bluuebunny/crossref_metadata_2025 huggingface dataset:
An Optimal Genetic Algorithm for Fatigue Life Control of Medium Carbon Steel in Laser Hardening Process
Authors: Ponticelli Gennaro Salvatore , Guarino Stefano , Giannini Oliviero
Published: February 2020

This study proposes a genetic algorithm-optimized model for the control of the fatigue life of AISI 1040 steel components after a high-power diode laser hardening process. First, the effect of the process parameters, i.e., laser power and scan speed, on the fatigue life of the components after the laser treatment was evaluated by using a rotating bending machine. Then, in light of the experimental findings, the optimization model was developed and tested in order to find the best regression model able to fit the experimental data in terms of the number of cycles until failure. The laser treatment was found to significantly increase the fatigue life of the irradiated samples, thus revealing its suitability for industrial applications. Finally, the application of the proposed genetic algorithm-based method led to the definition of an optimal regression model which was able to replicate the experimental trend very accurately, with a mean error of about 6%, which is comparable to the standard deviation associated with the process variability.
The Dietary Effect of Vitex agnus-castus Hydroalcoholic Extract on Growth Performance, Blood Biochemical Parameters, Carcass Quality, Sex Ratio and Gonad Histology in Zebrafish (Danio rerio)
Authors: Enayat Gholampour Tayebeh , Fadaei Raieni Raha , Pouladi Mojtaba , Larijani Mohamad , Pagano Maria , Faggio Caterina
Published: February 2020

The main purpose of this study was to consider the impact of Vitex agnus-castus hydroalcoholic extract, containing phytoestrogenic compounds on growth indices, sex ratio and histology of gonads of female Zebrafish. Fish larvae (4-day-old after hatching) were nourished with investigational diets (0 (control group T0), 5 g (T1), 10 g (T2) and 15 g (T3) kg−1 food) from first active feeding for 90 days. The results showed that Condition Factor (CF), Food Conversion Rate (FCR), Body Weight Gain (BWG), and Specific Growth Rate (SGR) were affected meaningfully by hydroalcoholic extract of Vitex agnus-castus (p < 0.05). These factors were significantly higher in compare to T3 treatment (p < 0.05). With increasing concentration of the extract in the diet, the ratio of female to male increased Treatment of T3 resulted in 87.23% feminization. Overall, this study suggests the use of T3 treatment achieves the best reproduction performance and a higher percentage of females in zebrafish as a model for aquaculture species. According to the results, the lowest levels of glucose and cholesterol were observed in T3 treatment and showed a significant changes with the control and treatments (p < 0.05).
Effective Assessment of Blast-Induced Ground Vibration Using an Optimized Random Forest Model Based on a Harris Hawks Optimization Algorithm
Authors: Yu Zhi , Shi Xiuzhi , Zhou Jian , Chen Xin , Qiu Xianyang
Published: February 2020

Most mines choose the drilling and blasting method which has the characteristics of being a cheap and efficient method to fragment rock mass, but blast-induced ground vibration damages the surrounding rock mass and structure and is a drawback. To predict, analyze and control the blast-induced ground vibration, the random forest (RF) model, Harris hawks optimization (HHO) algorithm and Monte Carlo simulation approach were utilized. A database consisting of 137 datasets was collected at different locations around the Tonglvshan open-cast mine, China. Seven variables were selected and collected as the input variables, and peak particle velocity was chosen as the output variable. At first, an RF model and a hybrid model, namely a HHO-RF model, were developed, and the prediction results checked by 3 performance indices to show that the proposed HHO-RF model can provide higher prediction performance. Then blast-induced ground vibration was simulated by using the Monte Carlo simulation approach and the developed HHO-RF model. After analyzing, the mean peak particle velocity value was 0.98 cm/s, and the peak particle velocity value did not exceed 1.95 cm/s with a probability of 90%. The research results of this study provided a simple, accurate method and basis for predicting, evaluating blast-induced ground vibration and optimizing the blast design before blast operation.
Electrochemical Deposition of Copper on Epitaxial Graphene
Authors: Shtepliuk Ivan , Vagin Mikhail , Yakimova Rositsa
Published: February 2020

Understanding the mechanism of metal electrodeposition on graphene as the simplest building block of all graphitic materials is important for electrocatalysis and the creation of metal contacts in electronics. The present work investigates copper electrodeposition onto epitaxial graphene on 4H-SiC by experimental and computational techniques. The two subsequent single-electron transfer steps were coherently quantified by electrochemistry and density functional theory (DFT). The kinetic measurements revealed the instantaneous nucleation mechanism of copper (Cu) electrodeposition, controlled by the convergent diffusion of reactant to the limited number of nucleation sites. Cu can freely migrate across the electrode surface. These findings provide fundamental insights into the nature of copper reduction and nucleation mechanisms and can be used as a starting point for performing more sophisticated investigations and developing real applications.
Modelling Lithium-Ion Battery Ageing in Electric Vehicle Applications—Calendar and Cycling Ageing Combination Effects
Authors: Redondo-Iglesias Eduardo , Venet Pascal , Pelissier Serge
Published: February 2020

