bluuebunny/crossref_metadata_2025 huggingface dataset:
Study on Two-Phase Permeation of Oxygen and Electrolyte in Lithium Air Battery Electrode Based on Digital Twin
Authors: Li Qiang , Zhang Tanghu , Zhang Tianyu , Xue Zhichao , Sun Hong
Published: September 2022

In this paper, the saturation of electrolytes on the mass transfer property of porous electrodes in non-aqueous lithium air batteries has been studied based on digital twin. Herein, we reconstruct the porous cathode based on X-ray micro-computed tomography (μct) and quantitatively analyze the pore size distribution, specific surface area, triple-phase interface area, conductivity and diffusion coefficient of reactants at varying filling degrees of the electrolyte. The results derived from digital twin provide insight into the gas–liquid two-phase mass transfer performance in the porous cathode with various degrees of electrolyte saturation and demonstrate that the optimum electrolyte saturation is 60%.
Thermodynamic Optimization of Advanced Organic Rankine Cycle Configurations for Geothermal Energy Applications
Authors: Mustapić Nenad , Brkić Vladislav , Duić Željko , Kralj Toni
Published: September 2022

The Organic Rankine Cycle (ORC) is commonly accepted as a viable technology to convert from low to medium temperature geothermal energy into electrical energy. In practice, the reference technology for converting geothermal energy to electricity is the subcritical simple ORC system. Over time, geothermal ORC plants with more complex configurations (architectures) have been developed. In the open literature, a large number of advanced architectures or configurations have been introduced. An analysis of the scientific literature indicates that there is some confusion regarding the terminology of certain advanced ORC system architectures. A new categorization of advanced configurations has been proposed, with a special emphasis on the application of geothermal energy. The basic division of advanced plant configurations is into dual-pressure and dual-stage ORC systems. In this study, the real potential of advanced ORC architectures or configurations to improve performance as compared with the simple ORC configuration was explored. The research was conducted for a wide range of geothermal heat source temperatures (from 120 °C to 180 °C) and working fluids. Net power output improvements as compared with the basic subcritical simple ORC (SORC) configuration were examined. The ability to produce net power with different ORC configurations depends on the magnitude of the geothermal fluid temperature and the type of working fluid. At a lower value of geothermal fluid temperature (120 °C), the most net power of 18.71 (kW/(kg/s)) was realized by the dual-pressure ORC (DP ORC configuration) with working fluid R1234yf, while the double stage serial-parallel ORC configuration with a low-temperature preheater in a high-temperature stage ORC (DS parHTS LTPH ORC) generated 18.51 (kW/(kg/s)) with the working fluid combination R1234yf/R1234yf. At 140 °C, three ORC configurations achieved similar net power values, namely the simple ORC configuration (SORC), the DP ORC configuration, and the DS parHTS LTPH ORC configuration, which generated 31.03 (kW/(kg/s)) with R1234yf, 31.07 (kW/(kg/s)) with R1234ze(E), and 30.96 (kW/(kg/s)) with R1234ze(E)/R1234yf, respectively. At higher values of geothermal fluid temperatures (160 °C and 180 °C) both the SORC and DP ORC configurations produced the highest net power values, namely 48.58 (kW/(kg/s)) with R1234ze(E), 67.23 (kW/(kg/s)) with isobutene for the SORC configuration, and 50.0 (kW/(kg/s)) with isobutane and 69.67 (kW/(kg/s)) with n-butane for the the DP ORC configuration.
Assessing the Potential of Rooftop Photovoltaics by Processing High-Resolution Irradiation Data, as Applied to Giessen, Germany
Authors: Koch Hannes , Lechner Stefan , Erdmann Sebastian , Hofmann Martin
Published: September 2022

In recent years, prices for photovoltaics have fallen steadily and the demand for sustainable energy has increased. Consequentially, the assessment of roof surfaces in terms of their suitability for PV (Photovoltaic) installations has continuously gained in importance. Several types of assessment approaches have been established, ranging from sampling to complete census or aerial image analysis methodologies. Assessments of rooftop photovoltaic potential are multi-stage processes. The sub-task of examining the photovoltaic potential of individual rooftops is crucial for exact case study results. However, this step is often time-consuming and requires lots of computational effort especially when some form of intelligent classification algorithm needs to be trained. This often leads to the use of sampled rooftop utilization factors when investigating large-scale areas of interest, as data-driven approaches usually are not well-scalable. In this paper, a novel neighbourhood-based filtering approach is introduced that can analyse large amounts of irradiation data in a vectorised manner. It is tested in an application to the city of Giessen, Germany, and its surrounding area. The results show that it outperforms state-of-the-art image filtering techniques. The algorithm is able to process high-resolution data covering 1 km2 within roughly 2.5 s. It successfully classifies rooftop segments which are feasible for PV installations while omitting small, obstructed or insufficiently exposed segments. Apart from minor shortcomings, the approach presented in this work is capable of generating per-rooftop PV potential assessments at low computational cost and is well scalable to large scale areas.
Numerical Investigation of the Effect of Hub Gaps on the 3D Flows Inside the Stator of a Highly Loaded Axial Compressor Stage
Authors: An Guangfeng , Fan Zhu , Qiu Ying , Wang Ruoyu , Yu Xianjun , Liu Baojie
Published: September 2022

