bluuebunny/crossref_metadata_2025 huggingface dataset:
Development of Thermally Conductive Polymer/CNF Nanocomposite Materials via PolyJet Additive Manufacturing by Improvement of Digital Material Design
Authors: Ulu Furkan Ismail , Mohan Ram , Tomar Ravi Pratap Singh
Published: January 2020

PolyJet printing technology allows building polymeric materials with complex multi-material structures in the resolution of tens of microns layer thickness providing high control over the entire 3-D part. On the other hand, thermally conductive polymer/CNF nanocomposite materials offer new opportunities for replacing metals in industry and applications that require heat dissipation to avoid degradation of materials prematurely. CNFs are one of the best promising filler types to enhance thermal conductance of polymers. However, experimental thermal conductivities of polymer/CNF nanocomposites are significantly low compared to the intrinsic thermal conductivity of CNFs. Present work focused on selectively addition CNF fillers to form a thermally conductive path which helps to control dispersion and alignment. PolyJet printing forms the material and the structure simultaneously which allows the control over the material distribution and morphology on entire 3-D parts while providing possibilities to manipulate the design and create a conductive path. In the present research, improvement of thermal conductivity of Polymer/CNF nanocomposites via PolyJet printing using voxel digital printing method was investigated. Samples were designed as VeroClear material, VeroClear with CNFs, VeroCyan material, VeroCyan with CNFs. DSC and TPS were used to perform the thermal characterization of the samples.
Optimizing Bolting Configurations in a Pressure Vessel
Authors: Mancovsky Justin , Ferriera Jarod
Published: January 2020

Control valve standards and guidelines (specifically ASME B16.34), which have been in place for over 50 years, have undergone incremental changes. These standards are important as they prevent field failure by maintaining system performance and ensuring the safety of workers and other components in proximity to valves.

New control valve technologies represent a significant alteration in valve geometry and operating characteristics. During the development, the valve body geometry and design requirements were closely examined. The authors have identified opportunities for adjustments to ASME B16.34 design requirements through the review of related standards and the process of design optimization.

Specifically, this paper reviews the design requirements for valve body joints and their bolting configurations. It examines bolt properties, including yield stress, proof strength, and allowable stress, through the ASME Boiler and Pressure Vessel Code [1], ASME B16.34 [2], ASME B16.5 [3], and ASME B31.3 [4].

It is proposed that the design requirements found in ASME B16.34 Section 6.4, Valve Joints, be adjusted such that the allowable stress limit for high strength bolts can be fully utilized.

Finite Element Analysis is performed to examine those dynamic loading scenarios that are accounted for in the determination of allowable stress - temperature gradients (which cause pipe expansion and contraction), cyclic fatigue, vibration, impact (flashing or hydraulic shock), seismic events, and live loads (ice/snow).

Data from the analysis is presented to show that the modified bolting configuration can withstand the maximum pressure and temperature requirements. Alternative bolting configurations can be shown to conform to the allowable stress requirements, allowing for design optimizations that reduce the overall size and weight of a valve.

Modifications to ASME B16.34 and ASME B16.5 are therefore recommended. When the proposed bolting configuration was applied to a DN25 valve, we were able to achieve weight savings of 4 lbs., along with a 0.6” reduction in outer diameter. These optimizations allow for manufacturing cost savings including cost of hardware, raw materials, and machining. This optimization can be extrapolated for greater savings with larger valve designs.
Characterizations of the Paper-Based Microfluidic Devices Used for Detecting Fentanyl and Related Synthetic Opioids
Authors: Rahman M. Shafiqur , Chakravarty Uttam K.
Published: January 2020

