mlsa-iai-msu-lab/ru_sci_bench_zho_cite_reranking huggingface dataset:
NONLINEAR STABILITY OF RAREFACTION WAVES TO THE COMPRESSIBLE NAVIER-STOKES EQUATIONS FOR A REACTING MIXTURE WITH ZERO HEAT CONDUCTIVITY

In this paper, we study the time-asymptotically nonlinear stability of rarefaction waves for the Cauchy problem of the compressible Navier-Stokes equations for a reacting mixture with zero heat conductivity in one dimension. If the corresponding Riemann problem for the compressible Euler system admits the solutions consisting of rarefaction waves only, it is shown that its Cauchy problem has a unique global solution which tends time-asymptotically towards the rarefaction waves, while the initial perturbation and the strength of rarefaction waves are suitably small.
Theory of an m × n apple surface network with special boundary

As is well known,any condition change in a network model will affect the research method and result.This paper studies an arbitrary m × n apple surface network with a pair of non-uniform boundary resistors,which is a complex network that has not been solved before.The research process of this paper consists of four strict basic steps according to RT-V theory.With the breakthrough of matrix transformation and eigenvector solution,two exact potential function formulae and two equivalent resistance formulae are derived.A series of applications and special cases are given to help readers understand the results.In particular,we have drawn eight visualized potential function images,which can intuitively understand the changing characteristics of potential function.The establishment of theoretical results provides a new theoretical basis for related interdisciplinary research.
Generation and Evolution of Cavitation Bubbles in Volume Alternate Cavitation (VAC)

Cavitation generation methods have been used in multifarious directions because of their diversity, and numerous studies and discussions have been conducted on cavitation generation methods. This study aims to explore the generating mechanism and evolution law of volume alternate cavitation (VAC). In the VAC, liquid water is placed in an airtight container with a variable volume. As the volume alternately changes, the liquid water inside the container continues to cavitate. Then, the mixture turbulence model and in-cylinder dynamic grid model are adopted to conduct computational fluid dynamics simulation of volume alternate cavitation. In the simulation, the cloud images at seven heights on the central axis are monitored, and the phenomenon and mechanism of height and eccentricity are analyzed in detail. By employing the cavitation flow visualization method, the generating mechanism and evolution law of cavitation are revealed. The synergistic effects of experiments and high-speed camera capturing confirm the correctness of the simulation results. In the experiment, the volume change stroke of the airtight container is set to 20 mm, the volume change frequency is 18 Hz, and the shooting frequency of the high-speed camera is set to 10000 FPS.The experimental results indicate that the position of the cavitation phenomenon has a reasonable law during the whole evolution cycle of the cavitation cloud. Also, the volume alternation cycle corresponds to the generation, development, and collapse stages of cavitation bubbles.
Establishment and study of a polarized X-ray radiation facility

With the advancement in X-ray astronomical detection technology, various celestial polarization detection projects have been initiated. To meet the calibration requirements of polarimeters on the ground, a polarized X-ray radiation facility was designed for this study. The design was based on the principle that X-rays incident at 45° on a crystal produce polarized X-rays, and a second crystal was used to measure the polarization of the X-rays produced by the facility after rotation. The effects of different diaphragm sizes on the degree of polarization were compared, and the facility produced X-rays with polarization degrees of up to 99.55 ± 0.96% using LiF200 and LiF220 crystals. This result revealed that the polarization of incident X-rays is one of the factors affecting the diffraction efficiency of crystals. The replacement of different crystals can satisfy the calibration requirements of polarized X-ray detectors with more energy points in the energy range (4-10) keV. In the future, the facility should be placed in a vacuum environment to meet the calibration requirements at lower energies.
New Construction of Quadriphase Golay Complementary Pairs

Based on an arbitrarily-chosen binary Golay complementary pair(BGCP)(c,d) of even length N, first of all, construct quadriphase sequences a and b of length N by weighting addition and difference of the aforementioned pair with different weights, respectively. Secondly, new quadriphase sequence u is given by interleaving three sequences d, a, and -c, and similarly, the sequence v is acquired from three sequences d, b, and c. Thus, the resultant pair(u,v) is the quadriphase Golay complementary pair(QGCP) of length 3N. The QGCPs play a fairly important role in communications, radar, and so on.
Cavitation Evolution Around a Twist Hydrofoil by Large Eddy Simulation (LES) with Mesh Adaption