Both the compressor performance and the 3D flows inside the stator passage are significantly impacted by the stator hub gap. The interplay between leakage flow and corner separation within a cantilevered stator of a highly loaded, low-speed axial compressor with a succession of stator hub gaps was examined numerically in this paper. Firstly, the simulated results were compared with the measured results, including the compressor characteristics, the 3D flow structures, and the flow fields at the stator outlet. The results revealed that the used CFD solver, as well as the corresponding setup, can reproduce the flow not only in terms of the trend along with the stator hub gap, but also in terms of the specific scale of the 3D flow structure. Hence, it is feasible enough to be applied in the present investigation. Secondly, the flow mechanisms of the interplay between the corner separation and the leakage flow with different stator hub gaps were analyzed. It was found that the velocity of the leakage flow is the key parameter that dominates the flow structures as well as the compressor performance. Additionally, a simple metric was proposed to be used to choose the optimum stator hub gap. By comparing our results with those from published research, this metric was proven to be feasible. Finally, it is also discussed how the stator hub gap affected the stator inlet flow and rotor performance. It is demonstrated that the stator passage flow blockage can affect the upstream flow field. As a result, the performance of the rotor tends to vary in the opposite direction to that of the stator.
A Study Exploring Opportunities to Utilize Wind Charge in Bangladesh
Authors: Muhibbullah Muhammad , Sadat Quazi Taif , Subramaniam Umashankar
Published: September 2022

Wind charge is produced naturally in space. Knowing the nature of space charge is important for various purposes. If the charge is received for the whole year long by an antenna, then, in this process, the charge can be used as electric power. In the present work, the nature of wind charge in space in the cities of Dhaka and Narayanganj was observed. A net-type antenna was used to receive the wind charge. The results show that the power decreased with the antenna gaps. The output power increased with the antenna’s gross area and the speed of air. The overall output power was increased with humidity. It was shown that wind with a higher distance from the ground carries more electric charge. This research reveals that electric charge is inhomogeneous in wind, and it is collectable as electric power. The nature of the results is similar in both cities, but the output power is larger in Dhaka than in Narayanganj. This alternative power source is environmentally friendly, and it reduces thunder and lighting due to charge being taken from wind. Thus, this creates a more danger-free environment.
Understanding Urban Heat Vulnerability Assessment Methods: A PRISMA Review
Authors: Li Fei , Yigitcanlar Tan , Nepal Madhav , Thanh Kien , Dur Fatih
Published: September 2022

Increasingly people, especially those residing in urban areas with the urban heat island effect, are getting exposed to extreme heat due to ongoing global warming. A number of methods have been developed, so far, to assess urban heat vulnerability in different locations across the world concentrating on diverse aspects of these methods. While there is growing literature, thorough review studies that compare, contrast, and help understand the prospects and constraints of urban heat vulnerability assessment methods are scarce. This paper aims to bridge this gap in the literature. A systematic literature review with the preferred reporting items for systematic reviews and meta-analyses (PRISMA) approach is utilized as the methodological approach. PRISMA is an evidence-based minimum set of items for reporting in systematic reviews and meta-analyses. The results are analyzed in three aspects—i.e., indicators and data, modelling approaches, and validation approaches. The main findings disclose that: (a) Three types of indicators are commonly used—i.e., demographic properties and socioeconomic status, health conditions and medical resources, and natural and built environmental factors; (b) Heat vulnerability indexing models, equal weighting method, and principal component analysis are commonly used in modelling and weighting approaches; (c) Statistical regressions and correlation coefficients between heat vulnerability results and adverse health outcomes are commonly used in validation approaches, but the performance varies across studies. This study informs urban policy and generates directions for prospective research and more accurate vulnerability assessment method development.
Wind Parks in Poland—New Challenges and Perspectives
Authors: Talarek Karolina , Knitter-Piątkowska Anna , Garbowski Tomasz
Published: September 2022

The wind farm market in Poland evolved very dynamically in the years 2000–2015. Unfortunately, the high public resistance caused the government in 2016 to freeze the development of this industry by introducing a restrictive act, which practically stopped the wind farm industry overnight. The climate aspects, such as reduction of the carbon footprint, which have been considered and widely discussed for several years at the European Union forums, were a chance to change this situation. The new regulations gave hope that the wind energy industry in Poland would soon be unblocked, unfortunately the commitment to coal was still an effective barrier, which is clearly visible in the presented study. The Russian aggression against Ukraine, which resulted in a blockade of hydrocarbon imports, has completely changed the center of gravity of the Polish energy and heating economy. The article focuses on the accelerated changes in the renewable energy sources (RESs) and the related legislation, especially emphasizing the prospect of building offshore wind farms. The huge European energy crisis means that new solutions, both legislative and technological, which will allow to quickly switch to green energy, must appear in Poland immediately. The direct conversion of green energy from RES farms into thermal energy in the planned investment in heat energy plants is discussed. This article also presents a broad view of new opportunities as well as the challenges and prospects that have recently arisen in the wind energy industry in Poland.
Impact of the Convolutional Neural Network Structure and Training Parameters on the Effectiveness of the Diagnostic Systems of Modern AC Motor Drives
Authors: Skowron Maciej , Kowalski Czeslaw T. , Orlowska-Kowalska Teresa
Published: September 2022

