bluuebunny/crossref_metadata_2025 huggingface dataset:
Pink-Beam Serial Synchrotron Crystallography at Pohang Light Source II
Authors: Kim Yongsam , Nam Ki Hyun
Published: November 2022

Serial crystallography (SX) enables the determination of room-temperature structures with minimal radiation damage. The photon flux of the pink beam of 1.2% bandwidth (BW) is one order higher than that of the monochromatic beam from a silicon crystal monochromator, and the energy resolution of 1.2% BW is enough to solve the structure; therefore, it is useful to use the pink beam for time-resolved serial synchrotron crystallography (SSX). Here, we demonstrate a pink-beam serial synchrotron crystallographic study at the 1C beamline at the Pohang Light Source II. Lysozyme crystals embedded in a beef tallow injection matrix were delivered through a syringe into the X-ray interaction point. Pink-beam SSX was performed with different X-ray exposure positions to the injection stream (center and edge) and X-ray exposure times (50 and 100 ms). All lysozyme crystal structures were successfully determined at a high resolution of 1.7 Å. Background analysis showed that X-ray diffraction data exposed to the edge of the injection stream could improve the signal-to-noise ratio. All the diffraction data and room-temperature lysozyme structures were comprehensively compared. The data collection strategy and analysis will be helpful in further pink-beam SSX experiments and their applications.
Merohedral Mechanism Twining Growth of Natural Cation-Ordered Tetragonal Grossular
Authors: Panikorovskii Taras L. , Galuskina Irina O. , Bocharov Vladimir N. , Shilovskikh Vladimir V. , Galuskin Evgeny V.
Published: November 2022

Garnet supergroup minerals are in the interest of different applications in geology, mineralogy, and petrology and as optical material for material science. The growth twins of natural tetragonal grossular from the Wiluy River, Yakutia, Russia, were investigated using single-crystal X-ray diffraction, optical studies, Raman spectroscopy, microprobe, and scanning electron microscopy. The studied grossular is pseudo-cubic (a = 11.9390 (4), c = 11.9469 (6) Å) and birefringent (0.01). Its structure was refined in the Ia3¯d, I41/acd, I41/a, and I4¯2d space groups. The I41/a space group was chosen as the most possible one due to the absence of violating reflections and ordering of Mg2+ and Fe3+ in two independent octahedral sites, which cause the symmetry breaking according to the group–subgroup relation Ia3¯d → I41/a. Octahedral crystals of (H4O4)4−-substituted grossular are merohedrally twinned by twofold axis along [110]. The mechanism of twining growth led to the generation of stacking faults on the (110) plane and results in the formation of crystals with a long prismatic habit.
Revisiting the Genetic, Taxonomic and Evolutionary Aspects of Chagas Disease Vectors of the Triatoma phyllosoma Subcomplex (Hemiptera, Triatominae)
Authors: Cesaretto Natália Regina , dos Reis Yago Visinho , de Oliveira Jader , Galvão Cleber , Alevi Kaio Cesar Chaboli
Published: November 2022

Triatoma bassolsae, T. longipennis, T. mazzottii, T. pallidipennis, T. phyllosoma and T. picturata are species that have great epidemiological importance in the transmission of Chagas disease in Mexico. However, there is no consensus regarding the specific status of these species, since they appear in various articles as species, subspecies and even subgenera. Thus, we revisited genetic, taxonomic and evolutionary data that allowed us to assess and discuss the specific status of these six species of the T. phyllosoma subcomplex. Phylogenetic studies were performed with nuclear (18S, 28S, ITS-2) and mitochondrial (16S, cytb, COI, COII, 12S) markers deposited in GenBank. In addition, data from experimental crosses were pooled and the genetic distance to the cytb gene was calculated. The phylogenetic reconstruction enabled us to rescue the six species as independent lineages. Post-zygotic reproductive isolation barriers (sterility and/or hybrid collapse) were observed for some experimental crosses. Although the other experimental crosses did not allow us to characterize reproductive barriers, these species showed high genetic distances in relation to the cytb gene (ranging from 4.6% to 14.9%). Thus, based on the revisited literature data, we confirmed the specific status of these six species of the T. phyllosoma subcomplex based on the phylogenetic and biological concepts of the species.
Explainable Machine Learning for Financial Distress Prediction: Evidence from Vietnam
Authors: Tran Kim Long , Le Hoang Anh , Nguyen Thanh Hien , Nguyen Duc Trung
Published: November 2022

The past decade has witnessed the rapid development of machine learning applied in economics and finance. Recent evidence suggests that machine learning models have produced superior results to traditional statistical models and have become the driving force for dramatic improvement in the financial industry. However, a much-debated question is whether the prediction results from black box machine learning models can be interpreted. In this study, we compared the predictive power of machine learning algorithms and applied SHAP values to interpret the prediction results on the dataset of listed companies in Vietnam from 2010 to 2021. The results showed that the extreme gradient boosting and random forest models outperformed other models. In addition, based on Shapley values, we also found that long-term debts to equity, enterprise value to revenues, account payable to equity, and diluted EPS had greatly influenced the outputs. In terms of practical contributions, the study helps credit rating companies have a new method for predicting the possibility of default of bond issuers in the market. The study also provides an early warning tool for policymakers about the risks of public companies in order to develop measures to protect retail investors against the risk of bond default.
Ant Colony Optimization ACO Based Autonomous Secure Routing Protocol for Mobile Surveillance Systems
Authors: Saleem Kashif , Ahmad Iftikhar
Published: November 2022

