bluuebunny/crossref_metadata_2025 huggingface dataset:
Method of static stability dominant identification
Authors: Hu Zhen , Cui Ting , Dai Yuanhang , Chen Daojun , Yang Dan , Li Yating
Published: June 2023

Two extreme cases of static stability are voltage stability and power angle stability. The general stability analysis only focuses on one of the voltage stability or power angle stability. The stability limit and state change are studied for a certain kind of stability characteristics. In this paper, the stability limits of static voltage and power angle are derived, respectively. Therefore, different stability characteristics and their interrelationships can be further studied. The index to judge the dominant stability characteristic is defined. The proposed index only needs the system wide‐area measurement information to quickly and accurately judge the dominant static stability characteristics. The dominant instability (DI) characteristic index proposed in this paper is equal to 1 or −1, which can help to quickly identify whether the power angle stability or voltage stability is dominant. The effectiveness of the method is proved by a simple system.
An enhanced hunter‐prey optimization for optimal power flow with FACTS devices and wind power integration
Authors: Hassan Mohamed H. , Daqaq Fatima , Kamel Salah , Hussien Abdelazim G. , Zawbaa Hossam M.
Published: June 2023

This paper proposes an improved version of the Hunter‐prey optimization (HPO) method to enhance its search capabilities for solving the Optimal Power Flow (OPF) problem, which includes FACTS devices and wind power energy integration. The new algorithm is inspired by the behavior of predator and prey animals, such as lions, wolves, leopards, stags, and gazelles. The primary contribution of this study is to address the tendency of the original HPO approach to get trapped in local optima, by proposing an enhanced Hunter‐prey optimization (EHPO) approach that improves both the exploration and exploitation phases. This is achieved through a random mutation for exploration and an adaptive process for exploitation, which balances the transition between the two phases. The performance of the EHPO algorithm is compared with other optimization algorithms, and subsequently, it is used to solve the OPF problem incorporating FACTS devices and wind power. The results demonstrate the effectiveness and superiority of the proposed algorithm. In conclusion, this study successfully enhances the EHPO algorithm to provide better accuracy and faster convergence in finding optimal solutions for complex real‐world problems.
A non‐isolated step‐up common‐ground cost‐effective microinverter for AC‐module application
Authors: Varnamkhasti Moheb Mahmoudi , Niroomand Mehdi , Adib Ehsan
Published: June 2023

This research proposes a cost‐efficient microinverter. The proposed microinverter can eliminate the leakage current using common‐ground configuration. It uses three switches and only one of them operates at high frequency. In addition, a passive lossless snubber is applied to limit voltage stress and provide soft‐switching performance for the high‐frequency switch. A pair of coupled inductors is used to provide higher voltage gain which makes it possible to keep the operating duty cycle in the normal range and makes the proposed inverter suitable for AC module application. The input current of the proposed microinverter is continuous which reduces the loss of the input capacitor by high‐frequency current component reduction. The operating principle of the proposed inverter is described in both positive and negative current modes. In positive current mode, the proposed microinverter works similar to SEPIC converter and in negative current mode its performance is similar to CUK converter. The dynamic behavior of the proposed microinverter is analyzed through simulation and a simple PI controller is designed to accommodate the worst case. Theoretical loss analysis is applied and finally the results of this research are compared with other researches. The performance of the proposed inverter is justified by simulation and practical results of a 300‐watts prototype.
Real‐time monitoring of transformer hot‐spot temperature based on nameplate data
Authors: Rezaeealam Behrooz , Askary Saeid
Published: June 2023

This paper proposes a real‐time hot‐spot monitoring method for three‐phase two‐winding oil‐filled transformers under steady‐state conditions, where the corresponding test certificates are not accessible to the customers. For this purpose, the separate determination of iron‐core and copper losses is achieved by real‐time measuring of voltages and currents in both primary and secondary sides and also employing nameplate data of the transformer, including the winding resistances. Subsequent calculations based on IEEE Std C57.110‐2018 provide the top‐oil and hot‐spot temperatures. It is shown that the estimated top‐oil and winding hot‐spot temperatures and also load and no‐load losses match with the measured ones with the maximum difference of 3.5%, 2%, 2.7%, and 9%, respectively.
Intelligent train stopping control for railways: A deep learning approach
Authors: Chen Xing , Yin Jiateng , Ning Chenhe
Published: June 2023