Currently, AC motors are a key element of industrial and commercial drive systems. During normal operation, the machines may become damaged, which may pose a threat to the users. Therefore, it is important to develop a fault detection method that allows for the detection of a fault at an early stage. Among the currently used diagnostic systems, applications based on deep neural structures are dynamically developed. Despite many examples of applications of deep learning methods, there are no formal rules for selecting the network structure and parameters of the training process. Such methods would make it possible to shorten the implementation process of deep networks in diagnostic systems of AC machines. The article presents a detailed analysis of the influence of deep convolutional network hyperparameters and training procedures on the precision of the interturn short-circuits detection system. The studies take into account the direct analysis of phase currents through the convolutional network for induction motors and permanent magnet synchronous motors. The research results presented in the article are an extension of the authors’ previous research.
A Survey of Recent Advances in the Smart Management of Microgrids and Networked Microgrids
Authors: Mannini Romain , Eynard Julien , Grieu Stéphane
Published: September 2022

Microgrids (MGs) and networked (interconnected) microgrids (NMGs) are emerging as an efficient way for integrating distributed energy resources (DERs) into power distribution systems. MGs and NMGs can disconnect from the main grid and operate autonomously, strengthen grid resilience, and help mitigate grid disturbances and maintain power quality. In addition, when supported by sophisticated and efficient management strategies, MGs and NMGs have the ability to enhance power supply reliability. However, their deployment comes with many challenges, in particular regarding the efficient management of DERs. That is why a survey of recent advances in the smart management—the term refers to a variety of planning and control tasks—of MGs and NMGs is presented in this paper. It aims at establishing a picture of strategies and identifying trends in methods. The reader is provided with an in-depth analysis of a variety of papers recently published in peer-reviewed journals: the way the methods are used and the common issues addressed by the scientific community are discussed. Following this analysis, one can especially observe that (1) model-based predictive control (MPC) is emerging as a competitive alternative to conventional methods, in particular in voltage and frequency regulation and DER management (2) due to their ability to handle complex tasks, data-driven strategies are getting more and more attention from the scientific community (3) game theory (GT) is a very good candidate for efficient management of complex systems as NMGs (4) MPC and artificial intelligence are increasingly being used for proper MG islanded operation or to manage electric vehicles (EVs) efficiently.
Fuzzy Control Strategy Applied to an Electromagnetic Frequency Regulator in Wind Generation Systems
Authors: Crisóstomo Daniel C. C. , do Nascimento Thiago F. , Nunes Evandro A. D. F. , Villarreal Elmer , Pinheiro Ricardo , Salazar Andrés
Published: September 2022

This paper presents the implementation of a fuzzy control strategy for speed regulation of an electromagnetic frequency regulator (EFR) prototype, aiming to eliminate the dependence on knowledge of physical parameters in the most diverse operating conditions. Speed multiplication is one of the most important steps in wind power generation. Gearboxes are generally used for this purpose. However, they have a reduced lifespan and a high failure rate, and are still noise sources. The search for new ways to match the speed (and torque) between the turbine and the generator is an important research area to increase the energy, financial, and environmental efficiency of wind systems. The EFR device is an example of an alternative technology that this team of researchers has proposed. It considers the main advantages of an induction machine with the rotor in a squirrel cage positively. In the first studies, the EFR control strategy consisted of the conventional PID controllers, which have several limitations that are widely discussed in the literature. This strategy also limits the EFR’s performance, considering its entire operating range. The simulation program was developed using the Matlab/Simulink platform, while the experimental results were obtained in the laboratory emulating the EFR-based system. The EFR prototype has 2 poles, a nominal power of 2.2 kW, and a nominal frequency of 60 Hz. Experimental results were presented to validate the efficiency of the proposed control strategy.
Design Aspects and Performance Evaluation of Pole-Phase Changing Induction Machines
Authors: Bitsi Konstantina , Bosga Sjoerd G. , Wallmark Oskar
Published: September 2022

