bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mobile Carrying Platform: i-Explore
Authors: Sohn Kiwon , Emami Aurian , Yang Jaesung 
Published: February 2021

Abstract
This paper presents the development of mobile transportation robot, i-Explore which has been designed and built by ART (Assistive Robot Team) in University of Hartford since 2018. The main objective of i-Explore is to assist and carry children who have severe physical disabilities in indoor environments, especially for domestic uses. In this paper, the mechanical design and building processes of i-Explore which focused on fast reactiveness and low-cost manufacturing as its main technical design requirements are described first. Then, the kinematic analysis and its implementation in the low-level body controller of the mobile robot are described. Lastly, i-Explore is tested and evaluated both in cleaned and cluttered works spaces with its semi-autonomous motions which are designed for the robot’s navigation in human centered environments.
Thermal Energy Replacement Potential in a Slaughter Plant From Rumen Pellets
Authors: Fajardo J. , Barreto D. , Morales O. 
Published: February 2021

Abstract
In this work, steam generation was studied using natural gas or rumen as energy sources in a slaughter plant that sacrifices 7500 cattle per month, with consumption 0.5749 kg/s of saturated steam at 624 kPa. For a slaughtered cow, 10.5 kg of rumen can be obtained after being dried outdoors; for its final disposal, the slaughter plant bears the costs of USD 7.2 per ton of rumen. In the study, exergy and exergoeconomic performances were compared by generating steam with a natural gas boiler with the steam generation with a rumen boiler. From this, combustion analysis, energy efficiency, exergy destruction, exergy efficiency, exergy destruction costs, and generating 1 kg of steam from the two boilers were evaluated. The study results showed that the generation of steam with rumen is less efficient than with natural gas since it presents the exergy destruction of 1175.9 kW and exergy efficiency of 26.83%. While the generation of steam with rumen boiler was obtained, with exergy destruction of 1419.9 kW and exergy efficiency of 23.29%. Exergy destruction cost and the cost of generating 1 kg of steam using rumen were $/h 7821 and 0.0073 $/kg, respectively. Although the generation of steam with natural gas present the exergy destruction cost of 26285 $/h and the cost of generating steam of 0.021 $/kg, this indicators are higher using natural gas as a fuel that with rumen pellets.
Stamp Forming: A Comparison in the Use of Draw Beads and Blank Holder Force for Producing Aluminum Panels
Authors: Emblom William J. 
Published: February 2021

Abstract
An investigation was performed examining the effects of draw beads and blank holder forces on local forces in various regions of a stamp forming process that produced oval aluminum panels. The results showed that provided there was sufficient blank holder forces to prevent wrinkling, the regions with draw beads were affected more by draw bead height than by blank holder force. However, at the die ends, away from the draw beads, blank holder force had more of an effect than the draw beads did with respect to local forces. Additionally, the draw bead height effects at the die end were not directly related but had to be interpreted based upon the effect on strains within the flange region at the die ends. This study may be especially useful for researchers in the automotive sector who are particularly interested in aluminum panel forming.
Evaluating the Influence of Nanofluid Type and Volume Fraction on the Performance of Heat Exchanger
Authors: Jassim Esam I. , Ahmed Faizan , Jasem Bashar 
Published: February 2021

Abstract
The utilization of nanofluid in heat exchanger is of immense interest in the petrochemical and power plant industries due to the durability provided to the exchanger long-life operation. In the present research, an experimental investigation is carried out to study the existence of copper and aluminum oxide nanoparticles in the base fluid and their impact on the performance of the heat exchanger. A comparison with the theoretical outcome is also conducted. Pure water is pumped through the tubes of the heat exchanger unit whereas the nanofluid is pumped into the shell of the unit by means of another impeller pump. Various volume fractions ranging from 0.26%–0.83% are tested to assess the morphology of nanoparticle and volume fraction on the exchanger efficiency. It is observed that the volume fraction of nanofluid has a significant positive impact on the effectiveness of the heat exchanger. An increase in the volume fraction of the nanofluid enhances the effectiveness of the heat exchanger up to 7% for Al2O3 and 10% for Copper. The impact of the Reynolds number is also studied. The Reynolds number for the cold-side nanofluid varies in the range 7000–15000. As the Reynolds number augments, the Nusselt number also increases by ∼13% for Al2O3 and 23% for Cu nanofluids. Additionally, the effect of varying inlet temperatures of hot fluid is investigated. The results indicate an enhancement in the exchanger performance at higher inlet temperatures of the hotside fluid.
The Flow Dynamics of Stranded Cables
Authors: Abdelhady Mohamed , Wood David H. 
Published: February 2021