Station parking accuracy is an important indicator for the automatic control of high‐speed trains; however, it is subject to many influencing factors, such as the characteristics of high nonlinearity and large time delays in the train control model, time‐variant humidity, and uncertain weather conditions, leading to unsatisfying performance with existing feedback control algorithms. This study first proposes an intelligent train stopping control approach based on deep learning for high‐speed railways. By collecting a large amount of historical train operation data from the Beijing–Shenyang high‐speed railway, three data‐driven models are developed for train stopping control. The first model is based on a deep‐layered feedforward neural network (DNN), which predicts the exact train stopping position with dynamic train running states (position, velocity etc.) as input. Taking advantage of the physical train control models used in practice, the DNN to a convolutional neural network (CNN) is then improved by customizing the convolutional layers of the CNN. To overcome the issues arising from the incompleteness of data samples, a few‐shot convolutional neural network (FSCNN) is further developed to enhance the prediction performance of the CNN. Compared with that of the current method used in practice, the simulation experiments show that the train station parking error can be decreased by 38.6%, 42.8%, and 49.2% by our developed DNN, CNN, and FSCNN, respectively.
Optimal scheduling of the energy storage system in a hybrid micro‐grid considering uncertainties, using the stochastic quasi‐gradient method
Authors: Ghazipour Shirvan Masoud , Hosseini Abardeh Mohamad , Hojjat Mehrdad
Published: June 2023

Energy storage and renewable sources play a unique role in the future advances of smart grids. In this article, the optimal scheduling of the energy storage system in a hybrid microgrid is presented considering the uncertainties of the renewable generations and the load. The optimisation problem in this article is non‐linear and non‐convex, therefore conventional optimisation methods such as linear programming (LP) are unable to solve this problem. On the other hand, because of parameters uncertainty, special considerations are required to simulate these parameters. In this regard, a new optimisation algorithm that can solve the non‐linearity and non‐convexity of the objective function is proposed based on the Stochastic Quasi‐Gradient optimisation Method (SQGM). Moreover, the uncertainties of the wind, PV generation, and the load are modelled. Different optimisation algorithms: the conventional Stochastic Dynamic Programming (SDP), the Stochastic Dual Dynamic Programming (SDDP) and the proposed SQGM are compared. A 9‐bus benchmark system with distributed generation units is used to evaluate the optimisation strategies.
Situation, Challenges and Suggestions for the Integrated Development of Transportation and Energy
Authors: Cui Peiqiang , Gong Weiwei , Yu Qi , Mao Ning , Liu Jie , Xu Donghui
Published: June 2023

Promoting integrated development of transportation and energy is of great significance for achieving carbon peaking and carbon neutrality goals, deepening the nationwide battle to prevent and control pollution and accelerating the building of China’s strength in transportation. In the future, with the continuous growth of traffic demand, the acceleration and improvement of the comprehensive national transportation network and the continuous expansion of new infrastructure construction in the transport sector, the energy demand of transportation will continue to increase. At present, the institutions and mechanisms for the integrated development of transportation and energy are imperfect, supporting policies are not yet sound, and some key technologies are in urgent need of breakthrough. To further promote the integrated development of transportation and energy, we need to further clarify the strategy and pathway, optimize development policies and mechanisms, explore feasible business models, and strengthen scientific and technological innovation in this field.
Problems and Significance of Marine Environment Monitoring
Authors: Long Ruilian
Published: June 2023

At this stage, compared with developed countries, China's Water environment monitoring technology is still in a relatively backward development trend. The improvement of Water environment monitoring technology requires a long process of accumulating experience. The construction of marine ecological civilization as a new cognitive concept has been raised to a national strategy, in which marine environmental monitoring is an important technical means to cognize the current situation of marine environment and guarantee the construction of marine ecological civilization, but compared with developed countries, certain monitoring technologies in China are still immature and some monitoring systems have not been perfected. Therefore, how to improve the quality of marine environmental monitoring, integrate marine monitoring team and build a three-dimensional marine monitoring system has become an important prerequisite for the implementation of ecological civilization construction.
Research on Surface Water Quality Prediction based on a CNN-BiLSTM-Attention Combined Deep Learning Approach
Authors: Li Ling , Gu Zhongxuan , Lu Dongjing
Published: June 2023

The ability to predict the environmental conditions of surface water is crucial for prompting the refined management of surface water pollution in China. This paper carried out research on the prediction method of surface water quality based on deep learning algorithms and combined with the real-time data of national automatic monitoring of surface water quality. Under the encoder-decoder framework, the research proposed a CNN-BiLSTM-Attention water quality prediction model which contains CNN, bidirectional LSTM, and attention mechanism. To evaluate the performance of the proposed hybrid model, the research also compared the model with LSTM and CNN-LSTM models, carrying out a comparative analysis of the prediction results of each model through three performance metrics. The research results showed that compared with other models, the CNN-BiLSTM-Attention water quality prediction model can effectively take advantages of each neural network layer and has better prediction ability and higher stability for forecasting future water quality, which can provide strong technical support for water environment management and early warning.
Ultrasonic pretreatment for Enhancing Sludge disintegration and Resource Utilization: A mini review
Authors: Guan Ziliang , Tian Qing
Published: June 2023