Pole-phase changing induction machines (IMs) offer the capability to extend the torque-speed envelope compared to their fixed pole-phase counterparts. Dynamic pole-changing can achieve higher torque levels at lower speeds, utilizing higher pole numbers, and extended flux-weakening range with lower pole-number operations. This paper investigates the design impact on the optimum pole-phase changing behavior and respective split of the operating region to different pole-phase operations. Additionally, the improvement in terms of the overall torque per ampere capability and efficiency is illustrated. For the purposes of the analysis, two different IMs with wound independently-controlled stator coils (WICSC) and different original pole numbers are evaluated in an effort to quantify the extent of the benefits of pole-phase changing. These geometries correspond to machines that were originally designed with 2- and 6 magnetic poles, respectively. It is shown that, in the case of the original 2-pole WICSC machine, shifting to a higher pole number is notably beneficial in terms of efficiency in a significant part of the operating region, whereas in the original 6-pole, both higher and lower pole numbers significantly enhance the overall torque capability and efficiency. The results highlight the notable benefits of pole-phase changing IMs and offer deep insight towards the derivation of standard design guidelines for these machines.
Experimental Study on Deformation Behavior and Permeability Evolution of Sandstone Responding to Mining Stress
Authors: Liu Yang , Zhang Tong , Wu Jun , Song Zhengyang , Wang Fei
Published: September 2022

Mining-induced hydromechanical behavior of sandstone is critical to mining safety and disaster prevention. To investigate the evolution behavior of the mechanical and permeability properties of sandstone, mining-induced stress was imitated by increasing axial stress and decreasing confining stress, and a set of hydromechanical experiments were further performed, incorporating the effect of in situ stress, pore pressure, and mining stress. The results show the similar variation tendencies of the deformation and permeability of sandstone under different loading paths of in situ stress and pore pressure. Most sandstone samples maintain a compression state for the peak stress condition. The failure mode evolved from shear failure to shear–tension failure with the increase in in situ stress. The stress-relief effect significantly effects the permeability, since the permeability of sandstone increases exponentially with decreasing effective confining stress. The growth rate of permeability in Stage II is significantly greater than that in Stage I. One order of magnitude of permeability was presented at the peak stress situation. A fitting exponential model based on the alteration of effective confining stress was proposed to describe the permeability evolution dominated by the stress-relief effect, and the discovered permeability model can accurately describe the experimental results. The research results provide significant guidance for understanding the hydromechanical behavior and water hazard prevention for underground coal mines.
Multi-Objective Optimization of Building Environmental Performance: An Integrated Parametric Design Method Based on Machine Learning Approaches
Authors: Lu Yijun , Wu Wei , Geng Xuechuan , Liu Yanchen , Zheng Hao , Hou Miaomiao
Published: September 2022

Reducing energy consumption while providing a high-quality environment for building occupants has become an important target worthy of consideration in the pre-design stage. A reasonable design can achieve both better performance and energy conservation. Parametric design tools show potential to integrate performance simulation and control elements into the early design stage. The large number of design scheme iterations, however, increases the computational load and simulation time, hampering the search for optimized solutions. This paper proposes an integration of parametric design and optimization methods with performance simulation, machine learning, and algorithmic generation. Architectural schemes were modeled parametrically, and numerous iterations were generated systematically and imported into neural networks. Generative Adversarial Networks (GANs) were used to predict environmental performance based on the simulation results. Then, multi-object optimization can be achieved through the fast evolution of the genetic algorithm binding with the database. The test case used in this paper demonstrates that this approach can solve the optimization problem with less time and computational cost, and it provides architects with a fast and easily implemented tool to optimize design strategies based on specific environmental objectives.
Assessment of Thermal Comfort in Rooms Equipped with a Decentralised Façade Ventilation Unit
Authors: Zender-Świercz Ewa , Telejko Marek , Galiszewska Beata , Starzomska Mariola
Published: September 2022

Thermal comfort affects not only the well-being of the occupants of a building but also the effectiveness of their learning and work efficiency. It can be disturbed if the ventilation airflow is increased when improving indoor air quality. When natural ventilation is used in the fall and winter period, the supply air temperature is low, resulting in a lack of thermal comfort. In existing buildings, there is often no place for mechanical ventilation; hence, decentralised façade ventilation units are increasingly used. The article presents an analysis of thermal comfort in rooms with this type of unit equipped with heat recovery exchangers of different efficiencies. Studies have shown that the alternating supply/exhaust airflow and the related unevenness of air streams flowing through the heat accumulator cause an inflow of low-temperature air, resulting in thermal discomfort. The highest value of the PMV index was −1.6, and the lowest was −4.1, which means that 54.8 to 100% of the occupants are dissatisfied with their thermal comfort. This means there is a need to change the construction of inlet/exhaust vents so that the stream of supply air is not directly parallel to the floor. In addition, the use of an air heater should be considered.
Utilization of Basalt Dust as Waste Material in Cement Grouts for Geothermal Application
Authors: Seńczuk Krzysztof , Sapińska-Śliwa Aneta , Kowalski Tomasz
Published: September 2022

