bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Angle, Temperature and Vacancy Defects on Mechanical Properties of PSI-Graphene
Authors: Xie Lu , Sun Tingwei , He Chenwei , An Haojie , Qin Qin , Peng Qing
Published: May 2019

The PSI-graphene, a two-dimensional structure, was a novel carbon allotrope. In this paper, based on molecular dynamics simulation, the effects of stretching direction, temperature and vacancy defects on the mechanical properties of PSI-graphene were studied. We found that when PSI-graphene was stretched along 0° and 90° at 300 K, the ultimate strength reached a maximum of about 65 GPa. And when stretched along 54.2° and 155.2° at 300 K, the Young’s modulus had peaks, which were 1105 GPa and 2082 GPa, respectively. In addition, when the temperature was raised from 300 K to 900 K, the ultimate strength in all directions was reduced. The fracture morphology of PSI-graphene stretched at different angles was also shown in the text. In addition, the number of points removed from PSI-graphene sheet also seriously affected the tensile properties of the material. It was found that, compared with graphene, PSI-graphene didn’t have the negative Poisson’s ratio phenomenon when it was stretched along the direction of 0°, 11.2°, 24.8° and 34.7°. Our results provided a reference for studying the multi-angle stretching of other carbon structures at various temperatures.
Molecular Structures Polymorphism the Role of F…F Interactions in Crystal Packing of Fluorinated Tosylates
Authors: Arkhipov Dmitry E. , Lyubeshkin Alexander V. , Volodin Alexander D. , Korlyukov Alexander A.
Published: May 2019

The peculiarities of interatomic interactions formed by fluorine atoms were studied in four tosylate derivatives p-CH3C6H4OSO2CH2CF2CF3 and p-CH3C6H4OSO2CH2(CF2)nCHF2 (n = 1, 5, 7) using X-ray diffraction and quantum chemical calculations. Compounds p-CH3C6H4OSO2CH2(CF2)nCHF2 (n = 1, 5) were crystallized in several polymorph modifications. Analysis of intermolecular bonding was carried out using QTAIM approach and energy partitioning. All compounds are characterized by crystal packing of similar type and the contribution of intermolecular interactions formed by fluorine atoms to lattice energy is raised along with the increase of their amount. The energy of intra- and intermolecular F…F interactions is varied in range 0.5–13.0 kJ/mol. Total contribution of F…F interactions to lattice energy does not exceed 40%. Crystal structures of studied compounds are stabilized mainly by C-H…O and C-H…F weak hydrogen bonds. The analysis of intermolecular interactions and lattice energies in polymorphs of p-CH3C6H4OSO2CH2(CF2)nCHF2 (n = 1, 5) has shown that most stabilized are characterized by the least contribution of F…F interactions.
Van der Waals Density Functional Theory vdW-DFq for Semihard Materials
Authors: Peng Qing , Wang Guangyu , Liu Gui-Rong , De Suvranu
Published: May 2019

There are a large number of materials with mild stiffness, which are not as soft as tissues and not as strong as metals. These semihard materials include energetic materials, molecular crystals, layered materials, and van der Waals crystals. The integrity and mechanical stability are mainly determined by the interactions between instantaneously induced dipoles, the so called London dispersion force or van der Waals force. It is challenging to accurately model the structural and mechanical properties of these semihard materials in the frame of density functional theory where the non-local correlation functionals are not well known. Here, we propose a van der Waals density functional named vdW-DFq to accurately model the density and geometry of semihard materials. Using β -cyclotetramethylene tetranitramine as a prototype, we adjust the enhancement factor of the exchange energy functional with generalized gradient approximations. We find this method to be simple and robust over a wide tuning range when calibrating the functional on-demand with experimental data. With a calibrated value q = 1.05 , the proposed vdW-DFq method shows good performance in predicting the geometries of 11 common energetic material molecular crystals and three typical layered van der Waals crystals. This success could be attributed to the similar electronic charge density gradients, suggesting a wide use in modeling semihard materials. This method could be useful in developing non-empirical density functional theories for semihard and soft materials.
Fault Feature Extraction of Hydraulic Pumps Based on Symplectic Geometry Mode Decomposition and Power Spectral Entropy
Authors: Zheng Zhi , Xin Ge
Published: May 2019

Aiming at fault feature extraction of a hydraulic pump signal, a new method based on symplectic geometry mode decomposition (SGMD) and power spectral entropy (PSE) is proposed. First, the SGMD is applied to decompose a multi-component fault signal, then the N symplectic geometry components (SGCs) can be obtained. Second, the N SGCs are reconstructed as a signal of interest and, consequently, the power spectral entropy of each constructed signal is computed to quantify the complexity and uncertainty of their spectra. Finally, the difference value (D-value) between the adjacent entropies is used as a SGCs criterion, whose turning point indicates the most information of reconstructed signal. Hydraulic pump signals are tested and verified, and results demonstrate that the proposed method can extract the richest fault feature information of hydraulic pump signals effectively.
Important Issues in Statistical Testing and Recommended Improvements in Accounting Research
Authors: Dyckman Thomas R. , Zeff Stephen A.
Published: May 2019

