bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Compact Integrated Thermosyphon Heat Sink for Power Electronics Cooling
Authors: Elkholy Ahmed , Kempers Roger 
Published: January 2020

Abstract
The trend in miniaturization of power electronic components requires the development of new robust and passive cooling methods to meet increased heat flux demands. Conventional heat sinks encounter inherent shortcomings due to heat spreading resistance of the heat sink baseplate particularly in natural convection heat sinks used to cool small localized heat sources. Heat pipes embedded within the base of heat sinks can be used to improve spreading performance but are limited by the ability to conduct heat into and out of the heat pipes.
In the current study, a small, naturally aspirated two-phase thermosyphon heat sink was developed and characterized experimentally. The proposed architecture integrates all thermosyphon components into one compact device, where the evaporator, riser and the downcomer are incorporated at the heat sink base. The downcomer also serves as the condenser within the base of a vertical finned natural convection heat sink.
The side-heated evaporator consists of an array mini-channels configuration which can operate in either pool boiling or flow boiling configuration, which allows the thermosyphon heat sink to operate in either reflux mode or looped mode, respectively.
Experiments were carried out using HFE 7000 as the working fluid. The effect of the of input power on the thermal performance is examined for both modes for powers ranging from 10 to 80 W. Results demonstrate that this approach significantly reduces the spreading resistance resulting in a net improvement which can be traded-off for a decrease the overall size or weight of the heat sink.
A Dynamic Pipeline Network Health Assessment Software Platform for Optimal Risk-Based Prioritization of Inspection, Structural Health Monitoring, and Proactive Management
Authors: Chalgham Wadie , Diaconeasa Mihai , Wu Keo-Yuan , Mosleh Ali 
Published: January 2020

Abstract
The Pipeline Health Monitoring and Management web application is a risk-based pipeline integrity management support tool to support pipeline operators in decision-making and planning activities. The platform design is supported by a multi-disciplinary science and engineering approach for a comprehensive, state-of-the-art solution. The goal of the software platform is to integrate the data, methods, and technologies into a dynamic pipeline heath monitoring system supported by multiple probabilistic predictive models such as dynamic hybrid causal logic, corrosion prognosis, and sensor placement optimization models. This total system health management support tool provides online or offline updates on the reliability state of various segments of the pipeline system, and dynamically updates the recommendations on when and where to take mitigating actions, e.g., increase or decrease inspection frequency. The pipeline health monitoring system software platform under development provides the ability for (a) Integrity assessment based on comprehensive range of evidence from sensing, inspection, and real-time monitoring in addition to probabilistic integration of mechanistic models and data on failure mechanisms relating to various causal factors (e.g., uniform corrosion, pitting corrosion, etc.) for assessment of the pipe segment health (remaining life); (b) Dynamic pipeline network probabilistic health assessment model software for optimal risk-based prioritization of inspection and proactive management, and (c) Geographical mapping capabilities that will augment the interaction of the pipeline operators with the pipeline system such as viewing pipeline/sensor locations, and adding new pipelines if desired. The selected computational foundation for the assessment is the hybrid causal logic engine with a wide range of capabilities in terms of system model building and probabilistic analysis of various types of evidence for assessment of model parameters. On this foundation we are adding capabilities to integrate predictive corrosion models, sensor placement optimization, and computational modules to perform pipeline health assessment, and develop inspection and maintenance strategies. The resulting software will be deployed as a control room health dashboard and hand-held web-based field inspection support tool.
A Smart Pipeline Monitoring and Emergency Response System Using Web Services
Authors: Chalgham Wadie , Diaconeasa Mihai , Elgazzar Khalid , Seibi Abdennour 
Published: January 2020

Abstract
The Smart Pipeline Monitoring System introduced in this paper demonstrates a proof-of-concept for replicating a full-scale water pipeline system that is able to monitor the pipeline health and respond to hazard conditions through the use of multiple sensors and a statistical monitoring control strategy. The system aims at mitigating the effects of common sources of damage that occur in pipelines, such as leaks and overheating, by offering real time data visualization and autonomous actions in case of emergencies. The data visualization is provided by a desktop user interface and a mobile application. In the case of a detected anomaly, described by out-of-bounds/out-of-statistical control conditions detected by the sensors, the system is programmed to shut off its pump and alert the supervisors by SMS instantly. The proposed monitoring system will enhance remote pipeline monitoring and structural safety by offering real-time data and automatic emergency response capabilities. Our experimental results and prototype implementation show that the proposed system effectively detects anomaly conditions under various realistic scenarios and takes necessary safety measures to prevent further damages.
Rapid Motion Control and Design of a Tricopter Style Hovering Ground Robot
Authors: Simko Justin , Tatoglu Akin 
Published: January 2020