Research on the utilization of the Earth’s heat focuses mainly on effective sourcing of energy accumulated in rock mass. One of the most important parameters is thermal conductivity, which can be modified using various compositions of cement grouts. Hardened cement slurry is intended to improve thermal conductivity. It should function as a sort of extension of the rock mass to the outer diameter of heat exchanger tubes. Regardless of the thermal conductivity of the rock, high conductivity of the grout increases the energy efficiency of the BHE. Heat accumulated in the rock mass can be extracted using borehole heat exchangers (BHE), in which high thermal conductivity of cement slurry is wanted over the entire length of the exchanger. Generally, in case of deep borehole heat exchangers (DBHE), it is recommended to use two types of cement slurry, one with reduced thermal conductivity in the upper part of the exchanger and grout with increased thermal conductivity in its lower part. When cementing geothermal wells, cement grout with decreased thermal conductivity along the entire length of the borehole is most commonly used. Geothermal boreholes extract geothermal water which, at the surface, is used for heating, for example. Then, after use, the cooled water is injected through injection holes. In this article, two different basalt dusts are examined. These dusts were obtained by crushing basalt boulders in open-pit mines. They were examined for their effect on thermal conductivity when added to grout. According to the Polish Ordinance of the Minister of Environment dated 9 December 2014 regarding the waste catalogue, they were classified as waste. The materials, named basalt dust A and basalt dust B, were used to create cement slurries with a water–cement ratio of 0.5–0.7 with a wide range of percentage concentration of basalt dust. The test results show that as concentrations in the slurry increase, the values of thermal conductivity and strength decrease. This correlation occurred for both tested additives.
Improved Whale Optimization Algorithm Based on Hybrid Strategy and Its Application in Location Selection for Electric Vehicle Charging Stations
Authors: Li Yongjing , Pei Wenhui , Zhang Qi
Published: September 2022

The charging station location model is a nonlinear programming model with complex constraints. In order to solve the problems of weak search ability and low solution accuracy of the whale optimization algorithm (WOA) in solving location models or high-dimensional problems, this paper proposes an improved whale optimization algorithm (IWOA) based on hybrid strategies. Chaos mapping and reverse learning mechanism are introduced in the original algorithm, and the change mode of convergence factor and probability threshold is improved. Through optimization experiments on 18 benchmark functions, the test results show that IWOA has the best solution ability. Finally, IWOA is used to solve a site selection optimization model aiming at the minimum comprehensive cost. The results show that the proposed algorithm and model can effectively reduce the comprehensive cost of site selection. This provides a necessary decision-making reference for the scientific site selection for electric vehicle charging stations.
Peak Shaving Methods of Distributed Generation Clusters Using Dynamic Evaluation and Self-Renewal Mechanism
Authors: Li Hongwei , Xu Qing , Wang Shitao , Song Huihui
Published: September 2022

As one of the power auxiliary services, peak shaving is the key problem to be solved in the power grid. With the rapid development of DGs, the traditional peak shaving scheduling method for centralized adjustable energy is no longer applicable. Thus, this paper proposes two-layer optimization methods of allocating the peak shaving task for DGs. Layer 1 mainly proposes four evaluation indexes and the peak shaving priority sequence can be obtained with modified TOPSIS, then the DG cluster’s task is allocated to the corresponding DGs. On the basis of dynamic evaluation and the self-renewal mechanism, layer 2 proposes a peak shaving optimization model with dynamic constraints which assigns peak shaving instructions to each cluster. Finally, the effectiveness of the method is verified by using the real DGs data of a regional power grid in China based on the MATLAB simulation platform. The results demonstrate that the proposed methods can simply the calculation complexity by ranking the DGs in the peak shaving task and update the reliable aggregate adjustable power of each cluster in time to allocate more reasonably.
Quantitative Evaluation of Water-Flooded Zone in a Sandstone Reservoir with Complex Porosity–Permeability Relationship Based on J-Function Classification: A Case Study of Kalamkas Oilfield
Authors: Li Xuanran , Wang Jingcai , Zhao Dingding , Ni Jun , Lin Yaping , Zhang Angang , Zhao Lun , Liu Yuming
Published: September 2022

The water-flooded zone in a sandstone reservoir with a complex porosity–permeability relationship is difficult to interpret quantitatively. Taking the P Formation of Kalamkas Oilfield in Kazakhstan as an example, this paper proposed a reservoir classification method that introduces the J-function into the crossplot of resistivity and oil column height to realize the classification of sandstone reservoirs with a complex porosity–permeability relationship. Based on the classification results, the initial resistivity calculation models of classified reservoirs were established. The oil–water seepage experiment was performed for classified reservoirs to measure the lithoelectric parameters and establish the relationship between water production rate and resistivity for these reservoirs, and then water production was quantitatively calculated according to the difference between the inverted initial resistivity and the measured resistivity. The results show that the reservoirs with an unclear porosity–permeability relationship can be classified by applying the J-function corresponding to grouped capillary pressure curves to the crossplot of oil column height and resistivity, according to the group average principle of capillary pressure curves. This method can solve the problem that difficult reservoir classification caused by a weak porosity–permeability correlation. Moreover, based on the results of reservoir classification, the water production rate and resistivity model of classified reservoirs is established. In this way, the accuracy of quantitative interpretation of the water-flooded zone in the reservoir can be greatly improved.
Fast Charging Optimization for Lithium-Ion Batteries Based on Improved Electro-Thermal Coupling Model
Authors: Li Ran , Wei Xue , Sun Hui , Sun Hao , Zhang Xiaoyu
Published: September 2022