Sensing plays a vital role in enabling smart cities. The mobile surveillance of different sectors, the retransmission of radio signals, and package delivery are the main applications conducted by unmanned vehicles in smart cities. Multiple unmanned vehicles or miniaturized real-time flying machines with onboard sensors, whether land- or air-based, communicate with each other to form a flying sensor network. Almost all of these machines are battery-operated. Therefore, power preservation is an extremely important factor to be taken into consideration. This paper proposes a power-aware biologically inspired secure autonomous routing protocol (P-BIOSARP) that depends on enhanced ant colony optimization (eACO). eACO autonomously and securely routes the data packet, and the power awareness maintains the power consumption of the flying sensor network. The novel intelligent power-aware routing protocol was implemented in network simulator 2 to perform a number of experiments with different scenarios. The scenarios included varying numbers of total nodes and mobile nodes, different packet rates, mobile source nodes, multiple mobile routing nodes, and, on the side of security, the injection of malicious nodes. The proposed protocol is compared with BIOSARP, E-BIOSARP, and SRTLD in terms of energy consumption, the delivery ratio, and traffic overhead. The analysis shows that the P-BIOSARP remarkably reduces energy consumption compared to other well-known protocols implemented on real testbeds.
Microdrone-Based Indoor Mapping with Graph SLAM
Authors: Karam Samer , Nex Francesco , Chidura Bhanu , Kerle Norman
Published: November 2022

Unmanned aerial vehicles offer a safe and fast approach to the production of three-dimensional spatial data on the surrounding space. In this article, we present a low-cost SLAM-based drone for creating exploration maps of building interiors. The focus is on emergency response mapping in inaccessible or potentially dangerous places. For this purpose, we used a quadcopter microdrone equipped with six laser rangefinders (1D scanners) and an optical sensor for mapping and positioning. The employed SLAM is designed to map indoor spaces with planar structures through graph optimization. It performs loop-closure detection and correction to recognize previously visited places, and to correct the accumulated drift over time. The proposed methodology was validated for several indoor environments. We investigated the performance of our drone against a multilayer LiDAR-carrying macrodrone, a vision-aided navigation helmet, and ground truth obtained with a terrestrial laser scanner. The experimental results indicate that our SLAM system is capable of creating quality exploration maps of small indoor spaces, and handling the loop-closure problem. The accumulated drift without loop closure was on average 1.1% (0.35 m) over a 31-m-long acquisition trajectory. Moreover, the comparison results demonstrated that our flying microdrone provided a comparable performance to the multilayer LiDAR-based macrodrone, given the low deviation between the point clouds built by both drones. Approximately 85 % of the cloud-to-cloud distances were less than 10 cm.
Finite-Time Thermodynamic Modeling and Optimization of Short-Chain Hydrocarbon Polymerization-Catalyzed Synthetic Fuel Process
Authors: Yu Yajie , Xia Shaojun , Jin Qinglong , Rong Lei
Published: November 2022

The short-chain hydrocarbon polymerization-catalyzed synthetic fuel technology has great development potential in the fields of energy storage and renewable energy. Modeling and optimization of a short-chain hydrocarbon polymerization-catalyzed synthetic fuel process involving mixers, compressors, heat exchangers, reactors, and separators are performed through finite-time thermodynamics. Under the given conditions of the heat source temperature of the heat exchanger and the reactor, the optimal performance of the process is solved by taking the mole fraction of components, pressure, and molar flow as the optimization variables, and taking the minimum entropy generation rate (MEGR) of the process as the optimization objective. The results show that the entropy generation rate of the optimized reaction process is reduced by 48.81% compared to the reference process; among them, the component mole fraction is the most obvious optimization variable. The research results have certain theoretical guiding significance for the selection of the operation parameters of the short-chain hydrocarbon polymerization-catalyzed synthetic fuel process.
Correspondence Heuristic and Filter-Empowerment Heuristic: Investigating the Reversed Gender Achievement Gap in a Sample of Secondary School Students in Saudi Arabia within the Framework of Educational and Learning Capital
Authors: Stoeger Heidrun , Almulhim Norah , Ziegler Albert
Published: November 2022

