bluuebunny/crossref_metadata_2025_split huggingface dataset:
Investigation and Characterization of Clay Mixture Feedstock for Extrusion-Based Additive Manufacturing
Authors: Alkindi Tawaddod , Alyammahi Mozah , Susantyoko Rahmat Agung 
Published: February 2021

Abstract
The extrusion-based AM technique has been recently employed for rapid ceramic components fabrication due to scalability and cost-efficiency. This paper investigated aspects of the extrusion technique to print ceramic materials. Specifically, we assessed and developed a process recipe of the formulations (the composition of water and ethanol-based clay mixtures) and mixing processes. Different clay paste formulations were prepared by varying clay, water, ethanol ratios. The viscosity of clay paste was measured using a DV3T Viscometer. Afterward, the produced clay paste was used as a feedstock for WASP Delta 60100 3D printer for computer-controlled extrusion deposition. We evaluated the quality of the clay paste based on (i) pumpability, (ii) printability, and (iii) buildability. Pressure and flow rate were monitored to assess the pumpability. The nozzle was monitored for continuous material extrusion to assess printability. The maximum layer-without-collapse height was monitored to assess the buildability. This study correlated the mixture composition and process parameters, to the viscosity of the mixture, at the same printing speed. We found that 85 wt% clay, 5 wt% water, 10 wt% ethanol paste formulation, with the viscosity of 828000 cP, 202400 cP, 40400 cP at 1, 5, and 50 rpm, respectively, demonstrates good pumpability, as well as best printability and buildability.
Enhance PV Panel Detection Using Drone Equipped With RTK
Authors: Ismail Hesham , Alhussein Mohammed , Aljasmi Nawal , Almazrouei Saeed 
Published: February 2021

Abstract
Solar energy is getting a lot of traction due to the reduced cost and friendlier to the environment compared to fossil fuel. It is essential to inspect the PV farms to ensure that the correct capacity produced through early PV fault detection. We proposed a full autonomous solution, where the drone mission is programmed to follow a specific Global Positioning System (GPS) waypoints. The collected videos will undergo various image processing techniques to detect and track the PV panels.
In this paper, we tried two different PV panel detection approaches. Both detections gave acceptable results. The first detection relies on various image processing techniques. The second detection relies on deep learning architecture called mask Region-based Convolution Neural Network (R-CNN). After that, we track the PV panels in every frame using camera data alone. The advantage of tracking the PV panels is to ensure unrepeated PV panel through tagging even if the drone flies over the panel again since each PV panel will be associated with a tag. The next step will be to test the PV panel’s proposed detection and tracking algorithm on a larger solar farm.
Investigation of Spatial Variability on Strut Diameters of Additively Manufactured Lattice Structures
Authors: Gorguluarslan Recep M. , Gungor O. Utku 
Published: February 2021

Abstract
In this study, the influence of the spatial variability of geometric uncertainties on the strut members of the lattice structures fabricated by additive manufacturing is investigated. Individual struts are fabricated with various printing angles and diameters using a material extrusion process and PLA material. The diameter values of the fabricated samples are measured along the printing and radial directions at each layer under an optical microscope. Spatial correlations are characterized based on the measurements using the experimental autocorrelation function. Candidate autocorrelation functions are fitted to the measured data to identify the best fitted one for each diameter parameter and the corresponding correlation lengths are evaluated for random field. The applicability of the Karhunen-Loeve expansion (KLE) is investigated to reduce the dimensionality of the random field discretization. The results show that the diameters of the strut members at each layer are spatially dependent and the KLE method was found to give a good representation of the random field.
Analytical and Numerical Investigation of the Fluid Structure Interaction of an Elastic Beam in a Water Channel
Authors: Fritsche Manuel , Epple Philipp , Delgado Antonio 
Published: February 2021