New energy automobiles possess broad application prospects, and the charging technology of vehicle power batteries is one of the key technologies in the development of new energy automobiles. Traditional lithium battery charging mostly adopts the constant current-constant voltage method, but continuous and frequent charging application conditions will cause temperature rise and accelerated capacity decay, which easily bring about safety problems. Aiming at the above-mentioned problems related to the charging process of lithium-ion batteries, this paper proposes an optimization strategy and charging method for lithium-ion batteries based on an improved electric-thermal coupling model. Through the HPPC experiment, the parameter identification of the second-order RC equivalent circuit model was completed, and the electric-thermal coupling model of the lithium battery was established. Taking into account the two factors of charging time and charging temperature rise, the multi-stage charging strategy of the lithium-ion battery is optimized by the particle swarm optimization algorithm. The experimental results show that the multi-stage constant current charging method proposed in this paper not only reduces the maximum temperature during the charging process by an average of 0.83% compared with the maximum temperature of the battery samples charged with the traditional constant current-constant voltage (CC-CV) charging method but also reduces the charging time by an average of 13.87%. Therefore, the proposed optimized charging strategy limits the charging temperature rise to a certain extent on the basis of ensuring fast charging and provides a certain theoretical basis for the thermal management of the battery system and the design and safe charging method of the battery charging system.
Robust Differentiator-Based NeuroFuzzy Sliding Mode Control Strategies for PMSG-WECS
Authors: Khan Malak Adnan , Khan Qudrat , Khan Laiq , Khan Imran , Alahmadi Ahmad Aziz , Ullah Nasim
Published: September 2022

A robust control algorithm is always needed to harvest maximum power from a Wind Energy Conversion System (WECS) by operating it consistently at a Maximum Power Point (MPP) in the presence of wind speed variations. In this work, a Maximum Power Point Tracking (MPPT) control algorithm is designed via Conventional Sliding Mode Control (CSMC), the Super Twisting Algorithm (STA), and the Real Twisting Algorithm (RTA) and is applied to a Permanent Magnet Synchronous Generator (PMSG)-based WECS. CSMC is model-based whereas the STA and RTA are model-free controllers. In practice, the unavailability of nonlinear terms and aerodynamic forces deteriorates the performance of these controllers. Thus, an offline NeuroFuzzy algorithm is incorporated to estimate the nonlinear drift and control input channel to improve the robustness of these algorithms. In addition, the generator shaft speed and its missing derivative is recovered via a Uniform Robust Exact Differentiator (URED). In order to carry out a comprehensive comparative study among the three competitors, the overall system is simulated in a closed loop under the action of these controllers at three different operating conditions, i.e., nominal, varying load and inertia, and varying wind speed, using MATLAB/Simulink. The acquired results confirm the superiority of the RTA over the STA and CSMC in terms of robustness and chatter reduction.
Solar Radiation Forecasting Using Machine Learning and Ensemble Feature Selection
Authors: Solano Edna S. , Dehghanian Payman , Affonso Carolina M.
Published: September 2022

Accurate solar radiation forecasting is essential to operate power systems safely under high shares of photovoltaic generation. This paper compares the performance of several machine learning algorithms for solar radiation forecasting using endogenous and exogenous inputs and proposes an ensemble feature selection method to choose not only the most related input parameters but also their past observations values. The machine learning algorithms used are: Support Vector Regression (SVR), Extreme Gradient Boosting (XGBT), Categorical Boosting (CatBoost) and Voting-Average (VOA), which integrates SVR, XGBT and CatBoost. The proposed ensemble feature selection is based on Pearson coefficient, random forest, mutual information and relief. Prediction accuracy is evaluated based on several metrics using a real database from Salvador, Brazil. Different prediction time-horizons are considered: 1 h, 2 h and 3 h ahead. Numerical results demonstrate that the proposed ensemble feature selection approach improves forecasting accuracy and that VOA performs better than the other algorithms in all prediction time horizons.
Numerical Investigation of Liquid Flow Behaviors through Closed Rough Fractures in the Self-Propped Shale Formation
Authors: Wang Qiqi , Chen Mian , Lv Jiaxin
Published: September 2022