Abstract
Only a few studies of the flow dynamics of stranded cables have been made despite their wide applications. This paper studies in detail the wake flow dynamics of two stranded cables using Particle Image Velocimetry at Reynolds number of 1,500. First and second order statistics were obtained for both cables. Besides, Proper Orthogonal Decomposition of the velocity and vorticity fields was used to determine the effect of the strands on the coherent structures. Results showed that wake flow dynamics are significantly affected by cable strands, specially as the ratio of cable overall diameter to strand diameter increases. Finally, this study provides detailed stranded cables wake flow dynamics. Such understanding could be used in optimizing cable design for different applications, to allow, for example, overhead transmission lines to passively increase their current carrying capacity.
Effect of the Environmental Conditions of Tropical Climates on the Performance Parameters of a Gas Turbine Power Generation Plant
Authors: Fajardo J. , Barreto D. , Castro T. , Baldiris I. 
Published: February 2021

Abstract
It is known that high temperatures adversely affect the performance of gas turbines, but the effect of the combination of atmospheric conditions (temperature and relative humidity -RH-) on the operation of this type of system is unknown. In this work the effects of atmospheric conditions on the energy and exergy indicators of a power plant with gas turbine were studied. The indicators studied were the mass flow, the specific work consumed by the compressor, specific work produced by the turbine, the combustion gas temperature, the NO concentration, the net output power, the thermal efficiency, the heat rate, the specific consumption of fuel, the destruction of exergy and exergy efficiency. Among the results, it is noted that for each degree celsius that reduces the temperature of the air at the compressor inlet at constant relative humidity on average, the mass flow of dry air increases by 0.27 kg/s, the specific work consumed by the compressors decreases by 0.45%, the output power increases by 1.17% and the thermal efficiency increases by 0.8%, the exergy destruction increases by 0.72% and the exergy efficiency increases by 0.81%. In addition, humidity changes relative to high temperatures are detected more significantly than at low temperatures. The power plant studied is installed in Cartagena, Colombia and since it is not operating in the design environmental conditions (15 °C and 60% relative humidity) it experiences a loss of output power of 6140 kW and a drop in thermal efficiency of 5.12 %. These results allow considering the implementation of air cooling technologies at the compressor inlet to compensate for the loss of power at atmospheric air conditions.
A Numerical Simulation of Unsteady Lid Driven Cavity Flow With Moving Boundaries Using CMSIP
Authors: Akyuzlu K. M. , Antoniou A. 
Published: February 2021

Abstract
A two-dimensional, mathematical model is adopted to investigate the development of circulation patterns for compressible lid driven flows inside a rectangular cavity where the bottom of the cavity is free to move at a specified speed. A time and space dependent transformation is applied to the governing equations to obtain a rigid (non-moving) solution domain. The transformed equations are discretized for a uniform and orthogonal computational mesh using second order in space and first order in time finite difference schemes. The resulting nonlinear equations are then linearized using Newton’s linearization method. Finally, the set of algebraic equations that result from this process are put into a matrix form and solved using the Coupled Modified Strongly Implicit Procedure (CMSIP). Numerical experiments are carried out for various Reynolds numbers to verify the accuracy of the solution algorithm. Then the numerical simulations of lid driven flow inside the cavity is carried out for the unsteady case where the aspect ratio of the cavity is changed from 1 to 1.5 at a constant speed. It is concluded that the proposed model is successful in predicting the unsteady characteristics of the primary vortex and the secondary vortices inside a cavity with moving bottom.
Infill Defective Detection System Augmented by Semi-Supervised Learning
Authors: Song Jinwoo , Moon Young B. 
Published: February 2021