A great deal of the accounting research published in recent years has involved statistical tests. Our paper proposes improvements to both the quality and execution of such research. We address the following limitations in current research that appear to us to be ignored or used inappropriately: (1) unaddressed situational effects resulting from model limitations and what has been referred to as “data carpentry,” (2) limitations and alternatives to winsorizing, (3) necessary improvements to relying on a study’s calculated “p-values” instead of on the economic or behavioral importance of the results, and (4) the information loss incurred by under-valuing what can and cannot be learned from replications.
Lessons Learned from the Development of Open Educational Resources at Post-Secondary Level in the Field of Environmental Modelling: An Exploratory Study
Authors: Hassan Quazi K. , Rahaman Khan R. , Sumon Kazi Z. , Dewan Ashraf
Published: May 2019

Open educational resources (OER) have become increasingly popular in recent times. Here, the aim was to synthesise the lessons learned through the development of OER materials for a university-level course called “environmental modelling”. Consequently, the topics of discussion included: (i) how to choose an appropriate creative commons license; (ii) ways of incorporating materials from other sources, such as publicly available sources, other open access materials, and an author’s own published materials if not published under a creative commons license; (iii) the impact of the developed OER in the field of environmental modelling; and (iv) the challenges in developing OER material. Upon developing the materials, we observed the following: (i) students enrolled in the course did not purchase textbooks; (ii) our OER materials ranked as one of the most accessed (i.e., number 7) materials according to the usage data that summed the number of file downloads and item views from PRISM (i.e., the hosting platform maintained by the University of Calgary); (iii) the students learned relatively better as per the data acquired by the University of Calgary’s universal student ratings of instruction (USRI) instrument; and (iv) other universities expressed interest in adopting the materials.
Analytical Gate Delay Variation Model with Temperature Effects in Near-Threshold Region Based on Log-Skew-Normal Distribution
Authors: Guo Jingjing , Cao Peng , Wu Jiangping , Liu Zhiyuan , Yang Jun
Published: May 2019

The near-threshold design is widely employed in the energy-efficient circuits, but it suffers from a high sensitivity to process variation, which leads to 2X delay variation due to temperature effects. Hence, it is not negligible. In this paper, we propose an analytical model for gate delay variation considering temperature effects in the near-threshold region. The delay variation model is constructed based on the log-skew-normal distribution by moment matching. Moreover, to deal with complex gates, a multi-variate threshold voltage approximation approach of stacked transistors is proposed. Also, three delay metrics (delay variability, ± 3 σ percentile points) are quantified and have a comparison with other known works. Experimental results show that the maximum of delay variability is 5% compared with Monte Carlo simulation and improves 5X in stacked gates compared with lognormal distribution. Additionally, it is worth mentioning that, the proposed model exhibits excellent advantages on − 3 σ and stacked gates, which improves 5X–10X in accuracy compared with other works.
A Novel Medical Blockchain Model for Drug Supply Chain Integrity Management in a Smart Hospital
Authors: Jamil Faisal , Hang Lei , Kim KyuHyung , Kim DoHyeun
Published: May 2019

At present, in pharmacology one of the most serious problems is counterfeit drugs. The Health Research Funding organization reported that in developing countries, nearly 10–30% of the drugs are fake. Counterfeiting is not the main issue itself, but, rather, the fact that, as compared to traditional drugs, these counterfeit drugs produce different side effects to human health. According to WHO, around 30% of the total medicine sold in Africa, Asia, and Latin America is counterfeit. This is the major worldwide problem, and the situation is worse in developing countries, where one out of every 10 medicines are either fake or do not follow drug regulations. The rise of Internet pharmacies has made it more difficult to standardize drug safety. It is difficult to detect counterfeits because these drugs pass through different complex distributed networks, thus forming opportunities for counterfeits to enter the authentic supply chain. The safety of the pharmaceutical supply chain has become a major concern for public health, which is a collective process. In this paper, we propose a novel drug supply chain management using Hyperledger Fabric based on blockchain technology to handle secure drug supply chain records. The proposed system solves this problem by conducting drug record transactions on a blockchain to create a smart healthcare ecosystem with a drug supply chain. A smart contract is launched to give time-limited access to electronic drug records and also patient electronic health records. We also carried out a number of experiments in order to demonstrate the usability and efficiency of the designed platform. Finally, we used Hyperledger Caliper as a benchmarking tool to conduct the performance of the designed system in terms of transactions per second, transaction latency, and resource utilization.
Active Virtual Impedance Control for Sound-Following Robots to Avoid Obstacles
Authors: Han Jong-Ho , Kim Dong-Hyun , Hwang Myeong-Hwan , Lee Gye-Seong , Cha Hyun-Rok
Published: May 2019