The surface morphology of fractures formed by hydraulic fracturing is usually rough. The roughness of the fracture surface is the main reason the actual fracture conductivity deviates from the ideal flat plate model result. In this paper, based on the three-dimensional reconfiguration of actual rough hydraulic fractures, a randomly generated geometric model of a micro-convex body with a rough fracture surface is used as an example of a hydraulic fracture in a shale reservoir. Assuming that the flow in the fracture conforms to the laminar flow pattern, the velocity and pressure fields of the fluid flow on the fracture surface are solved by the finite element method. The effects of micro-convex body size, uniformity, density, and shape on the non-uniform flow of the rough fracture surface are analyzed. The three-dimensional model shows that the average velocity is minimum in the near fully closed fracture. The fluid bypasses the micro-convex body during the flow, forming multiple nonlinear flow regions. The streamlined tortuosity increases with the density and size of the micro-convex bodies and depends on the distribution of the micro-convex areas. The bypassing accelerates the pressure drop and slows down the flow rate. The greater the degree of micro-convex body aggregation, the more significant the decrease in flow velocity. The more locations where the curvature of the micro-convex edge is not zero, the more nonlinear flow zones can significantly reduce the flow rate and thus affect oil and gas production. Targeted optimization of the proppant placement pattern to make the trailing part of the micro-convex body as close to streamlined as possible can reduce the nonlinear flow area and slow down the flow rate reduction.
A Review of Research on Tree Risk Assessment Methods
Authors: Li Haibin , Zhang Xiaowei , Li Zeqing , Wen Jian , Tan Xu
Published: September 2022

As an important part of the urban environment, trees have certain risks while living in harmony with humans. For example, the failure of trees in extreme weather may cause casualties and damage to public and private; the decline and death of old and valuable trees can have an impact on the diversity and cultural value of trees. This paper outlines the theories related to tree risk and the development of tree risk assessment, evaluates the advantages and disadvantages of various tree risk assessment methods in existing studies, and explains some factors affecting the bearing capacity and related applications using knowledge of tree mechanics. Approaches in modern probing techniques are applied to study the response and loading of tree crowns and branches under wind loads, the application of different non-destructive testing techniques in visual assessment for detecting internal defects and root distribution of trees, and the role and impact of objective quantitative test results on tree risk assessment. Finally, the future development direction of tree risk assessment is predicted, which provides an important reference for research on tree risk assessment.
Interaction of Subculture Cycle, Hormone Ratio, and Carbon Source Regulates Embryonic Differentiation of Somatic Cells in Pinus koraiensis
Authors: Ren Yuhui , Yu Xiaoqian , Xing Honglin , Tretyakova Iraida Nikolaevna , Nosov Alexander Mikhaylovich , Yang Ling , Shen Hailong
Published: September 2022

During somatic embryogenesis of Pinus koraiensis, the ability of the embryogenic callus to produce embryos gradually decreases with long-term proliferative culture, which seriously affects large-scale application of this technology. In this study, embryogenic calli of Korean pine 1–100 cell line were used as materials. It was found that in the 7-day subculture cycle of embryogenic calli the somatic embryogenic potential of Korean pine remained for the longer time. In comparison with a subculture cycle of 14 days, indoleacetic acid (IAA), soluble sugar, and starch contents in embryogenic callus were higher with a subculture cycle of 7 days, while hydrogen peroxide (H2O2) content showed the opposite trend. Further, low levels of endogenous abscisic acid (ABA) and high levels of IAA could inhibit somatic embryogenesis of P. koraiensis calli. Among different carbon sources, maltose produced more storage materials and higher superoxide dismutase (SOD) and catalase (CAT) activities than sucrose, which was conducive to cell differentiation and somatic embryogenesis. The results revealed the physiological characteristics of the loss of embryogenic capacity of Korean pine embryogenic callus and provided a basis for the long-term maintenance of its somatic embryogenic capacity.
Exploring the Use of Solid Biofertilisers to Mitigate the Effects of Phytophthora Oak Root Disease
Authors: López-Sánchez Aida , Capó Miquel , Rodríguez-Calcerrada Jesús , Peláez Marta , Solla Alejandro , Martín Juan A. , Perea Ramón
Published: September 2022

Oak forests are facing multiple threats due to global change, with the introduction and expansion of invasive pathogens as one of the most detrimental. Here, we evaluated the use of soil biological fertiliser Biohumin® to improve the response of Quercus ilex L. to the soil-borne pathogen Phytophthora cinnamomi Rands by using one-year-old seedlings fertilised at 0, 12.5, and 25% concentrations of Biohumin® (v/v). Our hypothesis was that plant vigour and response to the pathogen would improve with Biohumin®. The effects of soil infestation and fertilisation were tested by assessing plant survival, growth, and physiology. The soil infested with P. cinnamomi negatively affected all the studied traits. We observed that a moderate concentration of Biohumin® (12.5%) increased plant survival. However, a high concentration (25%) reduced the survival compared with the control, probably as a result of the stress caused by both biotic (infection) and abiotic (soil toxicity) factors. Biohumin® at the highest concentration reduced the plant height-to-stem diameter ratio (H/D) and negatively affected plant biomass and physiological activity. Combined biofertilisation and infection induced synergistic negative effects in the leaf water potential compared with infection and fertilisation applied alone. A higher concentration of Biohumin® may favour pathogens more than plants. Further studies should explore the causes of the negative effect of the high concentration of Biohumin® observed here and evaluate if lower concentrations may benefit plant survival and physiology against soil pathogens.
Relationships between Xylem Transport, Anatomical, and Mechanical Traits at Organ Level of Two Cupressaceae Species
Authors: Xie Jiang-Bo , Zhang Bo-Na , Wang Zhong-Yuan
Published: September 2022

