bluuebunny/crossref_metadata_2025 huggingface dataset:
Use of a Trilayer Shell Model to Determine Intrinsic Stress Within Titanium-Silicon Carbonitride Coating
Authors: Chakraborty Anurag , Thompson Forest , Ash Jason T. , Ahrenkiel Phil , Kustas Frank , Anderson Robert
Published: January 2019

Thin films of titanium-silicon carbonitride (TiSiCN) with titanium adhesion layers were deposited at approximately 280°C on horizontally and vertically-mounted strips of 301-stainless steel by reactive magnetron sputtering. Considerable differences in the mid-deflections and radii of curvature between the vertical and horizontal samples were observed. Cross-sectional characterizations done on a TEM revealed a columnar growth and uniform microstructure. A finite-element model of the tri-layer sandwich structure using Mesh-Tie constraints was developed to estimate the intrinsic stress levels in the overcoat as probable functions of substrate location and orientation. The computational model in the absence of intrinsic stress was validated by analytical expressions for multilayer films. The initial stress state parameter was varied in Abaqus until consistency in curvature-values was achieved with the physical measurement obtained from an optical setup specially-constructed for this purpose. The difference in the S11/S22 principal stresses provided the intrinsic stress estimate. The calculated values of intrinsic stress were then applied to an FEA test model with fixed constraints to computationally determine the stress reduction for individual samples.
Development of a Hybrid Heat and Mass Transfer Course
Authors: Mendez Julie
Published: January 2019

This work describes the development of a hybrid junior-level 4-credit-hour heat and mass transfer course. The lecture portion of the course was developed as approximately 80% online. The students and instructor met in person for the lecture portion of the course once every other week for 50 minutes, with the remaining activities completed online. The laboratory portion of the course remained in the traditional face-to-face format. Specifications grading was used to determine final course grades. This paper will describe the course structure, types of assignments, and use of face-to-face class time. Student performance in the hybrid course is compared to previous student performance in the same course taught in a face-to-face format. Student feedback and instructor observations are shared.
Preliminary Development of a Measurement Standard Using a Research Simplex Atomizer
Authors: Leask Scott B. , Li Alice K. , McDonell Vincent G. , Samuelsen Scott
Published: January 2019

Cold-flow spray researchers have an array of diagnostic tools to extract meaningful information on spray characteristics. The efficacy of many of these tools, however, depends heavily on calibration, alignment, and human operation. This can lead to large discrepancies in data values for seemingly identical setups between workers. The application of experimental data to numerical models is thereby hindered due to inconsistencies in results caused by experimental error. Previously, an attempt was made to produce a “standard spray” through the use of a research simplex atomizer (RSA). As manufacturing processes and diagnostic tools have improved, the research simplex atomizer is being revisited.

Here, a new research simplex atomizer has been investigated. Fundamental datasets captured from detailed test conditions are presented to provide benchmark data with the intention of other workers testing the reproducibility of the results. Preliminary findings between laboratories show good agreement in droplet size measurements.

Further, emphasis is placed on the sensitivity of laser diagnostics used and the effect their operation can incur. To satisfy the requirements of a measurement standard, it is paramount that all workers adhere to similar diagnostic configurations and detail their operating parameters.
Demonstration and Experimental Validation of Plastic-Encased Resonant Ultrasonic Piezoelectric Actuator for MRI-Guided Surgical Robots
Authors: Carvalho Paulo A. W. G. , Nycz Christopher J. , Gandomi Katie Y. , Fischer Gregory S.
Published: January 2019

Intra-operative medical imaging based on magnetic resonance imaging (MRI) coupled with robotic manipulation of surgical instruments enables precise feedback-driven procedures. Electrically powered non-ferromagnetic motors based on piezoelectric elements have shown to be well suited for MRI robots. However, even avoiding ferrous materials, the high metal content on commercially available motors still cause distortions to the magnetic fields. We construct semi-custom piezoelectric actuators wherein the quantity of conductive material is minimized and demonstrate that the distortion issues can be partly addressed through substituting several of these components for plastic equivalents, while maintaining motor functionality. Distortion was measured by assessing the RMS change in position of 49 centroid points in a 12.5mm square grid of a gelatin-filled phantom. The metal motor caused a distortion of up to 4.91mm versus 0.55mm for the plastic motor. An additional SNR drop between motor off and motor spinning of approximately 20% was not statistically different for metal versus plastic (p = 0.36).
Mechanism Interaction During Droplet Evaporation on Nanostructured Hydrophilic Surfaces
Authors: Carey Van P. , Wemp Claire K. , McClure Emma R. , Cabrera Samuel
Published: January 2019