As a byproduct of sewage treatment plants, sludge presents dual characteristics of “resource” and “pollution”. While it enriches nutrients from wastewater, it also contains a portion of toxic substances. Moreover, when the organic matter content of sludge is low, it affects the efficiency of resource utilization and energy recovery (sludge digestion efficiency, energy consumption of incineration systems). Developing new physicochemical-biological combined pretreatment to enhance the dissolution of organic matter in sludge (sludge disintegration) and reduce the solid content of sludge is a crucial step to improve sludge dewaterability and digestibility. Ultrasonic, as a novel sludge pretreatment technology, gains the advantages of being environmentally sustainable, efficient, and easily operable. It can disrupt sludge flocs, alter microbial activity, release intracellular organic matter, and be used in combination with other pretreatment processes. This article summarizes the mechanism of ultrasonic pretreatment of sludge and its research progress in improving sludge dewaterability and digestibility, providing a new perspective for the application of ultrasound in sludge resource utilization.
Analysis of the Influence of Sponge Bus Bay Stop on Stormwater Runoff
Authors: Sun Baoyun , Ma Lin , Yang Yaping , Dong Lei
Published: June 2023

The traditional bus bay stops are prone to ponding, with reduced waiting comfort, low traffic efficiency and easily damaged pavement structure. Given the problem, based on the sponge design of the bay stop in northern China, the rainstorm flood management model under the traditional and sponge modes is constructed, and the runoff condition of the bus stop is analyzed. The results show that the combination design of LID facilities, such as permeable pavement and the recessed green belt has a good control effect on rainwater runoff in the stop section. The larger the range of LID measures adopted in the stop section, the more pronounced the runoff control effect. The combined design of sponge facilities can effectively control rainwater runoff. However, with the increase in rainfall intensity, the control effect of sponge measures on rainwater runoff at the bus stop gradually decreases.
Effect of Distiller's Grains Biochar Combined with Lactobacillus plantarum on Remediation of Lead, Cadmium and Zinc Complex contaminated Soil
Authors: Zhu Guangxu , Cheng Dandan , Du Ronghui , Liu Yikai , He Youya
Published: June 2023

Aiming to clarify the effect of Lactobacillus plantarum combined with distiller's grains biochar on lead, cadmium and zinc complex contaminated soil, a pot experiment was conducted to investigate soil effective heavy metal concentration, plant growth, and heavy metal accumulation in the Sorghum hybrid sudangrass. The results revealed that single application of distiller's grains biochar, Lactobacillus plantarum thallus, Lactobacillus plantarum supernatant, and combined application of distiller's grain biochar and Lactobacillus plantarum thallus could significantly reduce the content of available Cd, Pb, and Zn in soil (P<0.05), and reduced the aboved metals content in the aerial parts and roots of Sorghum hybrid sudangrass to varying degrees. Compared with control group, high dosage of distiller's grain biochar and Lactobacillus plantarum thallus combined application treated Sorghum hybrid sudangrass with the lowest heavy metals content. The concentrations of Cd, Pb, and Zn decreased by 40.93%, 31.84%, and 40.25% in the aerial part, respectively, and decreased by 41.09%, 21.79%, and 29.62% in the root, respectively. The high dosage of distiller's grains biochar and the combination application of distiller's grains biochar and Lactobacillus plantarum thallus significantly increased the plant height and biomass of Sorghum hybrid sudangrass (P<0.05), and the overall promotion effect was better than other treatments.
Distribution characteristics of polycyclic aromatic hydrocarbons in Chinese flowering cabbage in different periods
Authors: He Gangjian , Sun Qiaojian , Long Minghua
Published: June 2023

The purpose of this study is to investigate the distribution characteristics of polycyclic aromatic hydrocarbons (PAHs) in Chinese flowering cabbage at different growth stages, and provide reference for people's daily diet and production activities. The growth stages of Chinese flowering cabbage were divided into three periods: seedling stage (from the growth of the first true leaf to the expansion of the fifth true leaf), leaf growth stage (from the growth of the sixth true leaf to the appearance of the plant buds), and stem formation stage (from the appearance of the plant buds to the harvest of the stem). The contents of PAHs in roots, stems, and leaves of Chinese flowering cabbage at each stage were detected by high-performance liquid chromatography, and their change patterns were studied.
Marine ecological impact analysis of residual chlorine emission from LNG transfer station
Authors: xin Li , Youping Shou , Lihong Qian
Published: June 2023

During the operation of LNG terminals, sodium hypochlorite was used to prevent Marine organisms from attaching to the equipment, resulting in aquatic life problems caused by residual chlorine discharge. The free residual chlorine in seawater is more toxic to aquatic organisms, and the maximum inhibitory effect on Chlorella growth is shown when the concentration of residual chlorine is 0.20mg/ L. Meanwhile, Chlorella growth is greatly affected by residual chlorine, and the recovery time is longer. The concentrations of zooplankton affected by continuous exposure to chlorine were lower than those affected by intermittent exposure. The effect of residual chlorine on shellfish is relatively small. When the residual chlorine concentration is lower than 1mg/L, shellfish can still open their shells to feed, but the feeding speed decreases.
Research on water quality prediction based on PE-CNN-GRU hybrid model
Authors: Zhang Langlang , Xie Jun , Liu Xinxiu , Zhang Wenbo , Geng Pan
Published: June 2023