A novel active virtual impedance algorithm is here proposed to help sound-following robots avoid obstacles while tracking a sound source. The tracking velocity of a mobile robot to a sound source is determined by virtual repulsive and attraction forces to avoid obstacles and to follow the sound source, respectively. Active virtual impedance is defined as a function of distances and relative velocities to the sound source and obstacles from the mobile robot, which is used to generate the tracking velocity of the mobile robot. Conventional virtual impedance methods have fixed coefficients for relative distances and velocities. However, in this research, the coefficients are dynamically adjusted to extend the obstacle avoidance performance to multiple obstacle environments. The relative distances and velocities are obtained using a microphone array consisting of three microphones in a row. The geometrical relationships of the microphones are utilized to estimate the relative position and orientation of the sound source with respect to the mobile robot, which carries the microphone array. The effectiveness of the proposed algorithm is demonstrated by experiments.
Radiation Properties of Conformal Antennas: The Elliptical Source
Authors: Leone Giovanni , Munno Fortuna , Pierri Rocco
Published: May 2019

The solution of inverse source problems by numerical procedures requires the investigation of the number of independent pieces of information that can be reconstructed stably. To this end, the mathematical properties of the relevant operators are to be examined in connection with the source shape. The aim of this work is to investigate the effect of the source shape on the eigendecomposition of the radiation operator in a 2D geometry, when the radiated field is observed over a semi-circumference in the far zone. We examine both the behavior of the eigenvalues and the effect of the choice of the representation variables on the point spread function (PSF). In particular, the effect of the choice of the representation variables is considered since operator properties may depend on it. We analyze different source shapes evolving from a line to a semi-ellipse and, finally, to a semi-circumference, in order to understand how the increase of the source aspect ratio affects the results. The main conclusions concern an estimate of the number of degrees of freedom in connection with the source geometry and the fact that the PSF exhibits the same variant behavior along the considered domain, independently of the observation variable. The practical relevance of the result is illustrated by two numerical examples. The first one deals with the conformal array diagnostics for the reliable reconstruction of the excitation of the array elements. The second one concerns the array synthesis problem, and a comparison between the radiating performances of the source geometries is presented.
Regularized Auto-Encoder-Based Separation of Defects from Backgrounds for Inspecting Display Devices
Authors: Jo Heeyeon , Kim Jeongtae
Published: May 2019

We investigated a novel method for separating defects from the background for inspecting display devices. Separation of defects has important applications such as determining whether the detected defects are truly defective and the quantification of the degree of defectiveness. Although many studies on estimating patterned background have been conducted, the existing studies are mainly based on the approach of approximation by low-rank matrices. Because the conventional methods face problems such as imperfect reconstruction and difficulty of selecting the bases for low-rank approximation, we have studied a deep-learning-based foreground reconstruction method that is based on the auto-encoder structure with a regression layer for the output. In the experimental studies carried out using mobile display panels, the proposed method showed significantly improved performance compared to the existing singular value decomposition method. We believe that the proposed method could be useful not only for inspecting display devices but also for many applications that involve the detection of defects in the presence of a textured background.
Fuzzy System and Time Window Applied to Traffic Service Network Problems under a Multi-Demand Random Network
Authors: Huang Chia-Ling , Huang Sin-Yuan , Yeh Wei-Chang , Wang Jinhai
Published: May 2019

The transportation network promotes key human development links such as social production, population movement and resource exchange. As cities continue to expand, transportation networks become increasingly complex. A bad traffic network design will affect the quality of urban development and cause regional economic losses. How to plan transportation routes and allocate transportation resources is an important issue in today’s society. This study uses the network reliability method to solve traffic network problems. Network reliability refers to the probability of a successful connection between the source and sink nodes in the network. There are many systems in the world that use network architecture; therefore, network reliability is widely used in various practical problems and cases. In the past, some scholars have used network reliability to solve traffic service network problems. However, the processing of time is not detailed enough to fully express the real user’s time requirements and does not consider that the route traffic will affect the reliability of the entire network. This study improves on past network reliability methods by using a fuzzy system and a time window to construct a network model. Using the concept of fuzzy systems, according to past experience, data or expert predictions to define the degree of flow, time and reliability, can also determine the relationship between these factors. The time window can be adjusted according to the time limit in reality, reaching the limit of the complete expression time. In addition, the network reliability algorithm used in this study is a direct algorithm. Compared with the past indirect algorithms, the computation time is greatly reduced and complex problems can be solved more efficiently.
Design for Reliability: The Case of Fractional-Slot Surface Permanent-Magnet Machines
Authors: Torreggiani Ambra , Bianchini Claudio , Davoli Matteo , Bellini Alberto
Published: May 2019