Recent studies of droplet spreading on nanostructured surfaces have demonstrated that the fluid motion and wicking effects impact the morphology of the liquid on the nanostructured surface and the thermophysics of the vaporization process. In the investigation summarized here, models of the spreading mechanism, and mechanisms of heat transport to the interface of a spreading droplet are used to explore the interaction of these mechanisms during the droplet vaporization process on nanostructured hydrophilic surfaces. Exploration of the trends in the model predictions and their comparison with experimental data suggests that the wickability of such surfaces causes an impinging droplet to quickly spread to form a thin liquid film with a somewhat curved interface. This liquid film has a mean thickness in the range of 10–100 microns near the contact line at the outer perimeter of the droplet footprint. If the surface is highly superheated, bubble nucleation and a nucleate boiling mechanism may augment conduction across the liquid film to facilitate evaporation. However, physical arguments and data from droplet evaporation experiments suggest that nucleation in the interstitial spaces of the nanoporous layer may be suppressed as a result of the extremely small size of those spaces. The role of these different mechanisms and the stages of the vaporization process for impinging droplets is discussed in detail. This exploration indicates that the wickability effect on droplet spreading strongly enhances the droplet evaporation heat transfer.
Functional Design of a Robust Dynamic Position and Data Acquisition System
Authors: Meyers James C. , Emami Tooran
Published: January 2019

This paper presents a successful functional design for a Robust Dynamic Positioning System (RDPS) capstone project. This design is created by using block diagrams with the inputs and outputs for all levels in order to build and test a vessel platform. The design at level 0 is a Light Detection and Ranging (LIDAR) sensor to determine position of the vessel. Level 1 is the design of all hardware components. Level 2 shows the internal communications for each component. The results of building this platform with the real time test of the platform with the controllers is presented at level 3. An Adaptive and Segmented Proportional Integral Derivative (ASPID) controller has been designed to meet the design performances of this platform.
Ranking of Biomechanical Metrics to Describe Human Response to Impact-Induced Damage
Authors: DeVogel Nicholas , Banerjee Anjishnu , Pintar Frank A. , Yoganandan Narayan
Published: January 2019

Determination of human tolerance to impact-induced damage or injury is needed to assess and improve safety in military, automotive, and sport environments. Impact biomechanics experiments using post mortem human surrogates (PMHS) are routinely used to this objective. Risk curves representing the damage of the tested components of the PMHS are developed using the metrics gathered from the experimental process. To determine the metric that best explains the underlying response to the observed damage, statistical analysis is required of all the output response metrics (such as peak force to injury) along with the examination of potential covariates. This is conducted by parametric survival analysis. The objective of this study is to present a robust statistical methodology that can be effectively used to achieve these goals by choosing the best metric explaining injury and provide a ranking of the metrics. Previously published data from foot-ankle-lower leg experiments were used with two possible forms of censoring: right and left censoring or right and exact censoring, representing the no injury and injury data points in a different manner. The statistical process and scoring scheme were based on the predictive ability assessed by the Brier Score Metric (BSM) which was used to rank the metrics. Response metrics were force, time to peak, and rate. The analysis showed that BSM is effective in incorporating different covariates: age, posture, stature, device used to deliver the impact load, and the personal protective equipment (PPE), i.e., military boot. The BSM-based analysis indicated that the peak force was the highest ranked metric for the exact censoring scheme and the age was a significant covariate, and that peak force was also the highest ranked metric for the left censored scheme and the PPE covariate was statistically significant. IRCs are presented for the best metric.
Parametric Resonance of Electrostatically Actuated MEMS Cantilever Resonators: Homotopy Analysis Method Versus the Method of Multiple Scales
Authors: Caruntu Dumitru I. , Reyes Christopher
Published: January 2019

This paper investigates the parametric resonance of electrostatically actuated MicroElectroMechanicalSystems (MEMS) cantilever resonators. The electrostatic force is modeled to include fringe effect. The MEMS consists of a cantilever over a parallel ground plate and an AC voltage between them. The actuation frequency is near first natural frequency of the cantilever beam. This leads to parametric resonance. It is of interest to investigate the amplitude frequency response of MEMS cantilever resonators. This paper uses the Homotopy Analysis Method (HAM), which is able to capture nonlinear behaviors for higher amplitudes, large parameters, and strong nonlinearities. The base method used for comparison in this work is the method of multiple scales (MMS). MMS is a perturbation method. It requires a relatively short computational time for simulations. Although the CPU time is advantageous, MMS is only accurate for weak nonlinearities and low amplitudes. It is in the interest to compare how well HAM captures the softening behavior of this system as opposed to MMS. In this paper the influences of Casimir forces and Van der Waals effects are included. Electrostatic, Van der Waals and Casimir forces are nonlinear. HAM is a deformation technique that continuously deforms the initial guess, provided to the procedure, to the exact solution. In this work the first and second order deformation equations are constructed for the equation of motion governing the behavior of the MEMS cantilever beam. In the first order deformation, HAM deviates from the solution obtained by MMS. This deviation demonstrates the power of the method to capture the softening behavior more accurately than MMS even at the 1st order deformation HAM. In the second order deformation construction, the HAM’s solution softens more than the previous, demonstrating that higher order deformation approximations result in higher accuracy. In the second order deformation, HAM contains the convergence control parameter. This parameter is chosen via the c0 curve approach. Up to 2nd order HAM deformations are evaluated for this paper. These higher order homotopy deformation solutions were developed and automated symbolically in the software Mathematica and tested numerically using Matlab software.
Development of a Membraneless Organic Redox Flow Battery
Authors: Cook Korey , Lau Ethan , Thayer Jordan , Mann Shane , Guarr Tom , Benard Andre
Published: January 2019