Abstract
In an effort to identify cyber-attacks on infill structures, detection systems based on supervised learning have been attempted in Additive Manufacturing (AM) security investigations. However, supervised learning requires a myriad of training data sets to achieve acceptable detection accuracy. Besides, since it is impossible to train for unprecedented defective types, the detection systems cannot guarantee robustness against unforeseen attacks.
To overcome such disadvantages of supervised learning, This paper presents infill defective detection system (IDDS) augmented by semi-supervised learning. Semi-supervised learning allows classifying a sheer volume of unlabeled data sets by training a comparably small number of labeled data sets. Additionally, IDDS exploits self-training to increase the robustness against various defective types that are not pre-trained.
IDDS consists of the feature extraction, pre-training, self-training. To validate the usefulness of IDDS, five defective types were designed and tested with IDDS, which was trained by only normal labeled data sets. The results are compared with the basis accuracy from the perceptron network model with supervised learning.
Pulse Shaping in 1D Elastic Waveguides for Shock Testing
Authors: Johnson William R. , Leamy Michael J. , DeLima Washington , Ruzzene Massimo 
Published: February 2021

Abstract
Mechanical shock events experienced by electronics systems can be reproduced in the laboratory using Hopkinson bar tests. In these tests a projectile strikes a bar, creating a pulse which travels through the bar into the system. The quality of these tests depends on the closeness of the shape of the incident pulse to the shape specified for the test. This paper introduces a new way to control the shape of the incoming pulse, through the use of elastic metamaterial concepts. Two dispersion-modifying material concepts, phononic crystals, and local resonators, are examined for their wave shaping capabilities in 1D elastic waveguides. They are then evaluated using a transfer matrix method to determine the output wave shape in the time domain. The concepts are then optimized for various pulse shapes, showing that they are most effective when they are tuned to introduce dispersion near the fundamental frequency of the incident wave.
Numerical Modelling for Oblique Impacts With Ductile Material Particle Erosion During Cold Gas Dynamic Spray
Authors: Oyinbo Sunday Temitope , Jen Tien-Chien , Aasa Samson A. 
Published: February 2021

Abstract
Another key parameter that affects the coating deposition efficiency of cold gas dynamic spray technology is the contact angle. The particle tangential sliding on the substrate at impact is due to the gas flow bow shock at a supersonic velocity which is liable for the erosion at the surface of the substrate. This study presented a finite element approach of a numerical model to investigate the profile of the deformed sprayed particles under the condition of oblique impact and the erosion mechanism for solid particle impact on ductile material during Cold Gas Dynamic spray. In the numerical modelling of cold gas dynamic spray (CGDS) by a Lagrangian approach that was developed, oblique erodent particle on the substrate at controlled contact angle (10°–90°), velocity (500 m/s) and friction coefficient (0.3) was simulated. It was discovered that in the substrate, the crater depth decreases as well as the area of contact between the substrate and the deformed particles when the contact angle increases at the same impacting conditions. The material removal and crack formation mechanism were also simulated successfully by the accumulation of residual strain that resulted in the dynamic detachment of material elements at the surface as they fail.
Analysis of Composite Bolted Connection Joints Under Out of Plane Loading
Authors: Mahmoud Hassan A. , Shazly Mostafa , Bahei-El-Din Yehia , El-Kashif Emad 
Published: February 2021

