Most Cited
2017, 66 (7): 074207.
doi: 10.7498/aps.66.074207
Abstract +
Distributed fiber-optic sensing (DFOS) is one of the most important parts in the fiber-optic sensing field, due to the following advantages:1) there is no need to manufacture sensors on the fiber; 2) fibers are able to realize transmission and detection simultaneously; 3) long-distance/large-scale sensing and networking can be accomplished prospectively; 4) the spatial distribution and measurement information of physical parameters such as temperature, strain and vibration, can be obtained continuously along the fiber link, and the number of sensing points on a single fiber can be up to several tens of thousands. Due to the above tremendous superiority, DFOS has found wide application prospects, including perimeter security, oil/gas exploration, electrical facilities and structure monitoring, etc. This paper overviews recent progress in ultra-long distributed fiber-optic static (Brillouin optical time-domain analyzer) and dynamic (phase-sensitive optical time-domain reflectometer) sensing at Key Laboratory of Optical Fiber Sensing and Communications, UESTC. This paper summarizes our work on both basic and application studies.
2017, 66 (7): 070705.
doi: 10.7498/aps.66.070705
Abstract +
With the superiority of anti-electromagnetic interference, corrosion resistance, light quality, small size and so on, optical fiber sensing technology is widely used in aerospace industry, petrochemical engineering, power electronics, civil engineering and biological medicine. It can be divided as discrete and distributed. Discrete optical fiber sensing utilizes fiber sensitive element as sensors to detect the quantity to be measured. Optical spectrum, light intensity and polarization are usually used as the sensitivity parameter because they can be modulated by parameter such as rotation, acceleration, electromagnetic field, temperature, pressure, stress, stress, vibration, humidity, viscosity, refractive index and so on. Fiber works as the channel and links the fiber sensor and demodulating equipment. After a long period of research, the discrete optical fiber sensing technology stretch out many branches, we discussed the most representative ones as follows, the fiber grating sensing technique, the fiber fabry perot sensing technique, the fiber gyroscope sensing technique, the fiber intracavity sensing technique, the fiber surface plasma sensing technique, hollow-core fiber whispering gallery mode sensing technique, magnetic fluid fiber sensing technique and fiber-based optical coherence tomography sensing technique. Based on optical effect as rayleigh scattering, Raman scattering and Brillouin scattering, distributed fiber sensing system uses fiber itself as a sensor, when the vibration, stress, voice or temperature acts on the fiber changes, the optical signal transfers inside the fiber will change accordingly. The fiber distributes in a large range and a long distance, then the signal can be located at different positions and realize the multi-position measurement. We discussed the main distributed fiber sensing technologies as follows, the interferometric disturbance fiber sensing technology, the optical frequency domain reflectometry fiber sensing technology, the -optical time domain reflectometer fiber sensing technology, the optical fiber Brillouin sensing technology and the optical fiber Raman sensing technology. The development of technology is promoting the integration and network of optical fiber sensing, now it also becomes a research hotspot. Fiber optic smart sensor network is formed by various discrete and discrete optical fiber sensors in certain topological structure with the function of self-diagnosis and self-healing. Current research concentrates in the following areas, the increase of the multiplex sensor number, the topological structure with higher robustness and the intelligent control of sensing network. In this paper, we discuss the origination, development and research progress of discrete, distributed optical fiber sensing technologies and optical fiber sensing network technology, and the future research direction is also prospected.
2017, 66 (3): 038902.
doi: 10.7498/aps.66.038902
Abstract +
Ranking node importance is of great significance for studying the robustness and vulnerability of complex network. Over the recent years, various centrality indices such as degree, semilocal, K-shell, betweenness and closeness centrality have been employed to measure node importance in the network. Among them, some well-known global measures such as betweenness centrality and closeness centrality can achieve generally higher accuracy in ranking nodes, while their computation complexity is relatively high, and also the global information is not readily available in a large-scaled network. In this paper, we propose a new local metric which only needs to obtain the neighborhood information within two hops of the node to rank node importance. Firstly, we calculate the similarity of node neighbors by quantifying the overlap of their topological structures with Jaccard index; secondly, the similarity between pairs of neighbor nodes is calculated synthetically, and the redundancy of the local link of nodes is obtained. Finally, by reducing the influence of densely local links on ranking node importance, a new local index named LLS that considers both neighborhood similarity and node degree is proposed. To check the effectiveness of the proposed method of ranking node importance, we carry out it on six real world networks and one artificial small-world network by static attacks and dynamic attacks. In the static attack mode, the ranking value of each node is the same as that in the original network. In the dynamic attack mode, once the nodes are removed, the centrality of each node needs recalculating. The relative size of the giant component and the network efficiency are used for network connectivity assessment during the attack. A faster decrease in the size of the giant component and a faster decay of network efficiency indicate a more effective attack strategy. By comparing the decline rates of these two indices to evaluate the connectedness of all networks, we find that the proposed method is more efficient than traditional local metrics such as degree centrality, semilocal centrality, K-shell decomposition method, no matter whether it is in the static or dynamic manner. And for a certain ranking method, the results of the dynamic attack are always better than those of the static attack. This work can shed some light on how the local densely connections affect the node centrality in maintaining network robustness.