The design and analysis of a paper-based microfluidic analytical device (μPAD) are presented in this paper for the detection of fentanyl and related synthetic opioids. Fentanyl, a synthetic opioid, is an extremely fast-acting synthetic narcotic analgesic having a high potency of approximately 100 to 200 times that of morphine. Detection of fentanyl can be done by colorimetric assays, i.e., spot tests with paper strips and μPADs which offer speed, simplicity of operation, portability, and affordability. The microfluidic behavior of liquid specimen and paper in the μPADs and test strips play a significant role in drug detection methods. Therefore, the study contains the fabrication of the test device using 3D printing and analysis of microfluidic behavior of the paper-based fentanyl test device. A multiphase computational fluid dynamics (CFD) model of a 3D microchannel is developed to evaluate the microfluidic properties. The CFD model incorporates the properties of cellulose and fentanyl solution to determine the flow parameters using the volume of fluid method. Wicking in the cellulose paper is studied analytically considering the Lucas-Washburn equation and Darcy’s law. Experiments with the fabricated μPAD and commercial test-kit samples are also conducted to compare the experimental results with the results for the flow parameters found from the numerical simulation.
Innovative Information Model to Improve Quality and Collaboration on Stone Industry
Authors: Cunha Adriana , Silva João
Published: January 2020

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

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

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

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.
Numerical Analysis of Detonability Assessment in a Natural Gas-Air Fueled Rotating Detonation Engine
Authors: Saha Pankaj , Strakey Peter , Ferguson Donald , Roy Arnab
Published: January 2020

Rotating Detonation Engines (RDE) offer an alternative combustion strategy to replace conventional constant pressure combustion with a process that could produce a pressure gain without the use of a mechanical compressor. Recent numerical and experimental publications that consider air as the oxidizer have primarily focused on the ability of these annular combustors to sustain a stable continuous detonation wave when fueled by hydrogen. However, for this to be a viable consideration for the land-based power generation it is necessary to explore the ability to detonate natural gas and air within the confines of the annular geometry of an RDE. Previous studies on confined detonations have expressed the importance of permitting detonation cells to fully form within the combustor in order to achieve stability. This poses a challenge for natural gas–air fueled processes as their detonation cell size can be quite large even at moderate pressures. Despite the practical importance, only a few studies are available on natural gas detonations for air-breathing RDE applications. Moreover, the extreme thermodynamic condition (high temperature inside the combustor) allows limited accessibility inside the combustor for detailed experimental instrumentations, providing mostly single-point data. Recent experimental studies at the National Energy Technology Laboratory (NETL) have reported detonation failure at higher methane concentration in an air-breathing RDE fueled by natural gas-hydrogen fuel blends. This encourages to perform a detailed numerical investigation on the wave characteristics of detonation in a natural gas-air fueled RDE to understand the various aspects of instability associated with the natural gas-air detonation.

This study is a numerical consideration of a methane-air fueled RDE with varying operating conditions to ascertain the ability to achieve a stable, continuous detonation wave. The simulations have been performed in a 2D unwrapped RDE geometry using the open-source CFD library “OpenFOAM” employing an unsteady pressure-based compressible reactive flow solver with a k–ε turbulence model in a structured rectangular grid system. Both reduced and detailed chemical kinetic models have been used to assess the effect of the chemistry on the detonation wave characteristics and the underlying flow features. A systematic grid sensitivity study has been conducted with various grid sizes to quantify the weakly stable overdriven detonation on a coarse mesh and oscillating features at fine mesh resolutions.

The main focus of the current study is to investigate the effects of operating injection pressure on detonation wave characteristics of an air-breathing Rotating Detonation Engine (RDE) fueled with natural gas-hydrogen fuel blends. Wave speeds, peak pressures and temperatures, and dominant frequencies have been computed from the time histories. The flow structures were then visualized using 2D contours of temperature and species concentration.
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

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

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

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

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

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

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

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

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

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

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.
Self-Powering Gyms: A Case Study on Energy Harvesting From a Static Bicycle
Authors: Ihsan Mustafa , Viswanathan Vimal
Published: January 2020

