bluuebunny/crossref_metadata_2025_split huggingface dataset:
Using d15 Piezoelectric Transducers for Ultrasonic Inspection of Delamination in Laminated Structures
Authors: Altammar Hussain , Salowitz Nathan 
Published: January 2022

Abstract
A laminated beam consisted of internally embedded d15 piezoelectric transducers in a pitch-catch configuration was fabricated with artificial delamination created at the interface of aluminum layers. The severity of damage was also varied to evaluate the effectiveness of the approach to detect delamination. A five-peak tone burst signal centered at 30 kHz was supplied to piezoelectric actuators throughout the experiment to produce antisymmetric waves in the laminate specimen. It was found that the closer the delamination occurred to the d15 PZT actuator the greater the change in signal increasing the probability to be identified using antisymmetric A0 wave mode. The analysis suggests that d15 PZT actuators should be placed in regions where delamination is likely to occur in laminated structures. Also, the propagation path of delamination was successfully predicted using a set of sensor signals processed using damage index methods including Pearson correlation coefficient and root mean square deviation. Evaluation of the results indicated that embedded d15 piezoelectric transducers exclusively couple to antisymmetric guided waves and can advance signal analysis for detection of delamination with ultrasonic structural health monitoring systems.
Experimental and Numerical Investigation of Phase Change Material Melting at Suboptimal Inclines
Authors: Troxler Casey J. , Freeman Thomas B. , Rodriguez Rafael M. , Boetcher Sandra K. S. 
Published: January 2022

Abstract
Phase change materials (PCMs) are a key component to thermal energy storage solutions, which have the potential to hold a critical role in future energy storage. PCMs take advantage of large latent heat capacities as a method for storing thermal energy for later use. The research presented in this paper is part of an ongoing effort to document the melt behavior of lauric acid in an insulated rectangular container. This paper presents new experimental data of melting occurring at 180° and 135° incline. The data is processed to show the melt interface development and the melt fraction over the duration of the experiment. The results of the 135° incline experiment are compared to a numerical model and differences in results are examined.
Experimental Investigation on the Effects of Direct Fuel Injection Into Low-O2 Recompression Interval of an HCCI Engine
Authors: Sok Ratnak , Kusaka Jin 
Published: January 2022

Abstract
Gasoline direct injection (GDI) and negative valve overlap (NVO) are standard strategies to control combustion characteristics and exhaust gas emissions in homogenous charge compression ignition (HCCI) engines. In this work, experimental data from a single-cylinder engine operated under the GDI-HCCI mode were analyzed. The experiments were performed at an equivalence ratio of 0.95 under a mid-load condition. A side-mounted injector delivered primary reference fuel with octane number 90 directly into the combustion chamber during the NVO. The measured results showed advanced combustion phase CA50 under the early start of injection (SOI) timings. Peak recompression pressures were lower than the motoring, emphasizing that the NVO reactions were net endothermic. Zero-dimensional kinetics calculations showed that classical reformate species increase almost linearly as a function of SOI timings.
This work also presents the effects of intake boosting pressure and single versus double pulses injections on CA50, burn duration CA10-90, peak cylinder pressure, combustion noise metrics, thermal efficiency, and emissions. The combustion noise metrics were over the engine constraint limit under advanced SOI timings, but a double-pulse injection could reduce the combustion noise metrics and NOx emission. Late fuel injection in the intake stroke could reduce NOx to a single digit.
Effects of Laser Parameters on Printing Quality of Injection Mold Cores
Authors: Yang Can , Yang Bao-Hua , Li Chun-Bo , Deng Liang , Yang Ren-Xiu 
Published: January 2022

