bluuebunny/crossref_metadata_2025 huggingface dataset:
Root Fractures in the Primary Teeth and Their Management: A Scoping Review
Authors: Spinas Enrico , Di Giorgio Gianni , Murgia Martina Salvatorina , Garau Valentino , Pinna Mara , Zerman Nicoletta
Published: May 2022

(1) Background: Traumatic dental injuries constitute a major global health problem. Primary deciduous teeth of the upper frontal group are frequently affected by trauma, especially at an early age. It is important to treat primary traumatic injuries because early tooth loss can lead to aesthetic and functional alterations. The most common injuries are extrusion, lateral luxation, and intrusion. Root fracture is a less common complication that can lead to tooth extraction if not properly diagnosed and managed. However, there are a lack of data regarding primary root fracture treatment. The literature was reviewed to study the current knowledge on the treatment of these injuries, and to propose an operative protocol based on the results obtained. (2) Methods: A literature search was performed on Web of Science, PubMed/MEDLINE, and SCOPUS. The research focused on the following features: age of the patient; localization of the root fracture and type of displacement suffered (intrusive, extrusive, or lateral); type of emergency treatment or diagnostic test performed and their compliance with IADT guidelines; follow-up duration. (2) Results: Only 8 articles fully met the inclusion criteria, with a total of 46 patients and 62 root fractures. Out of a total of 62 root fractures, regarding only upper incisors, the most common treatment was splinting (n = 39) for a period ranging from 3 weeks to 3 months (with an average of six weeks). No treatment was performed for 23 of the root fractures. The splinting performed in most of the included cases was semi-rigid, with the splint held in place using a composite resin material. An orthodontic splint using brackets and 0.5 mm stainless steel wire was used in only in one study. (4) Conclusions: We deduced that the root fracture of primary teeth is a rare traumatic dental injury that can cause numerous complications, such as eruptive problems in the permanent teeth. Correct radiological diagnosis, immediate repositioning and semi-rigid splinting could be conservative methods to prevent premature tooth loss in very young patients.
An Information-Theoretic View of Mixed-Delay Traffic in 5G and 6G
Authors: Nikbakht Homa , Wigger Michèle , Egan Malcolm , Shamai (Shitz) Shlomo , Gorce Jean-Marie , Poor H. Vincent
Published: May 2022

Fifth generation mobile communication systems (5G) have to accommodate both Ultra-Reliable Low-Latency Communication (URLLC) and enhanced Mobile Broadband (eMBB) services. While eMBB applications support high data rates, URLLC services aim at guaranteeing low-latencies and high-reliabilities. eMBB and URLLC services are scheduled on the same frequency band, where the different latency requirements of the communications render their coexistence challenging. In this survey, we review, from an information theoretic perspective, coding schemes that simultaneously accommodate URLLC and eMBB transmissions and show that they outperform traditional scheduling approaches. Various communication scenarios are considered, including point-to-point channels, broadcast channels, interference networks, cellular models, and cloud radio access networks (C-RANs). The main focus is on the set of rate pairs that can simultaneously be achieved for URLLC and eMBB messages, which captures well the tension between the two types of communications. We also discuss finite-blocklength results where the measure of interest is the set of error probability pairs that can simultaneously be achieved in the two communication regimes.
Space-Air-Ground Integrated Mobile Crowdsensing for Partially Observable Data Collection by Multi-Scale Convolutional Graph Reinforcement Learning
Authors: Ren Yixiang , Ye Zhenhui , Song Guanghua , Jiang Xiaohong
Published: May 2022

Mobile crowdsensing (MCS) is attracting considerable attention in the past few years as a new paradigm for large-scale information sensing. Unmanned aerial vehicles (UAVs) have played a significant role in MCS tasks and served as crucial nodes in the newly-proposed space-air-ground integrated network (SAGIN). In this paper, we incorporate SAGIN into MCS task and present a Space-Air-Ground integrated Mobile CrowdSensing (SAG-MCS) problem. Based on multi-source observations from embedded sensors and satellites, an aerial UAV swarm is required to carry out energy-efficient data collection and recharging tasks. Up to date, few studies have explored such multi-task MCS problem with the cooperation of UAV swarm and satellites. To address this multi-agent problem, we propose a novel deep reinforcement learning (DRL) based method called Multi-Scale Soft Deep Recurrent Graph Network (ms-SDRGN). Our ms-SDRGN approach incorporates a multi-scale convolutional encoder to process multi-source raw observations for better feature exploitation. We also use a graph attention mechanism to model inter-UAV communications and aggregate extra neighboring information, and utilize a gated recurrent unit for long-term performance. In addition, a stochastic policy can be learned through a maximum-entropy method with an adjustable temperature parameter. Specifically, we design a heuristic reward function to encourage the agents to achieve global cooperation under partial observability. We train the model to convergence and conduct a series of case studies. Evaluation results show statistical significance and that ms-SDRGN outperforms three state-of-the-art DRL baselines in SAG-MCS. Compared with the best-performing baseline, ms-SDRGN improves 29.0% reward and 3.8% CFE score. We also investigate the scalability and robustness of ms-SDRGN towards DRL environments with diverse observation scales or demanding communication conditions.
An Empirical Analysis of Russian Regions’ Debt Sustainability
Authors: Barykin Sergey Evgenievich , Mikheev Alexey Aleksandrovich , Kiseleva Elena Grigorievna , Putikhin Yuriy Evgenievich , Alekseeva Natalia Sergeevna , Mikhaylov Alexey
Published: May 2022