Sewage treatment is a complex and nonlinear process. In this paper, a prediction method based on convolutional neural network (CNN) and gated recurrent unit (GRU) hybrid neural network is proposed for the prediction of dissolved oxygen concentration in sewage treatment. Firstly, akima 's method is used to complete the filling preprocessing of missing data, and then the integrated empirical mode decomposition (EEMD) algorithm is used to denoise the key factors of water quality data. Pearson correlation analysis is used to select better water quality parameters as the input of the model. Then, CNN is used to convolve the data sequence to extract the feature components of sewage data. Then, the CNN-GRU hybrid network is used to extract the feature components for sequence prediction, and then the predicted output value is obtained. The mean absolute error (MAE), root mean square error (RMSE) and mean square error (MSE) were used as evaluation criteria to analyze the prediction results of the model. By comparing with RNN model, LSTM model, GRU model and CNN-LSTM model, the results show that the PCA-EEMD-CNN-GRU (PE-CNN-GRU) hybrid model proposed in this paper has significantly improved the prediction accuracy of dissolved oxygen concentration.
Effect of biochar on soil acidity and aluminum morphology in tea plantations
Authors: Qian Lian-Wen , Hu Rui-Xue , Liang Xu-Jun , Wang Yi-Xiang
Published: June 2023

Soil acidification in tea plantations has become a key factor restricting the development of the tea industry. Biochar reduces soil acidity significantly and has good short-term effects of acidic soil improvement in tea plantation trials, but the duration of the effect and the long-term environmental effects of biochar are still unclear. In this study, the acidic tea plantation soil to which biochar was applied five years ago was studied. The biochar applied to the soil was separated and analyzed for surface elements, and the aluminum form of the soil was measured. The results showed that : (1) Five years after biochar was applied to the soil, the surface aluminum elements of biochar increased significantly, indicating that biochar had a certain degree of adsorption effect on aluminum in the soil; (2) the pH of tea plantation soil increased significantly; (3) the exchangeable aluminum [Al3+] and monohydroxy and dihydroxy aluminum [Al(OH)2+, Al(OH)2+] both had the potential to convert to colloidal aluminum [Al(OH)3], and this conversion reduced the content of reactive aluminum in the soil, thus increasing the soil pH and reducing the toxicity of aluminum to plants.
Ecological Risk Assessment of Heavy Metals in Sediment from Beijing-Hangzhou Grand Canal
Authors: Wu Lijun , Li Xiangru , Luo Xin , Xie Jiye
Published: June 2023

Sediments contaminated by heavy metals (HMS) pose detrimental effects on both the public health and ecosystem. In our study, sediment samples were collected from Hangzhou Section of Beijing-Hangzhou Grand Canal. Based on heavy metals concentrations measured, the pollution status assessments were conducted adopting three methods namely the Nemerow index (PN), single factor index (Pi) and potential ecological risk index(RI). The order of concentration of heavy metals investigated is as follows: Zn>Cd>Cu≈As≈Pb≈Ni≈Cr. T2 and T7 sites had high level pollution based on PN characterized by Zn and Cd accumulation. Based on the findings of the RI assessment, site T2 reached a higher risk level toward the human and ecological environment in which Cd was the chief contributor.
Spatiotemporal dynamic interpolation simulation and prediction method of fine particulate matter based on multi-source pollution model
Authors: Ma Yinchi
Published: June 2023

Taking the air pollution monitoring data of 34 air monitoring stations in Beijing from February 8 to February 9, 2020, as an example. A spatiotemporal dynamic interpolation model of PM2.5 based on a multi-source pollution model was established. Based on the hourly spatiotemporal data of the day, the dispersion and attenuation of non-point source pollution in Beijing were interpolated. An improved hybrid genetic algorithm was used to solve the parameters of the air pollution model. The spatiotemporal Kriging model was used to predict the PM2.5 concentration diffusion on an hourly scale. The data of this area were analyzed quantitatively and qualitatively. The prediction data based on the spatiotemporal data before the current time was verified by the actual monitoring data. The results show that the model and method constructed in this paper could simulate and predict PM2.5 concentration on an hourly scale well, which could provide a good reference for the analysis, simulation, and prediction of air pollution.
Research on carbon emission factors of heavy chemical industry park based on generalized Divisia index method
Authors: Guoliang Cao , Chen Ning , Runxin Li , Yongliang Huang
Published: June 2023