The increasing levels of pollution and global climate changes have spurred growing interest in harvesting green energy from all possible resources. One of the under-utilized sources is the energy that one spends during physical exercise at gymnasiums. If the energy that a person expends can be harvested, that may suffice to power the facility at least partially. This paper describes the research, development, and execution of a low-cost arrangement to harvest energy from a static bicycle at a gym. Primarily, the setup uses a generator attached to the bicycle to produce low-voltage electricity. Further, an electrical circuit is designed and implemented to amplify the voltage and send it to a 585CCA battery. The resulting arrangement is found to be sufficient to completely charge the car battery with 12–15 hours of riding of one bicycle. It is estimated that this battery can power two energy-efficient lamps for around 13 hours. In other words, a simple setup attached to various cardio equipment in series may be sufficient to power the gym partially. Further, an economic analysis is conducted to estimate the energy saving resulting from the implementation of the energy harvesting arrangement in a college gym. It is found that with the help of such an arrangement, approximately 20% of the energy cost of the gym room can be saved.
Study of Printing Orientation on Mechanical Properties in Additive Manufacturing Process
Authors: Honarmandi Peyman , Xu Hongbin
Published: January 2020

Additive manufacturing (AM) is an innovative technology that creates parts by adding small portions of materials layer by layer, which frees designers to create parts that were not possible to manufacture with subtractive manufacturing processes previously. This led to wide-spread popularity of 3D-printing technology. In this technology. fused deposition modeling (FDM) is the most affordable one in the market now. Therefore, it is vital to understand how the print orientation, which can be customized very easily, affects the mechanical properties of the prints to maximize the strength of the product.

This paper aims to present the methodology and results of the experimental characterization of the acrylonitrile butadiene styrene (ABS) 3D-printed part. Tensile characterization of ABS was performed to analyze anisotropic nature of 3D-printed parts caused by its unique manufacturing process. Specimens were printed with six different configurations: four raster ([45/−45], [30/−60], [15/−75] and [0/90]) and three build orientations (0 or flat, 45, and 90 degrees with respect to the build plate, all printed in [45/−45] raster orientation). Dogbone tensile specimens were printed and pulled using the tensile test machine. The young’s modulus, yield strength, ultimate strength, strain at failure, breaking strength were found for each configuration.

As the build orientation angle increased and the raster orientation goes from [45/−45] to [0/90], mechanical properties decreased steadily except the Young’s modulus. For build orientation, Young’s modulus decreased first then increased as angle increased, and for the raster orientation, there was no statistically significant difference as raster changed from [45/−45] to [0/90]. Overall, [45/−45] flat configuration is the strongest and the most stable configuration.
The Effect of Crosswind Velocity on the Spray Drift of Flat Fan Nozzle
Authors: Raza S. , Sallam K. A. , Post S. L.
Published: January 2020

The objective of this research project is to eliminate the spray drift caused by crosswind. Spray drift is an important problem for the agricultural industry. Some herbicides (e.g. Dicamba) can cause serious damage if it drifts to nearby crops that are not genetically modified to withstand those herbicides. Our hypothesis is that the nozzle geometry and the injection angle can be actively/passively controlled to compensate for the crosswind velocity and effectively deliver the herbicides to the target area. The measurements include the breakup regime transitions, the droplet sizes, and the droplets trajectory as function of the wind speed and the injection angle. The current results show that the crosswind modifies the primary breakup mechanism from sheet breakup regime (i.e. thinning and fragmentation of the liquid sheet into ligaments) to bag breakup regime (i.e. the formation bags along the downstream side of liquid sheet) resulting in smaller drop sizes and an increased drift flux. Techniques to eliminate the bag breakup regime are presented.
On Multiple Inhomogeneities in Plane Elasticity
Authors: Honein Elie , Honein Tony , Najjar Michel , Rai Habib
Published: January 2020