The reversed gender achievement gap in the Kingdom of Saudi Arabia (KSA) in favor of girls developed in a societal environment that still predominantly favors men. The finding illustrates how equity gaps at higher systemic levels may not translate seamlessly to lower systemic levels. We propose that this lack of correspondence between systemic levels regarding equity gaps can be explained by the fact that more exogenous learning resources (educational capital) selectively reach girls’ actiotopes, enabling them to build more effective endogenous learning resources (learning capital) and, in particular, effective action repertoires. To investigate this assumption, we introduce a filter-empowerment heuristic and contrast it with a simpler correspondence heuristic. We employ the filter-empowerment heuristic and the education and learning capital approach to investigate the reversed gender achievement gap in a sample of secondary school students in the KSA. We test four hypotheses: (a) Girls have higher academic achievement than boys. (b) Girls have more educational capital and (c) more learning capital than boys. (d) Educational and learning capital mediate the relationship between gender and academic achievement. The hypotheses were tested with a sample of 2541 ninth-grade students from 55 KSA schools. The four hypotheses were confirmed and support a filter-empowerment heuristic rather than a correspondence heuristic.
A Strain Rate Dependent Damage Model for Evaluating the Dynamic Response of CFRTP Laminates with Different Stacking Sequence
Authors: Zhang Yiben , Liu Bo
Published: November 2022

Carbon fiber reinforced thermoplastic polymer (CFRTP) laminates can be used in packaging electronics components to reduce weight and shield external disturbance. The CFRTP structures in operation are inevitably to suffer dynamic loading conditions such as falling rocks, tools and impacts. In this study, a strain rate dependent material model for accurately evaluating the dynamic response of CFRTP laminates with different stacking sequence was proposed. The model was composed of three components: a strain rate dependent constitute model, a strain rate related damage initiation model and an energy-based damage evolution model. The strain rate effect of modulus and strength was described by a stacking sequence related matrix, and the damage initiation model could describe the matrix, fiber and delamination damage of CFRTP laminates without introducing cohesive elements. The material model was implemented into finite element software ABAQUS by user defines subroutine VUMAT. The low velocity impact tests of CFRTP laminates with quasi-isotropic and angle-ply stacking sequence were used to provide validation data. The dynamic response of CFRTP laminates from numerical results were highly consistent with the experimental results. The mechanical response of CFRTP laminates were affected by stacking sequence and impact energy, and the numerical error of proposed material model significantly decreased with the increasing impact energy especially for the laminae with damage occur.
A Refined Taylor-Fourier Transform with Applications to Wideband Oscillation Monitoring
Authors: Xu Qunwei , Ma Zhiquan , Li Pei , Jiang Xiaolong , Wang Chaoqun
Published: November 2022

The recent increase in renewable energy adoption has enhanced the penetration rate of electronic equipment, leading to an increased risk of wideband oscillations. Existing wide-area measurement systems mainly focus on fundamental phasors, which cannot effectively monitor wideband oscillations. This study presents an accurate wideband oscillation monitoring method based on radial basis function (RBF) neural networks and Taylor–Fourier transform (TFT). First, discrete Fourier transform is used to obtain a preliminary estimation of the oscillation signal, and then, TFT is adopted to obtain a precise estimation even under dynamic conditions. To reduce the computational burden of TFT, an RBF neural network is used for noise intensity estimation, which adaptively determines the window length. Finally, the proposed method is verified by synthetic data and the field data collected from Guyuan and Hami, China. The experimental results show that the RBF neural network has an excellent denoising effect. When the signal-to-noise ratio is 45 dB, the maximum overall phasor error and the maximum frequency error are 1% and 0.01 Hz, respectively. Hence, it is expected to be useful for next-generation monitoring systems.
Research on Steel Surface Defect Detection Based on YOLOv5 with Attention Mechanism
Authors: Shi Jianting , Yang Jian , Zhang Yingtao
Published: November 2022

Due to the irresistible factors of material properties and processing technology in the steel production, there may be different types of defects on the steel surface, such as rolling scale, patches and so on, which seriously affect the quality of steel, and thus have a negative impact on the economic efficiency of the enterprises. Different from the general target detection tasks, the defect detection tasks have small targets and extreme aspect ratio targets. The contradiction of high positioning accuracy for targets and their inconspicuous features makes the defect detection tasks difficult. Therefore, the original YOLOv5 algorithm was improved in this paper to enhance the accuracy and efficiency of detecting defects on steel surfaces. Firstly, an attention mechanism module was added in the process of transmitting the shallow feature map from the backbone structure to the neck structure, aiming at improving the algorithm attention to small targets information in the feature map and suppressing the influence of irrelevant information on the algorithm, so as to improve the detection accuracy of the algorithm for small targets. Secondly, in order to improve the algorithm effectiveness in detecting extreme aspect ratio targets, K-means algorithm was used to cluster and analyze the marked steel surface defect dataset, so that the anchor boxes can be adapted to all types of sizes, especially for extreme aspect ratio defects. The experimental results showed that the improved algorithms were better than the original YOLOv5 algorithm in terms of the average precision and the mean average precision. The mean average precision, demonstrating the largest increase among the improved YOLOv5 algorithms, was increased by 4.57% in the YOLOv5+CBAM algorithm. In particular, the YOLOv5+CBAM algorithm had a significant increase in the average precision for small targets and extreme aspect ratio targets. Therefore, the YOLOv5+CBAM algorithm could make the accurate localization and classification of steel surface defects, which can provide a reference for the automatic detection of steel defects.
A Multidimensional Adaptive Entropy Cloud-Model-Based Evaluation Method for Grid-Related Actions
Authors: Chen Xiaoling , Zhan Weiwen , Li Xingrui , Guo Jingkai , Zeng Jianyou
Published: November 2022