Based on the energy consumption and economic data of a heavy chemical industrial park in northwest China from 2013 to 2020, the carbon emissions of the park were calculated. The generalized Divisia index method (GDIM) was employed to analyze the effects of eight absolute and ten relative indicators of carbon emission changes in the heavy chemical industrial park. The results show that optimizing the electricity structure, reducing the energy output and carbon output intensities, and improving investment efficiency have a significant effect on inhibiting carbon emission. The inhibitory effect from reducing investment carbon intensity, fossil energy, and the total energy consumption scale was clearly evident. The deterioration of fossil fuel energy structure, and the increase in investment, output, and total electricity consumption scales are the main factors affecting carbon emission growth. Carbon emissions from industrial processes have a limited impact on carbon emissions. Finally, pertinent suggestions are provided.
Evaluation Model of Location Light Pollution Level based on Analytic Hierarchy Process and Entropy Weight Method
Authors: Zhang Yuyang , Cheng Long
Published: June 2023

With the development of society, the impact of light pollution has gradually intensified. It not only endangers human health and animal and plant activities but also indirectly damages the climate and environment. In the past, the research on the evaluation of urban light pollution often focused on the comparison between the light pollution level measured by the relevant photometry equipment and the natural light level. This means that many sites need to be selected for measurement in the evaluation city. To save resources and ensure the evaluation results have a certain validity, we built a Location Light Pollution Risk Index (LLPRI) model. First, we selected 16 indicators from 6 aspects and built a three-level indicator evaluation system. After that, based on combining the Analytic Hierarchy Process (AHP) and Entropy Weight Method (EWM) to calculate the index weight, we also use the Weight Combination Method to obtain the final weight of the index. Finally, we will bring the collected site sample data into the model and then use K-means Algorithm to cluster the model results and obtain the model metric We compare the results of the assessment of location light pollution risk level by the model with the data from the Military Meteorological Satellite Program (DMSP) and Visible Infrared Imaging Radiometer (VIIRS). The experimental results show that the LLRPI model has good effectiveness.
Study on the Relationship between Economic Growth and Air Pollution in the Pearl River Delta Region
Authors: Chen Jiaqi , Lan Zhoulin
Published: June 2023

To solve the problem of balancing the relationship between economic growth and air quality in the pearl river delta (PRD) region, based on selecting the indicators characterizing the environmental quality of the PRD region (i.e., the concentrations of four pollutants such as O3, SO2, NO2, and PM10) and the GDP of its three major industries during 2006-2021, this paper established a multiple linear regression model of the relationship between economic growth and air pollution in the PRD region, using E-Views and SPSS software. The results show that: the growth of the GDP in primary and tertiary industries in the PRD region will lead to the reduction of the concentration of air pollution; the growth of the GDP in secondary industries will lead to an increase in the concentration of air pollution. The suggestions based on the results are as follow: shifting the focus of industrial development, paying attention to the prospect of tertiary industry development, and continuously promoting the prevention and treatment of air pollution.
Characteristics of Gas Seepage and Pore Structure Response in CO2-ECBM Process of Low Permeability Coal Seam
Authors: Liu Junlin , Zhang Kun , Liu Huihu
Published: June 2023

CO2-ECBM is a method of enhanced coalbed methane extraction followed by cutting greenhouse gas emissions and new energy development. In order to reveal the characteristics of gas flow in porous media and the pore structure response characteristics of coal rocks, the experiments were carried out to simulate the process of CO2 displacement of N2 at a buried depth of 900 m, including monitoring the changes in gas permeability and strain of coal samples along with a comparison of the pore structure of low-temperature liquid nitrogen adsorption on coal samples both before and after displacement were both done. The findings of the experiment are listed below. The N2 permeability of the LiuZhuang sample ranges from 0.0008mD to 0.0014mD, whereas the permeability of QiDong is around 0.0003mD. With an increase in gas injection duration and an expansion of the coal matrix for N2 adsorption, the permeability steadily decreases. The efficient stress compression of the coal pore fracture structure during sample preparation and testing avoids the visible fracture region, which results in poor permeability. The displacement stages of CO2 can be divided into three phases. Free nitrogen flows from the end of the position and the permeability diminishes during the phase of free nitrogen. When CO2 is introduced into the penetration stage, the permeability tends to rise, however when there is no penetration, the permeability test values are frequently low. During the CO2 steady displacement phase, gas permeability gradually declines. Axial and radial strains are progressively raised during the initial stage of the CO2 injection whereas they are gradually reduced during the initial stage of the N2 injection. While CO2 is continuously supplied through the coal body stage, there are modest axial and radial strain changes. The axial and radial stresses are stabilized by the CO2 displacement. The overall pore volume of the coal significantly rises following the displacement. The increase part of the pore volume is primarily focused on the pore of absorption and filling (aperture < 10nm), whereas the decreased part is mainly concentrated in the diffusion pore of the Fick type and the permeability part (aperture > 50nm). The increased in pore volume ratio surface area is centered mostly in the fill pore region (aperture 10 nm) and is four times greater than it was before the displacement. The CO2 injection exerts an expansion impact on the adsorptionfilled and diffusion pores during the CO2-ECBM process, whereas the compression effect on the percolation pores results in a reduction in permeability.
Study on Well Pattern System Optimization of Fuyang Reservoir in H Oilfield
Authors: Zeng Jing
Published: June 2023