Abstract
The present work aimed at investigating the feasibility of product mass customization according to consumers’ needs, making full use of advantages of both the selective laser melting (SLM) and injection molding. For this purpose, a new type of cylindrical injection mold core with a diameter of 30 mm was designed. In this core, ear structures for assembly purpose were designed with different inclined angles (i.e., 45, 60 and 75°). As the first stage of the goal, in this paper all ear structures were 3D printed separately using the SLM machine (SLM Solution 125), and the printed angle accuracy and surface quality of the inclined surfaces were evaluated. It’s found that the angle accuracy of the 3D printed inclined surface is directly proportional to the designed angle of the ear structures. Meanwhile, the fringe laser re-melting strategy gave the smoothest surface of the printed components. For example, the roughness values for the top and inclined surfaces are 8.831 and 7.212 μm, respectively. As fully integrating the individualization of SLM and the batch production capacity of injection molding, this work will provide theoretical and experimental data support for the mass customization.
Design of an Efficient, Low-Cost, Stationary LiDAR System for Roadway Condition Monitoring
Authors: Bennett Jarod , Saladin Mather , Sizoo Daniel , Stewart Spencer , Wood Graham , DeAgostino Thomas , Depcik Christopher 
Published: January 2022

Abstract
Light Imaging Detection and Ranging (LiDAR) systems generate point cloud imagery by using laser light to measure distance to a surface and then combine numerous points to create a three-dimensional (3-D) image. Since early adaptations, LiDAR is now common in aerial and subterranean geographical surveying and autonomous vehicle operations. The transportation industry uses LiDAR to monitor roadway quality, which can allow hazardous roadway corrosion to be spotted and repaired before endangering drivers. However, a leading issue with LiDAR availability is the respectively high price point for effective systems, therefore preventing widespread usage.
Previous work at fabrication of a low-cost LiDAR system generated high resolution 3-D imagery but was faulted by limited portability and a long run-time while also finding issues with gimbal translation and C++ programming. This effort improves the prior work by combining a touchscreen Graphical User Interface (GUI) with a rangefinder (Garmin LiDAR-Lite v3HP) powered by Raspberry Pi 4 Model B hardware. The rangefinder is housed in a 3-D printed gimbal mount that translates via two stepper motors and driver board. The system runs via a Python script that allows the user to select varying levels of resolution on the GUI prior to data collection onto a Secure Digital card or a file accessible through an internet connection. Like the previous work, data output is in Cartesian coordinates through a .xyz file format with a MATLAB script used to create a point cloud and two-dimensional image with a depth gradient. Overall, a more efficient, easier to use, and accurate LiDAR system was created that offers various resolution levels for under the cost of $500.
Parametric Evaluation of Head Center of Gravity Acceleration Error From Rigid Body Kinematics Assumptions Used in Environmental Sensors
Authors: Brown Brandon A. , Daniel Ray W. , Chancey Valeta Carol , Rooks Tyler F. 
Published: January 2022

Abstract
Environmental sensors (ES) are a proposed way to identify potentially concussive events using Rigid Body Kinematics (RBK) to get motion at the head CG. This study systematically investigated the extent that errors in RBK assumptions including sensor orientation (SO), head CG position (HCGP), and exposure severity contribute to errors in sensor readings of predicted peak resultant linear acceleration (PRLA) at the head CG. Simulated sensor readings were defined by idealized representations of head motion [extension, lateral bending and axial rotation] using a half sine pulse for linear and angular acceleration. Peak magnitudes of linear acceleration ranged from 12.5 to 100 Gs and peak magnitudes of angular acceleration ranged from 1250 to 10000 rad/s/s. Durations of linear and angular accelerations ranged between 5 and 30 ms. Simulated HCGP variations ranged from −10% to 10% radius of the head (assumed to be a sphere) in each direction and SO variations ranged from −20 to 20 degrees about each axis. True head CG response was calculated using zero error for SO and HCGP. Mean (+/− standard deviation) of calculated errors for maximum percent error (MaxPE) of a given head exposure was 30.3% (+/−9.71). 50% and 38% of all simulated exposures had MaxPE associated with maximum SO and HCGP offset, respectively. MaxPE was likely due to user error, ES form factor, and anthropometric variation.
Approach for Modelling the Dynamic Transmission Behavior of Grinding Discs Using Transfer Functions
Authors: Dörr Matthias , Dürkopp Alexander , Zimprich Sebastian , Gwosch Thomas , Gittel Hans-Jürgen , Pelshenke Christian , Dültgen Peter , Matthiesen Sven 
Published: January 2022

