bluuebunny/crossref_metadata_2025 huggingface dataset:
Categorization of South Tyrolean Built Heritage with Consideration of the Impact of Climate
Authors: Hao Lingjun , Herrera-Avellanosa Daniel , Del Pero Claudio , Troi Alexandra
Published: December 2019

Climate change imposes great challenges on the built heritage sector by increasing the risks of energy inefficiency, indoor overheating, and moisture-related damage to the envelope. Therefore, it is urgent to assess these risks and plan adaptation strategies for historic buildings. These activities must be based on a strong knowledge of the main building categories. Moreover, before adapting a historic building to future climate, it is necessary to understand how the past climate influenced its design, construction, and eventual categories. This knowledge will help when estimating the implication of climate change on historic buildings. This study aims at identifying building categories, which will be the basis for further risk assessment and adaptation plans, while at the same time analyzing the historical interaction between climate and human dwelling. The results show some correlations between building categories and climate. Therefore, it is necessary to use different archetypes to represent the typical buildings in different climate zones. Moreover, these correlations imply a need to investigate the capability of the climate-responsive features in future climate scenarios and to explore possible further risks and adaptation strategies.
Influences of Oxygen Ion Beam on the Properties of Magnesium Fluoride Thin Film Deposited Using Electron Beam Evaporation Deposition
Authors: Zhang Gong , Fu Xiuhua , Song Shigeng , Guo Kai , Zhang Jing
Published: December 2019

Magnesium fluoride (MgF2) materials are commonly used for near/medium infrared anti-reflection optical coatings due to their low refractive index and wide-range transparency. Ion assistant deposition is an important technique to increase the density of MgF2 and reduce absorption around 2.94 µm caused by high porosity and moisture adsorption. However, the excessive energy of Argon ion will induce a color center and; therefore, lead to UV/Visible absorption. In this paper, oxygen ion was introduced to reduce the color center effect in MgF2 thin film deposited using electron beam evaporation with ion assistant. The films were deposited on Bk7 and single crystal silicon substrates under various oxygen ion beam currents. The microstructure, optical constant, film density, stress, and adhesion are investigated, including the absorption properties at the infrared hydroxyl (–OH) vibration peak. The results show that as the oxygen ion beam current increases, the absorption value at the position of the infrared OH vibration, defects, and stress of the film decrease, while the refractive index increases. However, MgF2 has poor adhesion using oxygen ion-assisted deposition. Thin MgF2 film without ion beam assistant was used as adhesive layer, high density, and low absorption MgF2 film with good adhesion was obtained.
Microstructure, Mechanical Properties and Wear Behavior of High-Velocity Oxygen-Fuel (HVOF) Sprayed (Cr3C2-NiCr+Al) Composite Coating on Ductile Cast Iron
Authors: Ksiazek Marzanna , Boron Lukasz , Tchorz Adam
Published: December 2019

In the present work Cr3C2-NiCr powder containing Al particles was deposited on ductile cast iron with high-velocity oxy-fuel (HVOF) thermal spray coating technique. An investigation was conducted to determine the role of Al particles in the Cr3C2-NiCr coating produced with HVOF technique on microstructure, mechanical and wear properties in a system Cr2C3-NiCr coating/ductile cast iron. The microstructure of the HVOF-sprayed Cr3C2-NiCr+Al coating was characterized by light microscopy, X-ray diffraction (XRD), scanning electron microscope (SEM), transmission electron microscope (TEM) and energy dispersive X-ray spectroscopy (EDS). Microstructure analysis reveals the formation of coating with low porosity, good adhesion to the substrate and dense structure with irregularly shaped particles of Al arranged in strips and finely fragmented Cr3C2 particles embedded in a nanocrystalline Ni-Cr alloy matrix. In addition, the results were discussed in reference to examination of bending strength considering cracking and delamination in the system of (Cr3C2-NiCr+Al)/ductile cast iron as well as microhardness and wear resistance of the coating. It was found that the addition of Al particles significantly increased resistance to cracking and wear behaviour in the studied system.
Liquid Crystal-Based Enclosed Coplanar Waveguide Phase Shifter for 54–66 GHz Applications
Authors: Li Jinfeng , Chu Daping
Published: December 2019

A 0–10 V bias voltage-driven liquid crystal (LC) based 0°–180° continuously variable phase shifter was designed, fabricated, and measured with insertion loss less than −4 dB across the spectrum from 54 GHz to 66 GHz. The phase shifter was structured in an enclosed coplanar waveguide (ECPW) with LC as tunable dielectrics encapsulated by a unified ground plate in the design, which significantly reduced the instability due to floating effects and losses due to stray modes. By competing for spatial volume distribution of the millimeter-wave signal occupying lossy tunable dielectrics versus low-loss but non-tunable dielectrics, the ECPW’s geometry and materials are optimized to minimize the total of dielectric volumetric loss and metallic surface loss for a fixed phase-tuning range. The optimized LC-based ECPW was impedance matched with 1.85 mm connectors by the time domain reflectometry (TDR) method. Device fabrication featured the use of rolled annealed copper foil of lowest surface roughness with nickel-free gold-plating of optimal thickness. Measured from 54 GHz to 66 GHz, the phase shifter prototype presented a tangible improvement in phase shift effectiveness and signal-to-noise ratio, while exhibiting lower insertion and return losses, more ease of control, and high linearity as well as lower-cost fabrication as compared with up-to-date documentations targeting 60 GHz applications.
Crystal Structure of Bacterial Cystathionine Γ-Lyase in The Cysteine Biosynthesis Pathway of Staphylococcus aureus
Authors: Lee Dukwon , Jeong Soyeon , Ahn Jinsook , Ha Nam-Chul , Kwon Ae-Ran
Published: December 2019