Abstract
The use of composite joints has been increased in recent years in structural applications such as aircraft, civil engineering structure, ship structure, wind energy sector, and automotive industry. In this paper, the behaviour of composite bolted connection joints under out of plane loading is investigated. A parametric study was conducted to study the joint stiffness variation with various geometric parameters, which include the edge distance, bolt diameter, plate width, and the laminate stacking sequence. The experimental work was conducted on GFRP tension clips (L-angle) joint specimens manufactured by the vacuum infusion technique. In the present work, two types of laminates were used, unidirectional laminates [0°]5 with an areal density of 1050 gm/m2, triaxial laminates [−45°/+45°/0°]5 with an areal density of 1200 g/m2. A 3D finite element (FE) model was developed to study the effect of joint parameters on its stiffness. Finite element models were constructed, and the experimental results were used to validate the finite element models. The analysis concluded that the failure load increases when the edge distance to bolt diameter ratio (E/D) increases and the triaxial stacking sequence is better than unidirectional. The (E/D) ratio, the (W/D) ratio and stacking sequence were found to be very significant parameters.
Ultrasonic Nondestructive Testing for In-Line Monitoring of Wire-Arc Additive Manufacturing (WAAM)
Authors: Hossain Md Shahjahan , Taheri Hossein , Pudasaini Niraj , Reichenbach Alexander , Silwal Bishal 
Published: February 2021

Abstract
The applications for metal additive manufacturing (AM) are expanding. Powder-bed, powder-fed, and wire-fed AM are the different kinds of AM technologies based on the feeding material. Wire-Arc AM (WAAM) is a wire-fed technique that has the potential to fabricate large-scale three-dimensional objects. In WAAM, a metallic wire is continuously fed to the deposition location and is melted by an arc-welding power source. As the applications for WAAM expands, the quality assurance of the parts becomes a major concern. Nondestructive testing (NDT) of AM parts is necessary for quality assurance and inspection of these materials. The conventional method of inspection is to perform testing on the finished parts. There are several limitations encountered when using conventional methods of NDT for as-built AM parts due to surface conditions and complex structure. In-situ process monitoring based on the ultrasound technology is proposed for WAAM material inspection during the manufacturing process. Ultrasonic inline monitoring techniques have the advantages of providing valuable information about the process and parts quality. Ultrasonic technique was used to detect the process condition deviations from the normal. A fixture developed by the authors holds an ultrasonic sensor under the build platform and aligned with the center of the base plate. Ultrasonic signals were measured for different process conditions by varying the current and gas flow rate. Features (indicators) from the radio frequency (RF) signal were used to evaluate the difference in signal clusters to identify and classify different build conditions. Results show that the indicator values of the ultrasonic signals in the region of interest (ROI) changes with different process conditions and can be used to classify them.
Controlling Drag and Down Forces on a Vehicle Side-View Mirror by Applying Vortex Generator Designs on the Bottom Surface
Authors: Dong Zulong , Jawad Badih , Liu Liping , Metwally Hossam 
Published: February 2021

Abstract
Side-view mirrors impact the aerodynamic performance of a vehicle due to the creation of extra drag force, noise, and vibration. This paper presents an alternative practical solution for improving aerodynamic performance of vehicle side-view mirrors. A CFD analysis is conducted for studying the airflow around a side-view mirror with different types of passive vortex generators (VGs) mounted on the bottom surface. VGs are small wingtips that are used to produce swirling motion in the flow stream. In recent years, VGs have been used in vehicle underbody diffusers to delay flow separation and to increase the flow control surface. This study aims to understand the effect of underbody VGs on the flow mechanisms downstream of the side-view mirror, and its impact on both drag and down forces.
The turbulent flow behind the side-view mirror is investigated to determine the effects of different VG types and attack angles. Four types of VGs are considered in this work. Changes are made to the baseline model by either adding the VGs close to the frontal edge of the bottom surface of the mirror which aims to control the flow separation, or adding the VGs close to the back edge which aims to reduce the shedding area. Computational Fluid Dynamics (CFD) analysis using ANSYS Fluent is conducted to simulate the flow behavior by using three dimensional Reynolds-averaged Navier-Stokes method with standard K-epsilon (K-ε) turbulence model. In order to incorporate the effect of vehicle body, each model is assembled on a quad-vehicle bluff body for analysis. The drag and down forces are numerically solved and compared with the results of the baseline model at the speeds of 15, 40, 60 and 80 miles per hour. It is concluded from the CFD analysis that: (1) Mounting VGs at the bottom surface of a side-view mirror reduces down force in most cases. (2) Setting underbody VGs at either the front or back edge of the mirror bottom surface has a slight effect on reducing drag force. (3) Multiple types of VGs show improved results with a 30 degree attack angle, which encourages future studies of VG applications with large attack angles.
Virtual Simulations Environment Development for Autonomous Vehicles Interaction
Authors: Malayjerdi Mohsen , Kuts Vladimir , Sell Raivo , Otto Tauno , Baykara Barış Cem 
Published: February 2021