Abstract
The interaction between fluids and solids is becoming increasingly important in the design and analysis of machines, buildings and systems. Due to the fluid-mechanical phenomenon of turbulence and the associated flow and vortex shedding, the fluid structure interaction must be considered, for example, in aircraft wings, civil engineering (e. g. television towers or bridges), the rotor blades of wind turbines or in the field of sensor technology. Due to the increasing computing power, increasingly complex tasks can be calculated with the help of numerical simulations.
In this paper, an elastic beam has been defined as test case and has been analyzed in different ways with the methods of the fluid structure interaction (FSI), i.e. with analytical and numerical approaches. For this purpose, the plastic beam has been fixed on one side in a water channel and the flow around it and the beam deflection have been measured. The deformation of the beam due to the flow load around it has been analyzed for varied flow velocities.
First, the beam deformation has been estimated based on the analytical equations from structural mechanics and an assumed stagnation pressure on the beam surface. Additionally, the drag coefficient from experimental data of the literature was used to estimate the force on and the bending of the beam. Then two numerical simulations with different FSI coupling methods have been performed with Ansys Workbench 2020 R1. On the one hand, a one-way coupling analysis has been performed in which the pressure field was calculated from the CFD simulation and then transferred to the mechanical analysis. On the other hand, a two-way coupling computation has been performed, which also takes transient effects into account. For this purpose, the flow field and the pressure field have been exchanged iteratively between the fluid and the mechanical solver. This coupling approach is general and corresponds to reality since large deformations and non-linearities are considered. However, this approach always requires a very computation intensive, non-stationary calculation.
The results obtained from these parameter studies have then been evaluated and compared in order to determine the accuracy of each analysis methodology. The elaborated results have been discussed and analyzed in detail.
Validation of Two Open Source Discrete Element Software Packages Against Theoretical Benchmarks
Authors: Rittenhouse Justin , Gustafson Peter 
Published: February 2021

Abstract
As computational expense decreases Discrete Element Method (DEM) has increased in popularity as a tool to model granular material. Unfortunately wide spread access to DEM software is still an issue, as many researchers in academia and industry simply do not have access to proprietary software packages, including the author of this paper. Thus the importance of verifying open-source packages for their legitimacy relative to their proprietary counterparts. Thus the scope of this paper is to further validate two open-source packages, Yet Another Dynamic Engine (Yade) and Project Chrono, are capable of generating reliable results.
Yade and Project Chrono were evaluated against a series of established particle level impact benchmark modeling cases (e.g., between two spheres or a sphere and rigid wall). These cases were designed to evaluate elastic normal impacts, energy dissipation for normal impacts, and energy dissipation due to oblique impacts. In addition each test case was investigated twice implementing a change in material properties on the second simulation. Many of the resulting forces, moments, and accelerations were found to agree with theoretical solutions and/or proprietary software model results published in the existing literature [1]. The discrepancies are still under investigation. These open source software packages are found to have advantages that are useful in an university research or an industrial environment.
Evaluation of Metal Lattice Structures With X-Ray Micro-Computed Tomography: Dimensional Accuracy and Manufacturability
Authors: Puttonen Tuomas 
Published: February 2021

Abstract
Additive manufacturing enables product designers to incorporate complexity onto their designs on multiple size scales. Computer-aided design methods, such as topology optimization and lattice design, have emerged as software tools for applications where part consolidation and weight reduction are desired. Still, a more delicate control of hierarchical complexity and submillimeter-sized features would unlock a widely unexplored frontier of new design possibilities.
However, the complexity of a design can respectively affect the manufacturing process. In powder bed fusion, the diameter, power and speed of the laser spot and the resulting size of the melt pool define the attainable feature resolution and accuracy in comparison with the original design intent. X-ray computed tomography can be a useful tool in validation and provide a detailed, volumetric representation of a part with internal features.
This paper examines the design accuracy of 316L metal lattice structures and density of solid cubes with industrial X-ray micro-computed tomography. Accessible tools with open source software are presented for CT data analysis. The nominal values are compared against the as-built and CT scanned samples for surface area, volume, and dimensional accuracy. A CT voxel size of 30–40 μm allows to identify printability issues and general trends in the part density in comparison to the geometry changes. However, a finer voxel size in the submicron range would be required to properly detect and localize internal porosity and evaluate surface topography.
On the Uses of Linear-Quadratic Methods in Solving Nonlinear Dynamic Optimization Problems With Direct Transcription
Authors: Herber Daniel R. , Sundarrajan Athul K. 
Published: February 2021

Abstract
Solving nonlinear dynamic optimization (NLDO) and optimal control problems can be quite challenging, but the need for effective methods is ever increasing as more engineered systems become more dynamic and integrated. In this article, we will explore the various uses of linear-quadratic dynamic optimization (LQDO) in the direct transcription-based solution strategies for NLDO. Three general LQDO-based strategies are discussed, including direct incorporation, two-level optimization, and quasi-linearization. Connections are made between a variety of existing approaches, including sequential quadratic programming. The case studies are solved with the various methods using a publicly available, MATLAB-based tool. Results indicate that the LQDO-based strategies can improve existing solvers and be effective solution strategies. However, there are robustness issues and problem derivative requirements that must be considered.
Rolling Resistance of a Skateboard
Authors: Maull Thomas , Eichaker Lauren , Buczek Sean , Graham Troy 
Published: February 2021