Many enzymes require pyridoxal 5’-phosphate (PLP) as an essential cofactor and share active site residues in mediating diverse enzymatic reactions. Methionine can be converted into cysteine by cystathionine γ-lyases (CGLs) through a transsulfuration reaction dependent on PLP. In bacteria, MccB, also known as YhrB, exhibits CGL activity that cleaves the C–S bond of cystathionine at the γ position. In this study, we determined the crystal structure of MccB from Staphylococcus aureus in its apo- and PLP-bound forms. The structures of MccB exhibited similar molecular arrangements to those of MetC-mediating β-elimination with the same substrate and further illustrated PLP-induced structural changes in MccB. A structural comparison to MetC revealed a longer distance between the N-1 atom of the pyridine ring of PLP and the Oδ atom of the Asp residue, as well as a wider and more flexible active site environment in MccB. We also found a hydrogen bond network in Ser-water-Ser-Glu near the Schiff base nitrogen atom of the PLP molecule and propose the Ser-water-Ser-Glu motif as a general base for the γ-elimination process. Our study suggests the molecular mechanism for how homologous enzymes that use PLP as a cofactor catalyze different reactions with the same active site residues.
High Efficient YVPO4 Luminescent Materials Activated by Europium
Authors: Minakova Tamara , Mjakin Sergey , Bakhmetyev Vadim , Sychov Maxim , Zyatikov Ilya , Ekimova Irina , Kozik Vladimir , Chen Yu-Wen , Kurzina Irina
Published: December 2019

YPO4:Eu, YVO4:Eu, and YVPO4:Eu based phosphors with various Eu(III) activator contents and phosphate-vanadate ratios were synthesized by the self-propagating high-temperature synthesis method. The samples were characterized by scanning electron microscopy, nitrogen sorption, acid-base indicators and photoluminescence. The particle surface features with a finely dispersed structure comprising all the involved elements. The pore structure and the specific surface areas of the samples were different depending on the compositions of the samples. The most finely dispersed sample was YVO4:Eu samples. The specific surface areas of the YPO4:Eu samples were 10 to 15 times greater than those of vanadate samples. The phosphors samples had a slightly basic (YVO4:Eu, YVPO4:Eu) or slightly acidic (YPO4:Eu) properties of the surface with different contents of Lewis and Brönsted sites. The differences in the compositions and acid-base state resulted in the difference in the intensity and brightness of the photoluminescence (PL) of the samples. The yttrium-phosphate-vanadate phosphors of the mixed YVxP1−xO4-Eu had higher brightness and PL intensity than those samples with similar phosphate as well as vanadate phosphors.
Design of a Bicycle Head Lamp Using an Atypical White Light-Emitting Diode with Separate Dies
Authors: Lin Hsin-Jung , Sun Ching-Cherng , Wu Chi-Shou , Lee Xuan-Hao , Yang Tsung-Hsun , Lin Shih-Kang , Lin Yi-Jou , Yu Yeh-Wei
Published: December 2019

To the best of our knowledge, this is the first demonstration of a design for a bicycle head lamp with a high-contrast cutoff line using an atypical white light-emitting diode (LED) with two separate dies. The precise optical model was created by setting the weighting factor on the emitting surface. The downward reflector was designed and fabricated to produce a high-contrast cutoff line in both short- and long-axis orientations, but a yellowish outer pattern was observed. A modified two-color optical model was created to describe the yellowish patterns in both orientations and explain the yellowish effect. Such an effect was caused by the larger coverage area of the phosphor than that by the blue dies. To reduce the yellowish effect near the cutoff line, a specific phosphor area was blocked in the experiment. The yellowish effect was greatly reduced, and the contrast across the cutoff line was enhanced. The presented technology is useful for designing a high-contrast light pattern with such an atypical white LED.
Comparative Study of ZnO Nanostructures Grown on Variously Orientated GaN and AlxGa1−xN: The Role of Polarization, and Surface Pits
Authors: Gao Zhiyuan , Lu Liwei , Xue Xiaowei , Li Jiangjiang , Zhao Lihuan , Ahmad Dilshad , Li Hongda
Published: December 2019