Abstract
One of the primary verification criteria of the autonomous vehicle is safe interaction with other road users. Based on studies, real-road testing is not practical for safety validation due to its time and cost consuming. Therefore, simulating miles driven is the only feasible way to overcome this limitation. The primary goal of the related research project is to develop advanced techniques in the human-robot interaction (HRI) safety validation area by usage of immersive simulation technologies. Developing methods for the creation of the simulation environment will enable us to do experiments in a digital environment rather than real. The main aim of the paper is to develop an effective method of creating a virtual environment for performing simulations on industrial robots, mobile robots, and autonomous vehicles (AGV-s) from the safety perspective for humans. A mid-size drone was used for aerial imagery as the first step in creating a virtual environment. Then all the photos were processed in several steps to build the final 3D map. Next, this mapping method was used to create a high detail simulation environment for testing an autonomous shuttle. Developing efficient methods for mapping real environments and simulating their variables is crucial for the testing and development of control algorithms of autonomous vehicles.
Large Eddy Simulations of Francis Turbine Operating at Ultra-Low Loads
Authors: Altimemy Muhannad , Caspar Justin , Watheq Saif , Oztekin Alparslan 
Published: February 2021

Abstract
High-fidelity large eddy simulations (LES) were conducted to characterize the spatial and temporal structure of turbulent flows in an industrial-sized Francis turbine. The unit operated at 50% and 40% of the best efficiency design flowrate. Contours of vorticity, velocity, pressure, and iso-surfaces of Q-Criterion were presented to characterize the effects on the draft tube. Probes placed alongside the draft tube measure the pressure signal to investigate the flow-induced pressure fluctuations inside the turbine unit. The maximum intensity of pressure fluctuations at 50% partial load was 22.66% of the turbine head, while the strength of the pressure fluctuations was 26.36% at 40% partial load. A large number of unorganized smaller vortices observed in the draft tube contribute to the creation of pressure fluctuations. Two pressure modes can be easily recognized (1) high frequency with low amplitude pressure fluctuations and (2) low frequency with high amplitude fluctuations. These pressure fluctuations could be harmful to the structural integrity of the unit and also have undesirable influences on the operational stability of the hydro-turbines.
Machine Learning Using Brain Computer Interface System
Authors: Matsuno Kevin , Nandikolla Vidya K. 
Published: February 2021

Abstract
With commercially available hardware and supporting software, different electrical potential brain waves are measured via a headset with a collection of electrodes. Out of the different types of brain signals, the proposed brain-computer interface (BCI) controller utilizes non-task related signals, i.e. squeezing left/right hand or tapping left/right foot, due to their responsive behavior and general signal feature similarity among patients. In addition, motor imagery related signals, such as imagining left/right foot or hand movement are also examined. The main goal of the paper is to demonstrate the performance of machine learning algorithms based on classification accuracy. The performances are evaluated on BCI dataset of three male subjects to extract the most significant features. Each subject undergoes a 30-minute session composed of four experiments: two non-task related signals and two motor imagery signals. Each experiment records fifteen trials of two classes (i.e. left/right hand movement). The raw data is then pre-processed using a MatLab plugin, EEGLAB, where standard processes of cleaning and epoching the signals is performed. The paper discusses machine learning for robotic application and the common flaws when validating machine learning methods in the context of BCI to provide a brief overview on biologically (using brain waves) controlled devices.