bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hydrodynamics of Metachronal Motion: Effects of Spatial Asymmetry on the Flow Interaction Between Adjacent Appendages
Authors: Lou Zhipeng , Herrera-Amaya Adrian , Byron Margaret L. , Li Chengyu 
Published: September 2022

Abstract
Metachronal motion is a unique swimming strategy widely adopted by many small animals on the scale of microns up to several centimeters (e.g., ctenophores, copepods, krill, and shrimp). During propulsion, each evenly spaced appendage performs a propulsive stroke sequentially with a constant phaselag from its neighbor, forming a metachronal wave. To produce net thrust in the low-to-intermediate Reynolds number regime, where viscous forces are dominant, the beat cycle of a metachronal appendage must present significant spatial asymmetry between the power and recovery stroke. As the Reynolds number increases, the beat cycle is observed to change from high spatial asymmetry to lower spatial asymmetry. However, it is still unclear how the magnitude of spatial asymmetry can modify the shear layers near the tip of appendages and thus affect its associated hydrodynamic performance. In this study, ctenophores are used to investigate the hydrodynamics of multiple appendages performing a metachronal wave. Ctenophores swim using paddle-like ciliary structures (i.e., ctenes), which beat metachronally in rows circumscribing an ovoid body. Based on high-speed video recordings, we reconstruct the metachronal wave of ctenes for both a lower spatial asymmetry case and a higher spatial asymmetry case. An in-house immersed-boundary-method-based computational fluid dynamics solver is used to simulate the flow field and associated hydrodynamic performance. Our simulation results aim to provide fundamental fluid dynamic principles for guiding the design of bio-inspired miniaturized flexible robots swimming in the low-to-intermediate Reynolds number regime.
Application of Proper Orthogonal Decomposition to Study the Flow Over an Oscillating Flag
Authors: Padilla Rodrigo , Durgesh Vibhav , Xing Tao 
Published: September 2022

Abstract
Fluid-Structure-Interaction (FSI) is the coupling between a flowing fluid and a structure that results in either a static or dynamic structure deformation. This investigation focused on applying Proper Orthogonal Decomposition (POD) to study the fluid flow behavior of an oscillating flag and using POD modes to quantify the changes in flow behavior associated with the change in flag oscillation modes. For this purpose, aerodynamic load, membrane location, and Particle Image Velocimetry (PIV) measurements were performed for a selected flag model. The flag location measurements helped identify the change in oscillation shapes and modes with change in flow conditions, while the aerodynamic load data allowed us to quantify the impact of flag oscillations on the aerodynamic load experienced by the flag. The PIV data provide flow field information around the oscillating flag and were used to perform POD analysis. We observed that the POD mode, energy, and time-varying coefficients changed with change in the oscillation modes of the flag (i.e., change from mode-2 to mode-3 oscillations). Flow reconstruction using the first three POD modes allowed us to capture changes generated in large-scale structures in the flow due to changes in the oscillation modes. Flow reconstruction using the remaining POD modes allowed us to observe the behavior of small-scale flow structures and K-H vortices in the wake of the flag. The POD approach used here allowed us to quantify the change in flow behavior and understand the underlying FSI mechanism therein.
Electrostatic Painting Process: Impact of Using Connected High-Voltage Embodiments With Rotary Bell Atomizers on Droplets Transport and Deposition
Authors: Pendar Mohammad-Reza , Páscoa José Carlos 
Published: September 2022

Abstract
This study implemented a 3D comprehensive Eulerian-Lagrangian numerical evaluation of the flow around the electrostatic rotary bell sprayer (ERBS) attached to a devised novel high-voltage emitting embodiment, portable retractable blades assembly or adjustable fixed control ring for improving the performance and transfer efficiency (TE) of the coating process. The electric potential distribution, which is produced by applying a voltage differential between the spray gun and the grounded target, is manipulated here to control the electrostatic force acting on the sprayed particles more effectively. The electrostatic rotary bell sprayers are widely utilized in the automotive industry, the disinfection process of different places, and the pesticides applications in agriculture. The disintegration process of the paint liquid inside and around the rotary bell cup surface, the spray plume pattern and the film formation on the workpiece for various introduced cases are compared precisely. Due to the concentration and distortion of the electrical field equipotential lines among the ERBS and target, thicker film distributions were obtained in the modified design of the sprayer in a combination of the retractable blades or the control ring compare to the conventional one. These results, achieved utilizing the new corona charging sprayer versions, satisfactorily confirm the applicability of the proposed concepts for all electrical effects, including space charge.
A Numerical Study on the Powder Flowability, Spreadability, Packing Fraction in Powder Bed Additive Manufacturing
Authors: Akib Yeasir Mohammad , Marzbanrad Ehsan , Ahmed Farid , Li Jianzhi 
Published: September 2022