Through comparing ZnO directly grown on the substrates of a-plane, c-plane, and (11-22) plane GaN and AlxGa1−xN (0.06 ≤ x ≤ 1), the roles of different factors that may influence growth have been studied. Seeded by surface pits, ZnO nanowire (NW) preferentially grew along the polarized direction on top of the nonpolar GaN (laterally aligned), polar GaN and AlGaN (vertically aligned), and semipolar GaN (obliquely upward aligned). Nanosheets were easily formed when the polarized surface of the AlGaN film was not intact. The kinetic effect of polarization must be considered to explain the high aspect ratio of NWs along the polarized direction. It was found that dislocation affected NW growth through the surface pits, which provided excellent nucleation sites. If the surface pits on GaN could be controlled to distribute uniformly, self-organized ZnO NW array could be controllably and directly grown on GaN. Moreover, surface pits could also seed for nanosheet growth in AlN, since Al(OH)4− would presumably bind to the Zn2+ terminated surface and suppress the kinetic effects of polarization.
Small Unmanned Aircraft Systems (SUAS) and Manned Traffic near John Wayne Airport (KSNA) Spot Check of the SUAS Facility Map: Towards a New Paradigm for Drone Safety Near Airports
Authors: Burke Peter J.
Published: December 2019

Using data from an Automatic Dependent Surveillance-Broadcast (ADSB) aggregator, a custom data-mining program was developed to identify all manned aircraft below 500′ AGL within 5 miles of the KSNA airport on six specific days in 2018–2019. The data (a spot check) show that several of the zero-foot grids are well outside of the traffic pattern, with no manned aircraft below 500′ AGL for at least a mile. Detailed maps showing all the traffic on those days are overlaid on the KSNA UAS facility map for comparison. This data-driven safety analysis is outlined as a new paradigm for drone safety near airports, which can be applied worldwide.
A Portable Wireless Device for Cyclic Alternating Pattern Estimation from an EEG Monopolar Derivation
Authors: Mendonça Fábio , Mostafa Sheikh Shanawaz , Morgado-Dias Fernando , Ravelo-García Antonio G.
Published: December 2019

Quality of sleep can be assessed by analyzing the cyclic alternating pattern, a long-lasting periodic activity that is composed of two alternate electroencephalogram patterns, which is considered to be a marker of sleep instability. Experts usually score this pattern through a visual examination of each one-second epoch of an electroencephalogram signal, a repetitive and time-consuming task that is prone to errors. To address these issues, a home monitoring device was developed for automatic scoring of the cyclic alternating pattern by analyzing the signal from one electroencephalogram derivation. Three classifiers, specifically, two recurrent networks (long short-term memory and gated recurrent unit) and one one-dimension convolutional neural network, were developed and tested to determine which was more suitable for the cyclic alternating pattern phase’s classification. It was verified that the network based on the long short-term memory attained the best results with an average accuracy, sensitivity, specificity and area under the receiver operating characteristic curve of, respectively, 76%, 75%, 77% and 0.752. The classified epochs were then fed to a finite state machine to determine the cyclic alternating pattern cycles and the performance metrics were 76%, 71%, 84% and 0.778, respectively. The performance achieved is in the higher bound of the experts’ expected agreement range and considerably higher than the inter-scorer agreement of multiple experts, implying the usability of the device developed for clinical analysis.
Towards Generation of Cat States in Trapped Ions Set-Ups via FAQUAD Protocols and Dynamical Decoupling
Authors: Palmero Mikel , Simón Miguel Ángel , Poletti Dario
Published: December 2019

The high fidelity generation of strongly entangled states of many particles, such as cat states, is a particularly demanding challenge. One approach is to drive the system, within a certain final time, as adiabatically as possible, in order to avoid the generation of unwanted excitations. However, excitations can also be generated by the presence of dissipative effects such as dephasing. Here we compare the effectiveness of Local Adiabatic and the FAst QUasi ADiabatic protocols in achieving a high fidelity for a target superposition state both with and without dephasing. In particular, we consider trapped ions set-ups in which each spin interacts with all the others with the uniform coupling strength or with a power-law coupling. In order to mitigate the effects of dephasing, we complement the adiabatic protocols with dynamical decoupling and we test its effectiveness. The protocols we study could be readily implemented with state-of-the-art techniques.
Proactive Uplink Interference Mitigation in HetNets Stressed by Uniformly Distributed Wideband Jammers
Authors: Abbas Ziaul Haq , Abbas Ghulam , Haroon Muhammad Sajid , Muhammad Fazal , Kim Sunghwan
Published: December 2019