In this paper we present some new analytical techniques which have been recently developed to solve for problems of circular elastic inhomogeneities in anti-plane and plane elasticity. The inhomogeneities may be composed of different materials and have different radii. The matrix may be subjected to arbitrary loadings or singularities. The solution to this heterogeneous problem is sought as a transformation performed on the solution of the corresponding homogeneous problem, i.e., the problem when all the inhomogeneities are removed and the homogeneous matrix is subjected to the same loading/singularities, a procedure which has been dubbed ‘heterogenization’. In previous works, a single inhomogeneity or hole has been considered and the transformation has been shown to be purely algebraic in the antiplane case and involves differentiation of the Kolosov-Mushkelishvili complex potentials in the plane case. Universal formulas, i.e., formulas which are independent of the loading/singularities, that express the stresses at the inter-face of the inhomogeneity in terms of the stresses that would have existed at the same interface had the inhomogeneity been absent, have been be derived. The solution for a single inhomogeneity bonded to a matrix which is subjected to arbitrary loading/singularities can then in principle be used systematically in a Schwarz alternating method to obtain the solution for multiple inhomogeneities to any degree of accuracy. However alternative and innovative methods have been sought which lead to a much faster convergence and in some cases to exact expressions in terms of infinite series. The aim of this paper is to present some of the progress that has been made in this direction.
Prediction of Transversal Flow in Non-Circular Tubes With a Higher Order Constitutive Equation
Authors: Letelier Mario F. , Siginer Dennis A. , Merino Paola , Stockle Juan S.
Published: January 2020

In this paper we explore the potential of an explicit constitutive equation in predicting secondary flows in straight, non–circular tubes in steady and fully developed flow. We show that secondary flows appear at first order in k a constitutive parameter in the new constitutive structure when solving the field through an asymptotic approach. The structure of the transversal stream–function predicted by the new structure is the same as that obtained at third order in Weissenberg number with the Modified Phan–Thien–Tanner constitutive equation aside from constitutive constants. We present predictions of the velocity field and a comparison with the corresponding predictions of the MPTT model. These results are obtained using the analytical algorithm based on the shape factor concept coupled with asymptotic expansions developed and used previously by the authors to solve related problems.
Energy Absorption Characteristics of a Nested Curved Column Reinforced Elastomer Composite
Authors: Van Valkenburgh Owen F. , Ekstrom Thomas C. , Goodman Erica M. , Leborte Cameryn C. , Haaland Kevin M. , Yasuda Nathan K. , Shih Frank J.
Published: January 2020

Advances in 3D printing technology and their increasing availability have allowed for design of novel structures. For designing material systems and structures that crumple to absorb energy from low-velocity impact events, the wide variability in material selection and geometry presents an attractive opportunity to optimize their performance. In the present study, 3D printed structures using high stiffness polymer were produced with a UV stereolithographic process. The structures utilized curved cylindrical columns of varying diameters, whose axial geometries were prescribed with a normal distribution equation, allowing for adjustments in the load absorption profile. The columns were arranged in a circular pattern, with four layers of reinforcements with a slight differential in heights to create cascading failure events. A polyurethane matrix keeps the structures together during impact. The systems, with varying rod geometry, rod curvature, and rod diameters were tested with both quasi-static compression testing and dynamic impact testing. The preliminary results are presented. Force-displacement curves were measured were to determine the optimal design which yields the best failure characteristics. Finite element analysis using ANSYS was used to model the failure characteristics and inform the design of the physical system.
A Passive Hybrid Model to Estimate the Elastic Performance of Left Ventricular Cardiac Fibres
Authors: Córdova Aquino Jacobo , Medellín-Castillo Hugo I.
Published: January 2020

The development of mathematical and numerical models of the human heart has become a matter of high relevance in the scientific community because of the difficulty of measuring the properties and performance of the cardiac tissue in vivo, and carrying out experimental tests under different healthy and pathological conditions. Several heart models have been proposed in the literature, but the results still differ from each other.

In this paper, a new passive heart model to estimate the elastic behaviour of the left ventricular (LV) cardiac fibres is presented. The model is based on a hybrid approach that combines a theoretical approach to determine the equivalent material properties of each layer of the LV tissue, which represents an advantage with respect to other more elaborated or complex models, and an inverse finite element method (FEM) to determine the volume of the LV internal cavity under loading conditions. The proposed model uses the LV pressure and volume measurements along a real cardiac cycle as loading and target conditions, respectively. The results are analysed in terms of the elastic properties of the cardiac fibres and compared with the results obtained from other more complex and elaborated models reported in the literature. From this analysis it is observed that the new proposed model is reliable and able to estimate the elastic behaviour of the cardiac tissue.
Controlling Out-of-Plane Shear Wave Propagation With Broadband Cloaking
Authors: Liu Mao , Zhu W. D.
Published: January 2020