This paper investigates the impact of the moderate growth of government borrowing on debt sustainability in 11 Russian regions over about 10 years, starting in 2010. The current study aims to assess the debt sustainability of the Russian region’s budget by determining Euclidean distance budget constraints and cluster analysis. This study is based on the methodology of hierarchical cluster analysis, which makes it possible to isolate regions of accumulation of objects from the aggregate data and combine them into homogeneous segments. The central hypothesis of this study is that by using this method, it is possible to increase the accuracy of the values that limit budget constraints in a region’s financial system. This study, using open data from the Federal State Statistics Service, is based on a database of statistical, financial, and economic indicators of the Russian economy. The calculations include about 45 macroeconomic indicators, which reflect the ratios of socio-economic development of the region’s financial system. The methodology described in the paper for assessing the debt sustainability of budget policy proves the need to calculate six indicators and determine the debt limits for the regions of each cluster. It finds a need to reduce the high debt burden of 46% of the regions belonging to the Northwestern Federal District. Confidence intervals for the debt limit suggest that the negative growth effect of high debt may start from levels of around 5% of the debt-to-GDP ratio and about 43% of the debt-to-revenue ratio. The results indicate that regions with a high level of debt sustainability include St. Petersburg city, the Leningrad region, and the Kaliningrad region. From a state debt policy perspective, the results provide additional arguments for debt reduction for the Republic of Komi, the Republic of Karelia, the Arkhangelsk region, and the Pskov region. The general conclusion of the study boils down to the need to reduce the debt burden of the budgets of some regions of the SFZO, as well as to the need to change the upper limits of debt, which are equally set for all regions by the Budget Code of the Russian Federation, to differentiated values of public domestic debt, taking into account the results obtained in the study.
The Power Actor and Madrasah Performance: Political Connections as a Moderating Variable
Authors: Rahmawaty  , Narsa I Made
Published: May 2022

With the background of public sector management reform in the world of education, the characteristics of the leaders have become the main thing in improving an institution’s performance theory; this study explores the influence of aspects of the heads of madrasah (their age, education, and tenure) and madrasah performance in Islamic educational institutions in East Java, Indonesia. This study shows that political relations strengthen the positive influence of the head’s age and tenure on madrasah performance. Meanwhile, political connections do not enhance the positive impact of the madrasah head’s formal educational background on madrasah performance.
N-Graphene Sheet Stacks/Cu Electrocatalyst for CO2 Reduction to Ethylene
Authors: Lesnicenoks Peteris , Knoks Ainars , Piskunov Sergei , Jekabsons Laimonis , Kleperis Janis
Published: May 2022

Renewable energy resources (wind, solar) are unpredictable, so it is wise to store the electricity they generate in an energy carrier X. Various PtX (power to useful energy-intensive raw material such as hydrogen, synthetic natural gas, fuel) applications have been proposed. At the heart of our work is widely used idea to convert residual CO2 from biogas plant into higher hydrocarbons using electricity from renewables (e.g., sun, wind, hydro). The specific goal is to produce ethylene-highly demanded hydrocarbon in plastics industry. The process itself is realised on electrocatalytic carbon/copper cathode which must be selective to reaction: 2CO2 + 12e− + 12H+→C2H4 + 4H2O. We propose a bottom-up approach to build catalyst from the smallest particles-graphene sheet stacks (GSS) coated with metallic copper nanocrystals. Composite GSS-Cu structure functions as a CO2 and proton absorber, facilitating hydrogenation and carbon–carbon coupling reactions on Cu-nanocluster/GSS for the formation of C2H4. In our design electrocatalytic electrode is made from nitrogen-doped graphene sheet stacks coated with copper nanostructures. The N-GSSitself can be drop-casted or electrophoretically incorporated onto the carbon paper and gas diffusion electrode. Electrochemical deposition method was recognized as successful and most promising to grow Cu nanocrystals on N-GSS incorporated in conducting carbon substrate. Gaseous products from CO2 electro-catalytic reformation on the cathode were investigated by mass-spectrometer but the electrode surface was analysed by SEM/EDS and XRD methods.
Transfer Learning-Based Automatic Hurricane Damage Detection Using Satellite Images
Authors: Kaur Swapandeep , Gupta Sheifali , Singh Swati , Hoang Vinh Truong , Almakdi Sultan , Alelyani Turki , Shaikh Asadullah
Published: May 2022