The selection of well pattern system is not only the key content in the process of oilfield development, but also the core problem in the design of oilfield development. It is also the basis for the effective utilization of tight reservoir technology. Through scientific analysis of the geological structure and dynamic characteristics of Yang reservoir in H oilfield, the well pattern system can be reasonably optimized and the development of Chinese oilfield can be vigorous. Starting from the selection of well pattern system for oil and gas field development, this paper analyzes the optimization of well pattern system parameters of Fuyang reservoir in H oilfield.
Adaptability Analysis of Three or Four Strips with Small Well Spacing in Zone A Transition Zone
Authors: Liu Xiaojuan
Published: June 2023

Small well spacing tests were carried out in three and four zones of the transitional zone to solve the problems of poor effect of water flooding and low reserves utilization. In order to improve the effect of water drive development in the transitional zone of Area A, the two test zones in area a have been reopened and utilized, well pattern is changed from anti-nine-point method to five-point method. Through strengthening the tracking adjustment of oil and water wells, the variation law of production and water cut in the test well area with small well spacing in the development process is understood, and the adaptability of different well patterns and well spacing in three or four zones is verified, it provides a technical reference for the adaptability of water injection in three or four zones of the transition zone.
A Review on Spatio-temporal Pattern Evolution of Shrub Fire Caused by Human Disturbance in Yunnan Province
Authors: Liu Yu , Gao Zhongliang , WangHe Chenyang , Yu Wentian , Cao Yufei
Published: June 2023

Artificial fire is the main cause of forest fires, and human intervention can reduce the occurrence of forest fires. Yunnan province is a province with a high incidence of forest fires. A large number of flammable shrubbery are distributed in many regions. The study on the time scale and space scale of shrubbery fires caused by human disturbance is conducive to the study on the evolution of the space-time pattern of shrubbery fires and the reduction of forest fires. Based on Yunnan province from 1990 to 2018 shrubbery fire data, combined with ArcGIS geographic information system, BP neural network analysis of the impact of human interference on Yunnan shrubbery fire and shrubbery fire time and space changes. The research results can provide some theoretical support for forest fire management departments.
Information model of power distribution IoT terminal for high-rise building electrical fire monitoring
Authors: Peng Tianhai , Yang Fan , Su Lei , Sun Lingyan , Chen Yu
Published: June 2023

Fires caused by electrical reasons such as short circuits and leakage in low-voltage distribution network lines account for a relatively large proportion of the high-rise building fires. Building an electrical fire monitoring system for high-rise buildings based on the Internet of Things (IoTs) technology can monitor electrical circuits in real-time and reduce electrical fires. Aiming at the interconnection and intercommunication of the information exchange of the IoT terminals in the electrical fire monitoring system of high-rise buildings, this paper firstly analyzes the functional communication requirements of the electrical fire monitoring system of high-rise buildings, and combined with the requirements of functional communication, the information model required for electrical quantity collection and non-electricity collection functions is studied based on IEC 61850, which is conducive to the fusion and application of low-voltage distribution network monitoring data and existing distribution automation system data. At the same time, the location information logical node is established by supplementing, which realizes the determination of the spatial position of the terminal and the sensor, the location of the fire source can be determined by analyzing and calculating according to the spatial location information and the spatiotemporal sequence of the detection information. Finally, the information modeling of different types of monitoring terminal equipment is carried out and the configuration suggestion based on SCL language is proposed. By realizing the integration of low-voltage terminal unit (LTU) into the system and the configuration of LTU, the standard system of IEC 61850 can be actually operated. A monitoring terminal based on the proposed information model has been developed and applied to a building in Wuhan.
Adaptive fault-tolerant control for electro-hydraulic servo actuator based on multiple unmodeled dynamics estimation and compensation
Authors: LI Ting , YAO Yeming , ZHANG Linhai , LI Yang , WANG Xinmin
Published: June 2023