The development of a novel electrochemical energy storage system, specifically a redox flow batteries (RFB), is discussed in this work. It has the distinction of not requiring an ion-selective membrane due to novel chemical compounds. The techno-economic aspects of a low-cost 3D printed flow cell and system design tailored for a novel chemistry is discussed. The organic compounds employed are inexpensive, have a long lifespan, and as mentioned enable the system to be membraneless. All these substantially decrease the capital and maintenance costs. Suitable systems were developed and tested using chemically compatible 3D printed materials for the flow cells. The estimated cost per kWh is lower than the Department of Energy’s target cost of $150/kWh for grid storage capacity. A commercial scale system, rated for a 1 MW, 5-hour discharge time, has an estimated cost of $65/kWh. The proposed technology could revolutionize the energy storage industry and help with the construction of a more stable and efficient energy grid.
Aerodynamics Analysis for Optimization the Design of a Baja SAE Chassis
Authors: Maradey Lázaro Jessica Gissella , Ardila Gómez Sergio Andrés , Esteban Villegas Helio Sneyder
Published: January 2019

The aerodynamic analysis of vehicles using Computational Fluid Dynamics (CFD) is a powerful tool that is used to explore and investigate how air flow behaves around the vehicle, gives a qualitative idea of aerodynamic behavior and provides engineers with the information necessary to design the pieces that will be tested in the wind tunnel. This technique allows to find the values of forces and moments to get an idea of the drag resistance and lift forces on the vehicle. It is also possible to determine the position of the center of pressure that exerts a vital importance in the definition of the directional stability of the vehicle in its lateral dynamics. On the other hand, it offers the advantage of being able to see many variables of the problem that are very difficult to access in reality, for example to see current lines, vortex shedding, fields of pressures around the vehicle. Although the use of CFD has become a common practice in the automotive industry in recent decades, it is still not considered as a single technique, since one of the limitations is related to the dynamics of a turbulent flow is quite complex so which analytical and computational study depends on what is called Turbulence Models.

This article aims to show the aerodynamic design process by CFD simulation of a Baja SAE vehicle chassis using Ansys software, widely used for simulation of static charges, thermodynamics, fluid mechanics, multiphysics systems and vibrations and to provide information that can be validated experimentally in the future.
A Study of Water Transport of Hollow Fiber Membranes Over Various Operating Conditions
Authors: Chae Jongmin , Yu Sangseok
Published: January 2019

A membrane humidifier is a device to provide water vapor into the proton exchange membrane fuel cell stack that is used for transportation application due to global warming. Since inadequate humidification severely affects the performance and durability of a fuel cell stack, it is necessary to equip the humidifier for delivery humidification into the fuel cell vehicle.

In this study, the performance of humidification in hollow fiber membrane is investigated. While the test section is exposed to external humidity condition, dry air is provided through hollow fiber membrane so that the water transport is facilitated. Since various parameters can change the performance, the performance investigation has to be carried out with parameters. In this study the water transport of hollow fiber membrane is investigated in terms of principle operating conditions such as temperature, pressure, and flow rate.
Evaluation of Optimal Designs for Hybrid Renewable Energy Systems Specific to Residential Communities in Saudi Arabia
Authors: Dehwah Ammar H. A. , Krarti Moncef
Published: January 2019

To meet the increasing energy demand and to shave the peak, the Kingdom of Saudi Arabia (KSA) is currently planning to invest more on renewable energy (RE) seeking diversity of energy resources. Through the integration of demand side management measures and renewable energy distributed generation (DG) systems, the study outlined in this paper aims at investigating the potential of hybrid renewable energy systems in supplying energy demands for residential communities in an oil-rich country. The residential community considered in this study, located in the eastern region of KSA, has an annual electrical usage of 1,174 GWh and an electrical peak load of 335 MW that are met solely by the grid. The results of the analyses indicated that the implementation of cost-effective energy efficiency measures (EEMs) reduced electricity usage by 38% and peak demand by 51% as well as CO2 emissions by 38%. While, the analysis of the hybrid systems showed that purchasing electricity from the grid is the best option with a levelized cost of energy (LCOE) of $0.1/kWh based on the current renewable energy market and economic conditions of KSA, RE systems can be cost-effective to meet the loads of the residential communities under specific electricity prices and capital cost levels. This study can assist KSA decision makers establish effective and targeted policies that can facilitate and promote renewable technologies.
On the Temporal Network Analysis With Link Prediction
Authors: Wu Bin , Suh C. Steve
Published: January 2019