After the occurrence of a hurricane, assessing damage is extremely important for the emergency managers so that relief aid could be provided to afflicted people. One method of assessing the damage is to determine the damaged and the undamaged buildings post-hurricane. Normally, damage assessment is performed by conducting ground surveys, which are time-consuming and involve immense effort. In this paper, transfer learning techniques have been used for determining damaged and undamaged buildings in post-hurricane satellite images. Four different transfer learning techniques, which include VGG16, MobileNetV2, InceptionV3 and DenseNet121, have been applied to 23,000 Hurricane Harvey satellite images, which occurred in the Texas region. A comparative analysis of these models has been performed on the basis of the number of epochs and the optimizers used. The performance of the VGG16 pre-trained model was better than the other models and achieved an accuracy of 0.75, precision of 0.74, recall of 0.95 and F1-score of 0.83 when the Adam optimizer was used. When the comparison of the best performing models was performed in terms of various optimizers, VGG16 produced the best accuracy of 0.78 for the RMSprop optimizer.
Feature Extraction of Anomaly Electricity Usage Behavior in Residence Using Autoencoder
Authors: Tsai Chia-Wei , Chiang Kuei-Chun , Hsieh Hsin-Yuan , Yang Chun-Wei , Lin Jason , Chang Yao-Chung
Published: May 2022

Due to the climate crisis, energy-saving issues and carbon reduction have become the top priority for all countries. Owing to the increasing popularity of advanced metering infrastructure and smart meters, the cost of acquiring data on residential electricity consumption has substantially dropped. This change promotes the analysis of residential electricity consumption, which features both small and complicated consumption behaviors, using machine learning to become an important research topic among various energy saving and carbon reduction measures. The main subtopic of this subject is the identification of abnormal electricity consumption behaviors. At present, anomaly detection is typically realized using models based on low-level features directly collected by sensors and electricity meters. However, due to the significant number of dimensions and a large amount of redundant information in these low-level features, the training efficiency of the model is often low. To overcome this, this study adopts an autoencoder, which is a deep learning technology, to extract the high-level electricity consumption information of residential users to improve the anomaly detection performance of the model. Subsequently, this study trains one-class SVM models for anomaly detection by using the high-level features of five actual residential users to verify the benefits of high-level features.
Optical CDMA MAC Evaluation in Vehicle-to-Vehicle Visible Light Communications
Authors: Plascencia Emmanuel , Shagdar Oyunchimeg , Guan Hongyu , Barrois Olivier , Chassagne Luc
Published: May 2022

One of the most critical challenges in vehicle-to-vehicle (V2V) visible light communications (VLCs) is the access capability of multi-users over the same channel. VLC links are known to be line of sight (LOS) and highly directional compared to the commonly used radio-frequency (RF) technologies, but multi-user interference can still be problematic. Consequently, it is necessary to develop a medium access control (MAC) protocol for VLC. In the present work, we propose a novel optical code division multiple access (OCDMA) protocol. The fundamentals of the VLC channel are presented, and the interference problem is discussed in more detail. We also explain the CDMA MAC protocol and its adaptation from optical fiber communications. The simulations with our OCDMA protocol based on pseudo-noise (PN) sequence codes are presented, and the results are compared with those obtained using a solution based on VLC and optical orthogonal codes (OOCs) from the OCDMA gold standard. Finally, the results show that PN sequence OCDMA can provide sufficiently high performance and is particularly attractive because there are no synchronization requirements between nodes in real V2V scenarios.
CNTFET-Based Ternary Multiply-and-Accumulate Unit
Authors: Mohammaden Amr , Fouda Mohammed E. , Alouani Ihsen , Said Lobna A. , Radwan Ahmed G.
Published: May 2022

Multiply-Accumulate (MAC) is one of the most commonly used operations in modern computing systems due to its use in matrix multiplication, signal processing, and in new applications such as machine learning and deep neural networks. Ternary number system offers higher information processing within the same number of digits when compared to binary systems. In this paper, a MAC is proposed using a CNTFET-based ternary logic number. Specifically, we build a 5-trit multiplier and 10-trit adder as building blocks of two ternary MAC unit designs. The first is a basic MAC which has two methods to implement, serial and pipeline. The second is an improved MAC design that optimizes the number of transistors, offers higher performance and lower power consumption. The designed MAC unit can operate up to 300 MHz. Finally, a comparative study in terms of power, delay, and area variations is conducted under different supply voltages and temperature levels.
Improving the Reverberation Chamber Performance Using a Reconfigurable Source Stirring Antenna Array
Authors: Yu Chen , Zhao Yongjiu , Dai Huijuan , Qi Wenjun , Fang Feng , Xia Wenjun , Xu Qian
Published: May 2022