Abstract
Knowledge of the forces acting on the drive train of a machine is important for testing and Design for Reliability. In the case of angle grinders, these forces arise primarily at the contact between the workpiece and the grinding disc. Previous state-of-the-art approaches can determine the dynamic tool forces. Thereby it remains unclear whether the dynamic tool forces also correspond to the dynamic forces on the drive train since the dynamic force transmission via a grinding disc is not taken into account. Therefore, this article shows an approach to how the transmission behavior of a tool can be modeled by transfer functions to calculate the load on the drive train from the tool forces. It is shown that transfer functions for constant operating points can be generated by a test rig in three force directions and that these transfer functions can be merged for different grinding discs. It is also shown that the load of the drive train differs from the load from the tool forces. This means that the transmission behavior of tools such as grinding discs must be taken into account when testing and Design for Reliability. With the chosen approach, a solution is shown how the load on a drive train can be determined via transfer functions of a grinding disc from tool forces.
Pulse Wave Velocity and Transmission at the Carotid Artery and the Ascending Aorta
Authors: Smith Sara M. , Marin Justine , Adams Amari , West Keith , Hao Zhili 
Published: January 2022

Abstract
With consideration of a full set of mechanical properties: elasticity, viscosity, and axial and circumferential initial tensions, and radial and axial motion of the arterial wall, this paper presents a theoretical study of pulse wave propagation in arteries and evaluates pulse wave velocity and transmission at the carotid artery (CA) and the ascending aorta (AA). The arterial wall is treated as an initially-tensioned, isotropic, thin-walled membrane, and the flowing blood in the artery is treated as an incompressible Newtonian fluid. Pulse wave propagation in arteries is formulated as a combination of the governing equations of radial and axial motion of the arterial wall, the governing equations of flowing blood in the artery, and the interface conditions that relate the arterial wall variables to the flowing blood variables. We conduct a free wave propagation analysis of the problem and derive a frequency equation. The solution to the frequency equation indicates two waves: Young wave and Lamb wave, propagating in the arterial tree. With the related values at the CA and the AA, we evaluate the influence of arterial wall properties on their wave velocity and transmission, and find the opposite effects of axial and circumferential initial tensions on transmission of both waves. Physiological implications of such influence are discussed.
Aerodynamic Analysis of Flat Plates as Lift Generating Devices for Micro Aerial Vehicles
Authors: Borah Bastav , Kulkarni Vinayak , Saha Ujjwal K. 
Published: January 2022

Abstract
With the advent of Micro Aerial Vehicles (MAVs) and their widespread applications, the use of flat plate as a lift generation device has drawn utmost attention, and therefore, it needs to be investigated further. Usually, fixed wing MAVs work in the range of Reynolds number, Re = 104–105, and it is reported that a flat plate shows a better lift-to-drag ratio in this range of Re as compared to conventional airfoils. This investigation aims to understand the aerodynamic characteristics of a flat plate at low Re and its applicability on fixed wing MAVs. In this regard, a two-dimensional computational study using the Spalart-Allmaras turbulence model is conducted to observe the flow around a flat plate for Re of 4.8 × 104 and 7.6 × 104. Two flat plates having thickness ratios of 1% and 3% are considered in the present study. In each case, the trailing edge vortices are studied and the corresponding Strouhal number is calculated. The general observation is that the Strouhal number decreases with the increase of angle of attack. The flat plate with 1% thickness ratio shows a better lift-to-drag ratio than the flat plate with 3% thickness ratio. The pressure distribution along the flat plate has also been plotted and compared to that of a conventional low Re airfoil, S5010. For the Re under investigation, the difference in pressure between the suction and pressure sides is found to be higher for the flat plate at higher AoAs.
Communications and Learning for DevOps (CALDO): A Framework for Leveraging Automation for Human Performance Support and Training Systems
Authors: LeBlanc E. J. 
Published: January 2022