Literature review shows that much effort has been given to model physical systems involving a large number of interacting constituents. As a network evolves its constituents (or nodes) and associated links would either increase or decrease or both. It is a challenge to extract the specifics that underlie the evolution of a network or indicate the addition and/or removal of links in time. Similarity-based algorithm, Maximum likelihood methods, and Probabilistic models are 3 mainstream methods for link prediction. Methods incorporating topological feature and node attribute are shown to be more effective than most strategies for link prediction. However, to improve prediction accuracy, an effective prediction strategy of practicality is still being sought that captures the characteristics fundamental to a complex system. Many link prediction algorithms have been developed that handle large networks of complexity. These algorithms usually assume that a network is static. They are also computationally inefficient. All these limitations inevitably lead to poor predictions. This paper addresses the link prediction problem by incorporating microscopic dynamics into the matrix factorization method to extract specific information from a time-evolving network with improved link prediction. Numerical experiments in applying static methods to temporal networks show that existing link prediction algorithms all demonstrate unsatisfactory performances in link prediction, thus suggesting that a new prediction algorithm viable for time-evolving networks is required.
Experimental Identification of Model Parameters and the Statistical Processing Using a Nonlinear Oscillator Applied to EEG Analysis
Authors: Uehara Kenyu , Saito Takashi
Published: January 2019

The nonlinear analysis may help to reveal the complex behavior of the Electroencephalogram (EEG) signal. In order to analyze the EEG in real time, we have proposed an EEG analysis model using a nonlinear oscillator with one degree of freedom and minimum required parameters. Our method identifies EEG model parameters experimentally. The purpose of this study is to examine the specific characteristic of model parameters. Validation of the method and investigation of characteristic of model parameters were conducted based on alpha frequency EEG data in both relax state and stress state. The results of the parameter identification with the time sliding window for 1 second show almost all of the identified parameters have a normal distribution spread around the average. The model outputs can closely match the complicated experimental EEG data. The results also showed that the existence of nonlinear term in the EEG analysis is crucial and the linearity parameter shows a certain tendency as the nonlinearity increases. Furthermore, the activities of EEG become linear on the mathematical model when suddenly change from the relax state to the stress state. The results indicate that our method may provide useful information in various field including the quantification of human mental or psychological state, diagnosis of brain disease such as epilepsy and design of brain machine interface.
Optimization of Heat Transfer Process in a Walking Beam Reheat Furnace Using Computational Fluid Dynamics
Authors: Chen Yuchao , Silaen Armin K. , Walla Nicholas , Johnson Kurt , Zhou Chenn Q.
Published: January 2019

In the steelmaking process, reheating furnaces are used to reheat steel slabs to a target rolling temperature. The bottom intermediate zone inside the reheating furnace plays a decisive role in controlling the slab temperature distribution before slabs enter the soaking zone. Efforts to maintain a uniform slab surface temperature and thus enhance product quality require a good understanding of the furnace’s operation. However, traditional physical experiments are costly and have high risks as well. In this study, a three-dimensional steady-state computational fluid dynamics (CFD) model was developed to investigate the flow field in the bottom intermediate zone of a full-scale reheating furnace. The commercial software ANSYS Fluent® was used to solve the transport equations to predict the flame length, heat transfer, and gas temperature near the slab. Total input mass flow rate, preheated air temperature, and air/fuel ratio were selected to investigate the comprehensive influence of the furnace’s performance, which can be evaluated from the flame length, flame angle, and average gas temperature near the slab. Importantly, an orthogonal experimental design was conducted to optimize the evaluation factors by considering the multi influencing factors simultaneously. The simulation results indicate that a higher mass flow rate produces a lower upwards flame angle, which can prevent the hot spot detected on the slab surface. A higher preheated air temperature leads to a higher average gas temperature in this furnace; meanwhile, the flame becomes shorter by enhancing the air-fuel ratio.
A Novel Modeling Approach for Solving the Cell Formation Problem
Authors: Dmytryshyn Taras , Ismail Mohamed , Rashwan Ola
Published: January 2019

