bluuebunny/crossref_metadata_2025_split huggingface dataset:
Innovative Information Model to Improve Quality and Collaboration on Stone Industry
Authors: Cunha Adriana , Silva João 
Published: January 2020

Abstract
Stone market requirements demand for increasing quality and monitoring criteria, so the need for new innovative solutions that allow to monitor and control entire value chains. IoT4Stone solution proposes a new innovative approach to monitor and control the stone value chain through its entire lifecycle. That is done through the automation and control of the production processes and the definition of an information model to process and optimize the entire value chain increasing collaboration efficiency. This goal is achieved through a digital-twin between the machinery used in the shop-floor and CPPS.
Effect of Current Density and Temperature on Template Assisted Cobalt Nanowire
Authors: Shiave Ali Imran , Mohan Ram , Samykano Mahendran 
Published: January 2020

Abstract
Metal 1-D nanostructures are of special interest in industry applications because of their unique properties. Various synthesizing techniques have been employed to grow free standing and well dispersed nanowires. Among these methods, template assisted electrodeposition (TAE) is the most popular one because of its simplicity, cost effectiveness, high yield, ease of control over growth parameters, less contamination, and scalability to mass production. Processing conditions during the deposition process can affect the nanowire properties by a great deal. So far, these effects are not well established, and are in the early stages. In this work, we study the effect of current density and temperature on electrodeposited cobalt (Co) nanowire synthesized via template-assisted approach. Commercially available anodic alumina oxide templates were used for galvanostatic two electrode electrodeposition. Scanning electron microscopy was used to study the morphology of formed cobalt nanowires with EDS analysis confirming Co as main building element. Detailed XRD analysis was performed to find crystal orientation as well as crystal size.
Identification of the Mechanical Characteristics of 3D Printed NinjaFlex®
Authors: Messimer Patrick , O’Toole Brendan , Trabia Mohamed 
Published: January 2020

Abstract
NinjaFlex is a flexible thermoplastic polyurethane (TPU) material manufactured for use with Fused Deposition Modelling 3D printers. It is widely available, relatively inexpensive, and is useful in various applications including gaskets, wearable electronics, and customized prosthetics because of its great flexibility and strength. The objective of this research was to expand on the limited information available regarding the mechanical characteristics of NinjaFlex and learn how infill density and printing orientation influence those characteristics.
An experiment was designed using the ASTM D638-14 standard to evaluate tensile properties of NinjaFlex specimens printed in two different orientations with their longitudinal axis parallel to the printing surface and with their longitudinal axis normal to the printing surface. Four different infill densities were used. Specimens were subjected to tensile loading along their longitudinal axes. A calibrated load cell measured applied force while a camera filmed the experiment for determining the corresponding extension using computer vision methods.
The results show that NinjaFlex has sizably greater ultimate strength, elongation, and toughness when loaded parallel to its print layers then when loaded normal to its print layers. The effects of infill density on tensile properties vary depending on loading direction relative to the print layer direction.
Dynamic Simulation and Control of a Roller Conveyor
Authors: Range Bradford 
Published: January 2020

Abstract
Passive roller conveyors are frequently used in material handling applications to transport objects of various sizes and shapes. Passive systems cannot control unit flow, leading to queues and system jams. In this paper we analyze the performance of a gravity-driven roller conveyor with brakes selectively installed on rollers to control package flow in the load lanes of a transportation hub. Dynamics of the rollers and kinematic interaction with boxes on the conveyor were derived and fully modeled in MATLAB to simulate accurate conveyor behavior. Sensitivity analyses were performed to evaluate the effect of friction, box mass, roller inertia, and other factors. Using heuristic data to define boundary conditions (box weight, size, and input frequency), several control cases were evaluated. Performance was defined by buffering efficiency of the conveyor, or how effectively the conveyor “kept pace” with a person moving boxes from the load conveyor onto a waiting truck. Several dynamic control cases were simulated. It was found that the optimal number of installed brakes is 30% of the total rollers on the conveyor. Even rudimentary brake control schemes (applying a simple duty-cycle on/off to roller brakes) had the potential to increase the conveyor buffer efficiency by 10% over baseline, with the potential for much greater benefits from more “intelligent” closed-loop control schemes. The simulation and optimization of the active roller conveyor gave insights into the behavior of their truck loading system and identified several ways to increase loading efficiency.
Data Collection and Analysis Using a Wind Turbine and a Photovoltaic Solar Panel
Authors: Azzouz Salim , Blevins Johnny , Thomas Tyler , Johnson Makenzie , O’Connor Clarke , Anih Nchetachukwu C. , Ronoh Melanie , Tonge Ernuel , Semper Cykelle 
Published: January 2020