Surface permanent-magnet machines are widely used in different applications, from industrial automation to home appliance and electrical traction. Among any possible machine topology, the fractional-slot surface permanent-magnet one has gained increasing importance, because of its high torque density, low cogging torque, extended flux weakening capability and high efficiency. In addition, fractional-slot machines are attractive for tooth concentrated windings, which allow some optimized manufacturing solutions such as modular stator tooth and high slot filling factor, which result in copper volume reduction; cost reduction, and lower stator parasitic resistances. The slot–pole combination is one of the most important design parameter and, as shown in this paper, it affects performances and the robustness of the machine with respect to the manufacturing imperfections. In the literature, slot–pole combinations are optimized at design phase by finite-element analysis relying on a healthy machine model. The original contribution of this paper is a design for reliability method that models manufacturing defects and includes them at design phase in the optimization process of slot–pole combinations. A method is presented that allows defining the optimal design parameters for maximum performances and robustness towards unavoidable imperfections caused by tolerances of the manufacturing process.
A Multi-Objective Optimization Model for a Non-Traditional Energy System in Beijing under Climate Change Conditions
Authors: Ding Xiaowen , Liu Lin , Huang Guohe , Xu Ye , Guo Junhong
Published: May 2019

In recent years, with the increase of annual average temperature and the decrease of annual precipitation in Beijing, the fragility of Beijing’s energy system has become more and more prominent, especially the balance of electricity supply and demand in extreme weather. In the context of unstable supply of new and renewable energies, it is imperative to strengthen the ability of the energy system to adapt to climate change. This study first simulated climate change in Beijing based on regional climate data. At the same time, the Statistical Program for Social Sciences was used to perform multiple linear regression analysis on Beijing’s future power demand and to analyze the impact of climate change on electricity supply in both the RCP4.5 and RCP8.5 (representative concentration pathway 4.5 and 8.5) scenarios. Based on the analysis of the impact of climate change on energy supply, a multi-objective optimization model for new and renewable energy structure adjustment combined with climate change was proposed. The model was then used to predict the optimal power generation of the five energy types under different conditions in 2020. Through comparison of the results, it was found that the development amount and development ratio of various energy forms underwent certain changes. In the case of climate change, the priority development order of new and renewable energies in Beijing was: external electricity > other renewable energy > solar energy > wind energy > biomass energy. The energy structure adjustment program in the context of climate change will contribute to accelerating the development and utilization of new and renewable energies, alleviating the imbalance between power supply and demand and improving energy security.
Sensors Fault Diagnosis and Active Fault-Tolerant Control for PMSM Drive Systems Based on a Composite Sliding Mode Observer
Authors: Zhu Qinyue , Li Zhaoyang , Tan Xitang , Xie Dabo , Dai Wei
Published: May 2019

Due to the use of multiple observers and controllers in multi-sensor fault-tolerant control of PMSM drive systems, the algorithm is complex and the system control performance is affected. In view of this, the paper studies multi-sensor fault diagnosis and active fault-tolerant control strategies based on a composite sliding mode observer. With the mathematical model of PMSM built, a design method of the composite sliding mode observer is proposed. A single observer is used to observe and estimate various state variables in the system in real time, which simplifies the implementation of observer-related algorithms. In order to improve the diagnostic accuracy of different types of sensors under different faults, a method for determining fault thresholds is proposed through global search for the maximum residual value. Based on this, a fault diagnosis and active fault-tolerant control strategy is proposed to realize fast switching and reconstruction of feedback signals of closed-loop control systems under different faults of multiple sensors, thus restoring the system performance. Finally, the effectiveness of the proposed algorithm and control strategy is verified by simulation experiments
Oscillating Heat Pipe Cooling System of Electric Vehicle’s Li-Ion Batteries with Direct Contact Bottom Cooling Mode
Authors: Chi Ri-Guang , Rhi Seok-Ho
Published: May 2019

Recently, the use of electrical vehicles has abruptly increased due to environmental crises. The high energy density of lithium-ion batteries is their main advantage for use in electric vehicles (EVs). However, the thermal management of Li-ion batteries is a challenge due to the poor heat resistance of Lithium ions. The performance and lifetime of lithium ion batteries are strongly affected by the internal operating temperature. Thermal characterization of battery cells is very important to ensure the consistent operation of a Li-ion battery for its application. In the present study, the OHP (Oscillating Heat Pipe) system is proposed as a battery cooling module, and experimental verification was carried out. OHP is characterized by a long evaporator section, an extremely short condenser section, and almost no adiabatic section. Experimental investigations were conducted using various parameters such as the filling ratio, orientation, coolant temperature, and heat flux. Average temperature of the heater’s surface was maintained at 56.4 °C using 14 W with 25 °C coolant water. The experimental results show that the present cooling technology basically meets the design goal of consistent operation.
A Fault Detection Method for Photovoltaic Systems Based on Voltage and Current Observation and Evaluation
Authors: Pei Tingting , Hao Xiaohong
Published: May 2019