The cavitating flow around a Delft Twist-11 hydrofoil is simulated using the large eddy simulation approach. The volume- of-fluid method incorporated with the Schnerr-Sauer cavitation model is utilized to track the water-vapor interface. Adaptive mesh refinement (AMR) is also applied to improve the simulation accuracy automatically. Two refinement levels are conducted to verify the dominance of AMR in predicting cavitating flows. Results show that cavitation features, including the U-type structure of shedding clouds, are consistent with experimental observations. Even a coarse mesh can precisely capture the phase field without increasing the total cell number significantly using mesh adaption. The predicted shedding frequency agrees fairly well with the experimental data under refinement level 2. This study illustrates that AMR is a promising approach to achieve accurate simulations for multiscale cavitating flows within limited computational costs. Finally, the force element method is currently adopted to investigate the lift and drag fluctuations during the evolution of cavitation structure. The mechanisms of lift and drag fluctuations due to cavitation and the interaction between vorticity forces and cavitation are explicitly revealed.
An artificial neural network potential for uranium metal at low pressures

Based on machine learning, the high-dimensional fitting of potential energy surfaces under the framework of first principles provides density-functional accuracy of atomic interaction potential for high-precision and large-scale simulation of alloy materials. In this paper, we obtained the high-dimensional neural network(NN) potential function of uranium metal by training a large amount of first-principles calculated data. The lattice constants of uranium metal with different crystal structures, the elastic constants, and the anisotropy of lattice expansion of alpha-uranium obtained based on this potential function are highly consistent with first-principles calculation or experimental data. In addition, the calculated formation energy of vacancies in alpha- and beta-uranium also matches the first-principles calculation. The calculated site of the most stable self-interstitial and its formation energy is in good agreement with the findings from density functional theory(DFT) calculations. These results show that our potential function can be used for further large-scale molecular dynamics simulation studies of uranium metal at low pressures, and provides the basis for further construction of potential model suitable for a wide range of pressures.
Important edge identification in complex networks based on local and global features

Identifying important nodes and edges in complex networks has always been a popular research topic in network science and also has important implications for the protection of real-world complex systems. Finding the critical structures in a system allows us to protect the system from attacks or failures with minimal cost. To date, the problem of identifying critical nodes in networks has been widely studied by many scholars, and the theory is becoming increasingly mature. However, there is relatively little research related to edges. In fact, critical edges play an important role in maintaining the basic functions of the network and keeping the integrity of the structure. Sometimes protecting critical edges is less costly and more flexible in operation than just focusing on nodes. Considering the integrity of the network topology and the propagation dynamics on it, this paper proposes a centrality measure based on the number of high-order structural overlaps in the first and second-order neighborhoods of edges. The effectiveness of the metric is verified by the infection- susceptibility(SI) model, the robustness index R, and the number of connected branches θ. A comparison is made with three currently popular edge importance metrics from two synthetic and four real networks. The simulation results show that the method outperforms existing methods in identifying critical edges that have a significant impact on both network connectivity and propagation dynamics. At the same time, the near-linear time complexity can be applied to large-scale networks.
Shading Fault Detection Method for Household Photovoltaic Power Stations Based on Inherent Characteristics of Monthly String Current Data Mapping

The poor outdoor operating conditions of household photovoltaic (PV) make the power station prone to various faults. However, the dispersion of household PV installations often increases the difficulty and cost of operation and maintenance (O&M). Although the remote monitoring and fault detection of a PV power station can be realized by the use of operation data, the particularity of a household power station also brings many problems to fault detection. In this study, we propose a shading fault detection method of household PV power based on inherent characteristics of monthly string current data mapping. The ideal current peak obtained by a new fitting method is used to normalize string current data. The current probability density function (PDF) at each time point is estimated by kernel density estimation (KDE). Through the normalized current data corresponding to the maximum probability density, the inherent characteristics of the strings are obtained, such that whether the strings have shading can be judged and the shading degree can then be evaluated. Not only are no additional sensors needed to collect environmental data, such as irradiation and temperature, but also simulating the detailed parameters of the power station is not required. The interference caused by meteorological factors can thus be eliminated, which can be easily used in old power stations and newly constructed power stations. The effectiveness and performance of the proposed shading fault detection method is verified by experimental data collected from the actual household PV power station.
Fast SHEPWM Solution Method for Wind Power Converter Based on State Equations

Selective harmonic elimination pulse width modulation (SHEPWM) is a modulation strategy widely used for threelevel wind power grid-connected converters. Its purpose is to eliminate specified sub-low frequency harmonics by controlling switching angle. Furthermore, it can reduce fluctuation of the microgrid system and improve system stability. Intelligent algorithms have been applied to the SHEPWM solution process to mitigate calculation complexity associated with the algebraic method, as well as the need to set the initial value. However,disorder of the optimization result causes difficulty in satisfying incremental constraint of the three-level NPC switching angles,and affects the success rate of the algorithm. To overcome this limitation, this paper proposes a fast SHEPWM strategy to optimize the result obtained by the intelligent algorithm. The SHEPWM can be realized by solving switching angles through a state equations-based mathematical model, which is constructed by using the initial variables randomly generated by the intelligent algorithm as the disturbance. This mathematical model improves the success rate of calculation by simplifying constraint representation of switching angles and solving the disorder problem of the optimization result. At the same time,a method based on the circle equation and the trigonometric function is applied to the initial variable assignment of the state equation, which further improves the speed and accuracy of the solution, realizes a more thorough filtering effect, and further reduces the impact of sub-low frequency harmonics on a wind power integrated system. Finally, simulation and experiment results have been used to prove the effectiveness of the proposed SHEPWM strategy when combined with intelligent algorithms.
Microgrid Energy Management: Classification,Review and Challenges