Abstract
A weather data collection study is currently conducted using a renewable energy training system. The system is composed of a LabVolt trainer, two sun tracking photovoltaic solar panels and a small wind turbine. The LabVolt training system is located in one of the McCoy School of Engineering laboratories, the solar panels and the wind turbine are located in the neighborhood of the Engineering building at Midwestern State University in Wichita Falls, Texas. A set of meteorological data collecting outdoor sensors to monitor the impact of weather conditions on the power generation of the sun-tracking photovoltaic solar panels and the wind turbine have been installed on the building roof. Weather parameters such as atmospheric temperature, pressure, humidity, and rainfall are monitored using a Davis Vantage Pro 2 data collecting system. A number of LabVIEW data acquisition cards and signal processing modules are used to monitor the sun-tracking photovoltaic solar panels’ output voltage, the wind turbine output voltage, the atmospheric temperature, the solar irradiance, and the wind direction, speed, and RPM. A voltage divider has been built to step down the 90V DC voltage produced by the solar panels to 12V DC voltage required for the trainer electrical circuits. A LabVIEW data processing program is used to create instantaneous graphic displays of the collected data on a monitoring screen. The LabVolt trainer is equipped with two charge controller electronic devices, one is used for the sun tracking photovoltaic solar panels, and one is used for the wind turbine. They are used to control the flow of electrical energy through a set of electrical loading devices and a set of storages batteries. Additionally, the LabVolt trainer is equipped with two kilowatt-hour-meters counting the electrical energy consumed by the electrical loads. The trainer is also equipped with two inverters transforming the 12 V DC voltage collected from both energy producing devices to 120 V that can be used by the electrical loading devices. A brief description of all used electronic components and devices is provided in the paper, as well a detailed experiment set-up with a procedure to run them. The project has been divided into three consecutive phases. The first phase dealt with connecting the solar panels, wind turbine, and data collecting sensors to the LabVIEW data acquisition software. The second phase is currently dealing with setting up the trainer solar and wind electricity providing circuits. In the third upcoming phase, it is expected that the data collected by the sensors will be gradually archived using Excel files and analyzed for weather data correlation purposes. It is also expected that the training system will be used to teach upcoming mechanical engineering students about how to set up an independent renewable energy system and the necessary equipment required to run it.
Detailed Three-Dimensional Velocity Field Measurements of a Complex Internal Cooling Flow Within a Gas Turbine Vane
Authors: Benson Michael J. , Helmer David , Van Poppel Bret P. , Duhaime Benjamin , Bindon David , Cooper Mattias , Woodings Robert , Elkins Christopher J. 
Published: January 2020