Smart grid training system needs to evaluate actions during power grid operations in order to complete training for relevant personnel. The commonly used action evaluation methods are difficult for evaluating fine actions during power grid operations, and the evaluation results are subjective. The use of an effective method to evaluate the actions of the power grid operation is important for improving the smart grid training system, enhancing the skills of the trainers, and ensuring the personal safety of operators. This paper proposes a cloud attention mechanism and an evaluation method of grid-related actions based on a multidimensional adaptive entropy cloud model to complete the evaluation of fine actions in the grid’s operation process. Firstly, the OpenCV technique is used to obtain the data related to hand actions during grid operation and to extract the action features to complete the construction of multiscale date sets; then, the adaptive entropy weight matrix at different scales is constructed based on multiscale data sets using the cloud attention mechanism, and the basic cloud model is generated from original hand-action feature data; finally, the multidimensional adaptive entropy cloud model is constructed by the adaptive entropy weight matrix and the basic cloud model, and the multidimensional adaptive entropy cloud model obtained is compared with the multidimensional adaptive entropy cloud model generated based on the standard action features in the same space to obtain the evaluation level of the hand action. The results show that the evaluation method of grid-related actions based on the multidimensional adaptive entropy cloud model can solve the mutual mapping problem between quantitative indicators and qualitative evaluation results in the evaluation of grid operation processes relatively well, and it effectively solves the subjectivity of the weight assignment of evaluation indicators, which can be used for the evaluation of fine actions in the grid’s operation processes.
Effect of Mixing Section Acoustics on Combustion Instability in a Swirl-Stabilized Combustor
Authors: Hwang Donghyun , Kang Cheolwoong , Ahn Kyubok
Published: November 2022

An experimental study was performed to investigate the characteristics of two different combustion instability modes in a swirl-stabilized combustor. The first is the eigenfrequency corresponding to the half-wave of the combustion chamber section, and the second is the quarter-wave eigenmode of the inlet mixing section. The purpose of this study is to understand the effects of the swirl number on each combustion instability mode and analyze their generalized characteristics. Premixed gases composed of hydrocarbon fuels (C2H4 and CH4) and air were burned by independently varying the experimental conditions. Three dynamic pressure transducers and a photomultiplier tube were installed to detect pressure oscillations and heat release fluctuations in the inlet and combustion chamber sections, respectively. A high-speed camera was used to capture the instantaneous flame structures. In the swirl-stabilized combustor, the bands of the dominant frequencies were strongly dependent on the swirl number of the swirler vane. When the swirl number was low, the entire combustion system was often coupled with the quarter-wave eigenmode of the inlet mixing section. However, as the swirl number increased, the combustion instability mode was almost independent of the mixing section acoustics. Analysis of the phase difference and flame structure clearly demonstrated the differences between each eigenmode. The results provide new insights into the effect of the resonance mode in the inlet mixing section on combustion instability, depending on the swirl number in the swirl-stabilized combustor.
Study on Stability and Control of Surrounding Rock in the Stopping Space with Fully Mechanized Top Coal Caving under Goaf
Authors: He Fulian , Liu Bingquan , Wang Deqiu , Chen Dongdong , Wu Yanhao , Song Liming , Ma Xiang , Ye Qiucheng , Jiang Zaisheng , Guo Fangfang , Wang Weiguang , Wu Yiyi
Published: November 2022

Under the condition of fully mechanized top coal caving in close-distance coal seams, the surrounding rock of the stopping space easily loses stability during the withdrawal of mining equipment in the working face because the lower coal seam working face is located under the goaf and the overburden rock has a large range of complex interaction. Field investigation, theoretical analysis, laboratory experiment, similar simulation experiment, numerical simulation, and field industrial tests are used to carry out the research on the stability and control of the surrounding rock in the large section stopping space under the goaf in this paper. The research conclusions are as follows. (1) It is determined that the lower coal seam working face can only stop mining under the goaf, and the reasonable stopping position under the goaf should ensure that the key block fracture line of the main roof is behind the support. (2) The interaction law between the main roof’s key blocks of the upper and lower coal seams is analyzed, and the catastrophic conditions for sliding instability and rotary instability of the main roof’s key blocks of the upper and lower coal seams are obtained. (3) “Anchorage with push and pull equipment-Embedded anchorages and trays” integral anchoring technology is developed. The dimensions of the push and pull equipment are determined. (4) Through numerical simulation of the distribution characteristics of the anchor cable pre-stress field, the asymmetric control scheme of “Partition long and short anchor cables + Integral polyurethane mesh + Embedded anchorages and trays for roof protection” is determined. The rock pressure observation shows that the withdrawal of the working face equipment is implemented safely.
Dandelion Optimizer-Based Combined Automatic Voltage Regulation and Load Frequency Control in a Multi-Area, Multi-Source Interconnected Power System with Nonlinearities
Authors: Ali Tayyab , Malik Suheel Abdullah , Daraz Amil , Aslam Sheraz , Alkhalifah Tamim
Published: November 2022