In heterogeneous cellular networks (HetNets), densification of small base stations (SBSs) in the macro base station (MBS) coverage region leads to improved network coverage and capacity. However, this improvement is at the cost of inter-cell interference (ICI) due to the high MBS transmit power. The situation deteriorates further when uniformly deployed wideband jammers (WBJs) to initiate distributed denial-of-service (DDoS) attacks are present. With sufficient knowledge about the network parameters, WBJs produce substantial jammer interference (JI) by transmitting unwanted energy in the legitimate band. Such jamming attacks can cause significant JI in the UL communications of MBS edge users (M-EUs) due to i) low uplink (UL) transmit power of user equipment (UE) and ii) longer distances of M-EUs. As a result of ICI and JI, M-EUs are severely affected and go off the coverage due to a low received signal-to-interference ratio (SIR). Hence, to mitigate both ICI and JI, we use a proactive resource allocation scheme known as reverse frequency allocation (RFA). The results indicate that although ICI and JI significantly degrade network performance, RFA employment leads to improved SIR due to effective ICI and JI mitigation.
Recognition of Activities of Daily Living and Environments Using Acoustic Sensors Embedded on Mobile Devices
Authors: Pires Ivan Miguel , Marques Gonçalo , Garcia Nuno M. , Pombo Nuno , Flórez-Revuelta Francisco , Spinsante Susanna , Teixeira Maria Canavarro , Zdravevski Eftim
Published: December 2019

The identification of Activities of Daily Living (ADL) is intrinsic with the user’s environment recognition. This detection can be executed through standard sensors present in every-day mobile devices. On the one hand, the main proposal is to recognize users’ environment and standing activities. On the other hand, these features are included in a framework for the ADL and environment identification. Therefore, this paper is divided into two parts—firstly, acoustic sensors are used for the collection of data towards the recognition of the environment and, secondly, the information of the environment recognized is fused with the information gathered by motion and magnetic sensors. The environment and ADL recognition are performed by pattern recognition techniques that aim for the development of a system, including data collection, processing, fusion and classification procedures. These classification techniques include distinctive types of Artificial Neural Networks (ANN), analyzing various implementations of ANN and choosing the most suitable for further inclusion in the following different stages of the developed system. The results present 85.89% accuracy using Deep Neural Networks (DNN) with normalized data for the ADL recognition and 86.50% accuracy using Feedforward Neural Networks (FNN) with non-normalized data for environment recognition. Furthermore, the tests conducted present 100% accuracy for standing activities recognition using DNN with normalized data, which is the most suited for the intended purpose.
Robust 2D Mapping Integrating with 3D Information for the Autonomous Mobile Robot Under Dynamic Environment
Authors: Zhang Bin , Kaneko Masahide , Lim Hun-ok
Published: December 2019

In order to move around automatically, mobile robots usually need to recognize their working environment first. Simultaneous localization and mapping (SLAM) has become an important research field recently, by which the robot can generate a map while moving around. Both two-dimensional (2D) mapping and three-dimensional (3D) mapping methods have been developed greatly with high accuracy. However, 2D maps cannot reflect the space information of the environment and 3D mapping needs long processing time. Moreover, conventional SLAM methods based on grid maps take a long time to delete the moving objects from the map and are hard to delete the potential moving objects. In this paper, a 2D mapping method integrating with 3D information based on immobile area occupied grid maps is proposed. Objects in 3D space are recognized and their space information (e.g., shapes) and properties (moving objects or potential moving objects like people standing still) are projected to the 2D plane for updating the 2D map. By using the immobile area occupied grid map method, recognized still objects are reflected to the map quickly by updating the immobile area occupancy probability with a high coefficient. Meanwhile, recognized moving objects and potential moving objects are not used for updating the map. The unknown objects are reflected to the 2D map with a lower immobile area occupancy probability so that they can be deleted quickly once they are recognized as moving objects or start to move. The effectiveness of our method is proven by experiments of mapping under dynamic indoor environment using a mobile robot.
A Phantom Investigation to Quantify Huygens Principle Based Microwave Imaging for Bone Lesion Detection
Authors: Khalesi Banafsheh , Sohani Behnaz , Ghavami Navid , Ghavami Mohammad , Dudley Sandra , Tiberi Gianluigi
Published: December 2019

This paper demonstrates the outcomes of a feasibility study of a microwave imaging procedure based on the Huygens principle for bone lesion detection. This study has been performed using a dedicated phantom and validated through measurements in the frequency range of 1–3 GHz using one receiving and one transmitting antenna in free space. Specifically, a multilayered bone phantom, which is comprised of cortical bone and bone marrow layers, was fabricated. The identification of the lesion’s presence in different bone layers was performed on images that were derived after processing through Huygens’ principle, the S21 signals measured inside an anechoic chamber in multi-bistatic fashion. The quantification of the obtained images was carried out by introducing parameters such as the resolution and signal-to-clutter ratio (SCR). The impact of different frequencies and bandwidths (in the 1–3 GHz range) in lesion detection was investigated. The findings showed that the frequency range of 1.5–2.5 GHz offered the best resolution (1.1 cm) and SCR (2.22 on a linear scale). Subtraction between S21 obtained using two slightly displaced transmitting positions was employed to remove the artefacts; the best artefact removal was obtained when the spatial displacement was approximately of the same magnitude as the dimension of the lesion.
Delay Bound Optimization in NoC Using a Discrete Firefly Algorithm
Authors: Du Gaoming , Tian Chao , Li Zhenmin , Zhang Duoli , Zhang Chuan , Wang Xiaolei , Yin Yongsheng
Published: December 2019