An antenna array composed of 16 asymmetric distributed monopoles on a circular dielectric substrate is proposed to use as a reconfigurable source stirrer in a reverberation chamber (RC). The distance between antennas is above λ2 to ensure the isolation between antennas below −15 dB. In order to ensure the mutual independence of the stirring modes of the antenna array, the 16 monopoles are asymmetrically distributed on both sides with X and Y as axes. The stirring efficiency of a stirrer is related to its size, and usually a higher stirring efficiency means a larger stirrer. The source stirring technique can achieve high efficiency, but the rotation of a source stirring antenna is limited to the radius of the turntable in an RC. To solve this problem, we propose to use an antenna array as a reconfigurable source stirrer, which can achieve a high efficiency of source stirring. As the antenna array can achieve source stirring and mechanical stirring at the same time, the source stirring section is not limited to the radius of the turntable; the switch between the selected antennas of the antenna array can increase the actual stirring samples of the stirring. Thus, the efficiency can be improved significantly and has been verified by the measurement results. The volume occupied by the conventional mechanical stirrer is reduced, which improves the working volume. The figures of merit, such as the field uniformity (FU), the independent sample numbers, the average K-factor, and the total scattering cross-section (TSCS), are measured and compared to the conventional mechanical stirring, mechanical stirring, and source stirring of the antenna array. Measurement results of the reconfigurable stir are illustrated below. FU has the best convergence and the lowest value, below 0.5 dB. The independent sample number is the largest. K-factor is the lowest, and most ranges are below −15 dB. Additionally, the proposed method has the largest TSCS, above 2 m2. These confirm that the proposed reconfigurable source stirring technique outperforms other three stirring techniques significantly. The antenna array can be easy to disassemble and install in different RC. With a wide range of working band, the proposed method can be applied to 5G OTA testing.
Unlocking the Flexibility of District Heating Pipeline Energy Storage with Reinforcement Learning
Authors: Stepanovic Ksenija , Wu Jichen , Everhardt Rob , de Weerdt Mathijs
Published: May 2022

The integration of pipeline energy storage in the control of a district heating system can lead to profit gain, for example by adjusting the electricity production of a combined heat and power (CHP) unit to the fluctuating electricity price. The uncertainty from the environment, the computational complexity of an accurate model, and the scarcity of placed sensors in a district heating system make the operational use of pipeline energy storage challenging. A vast majority of previous works determined a control strategy by a decomposition of a mixed-integer nonlinear model and significant simplifications. To mitigate consequential stability, feasibility, and computational complexity challenges, we model CHP economic dispatch as a Markov decision process. We use a reinforcement learning (RL) algorithm to estimate the system’s dynamics through interactions with the simulation environment. The RL approach is compared with a detailed nonlinear mathematical optimizer on day-ahead and real-time electricity markets and two district heating grid models. The proposed method achieves moderate profit impacted by environment stochasticity. The advantages of the RL approach are reflected in three aspects: stability, feasibility, and time scale flexibility. From this, it can be concluded that RL is a promising alternative for real-time control of complex, nonlinear industrial systems.
Research on Intelligent Comprehensive Evaluation of Coal Seam Impact Risk Based on BP Neural Network Model
Authors: Zhang Kexue , Zhu Junao , He Manchao , Jiang Yaodong , Zhu Chun , Li Dong , Kang Lei , Sun Jiandong , Chen Zhiheng , Wang Xiaoling , Yang Haijiang , Wu Yongwei , Yan Xingcheng
Published: May 2022

Coal seam impact risk assessment is the premise of coal mine safety, which can reduce the occurrence of underground impact pressure accidents and directly affect the safety, coal production, economic and social benefits of coal mining enterprises. In order to evaluate the impact risk of coal seams more reasonably and comprehensively, and consider the weights of different influencing factors on the impact risk of coal seams, the neural network model is proposed to evaluate the impact risk of coal seams. Mining depth, impact tendency, geological structure and mining technology are selected as the influencing factors of coal seam impact risk. Each influencing factor contains different evaluation indices, a total of 18. The 18 evaluation indices and the impact risk level are normalized and quantified. The BP neural network model for evaluating coal seam impact risk level is established, and the impact risk of 2-1 coal seams in a mine in Inner Mongolia is comprehensively evaluated and analyzed in this study. The results show that the BP neural network model can represent coal seam impact risk level well. The application of the BP neural network model to evaluate coal seam impact risk level has the characteristics of high precision, fast calculation speed and less artificial calculation, which provides an efficient and convenient method for the evaluation of coal seam impact risk.
Load Spectrum Compilation Method of Hybrid Electric Vehicle Reducers Based on Multi-Criteria Decision Making
Authors: Li Jie , Han Chongyang , Wu Weibin , Tang Ting , Ran Xiao , Zheng Zefeng , Sun Shunli
Published: May 2022