A major challenge in designing a perfect invisibility cloak for elastic waves is that density and elasticity tensors need to be independent functions of its radius with a linear transformation medium. The traditional cloak for out-of-plane shear waves in membranes exhibits material properties with inhomogeneous and anisotropic shear moduli and densities, which yields a poor or even negative cloaking efficiency. This paper presents design of a cylindrical cloak for shear waves based on a nonlinear transformation. This excellent broadband nonlinear cloak only requires variation of its shear modulus, while the density in the cloak region remains unchanged. The nonlinear ray trajectory equation for out-of-plane shear waves is derived and a parameter to adjust the efficiency of the cylindrical cloak is introduced. Qualities of the nonlinear invisibility cloak are discussed by comparison with those of a cloak with the linear transformation. Numerical examples show that the nonlinear cloak is more effective for shielding out-of-plane shear waves from outside the cloak than the linear cloak and illustrate that the nonlinear cloak for shear waves remains highly efficient in a broad frequency range. The proposed nonlinear transformation in conjunction with ray trajectory equations can also be used to design nonlinear cloaks for other elastic waves.
Machine Learning Classification of Head Impact Sensor Data
Authors: Rooks Tyler F. , Dargie Andrea S. , Chancey Valeta Carol
Published: January 2020

A shortcoming of using environmental sensors for the surveillance of potentially concussive events is substantial uncertainty regarding whether the event was caused by head acceleration (“head impacts”) or sensor motion (with no head acceleration). The goal of the present study is to develop a machine learning model to classify environmental sensor data obtained in the field and evaluate the performance of the model against the performance of the proprietary classification algorithm used by the environmental sensor. Data were collected from Soldiers attending sparring sessions conducted under a U.S. Army Combatives School course. Data from one sparring session were used to train a decision tree classification algorithm to identify good and bad signals. Data from the remaining sparring sessions were kept as an external validation set. The performance of the proprietary algorithm used by the sensor was also compared to the trained algorithm performance. The trained decision tree was able to correctly classify 95% of events for internal cross-validation and 88% of events for the external validation set. Comparatively, the proprietary algorithm was only able to correctly classify 61% of the events. In general, the trained algorithm was better able to predict when a signal was good or bad compared to the proprietary algorithm. The present study shows it is possible to train a decision tree algorithm using environmental sensor data collected in the field.
Brain White Matter Model of Orthotropic Viscoelastic Properties in Frequency Domain
Authors: Wu Xuehai , Georgiadis John G. , Pelegri Assimina A.
Published: January 2020

Finite element analysis is used to study brain axonal injury and develop Brain White Matter (BWM) models while accounting for both the strain magnitude and the strain rate. These models are becoming more sophisticated and complicated due to the complex nature of the BMW composite structure with different material properties for each constituent phase. State-of-the-art studies, focus on employing techniques that combine information about the local axonal directionality in different areas of the brain with diagnostic tools such as Diffusion-Weighted Magnetic Resonance Imaging (Diffusion-MRI). The diffusion-MRI data offers localization and orientation information of axonal tracks which are analyzed in finite element models to simulate virtual loading scenarios.

Here, a BMW biphasic material model comprised of axons and neuroglia is considered. The model’s architectural anisotropy represented by a multitude of axonal orientations, that depend on specific brain regions, adds to its complexity. During this effort, we develop a finite element method to merge micro-scale Representative Volume Elements (RVEs) with orthotropic frequency domain viscoelasticity to an integrated macro-scale BWM finite element model, which incorporates local axonal orientation. Previous studies of this group focused on building RVEs that combined different volume fractions of axons and neuroglia and simulating their anisotropic viscoelastic properties. Via the proposed model, we can assign material properties and local architecture on each element based on the information from the orientation of the axonal traces. Consecutively, a BWM finite element model is derived with fully defined both material properties and material orientation. The frequency-domain dynamic response of the BMW model is analyzed to simulate larger scale diagnostic modalities such as MRI and MRE.