Abstract
Skateboards have been used as a means of transportation and extreme sports for decades. The forensic analysis of skateboard-related accidents requires knowledge of the kinematic characteristics of the skater-skateboard and skateboard-ground interactions to aid in the investigative process.
Much of the existing skateboard research has focused on the motion of the skater-skateboard system. Few studies have investigated the interactions of the skateboard and the ground surface. The velocities and accelerations of a skateboard/skater system is not well defined in literature. A skateboard’s rolling resistance has also not been defined. Therefore, this study was conducted to describe the effect of rider mass and wheel bearing resistance on the rolling resistance of a skateboard.
Understanding the dynamics of the skateboard and rider in relation to rolling resistance is critical to an investigator attempting to determine the behavior of a skateboard when reconstructing a skateboard related incident. In addition, the data that will be presented in this study is beneficial to a wide audience including, but not limited to; traffic safety, accident reconstruction, skateboard design, bearing design and useful life, and wheel design and useful life.
Numerical Analysis and Parametric Study of a Thermoelectric-Based Radiant Ceiling Panel for Building Cooling Applications
Authors: Seyednezhad Mohadeseh , Najafi Hamidreza 
Published: February 2021

Abstract
Buildings are known as one of the foremost energy consumer sectors in the world with a share of nearly 40% and hence the design and development of clean and energy efficient building energy systems is an important step towards a sustainable future. Cooling and air conditioning systems, as an essential component for occupants’ comfort, are among the largest energy end-users in buildings. Additionally, most air conditioning systems rely on using refrigerants that are harmful for the environment with considerable potential for ozone depletion and global warming. Solid-state cooling technologies that do not require refrigerant are therefore of interest to eliminate these environmental concerns. Thermoelectric (TE) modules, as a solid-state cooling technology, when supplied by DC electricity, produce a temperature gradient through the Peltier effect that can be used for cooling purposes. Due to the attractive characteristics that TE technology offers, mainly high controllability, lack of refrigerant and large moving parts, quiet operation, promising efficiency and requiring minimum maintenance required, TE-based systems are becoming an emerging technology for building cooling applications. TE-based cooling technologies have been developed and tested through integrated and non-integrated systems in the building envelope. In the present paper, the design of a TE-based radiant cooling ceiling panel is investigated through numerical modeling and parametric study. The system can be incorporated in the ceiling and will maintain a reduced ceiling temperature to provide cooling through radiation and convection for the occupants. COMSOL Multiphysics is used for modeling and simulation purposes and the performance of the system under various configurations is assessed. The effect of number and placement of TE modules for a given size of ceiling panel are investigated using several simulations in COMSOL to achieve a desired and uniform surface temperature in the minimum amount of time. The impact of incorporating various amounts of phase change material (PCM) in the ceiling panel is also assessed. PCM allows the ceiling panel to maintain the desired temperature for an extended amount of time, but it also increases the time that it takes for the panel to reach the desired temperature. Transient thermal simulations are performed for both start up and shut down scenarios and the amount of time that it takes for the ceiling temperature to cool down to the desired level (on-mode) or heat up (off-mode) to the temperature at which it has to turn back on again are calculated for various system configurations. The results from this study can be used for optimal design of TE-based radiant cooling ceiling panels to achieve high energy efficiency and low operating cost while maintaining occupants’ comfort in the buildings.
An Improved Risk Priority Measure for the Management of Project Risk
Authors: Unwin Stephen D. , Calderin Duriem , Simpson Brett C. , Spitz Casey J. , Veeramany Arun , Gastelum Jason A. , Maloney Craig T. 
Published: February 2021

Abstract
Monte Carlo-based project risk models are essential tools in project risk management, particularly for large, complex projects in which it is difficult to glean intuitively the importance of individual risks to the overall project. Conventional correlation-based methods for measuring the importance of contributing risks in such models are argued here to be both statistically flawed and unintuitive in the importance metrics they produce. Drawing on and adapting methods more traditionally associated with engineering risk models, Risk Reduction Worth (RRW) is introduced as an importance measure. RRW is shown to be statistically robust and provide an easily interpretable, quantitative measure of the importance of a risk to the overall performance of a project; specifically, measuring the extent to which removal of a risk would improve confidence in project outcomes. To ensure practicality of the method, an approach is described in which RRWs can be produced for all contributing risks based on a single Monte Carlo sample. This is demonstrated through application to a large, complex project risk model from which intuitive risk importance insights provide a robust, transparent basis for the allocation of risk management resources.
Machine Learning Assisted Design for Active Cathode Materials
Authors: Yong Sihan , Zheng Zhuoyuan , Wang Pingfeng , Li Yumeng 
Published: February 2021