Frequency, voltage, and power flow between different control zones in an interconnected power system are used to determine the standard quality of power. Therefore, the voltage and frequency control in an IPS is of vital importance to maintaining real and reactive power balance under varying load conditions. In this paper, a dandelion optimizer (DO)-based proportional-integral-proportional-derivative (PI-PD) controller is investigated for a realistic multi-area, multi-source, realistic IPS with nonlinearities. The output responses of the DO-based PI-PD were compared with the hybrid approach using artificial electric field-based fuzzy PID algorithm (HAEFA), Archimedes optimization algorithm (AOA)-based PI-PD, learning performance-based behavior optimization (LPBO)-based PI-PD and modified particle swarm optimization (MPSO)-based PI-PD control schemes in a two-area network with 10% step load perturbation (SLP). The proposed strategy was also investigated in a two- and three-area IPS in the presence of different nonlinearities and SLPs. The simulation results and the comprehensive comparison between the different control schemes clearly confirm that the proposed DO-based PI-PD is very effective for realistic, multi-area multi-source IPS with nonlinearities.
Prospects and Challenges of Solar Thermal for Process Heating: A Comprehensive Review
Authors: Kumar Laveet , Ahmed Junaid , El Haj Assad Mamdouh , Hasanuzzaman M.
Published: November 2022

To mitigate the consequences of climate change, there is an increasing need to minimize the usage of fossil fuels, especially in the industrial sector because the majority of the industrial sector primarily rely on fossil fuels to meet their needs for heat energy, and a practical strategy to reduce reliance on fossil fuels is to use energy from the sun. Due to their environmental advantages, energy security, and viability as a potential substitute for fossil fuels, solar thermal collectors are acknowledged as promising technology to harness solar thermal energy fir process heating applications. This review is a thorough compendium and evaluation of contemporary literature on solar thermal collectors and their applications in industry. Apart from applications, this review paper also assesses the challenges and limitations currently hindering the global acceptance of this technology in the industrial sector.
Prospects for the Development of Hydrogen Energy: Overview of Global Trends and the Russian Market State
Authors: Vechkinzova Elena , Steblyakova Larissa P. , Roslyakova Natalia , Omarova Balnur
Published: November 2022

This review is devoted to an overview of the prospects for the development of the global hydrogen market and the strategies of individual countries aimed at transforming energy systems in favor of decarbonization and greening through the use of hydrogen. Special attention is paid to the prospects for the development of the Russian hydrogen market. The authors of the review used the method of comparative analysis and analytical generalization of publications, programs and regulatory documents from different countries. The results of the comparative analysis led to the conclusion that most of the publications currently focus on the technical and technological aspects of hydrogen energy, solving the problem of increasing the efficiency of methods for the production, transportation, distribution and storage of hydrogen fuel. The results of the analytical generalization led to the conclusion that in all countries of the world, the technology for the production of highly environmentally friendly “green” hydrogen is at an early stage, which makes it highly dependent on government initiatives to develop hydrogen projects and government funding of both scientific research in this area and realizable projects. In addition, the peaks of interest in the field of hydrogen energy are associated with market changes in the fossil energy markets, which makes the development of this technology unstable and dependent on market conditions. Moreover, the focus of attention of a number of authors is the prospects for the development of the hydrogen market. It is concluded that many countries are ready to invest in the development of hydrogen energy and, given the growth in demand for hydrogen, are ready to export it at an affordable price. That is, in the future, the international hydrogen market, as technical, technological, and economic problems are solved, will grow. The results of the study also indicate the fundamental co-direction of the trends in the development of hydrogen energy in Russia with global trends. At the same time, it should be emphasized that the high resource and scientific and technological potential allows Russia to fully focus its strategy on its implementation, not only developing the domestic market but also acting as an exporter of hydrogen and expanding international cooperation in this area.
Effect of Chitosan on the Corrosion Inhibition for Aluminium Alloy in H2SO4 Medium
Authors: Arwati I Gusti Ayu , Majlan Edy Herianto , Alva Sagir , Muhammad Wahyu
Published: November 2022

Aluminum AA5052 is an inexpensive and lightweight metal that has been used in a variety of applications, including the Bipolar Plate in Proton Exchange Membrane Fuel Cells (BPs PEMFC). The alloy has good electrical conductivity and low corrosion. Corrosion rate (CR) increases during PEMFC operation with increasing temperature. Inorganic dyes, such as chromate, are commonly used to reduce metal corrosion. Unfortunately, they are toxic and have a negative impact on the environment. Chitosan, which is a green, cheap, non-toxic, and environmentally friendly organic solvent, can be used to solve this problem. Electrophoretic Deposition (EPD) technique was used to coated the surface of AA5052 with chitosan. CR was measured using electrochemical and weight loss methods (in 0.5 M H2SO4). The best research results are as follows. The lowest CR values were obtained at the EPD time of 20 min at a chitosan concentration of 0.5% wt. The results of the study using the weight loss method indicated that after soaking for 72 h, the chitosan inhibitor can reduce the corrosion rate (CR) with an inhibitor efficiency of 87.89%, while the electrochemical method obtained a higher efficiency of 95.12%. An increase in temperature will result in a decrease in the efficiency of the inhibitor. Testing with SEM-EDX, after being coated with chitosan inhibitor, the metal surface looks smoother and the Al composition is reduced and it is detected that there is adsorption of O, N and S elements that coated the metal to form insoluble complex compounds, so the corrosion rate decreases.
A State-Observer-Based Protection Scheme for AC Microgrids with Recurrent Neural Network Assistance
Authors: Mumtaz Faisal , Khan Haseeb Hassan , Zafar Amad , Ali Muhammad Umair , Imran Kashif
Published: November 2022

