks
Authors: Bowman Travis , Miranda Cairen , Palmore John 
Published: February 2023

Abstract
The ultimate goal of this work is to facilitate the design of gas turbine engine particle separators by reducing the computational expense to accurately simulate the fluid flow and particle motion inside the separator. It has been well-documented that particle ingestion yields many detrimental impacts for gas turbine engines. This ingestion is of concern for operation in environments where dust, ash, or ice persist. The consequences of ice particle ingestion can range from surface-wear abrasion to engine power loss. Ice particles are chosen for this study because of their relevance to civil aviation. It is known that sufficiently small particles, characterized by small particle response times (τp), closely follow the fluid trajectory whereas large particles deviate from the streamlines. The behavior of small particles hints at a method for larger particle trajectories because the higher order terms (HOT) in the asymptotic particle acceleration solution can be shown to be O(τp). By explicitly considering τp, these HOT can be derived. Rather than manually deriving these terms, this work chooses to implicitly derive them using machine learning (ML). Inertial particle separators are devices designed to remove particles from the engine intake flow. Particle separators contribute to both elongating the lifespan and promoting safer operation of aviation gas turbine engines. Complex flows, such as flow through a particle separator, naturally have rotation and strain present throughout the flow field. This study attempts to understand if the motion of particles within rotational and strained canonical flows can be accurately predicted using supervised ML. This report suggests that preprocessing the ML training data to the fluid streamline coordinates can improve model training. Furthermore, this work provides some guidelines for applying ML, particularly deep feed-forward neural networks, with physics driven multiphase flow data. Additionally, the ML model is able to predict the particle accelerations in the fully rotational and irrotational canonical laminar flows quite well. For combined flows with rotation and strain, however, the model struggles to predict the particle accelerations.
Topology Optimization for Acoustic Structures Without Floating Components
Authors: Noguchi Yuki , Ohta Yusei , Matsushima Kei , Yamada Takayuki 
Published: February 2023

Abstract
We propose a level-set method for topology optimization to design acoustic structures without unsupported floating structures. The proposed method involves developing an artificial physical model for detecting floating structures and an objective function for eliminating them. As a design problem, we chose acoustic cloaking and formulated a topology optimization problem under geometric constraints. We applied an optimization algorithm that includes finite element analysis for the acoustic system and an artificial physical field. We provide several numerical examples demonstrating the validity and applicability of the proposed method, and we show how it can be used to design a cloaking structure without any floating components.
High Resolution Real Time Synthetic Aperture Imaging in Solids Using Virtual Elements
Authors: Huang Chengyang , Lanza di Scalea Francesco 
Published: February 2023

Abstract
This paper discusses some improvements to ultrasonic synthetic aperture imaging in solids with primary applications to in-situ non-destructive testing of railroad tracks. Specifically, the study examines three different subarray emission modalities that enhance the signal-to-noise ratio in ultrasound inspection using a phased array with the addition of a transducer wedge. The subarray emission approach effectively compensates for the loss of synthetic transmit power in sparse transmission. Numerical analysis and experimental testing of a point scatterer evaluate the focusing ability of the three subarray emission methods with different subaperture configurations. The Delay-and-Sum (DAS) algorithm builds synthetic aperture images by tracing the refracted ray paths in the multi-layered structure. The transmit subarrays are modeled as virtual elements in the DAS algorithm to accommodate the phase coherence of the synthetic wavefronts. The best subaperture configuration is found by evaluating the resolution and contrast of synthetic aperture images of a subwavelength scatterer in an aluminum block. The SAF imaging approach proposed in this paper have been tested in a portable system aimed at the imaging of internal flaws in rails. The ability to obtain 3D images of rail flaws is badly needed in the railroad maintenance community to enable the most informed remedial decisions following the detection of a defect. The portable system utilizes GPU parallel computation to realize quasi real-time DAS beamforming, and defects are visualized in 3D with calibration of the rail profile. Results are shown from a series of tests conducted on a variety of flaws present in rail sections. These results show the improvements in both imaging speed and signal strength that can be achieved by the subarray emission methods over the conventional synthetic aperture imaging methods.