The delay bound in system on chips (SoC) represents the worst-case traverse time of on-chip communication. In network on chip (NoC)-based SoC, optimizing the delay bound is challenging due to two aspects: (1) the delay bound is hard to obtain by traditional methods such as simulation; (2) the delay bound changes with the different application mappings. In this paper, we propose a delay bound optimization method using discrete firefly optimization algorithms (DBFA). First, we present a formal analytical delay bound model based on network calculus for both unipath and multipath routing in NoCs. We then set every flow in the application as the target flow and calculate the delay bound using the proposed model. Finally, we adopt firefly algorithm (FA) as the optimization method for minimizing the delay bound. We used industry patterns (video object plane decoder (VOPD), multiwindow display (MWD), etc.) to verify the effectiveness of delay bound optimization method. Experiments show that the proposed method is both effective and reliable, with a maximum optimization of 42.86%.
Fast Scalable Architecture of a Near-ML Detector for a MIMO-QSM Receiver
Authors: Lopez Ismael , Pizano-Escalante L. , Cortez Joaquin , Longoria-Gandara O. , Garcia Armando
Published: December 2019

This paper presents a proposal for an architecture in FPGA for the implementation of a low complexity near maximum likelihood (Near-ML) detection algorithm for a multiple input-multiple output (MIMO) quadrature spatial modulation (QSM) transmission system. The proposed low complexity detection algorithm is based on a tree search and a spherical detection strategy. Our proposal was verified in the context of a MIMO receiver. The effects of the finite length arithmetic and limited precision were evaluated in terms of their impact on the receiver bit error rate (BER). We defined the minimum fixed point word size required not to impact performance adversely for n T transmit antennas and n R receive antennas. The results showed that the proposal performed very near to optimal with the advantage of a meaningful reduction in the complexity of the receiver. The performance analysis of the proposed detector of the MIMO receiver under these conditions showed a strong robustness on the numerical precision, which allowed having a receiver performance very close to that obtained with floating point arithmetic in terms of BER; therefore, we believe this architecture can be an attractive candidate for its implementation in current communications standards.
Fusion of 2D CNN and 3D DenseNet for Dynamic Gesture Recognition
Authors: Zhang Erhu , Xue Botao , Cao Fangzhou , Duan Jinghong , Lin Guangfeng , Lei Yifei
Published: December 2019

Gesture recognition has been applied in many fields as it is a natural human–computer communication method. However, recognition of dynamic gesture is still a challenging topic because of complex disturbance information and motion information. In this paper, we propose an effective dynamic gesture recognition method by fusing the prediction results of a two-dimensional (2D) motion representation convolution neural network (CNN) model and three-dimensional (3D) dense convolutional network (DenseNet) model. Firstly, to obtain a compact and discriminative gesture motion representation, the motion history image (MHI) and pseudo-coloring technique were employed to integrate the spatiotemporal motion sequences into a frame image, before being fed into a 2D CNN model for gesture classification. Next, the proposed 3D DenseNet model was used to extract spatiotemporal features directly from Red, Green, Blue (RGB) gesture videos. Finally, the prediction results of the proposed 2D and 3D deep models were blended together to boost recognition performance. The experimental results on two public datasets demonstrate the effectiveness of our proposed method.
Energy-Related CO2 Emissions Growth in ASEAN Countries: Trends, Drivers and Policy Implications
Authors: Sandu Suwin , Yang Muyi , Mahlia Teuku Meurah Indra , Wongsapai Wongkot , Ong Hwai Chyuan , Putra Nandy , Rahman S. M. Ashrafur
Published: December 2019

The primary objective of this paper is to analyse the growth of energy-related CO2 emissions in ASEAN (Association of Southeast Asian Nations), with specific emphasis on identifying its trends and underlying drivers. This objective is premised on the arguments that: (1) there is a general lack of analysis of energy-related CO2 emissions growth across ASEAN countries; and (2) such an analysis is critical, because it could enable an assessment to be made of the efficacy of existing energy policies for reducing emissions. Decomposition analysis is the main approach adopted in this paper. The findings of this paper suggest that the growth of energy-related CO2 emissions has slowed in some major emitters in the region, due to energy efficiency improvement, and, to a lesser extent, a gradual switch in energy fuel mix towards lower emission sources (gas and renewables). However, this improvement is unlikely to drive a major transformation in the energy sectors of the region to the extent considered adequate for redressing the challenge of rising emissions, as indicated by a steady emissions growth in most ASEAN countries over the entire study period (1971–2016). By implication, this suggests that a significant scale-up of existing policy effort is needed to rectify the situations.
Is Renewable Energy-Powered Desalination a Viable Solution for Water Stressed Regions? A Case Study in Algarve, Portugal
Authors: Azinheira Gil , Segurado Raquel , Costa Mário
Published: December 2019