Battery ageing is an important issue in e-mobility applications. The performance degradation of lithium-ion batteries has a strong influence on electric vehicles’ range and cost. Modelling capacity fade of lithium-ion batteries is not simple: many ageing mechanisms can exist and interact. Because calendar and cycling ageings are not additive, a major challenge is to model battery ageing in applications where the combination of cycling and rest periods are variable as, for example, in the electric vehicle application. In this work, an original approach to capacity fade modelling based on the formulation of reaction rate of a two-step reaction is proposed. A simple but effective model is obtained: based on only two differential equations and seven parameters, it can reproduce the capacity evolution of lithium-ion cells subjected to cycling profiles similar to those found in electric vehicle applications.
Addition of K22 Converts Spider Venom Peptide Pme2a from an Activator to an Inhibitor of NaV1.7
Authors: Yin Kathleen , Deuis Jennifer R. , Dekan Zoltan , Jin Ai-Hua , Alewood Paul F. , King Glenn F. , Herzig Volker , Vetter Irina
Published: February 2020

Spider venom is a novel source of disulfide-rich peptides with potent and selective activity at voltage-gated sodium channels (NaV). Here, we describe the discovery of μ-theraphotoxin-Pme1a and μ/δ-theraphotoxin-Pme2a, two novel peptides from the venom of the Gooty Ornamental tarantula Poecilotheria metallica that modulate NaV channels. Pme1a is a 35 residue peptide that inhibits NaV1.7 peak current (IC50 334 ± 114 nM) and shifts the voltage dependence of activation to more depolarised membrane potentials (V1/2 activation: Δ = +11.6 mV). Pme2a is a 33 residue peptide that delays fast inactivation and inhibits NaV1.7 peak current (EC50 > 10 μM). Synthesis of a [+22K]Pme2a analogue increased potency at NaV1.7 (IC50 5.6 ± 1.1 μM) and removed the effect of the native peptide on fast inactivation, indicating that a lysine at position 22 (Pme2a numbering) is important for inhibitory activity. Results from this study may be used to guide the rational design of spider venom-derived peptides with improved potency and selectivity at NaV channels in the future.
NOM (HA and FA) Reduction in Water Using Nano Titanium Dioxide Photocatalysts (P25 and P90) and Membranes
Authors: Rajca Mariola
Published: February 2020

This study examined the removal of natural organic substances (humic acids-HA, and fulvic acids-FA) from model solutions using photocatalysis and ultrafiltration. The effect of two nano titanium dioxide types (P25 and P90) with different active surface areas and two UV lamps (low-pressure and medium-pressure) on the effectiveness of FA and HA removal during photocatalysis was tested. An integrated photocatalytic + ultrafiltration system was also analyzed to determine the effectiveness of FA and HA removal and the changes in the relative permeate flux (Ultrafiltration Membrane Fouling-UF). We observed that photocatalysis using the P90 nano titanium dioxide was more efficient than the P25 due to the larger surface area (2×). The decomposition of organic substances proceeded efficiently up to 30 min of solution exposure, and the use of a medium-pressure lamp accelerated compound decomposition relative to the low-pressure lamp. The applied photocatalysis + ultrafiltration system was characterized by a high degree of FA removal while improved hydraulic efficiency was observed during ultrafiltration.
VARTTA: A Visual Analytics System for Making Sense of Real-Time Twitter Data
Authors: Haghighati Amir , Sedig Kamran
Published: February 2020

Through social media platforms, massive amounts of data are being produced. As a microblogging social media platform, Twitter enables its users to post short updates as “tweets” on an unprecedented scale. Once analyzed using machine learning (ML) techniques and in aggregate, Twitter data can be an invaluable resource for gaining insight into different domains of discussion and public opinion. However, when applied to real-time data streams, due to covariate shifts in the data (i.e., changes in the distributions of the inputs of ML algorithms), existing ML approaches result in different types of biases and provide uncertain outputs. In this paper, we describe VARTTA (Visual Analytics for Real-Time Twitter datA), a visual analytics system that combines data visualizations, human-data interaction, and ML algorithms to help users monitor, analyze, and make sense of the streams of tweets in a real-time manner. As a case study, we demonstrate the use of VARTTA in political discussions. VARTTA not only provides users with powerful analytical tools, but also enables them to diagnose and to heuristically suggest fixes for the errors in the outcome, resulting in a more detailed understanding of the tweets. Finally, we outline several issues to be considered while designing other similar visual analytics systems.
Redesign of an In-Market Conveyor System for Manufacturing Cost Reduction and Design Efficiency Using DFMA Methodology
Authors: Butt Javaid , Jedi Sunny
Published: February 2020