This paper presents a new modeling approach called Progressive Modeling (PM) and demonstrates it by solving the Cell Formation Problem (CFP). In this paper, the Progressive Modeling (PM), a component-based optimization technique, is used to solve the cell formation problem (CFP). This novel solution algorithm is utilized to find optimal or near-optimal solutions. A user-friendly Windows application is presented to capture the problem data, demonstrate the solution process, and display the results. A benchmark problem in the literature is solved and presented in this paper. The paper concludes by demonstrating the efficiency of the new modeling approach and its future extension.
Reliability-Based Optimal Design of a Micro-Grid System Under Natural Disasters
Authors: Chen Zhetao , Xi Zhimin
Published: January 2019

This paper proposes reliability-based optimal design of a micro-grid system under service disruptions due to natural disasters. The objective is to determine the minimum number of generators and their distributions in the micro-grid so that the system’s recoverability (or resilience) and operation efficiency can be guaranteed under random failure scenarios of the power transmission lines. Power flow analysis combing with the Monte Carlo simulation (MCS) are used for uncertainty propagation analysis to quantify the system’s recoverability distribution and the transmission efficiency distribution under random failure scenarios of the transmission lines. The optimal allocation of the generators is much more reliable compared to the deterministic solutions without considering various uncertainties in the system. The proposed work is demonstrated through a 12-bus power system.
Continuous Cell Sorting by Dielectrophoresis in a Straight Microfluidic Channel
Authors: Qiang Yuhao , Liu Jia , Dieujuste Darryl , Ramsamooj Katrina , Du Sarah E.
Published: January 2019

Dielectrophoresis (DEP) has been demonstrated as an effective mechanism for cell sorting in microfluidic settings. Many existing methods utilize sophisticated microfluidic designs that require complicated fabrication process and operations. In this paper, we present a microfluidics-based cell sorter that is capable of sorting microparticles continuously in a simple straight channel, thus facilitating easier fabrication and operation. An array of indium-tin oxide (ITO) electrodes are embedded on the bottom surface of the straight channel to generate a DEP force field. This force results in deviation of the particles with different dielectric properties from their paths that are hydrodynamically focused in the channel. Particle trajectories are predicted by numerical simulation at different flow rates and field strengths using COMSOL. Separation of red blood cells from polystyrene beads is demonstrated and numerical prediction is validated experimentally. High separation efficiency for the two particle types is confirmed by counting the concentrations of particles collected at the respective collection outlet.
Monitoring, Risk Assessment and Actuation for Alzheimer Patients: A Case Study
Authors: Luís-Ferreira Fernando , Gião João , Corista Pedro , Calado Jorge , Sarraipa Joao
Published: January 2019

Alzheimer is one of the most frequent types of dementia. With the increasing extension of life expectancy, and an increasing incidence above sixty-five years. Near to thirteen million cases are foreseen in 2050 with an estimate cost above two hundred billion dollars in associated care expenses. It becomes important to take measures to ensure quality of life to patients, carers and promote the sustainability of public and personal finances. The major concerns with those patients are memory faults with the tendency for wandering and get lost. The present work proposes a solution for permanent monitoring, risk assessment and reaction, when needed, while extending battery autonomy for the worn device. Data is periodically uploaded to be processed and analysed in a remote infrastructure such as FIWARE. The aim is to establish profiles that better adapt to each citizen of the evergrowing community of dementia patients, including those with Alzheimer disease.
OBACIS Analytics: The Catalogs
Authors: Ismail Mohamed
Published: January 2019

OBACIS is an integrated framework being developed to accelerate the accreditation reporting work-flow, cut down the reporting cost by an order of magnitude, and close the data-driven continuous improvement loop. This paper focuses on creating a centralized database for compiling accreditation data required for accreditation reporting from various resources such as previous visit accreditation reports, academic calendars, course schedules, and a handful of other resources are used to create what we call the Catalogs. Despite the fact that the Catalogs framework has been developed to meet the reporting standards of Canadian Engineering and Accreditation Board (CEAB), The system can be easily adapted to meet other standards such as ABET and EUR-ACE. The Catalogs are supposed to save a sheer amount of time needed for accreditation reporting and should act as an instrumental tool for accelerating accreditation data collection, creating insightful analyses, and identifying gaps for continuous improvement initiatives at both program and faculty levels.
Experimental Study on Machining of Hybrid Composite Stacks Using Submerged Abrasive Waterjet Machining Process
Authors: Narkhede Mayur , James Sagil
Published: January 2019