Abstract
A 6.67 scale model of the Advanced Recirculation Total Impingement Cooling (ARTIC) gas turbine vane insert’s leading edge was designed, built using stereolithography (SLA) fabrication methods, and tested using Magnetic Resonance Velocimetry (MRV), a non-invasive data acquisition technique that captures three-dimensional, three-component velocity fields of a copper sulfate solution over the course of several hours. The experimental apparatus supplied constant flow rates through a test section placed within a 3.0 Tesla MRI magnet. Tests were run at two fully turbulent flow rates corresponding to Reynolds numbers based on hydraulic diameter of 10,000 and 20,000 with the higher flow rate case achieving dynamic similarity with the full-scale ARTIC device. The experimental results elucidated key details and intricacies of the complex flow within the insert. Analysis of flow distribution between each of the three independent impingement zones revealed a degree of measurable jet to jet variability. Stagnation and recirculation zones were detected, informing design modifications and enabling assessment of inlet effects on impingement. Measurement uncertainty was assessed and estimated to be approximately 7.5% of the peak velocity at the inlet to the central feed cavity.
Effect of Sample Preparation on Volta Potential Measurements of Plastically Deformed Mg-Al Alloys
Authors: Fialkova Svitlana , Zhang Honglin , Xu Zhigang , Sankar Jagannathan 
Published: January 2020

Abstract
The low corrosion resistance of Mg alloys is the major challenge that slows down the actual application of these lightweight materials. Magnesium has a more negative standard reduction potential than common alloying elements — aluminum and zinc. The formation of local galvanic couples was reported in AZ31-AZ91 alloys due to precipitation of secondary phases, and it was suggested that these galvanic couples provided initiation sites for localized pitting corrosion.
Scanning Kelvin probe force microscopy (SKPFM) technique is a precise tool to study the Volta potential distribution on surfaces. Since the lateral resolution of SKPFM maps can reach several nanometers, the technique can be used to detect the deformation-induced formation of nano-particles and phases nucleates. However, the precision of the measurements is affected by several factors: tip-sample distance, humidity, the roughness of the surface and tip characteristics, i.e. tip radius, conductivity, and stiffness. Taking into account that magnesium surface is commonly covered by the self-forming oxide layer, which is reducing electrical sensitivity of the tip, the sample preparation and handling can be considered the major factor that affects the quality of measurements by SKPFM.
The aim of our work was to investigate different alternative sample preparation methods for SKPFM and to compare the results (Volta potential maps and topography) with the optical, Scanning Electron Microscopy and Energy Dispersive Spectroscopy maps. The samples were prepared by mechanical polishing, mechanical polishing followed by chemical etching and mechanical polishing followed by ion-milling. For our study, we used a laboratory hot-rolled magnesium-aluminum alloy samples and analysis were focused on typical metallurgical features: surface topography, intermetallic nano-particules and phases nucleates, grain boundary precipitates and grain boundaries.
Real Time Pattern Recognition for Prosthetic Hand
Authors: Benitez Lopez Mario A. , Rodriguez Carlos , Camargo Jonathan 
Published: January 2020

Abstract
Control of prosthetic hands is still an open problem, currently, commercial prostheses use direct myoelectric control for this purpose. However, as mechanical design advances, more dexterous prostheses with more degrees of freedom (DOF) are created, then a more precise control is required. State of the art has focused in the use of pattern recognition as a control strategy with promising results. Studies have shown similar results to classic control strategies with the advantage of being more intuitive for the user. Many works have tried to find the algorithms that best follows the user’s intention. However, deployment of these algorithms for real-time classification in a prosthesis has not been widely explored. This paper addresses this problem by deploying and testing in real-time an Artificial Neural Network (ANN). The ANN was trained to classify three different motions: no grasp, precision grasp and power grasp in order to control a two DOF trans-radial prosthetic hand with electromyographic signals acquired from two channels. Static and dynamic tests were made to evaluate the ANN under those conditions, 95% and 81% accuracy scores were reached respectively. Our work shows the potential of pattern recognition algorithms to be deployed in microcontrollers that can fit inside myoelectric prostheses.
Nano Sized Bubble Formation, Growth and Collapse in Liquid Water by Central Heating: A Molecular Dynamics Simulation
Authors: Bin Shahadat Muhammad Rubayat , Morshed AKM M. , Tikadar Amitav , Paul Titan C. , Khan Jamil A. 
Published: January 2020