Photovoltaic (PV) power generation systems work chronically in various climatic outdoor conditions, therefore, faults may occur within the PV arrays in PV systems. Online fault detection for the PV arrays are important to improve the system’s reliability, safety and efficiency. In view of this, a fault-detection method based on voltage and current observation and evaluation is presented in this paper to detect common PV array faults, such as open-circuit, short-circuit, degradation and shading faults. In order to develop this detection method, fault characteristic quantities (e.g., the open-circuit voltage, short-circuit current, voltage and current at the maximum power point (MPP) of the PV array) are identified first to define the voltage and current indicators; then, the fault-detection thresholds are defined by utilizing voltage and current indicators according to the characteristic information of various faults; finally, voltage and current indicators evaluated at real-time voltage and current data are compared with the corresponding thresholds to detect potential faults and fault types. The performances of the proposed method are simulated verifying by setting eight different fault patterns in the PV array. Simulation experimental results show the effectiveness of the proposed method, especially the capacities of distinguishing the degradation faults, partial shading faults and variable shading faults.
Microalgal-Based Carbon Sequestration by Converting LNG-Fired Waste CO2 into Red Gold Astaxanthin: The Potential Applicability
Authors: Hong Min Eui , Chang Won Seok , Patel Anil Kumar , Oh Mun Sei , Lee Jong Jun , Sim Sang Jun
Published: May 2019

The combinatorial approach of anthropogenic activities and CO2 sequestration is becoming a global research trend to alleviate the average global temperature. Although microalgae have been widely used to capture CO2 from industrial flue gas, the application of bioproducts was limited to bioenergy due to the controversy over the quality and safety of the products in the food and feed industry. Herein, the waste CO2 emitted from large point sources was directly captured using astaxanthin-hyperproducing microalgae Haematococcus pluvialis. Astaxanthin production was successfully carried out using the hypochlorous acid water-based axenic culture process under highly contamination-prone outdoor conditions. Consequently, after 36 days of autotrophic induction, the productivity of biomass and astaxanthin of H. pluvialis (the mutant) reached 0.127 g L−1 day−1 and 5.47 mg L−1 day−1 under high summer temperatures, respectively, which was 38% and 48% higher than that of wild type cell. After grinding the wet astaxanthin-enriched biomass, the extract was successfully approved by compliance validation testing from Korea Food and Drug Administration. The assorted feed improved an immune system of the poultry without causing any side effects. The flue gas-based bioproducts could certainly be used for health functional food for animals in the future.
A Three-Zone Scavenging Model for Large Two-Stroke Uniflow Marine Engines Using Results from CFD Scavenging Simulations
Authors: Foteinos Michael I. , Papazoglou Alexandros , Kyrtatos Nikolaos P. , Stamatelos Anastassios , Zogou Olympia , Stamatellou Antiopi-Malvina
Published: May 2019

The introduction of modern aftertreatment systems in marine diesel engines call for accurate prediction of exhaust gas temperature, since it significantly affects the performance of the aftertreatment system. The scavenging process establishes the initial conditions for combustion, directly affecting exhaust gas temperature, fuel economy, and emissions. In this paper, a semi-empirical zero-dimensional three zone scavenging model applicable to two-stroke uniflow scavenged diesel engines is updated using the results of CFD (computational fluid dynamics) simulations. In this 0-D model, the engine cylinders are divided in three zones (thermodynamic control volumes) namely, the pure air zone, mixing zone, and pure exhaust gas zone. The entrainment of air and exhaust gas in the mixing zone is specified by time varying mixing coefficients. The mixing coefficients were updated using results from CFD simulations based on the geometry of a modern 50 cm bore large two-stroke marine diesel engine. This increased the model’s accuracy by taking into account 2-D fluid dynamics phenomena in the cylinder ports and exhaust valve. Thus, the effect of engine load, inlet port swirl angle and partial covering of inlet ports on engine scavenging were investigated. The three-zone model was then updated and the findings of CFD simulations were reflected accordingly in the updated mixing coefficients of the scavenging model.
Image Recognition of Coal and Coal Gangue Using a Convolutional Neural Network and Transfer Learning
Authors: Pu Yuanyuan , Apel Derek B. , Szmigiel Alicja , Chen Jie
Published: May 2019