Abstract
The powder bed fusion (PBF) process is widely adopted in many manufacturing industries because of its capability to 3D print complex parts with micro-scale precision. In PBF process, a thermal energy source is used to selectively fuse powder particles layer by layer to build a part. The build quality in the PBF process primarily depends on the thermal energy deposition and properties of the powder bed. Powder flowability, powder spreading, and packing fraction are key factors that determine the properties of a powder bed. Therefore, the study of these process parameters is essential to better understand the PBF process. In our study, we developed a two-dimensional powder bed model using the granular package of the LAMMPS molecular dynamics simulator. Cloud-based deposition was adopted for pouring powder particles on the powder bed. The spreading of particles over the substrate was mimicked like a powder bed system. The powder flowability in the proposed study was analyzed by varying the particle size distribution. The simulation results showed that a greater number of larger particles in a power sample results in an increase in the Angle of Repose (AOR) which ultimately affects the flowability. Two different kinds of recoater geometry were considered in this study: circular and rectangular blades. Simulation results showed that depending on the recoater shape there is a change in the packing fraction in the powder bed. Cross-sectional analysis of the power bed showed a significant presence of voids when a greater number of larger particles existed in the powder batch. The packing fraction of the powder bed was found to be a strong function of particle size distribution. These analyses help understand the influence of particle size and recoater shape on the powder bed properties. Findings from this study help to provide a guideline for choosing particle size distribution if the spherical particles are considered. While the present study focuses on the spherical powder particles, the proposed system can also be adapted to the study of powder bed with aspherical particles.
Surface Roughness Prediction for Additively Manufactured Ti-6Al-4V Components Based on Supervised Learning Models
Authors: Maitra Varad , Shi Jing 
Published: September 2022

Abstract
To avoid redundant trial and error experiments in hope of achieving acceptable surface roughness, reliable predictive models must be engineered to anticipate surface characteristics based on process parameter inputs. In the present study, two rigorously tested supervised machine-learning based models are proposed to predict the arithmetic average (Ra) of profile deviation for the surface of Ti-6Al-4V alloy manufactured via selective laser melting (SLM). Firstly, a Gaussian Process Regression (GPR) model with Rational Quadratic kernel function is constructed after ten-fold cross validation of the training data. Secondly, using the same training data and the same ten-fold cross validation, a feed-forward narrow neural network (NN) is employed. Primary input parameters of SLM process, namely laser power, scanning speed, hatch spacing, layer thickness and volumetric energy density are mined from literature investigating as-built surface characteristics of SLMed Ti-6Al-4V alloy. To further test the developed machine-learning models, ten 8 × 8 × 8 mm Ti-6Al-4V cubes are manufactured and a comparative between two non-parametric (GPR and NN) models is performed by predicting the surface roughness (Ra) of the ten samples. It is discovered that the NN model underperforms with a root mean squared error (RMSE) of 2.76 μm, as opposed to its counterpart GPR model, exhibiting RMSE of 0.82 μm. Additionally, analyses of the surface characteristics of the fabricated samples, the surface profiles, and impact of such a predictive model are provided.
Effects of Flight Distance on Metal Microdroplet Depositing Behaviors in Laser-Induced Forward Transfer
Authors: Wu Di , Lu Zijie , Luo Guohu , Hu Yongxiang 
Published: September 2022

Abstract
Laser-induced forward transfer (LIFT) presents promising perspectives towards high precision three-dimensional metal microstructure fabrication. However, the positional deviation of deposits produced in LIFT reduces the printing resolution. In this study, we experimentally investigate the effects of flight distance on the depositing behaviors of the metal droplets in LIFT. A series of droplet deposition experiments with different flight distances were performed, printing a large number of particles in each set of parameters to avoid random errors. Morphology of deposited particles under different conditions was compared. Positional information was extracted by the image matching algorithm. The flight distance was optimized by analyzing the positional deviation and the morphology of particles.
The results demonstrate that the positional deviation of particles increases linearly with the flight distance, while the average size of particles is constant. Excessive flight distance increases the oxidation of copper droplets. For the distance less than 20 μm, a portion of particles disappears in the array. There is a flat surface on the top of particles, indicating that droplets have been squashed by the carrier substrate. This conjecture is confirmed by the observation of residual metal particles on the carrier substrate. This study will advance the understanding of droplet generation and the application of LIFT in the industry.
Machine Setup Abnormality Detection Using Machine Vision and Deep Learning
Authors: Choudhari Sahil J. , Singh Swarit Anand , Kumar Aitha Sudheer , Desai K. A. 
Published: September 2022