Abstract
An analysis of the design and manufacture of a tricopter style hovercraft is realized in detail, along with the parameters for determining the geometry due to power requirements. The aircraft is constructed with three ducted fans in the vertical orientation, denoting the layout of the classic tricopter frame. The purpose of this study is to establish a design of a ground vehicle capable of multi-terrain navigation. A simplified skirt solution is presented for the aircushion. The model is robust enough for rough terrain and sufficient for maintaining the cushion pressure that enables the ground effect to work towards a higher efficiency. The design process for the model consists of the use of CAD to layout and simulate all components. The efficiency and battery life of the vehicle is compared to the tricopter and a flight test verifies its capability to follow a given path.
Wind Effects on Power Generation of Solar Farm in California
Authors: Li Ni , Fatahi Arianna , Lee Dennis , Kuo Jim Y. , Shen He 
Published: January 2020

Abstract
In comparison to fossil fuels, solar energy is a more sustainable option due to its high availability and less environmental impact. Improving the efficiency of solar farms has been a primary concern of solar energy research. Many studies focus on the control of the tilt angle of solar modules to maximize their solar radiation reception and energy generation. However, an increase in solar radiation is accompanied by an increase in module temperature, which is known to be a significant parameter that reduces the power generation efficiency. Wind is another influential factor that helps Photovoltaic systems maintain a low operating temperature by enhancing the rate of heat transfer. Therefore, solar radiation and wind behavior are both critical parameters that must be considered to optimize solar panel performance. In this paper, the effect of wind conditions on solar panel performance will be examined. The solar panel energy output model will be built by empirically considering the irradiation, ambient temperature, wind speed, and wind direction. The published weather data and energy output data for the year 2017–2018 have been collected from Antelope Valley Solar Ranch, located in Lancaster, California. Four models have been proposed and the results indicate that the model which incorporates the wind conditions has the highest accuracy in approximating the energy production of solar farms. Among the factors that affect the temperature of solar panels and further the efficiency of solar panels including solar irradiation, convection, conduction, wind plays a major role in convective heat transfer. Based on this model, the potential improvement of energy generation via introducing a horizontal installation angle and adjusting this angle monthly according to the wind conditions is further analyzed. These results will help designers improve the design of solar farms by taking into consideration the local weather conditions.
Evaluate the Performance of Vertical and Horizontal Liquefied Natural Gas Storage Tanks by Using a Non-Equilibrium Resistance-Capacitance Model
Authors: Wang Zhihao , Sharafian Amir , Mérida Walter 
Published: January 2020

Abstract
Methane is the primary component of liquefied natural gas (LNG) and a potent greenhouse gas (GHG). The undesired methane emissions across the natural gas supply chain has been proven to worsen the lifecycle GHG emissions from the transportation sector compared with diesel. Therefore, having accurate fast-response models to predict the performance of natural gas infrastructure, such as LNG storage facilities, becomes crucial to minimize methane emissions. In this study, a novel non-equilibrium multi-species thermodynamic model based on the resistance-capacitance network is developed to assess the thermal performance of LNG storage tanks. The accuracy of the non-equilibrium model is validated against the experimental data of a storage tank under dynamic hot gas injection. Then, the model is employed to analyze the performance of two identical vertical and horizontal storage tanks in a refueling station under self-pressurization condition. The results show that the pressure rise in the stationary vertical and horizontal tanks is similar. However, the temperature gradient between the vapor phase and LNG in the horizontal tank is less than that in the vertical tank due to the larger vapor-liquid interface. This feature allows the horizontal tank to reduce the tank pressure faster than the vertical tank under sudden pressure increase.
The Natural Sit-to-Stand-Walk of the Frail
Authors: Taylor Dorothy , Merryweather Andrew , Morse Janice , Wong Bob 
Published: January 2020