Recognizing and distinguishing coal and gangue are essential in engineering, such as in coal-fired power plants. This paper employed a convolutional neural network (CNN) to recognize coal and gangue images and help segregate coal and gangue. A typical workflow for CNN image recognition is presented as well as a strategy for updating the model parameters. Based on a powerful trained image recognition model, VGG16, the idea of transfer learning was introduced to build a custom CNN model to solve the problems of massive trainable parameters and limited computing power linked to the building of a brand-new model from scratch. Two hundred and forty coal and gangue images were collected in a database, including 100 training images and 20 validation images for each material. A recognition accuracy of 82.5% was obtained for the validation images, which demonstrated a decent performance of our model. According to the analysis of parameter updating in the training process, a principal constraint for obtaining a higher recognition accuracy mainly resided in a shortage of training samples. This model was also used to identify photos from a washing plant stockpiles, which verified its capability of dealing with field pictures. CNN combined with the transfer learning method we used can provide fast and robust coal/gangue distinction that does not require harsh data support and equipment support. This method will exhibit brighter prospects in engineering if the target image database (as with the coal and gangue images in this study) can be further enlarged.
Five-Level T-type Cascade Converter for Rooftop Grid-Connected Photovoltaic Systems
Authors: Verdugo Cristian , Kouro Samir , Rojas Christian A. , Perez Marcelo A. , Meynard Thierry , Malinowski Mariusz
Published: May 2019

Multilevel converters are widely considered to be the most suitable configurations for renewable energy sources. Their high-power quality, efficiency and performance make them interesting for PV applications. In low-power applications such as rooftop grid-connected PV systems, power converters with high efficiency and reliability are required. For this reason, multilevel converters based on parallel and cascaded configurations have been proposed and commercialized in the industry. Motivated by the features of multilevel converters based on cascaded configurations, this work presents the modulation and control of a rooftop single-phase grid-connected photovoltaic multilevel system. The configuration has a symmetrical cascade connection of two three-level T-type neutral point clamped power legs, which creates a five-level converter with two independent string connections. The proposed topology merges the benefits of multi-string PV and symmetrical cascade multilevel inverters. The switching operation principle, modulation technique and control scheme under an unbalanced power operation among the cell are addressed. Simulation and experimental validation results in a reduced-scale power single-phase converter prototype under variable conditions at different set points for both PV strings are presented. Finally, a comparative numerical analysis between other T-type configurations to highlight the advantages of the studied configuration is included.
Optimizing the Regulation of Aggregated Thermostatically Controlled Loads by Jointly Considering Consumer Comfort and Tracking Error
Authors: Yang Jie , Liu Tongyu , Wang Huaibao , Tian Zhenhua , Liu Shihao
Published: May 2019

Thermostatically controlled loads (TCLs) are promising to offer demand-side regulation with proper control. In this paper, the aggregate power of TCLs is used to track the automatic generation control (AGC) signal by changing the temperature setpoint. The dynamics of the indoor temperature are described by a Monte Carlo model, and population dissatisfaction is described by the predicted percentage of dissatisfied (PPD). The objective is optimization from two aspects, minimizing both population dissatisfaction and tracking error. We propose an improved active target particle swarm optimization (APSO) algorithm to optimize the model, making it possible to ensure that the user’s dissatisfaction is as small as possible while the aggregate power tracks the AGC signal. The novelty of this paper is to introduce PPD into the model and at the same time establish three models using PPD as the objective function and constraints. The simulation results are shown to verify the efficiency of the designed model.
Optimization of a Power Line Communication System to Manage Electric Vehicle Charging Stations in a Smart Grid
Authors: Carcangiu Sara , Fanni Alessandra , Montisci Augusto
Published: May 2019

In this paper, a procedure is proposed to design a power line communication (PLC) system to perform the digital transmission in a distributed energy storage system consisting of fleets of electric cars. PLC uses existing power cables or wires as data communication multicarrier channels. For each vehicle, the information to be transmitted can be, for example: the models of the batteries, the level of the charge state, and the schedule of charging/discharging. Orthogonal frequency division multiplexing modulation (OFDM) is used for the bit loading, whose parameters are optimized to find the best compromise between the communication conflicting objectives of minimizing the signal power, maximizing the bit rate, and minimizing the bit error rate. The off-line design is modeled as a multi-objective optimization problem, whose solution supplies a set of Pareto optimal solutions. At the same time, as many charging stations share part of the transmission line, the optimization problem includes also the assignment of the sub-carriers to the single charging stations. Each connection between the control node and a charging station has its own frequency response and is affected by a noise spectrum. In this paper, a procedure is presented, called Chimera, which allows one to solve the multi-objective optimization problem with respect to a unique frequency response, representing the whole set of lines connecting each charging station with the central node. Among the provided Pareto solutions, the designer will make the final decision based on the control system requirements and/or the hardware constraints.
DEA Non-Radial Approach for Resource Allocation and Energy Usage to Enhance Corporate Sustainability in Japanese Manufacturing Industries
Authors: Sueyoshi Toshiyuki , Goto Mika
Published: May 2019