Abstract
The Industry 4.0 paradigm and digital transformation, with the powers of automation and machine learning, are fundamentally changing what it means to manufacture goods and services. Across the globe, manufacturers and their work forces are scrambling to keep up. The Communications and Learning for DevOps (CALDO) framework strives to empower communications and learning professionals to thrive in DevOpsoriented environments by making the paradigm leaps necessary to embrace the opportunities Industry 4.0 provides. The purpose of this paper is to convey to human communications and learning professionals the principles of DevOps, define the broad array of communications and learning professionals working in manufacturing today, and describe the process of implementing the CALDO framework.
A Viscoelastic Tuned Mass Damper for Vibration Treatment of Large Structures
Authors: Al-Rumaih Wail S. , Kashani Ahmad R. 
Published: January 2022

Abstract
Viscoelastic (VE) tuned mass dampers (TMDs) using commercially available, small thickness, VE material have been used extensively in adding targeted damping to light structures. The most common approach for realizing stiffness and damping in these tuned devices has been applying VE material to strips of elastic material (mainly metal, e.g. steel) in an unconstrained or constrained layer fashion and using such assemblies, which can be viewed as a damped leaf-springs, for the suspension element of the tuned mass damper. In this work, the suitability of tuned mass dampers with visco-elastically damped leaf-spring suspension for treating large, massive civil engineering structures, more specifically floor systems, was studied numerically and experimentally. The effectiveness of this tuned mass damper configuration turned out to be disappointing.
In parallel to the above-mentioned study, an alternative VE suspension was devised by stacking a number of 25 mm (1 inch) thick VE rings interlaced with the same number of metal constraining ring layers. By changing the number of these rings, different stiffness’s are realized and thus different tuning frequencies are achieved.
The material properties of the VE polymer used in both studies are defined in terms of Prony series parameters. Viewing the Prony series parameters as optimization variables, they are recovered by minimizing the mean squared error between the dynamic material properties predicted by the Prony series parameters and the frequency-dependent dynamic material properties provided by the manufacturer. Using the material properties of the VE material, the dynamic finite element model of a 100 lb TMD was constructed and its tuned damping effectiveness demonstrated, numerically. The 100 lb TMD was also built and used to a) verify the numerical model and b) experimentally demonstrate the performance of the TMD.
Experimental Study of Heat Transfer Characteristics of Drying Process with Dielectrophoresis Mechanism
Authors: Yang Mengqiao , Asar Munevver Elif , Yagoobi Jamal 
Published: January 2022

Abstract
Drying of moist porous media, such as paper and pulp, is an extremely energy-consuming process. Traditional drying techniques are primarily associated with convection, conduction, and thermal radiation. It is desirable to develop innovations in non-thermal and high-efficiency drying techniques. In the previous study, a novel drying technology, making use of the Dielectrophoresis (DEP) mechanism, has been experimentally proved to be an energy-efficient method to enhance the drying rate of moist porous media. DEP is a translational motion of neutral matter caused by the polarization effects in a diverging electric field. During the drying process, in the presence of the DEP force, the vapor phase is extracted away from the porous medium, which results in an increase of the evaporation rate and a decrease of the sample surface temperature. This paper extends previous experimental studies by including analysis of the heat-transfer characteristics. Specifically, the heat flux rate underneath the moist paper is monitored during the drying process. The sample surface temperature is monitored through an Infrared (IR) camera. Moreover, the convection heat transfer coefficients are estimated, and the sample’s initial moisture content is studied as a function of drying time. The experimental results show an up to 132% increase of the heat flux rate and a 242% increase of the convection coefficient due to the application of an electric field, as compared to conventional drying process. The experimental results also illustrate that the DEP effects diminish at low moisture levels. The detailed heat transfer analysis provides a foundation for the enhancement of moist porous media using the DEP mechanism for drying fragile products.
The Role of Protective System Reliability Analysis in the Study of System Safety
Authors: Wortman Martin , Kee Ernie , Kannan Pranav 
Published: January 2022