To remain competitive in the market, it is crucial to reduce the time and costs involved in product development. Design for manufacturing and assembly is an engineering methodology that can reduce costs without compromising reliability, performance and time to market objectives. This paper presents a case study for an in-market Table Top Chain (TTC) conveyor system used by a reputed company in Saudi Arabia. TTC conveyor systems are extensively used by major food companies around the world for transporting packaged bottles, glass and cans. There are three main types of these systems, i.e., straight running, side flexing and multiflex. This work focuses on the redesign of a side flexing TTC conveyor system. The existing design of the TTC conveyor system was analysed using the DFMA 9.3 software. The outcomes of the initial analysis were utilised to redesign the TTC conveyor system for cost and design efficiency improvements. The optimum design was selected using Pugh controlled convergence method and further tested for its structural performance using finite element analysis. The redesigned model showed substantial improvements with cost reductions of 29% and an increase in design efficiency from 1.7% to 5%. Finite element analysis has also been carried out with SolidWorks 2019 to validate the structural integrity of the new concept design.
sDeepFM: Multi-Scale Stacking Feature Interactions for Click-Through Rate Prediction
Authors: Qiang Baohua , Lu Yongquan , Yang Minghao , Chen Xianjun , Chen Jinlong , Cao Yawei
Published: February 2020

For estimating the click-through rate of advertisements, there are some problems in that the features cannot be automatically constructed, or the features built are relatively simple, or the high-order combination features are difficult to learn under sparse data. To solve these problems, we propose a novel structure multi-scale stacking pooling (MSSP) to construct multi-scale features based on different receptive fields. The structure stacks multi-scale features bi-directionally from the angles of depth and width by constructing multiple observers with different angles and different fields of view, ensuring the diversity of extracted features. Furthermore, by learning the parameters through factorization, the structure can ensure high-order features being effectively learned in sparse data. We further combine the MSSP with the classical deep neural network (DNN) to form a unified model named sDeepFM. Experimental results on two real-world datasets show that the sDeepFM outperforms state-of-the-art models with respect to area under the curve (AUC) and log loss.
A Baseline Roadmap for Advanced Wireless Research Beyond 5G
Authors: Mourad Alain , Yang Rui , Lehne Per Hjalmar , De La Oliva Antonio
Published: February 2020

This paper presents a baseline roadmap for the evolution of 5G new radio over the next decade. Three timescales are considered, namely short-term (2022-ish), medium-term (2025-ish), and long-term (2030-ish). The evolution of the target key performance indicators (KPIs) is first analyzed by accounting for forecasts on the emerging use cases and their requirements, together with assumptions on the pace of technology advancements. The baseline roadmap is derived next by capturing the top-10 and next the top-5 technology trends envisioned to bring significant added value at each timescale. Being intrinsically predictive, our proposed baseline roadmap cannot assert with certainty the values of the target KPIs and the shortlisting of the technology trends. It is, however, aimed at driving discussions and collecting feedback from the wireless research community for future tuning and refinement as the 5G evolution journey progresses.
Cooperative Secure Transmission in MISO-NOMA Networks
Authors: Chen Yang , Zhang Zhongpei , Li Bingrui
Published: February 2020

In this paper, we investigate cooperative secure transmission in non-orthogonal multiple access (NOMA) networks where a source (Alice) intends to transmit confidential messages to one legitimate user with high-level security requirement (LU1), and serve another normal one (LU2) simultaneously. In order to enhance the transmission security, a cooperative jammer (Charlie) is employed to confuse multiple non-colluding eavesdroppers (Eves). Taking both secrecy outage restriction of LU1 and the desired quality of service (QoS) requirement of LU2 into consideration, we propose an adaptive power allocation strategy for maximizing secrecy rate. Numerical results are provided to validate that our proposed scheme significantly outperforms the conventional NOMA secure transmission scheme.
Method for Estimating Harmonic Parameters Based on Measurement Data without Phase Angle
Authors: Zhou Fulin , Liu Feifan , Yang Ruixuan , Liu Huanrui
Published: February 2020

The excessive use of power electronics makes power quality problems in power grids increasingly prominent. The estimation of the harmonic parameters of harmonic sources in the power grid and the division of harmonic responsibilities are of great significance for the evaluation of power quality. At present, methods for estimating harmonic parameters and harmonic responsibilities need to provide the amplitude and phase information of the current and voltage of the point of common coupling (PCC). However, in practical engineering applications, the general power quality monitor only provides the amplitude information of the voltage and current of the measured point and the phase difference information between them. Missing phase information invalidates existing methods. Based on the partial least squares regression method, the present work proposes a method for estimating harmonic parameters in the case of monitoring data without phase. This method only needs to measure the amplitude information of the harmonic voltage and current of the PCC and the phase difference between them, then use the measurable data to estimate the harmonic parameters and the harmonic responsibility of each harmonic source. It provides a new way to effectively solve the problem that the measured data of the project has no phase information. The feasibility and effectiveness of the proposed method are proved by simulation data and measured engineering data.
Floating Performance of a Composite Bucket Foundation with an Offshore Wind Tower during Transportation
Authors: Ding Hongyan , Feng Zuntao , Zhang Puyang , Le Conghuan , Guo Yaohua
Published: February 2020