The internal leakage fault-tolerant control problem of the electro-hydraulic servo actuator under the influence of multiple unmodeled dynamics is investigated in this paper, and an adaptive fault-tolerant control scheme based on unmodeled dynamics estimation and compensation is proposed. The model of the actuator is divided into two subsystems, which extended-state observers are respectively constructed to estimate the matched and mismatched unmodeled dynamics. Combined with the estimation results of the unmodeled dynamics, an adaptive fault-tolerant controller is designed by using the backstepping method. In which a controller reconfiguration mechanism based on internal leakage fault parameter online adaptation is used to accommodate the fault, and a feedforward compensation strategy is used to suppress the influence of unmodeled dynamics. Semi-physical simulation test of the proposed scheme is conducted under serious cylinder internal leakage. The test result shows that when the maximum internal leakage flow reaches 10.53 L/min, accounting for about 56.77% of the load flow, at the moment the opening of the servovalve is close to the maximum and the proposed scheme can still achieve high-precision position tracking control, where the maximum position tracking errors of fault transient and post-fault steady state are both limited within ±1.5% of the given position.
Influence of geometric parameters of leading edge horn-ice on stall characteristics of airfoil
Authors: ZHAO Binbin , LI Xianping , LI Jie , ZHANG Heng
Published: June 2023

The irregular characteristics and geometric randomness of horn-type ice are significant while the behaviors of separation are complex. The mechanism and factor leading to the essential change of stall performance are still not clear. According to actual requirements of airworthiness certification of a large passenger aircraft, a family of horn-type ice shapes with different parameters are constructed based on typical supercritical airfoil and icing environment. By combining with wind tunnel test and numerical simulation methods, the parameter sensitivity of airfoil stall characteristics to the change of ice height and angle is systematically analyzed and the essential influence mechanism of the ice shape parameters leading to the change of separation bubble development under stall process is summarized, which provides a theoretical basis for ice airworthiness certification of large passenger aircraft.
The viscoplastic constitutive model of TC4 alloy under high temperature
Authors: HE Yuxin , MA Yu'e
Published: June 2023

TC4 alloy is widely used in the high temperature environment. This paper proposed an ununified viscoplastic constitutive model according to the uniaxial creep experiment and high temperature tensile experiment of TC4 alloy. The inelastic strain rate was decomposed into two parts: creep strain rate and plastic strain rate. The creep strain was calculated by multiaxial ductility exhaustion creep damage law, and the plastic strain was get from the yield function containing the damage and the kinematic hardening effect. The implicit stress integration algorithm and the consistent tangent modulus of this model were derived. The material constants of the proposed model were determined by using genetic algorithm. The proposed constitutive model was compiled in a UMAT subroutine of finite element software Abaqus and 3D eight nodes isoparametric brick element was employed to simulate the creep and the tensile behavior of TC4 alloy. Form the result, the proposed constitutive model can predict the three stages of creep curves and the softening stage of tensile curves accurately.
Central node selection algorithm of minimizing maximum weighted response time based on dynamic programming
Authors: WAN Bailin , YANG Qi , YAN Zhongjiang , YANG Mao , LI Bo
Published: June 2023

In order to minimize the maximum weighted response time for any node in the network to reach the central control node, a central control node election algorithm based on dynamic programming is proposed. Firstly, the response times of nodes and links in the wireless network are modeled as the node weights and edge weights in the network topology, and then the central control node election problem that minimizes the maximum weighted response time for any node in the network to reach the central control node is modeled as the central problem, where represents the number of central control nodes. Then, by using the interpolation method based on dynamic programming, the weighted response time between the two points can be obtained, and the K-central problem modeled is transformed into several R-control set problems. Then, several control R-set problems are transformed into several 0-1 integer programming problems, and each integer programming problem can be solved one by one by using the branch and bound method. Finally, a simplified implementation method based on the above algorithm is given when K=1, the optimality of the proposed algorithm is proved and the complexity of the algorithm is analyzed. Simulation results show that the proposed central control algorithm can minimize the maximum weighted response time of the network.
Study on fine-grained mechanism of delay guarantee based on idea of particle access in wireless networks
Authors: SUN Ke , LI Bo , YAN Zhongjiang , YANG Mao
Published: June 2023

Aiming at the problems existing in the current mechanisms of delay guarantee in wireless networks(i.e. poor scalability, coarse granularity for provided service levels, and improving delay performance at the expense of sacrificing some resource utilization), this paper puts forward both the idea of particle access and the corresponding access mechanism. In this paper, a traffic flow is modeled as a group of information particles that carry a certain amount of information and are valid for certain periods of time. Firstly, the definitions of information particles and the group of information particles are given. It is proved that the minimum reachable access bandwidth of an information particle group can be achieved by using the EDF(earliest deadline first) transmission strategy. Moreover, a fine-grained mechanism of delay guarantee based on the idea of particle access is proposed for the dynamic access environment in wireless networks. Extensive simulations are carried out for the application scenario of downlink transmissions, and it is shown that, in the case of heavy traffic loads, comparing with the rapid growth of the average packet delays and the packet loss rates in a legacy access mechanism, the proposed fine-grained access strategy based on the idea of particle access can also achieve the better performance on the average packet delays and the packet loss rates, and hence higher effective throughput is obtained. The research in this paper pave a new way for further improving quality of service (QoS) mechanisms of wireless networks.
Analyzing thermal radiation in cylindrical anisotropic scattering medium with element differential method
Authors: LI Yifan , SUN Yasong , ZHANG Huabo , LI Sida , LIU Changhao , MA Jing
Published: June 2023