The research involves experimental study on precision machining of hybrid composite stacks using Submerged Abrasive Waterjet Machining (SAWJM) process. In this study, an in-house fabricated SAWJM setup is used to machine a stack of Carbon Fiber Reinforced Polymer (CFRP) and Titanium. The effect of critical parameters including stand-off distance and abrasive grain size on the size of the cavity machined during SAWJM and Abrasive Waterjet Machining (AWJM) processes are studied. The study found that SAWJM process is capable of successfully machining CFRP/Titanium composites with high precision. The machined surface is free of thermal stresses and did not show any delamination or cracking around the edges. The study suggested that the stand-off distance and abrasive grain size has significant influence on the machining process. The cavities machined on both CFRP and titanium during SAWJM process are smaller and more circular than that produced during AWJM process. The results of this study provide deeper insight into precision machining of hybrid composite stacks.
Optimization Methods for Controlling Stresses at Contacting Surfaces of Interference Fit Assemblies Under Axial and Torsional Loads
Authors: Florio C. S.
Published: January 2019

While the nonuniformity of the diameter of a shaft can be optimized to reduce damaging stress concentrations at the ends of the contact region that are typically found in interference fits between uniform diameter shafts and hubs, the resulting shape changes may adversely affect the joint strength. A more robust design may be achieved if the surface profile is optimized under both interference fit and functional loads. A novel gradientless structural shape optimization method is applied in this work with a unique multiobjective formulation that includes the contact interactions and their effects on the shaft. The method incorporates surface-averaged based optimization goals, which consider both local and global variations, so that the optimization of the entire contacting region can be readily achieved. The formulation has no system-dependent parameters, weighting factors, or stopping criterion, allowing for its broad application to design and compare systems of varying geometries, loads, and meshes. The method was used to attain design goals specific to contacting interfaces subjected to interference, axial, and torsional loads, achieving a 50% improvement in the stress state uniformity over the entire contract region in all cases. Through the presented method, the relative influence of each optimization goal on the resulting shape is demonstrated.
Dynamic Analysis for Motor-Powered Periotomes in Dentistry
Authors: Lin Jianping , Sharma Om A. , Park Wooram
Published: January 2019

A periotome is a hand-held manual instrument that dentists use during tooth extraction. Using the sharp blade at the tool tip, dentists cut the periodontal ligaments that bonds the alveolar bone and the cementum surrounding the roots of teeth. Since this procedure usually requires dentists to repeatedly apply a certain level of force on the hand-held tool during the long-time procedure, it leads to dentists’ fatigue on their hands, inaccurate hand motion, and patients’ discomfort. Motorized periotomes can significantly improve the tooth extraction procedure by decreasing the force required from a dentist and reducing the procedure time. In this paper, we consider simple designs for motor-powered periotomes focusing on dynamic behaviors. Since the motor inside the tool creates motion and the hand-held tool moves as a result of dynamic response, the analysis requires detailed consideration of many factors such as tool mass, hand stiffness and damping. The motion of the tool tip should be monitored in this analysis to maximize the cutting performance. The analysis results will be used for choosing design options and parameters. This approach will be demonstrated using dynamic modeling and computer simulations.
Curricular Structure for a Mechanical Engineering Undergrad Program Based on Human Capabilities and Professional Competences
Authors: Flórez Diego A.
Published: January 2019

This paper addresses the curriculum change in the mechanical engineering (ME) undergraduate program at the Universidad Pontificia Bolivariana (UPB), located in Medellin, Colombia. The curriculum model of the UPB is based on develop of Human Capabilities and Professional Competences, through of learning and the achievement of outcome-related course learning objectives during the education process. The faculty of the ME department developed the Human Capabilities and Outcomes Map. This map shows the connection between general human capabilities that are strengthen through the ME program, the competences that are to be achieved, and the courses where the outcomes are developed in the curriculum. The courses organized in four technical areas: Design and Control, Materials and Manufacturing Processes, Energy and Thermofluids, and Management. The curricular design includes too the incorporation of four courses with integrator character. These courses are called Modules of Applied Engineering. In them, the student develops projects of engineering of low complexity; These projects involve the integration of topical courses in technical areas and the intentional development of human capacities and transversal competences. The faculty will assess the performance within a two-year period in order to quantify the impact of the curricular proposed.
Micro-Mechanical Modeling of the Stress Softening in Double-Network Hydrogels
Authors: Morovati Vahid , Dargazany Roozbeh
Published: January 2019

While single network hydrogels show limited extensibility and low strength, double-network hydrogels benefit from significantly high stretchability and toughness due to their reinforcing mechanism of combining two soft and rigid networks. Here, a micro-mechanical model is developed to characterize the constitutive behavior of DN hydrogels in quasi-static large deformation. In particular, we focused on describing the permanent damage in DN gels under large deformations. Irreversible chain detachment and decomposition of the first network are explored as the underlying reasons for the nonlinear inelastic phenomenon. The proposed model enables us to describe the damage and the way it influences the micro-structure of the gel. The model is validated with uni-axial loading and unloading experiments of DN gels. The proposed model contains a few numbers of material constants and shows a good agreement with cyclic uni-axial test data.
Statistical Volume Elements for the Characterization of Angle-Dependent Fracture Strengths
Authors: Garrard Justin M. , Abedi Reza , Clarke Philip L.
Published: January 2019