The microgrids operate in tie-up (TU) mode with the main grid normally, and operate in isolation (IN) mode without the main grid during faults. In a dynamic operational regime, protecting the microgrids is highly challenging. This article proposes a new microgrid protection scheme based on a state observer (SO) aided by a recurrent neural network (RNN). Initially, the particle filter (PF) serves as a SO to estimate the measured current/voltage signals from the corresponding bus. Then, a natural log of the difference between the estimated and measured current signal is taken to estimate the per-phase particle filter deviation (PFD). If the PFD of any single phase exceeds the preset threshold limit, the proposed scheme successfully detects and classifies the faults. Finally, the RNN is implemented on the SO-estimated voltage and current signals to retrieve the non-fundamental harmonic features, which are then utilized to compute RNN-based state observation energy (SOE). The directional attributes of the RNN-based SOE are employed for the localization of faults in a microgrid. The scheme is tested using Matlab® Simulink 2022b on an International Electrotechnical Commission (IEC) microgrid test bed. The results indicate the efficacy of the proposed method in the TU and IN operation regimes on radial, loop, and meshed networks. Furthermore, the scheme can detect both high-impedance (HI) and low-impedance (LI) faults with 99.6% of accuracy.
Fluidic Thrust, Propulsion, Vector Control of Supersonic Jets by Flow Entrainment and the Coanda Effect
Authors: Shakouchi Toshihiko , Fukushima Shunsuke
Published: November 2022

Thrust, propulsion, vector control of supersonic jets has been applied to jet and rocket engines, ejectors, and other many devices. In general, there are two approaches to this type of control, namely mechanical moving systems and fluidic thrust vector control systems without moving parts, with mechanical moving systems being the most common. However, generally speaking, these systems are very complicated, and more simple methods and devices are desired. In this study, an extremely simple method for the thrust vector control of a supersonic jet by a fluidic Coanda nozzle (FC-nozzle) using the entrainment of the surrounding fluid and Coanda effect is newly proposed. The FC-nozzle consists of a pipe nozzle (Pi-nozzle), spacer, and linearly expanded Coanda nozzle (Co-nozzle) with eight suction pipes (Su-pipes) installed to surround the jet from the Pi-nozzle. The jet from the Pi-nozzle flows straight with the entrainment flow of the surrounding fluid. When some Su-pipes are closed, the pressure between the jet and Co-nozzle wall decreases, and subsequently, the jet deflects to the closed side of the Su-pipe and reattaches to the wall by the Coanda effect. The flow characteristics and deflection characteristics of the supersonic jet from the FC-nozzle are examined by the visualized flow pattern using the Schlieren method and measurements of the velocity distribution. As a result, it is shown that by changing the number of Su-pipes and the locations at which they are closed, the deflection angle and circumferential position of the jet from the Pi-nozzle can be easily controlled.
Towards a Sustainable Spatial Planning Approach for PV Site Selection in Portugal
Authors: Spyridonidou Sofia , Loukogeorgaki Eva , Vagiona Dimitra G. , Bertrand Teresa
Published: November 2022

In the present paper, we introduce a decision-support framework to (a) classify and prioritize the municipalities of a country based on their suitability to host PV energy projects and (b) pinpoint and evaluate suitable technically and economically viable, as well as environmentally and socially sustainable, sites for PV installation in the most suitable municipalities of a country. The proposed framework is applied in Portugal. It consists of two distinctive stages: ‘Energy Roadmap for PV Deployment’ and ‘PV Site-Selection Analysis and Assessment’. In the first stage, the most and least suitable municipalities for PV deployment in Portugal are identified by analyzing important environmental and technoeconomic PV siting criteria in GIS and applying the TOPSIS method. In the second stage, an integrated PV site-selection assessment is conducted in the Portuguese municipality with the highest suitability index for PV installations. This is achieved by combining a proper GIS siting model with various multicriteria decision-making methods, such as ENTROPY, AHP and TOPSIS. The results illustrate the suitability of numerous municipalities in the country for PV deployment and verify the excellent suitability of the Municipality of Mértola for PV installations. In conclusion, a PV energy roadmap for Portugal is formulated, contributing to national energy autonomy.
Optimal DG Placement in Power Systems Using a Modified Flower Pollination Algorithm
Authors: Ramshanker Abinands , Isaac Jacob Raglend , Jeyeraj Belwin Edward , Swaminathan Jose , Kuppan Ravi
Published: November 2022