This article proposes a method for compiling the load spectra of reducers for hybrid electric vehicles. Selecting typical working conditions for real vehicle data collection, the load data under each typical working condition were divided into five categories according to the state of the power source and the data were preprocessed. The optimal sample loads for compiling load spectra were obtained based on a multi-criteria decision-making method, rainflow counting for optimal sample loads was performed according to different power source output patterns, non-parametric extrapolation was performed to obtain the full-life two-dimensional load spectrum after dimensionality reduction, and a full-life eight-level programmed load spectrum that could be used for bench tests was obtained. Using the programmed load spectrum and the extracted sample load as the load input, a fatigue life prediction simulation of the reducer gear of a hybrid electric vehicle was carried out. The reducer gear fatigue life from the programmed load spectrum was compared to the gear fatigue life under actual load. The fatigue life of the reducer gear when the programmed load spectrum was used as the input was 1.412 × 103. When the actual load was used as the input load, the fatigue life of the reducer gear was 1.933 × 103. The relative error between the two is only 26%, which is in the normal range. The results show that the programmed load spectrum is effective and reliable and that the load spectrum compilation method provides a basis for accurately evaluating the reliability of the hybrid electric vehicle reducer.
Modeling, Simulation and Analysis of Intermediate Fixed Piezoelectric Energy Harvester
Authors: Wang Yulong , Lv Yaran , Lv Baozhan , Zhang Ying
Published: May 2022

To address the problem that piezoelectric energy harvesters are difficult to apply in certain environments, this paper establishes the theoretical study of the intermediate fixed disc piezoelectric energy harvester (IFDPEH) based on the unimorph under concentrated force. The reliability of the model was indirectly verified by numerical simulation and Computer-Aided Engineering (CAE) simulation. The effects of load, radius ratio (piezoelectric layer/intermediate support), thickness ratio (piezoelectric layer/total thickness), and elastic modulus ratio (substrate/piezoelectric layer) on electrical energy were studied. The results indicate that the radius/thickness ratios of the IFDPEH based on aluminum and beryllium bronze are 0.05/0.31 and 0.05/0.48, respectively. In addition, through parameter comparison, it is found that the most important parameters affecting IFDPEH power are radius ratio and large load. The results are demonstrated to be meaningful for broadening the application of piezoelectric energy harvesters by the derived closed-form equations for the electrical energy along the diameters of the piezoelectric discs in the z-direction.
Numerical Simulation and Economic Evaluation of Wellbore Self-Circulation for Heat Extraction Using Cluster Horizontal Wells
Authors: Zhao Zhen , Qin Guangxiong , Chen Huijuan , Yang Linchao , Geng Songhe , Wen Ronghua , Zhang Liang
Published: May 2022

The heat extraction capacity of the self-circulation wellbore is usually small because of the limited heat exchange area. In the paper, the cluster horizontal well group technology was proposed to enhance the heat extraction capacity and decrease the unit cost. Based on the mathematical model of heat transfer, a numerical simulation model of wellbore self-circulation for heat extraction using cluster horizontal wells was established to study the influence of main factors on heat extraction capacity. The economic analysis of heat extraction and power generation was carried out according to the model of the levelized cost of energy. The results show that the enhancement of heat extraction capacity is limited after the injection rate exceeds 432 m3/d (1.59 MW/well). The inflection point of the injection rate can be determined as the design basis for injection-production parameters. When the thermal conductivity of formation increases from 2 to 3.5 W/(m·K), the heat extraction rate will increase 1.45 times, indicating that the sandstone reservoirs with good thermal conductivity can be preferred as the heat extraction site. It is recommended that the well spacing of cluster wells is larger than 50 m to avoid the phenomenon of thermal short circuit between wells, and the thermal conductivity of the tubing should be less than 0.035 W/(m·K) to reduce the heat loss of heat-carrying fluid in the tubing. Compared with a single well, a cluster horizontal well group can reduce the unit cost of heat extraction and power generation by 24.3% and 25.5%, respectively. The economy can also be improved by optimizing heat-carrying fluids and retrofitting existing wells.
IBM-LBM-DEM Study of Two-Particle Sedimentation: Drafting-Kissing-Tumbling and Effects of Particle Reynolds Number and Initial Positions of Particles
Authors: Li Xiaohui , Liu Guodong , Zhao Junnan , Yin Xiaolong , Lu Huilin
Published: May 2022

Particle sedimentation is a fundamental process encountered in various industrial applications. In this study, we used immersed boundary lattice Boltzmann method and discrete element method (IBM-LBM-DEM) to investigate two-particle sedimentation. A lattice Boltzmann method was used to simulate fluid flow, a discrete element method was used to simulate particle dynamics, and an immersed boundary method was used to handle particle–fluid interactions. Via the IBM-LBM-DEM, the particles collision process in fluid or between rigid walls can be calculated to capture the information of particles and the flow field more efficiently and accurately. The numerical method was verified by simulating settling of a single three-dimensional particle. Then, the effects of Reynolds number (Re), initial distance, and initial angle of particles on two-particle sedimentation were characterized. A specific focus was to reproduce, analyze, and define the well-known phenomenon of drafting-kissing-tumbling (DKT) interaction between two particles. Further kinematic analysis to define DKT is meaningful for two-particle sedimentation studies at different particle locations. Whether a pair of particles has experienced DKT can be viewed from time plots of the distance between the particles (for kissing), the second-order derivative of distance to time (for drafting), and angular velocities of particles (for tumbling). Simulation results show that DKT’s signatures, including attraction, (near) contact, rotation, and in the end, separation, is only completely demonstrated when particles have nearly vertically aligned initial positions. Hence, not all initial positions of particles and Reynolds numbers lead to DKT and not all particle–particle hydrodynamic interactions are DKT. Whether particle–particle interaction is attractive or repulsive depends on the relative positions of particles and Re. Collision occurs when Re is high and the initial angle is small (<20°), almost independent of the initial distance.
Multiple Power Supply Capacity Planning Research for New Power System Based on Situation Awareness
Authors: Li Dahu , Cheng Xiaoda , Ge Leijiao , Huang Wentao , He Jun , He Zhongwei
Published: May 2022