Microgrids provide a way to introduce ecologically acceptable energy production to the power grid. The main challenges with microgrids are overall control, as well as maintaining safe, reliable and economical operation. Researchers explore implementing these possibilities, but in rapidly expanding areas of research there is always a need to review what has been done so far and give guidelines to new researchers on topics in need of more exploration. This paper offers an extensive literature review of the energy management part of the microgrid control system. Based on extensive literature research, the authors of this article offer their view on energy management system organization. Review through centralized and decentralized structure is given. The most popular research topic is the optimization of energy management. This paper offers a new perspective on the classification of optimization methods used for microgrid energy management, listing and sorting many problem related references. The microgrid is not an assembly of independent elements but rather a coordinated system of intertwined functions. These elements of microgrid functioning, like energy storage systems,demand side management. Electric vehicles are also explored in this paper, giving the current state of their research through references.
Improving the Performance of DC Microgrids by Utilizing Adaptive Takagi-Sugeno Model Predictive Control

In naval direct current (DC) microgrids, pulsed power loads (PPLs) are becoming more prominent. A solar system,an energy storage system, and a pulse load coupled directly to the DC bus compose a DC microgrid in this study. For DC microgrids equipped with sonar, radar, and other sensors, pulse load research is crucial. Due to high pulse loads, there is a possibility of severe power pulsation and voltage loss. The original contribution of this paper is that we are able to address the nonlinear problem by applying the Takagi-Sugeno (TS) model formulation for naval DC microgrids. Additionally, we provide a nonlinear power observer for estimating major disturbances affecting DC microgrids. To demonstrate the TS-potential, we examine three approaches for mitigating their negative effects: instantaneous power control (IPC) control, model predictive control (MPC) formulation, and TS-MPC approach with compensated PPLs. The results reveal that the TS-MPC approach with adjusted PPLs effectively shares power and regulates bus voltage under a variety of load conditions, while greatly decreasing detrimental impacts of the pulse load. Additionally, the comparison confirmed the efficiency of this technique.
Low-loss and Compact Hybrid DC Circuit Breaker Scheme Using Self-commutated Semiconductor Switch Module

In traditional hybrid DC circuit breakers (HCBs) schemes, complex equipment is usually required to ensure current commutation from mechanical to semiconductor switches, which cause not only additional construction costs and volume but also additional losses and maintenance work. Different from this condition, a low-loss and compact HCB scheme that does not use separate current commutation equipment is proposed in this study. By rationally using the charge and discharge of the snubber capacitor, the self-commutated semiconductor switch (SCS) module can integrate both the current commutation and shutdown functions, thereby greatly reducing cost and volume. The working process is discussed and analyzed in detail, and then a 10-kA prototype is developed and tested, which verifies the feasibility and effectiveness of the proposed scheme.
A Review on Robust and Adaptive Control Schemes for Microgrid

Several challenges are encountered while integrating microgrids (MGs) with an existing utility grid.These are low inertia,intermittent nature of renewable energy resources (RESs),sensor and actuator faults,unbalanced and nonlinear loads,supply-demand mismatch,and uncertain switching functions of the power electronic converter.MG control is fully dependent on the communication network,which is also susceptible to different types of failures such as noise in communication links,communication delay,limited bandwidth,packet dropout,and various malicious cyber attacks.Very few papers are available in the literature that focus on the review of control schemes for MG.Consequently,this paper presents a comprehensive review of different robust and adaptive control schemes that address the challenges encountered due to communication constraints,uncertainties,and disturbances for different MG topologies such as AC,DC,and hybrid AC/DC MGs,as well as the current research trends in the field of robust and adaptive control.It can be concluded that to achieve control objectives of MG and overcome the existing challenges,robust and adaptive controllers show significantly improved performance in terms of transient and steady-state behavior and robustness as compared to traditional controllers.
A Generalized Wind Turbine Anomaly Detection Method Based on Combined Probability Estimation Model