The composite bucket foundation (CBF) for offshore wind turbines is the basis for a one-step integrated transportation and installation technique, which can be adapted to the construction and development needs of offshore wind farms due to its special structural form. To transport and install bucket foundations together with the upper portion of offshore wind turbines, a non-self-propelled integrated transportation and installation vessel was designed. In this paper, as the first stage of applying the proposed one-step integrated construction technique, the floating behavior during the transportation of CBF with a wind turbine tower for the Xiangshui wind farm in the Jiangsu province was monitored. The influences of speed, wave height, and wind on the floating behavior of the structure were studied. The results show that the roll and pitch angles remain close to level during the process of lifting and towing the wind turbine structure. In addition, the safety of the aircushion structure of the CBF was verified by analyzing the measurement results for the interaction force and the depth of the liquid within the bucket. The results of the three-DOF (degree of freedom) acceleration monitoring on the top of the test tower indicate that the wind turbine could meet the specified acceleration value limits during towing.
A New Method of Lithology Classification Based on Convolutional Neural Network Algorithm by Utilizing Drilling String Vibration Data
Authors: Chen Gang , Chen Mian , Hong Guobin , Lu Yunhu , Zhou Bo , Gao Yanfang
Published: February 2020

Formation lithology identification is of great importance for reservoir characterization and petroleum exploration. Previous methods are based on cutting logging and well-logging data and have a significant time lag. In recent years, many machine learning methods have been applied to lithology identification by utilizing well-logging data, which may be affected by drilling fluid. Drilling string vibration data is a high-density ancillary data, and it has the advantages of low-latency, which can be acquired in real-time. Drilling string vibration data is more accessible and available compared to well-logging data in ultra-deep well drilling. Machine learning algorithms enable us to develop new lithology identification models based on these vibration data. In this study, a vibration dataset is used as the signal source, and the original vibration signal is filtered by Butterworth (BHPF). Vibration time–frequency characteristics were extracted into time–frequency images with the application of short-time Fourier transform (STFT). This paper develops lithology classification models using new data sources based on a convolutional neural network (CNN) combined with Mobilenet and ResNet. This model is used for complex formation lithology, including fine gravel sandstone, fine sandstone, and mudstone. This study also carries out related model accuracy verification and model prediction results interpretation. In order to improve the trustworthiness of decision-making results, the gradient-weighted class-activated thermal localization map is applied to interpret the results of the model. The final verification test shows that the single-sample decision time of the model is 10 ms, the test macro precision rate is 90.0%, and the macro recall rate is 89.3%. The lithology identification model based on vibration data is more efficient and accessible than others. In conclusion, the CNN model using drill string vibration supplies a superior method of lithology identification. This study provides low-latency lithology classification methods to ensure safe and fast drilling.
Effects of Pig Manure and Corn Straw Generated Biogas and Methane Enriched Biogas on Performance and Emission Characteristics of Dual Fuel Diesel Engines
Authors: Ahmed Salman Abdu , Zhou Song , Zhu Yuanqing , Tsegay Asfaw Solomon , Feng Yoming , Ahmad Naseem , Malik Adil
Published: February 2020

In recent years, due to stringent emission regulations vehicle manufacturers have been compelled to cut down noxious pollutants released from diesel engines. Different alternative solutions have been recommended to achieve this challenging task. One of these alternative solutions is the utilization of biogas in addition to the use of liquid diesel. In this regard, the current study investigates the combustion characteristics and exhaust emissions of a turbocharged, direct injection, diesel engine operating at constant speed (1800 rpm) and under dual fuel mode with diesel as the pilot fuel and biogas (generated from pig manure and corn straw) and methane enriched biogas. Simulations were carried out at four various engine loads corresponding to brake mean effective pressure (BMEP) of 0.425, 0.85, 1.275, and 1.7 MPa using GT-Power package. The BTE values of biogas-diesel were higher as compared to diesel fuel. The CO2 ratio of biogas did not impact BTE considerably. The highest BTE value of 38.22% was recorded for BG45. However, the Brake specific fuel consumption (BSFC) values for the biogas-diesel fuels were higher than that of diesel fuel operations. With respect to emissions, compared to diesel fuel operation, the hydrocarbon (HC) and CO2 of the biogas-diesel were higher, but NOx and CO pollutants were much lower. The utilization of biogas with diesel by all accounts is attractive to cut down discharges and improve performance of the engine. The engine performance did not deteriorate with up to 45% CO2 proportion in biogas.
An Induction Curve Model for Prediction of Power Output of Wind Turbines in Complex Conditions
Authors: Vahidzadeh Mohsen , Markfort Corey D.
Published: February 2020

Power generation from wind farms is traditionally modeled using power curves. These models are used for assessment of wind resources or for forecasting energy production from existing wind farms. However, prediction of power using power curves is not accurate since power curves are based on ideal uniform inflow wind, which do not apply to wind turbines installed in complex and heterogeneous terrains and in wind farms. Therefore, there is a need for new models that account for the effect of non-ideal operating conditions. In this work, we propose a model for effective axial induction factor of wind turbines that can be used for power prediction. The proposed model is tested and compared to traditional power curve for a 2.5 MW horizontal axis wind turbine. Data from supervisory control and data acquisition (SCADA) system along with wind speed measurements from a nacelle-mounted sonic anemometer and turbulence measurements from a nearby meteorological tower are used in the models. The results for a period of four months showed an improvement of 51% in power prediction accuracy, compared to the standard power curve.
Time-Dependent Flexibility Potential of Heat Pump Systems for Smart Energy System Operation
Authors: Steinle Sina , Zimmerlin Martin , Mueller Felicitas , Held Lukas , Suriyah Michael R. , Leibfried Thomas
Published: February 2020