In the context of new power systems, reasonable capacity optimization of multiple power systems can not only reduce carbon emissions, but also improve system safety and stability. This paper proposes a situation awareness-based capacity optimization strategy for wind-photovoltaic-thermal power systems and establishes a bi-level model for system capacity optimization. The upper-level model considers environmental protection and economy, and carries out multi-objective optimization of the system capacity planning solution with the objectives of minimizing carbon emissions and total system cost over the whole life cycle of the system, further obtaining a set of capacity planning solutions based on the Pareto frontier. A Pareto optimal solution set decision method based on grey relativity analysis is proposed to quantitatively assess the comprehensive economic–environmental properties of the system. The capacity planning solutions obtained from the upper model are used as the input to the lower model. The lower model integrates system stability, environmental protection, and economy and further optimizes the set of capacity planning solutions obtained from the upper model with the objective of maximizing the inertia security region and the best comprehensive economic–environmental properties to obtain the optimal capacity planning scheme. The NSGA-II modified algorithm (improved NSGA-II algorithm based on dominant strength, INSGA2-DS) is used to solve the upper model, and the Cplex solver is called on to solve the lower model. Finally, the modified IEEE-39 node algorithm is used to verify that the optimized capacity planning scheme can effectively improve the system security and stability and reduce the carbon emissions and total system cost throughout the system life cycle.
Research on Operation Optimization of LNG Submerged Pump System in LNG Receiving Terminals
Authors: Wang Baoqing , Chen Kun , Huang Cheng , Zhao Jinrui , Zhang Yaotong , Li Dequan , Wang Lin
Published: May 2022

This paper focuses on improving the operating efficiency of the Liquified Natural Gas (LNG) submerged pump system in the LNG receiving terminals and achieve energy saving. The minimum input energy consumption of the LNG submerged pump system is taken as the objective function, and an optimization model for the operation of the LNG submerged pump system with variable frequency speed is established. LINGO18.0 optimization software is used to solve the model to get the optimal LNG submerged pump operation plan that satisfies the constraints. Taking a certain LNG receiving terminal as an example, the operation optimization of its LNG submerged pump system is carried out, and the input energy consumption of the system before and after optimization is compared. The results show that the use of variable frequency pumps can reduce the energy consumption of the LNG submerged pump system of LNG receiving terminals, and the optimization model can reduce the input power consumption of the system by about 10% under different transportation conditions. After applying the optimization model to actual production, it is found that the model has certain practicability for guiding the production of LNG receiving terminal.
Investigation on Performance of Various Power Control Strategies with Bifilar Coil for Induction Surface Melting Application
Authors: Sureshkumar Alagarsamy , Gunabalan Ramachandiran , Vishnuram Pradeep , Ramsamy Sridhar , Nastasi Benedetto
Published: May 2022

In recent years, induction heating applications assisted by electronic power control have been very appealing. For melting applications, induction heating is widely used as it seems to be appropriate and provides higher efficiency, zero pollutants, non-contamination of material, etc. in comparison with conventional heating. The conventional variable frequency control scheme is not sufficient for melting applications because of its high switching loss, low efficiency, and lower heat rate. A superlative control technique is required to control the output power smoothly, for a high heating rate with minimum power loss, and to lower the number of components. In this paper, a capacitorless self-resonating bifilar coil is proposed for induction surface melting applications. The performance of the system in terms of modular losses, heat rate, and efficiency is analyzed for various power methods such as pulse duty cycle control, phase shift control, pulse density modulation control, and asymmetric duty cycle control. An experimental validation is performed for the 1 kW prototype, and the heating rate, efficiency, and modular losses are calculated. The control technique is digitally validated using a PIC16F877A microcontroller with 30 kHz switching frequency. The temperature distribution is analyzed using a FLIR thermal imager. Among the tested methods, pulse density modulation-based control provides smooth and varied power control from 0% to 100% with minimum modular losses. The efficiency of the system is 89% at a rated output power and is greater than 85% for pulse density modulation control with a fast heating rate.
Transient Response Characteristics of Metal Oxide Arrester under High-Altitude Electromagnetic Pulse
Authors: Qin Feng , Chen Wei , Wang Xutong , Huang Tao , Cui Zhitong , Nie Xin
Published: May 2022