Abstract
Machine tools can perform manufacturing operations autonomously with minimal involvement of machine operators. However, significant human expertise is required while machine setup to minimize machine faults, downtime, and scrap parts for achieving better productivity. The machine setup involves activities such as the presence/absence of a correct cutting tool in the spindle, adequate placement of workpiece on the fixture, ensuring proper coolant flow, clogging of chips, etc. The present machine shops employ skilled human operators to perform these tasks with a checklist for ensuring completeness. The outcomes of the process are dependent on the judgment, consistency, and skills of the operator. Machine vision is considered a low-cost, low-error, and higher consistency substitute for skilled humans in industrial processes involving repetition or fatiguing tasks. The existing machine vision systems developed for dimension measurement or surface defect detection application cannot detect machine setting abnormalities due to the distinct requirements. The present work explores the development of a robust algorithm by augmenting machine vision with the deep learning algorithm You Only Look Once (YOLO) to directly extract features from the captured images. The object detection algorithm based on YOLO-v2 and ResNet-50 is implemented to detect and segregate the elements of interest from different shop-floor images. The algorithm is trained using labeled image datasets generated for several machine setup abnormalities. An interactive Graphical User Interface (GUI) is developed and integrated with the model to implement the proposed framework on the manufacturing shop floor. The developed system was implemented to detect machine setup abnormalities by considering different case studies. The study demonstrated robust detection abilities of the algorithm, offering a potential solution to minimize dependence on human operators for machine setup abnormalities.
Design of Micro-Scale Periodic Surface Textures by Pulsed Laser Melting and its Influence on Wettability
Authors: Gupta Rohit , Hijam Justin , Balhara Rama , Vadali Madhu 
Published: September 2022

Abstract
Micro- and nano-scale surface texture plays a major role in the wetting behavior of various metallic and non-metallic components. Modifying surfaces using lasers has been widely explored to induce periodic surface textures and thus modify the wetting behavior. Most of these modifications are either through addition or ablation material, making the process uneconomical for the industries. This work presents the pulsed laser surface melting (pLSM) based modification of metallic surfaces to change the wetting behavior, wherein the material is neither removed nor added but is redistributed to create micro-scale features. The size and geometry of the redistributed material depend on the incident laser power and pulse duration and thus affect the wetting behavior. Detailed experimental study on an initially near-flat titanium alloy (Ti6Al4V) surface at various laser powers and pulse durations are presented to understand their influence on the wetting behavior. Experiments are carried out at various laser powers ranging from 120W to 300W and various pulse durations ranging from 3μs to 20μs to understand the size and geometry achievable through pLSM. The highest peak to valley height of the pLSM induced feature (2.3μm) was achieved with 10μs long laser pulses at 210W power. This single spot feature was then rastered across the surface with varying spot spacing and line spacing to generate nine textured surfaces. The corresponding transverse contact angles and the orthogonal contact angles are reported. The results show that the textured surfaces are more wettable or hydrophilic than the near-flat untextured surface of Ti6AL4V. In addition, line spacing of the raster scan in the transverse direction has a more significant impact on the contact angle than the spot spacing in the orthogonal direction. The transverse direction has uniform groove-like features, which aid wettability more than the periodic circular features in the orthogonal direction. Nonetheless, pLSM is demonstrated as a potential method to develop micro-scale surface textures to increase the wettability (hydrophilicity) of the Ti6Al4V surface.
Exploring Surface Texture Quantification in Piezo Vibration Striking Treatment (PVST) Using Topological Measures
Authors: Yesilli Melih C. , Chumley Max M. , Chen Jisheng , Khasawneh Firas A. , Guo Yang 
Published: September 2022

Abstract
Surface texture influences wear and tribological properties of manufactured parts, and it plays a critical role in end-user products. Therefore, quantifying the order or structure of a manufactured surface provides important information on the quality and life expectancy of the product. Although texture can be intentionally introduced to enhance aesthetics or to satisfy a design function, sometimes it is an inevitable byproduct of surface treatment processes such as Piezo Vibration Striking Treatment (PVST). Measures of order for surfaces have been characterized using statistical, spectral, and geometric approaches. For nearly hexagonal lattices, topological tools have also been used to measure the surface order. This paper explores utilizing tools from Topological Data Analysis for measuring surface texture. We compute measures of order based on optical digital microscope images of surfaces treated using PVST. These measures are applied to the grid obtained from estimating the centers of tool impacts, and they quantify the grid’s deviations from the nominal one. Our results show that TDA provides a convenient framework for characterization of pattern type that bypasses some limitations of existing tools such as difficult manual processing of the data and the need for an expert user to analyze and interpret the surface images.
The Influence of Cell Phone Usage on Dynamic Stability of the Body During Walking
Authors: Shahidian Hamed , Begg Rezaul , Ackland David C. 
Published: September 2022