This article discusses how to enhance corporate sustainability by simultaneously measuring operational and environment achievements. In past decades, most companies have made steady efforts to enhance their sustainability levels. However, they still have strategic space for improving sustainability. This research proposes a new use of environmental measurement by data envelopment analysis. We apply the approach to Japanese industrial sectors and obtain five implications. First, they maintain a high level of unified efficiency on resource allocation and energy usage under natural disposability (priority: operation). Second, the efficiency under managerial one (priority: environment) is generally lower than that of natural disposability. Third, among the industries with high operational achievement, only the pharmaceutical product industry presents high attainment on environmental protection. Fourth, the pulp and paper industry as well as the textile product industry have a potential for efficiency improvement by investing in green technology. Finally, desirable congestion indicates a potential of performance improvement by investing in green technology. Those results imply that the current business situation is different from the previous image on Japanese industries, often referred to as “Japan Inc.”, where all firms used to operate like a single entity under the governmental regulation.
How Big Is an Error in the Analytical Calculation of Annular Fin Efficiency?
Authors: Bošnjaković Mladen , Muhič Simon , Čikić Ante , Živić Marija
Published: May 2019

An important role in the dimensioning of heat exchange surfaces with an annular fin is the fin efficiency. The fin efficiency is usually calculated using analytical expressions developed in the last century. However, these expressions are derived with certain assumptions and simplifications that involve a certain error in the calculation. The purpose of this paper is to determine the size of the error due to the assumptions and simplifications made when performing the analytical expression and to present what has the greatest impact on the amount of error, and give a recommendation on how to reduce that error. In order to determine the error, but also to gain a more detailed insight into the physics of heat exchange processes on the fin surface, computational fluid dynamics was applied to the original definition of fin efficiency. This means that a numerical simulation was performed for the actual fin material and for the ideal fin material with infinite thermal conductivity for the selected fin geometry and Re numbers from 2000 to 18,000. The results show that fin efficiency determined by numerical simulations is greater by up to 12.3% than the efficiency calculated analytically. The greatest impact on the amount of error is the assumption of the same temperature of the fin base surface and the outer tube surface and the assumption of equal heat transfer coefficient on the entire fin surface area. Using a newly recommended expression for the equivalent length of the fin tip, it would be possible to calculate the fin efficiency more precisely and thus the average heat transfer coefficient on the fin surface area, which leads to a more accurate dimensioning of the heat exchanger.
Q-Learning-Based Operation Strategy for Community Battery Energy Storage System (CBESS) in Microgrid System
Authors: Bui Van-Hai , Hussain Akhtar , Kim Hak-Man
Published: May 2019

Energy management systems (EMSs) of microgrids (MGs) can be broadly categorized as centralized or decentralized EMSs. The centralized approach may not be suitable for a system having several entities that have their own operation objectives. On the other hand, the use of the decentralized approach leads to an increase in the operation cost due to local optimization. In this paper, both centralized and decentralized approaches are combined for managing the operation of a distributed system, which is comprised of an MG and a community battery storage system (CBESS). The MG is formed by grouping all entities having the same operation objective and is operated under a centralized controller, i.e., a microgrid EMS (MG-EMS). The CBESS is operated by using its local controller with different operation objectives. A Q-learning-based operation strategy is proposed for optimal operation of CBESS in both grid-connected and islanded modes. The objective of CBESS in the grid-connected mode is to maximize its profit while the objective of CBESS in islanded mode is to minimize the load shedding amount in the entire system by cooperating with the MG. A comparison between the Q-learning-based strategy and a conventional centralized-based strategy is presented to show the effectiveness of the proposed strategy. In addition, an adjusted epsilon is also introduced for epsilon-greedy policy to reduce the learning time and improve the operation results.
Development and Assessment of Two-Stage Thermoacoustic Electricity Generator
Authors: Hamood Ahmed , Jaworski Artur J. , Mao Xiaoan
Published: May 2019

This paper presents the development and assessment of a two-stage thermoacoustic electricity generator that aims to mimic the conversion of waste heat from the internal combustion engine exhaust gases into useful electricity. The one wavelength configuration consists of two identical stages which allow coupling a linear alternator in a “push-pull” mode because of the 180° out of phase acoustic excitation on two sides of the piston. This type of coupling is a possible solution for the low acoustic impedance of looped-tube traveling-wave thermoacoustic engines. The experimental set-up is 16.1 m long and runs at 54.7 Hz. The working medium is helium at maximum pressure of 28 bar. In practice, the maximum generated electric power was 73.3 W at 5.64% thermal-to-electric efficiency. The working parameters, namely load resistance, mean pressure and heating power, were investigated. System debugging illustrates the effect of local acoustic impedance of the regenerator on the start-up process of the thermoacoustic engine. The additional modelling showed that the feedback loop length can be reduced by using a combination of acoustic inertance and compliance components.
Current Policy and Technology for Tidal Current Energy in Korea
Authors: Ko Dong-Hui , Chung Jaekwan , Lee Kwang-Soo , Park Jin-Soon , Yi Jin-Hak
Published: May 2019