The integration of multiple energy sectors, such as electricity, heating, and mobility, into an overall smart energy system is a key part of the journey towards a fossil-free energy system. Exploiting the operational flexibility of these sectors will lead to the efficient operation of the integrated smart energy system. The use of heat pumps for the heating supply based on renewable energy resources is reasonable in many cases. Combining heat pumps with thermal storages, these systems can offer flexibility to an energy system based on fluctuating power generation. Flexibility can be defined as the capability to adapt an initial schedule in order to support the energy system in terms of the provision of power reserve. In this paper, an approach to determine the time-dependent flexibility potential of a heat pump system is presented. The optimization-based approach considers all the constraints resulting from the system topology, including the required heating demand of the connected building. As a result, constraints for the integration of the available flexibility in a modified Optimal Power Flow (OPF) calculation are given. These lead to the ensured feasibility of the flexibility provision without considering the system boundaries of the heat pump site within the OPF.
Application of Specific Energy in Evaluation of Geological Conditions Ahead of Tunnel Face
Authors: Liu Jiankang , Sakaguchi Osamu , Ishizu Sodai , Luan Hengjie , Han Wei , Jiang Yujing
Published: February 2020

In underground construction, especially tunnel building, a detailed knowledge of the geological conditions ahead of the tunnel face is essential for both safety and efficiency of work. Many tunnel collapses have been reported to occur because of a lack of accurate evaluation of the geological conditions. While conventional horizontal boring conducted from a tunnel face provides good accuracy, it is infrequently conducted due to its high cost and time-consuming nature. In addition, the tunnel seismic reflection method has limited practicality owing to the complexity of data processing. This paper presents a new approach based on the specific energy of the mechanical drilling rig to evaluate the geological conditions ahead of the tunnel face. In order to assess the geological conditions, rock mass quality index, buried depth of the tunnel and tunnel deformation investigation were undertaken, and the obtained data were compared to the specific energy. Results from the comparison reveal the evaluation criterion that if the distribution of specific energy in some areas deviates from the distribution of buried depth, it is considered that abnormal geological conditions exist in this area. This work can greatly contribute to the accurate and effective evaluation of the geological conditions ahead of the tunnel face.
An Optimal Design of an Electromagnetic Actuation System towards a Large Homogeneous Magnetic Field and Accessible Workspace for Magnetic Manipulation
Authors: Manamanchaiyaporn Laliphat , Xu Tiantian , Wu Xinyu
Published: February 2020

Untethered nano-/microrobots have been appealing to biomedical applications under magnetic guidance. Numerous actuation systems are specifically designed to generate either uniform or non-uniform fields which are unable to support all actuating mechanisms of magnetic robots. The size of their accessible space does not enable applications in life sciences (e.g., placing around human parts for tasks or an in vivo experiment in animals). Moreover, homogeneity of uniform magnetic fields is limited in a small region. Here, we propose an electromagnetic coil system that is optimally designed based on numerical simulation investigations to derestrict the mentioned constraints. The built-up system provides a large bore in which magnetic field generation by passing a 10 A current is strong enough for nano-/micromanipulation switchable between uniformity in a large-homogeneous region about 50-mm-wide along the x- and y-axes and 80-mm-wide along the z-axis, and with a non-uniformity of about 12 mT with 100 mT/m. It experimentally carries out potential and versatile controls to manipulate several commonly used microrobots that require a particular type of magnetic field to perform multi-DOF locomotion in diverse viscous environments. (e.g., helical propulsion by rotating magnetic field in the 3D-large workspace and in the complex network path, side-to-side sweeping-slip locomotion by oscillating fields, translation and rocking-slip locomotion by gradient-based fields). Besides, the system can be reproduced into any accessible space size regarding the square coil size to support diverse applications and guarantee the result in both uniformity of magnetic field in the large homogeneous region and a sufficiently strong gradient over the workspace.
Open Circuit Performance of Axial Air Gap Flux Switching Permanent Magnet Synchronous Machine for Wind Energy Conversion: Modeling and Experimental Study
Authors: Diab Haidar , Amara Yacine , Barakat Georges
Published: February 2020

The aim of this paper is to present the design and modeling of a machine that possesses some advantageous characteristics for wind energy conversion applications. The studied machine is a double stator inner rotor axial airgap flux switching permanent magnet machine (AFSPM). The paper will start by presenting this type of machine and its points of interest. Then, it will continue by introducing the constructed prototype and its specifications and structure. This prototype has been designed based on a reference specification used at GREAH to develop different prototypes and compare their performances. The second part will introduce the reluctance network model specifically constructed for this type of machine. The constructed model was validated by comparing its results to the results from the finite element method model. Finally, the experimental results will be presented and compared to the reluctance network (RN) model results where satisfying agreement between both results was obtained.
Determination of the Differential Capacity of Lithium-Ion Batteries by the Deconvolution of Electrochemical Impedance Spectra
Authors: Guo Dongxu , Yang Geng , Zhao Guangjin , Yi Mengchao , Feng Xuning , Han Xuebing , Lu Languang , Ouyang Minggao
Published: February 2020