Anomaly detection based on the data collected from the supervisory control and data acquisition (SCADA) system is crucial to reduce the failure rate of wind turbines (WTs).The difficulty of this kind of methods is to dynamically identify the threshold for anomaly detection under changing operating conditions.In this paper,a generalized WT anomaly detection method based on the combined probability estimation model (CPEM) is proposed.The CPEM can estimate the conditional probability density function (PDF) of the target variable given changing conditions.Its generalization and accuracy are better than those of the independent probability estimation model because it combines the advantages of various kinds of probability estimation models through linear combination.By using the CPEM,the normal operating bounds under different operating conditions can be obtained,which dynamically form the thresholds for anomaly detection.Meanwhile,with respect to the thresholds,hypothesis testing (HT) is adopted to identify the anomaly by inspecting whether the observations exceed the thresholds at a given significance level,providing sound mathematical support for anomaly detection and making the detection results more reliable.The effectiveness of the proposed method is tested by using the actual data of WTs with known faults.The results illustrate that the proposed method can detect the abnormal operating state of the gearbox and generator much more early than the system fault alarm.
A Novel PLL Structure for Dynamic Stability Improvement of DFIG-based Wind Energy Generation Systems During Asymmetric LVRT

The dynamic coupling effect,which is introduced by the dual-sequence phase-locked loops (PLLs) used in doublyfed induction generator (DFIG) based wind energy generation systems (WEGSs) during asymmetric low voltage ride-through (LVRT) in weak grid,needs attention.In order to study this new dynamic coupling effect,an equivalent two-degree-of-freedom (2-DOF) spring damper particle model is used in this paper to develop a small-signal model for the dual-sequence PLLs.The dynamic interaction between the positive-sequence (PS) and negative-sequence (NS) PLLs is unveiled.Moreover,the impact of the dynamic coupling between the dual-sequence PLLs on the dynamic stability during the steady-state stage of an asymmetric fault is analyzed.The analysis results show that the dynamic coupling between the dual-sequence PLLs will cause drift in the frequency and damping for the PS and NS PLL modes.This will change the instability modal of the system and introduce the risk of dynamic instability.Hence,the effectiveness of existing control strategies for enhancing the dynamic stability will be decreased.Finally,a novel PLL structure is designed to improve the dynamic stability of the system during the steady-state stage of an asymmetric fault.The effectiveness of the proposed strategy is verified by simulations and experiments.
Three-way Subsynchronous Torsional Interactions Between LCC HVDC,MMC HVDC and a Thermal Generator

This paper performs a study on three-way subsynchronous torsional interactions (SSTI) between a hybrid dual-infeed high-voltage direct current (HVDC) system and a nuclear generator.The test case is based on the French IFA2000 line commutated converter (LCC) HVDC (2 GW) and the new Eleclink modular multilevel converter (MMC) HVDC (1 GW) interacting with the Gravelines generator (1 GW).The analysis is performed by the means of the eigenvalue stability assessment on an analytical model,while the accuracy of the conclusions is verified using the detailed non-linear electromegnetic transient program (EMTP) model.The study shows that the dual-infeed system may introduce higher risk of the SSTI compared with the point-to-point HVDC systems.It shows that MMC operating as static synchronous compensator (STATCOM) may further reduce the torsional damping at 6.3 Hz mode.This conclusion may be unexpected since it is known fact from literature that STATCOM has a beneficial impact on the transient performance of LCC.Further studies show that in a sequential HVDC loading,it may be beneficial to load the MMC HVDC first.Also,the risk of the SSTI may be minimized by changing HVDC controller gains,in particular,by increasing phaselocked-loop (PLL) gains on the LCC rectifier.
Grid Strength Assessment for Inhomogeneous Multi-infeed HVDC Systems via Generalized Short Circuit Ratio

Generalized short circuit ratio (gSCR) for grid strength assessment of multi-infeed high-voltage direct current (MIDC) systems is a rigorous theoretical extension of the traditional SCR,which enables SCR to be extended to MIDC systems.However,gSCR is originally based on the assumption of homogeneous MIDC systems,in which all high-voltage direct current (HVDC) converters have an identical control configuration,thus presenting challenges to applications of gSCR to inhomogeneous MIDC systems.To weaken this assumption,this paper applies matrix perturbation theory to explore the possibility of utilization of gSCR into inhomogeneous MIDC systems.Results of numerical experiments show that in inhomogeneous MIDC systems,the previously proposed gSCR can still be used without modification.However,critical gSCR (CgSCR) must be redefined by considering the characteristics of control configurations of HVDC converter.Accordingly,the difference between gSCR and redefined CgSCR can effectively quantify the pertinent AC grid strength in terms of the static-voltage stability margin.The performance of the proposed method is demonstrated in a triple-infeed inhomogeneous line commutated converter based high-voltage direct current (LCC-HVDC) system.