As global energy consumption continues to increase, the negative impact of global warming also grows. Therefore, eco-friendly energy policy is being established all over the world. Korea’s energy consumption problems are further complicated by the country’s high dependence on energy sourced overseas. Korean energy policy is evolving rapidly to address these problems. Korea has begun to phase out nuclear power and is focusing on developing new sources of renewable energy. So there has been substantial interest in the development of ocean energy. Of all ocean energy technologies, tidal current energy is the closest to the commercialization. Especially, the southwestern coast of Korea is the most promising candidate site for the development of tidal current energy owing to the abundant tidal current energy resource. Meanwhile, ocean energy policy is an important factor in determining the development of ocean energy. Thus, this paper presents the overview of the current status of policy and technology for the tidal current energy system in Korea. These policies explained in this paper can provide significant interest and motivation for the use of tidal current energy resources.
Combination Optimization Configuration Method of Capacitance and Resistance Devices for Suppressing DC Bias in Transformers
Authors: Wang Donghui , Liu Chunming
Published: May 2019

The ground current of a high-voltage direct current (HVDC) transmission system can cause DC bias in transformers near the grounding electrode during monopole operations, which affects the alternating current (AC) power system operation. Owing to multiple bias current flow paths, a capacitance blocking device installed at the neutral point of a transformer may increase the DC bias in adjacent transformers, while suppressing the DC current in that transformer. This paper introduces the use of an effective bias current indicator to describe the effect of the grounding current on transformers in a network, considering the wiring characteristics of the autotransformers and the power system topology. Additionally, a combination optimization method for the capacitance and resistance is applied in order to determine the minimum number of installed devices that restrict the maximum effective bias current throughout the network to a permissible range. A genetic algorithm based on an improved roulette selection method is adopted to solve the optimal configuration problem. The method is validated by using a test case based on the Xizhe HVDC transmission receiving-end grid near the Jinsi grounding electrode. The configuration of the capacitance and resistance was optimized by the improved genetic algorithm. This method can achieve the desired level of DC bias management with fewer devices than the conventional method, which verifies the feasibility and superiority of the proposed optimization method.
Composite Estimators for Forest Growth Derived from Symmetric, Varying-Length Observation Intervals
Authors: Roesch Francis A.
Published: May 2019

Estimates of growth or change in a forest population parameter for a specific length of time, such as cubic meters of wood per hectare per year, are often made from sample observation intervals of different lengths of time. For instance, a basic building block of growth estimators in forest inventory systems is often the annual mean of the first differences of all observations for a particular year, regardless of observation interval length. The aggregate differences between successive observations on re-measured forest sample plots can be viewed as a linear combination, while forest growth is usually assumed to be non-linear. Bias can be assumed to exist whenever a linear combination is used to estimate a specific segment of an underlying non-linear trend. The amount of bias will depend upon the relationship of the intended estimation interval relative to the set of observation intervals. Here, three specific segments, relative to each year of interest, form the bases for a standard set of three estimands. Bias-ratio-adjusted composite estimators for use with observations made on alternative sets of symmetric interval lengths are compared in a simulation against this standard set of estimands. The first estimand has a one-year basis, the second has a five-year mid-interval basis, and the third has a five-year end-of-period basis. For the first and second bases, the initial results clearly show a logical ordering of bias and mean-squared error by observation interval length relative to the target interval length. As expected, some deviance from these clear trends are shown for the end-of-period basis. In the presence of three simple distributions of symmetric measurement intervals, the bias-ratio adjustments and subsequent composite estimators are shown to usually be effective in reducing bias and mean-squared error, while being most obviously effective for the most disparate distribution of intervals and for the end-of-period basis.
History of the Environmental Seismic Intensity Scale ESI-07
Authors: Serva Leonello
Published: May 2019

This brief note aims to describe the history, from its early original idea, of the new macroseismic scale: The Environmental Seismic Intensity Scale 2007 (ESI 2007). It can be used together with other existing scales or alone when needed for measuring the intensity of an earthquake on the basis of the primary and secondary effects of a seismic event on the natural environment. These effects could be the major sources of earthquake hazards, as recently proved. This note also aims to contribute to the understanding of processes that induced the researcher to develop an idea, to pursue it, and bring it to its end, first through the help of valuable Italian researchers and then through the constructive exchange of ideas with researchers of different cultural backgrounds operating almost everywhere in the world. This note is sponsored and approved by the International Union for Quaternary Research (INQUA), and the Environmental Seismic Intensity scale (ESI-07) was published in 2007 after a revision process of about eight years.