With a severe seasonal concentration of precipitation and unevenly distributed water resources, the water supply in Portugal is under stress, and the problem is expected to increase with climate change. Water desalination is increasingly becoming the preferred solution to fight water scarcity, but, because it is energy-intensive, the underlying costs and sustainability concerns over the power sources chosen remain a challenge to its implementation. This study aims to assess if the introduction of renewable energy sources (RES) powered desalination in mainland Portugal is viable and can contribute to guarantee water security. The Portuguese Algarve region is a viable case study to be considered because it is particularly water stressed and subject to highly varying demographics depending on the season. Taking the region’s freshwater demand, hourly RES production and power demand, a cost analysis was performed in order to obtain the levelized cost of water (LCOW) for two different strategies (centralized and decentralized). Two models were developed to estimate the LCOW: a simplified model and a subsequent optimization model, minimizing electricity costs. The resulting LCOW of 72.66 c€/m3, obtained for the decentralized solution, fits within the industry standard rate despite being 61.3% higher than the estimated conventional water supply production cost.
Comparison of Gas–Liquid Flow Characteristics in Geometrically Different Swirl Generating Devices
Authors: Putra Ryan Anugrah , Neumann-Kipping Martin , Schäfer Thomas , Lucas Dirk
Published: December 2019

The gas–liquid flow characteristics for blade, single, and the double-helical swirl elements were numerically investigated and compared in this work. The Euler–Euler model assuming bi-modal bubble size distributions was used. The experiment, conducted in a vertical pipe equipped with a static blade swirl element, was used as the basis for the computational fluid dynamics (CFD) simulations. In the experiment, high-resolution gamma-ray computed tomography (HireCT) was used to measure the gas volume fractions at several planes within the blade swirl element. The resulting calculated profiles of the pressure, liquid and gas velocities as well as the gas fraction showed a large influence of the swirl elements’ geometry. The evolution and characteristics of the calculated gas–liquid phase distributions in different measurement planes were found to be unique for each type of swirl element. A single gas core in the center of the pipe was observed from the simulation of the blade element, while multiple cores were observed from the simulations of the single and double helix elements. The cross-sectional gas distribution downstream of the single and double helical elements changed drastically within a relatively short distance downstream of the elements. In contrast, the single gas core downstream of the blade element was more stable.
Optimal Decomposition and Reconstruction of Discrete Wavelet Transformation for Short-Term Load Forecasting
Authors: Aprillia Happy , Yang Hong-Tzer , Huang Chao-Ming
Published: December 2019

To achieve high accuracy in prediction, a load forecasting algorithm must model various consumer behaviors in response to weather conditions or special events. Different triggers will have various effects on different customers and lead to difficulties in constructing an adequate prediction model due to non-stationary and uncertain characteristics in load variations. This paper proposes an open-ended model of short-term load forecasting (STLF) which has general prediction ability to capture the non-linear relationship between the load demand and the exogenous inputs. The prediction method uses the whale optimization algorithm, discrete wavelet transform, and multiple linear regression model (WOA-DWT-MLR model) to predict both system load and aggregated load of power consumers. WOA is used to optimize the best combination of detail and approximation signals from DWT to construct an optimal MLR model. The proposed model is validated with both the system-side data set and the end-user data set for Independent System Operator-New England (ISO-NE) and smart meter load data, respectively, based on Mean Absolute Percentage Error (MAPE) criterion. The results demonstrate that the proposed method achieves lower prediction error than existing methods and can have consistent prediction of non-stationary load conditions that exist in both test systems. The proposed method is, thus, beneficial to use in the energy management system.
Research on Multifunctional High-Power Grid Source Simulator System with Synchronous Generator, Line Impedance Imitation, and ZIP Load Emulator
Authors: Zhu Hong , Zhang Xing , Li Ming , Liu Xiaoxi
Published: December 2019

As the penetration of distributed power sources in the power grid is getting higher and higher, the adverse effects are also increasing. It is necessary to adopt control technology to make the distributed power source participate in the power regulation of the power system. In this paper, a multifunctional high-power grid source simulator system is presented. For wider control bandwidth and better performance, a high-power, back-to-back converter and an auxiliary lower-power, back-to-back converter connected in cascade mode topology is proposed in this paper. The basic principle and implementation method of virtual synchronous generator (VSG) in the high-power, back-to-back converter are described to reflect the same power frequency characteristics and voltage regulation characteristics as synchronous generators. Amplitude closed-loop control is proposed to realize zero steady-state error in the lower-power, back-to-back converter, also with line impedance imitation. Meanwhile, a constant-impedance, constant-current, and constant-power (ZIP) load model is used to emulate static load in the grid simulator system. At last, a set of experimental results for a 2 MW grid simulator system is provided to verify the effectiveness and validity of the proposed approach.
Directional Blasting Fracturing Technology for the Stability Control of Key Strata in Deep Thick Coal Mining
Authors: Xue Haojie , Gao Yubing , Zhang Xingyu , Tian Xichun , Wang Haosen , Yuan Di
Published: December 2019