There is a huge requirement for power systems to reduce power losses. Adding distributed generators (DGs) is the most common approach to achieving lower power losses. However, several challenges arise, such as determining the ideal size as well as location of the utilized distributed generators. Most of the existing methods do not consider the variety of load types, the variety and size of the utilized DGs besides reducing the convergence time and enhancing the optimization results. The paper performed an optimization algorithm that integrated a golden search-based flower pollination algorithm and fitness-distance balance (FDB) to find out the optimal size as well as the location of the distributed generators. It was then compared with different optimization methods to determine the best optimization technique, and it was determined to be the best technique. In addition, different types of DGs are considered, including solar energy, wind energy, and biogas, along with optimizing the size of the utilized DGs to reduce the system cost. Testing with different types of bus systems, and different types of DGs in a radial distribution system was done to reveal that the modified flower pollination with golden section search was superior in comparison to others with regards to convergence and power loss reduction.
Optimization of a Solar Water Pumping System in Varying Weather Conditions by a New Hybrid Method Based on Fuzzy Logic and Incremental Conductance
Authors: Hilali Abdelilah , El Ouanjli Najib , Mahfoud Said , Al-Sumaiti Ameena Saad , Mossa Mahmoud A.
Published: November 2022

The present work consists of developing a new hybrid FL-INC optimization algorithm for the solar water pumping system (SWPS) through a SEPIC converter whose objective is to improve these performances. This technique is based on the combination of the fuzzy logic of artificial intelligence and the incremental conductance (INC) technique. Indeed, the introduction of fuzzy logic to the INC algorithm allows the extraction of a maximum amount of power and an improvement in the efficiency of the SWPS. The performance of the system through the SEPIC converter is compared with those of the direct coupling to show the interest of the indirect coupling, which requires an adaptation stage driven by an optimal control algorithm. In addition, a comparative analysis between the proposed hybrid algorithm and the conventional optimization techniques, namely, P&O and INC Modified (M-INC), was carried out to confirm improvements related to the SWPS in terms of efficiency, tracking speed, power quality, tracking of the maximum power point under different weather changes, and pumped water flow.
Research on Location Estimation for Coal Tunnel Vehicle Based on Ultra-Wide Band Equipment
Authors: Yuan Xiaoming , Bi Yueqi , Hao Mingrui , Ji Qiang , Liu Zhigeng , Bao Jiusheng
Published: November 2022

Because the road surfaces of the underground roadways in coal mines are slippery, uneven, with dust and water mist, and the noise and light illumination effects are significant, global positioning system (GPS) signals cannot be received, which seriously affects the ability of the odometer, optical camera and ultrasonic camera to collect data. Therefore, the underground positioning of coal mines is a difficult issue that restricts the intellectualization of underground transportation, especially for automatic robots and automatic driving vehicles. Ultra-wide band (UWB) positioning technology has low power consumption, high performance and good positioning effects in non-visual environments. It is widely used in coal mine underground equipment positioning and information transmission. In view of the above problems, this research uses the WLR-5A mining unmanned wheeled chassis experimental platform; uses two UWB receivers to infer the position and yaw information of the vehicle in the underground roadway through the method of differential mapping; and tests the vehicle on the double shift line and quarter turn line in the GAZEBO simulation environment and on the ground simulation roadway to simulate the vehicle meeting conditions and quarter turning conditions in the underground roadway. The positioning ability of the method in these two cases is tested. The simulation and test results show that the vehicle position and attitude information deduced by two UWB receivers through the differential mapping method can basically meet the requirements of underground environments when the vehicle is traveling at low speeds.
A Review of Electricity Tariffs and Enabling Solutions for Optimal Energy Management
Authors: Zaki Dina A. , Hamdy Mohamed
Published: November 2022

Today, electricity tariffs play an essential role in the electricity retail market as they are the key factor for the decision-making of end-users. Additionally, tariffs are necessary for increasing competition in the electricity market. They have a great impact on load energy management. Moreover, tariffs are not taken as a fixed approach to expense calculations only but are influenced by many other factors, such as electricity generation, transmission, distribution costs, and governmental taxation. Thus, electricity pricing differs significantly between countries or between regions within a country. Improper tariff calculation methodologies in some areas have led to high-power losses, unnecessary investments, increased operational expenses, and environmental pollution due to the non-use of available sustainable energy resources. Due to the importance of electricity tariffs, the authors of this paper have been inspired to review all electricity tariff designs used worldwide. In this paper, 103 references from the last ten years are reviewed, showing a detailed comparison between different tariff designs and demonstrating their main advantages and drawbacks. Additionally, this paper reviews the utilized electricity tariffs in different countries, focusing on one of the most important countries in the Middle East and North Africa regions (Egypt). Finally, some recommended solutions based upon the carried-out research are discussed and applied to the case study for electricity tariff improvement in this region. This review paper can help researchers become aware of all the electricity tariff designs used in various countries, which can lead to their design improvements by using suitable software technologies. Additionally, it will increase end-users’ awareness in terms of deciding on the best electricity retail markets as well as optimizing their energy usage.
Levelized Cost of Heat of the CSPth Hybrid Central Tower Technology
Authors: Cruz-Robles Irving , Islas-Samperio Jorge M. , Estrada Claudio A.
Published: November 2022