Abstract
Safety–critical protective systems mitigate possible collateral harm to the public, when randomly occurring initiating events challenge the operational integrity of hazardous technologies. Quantifying the efficacy of protection remains a challenge to engineers and regulators responsible for safety. In this paper, we will explore the analytical relationship between protective system reliability and safety efficacy. Central to our discussions is the understanding that: Not only should protective systems be reliable over time, but they must be highly effective at the exact instants of initiating event arrivals. Extending traditional system reliability analyses to quantify the effectiveness of protective systems that are challenged by potentially catastrophic initiating events, requires identifying and redressing certain modeling pitfalls that are counterintuitive. It is our purpose, here, to reveal some of these pitfalls by appealing to well known results from system reliability theory and the theory of stochastic point processes.
Optimization of Powertrain Energy Management for Range Extended Electric Vehicle Using Modified Particle Swarm Algorithm
Authors: Parkar Omkar , Snyder Benjamin , Anwar Sohel 
Published: January 2022

Abstract
Energy and Power Management Strategies play vital role in improving efficiency of any hybrid propulsion system. However, these control strategies are sensitive to the dynamics of the powertrain components used is the given system. A mathematical model for hybrid powertrain of Range Extended Electric Vehicle (REEV) has been developed in this study and is further optimized to reduce the level of fuel consumption and NOx emissions individually by optimizing the control strategy of Power Management System (PMS). A modified Particle Swarm Optimization (PSO) algorithm has been used in this research, to determine the optimum PMS strategy. In performing these optimizations, the control signal consisting of genset speed and power for a full 2-hour cycle was used as the controllable decision parameters input directly from the optimizer. Each element of the control signal was split into 50 distinct points representing the full 2 hours giving slightly more than 2 minutes per point, noting that the values used in the models were interpolated between the points for each time step. With the control signal consisting of 2 distinct signals viz. speed and power, as 50 element time variant signals, a 100-D problem was formulated for the optimizer. The developed algorithms were simulated on the REEV model on MATLAB/SIMULINK platform. Simulation results show that the fuel consumption reduction of 12% and NOx emission reduction of 35% was achieved individually by deploying the optimal PMS strategy when compared with the baseline results.
Vision Based Obstacle Detection and Navigation of an Autonomous Vehicle
Authors: Nandikolla Vidya K. , Ferman Keven , Barragan Eddie , Fuentes Melgar Stefany , Perez Hector 
Published: January 2022

Abstract
Using the vision system, the autonomous vehicle detects and classifies objects with high accuracy and determines its navigation. The image files are transported into the robot operating system (ROS) to test in the simulation. Google’s TensorFlow and ImageAI computer vision Python library, are used to create a custom neural network model to detect and classify specific objects, i.e. lane lines to drive within or caution cones to avoid hazards. Initial development focused on processing and annotating two hundred images of a random object in various angles, distances, and light conditions recorded from the cameras on the autonomous vehicle. These images are processed through Google’s CoLaboratory, a cloud-based development server providing free GPU hardware, for faster processing. The goal is to take the customized detection model and provide a desired output. The test procedure included coding annotated pictures of different objects and creating datasets. The procedure for training the datasets are developed and as a result, several models for each of the objects are obtained. The object detection model with the best capability to detect designated objects were evaluated. The paper reflects how machine learning is utilized for obstacle detection and navigation for autonomous vehicle to maneuver around assigned constraints.