The fracture response of rock, a quasi-brittle material, is very sensitive to its microstructural defects. Herein, we use statistical volume elements (SVEs) to characterize rock fracture strength at the mesoscale, based on the distribution of microcracks at the microscale. The use of SVEs ensures that the material randomness is maintained upon “averaging” of microscale features. Certain fracture strengths, such as uniaxial tensile strength, uniaxial hydrostatic strength, shear strength, and uniaxial compressive strength, are obtained and characterized for different angles of loading. Thus, a material with anisotropic fracture strength can be characterized. Statistics of the characterized strengths are analyzed, as well as their auto- and cross-correlation functions of these random fields to shed light on the length scales, relative to the volume element size, at which homogenized properties vary. While crack interaction is not included, the analysis provides insight on the distribution and correlation of different strengths. Finally, the asynchronous spacetime discontinuous Galerkin method is used for macroscopic fracture analyses of two rock domains homogenized by SVEs.
Effect of Inter-Connector on Thermo-Hydraulic Characteristics of Parallel and Counter Flow Mini-Channel Heat Sink
Authors: Tikadar Amitav , Oudah Saad K. , Salman Azzam S. , Morshed A. K. M. M. , Paul Titan C. , Khan Jamil A.
Published: January 2019

A numerical investigation of three-dimensional conjugate heat transfer was performed to quantify the thermal and hydraulic performance of an inter-connected parallel and counter flow mini-channel heat sink under laminar flow condition and within the single-phase regime. The aspect ratio (height/width) and the hydraulic diameter of the mini-channel were 0.33 and 750μm respectively. Three different widths of the inter-connector were selected to analyze the effect of cross flow for Reynolds number ranging from 150 to 1044, at a constant heat flux (20 W/cm2). To understand the fluid flow and heat transfer mechanism inside the inter-connector and their effects on overall thermal performance of the heat sink, Nusselt number (Nu), friction factor, pumping power, and overall thermal resistance were analyzed. Results show that the inter-connector has significantly higher effect on counter flow mini-channel heat sink than parallel flow mini-channel heat sink.
Indent Depth in the Clay Backing for Ceramic Armor
Authors: Zhang Timothy G. , Satapathy Sikhanda S.
Published: January 2019

Numerical models were conducted to study the load/momentum/energy transfer to the clay and the clay response when it was used as backing behind hard and soft armor during ballistic experiments. Tie-break contacts were used to explicitly model the delamination in the composite panels. Yarn level models accounting for woven structures were used to model the soft armor. A rate-dependent material model with different responses under compression and tension, developed previously from impact tests, was used to model the clay. The clay indent depth was correlated to the momentum and kinetic energy transferred to the clay for with and without soft armor between the hard armor and clay backing.
Comparison of Interfacial and Continuum Models for Dynamic Fragmentation Analysis
Authors: Bahmani Bahador , Clarke Philip , Abedi Reza
Published: January 2019

The microstructural design has an essential effect on the fracture response of brittle materials. We present a stochastic bulk damage formulation to model dynamic brittle fracture. This model is compared with a similar interfacial model for homogeneous and heterogeneous materials. The damage models are rate-dependent, and the corresponding damage evolution includes delay effects. The delay effect provides mesh objectivity with much less computational efforts. A stochastic field is defined for material cohesion and fracture strength to involve microstructure effects in the proposed formulations. The statistical fields are constructed through the Karhunen-Loeve (KL) method. An advanced asynchronous Spacetime Discontinuous Galerkin (aSDG) method is used to discretize the final system of coupled equations. Application of the presented formulation is shown through dynamic fracture simulation of rock under a uniaxial compressive load. The final results show that a stochastic bulk damage model produces more realistic results in comparison with a homogenizes model.
Measuring Points Selection for Laser Tracker Measurement of Five-Axis Machine Tool
Authors: Li Qingzhao , Wang Wei , Li Hai , Zhang Jing , Jiang Zhong
Published: January 2019

Due to the advantages of high efficiency, good flexibility and large measurement scale, the laser tracker measurement method is widely used in the error measurement of the machine tool. For the laser tracker measurement, the selection of the measuring points in the workspace has a significant influence on the identification effect of the errors. In this paper, the method to select the optimal measuring points is proposed. By construction of the suitable error vector and its corresponding error transformation matrix, the optimization criterion in robotic area is adopted to evaluate the identification effect of the measuring points. Based on the optimization criterion, the scheme of the measuring points selection can be established. The method proposed is validated by a case study. The method can help increase both the measurement efficiency and the error identification effect.
Neck Loading Model of a Child in a Car Seat
Authors: Bohn Gregory , Valerio Veronica , Hall Caitlin , Coronado Kathia , Saboori Parisa
Published: January 2019

It has been shown that children are susceptible to many dangers in child safety seats that do not involve a car accident. One issue involves the hyperextension of the neck muscles when the child falls asleep in a slumped position. Another issue is positional asphyxia, which is a form of asphyxia where the child’s position prevents them from breathing adequately.