Dual-task walking and cell phone usage, which is associated with high cognitive load and reduced situational awareness, can increase risk of a collision, a fall event, or death. The objective of this study was to quantify the effect of dual-task cell phone talking, texting, and reading while walking on spatiotemporal gait parameters; minimum foot clearance; and dynamic stability of the lower limb joints, trunk, and head. Nineteen healthy male participants walked on an instrumented treadmill at their self-selected speed as well as walking while simultaneously (1) reading on a cell phone, (2) texting, and (3) talking on a cell phone. Gait analyses were performed using an optical motion analysis system, and dynamic stability was calculated using the Maximum Lyapunov Exponent. Dual-task cell phone usage had a significant destabilizing influence on the lower limb joints during walking. Cell phone talking while walking significantly increased step width and length and decreased minimum foot clearance height (P < .05). The findings suggest that dual-task walking and cell phone conversation may present a greater risk of a fall event than texting or reading. This may be due to the requirements for more rapid information processing and cognitive demand at the expense of motor control of joint stability.
Matching study using health and police datasets for characterising interpersonal violence in the community of Khayelitsha, South Africa 2013–2015
Authors: Jabar Ardil , Oni Tolu , London Leslie , Cois Annibale , Matzopoulos Richard 
Published: September 2022

ObjectivesThe Cardiff Model of data sharing for violence prevention is premised on the idea that the majority of injury cases presenting at health facilities as a result of interpersonal violence will not be reported to the police. The aim of this study was to determine the concordance between violent crimes reported to the police with violence-related injuries presenting at health facilities in Cape Town, South Africa.MethodsWe conducted a retrospective analysis of secondary cross-sectional health and police data, from three health facilities and three police stations in the community of Khayelitsha, Cape Town. 781 cases of injuries arising from interpersonal violence seen at health facilities were compared with 739 violence-related crimes reported at police stations over five separate week-long sampling periods from 2013 to 2015. Personal identifiers, name and surname, were used to match cases.ResultsOf the 708 cases presenting at health facilities, 104 (14.7%) were matched with police records. The addition of non-reported cases of violence-related injuries from the health dataset to the police-reported crime statistics resulted in an 81.7% increase in potential total violent crimes over the reporting period. Compared with incidents reported to the police, those not reported were more likely to involve male patients (difference: +47.0%; p<0.001) and sharp object injuries (difference: +24.7%; p<0.001). Push/kick/punch injuries were more frequent among reporting than non-reporting patients (difference: +17.5%; p<0.001).ConclusionThese findings suggest that the majority of injuries arising from interpersonal violence presenting at health facilities in Khayelitsha are not reported to the police. A data-sharing model between health services and the police should be implemented to inform violence surveillance and reduction.
Development of a core outcome set and identification of patient-reportable outcomes for primary brain tumour trials: protocol for the COBra study
Authors: Retzer Ameeta , Sivell Stephanie , Scott Hannah , Nelson Annmarie , Bulbeck Helen , Seddon Kathy , Grant Robin , Adams Richard , Watts Colin , Aiyegbusi Olalekan Lee , Kearns Pamela , Cruz Rivera Samantha , Dirven Linda , Baddeley Elin , Calvert Melanie , Byrne Anthony 
Published: September 2022

IntroductionPrimary brain tumours, specifically gliomas, are a rare disease group. The disease and treatment negatively impacts on patients and those close to them. The high rates of physical and cognitive morbidity differ from other cancers causing reduced health-related quality of life. Glioma trials using outcomes that allow holistic analysis of treatment benefits and risks enable informed care decisions. Currently, outcome assessment in glioma trials is inconsistent, hindering evidence synthesis. A core outcome set (COS) - an agreed minimum set of outcomes to be measured and reported - may address this. International initiatives focus on defining core outcomes assessments across brain tumour types. This protocol describes the development of a COS involving UK stakeholders for use in glioma trials, applicable across glioma types, with provision to identify subsets as required. Due to stakeholder interest in data reported from the patient perspective, outcomes from the COS that can be patient-reported will be identified.Methods and analysisStage I: (1) trial registry review to identify outcomes collected in glioma trials and (2) systematic review of qualitative literature exploring glioma patient and key stakeholder research priorities. Stage II: semi-structured interviews with glioma patients and caregivers. Outcome lists will be generated from stages I and II. Stage III: study team will remove duplicate items from the outcome lists and ensure accessible terminology for inclusion in the Delphi survey. Stage IV: a two-round Delphi process whereby the outcomes will be rated by key stakeholders. Stage V: a consensus meeting where participants will finalise the COS. The study team will identify the COS outcomes that can be patient-reported. Further research is needed to match patient-reported outcomes to available measures.Ethics and disseminationEthical approval was obtained (REF SMREC 21/59, Cardiff University School of Medicine Research Ethics Committee). Study findings will be disseminated widely through conferences and journal publication. The final COS will be adopted and promoted by patient and carer groups and its use by funders encouraged.PROSPERO registration numberCRD42021236979.