Under the conditions of high ground stress and mining disturbance, the strata breakage that is induced by mining is severe. Thus, it is critical to investigate the structural characteristics of key strata (KS) in deep thick mining. This study introduces an innovative technology, namely, directional blasting fracturing, in which an energy-gathering tube is installed in a borehole and an explosive is detonated to break the roof in a specified direction. A theory of balanced bulk filling is established based on the requirements of developing a voussoir beam structure, which can be used to effectively evaluate the percentage of bulk filling in gob and to determine to which structure the key strata belongs. Based on this theory, two types of novel structural models in the advancing and lateral directions of the longwall face are established and defined for studying the roof fracturing mechanism. Compared with a cantilever structure, Model C can develop a stable voussoir beam structure, limiting the rotation space of the KS and reducing both the peak abutment pressure and the dynamic disturbance time in the advancing of the longwall face. Model E is defined as when the technology of directional blasting fracturing effectively cuts a stress transfer path into the barrier pillar. The peak abutment pressures on the barrier pillar and auxiliary entry are smaller, and the dynamic disturbance time is shorter, which can effectively improve the stability of the auxiliary entry. The key parameters of directional blasting fracturing are designed and constructed, and they include the roof fracturing height, angle, and charge structure. The field application performance of this innovative technology at the longwall face of 3−1101 in Hongqinghe coal mine was evaluated by analyzing the chock pressure stress, the pillar pressure stress, and the deformation of the auxiliary entry during mining, which lays a foundation for the application of this technology in coal mines in China.
A New FPGA-Based Real-Time Digital Solver for Power System Simulation
Authors: Zhang Bingda , Jin Xianglong , Tu Sijia , Jin Zhao , Zhang Jie
Published: December 2019

Considering the rational use of field programmable gate array (FPGA) resources, this paper proposes a new FPGA-based real-time digital solver (FRTDS) for power system simulation. Based on the relationship between the number of computing components, the operating frequency, and the pipeline length, the best selection principle is given. By analyzing the implementation method of the Multi-Port Read/Write Circuit, the computing formula of the Look-Up-Table (LUT) consumption was derived. Given the excessive use of LUTs in the original computing components, the computing components were assembled in a single typical arithmetic expression of the power system simulation program, as the basic computing formula was characterized by a subset of the typical computing formula and multiple uses of the same variable. Data communication between different computing components was realized by using Multi-Port Input Circuits that share some outputs of read controller, and Multi-Port Output Circuits, which share some outputs of computing cores. According to the test results of original FRTDS and new FRTDS, it was found that the solution proposed in this paper had a shorter ideal simulation time and a higher parallel computing capability, which was very suitable for real-time digital simulation of power systems.
A Survey on Power Grid Faults and Their Origins: A Contribution to Improving Power Grid Resilience
Authors: Mar Adriana , Pereira Pedro , F. Martins João
Published: December 2019

One of the most critical infrastructures in the world is electrical power grids (EPGs). New threats affecting EPGs, and their different consequences, are analyzed in this survey along with different approaches that can be taken to prevent or minimize those consequences, thus improving EPG resilience. The necessity for electrical power systems to become resilient to such events is becoming compelling; indeed, it is important to understand the origins and consequences of faults. This survey provides an analysis of different types of faults and their respective causes, showing which ones are more reported in the literature. As a result of the analysis performed, it was possible to identify four clusters concerning mitigation approaches, as well as to correlate them with the four different states of the electrical power system resilience curve.
Using Artificial Intelligence to Predict Wind Speed for Energy Application in Saudi Arabia
Authors: Brahimi Tayeb
Published: December 2019

Predicting wind speed for wind energy conversion systems (WECS) is an essential monitor, control, plan, and dispatch generated power and meets customer needs. The Kingdom of Saudi Arabia recently set ambitious targets in its national transformation program and Vision 2030 to move away from oil dependence and redirect oil and gas exploration efforts to other higher-value uses, chiefly meeting 10% of its energy demand through renewable energy sources. In this paper, we propose the use of the artificial neural networks (ANNs) method as a means of predicting daily wind speed in a number of locations in the Kingdom of Saudi Arabia based on multiple local meteorological measurement data provided by K.A.CARE. The suggested model is a feed-forward neural network model with the administered learning technique using a back-propagation algorithm. Results indicate that the best structure is obtained with thirty neurons in the hidden layers matching a minimum root mean square error (RMSE) and the highest correlation coefficient (R). A comparison between predicted and actual data from meteorological stations showed good agreement. A comparison between five machine learning algorithms, namely ANN, support vector machines (SVM), random tree, random forest, and RepTree revealed that random tree has low correlation and relatively high root mean square error. The significance of the present study relies on its ability to predict wind speeds, a necessary prerequisite to executing sustainable integration of wind power into Saudi Arabia’s electrical grid, assisting operators in efficiently managing generated power, and helping achieve the energy efficiency and production targets of Vision 2030.
Soybean Oil Transesterification for Biodiesel Production with Micro-Structured Calcium Oxide (CaO) from Natural Waste Materials as a Heterogeneous Catalyst
Authors: Santos Samuel , Nobre Luís , Gomes João , Puna Jaime , Quinta-Ferreira Rosa , Bordado João
Published: December 2019