The spontaneous radiation combustion diagnosis technology has high requirements for obtaining the radiation intensity of highly directional resolution in a combustion system. Taking advantage of the numerical stability and easy implementation of the element differential method, this paper constructs a radiation model that can achieve the radiation intensity of spatial and angular high-resolution in cylindrical anisotropic scattering medium. In analyzing the radiation model, the radiation intensity is discretized in three dimensions. An upwind scheme is proposed to suppress the numerical oscillation of the strong convection characteristics of the radiation transfer equation. The double-layer node algorithm is used to capture the strong discontinuous singularities at the radiation boundary. The comparison with the analytical solution shows that the radiation model based on the element differential method can achieve the high-resolution description of radiation intensity with high-order accuracy. The accuracy and validity of the radiation model are verified through comparing with the results on the Monte Carlo method. The further description of the three-dimensional distribution of radiation intensity in angle and space proves that the up-wind scheme can effectively suppress numerical oscillation and realize stable calculation.
Design of finite time cooperative mid-course guidance law for unmanned target drone aircrafts
Authors: GUO Xiaowen , FAN Yonghua , ZHANG Minghuan , YAN Jie , WU Baoyuan
Published: June 2023

For cooperative mid-course guidance problem of multiple unmanned target drone aircrafts(UTDA), a novel cooperative guidance law with impact angle constraints is proposed in this study. Firstly, the relative motion equation of UTDAs and target, and the multiple-UTDA cooperative guidance model with impact angle constraints are constructed. Then, the process of cooperative guidance law design is divided into two stages. In the first stage, the acceleration command on the LOS direction is designed based on the fixed-time consensus theory, the speed dimension is introduced which can guarantee the consensus of all UTDAs' impact times in fixed time. In the second stage, an impact-angle-control guidance law is proposed based on the approaches of variable coefficients sliding mode control and finite-time convergence theory to reach the virtual targets, the acceleration command on the direction of perpendicular to the LOS is developed, which can ensure that all the LOS angles converge to the desired terminal LOS angle in finite-time and some mobility when approaching the virtual targets is achieved, and the Lyapunov stability is adopted. Finally, numerical simulations express that the cooperative mid-course guidance law designed in this study can make each UTDA reach the virtual target at the same time with small miss distance and meet the LOS constraint, and demonstrate the effectiveness of the proposed mid-course guidance law.
Ternary redundant sparse linear array design with high robustness
Authors: HOU Shuhua , ZHAO Xuanzhi , LIU Zengli , PENG Yi , WANG Na
Published: June 2023

Sparse linear array is prone to element failure affected by environmental and other factors in practical application, resulting in the decline of degrees of freedom and the attenuation or even failure of direction of arrival (DOA) estimation performance. To address this problem, a ternary redundant sparse array composed of three uniform linear arrays with different spacings at specific distances is designed, and the analytical expression of its degrees of freedom is derived. The configuration rules of the array are concise, and the difference coarrays of the array are hole-free. Mathematically proves that all virtual array elements can be covered with a weight of not less than 3 except the 4 farthest. The array has lower sensors importance and less generalized k-fragility. The array design takes into account the maximum degrees of freedom, redundancy and sparsity. In case of sensors failure, compared with the other sparse linear arrays, the array has more stable difference coarrays and higher uniform degrees of freedom. Compared with multiple-fold redundancy arrays, the array has lower mutual coupling. Simulation results show that the ternary redundant array has superior robustness and higher DOA estimation accuracy under sensors failure.
Three-dimensional growth simulation of swellable soft materials based on CS-FEM
Authors: PENG Fan , HUANG Wei , MA Yu'e , GUO Wen
Published: June 2023

In this paper, a three-dimensional numerical framework for modeling growth of swellable soft materials at large deformation is established based on the cell-based smooth finite element method, and the multiplicative decomposition scheme of deformation gradient is given. The second P-K stress and Green's strain tensor are selected as work conjugate pairs, and the corresponding mathematical expressions of stiffness matrix and geometric stiffness matrix are derived. The numerical method is implemented based on Matlab platform, and the isotropic and anisotropic growth behaviors of swellable soft materials are simulated respectively. The results show that anisotropic growth will inhibit the deformation of expandable soft materials compared with isotropic growth. The simulation results are compared with the calculation results in the existing literature. The comparison results show that the characteristics and the morphological mode are in good agreement, which proves the effectiveness of the numerical framework in simulating the growth behavior of expandable soft materials at large deformation, and is able to reveal the mechanical mechanism of the plant growth phenomenon in nature.