Electrochemical impedance spectroscopy (EIS) is a powerful tool for investigating electrochemical systems, such as lithium-ion batteries or fuel cells, given its high frequency resolution. The distribution of relaxation times (DRT) method offers a model-free approach for a deeper understanding of EIS data. However, in lithium-ion batteries, the differential capacity caused by diffusion processes is non-negligible and cannot be decomposed by the DRT method, which limits the applicability of the DRT method to lithium-ion batteries. In this study, a joint estimation method with Tikhonov regularization is proposed to estimate the differential capacity and the DRT simultaneously. Moreover, the equivalence of the differential capacity and the incremental capacity is proven. Different types of commercial lithium-ion batteries are tested to validate the joint estimation method and to verify the equivalence. The differential capacity is shown to be a promising approach to the evaluation of the state-of-health (SOH) of lithium-ion batteries based on its equivalence with the incremental capacity.
Optimal Coordination of Overcurrent Relays in Microgrids Considering a Non-Standard Characteristic
Authors: Saldarriaga-Zuluaga Sergio Danilo , López-Lezama Jesús María , Muñoz-Galeano Nicolás
Published: February 2020

The optimal coordination of overcurrent relays (OCRs) has recently become a major challenge owing to the ever-increasing participation of distributed generation (DG) and the multi-looped structure of modern distribution networks (DNs). Furthermore, the changeable operational topologies of microgrids has increased the complexity and computational burden to obtain the optimal settings of OCRs. In this context, classical approaches to OCR coordination might no longer be sufficient to provide a reliable performance of microgrids both in the islanded and grid-connected operational modes. This paper proposes a novel approach for optimal coordination of directional OCRs in microgrids. This approach consists of considering the upper limit of the plug setting multiplier (PSM) as a variable instead of a fixed parameter as usually done in traditional approaches for OCRs coordination. A genetic algorithm (GA) was implemented to optimize the limits of the maximum PSM for the OCRs coordination. Several tests were performed with an IEC microgrid benchmark network considering several operational modes. Results showed the applicability and effectiveness of the proposed approach. A comparison with other studies reported in the specialized literature is provided showing the advantages of the proposed approach.
Some Aspects of the Control for the Radial Distribution of Burden Material and Gas Flow in the Blast Furnace
Authors: Golovchenko Anatoliy , Dychkovskyi Roman , Pazynich Yuliya , Edgar Cáceres Cabana , Howaniec Natalia , Jura Bartłomiej , Smolinski Adam
Published: February 2020

The paper presents an experimental study on the formation process of burden surface texture on the blast furnace throat and its influence on the radial distribution of gas flow. The study was performed with the application of blast furnaces equipped with a bell-type charging device using radio-isotope means for the control of burden surface texture (profile) and burden surface level, i.e., gamma locators for burden surface texture. The study was carried out under the conditions of an operating blast furnace in an iron and steel plant using a unique GEOTAPS system for automated control of geometric and temperature parameters of burden material surface on the blast furnace throat. The influence of the surface texture on the gas flow distribution was also investigated. The possibility of a self-stabilization effect for burden surface texture and gas flow in an operating blast furnace under suitable conditions was experimentally proven. As a result of the experimental study performed, four ways of energy-saving technology implementation were determined for the control of blast furnace melting based on the data on the burden surface texture and previously unknown regularities of surface layer formation of burden material on the throat of an operating blast furnace with a bell-type charging device. The main idea of the paper is the development of automated control for the radial distribution of burden material and gas flow using actual or predicted surface texture parameters as important intermediate factors that both describe the process and have a significant simultaneous influence on it.
Simulation Study on the Electricity Data Streams Time Series Clustering
Authors: Gajowniczek Krzysztof , Bator Marcin , Ząbkowski Tomasz , Orłowski Arkadiusz , Loo Chu Kiong
Published: February 2020

Currently, thanks to the rapid development of wireless sensor networks and network traffic monitoring, the data stream is gradually becoming one of the most popular data generating processes. The data stream is different from traditional static data. Cluster analysis is an important technology for data mining, which is why many researchers pay attention to grouping streaming data. In the literature, there are many data stream clustering techniques, unfortunately, very few of them try to solve the problem of clustering data streams coming from multiple sources. In this article, we present an algorithm with a tree structure for grouping data streams (in the form of a time series) that have similar properties and behaviors. We have evaluated our algorithm over real multivariate data streams generated by smart meter sensors—the Irish Commission for Energy Regulation data set. There were several measures used to analyze the various characteristics of a tree-like clustering structure (computer science perspective) and also measures that are important from a business standpoint. The proposed method was able to cluster the flows of data and has identified the customers with similar behavior during the analyzed period.
Optimal Design and Comparison of High-Frequency Resonant and Non-Resonant Rotary Transformers
Authors: Bastiaens Koen , Krop Dave C. J. , Jumayev Sultan , Lomonova Elena A.
Published: February 2020