Abstract
Non-equilibrium Molecular Dynamics (NEMD) Simulation has been employed to investigate the nanobubble generation, growth and collapse in liquid water. The center molecules (240 water molecule) of the simulation domain were heated at five different temperatures (400K, 800K, 1500K, 2100K and 2800K) by velocity scaling for a very short period of time and the radius of the nano sized bubble was calculated. At 400K temperature, no nano bubble is formed but as temperature increases, nano bubble forms and the radius of the nano bubble increases. TIP-3P potential model has been used to predict the structural parameters of water molecules. The SHAKE algorithm has been employed to hold the bonds of O-H and H-O-H as rigid. The results obtained from the simulation were then compared with the results got from Rayleigh-Plesset Equation in order to show the discrepancy of MD simulation and the Hydrodynamic model. The simulation results indicate that Rayleigh-Plesset equation is not valid for prediction the formation, growth and collapse of nano bubble in liquid water because of its uncertainty in predicting the surface tension and ignoring the viscosity.
A Study of Hybrid Composite Sandwich Beam
Authors: Alam Shah , Li Guoqiang 
Published: January 2020

Abstract
This study presents the testing and numerical modeling results of composite sandwich beams. The sandwich beams are constructed from balsa wood in the core and high strength steel wire and E-glass fiber reinforced polymer composite in the facings. The testing of these beams is performed using a monotonic static four-point loading to failure in accordance with ASTM C393-00. Local strain distribution in the mid-span of the beams is obtained using strain gauges. Mid-span deflections of the beams are real-time measured using linear variable displacement transducer (LVDT). From the experimental results, flexural properties of the beams are calculated, including bending stiffness, bending strength, core shear strength, and facing modulus, core modulus, etc. The experimental results have shown that the beams have all failed in the compression zone by local buckling of the top face and shear of the core. The bottom skin does not exhibit any type of premature failure or distress. No bond failure of the composite in the tension zone is observed in any of the tested beams. Finite element modeling of the beam has been conducted using ANSYS. The mechanical properties of the skin and core material used in finite element modeling have been determined by testing of coupons. The predicted results are compared to experimental results, with a reasonable agreement.
An Analysis of the Trends in US Offshore Oil and Gas Safety and Environmental Performance
Authors: Gernand Jeremy M. 
Published: January 2020

Abstract
The production of oil and gas in the offshore waters of the United States continues to be a major part of US energy extraction activities amounting to just less than a third of total US oil and gas production. However, this industry has been marked by occasional safety and environmental disasters including most famously the Deepwater Horizon explosion and oil spill that resulted in the deaths of 11 workers and the release of more than 130 million gallons of oil in to the Gulf of Mexico. In response, the Bureau of Safety and Environmental Enforcement (BSEE) was created in 2011 to separate enforcement activities from federal lease management activities and reduce the possibility for conflicts of interests and regulatory capture. This paper presents an analysis of the safety and environmental performance of the US offshore oil and gas industry in the years before and after the creation of the BSEE to quantify the changes in the industry record and the level of risk that remains. Recorded events including fires and explosions, spills, and gas releases, collisions, and injuries and fatalities are included in the analysis. The overall level of exposure is estimated based on rig counts and oil and gas production quantities since detailed employment records by facility are not available. Data is sourced from the BSEE, Bureau of Labor Statistics (BLS), and the Energy Information Agency (EIA). In addition to linear regression analysis of trends, this paper presents the results of a random forest-based machine learning investigation of the characteristics of safety and environmental incidents to evaluate the most significant contributors that remain, especially those amenable to control through engineering system design. Facility type, water depth, distance to shore, and time of day or year in the relevant incident reports were included in the input dataset for the random forest model. Results indicate that the overall oil and gas industry has become safer in recent years, though significant risks remain. It is yet unclear whether the BSEE approach bears any responsibility for this change as the data are not yet sufficient to declare the post-2011 period as statistically significantly improved from prior years, though additional data in line with 2016–2017 level of performance would satisfy this condition. The random forest model indicates that increased risk is associated with time of day, quarter of the year, water depth, and distance to shore. Data quality concerns remain present as minor incidents and injuries may be under-reported. BSEE enforcement does not appear to be a direct cause of the noted improvements.
A Numerical and Experimental Study Supporting a Methodology for Live Monitoring, Leak Detection, and Automatic Response in Water Pipelines
Authors: Chalgham Wadie , Diaconeasa Mihai , Gottumukkala Raju , Seibi Abdennour 
Published: January 2020