In this study, micro-structured calcium oxide obtained from the calcination (850 °C for 3 h) of Gallus gallus domesticus (chicken) eggshells was used as a catalyst in the transesterification of soybean oil. This catalyst was characterized by Scanning Electron Spectroscopy (SEM) methods. The structure of the obtained CaO showed several agglomerates of white granular solids with a non-regular and unsymmetrical shape. In terms of calcium oxide catalytic activity, three different catalyst loadings (1%wt, 3%wt, and 5%wt) were tested for the same reaction conditions, resulting in transesterification yields of 77.27%wt, 84.53%wt, and 85.83%wt respectively. The results were compared to the current literature, and whilst they were lower, they were promising, allowing us to conclude that the tendency of yield improvement for this reaction, when the size range of catalyst particles is to be reduced to a nano scale, can be verified.
Partial Discharge Pattern Recognition of Gas-Insulated Switchgear via a Light-Scale Convolutional Neural Network
Authors: Wang Yanxin , Yan Jing , Yang Zhou , Liu Tingliang , Zhao Yiming , Li Junyi
Published: December 2019

Partial discharge (PD) is one of the major form expressions of gas-insulated switchgear (GIS) insulation defects. Because PD will accelerate equipment aging, online monitoring and fault diagnosis plays a significant role in ensuring safe and reliable operation of the power system. Owing to feature engineering or vanishing gradients, however, existing pattern recognition methods for GIS PD are complex and inefficient. To improve recognition accuracy, a novel GIS PD pattern recognition method based on a light-scale convolutional neural network (LCNN) without artificial feature engineering is proposed. Firstly, GIS PD data are obtained through experiments and finite-difference time-domain simulations. Secondly, data enhancement is reinforced by a conditional variation auto-encoder. Thirdly, the LCNN structure is applied for GIS PD pattern recognition while the deconvolution neural network is used for model visualization. The recognition accuracy of the LCNN was 98.13%. Compared with traditional machine learning and other deep convolutional neural networks, the proposed method can effectively improve recognition accuracy and shorten calculation time, thus making it much more suitable for the ubiquitous-power Internet of Things and big data.
Adaptive Control for Pure-Feedback Nonlinear Systems Preceded by Asymmetric Hysteresis
Authors: Lai Xiaohuan , Pan Haipeng , Zhao Xinlong
Published: December 2019

An adaptive control scheme is proposed for a class of uncertain pure-feedback nonlinear systems preceded by asymmetric hysteresis nonlinearity. The asymmetric property is described by the modified Bouc-Wen model based on the proposed asymmetric factor. State variables in the controller design are directly replaced with nonaffine functions to address the control problem caused by nonaffine appearance. Moreover, the control method can handle systems with external disturbances and guarantee the global stability of all the signals in the closed-loop system. The feasibility of the control scheme is verified by a simulation example and experimental results.
A Marine Gas Turbine Fault Diagnosis Method Based on Endogenous Irreversible Loss
Authors: Cao Yunpeng , Luan Junqi , Han Guodong , Lv Xinran , Li Shuying
Published: December 2019

When a malfunction occurs in a marine gas turbine, its thermal efficiency will decrease slightly, and the gas path fault is often difficult to distinguish. In order to solve this problem, based on the second law of thermodynamics, the endogenous irreversible loss (EIL) model of the marine gas turbine is established, and the exergy loss analysis under normal conditions is carried out to verify the accuracy of the model. The fault diagnosis of gas turbine gas path based on EIL is proposed, and a simulation experiment conducted on a three-shaft marine gas turbine demonstrated that the proposed approach can detect and isolate gas path fault accurately under different operating conditons and enviroments.
A Control-Oriented Engine Torque Online Estimation Approach for Gasoline Engines Based on In-Cycle Crankshaft Speed Dynamics
Authors: Tong Qiang , Xie Hui , Song Kang , Zou Dong
Published: December 2019

Engine brake torque is a key feedback variable for the optimal torque split control of an engine–motor hybrid powertrain system. Due to the limitations in available sensors, however, engine torque is difficult to measure directly. For torque estimation, the unknown external load torque and the overlap of the expansion stroke between cylinders introduce a great disturbance to engine speed dynamics. This makes the conventional cycle average engine speed-based estimation approach unusable. In this article, an in-cycle crankshaft speed-based indicated torque estimation approach is proposed for a four-cylinder engine. First, a unique crankshaft angle window is selected for load torque estimation without the influence of combustion torque. Then, an in-cycle angle-domain crankshaft speed dynamic model is developed for engine indicated torque estimation. To account for the effects of model inaccuracy and unknown external disturbances, a “total disturbance” term is introduced. The total disturbance is then estimated by an adaptive observer using the engine’s historical operating data. Finally, a real-time correction method for the friction torque is proposed in the fuel cut-off scenario. Combining the aforementioned torque estimators, the brake torque can be obtained. The proposed algorithm is implemented in an in-house developed multi-core engine control unit (ECU). Experimental validation results on an engine test bench show that the algorithm’s execution time is about 3.2 ms, and the estimation error of the brake torque is within 5%. Therefore, the proposed method is a promising way to accurately estimate engine torque in real-time.