In order to study the strong electromagnetic pulse effect of critically vulnerable equipment in power systems and evaluate the survivability under high-altitude electromagnetic pulses, it is necessary to study the characteristics of the transient response of metal oxide arresters to the high-altitude electromagnetic pulse by experiment. In this paper, an experimental platform for high-altitude electromagnetic pulse conduction current injection for a typical 10 kV metal oxide arrester was set up, and the key parameters such as peak value of overshoot voltage, peak value of residual voltage, action voltage and response time were obtained by the experiment. The results show that: the action voltage of this type of metal oxide arrester is 3.53 times higher than that of its rated voltage; the peak value of overshoot voltage is 2.19 times that of the peak value of residual voltage under lightning impulse current; the peak value of residual voltage is 1.57 times that under lightning impulse; and the response time varies little with the electromagnetic pulse conduction current amplitude, averaging 46.86 nanoseconds under a high-altitude electromagnetic pulse conduction environment.
Emission Quantification via Passive Infrared Optical Gas Imaging: A Review
Authors: Kang Ruiyuan , Liatsis Panos , Kyritsis Dimitrios C.
Published: May 2022

Passive infrared optical gas imaging (IOGI) is sensitive to toxic or greenhouse gases of interest, offers non-invasive remote sensing, and provides the capability for spatially resolved measurements. It has been broadly applied to emission detection, localization, and visualization; however, emission quantification is a long-standing challenge for passive IOGI. In order to facilitate the development of quantitative IOGI, in this review, we summarize theoretical findings suggesting that a single pixel value does not provide sufficient information for quantification and then we proceed to collect, organize, and summarize effective and potential methods that can support IOGI to quantify column density, concentration, and emission rate. Along the way, we highlight the potential of the strong coupling of artificial intelligence (AI) with quantitative IOGI in all aspects, which substantially enhances the feasibility, performance, and agility of quantitative IOGI, and alleviates its heavy reliance on prior context-based knowledge. Despite progress in quantitative IOGI and the shift towards low-carbon/carbon-free fuels, which reduce the complexity of quantitative IOGI application scenarios, achieving accurate, robust, convenient, and cost-effective quantitative IOGI for engineering purposes, interdisciplinary efforts are still required to bring together the evolution of imaging equipment. Advanced AI algorithms, as well as the simultaneous development of diagnostics based on relevant physics and AI algorithms for the accurate and correct extraction of quantitative information from infrared images, have thus been introduced.
Numerical Investigation into a New Method of Non-Axisymmetric End Wall Contouring for Axial Compressors
Authors: You Fuhao , Li Xiangjun , Lu Qing , Zhang Haoguang , Chu Wuli
Published: May 2022

To deal with corner separation in high-load axial compressors, this paper proposes a new end wall contouring method aimed at controlling the end wall secondary flow in more than one local area, generating a geometry with fewer control variables that is applicable for multiple working conditions. The new method defines more than one surface unit function, with different effects on end wall secondary flow. Then, the geometry of these surface unit functions will be superposed to generate the end wall contouring, to combine their flow control effects. After applying the new method to a bi-objective optimization design process, with 15 design variables aimed at minimizing the loss of cascade at 0° and 4° incidence, the optimal design reduces the total pressure loss of the high-load cascade by 5% under the former incidence and by 3% under the latter. The most effective design rule is constructing an end wall surface with the rising suction side and sinking pressure side in the blade channel, while locally raising the SS corner with a gentle upstream slope. According to the analysis, the design variables of the new method show an intuitive influence on the variation of end wall geometry and the movement of secondary flow. The corner separation has been effectively suppressed, with fewer control variables than before. It, thus, indicates the advantage of the newly developed end wall contouring method compared with previous studies.
Model Analysis of Eco-Innovation for National Decarbonisation Transition in Integrated European Energy System
Authors: Koval Viktor , Borodina Oksana , Lomachynska Iryna , Olczak Piotr , Mumladze Anzor , Matuszewska Dominika
Published: May 2022

Consolidation with European social, economic and environmental programmes in the framework of Ukraine’s integration into the European energy space has become extremely important given the growing threats to energy security and should become the basis for greening regional and national innovation systems in the context of decarbonisation, the minimisation of carbon emissions and the transition to alternative energy sources. The comparison of the regions of the country by the level of enterprise innovation and the extrapolation of these results to the share of such enterprises in the total number of industrial entities in the regions helped identify their lack of correlation and emphasised the lack of stable dependence between industrial development and innovation activity. The methodology of the article includes a number of general scientific, special and interdisciplinary methods that allowed the screening of areas for the most favourable economic development, taking into account the synergistic component of regional development and achieving the research goal. The aim of this article is to analyse the innovative component of regional and national economic development for the implementation of decarbonisation and green energy transition in Ukraine, as well as substantiate the world’s leading imperatives and national directions for effective integration into relevant European programmes. An analysis of Ukraine’s rating status in several international indices of environmental efficiency and innovation activity in the regions showed the lack of correlation between regions of Ukraine, which actualises the search for the most effective drivers of economic development. At the same time, the consolidation of efforts of national stakeholders of innovative development in a country with relevant European institutions, particularly in the direction of greening regional economic systems, will ensure the development of innovative regions and industries, which will in turn be drivers of related territories and industries while ensuring a synergistic effect.
Assessing the Benthic Response to Climate-Driven Methane Hydrate Destabilisation: State of the Art and Future Modelling Perspectives
Authors: De La Fuente Maria , Arndt Sandra , Marín-Moreno Héctor , Minshull Tim A.
Published: May 2022