The present study designed a realistic model of the cervical spine and conducted a finite element analysis to observe if and where stress and strain concentrations existed. This analysis simulated the effects of a moving vehicle on the child while their head was slumped forward.

A car seat redesign was also undertaken to overcome the afore mentioned issues. This involved employing a motor and control system.
Neural Network Modeling of Maximum Insertion Force of Bevel-Tip Surgical Needle
Authors: Gidde Sai Teja Reddy , Verissimo Tololupe , Chen Nuo , Hutapea Parsaoran , Loh Byoung-gook
Published: January 2019

Recently there has been a growing interest to develop innovative surgical needles for percutaneous interventional procedures. Needles are commonly used to reach target locations inside of the body for various medical interventions. The effectiveness of these procedures depends on the accuracy with which the needle tips reach the targets, such as a biopsy procedure to assess cancerous cells and tumors. One of the major issues in needle steering is the force during insertion, also known as the insertion (penetration) force. The insertion force causes tissue damage as well as tissue deformation. It has been well studied that tissue deformation causes the needle to deviate from its target thus causing an ineffective procedure. Simulation of surgical procedures provides an effective method for a robot-assisted surgery for pre- and intra-operative planning. Accurate modeling of the mechanical behavior on the interface of surgical needles and organs, specifically the insertion force, has been well recognized as a major challenge. Overcoming such obstacle by development of robust numerical models will enable realistic force feedback to the user during surgical simulation. This study investigates feasibility of predicting the insertion force of bevel-tip needles based on experimental data using neural network modeling. Simulation of the proposed neural network model is performed using Kera’s Python Deep Learning Library with TensorFlow as a backend. The insertion forces of needles with different bevel-tip angles in gel tissue phantom are measured using a specially designed automated needle insertion test setup. Input-output datasets are generated where the inputs are defined as bevel-tip angles and gel tissue phantom stiffness, and the output is defined as the insertion force. A properly trained neural network then maps the input data to the output data and the input-output dataset is supplied to train a neural network. Its performance is then evaluated using different and unseen input-output dataset. This paper shows that the proposed neural network model accurately predicts the insertion force.
Modeling Three-Dimensional Complex Flow-Fields of Proton Exchange Membrane Fuel Cells With Large Gas Density Change in Cathode
Authors: Kim Jinyong , Wang Chao-Yang
Published: January 2019

Three-dimensional (3D) complex flow-fields of proton exchange membrane (PEM) fuel cells have attracted much attention owing to their excellent liquid water management and mass transport. However, due to their complex flow structure, PEMFCs with 3D complex flow-fields suffer from large pressure drops (> 0.1 bar) and hence large density variations along the flow direction, especially at high current density operations. In this work, the effect of gas density variation due to the frictional pressure loss is considered in the current three-dimensional computational model using the multi-phase mixture (M2) formulation, in order to elucidate the effect of frictional loss on cell performance. The current work shows that the gas density drop in flow-fields can be significant at high current densities (20% at 3.0 A cm−2 and 30% at 4.0 A cm−2) and causes gas flow expansion, resulting in better liquid water management in flow-fields and gas diffusion layers (GDL) due to the gradually increasing gaseous viscous force along the flow direction. However, it is also pointed out that the gas density drop in cathode flow-fields results in cell performance loss due to lower oxygen concentrations (15mV voltage loss at 0.5 bar pressure drop, 60mV voltage loss at 0.78 bar pressure drop).
Student Learning Projects in Sustainable Energy: Solar-Powered Algae Culture, Photovoltaics, and CO2 Capture
Authors: Mauk Michael G. , Ruiz Carlos , Chiou Richard Y. , Espaillat Jean , Wang Senyu , Garcia Ainhoa , Surrette Robert
Published: January 2019

A systems approach combining algae aquaculture for biofuels, photovoltaic solar electric generation, and a subsystem for atmospheric CO2 capture as a carbon source for the algae, is developed as a platform and testbed for student engineering design projects. This work serves as a hands-on learning design project for engineering undergraduates in renewable energy, industrial microbiology, and sustainable and ‘green’ technology. Fully-instrumented and automated tabletop systems for circulating algae cultures in plastic fluidic channels integrated with silicon solar cells are designed, prototyped and tested with the aim of optimizing the yields and solar energy utilization.