Abstract
This paper describes a numerical analysis supported by small scale experiments for demonstrating a monitoring and leak detection methodology. This study can be used to build a full-scale water pipeline monitoring and response system. The monitoring system is able to monitor the pipeline health and respond to hazard conditions through the use of multiple sensors driven by a hybrid rule-based and statistical monitoring control strategy. The system is programmed to automatically shut off its pump in the event of out-of-bounds/out-of-statistical control conditions detected by its sensors. In addition, this paper presents a numerical simulation analysis approach supported by an experiment that aims at finding a relationship between the location and size of an induced leak and the reported sensor data. The obtained results are used to inform a probabilistic model that can be used to estimate the leak location and size based on flow rate variations. The proposed project will enhance remote pipeline monitoring and structural safety by offering real-time data and automatic emergency response capabilities.
Design and Optimization of LIDAR Based 3D Point Cloud Parsers and Algorithms for Mobile Robotics Applications
Authors: Benvenuto Michael , Tatoglu Akin 
Published: January 2020

Abstract
With mobile autonomous robots on the rise, data structuring and algorithm design plays a significant role in how fast data can be parsed and processed. With robotic systems that are decreasing in size and increasing with complexity, the speed at which data can be processed from multiple sources is crucial to how the system as a whole works. This paper plans to show the difference between certain computational algorithm complexities, both time and space complexity, in order to demonstrate the key ideas in data parsing for systems where computational time of an algorithm can affect the outcome performance of a robot dramatically. The algorithmic types being analyzed in this paper are in relation to a 3D LIDAR scanner in order to produce a point cloud as the output from pre-recorded files. Trigonometric calculations will need to be done in order to produce this output and each file used will be verified using a program supplied from the manufacturer of the LIDAR, Velodyne, in order to ensure the data is being read correctly. The sample data consists of two specific recorded sets, a loading bay and a downtown urban city. Each of data set covers the two configurable outputs, a 20 Mhz Dual Return mode and a 10 Mhz Single Return mode, providing a reasonable range in terms of size in bytes. This paper will show various levels of optimization in areas of trigonometric functions, specifically sine and cosine, algorithmic design, memory safety and defragmenting, and pointer manipulation in order to produce a robust, complex yet ideal algorithm for loading large sets of data rapidly and quickly while holding the level of reliability high. All software written in this paper intends to be natively implemented, meaning no operating system specific external binaries will be used for the end product.
A Test Rig to Characterize the Friction Force of Reciprocating Seals Under Dynamic Linear Motion
Authors: Keegan Jon , Ramachandran Madhumitha , Flenniken Adam , Page Geoffrey , Siddique Zahed 
Published: January 2020

Abstract
Seals are used in rotary and linear motion applications as barriers to protect components and equipment from hazardous materials and particulates. Although studies have presented research to characterize seals under rotary motion, performance of seals under linear motion have not been studied in details. In this research paper we will present a test rig and a systematic approach to understand and characterize seals under different conditions for linear motions. We investigate the effects of temperature, pressure and compression (squeeze) on force requirement. These factors are important for applications in oil and gas, manufacturing, combustion to name a few. A unique setup is built to test and gather information on different parameters to characterize seal behavior. Results from the study will be useful for design of components that use seals.