Modern observations and geological records suggest that anthropogenic ocean warming could destabilise marine methane hydrate, resulting in methane release from the seafloor to the ocean-atmosphere, and potentially triggering a positive feedback on global temperature. On the decadal to millennial timescales over which hydrate-sourced methane release is hypothesized to occur, several processes consuming methane below and above the seafloor have the potential to slow, reduce or even prevent such release. Yet, the modulating effect of these processes on seafloor methane emissions remains poorly quantified, and the full impact of benthic methane consumption on ocean carbon chemistry is still to be explored. In this review, we document the dynamic interplay between hydrate thermodynamics, benthic transport and biogeochemical reaction processes, that ultimately determines the impact of hydrate destabilisation on seafloor methane emissions and the ocean carbon cycle. Then, we provide an overview of how state-of-the-art numerical models treat such processes and examine their ability to quantify hydrate-sourced methane emissions from the seafloor, as well as their impact on benthic biogeochemical cycling. We discuss the limitations of current models in coupling the dynamic interplay between hydrate thermodynamics and the different reaction and transport processes that control the efficiency of the benthic sink, and highlight their shortcoming in assessing the full implication of methane release on ocean carbon cycling. Finally, we recommend that current Earth system models explicitly account for hydrate driven benthic-pelagic exchange fluxes to capture potential hydrate-carbon cycle-climate feed-backs.
Geometric Aspects of Assessing the Anticipated Energy Demand of a Designed Single-Family House
Authors: Koźniewski Edwin , Sadowska Beata , Banaszak Karolina
Published: May 2022

Many factors affect energy demand, and knowing their impact is very important for being able to design a low-energy building. In this group of factors, there are those that cannot be changed and improved after the building is constructed, so taking them into account when choosing a project is important for energy savings. This group includes geometric parameters. We propose a geometric method of assessing the energy demand of a single-family house. The idea is to predict the level of energy demand by calculating the values of simple geometric parameters in the first stage of design. Based on the analysis of 30 realistically designed single-family houses, we show that the geometric indicators expressed by the base area Af, and perimeter P at a fixed building wall height h, perfectly characterize the amount of energy, both usable and final. Moreover, we show linear relationships between the nominated A/V and non-nominated EWA/FA, RCcd compactness ratios. This relationship allows one indicator to be measured with another. As a result, we show how a designer can use a simple calculated index RCcd to find out the level of energy demand.
Energy Performance Curves Prediction of Centrifugal Pumps Based on Constrained PSO-SVR Model
Authors: Luo Huican , Zhou Peijian , Shu Lingfeng , Mou Jiegang , Zheng Haisheng , Jiang Chenglong , Wang Yantian
Published: May 2022

It is of great significance to predict the energy performance of centrifugal pumps for the improvement of the pump design. However, the complex internal flow always affects the performance prediction of centrifugal pumps, particularly under low-flow operating conditions. Relying on the data-fitting method, a multi-condition performance prediction method for centrifugal pumps is proposed, where the performance relationship is incorporated into the particle swarm optimization algorithm, and the prediction model is optimized by automatically meeting the performance constraints. Compared with the experimental results, the performance under multiple operating conditions is well predicted by introducing performance constraints with the mean absolute relative error (MARE) for the head, power and efficiency of 0.85%, 1.53%,1.15%, respectively. By comparing the extreme gradient boosting and support vector regression models, the support vector regression is more suitable for the prediction of performance curves. Finally, by introducing performance constraints, the proposed model demonstrates a dramatic decrease in the head, power and efficiency of MARE by 98.64%, 82.06%, and 85.33%, respectively, when compared with the BP neural network.
Riboflavin as a Biodegradable Functional Additive for Thermoplastic Polymers
Authors: Puszczykowska Natalia , Rytlewski Piotr , Macko Marek , Fiedurek Kacper , Janczak Katarzyna
Published: May 2022

With continuous development of biodegradable polymers, new areas of applications are intensively researched. Modifications of these polymers are commonly conducted by an extrusion compounding process. While additives are changing desired properties, biodegradability of such composites can be deteriorated. The aim of the work is to investigate a novel, functional, organic additive, riboflavin (vitamin B-2), in terms of thermal stability, extrusion processability, wettability, surface energy, especially biodegradability, and when compounded with PLA. Additionally, a comparison of unmodified PLA resin, as well as PLA-modified with inorganic talc—which is known for its nucleation promotion in a variety of polymers—to PLA with riboflavin, was presented. Research reveals the outstanding thermal stability of riboflavin and the sufficient extrusion process properties with no significant changes of wettability and, surprisingly, a significant degradation rate as compared to pure PLA or and PLA with talc. The obtained results do not exclude further modifications of PLA depending on the target application, e.g., antimicrobial agents, flame retardants, etc.