This paper concerns the optimal design and comparative analysis of resonant and non-resonant high-frequency GaN-based rotating transformers. A multi-physical design approach is employed, in which magnetic, electrical, and thermal models are coupled. The results are verified by experiments. Two different optimization objectives are considered; firstly, the efficiency of two standard core geometries is maximized for a required output power level. Secondly, a geometrical optimization is performed, such that the core inertia is minimized for the desired output power level. The results of both design optimizations have shown large improvements in terms of output power and core inertia as a result of applying series–series resonant compensation.
Snapshot of Photovoltaics—February 2020
Authors: Jäger-Waldau Arnulf
Published: February 2020

Since the demonstration of the first modern silicon solar cells at Bell Labs in 1954, it took 58 years until the cumulative installed photovoltaic electricity generation capacity had reached 100 GW by the end of 2012. Then, it took another five years to reach an annual installation capacity of over 100 GW in 2017 and close to 120 GW in 2019. As a consequence, the total world-wide installed photovoltaic electricity generation capacity exceeded 635 GW at the end of 2019. Although it witnessed a 20% and 25% decrease in annual installations in 2018 and 2019, respectively, China was again the largest market with 30 GW of annual installations. The number of countries in the club with more than 1 GW annually has increased to 18 countries in 2019. The use of local battery storage systems in solar farms as well as decentralized photovoltaic electricity generation systems combined has again increased, due to the falling storage system costs.
How to Select the Optimal Electrochemical Energy Storage Planning Program? A Hybrid MCDM Method
Authors: Li Nan , Zhang Haining , Zhang Xiangcheng , Ma Xue , Guo Sen
Published: February 2020

Electrochemical energy storage (EES) is a promising kind of energy storage and has developed rapidly in recent years in many countries. EES planning is an important topic that can impact the earnings of EES investors and sustainable industrial development. Current studies only consider the profit or cost of the EES planning program, without considering other economic criteria such as payback period and return on investment (ROI), which are also important for determining an optimal EES planning program. In this paper, a new hybrid multi-criteria decision-making (MCDM) method integrating the Bayesian best-worst method (BBWM), the entropy weighting approach, and grey cumulative prospect theory is proposed for the optimal EES planning program selection with the consideration of multiple economic criteria. The BBWM and entropy weighting approach are jointly employed for determining the weightings of criteria, and the grey cumulative prospect theory was utilized for the performance rankings of different EES planning programs. Five EES planning programs were selected for empirical analysis, including 9MW PbC battery EES, 2MW LiFePO lithium ion battery EES, 3MW LiFePO lithium ion battery EES, 2MW vanadium redox flow battery EES, and 3MW vanadium redox flow battery EES. The empirical results indicate the 2MW LiFePO lithium ion battery EES is the optimal one. The sensitivity analysis related to different risk preferences of decision-makers also shows the 2MW LiFePO lithium ion battery EES is always the optimal EES planning program. The proposed MCDM method for the optimal EES planning program selection in this paper is effective and robust, and can provide certain references for EES investors and decision-makers.
Two Phase Anaerobic Digestion System of Municipal Solid Waste by Utilizing Microaeration and Granular Activated Carbon
Authors: Canul Bacab Fernando , España Gamboa Elda , Ruiz Espinoza Juan Enrique , Leal-Bautista Rosa M , Tapia Tussell Raúl , Domínguez Maldonado Jorge , Canto Canché Blondy , Alzate-Gaviria Liliana
Published: February 2020

In an anaerobic digestion (AD) process, the hydrolysis phase is often limited when substrates with high concentrations of solids are used. We hypothesized that applying micro-aeration in the hydrolysis phase and the application of granular activated carbon (GAC) in the methanogenesis phase could make the AD process more efficient. A packed bed reactor (PBR) coupled with an up-flow anaerobic sludge blanket (UASB) was conducted, and its effects on methane generation were evaluated. The micro-aeration rate applied in PBR was 254 L-air/kg-Total solids (TS)-d was compared with a control reactor. Micro-aeration showed that it reduced the hydrolysis time and increased the organic matter solubilization as chemical oxygen demand (COD) increasing 200%, with a volatile fatty acids (VFAs) increment higher than 300%, compared to the control reactor (without aeration). Our findings revealed that the implementations of microaeration and GAC in the two-phase AD system could enhance methane production by reducing hydrolysis time, increasing solid waste solubilization.
Research on Safety Technology for High-Speed Interruption for Mining Flameproof Movable Substation
Authors: Wang Yanwen , Wang Le , Bilén Sven G. , Gao Yan
Published: February 2020