Abstract
The traditional way of designing materials, including experimental measurement and computational simulation, are not efficient. Machine learning is considered a promising solution for material design in the recent years. By observing from previous data, machine learning finds patterns, learns from the patterns and predict the material properties. In this study, machine learning methods are used for discovering new cathode with better properties, includes crystal system learning and the property prediction. K-Folder cross-validation is used for finding the best training data with a limited dataset, nevertheless increasing the percentage of training data would ultimately result in better performance on prediction. It is found that, random forest gives the highest average accuracy in crystal system classification, meanwhile, extra randomized tree algorithm provides a higher averaged coefficient of determination and lower mean squared error in the regression model predicting electrical properties of cathodes. The random forest algorithm is chosen from a wide range of machine learning algorithms with the implementation of Monte Carlo validation. Based on the feature importance evaluation, oxygen contents are found to have the highest effects in determining capacity gravity and volume change in properties prediction.
Characterization of Fluid-Filled Interconnected Dual-Cells for Reduction of Force and Linear Acceleration due to Blunt Impact
Authors: Erel Veysel , Lindsay Alexandra R. , Singh Inderjeet , Wijesundara Muthu B. J. 
Published: February 2021

Abstract
Although modern body and head protective gears are well studied by experts, innovators, and manufacturers, incidence of sports-related injuries is still very high in the United States and all around the world. To reduce the negative effects from blunt impact, an impact reduction structure which contains a channel, shell, and dual-cells was designed and developed with the intention of improving existing helmet liners. This study utilized a previously proven interconnected-cells concept, where a primary cell compresses, then air inside the cell transfers to a secondary cell which expands accordingly, causing impact reduction. While the concept remained the same, a new dual-cells architecture was explored, with numerical and experimental studies for helmet liner impact reduction, and compared to a commercial Xenith helmet liner element. The simulation study began with exploring the effect of adding corrugation to the walls of both cells on impact behavior, then persisted with optimizing impact reduction structure design, and finalized with a comparison study. An experimental study was performed with the optimized structure, provided by simulation, and compared against commercial Xenith helmet liner element in terms of reaction force, linear acceleration, and impact duration. Experimental and simulation results showed that our impact reduction structure provides lower reaction force and linear acceleration.
Numerical Study of Airfoil Shape and Blade Pitching on Vertical Axis Wind Turbine Through CFD Simulations
Authors: Ali Ussama , Modrek Mhd , Islam Md , Janajreh Isam 
Published: February 2021

Abstract
Wind energy has proved to be a promising sustainable energy source; the energy of wind has been harvested not only for decades but for centuries. It was in the late 19th century that wind energy was used to directly obtain electrical power. Horizontal axis wind turbines (HAWTs) are widely used in commercial applications but recently a lot of research is being done on vertical axis wind turbines (VAWTs) to improve their operation and efficiency. Absence of yaw mechanism, low noise emission, and low manufacturing, installation and maintenance costs are some of the prominent advantages of VAWT over HAWT. The objective of this study is to evaluate the performance of different blade airfoils and the influence of blade pitching in the operation of VAWT. Blade pitching is widely used in HAWTs and has proven to be very advantageous in terms of output power, but the effect of blade pitching on VAWT has not been widely studied and much less practically implied due to complex functional mechanism. VAWTs with fixed pitch experience continuously varying angle of attack which reduces the power generation. Airfoils tested in this study, for their performance on a VAWT rotor, are Joukowski airfoil (J-15), NACA0012 and NACA4312, furthermore, passive blade pitching was applied to analyze the effect of inoffset and out-offset blade pitching on the performance of the turbine. High fidelity Navier-Stokes computational flow models were applied for the analysis. A 2D unsteady CFD model was constructed to perform the simulations. Power and torque coefficients were evaluated over a varying range of tip speed ratios and a strong correlation of these coefficients was seen with different input parameters, such as airfoil shape, turbine solidity and tip speed ratios. Out-offset blade pitch angles showed better results than in-offset blade pitch angles.
Study the Effect of Communication Delay for Perception and Collision Avoidance in Cooperative Autonomous Driving
Authors: Ghorai Prasenjit , Eskandarian Azim , Kim Young-Keun 
Published: February 2021

Abstract
Cooperative perception through connectivity offers additional safety to autonomous driving by extending the field of view of the vehicles beyond their sensors. Critical safety information is passed among vehicles via wireless communications; therefore, communication among the vehicles in the system should be perfect and delay-free. In this article, an analytical study is proposed to show the effect of communication delays in a critical and emergency situation, where relying on the lead vehicle is so much crucial for an ego vehicle to avoid danger without any delay in sharing the dynamic information of on-road pedestrian or any such vulnerable road users. A simple and effective control algorithm is utilized based on distance modeling in a cooperative driving environment to control the vehicle’s longitudinal dynamics. A detailed simulation study using a dynamic model for both ego and lead vehicles, as well as a pedestrian on a hazardous on-road scenario, is presented to illustrate the effect of communication delays in autonomous driving.