Abstract
Sit-to-stand-walk (STW) is a complex task that sequentially transitions an individual from sitting through standing to walking. In this study we evaluate the unrestricted, natural pattern of movement of the STW task from a hospital bed of 21 (5 Female, 16 Male) frail (MFS &gt; 55) adults (68.0±11.2 years) with a total of 144 unique trials. Bed height (low, medium, high) and bed rail condition (no rails, Hill-Rom®, Stryker®), were varied, generating 9 potential trial types per participant. A new STW phase, Stand Preparation, is defined specifically for the frail that occurs just prior to the Flexion Momentum Phase, also named here as the Stand Initiation Phase. In conjunction with the newly defined Stand Preparation Phase, movements used by the frail to maintain or regain balance during STW task are newly defined as corrective behaviors (CBs). These include hand, foot, leg and torso CBs. In 144 unique STW trials, 678 hand and foot CBs were observed and recorded. The most frequent CB type was the hand CB (335), followed by the foot CB (316). A coding system for use in the kinematic analysis of the natural STW task was developed that identifies CBs through visual observation. In addition, a 3D biomechanical model was generated from collected marker position data and will be used in future biomechanical analyses with the visually observed CB data. The Stand Initiation Phase contained the most CBs. Significant factors included bed height and phase, as well as their interaction (all with p-values ≤ 0.006). This is the first study to establish a more accurate and complete STW of the frail elderly, as well as to define CBs employed during their natural STW. The dataset from this coding system, along with the newly established STW phases of the frail, are currently being used for further analyses to determine the exact timing and position of fall initiations during STW of the frail.
An Approach to Bringing Automated Fault Detection and Diagnosis (AFDD) Tools for HVAC&R Into the Mainstream
Authors: Hacker Annika , Gorthala Ravi , Thompson Amy 
Published: January 2020

Abstract
Heating, ventilation and air-conditioning (HVAC) systems can consume over 5 quads of energy annually, representing 30% of energy consumption in the U.S. in commercial buildings. Additionally, commercial refrigeration (R) systems add about 2 quads to commercial buildings energy consumption. Most HVAC systems have one or more faults (low/high refrigerant charge, valve leakage, condenser/evaporator fouling, filter/dryer restriction, economizer faults, controls faults) that result in increased energy consumption. Automated fault detection and diagnosis (AFDD) tools have been developed to address this national issue and many tools are commercially available. AFDD tools have the potential to save considerable energy for existing commercial RTUs, chillers and refrigeration systems. These devices can be used for both retro commissioning, and, when faults are addressed, continuous commissioning as well. However, there appears to be multiple market barriers for this technology. A key market barrier for this technology is the lack of awareness of AFDD products among potential customers. Most HVAC contractors are not familiar with the latest AFDD technologies and HVAC technicians lack skills regarding these technologies. Quantifying potential benefits to building owners is difficult since there are several FDD tools with varying capabilities. For instance, there are several FDD products ranging from handling just economizer faults to those that also handle full-blown refrigerant-side and air-side faults. Methods/algorithms used in FDD vary significantly. Even though there are efforts to develop standards, currently there are no standards/methods to define functions, capabilities, accuracy, and reliability of FDD tools. Moreover, most of the commercial AFDD tools have not been verified in the field independently. This paper presents a comprehensive approach to bringing HVAC AFDD tools into the mainstream. The approach involves demonstrating ten commercially available tools at ten different sites, independent testing and evaluation of the FDD tools, communication with various stakeholders, identifying market barriers, and assisting utility companies in developing incentive programs. This paper presents selection of AFDD tools, site identification, and field testing and evaluation method.
Controlling Evaporation Induced Self-Assembly of Polymeric Nanoparticles: A VOF-DPD Study
Authors: Tayeb Raihan , Zhang Yuwen 
Published: January 2020

Abstract
A mesoscopic simulation method combining multiphase Volume of Fluid (VOF) method and Dissipative Particle Dynamics (DPD) is employed to investigate and control self-assembly of charged polymeric nanoparticles in microdroplet solution deposited on plane substrate during solvent evaporation. A droplet evaporation model is first developed and validated. A coupling scheme between the CFD and the DPD simulation for particles is then presented. The DPD simulation includes the DLVO forces between the particles, their interaction with the substrate surface, Stokes drag, Brownian, and capillary forces. Numerical results show qualitative agreement with available experimental results. The proposed simulation method is expected to provide valuable tools for controlling and optimizing self-assembly of nanoparticles.
Finite Element Microstructural Analysis of Thermal Damage in High Volume Fraction RVE of Particle-Reinforced Refractory Composites
Authors: Makarian Kamran , Santhanam Sridhar 
Published: January 2020

Abstract
Previously, we experimentally studied high-temperature behavior of three types of castable particle-reinforced ceramic composites that we designed for application in aerospace industry. These composites contain Zirconia particles (ZrO2) and bubbles, and silicon-carbide (SiC) particles as reinforcements, dispersed in an alumina (Al2O3) matrix. The present work aims to implement a Finite Element (FE) damage mechanics modeling approach based on the experimental results to investigate micro-scale mechanisms of failure in these materials and ascertain the effect of particle size and volume fraction (VF). Different mechanisms of failure are detected for different types of inclusions, and the percentage of yielded elements seem to strongly correlate with the theoretical thermal shock indices. Additionally, within the limits of this study, VF showed to have a positive correlation with the percentage of yielded elements, whereas inclusion size depicted an inverse correlation to that parameter. These novel findings shed new light on the micro-scale mechanisms of thermal failure in ceramic composites with complex microstructures.
A Feasibility Study of Wind Farm Yaw Angle Optimization
Authors: Kuo Jim , Li Ni , Shen He 
Published: January 2020