Process heating represents about two-thirds of the energy that the industry sector consumes worldwide; this energy comes primarily from burning fossil fuels. There is a wide variety of processes for which solar technologies can supply energy. Within these technologies, the CSPth Central Tower produces heat at temperatures about 600 °C, making it suitable for high-temperature processes. A CSPth Central Tower can be combined with a fuel-based system to form a CSPth Hybrid Central Tower system, which results in a high-reliable energy source with low rates of CO2 emissions. In this work, the levelized cost of heat (LCOH) of the CSPth Hybrid Central Tower technology was calculated. SolarPILOT was used to design and evaluate the CSPth Central Tower; fuel consumption was calculated using a steady-state energy balance. The LCOH was evaluated considering the CO2 prices recommended by the High-Level Commission on Carbon Pricing. The analysis shows that this technology can be highly competitive and, in certain cases, shows lower LCOH than fuel-based systems. However, these cases depend on reasonable CO2 prices, low costs of capital (≈5%), and efforts to reduce the capital expenditure, which can nowadays be possible for CSPth Hybrid Central Tower systems designed with large solar multiples.
Radially Symmetrical Heat Hydrate Dissociation Model with a Density Difference
Authors: Wang Qian , Lian Hairong , Luo Wanjing , Teng Bailu , Fang Xinyu , Yao Gang
Published: November 2022

The hydrate dissociation is viewed as a phase change process in which hydrates transform from a solid phase into gas and liquid phase at a moving dissociation boundary. The boundary separates the dissociation zone containing gas and water from the undissociated zone containing the hydrates, leading to a density difference. Based on the assumption of a density difference between the dissociation zone and the hydrate zone, the authors propose a mathematical model to study hydrate dissociation under thermal stimulation in an infinite radially symmetrical reservoir. Analytical solutions to the temperature distribution are derived by using the self-similarity transformation. Considering the effect factors of the initial heated-water temperature and hydrate density, the authors conducted a thorough investigation of the temperature distribution and the location of the dissociation front for a sample hydrate reservoir. The results from our model show that the heated-water temperature and hydrate density exert significant influence on the hydrate dissociation. With the injection time unchanged, the dissociation distance tends to be increased as the heated-water temperature is increased, leading to a larger dissociation zone. Additionally, a smaller hydrate density can result in a larger dissociation distance. For hydrate thermal stimulation, a higher heated-water temperature and a lower hydrate density can lead to a larger dissociation distance with the injection time unchanged. As the hydrate dissociation proceeds, the dissociation rate is decreased.
Environmental Pollution by Lost Fishing Tackle: A Systematic Assessment in Lake Eixendorf
Authors: Pander Joachim , Dobler Andreas H. , Hoos Philipp , Geist Juergen
Published: November 2022

Environmental pollution by lost fishing tackle is hardly considered in freshwater management. We collected and classified lost angling tackle during the dewatering of Lake Eixendorf, Germany. Based on the results, 1 item per 100 m2 lake area was found, resulting in 5442 items, with an overall weight of more than 65 kg. This included more than 5 km of braided and monofilament fishing lines of various diameters. Lures used for active fishing methods such as stickbaits (shads and twister), metal spoons, spinners, and hard plastic baits had the greatest weight contribution (53.4%). Tackle lost from passive fishing methods (45.1%) mostly comprised groundbaiting feeder baskets and classical lead sinkers. Concerning the chemical composition, most lost items contained a composite mix of different materials. Lead was most abundant (45 kg), followed by plastics (13 kg) and steel (6 kg). Other materials such as copper, aluminum, brass (altogether 376 g), and chemicals from glow sticks (25 g) were less frequently found. Environmental pollution by lost fishing tackle deserves attention and, due to its potential environmental consequences, needs to be integrated into the pollution management of aquatic ecosystems, e.g., by identifying the most problematic items and by regulating the production and use of gear containing hazardous substances.
The Impact of COVID-19 Lockdown Strategies on Oxidative Properties of Ambient PM10 in the Metropolitan Area of Milan, Italy
Authors: Pietrogrande Maria Chiara , Colombi Cristina , Cuccia Eleonora , Dal Santo Umberto , Romanato Luisa
Published: November 2022

This research investigates the impact of controlling pandemic measures on the characteristics of atmospheric particulate matter (PM), with specific concern to its toxicity, measured by its oxidative properties. The investigated PM10 samples were collected in the metropolitan area of Milan during the epidemic lockdown, and their oxidative potential (OP) was assessed using ascorbic acid (AA) and dithiothreitol (DTT) acellular assays. During the full lockdown, we estimated reductions to 46% and 60% for nitrogen dioxide (NO2) and black carbon (BC) concentrations, respectively, based on the aggregated 2018–2019 data of NO2 and BC levels, used as baseline conditions. To quantify the impact of lockdown restrictions on PM oxidative activity, we studied the OP data measured in our laboratory on PM10 filters and directly compared the results from 15–30 April 2020 with those from the same time span in 2019. The OPAA values dropped to nearly 50%, similar to the concentration decrease in Elemental Carbon (EC) and traffic related metals, as well as to the variation in NO2 level. Otherwise, the OPDTT responses decreased to nearly 75%, as described by the corresponding reduction in Organic Carbon (OC) concentration and BC level.