Due to the working condition of low-voltage cabling from the mining flameproof movable substation to the loads of the mining face being poor, it is easy to cause various external mechanical damages to the cable sheaths. Furthermore, a single-phase earth leakage fault or short-circuit fault can occur when the low-voltage cable sheaths are damaged, and electric sparks caused by these faults can lead to a gas explosion. As the gas detonation time caused by the above faults is usually more than 5 ms, the high-speed interruption solid-state switch which controls the cables must cut off the current within 3 ms. This requires the action time of the solid-state switch to be less than 1 ms, and at the same time, the sampling and calculation time of the relay protection must be less than 2 ms. Based on these problems, this paper proposes the use of a high-speed solid-state circuit breaker (SSCB) topology at the neutral point of transformer, and analyzes the conduction mechanism and shut-off mechanism of the current of the SSCB. It presents an ultra-high-speed algorithm based on pattern recognition of single-phase earth leakage fault protection, and an ultra-high-speed algorithm of short-circuit fault which is based on the rate-of-change of the current. Finally, through computer simulation experiments and semi-physical simulation experiments, the feasibility of the above three technologies is verified to ensure that when a single-phase earth leakage fault or short-circuit fault occurs in the low-voltage cable, the solid-state switch which is installed in the mining flameproof movable substation will cut off the current within 3 ms.
Computational Modeling and Empirical Analysis of a Biomass-Powered Drinking Water Pasteurization Technology
Authors: Burleson Grace , Caplan Daniel , Mays Catherine , Moses Nicholas , Navab-Daneshmand Tala , Sharp Kendra , MacCarty Nordica
Published: February 2020

While filtration, chlorination, and UV drinking water treatments are commonplace, globally an estimated 1.2 billion people continue to boil their drinking water over inefficient biomass fires instead because it allows them to use available resources paired with a time-tested and trusted method. Although boiling water is culturally well-established, there is vast potential to improve human health, environmental impact, and efficiency by leveraging the fact that a significant reduction in pathogenic microorganisms occurs at temperatures well below boiling through a process known as pasteurization. This paper presents the evaluation of a community-scale, biomass-powered, flow-through water pasteurization system that was designed to heat water to the temperature required for pasteurization to occur before recuperating heat while cooling treated water down to a safe-to-handle temperature. The system is then compared to other common thermal treatment methods including batch-boiling over open fires and improved cookstoves. Results from computational modeling and empirical analysis show that the water pasteurizer significantly increases the overall water treatment capacity (from 7.9 to 411 L/h, adjusted for one hour of treatment via household boiling and operation of the water pasteurizer at steady-state, respectively) and uses far less biomass fuel (from 22 to 5.5 g/L, adjusted for treatment of 1 L of water via household boiling and operation of the water pasteurizer at steady-state, respectively). Notable comparisons to the batch-boiling of water over institutional-sized traditional and improved cookstoves are also demonstrated. Further, the results of fecal indicator reduction through the system (8 log and 6 log reduction of E. coli and bacteriophage MS2, respectively) suggest compliance with US-EPA (6 log and 4 log reduction of E. coli and bacteriophage MS2, respectively) and WHO requirements (effluent concentrations below the detection limit, specified as <1 E. coli CFU/100 mL and <10 bacteriophage MS2 PFU/mL) for the reduction in and effluent concentration of E. coli and bacteriophage for water treatment processes. It is recommended that engineers continue to explore the use of heat transfer and microorganism reduction theory to design technologies that increase the capacity and efficiency for thermal water purification that uses locally-available biomass resources.
Density, Viscosity, and Excess Properties of Ternary Aqueous Mixtures of MDEA + MEA, DMEA + MEA, and DEEA + MEA
Authors: Karunarathne Sumudu S. , Eimer Dag A. , Jens Klaus J. , Øi Lars E.
Published: February 2020

This study presents the measured densities and viscosities of three ternary aqueous mixtures of tertiary and primary amines. The tertiary amines of n-methyldiethanolamine (MDEA), dimethylethanolamine (DMEA), diethylethanolamine (DEEA), and the primary amine monoethanolamine (MEA) at different concentrations (mass%) were mixed to prepare the liquid mixtures. The excess molar volume VE of the mixtures was analyzed using measured densities to acquire a better understanding of the molecular packing and intermolecular interactions in the mixtures. The excess free energy of activation ∆GE* and excess entropy of activation ∆SE* for viscous flow were determined from the measured viscosities by implementing the theory of rate processes of Eyring. Correlations based on the Redlich–Kister type polynomial were adopted to correlate the excess properties VE and ∆GE* as a function of the amine mole fraction and temperature. The results showed that the correlations were able to represent the measured data with satisfactory accuracies for engineering calculations.
Insights from the Historical Lived Experience of a Fragmented Economy of Welfare in Britain: Poverty, Precarity and the Peck Family 1928–1950
Authors: Edwards Rosalind , Gillies Val
Published: February 2020

We draw upon a ‘small history’ of one family to throw light on lived experience of welfare in the past, and consider how it may provide some glimpses into what Britain’s current economy of welfare trajectory could mean, where the state welfare safety net has holes and an ad hoc charitable safety net is being constructed beneath them. Using archived case notes from the Charity Organisation Society across the interwar period to the comprehensive welfare state, we discuss one family’s negotiation of poverty and the fragmented economy of welfare involving nascent state provision and a safety net of myriad charitable bodies, and the need to be judged as respectable and worthy. While lived experience of inequalities of assessment criteria, provision and distribution provide some indication for the potential trajectory of contemporary welfare in Britain, towards fragmented localised settlements, the small history also reveals a muted story of alternatives and reliability.