Abstract
Wind farm energy production optimization has received significant attention in recent years. Much of this effort had been focused on optimizing positions of wind turbines within a wind farm domain during the design and planning stage. Optimization of wind turbine positions can reduce wake interactions of upstream turbines. In addition to optimizing turbine positions to reduce wake interactions, prior studies have shown that optimizing yaw and pitch angles can improve energy production as upstream wakes yaw away from downstream turbines. However, yaw angle optimization at the wind farm level has been difficult due to lack of low-fidelity wake model for simulating yawed wakes. Recently, an analytical wake model capable of simulating yawed turbine wakes had been developed, which enable wind farm-scale yaw optimization. In this work, a binary quadratic programming model problem formulation has been developed to optimize yaw angles of wind farms. Yaw optimization of two position-optimized layouts available in the literature were performed to study the potential of yaw optimization. In particular, we set out to understand how layout and wind farm density affect yaw optimization potential. An optimized layout of 39 turbines with 40m rotor diameter in a 2km by 2km domain was used in this study. For this wind farm, yawing optimization only improved power production by ∼1.5% under favorable wind directions. However, as wind farm power density increases by increasing rotor diameter to 60m and 80m, power production improved by ∼5% and ∼10% respectively, under favorable wind directions. Finally, another yaw optimization was performed on an optimized layout with 48 turbines of 82m rotor diameter in a 4km by 4km domain using the proposed model formulation. Under favorable wind directions, yaw angle optimization improved performance by ∼4%. The results show that yaw optimization can improve power production in the same order of magnitude as layout optimization, and that it should be considered in addition and/or in tandem to layout optimization.
Autonomous Detection of PV Panels Using a Drone
Authors: Ismail Hesham , Chikte Rufaidah , Bandyopadhyay Akash , Al Jasmi Nawal 
Published: January 2020

Abstract
In recent years, there has been a lot of interest in clean energy especially in solar energy leading to the construction of numerous photovoltaic (PV) panels around the world. These panels need to be inspected to make sure they produce the desired amount of electricity. There are many methods to inspect which are manual, semi-autonomous and fully autonomous. The manual and semi-autonomous already exist but the process is tedious and requires a lot of time and resources. In this paper, we propose a fully autonomous solution where the drone will be preprogrammed to follow certain waypoints inputted via GPS data. The drone is equipped with a thermal camera where the video is recorded for postprocessing. The video is processed offline in order to detect the panels using image processing techniques such as thresholding, binary, canny edge, hough transform, and others. The novelty of this paper is on proposing a fully integrated solution for PV panel detection using a drone; it paves a way for future applications involving machine and deep learning.
Retracted: “Insights Into the Mechanical Properties of Bi-Layer Germanene Coupled by Covalent Bonding” [ASME 2019 International Mechanical Engineering Congress and Exposition, Volume 10: Micro- and Nano-Systems Engineering and Packaging, Salt Lake City, Utah, USA, November 11–14, 2019, Conference Sponsors: ASME, ISBN: 978-0-7918-5947-6, Copyright © 2019 by ASME. Paper No. IMECE2019-12129, pp. V010T12A023; 8 pages; doi: 10.1115/IMECE2019-12129]
Authors: ASME  
Published: January 2020

Abstract
The above referenced paper has been removed from publication. (March 11, 2020)
Copyright © 2020 by ASME
An Experimental Approach in Defect Detection of a Single Row Ball Bearing Using Noise Generation Signal
Authors: Afsharfard Aref , Sanei Seyed Hamid Reza 
Published: January 2020

Abstract
Bearings are critical mechanical components that are used in rotary machinery. Timely detection of defects in such components can prevent catastrophic failure. Noise is generated during the rotation of bearings even without the presence of defects due to finite number of rotating elements to carry the load. Such noise is associated with the change in effective stiffness during rotation, however, a sharp spike is observed in the noise level with presence of local defects. This study uses the noise generation aspect of roller bearings to identify local defect in a single row ball bearing with outer race stationary under radial load. Experimental testing is conducted on two identical bearings. The defective bearing is selected from a diesel engine subjected to 20 years of service. Dissecting the defective bearing revealed pitting and spalling of the inner race and balls, the most two common bearing defects. Both time and frequency analysis of sound pressure generated by the bearings were performed. The results show that there is a clear distinction in the time and frequency spectra between healthy and defective bearings. Findings of this study revealed that using a simple cost efficient in-house experimental setup, local defects can be readily detected.