Compared to arid regions, forests in humid regions can be more vulnerable to drought as they are not used to, and thus not adapted to, water stress. Therefore, it is vital to understand the drought responses of woodland species in humid areas. Xylem structures and functions of species growing in the humid regions are the key to their drought responses. Two Cupressaceae species (including three taxa: Sequoia sempervirens, Taxodium distichum and its variety Taxodium distichum var. imbricatum) grown in a mesic common garden were targeted, and their xylem hydraulic function (hydraulic conductivity, Ks; cavitation resistance, P50), anatomical structure (tracheid and pit structure), and mechanical support (wood density, WD; tracheid thickness-to-span ratio, Ttob) were measured. Likewise, we analyzed the differences in hydraulic function and anatomical structure of xylem in branches and roots, and the quantitative relationship between xylem water transport, anatomical structure, and mechanical support. Our results showed that roots had a higher hydraulic conductivity and a weaker cavitation resistance than branches. There was no safety–efficiency trade-off in the branches and roots within species. Tracheid mechanical support had a trade-off relationship with Ks or P50 (negative correlation appeared in branch Ks ~ WD and root Ks ~ Ttob of S. sempervirens, root P50 ~ Ttob of T. distichum var. imbricatum, and branch P50 ~ WD). There was no trade-off in anatomical structure, which led to no safety–efficiency trade-off in xylem function. Our results suggest that the two species exhibit both low efficiency and low safety in xylem, and that there is no safety–efficiency trade-off in branches and roots. The reason behind this is that the structural demand for high safety and high efficiency differs (i.e., the root Ks of S. sempervirens was strongly controlled by Dh; in contrast, the root P50 of S. sempervirens was strongly determined by tracheid density, N). Namely, the structural basis for a safety–efficiency trade-off does not exist and therefore trade-offs cannot be achieved.
Faster Measurement for Formaldehyde Emissions from Veneered Particleboard Based on the Standardized Desiccator Method
Authors: Zhang Jijuan , Gui Zhaozhen , Chen Yang , Xue Li , Song Feifei , Zhang Zhongfeng
Published: September 2022

Desiccator method is a fast and effective way to measure formaldehyde emissions from wood-based panels. This method is popular in the Chinese furniture industry and testing institutions. It is also an important method for production control due to its characteristics of low cost, fast speed, and simple operation. In order to further increase the measurement speed of the desiccator method, this study focuses on the impact of temperature and time conditions in regard to standard GB/T 17657-2013. The corresponding relationships for the measurement of formaldehyde emissions between the standardized desiccator method and those under different temperature and time conditions were studied. Four different experimental conditions were used: 60 °C for 6 h, 40 °C for 6 h, 43 °C for 4 h, and 45 °C for 4 h. The results showed that under 40 °C for 6 h the formaldehyde emissions measured using desiccator method were about twice as much as those under 20 °C for 24 h, at a correlation coefficient of R = 0.820. Under 45 °C for 4 h, the formaldehyde emissions measured using desiccator method were almost near equilibrium to emissions under 20 °C for 24 h, which was supported by a correlation coefficient of R = 0.955. A corresponding relationship between the formaldehyde emissions measurement results under these two conditions and those under the standardized conditions was observed. This relationship can be applied in the actual production control in the furniture industry in order to shorten the formaldehyde measurement time from 24 h to 6 h and 4 h, which can greatly improve measurement efficiency.
Author Identification from Literary Articles with Visual Features: A Case Study with Bangla Documents
Authors: Dhar Ankita , Mukherjee Himadri , Sen Shibaprasad , Sk Md Obaidullah , Biswas Amitabha , Gonçalves Teresa , Roy Kaushik
Published: September 2022

Author identification is an important aspect of literary analysis, studied in natural language processing (NLP). It aids identify the most probable author of articles, news texts or social media comments and tweets, for example. It can be applied to other domains such as criminal and civil cases, cybersecurity, forensics, identification of plagiarizer, and many more. An automated system in this context can thus be very beneficial for society. In this paper, we propose a convolutional neural network (CNN)-based author identification system from literary articles. This system uses visual features along with a five-layer convolutional neural network for the identification of authors. The prime motivation behind this approach was the feasibility to identify distinct writing styles through a visualization of the writing patterns. Experiments were performed on 1200 articles from 50 authors achieving a maximum accuracy of 93.58%. Furthermore, to see how the system performed on different volumes of data, the experiments were performed on partitions of the dataset. The system outperformed standard handcrafted feature-based techniques as well as established works on publicly available datasets.