2017, 66 (5): 050502.
doi: 10.7498/aps.66.050502
Abstract +
Particle filer is apt to have particle impoverishment with unstable filtering precision, and a large number of granules are required to estimate the nonlinear system accurately, which reduces the comprehensive performance of the algorithm. To solve this problem, a new particle filter based on bat algorithm is presented in this paper, where particles are used to represent individual bat so as to imitate the search process of bats for preys. In traditional resampling process, particles are directly discarded, the improved algorithm adopts another approach and solves the problem of particle impoverishment. It combines the advantages of particle swarm optimization algorithm and harmonic algorithm perfectly. New particle filter has capacity of global and local search and is superior in computation accuracy and efficiency. By adjusting frequency, loudness, and impulse emissivity of particle swarm, the optimal particle at that time is followed by particle swarm to search in the solution space. The global search and local search can be switched dynamically to improve the overall quality of the particles swarm as well as the distribution rationality. In addition, the improved particle filter uses Lvy flight strategy to avoid being attracted by harmful local optimal solution, it expands the space of research and further promotes the optimization effect of particle distribution. Using the useful information about particle swarm, improved particle filter can make particles get rid of local optimum and reduce the waste of iterations in insignificant status change. Based on the number of valid particle samples, it can improve quality of particle samples by expanding their diversity. In information interaction mechanism of improved particle filter, the method in this paper sets scoreboard of particle target function to compare the value of particle target function at each iteration sub-moment with the value of target function on scoreboard to gain global optimum of all particles at current filtering moment. Taking information interaction between global optimum and particle swarm, the guiding function of global optimum is realized. The process of particle optimization is ended prematurely through setting a maximum iteration or termination threshold. There is a tendency for the whole particle swarm closing to high likehood area without global convergence so that the advantages of improved particle filter in accuracy and speed will not be damaged. In addition, convergence analysis and computational complexity analysis are given in this paper. Experiment indicates that this method can improve the particle diversity and prediction accuracy of particle filter, and meanwhile reduce the particle quantity obviously which is required by the state value prediction for nonlinear system.
2017, 66 (9): 094502.
doi: 10.7498/aps.66.094502
Abstract +
This paper is aimed at building a framework for string stability analysis of traffic flow mixed with different cooperative adaptive cruise control (CACC) market penetration rates. In addition to the string stability, the fundamental diagram of the mixed flow is also taken into consideration for evaluating the effect of CACC vehicles on capacity.
In order to describe the car-following dynamics of real CACC vehicles, the CACC model proposed by PATH is employed, which is validated by real experimental data. The intelligent driver model (IDM) is used as a surrogate car-following model for traditional manual driven vehicles. Based on the guidelines proposed by Ward[Ward J A 2009 Ph. D. Dissertation (Bristol:University of Bristol)], a framework is developed for the analytical investigation of heterogeneous traffic flow string stability. The framework presented considers the instability condition of traffic flow as a linear function of CACC market penetration rate. Following the framework, the string stabilities of the mixed traffic flow under different CACC market penetration rates and equilibrium velocities are analyzed. For fundamental diagram of the heterogeneous traffic flow, the equilibrium velocity-spacing functions of manual vehicles and CACC vehicles are obtained respectively based on car-following model. Then, the fundamental diagram of the density-velocity relationship of the heterogeneous traffic flow is derived based on the definition of traffic flow density. In addition, the theoretical fundamental diagram is plotted to show the property of traffic throughput. The numerical simulations are also carried out in order to investigate the effect of CACC vehicle on the characteristics of fundamental diagram. Besides, sensitivity analyses on CACC desired time gap are conducted for both string stability and fundamental diagram.
Analytical studies and simulation results are as follows. 1) The heterogeneous traffic flow is stable for different equilibrium velocities and CACC market penetration rates, if manual driven vehicles are stable. Otherwise, the instability of traditional traffic flow is improved gradually with the increase of the CACC market penetration rate. Additionally, the stability will become better when equilibrium velocity is away from the velocity range of 9.6-18.6 m/s. 2) Because CACC vehicles can travel at free-flow speed in a relatively small headway, CACC vehicles can improve the capacity of heterogeneous traffic flow. 3) The results of sensitivity analysis indicate that with the increase of the CACC desired time gap, the stable region of heterogeneous traffic flow increases. However, the capacity of the fundamental diagram drops. Therefore, the value of the desired time gap should be determined with considering the effects of the two aspects on the heterogeneous traffic flow. It is noted that the CACC model used in this paper is based on the current state-of-the-art real CACC vehicle experiments. In the future, more experimental observations will yield new CACC models. However, the framework presented in this paper can still be used for the analytical investigation of string stability of the heterogeneous traffic flow at that time.
2017, 66 (4): 048102.
doi: 10.7498/aps.66.048102
Abstract +
Magnetic flux leakage (MFL) has been widely applied to the nondestructive testing (NDT) of ferromagnetic materials due to its simple operation, low cost, and steady signal. Its defects are evaluated based on the relationship between MFL signal and the geometrical characteristic of defect. In this paper, a three-dimensional (3D) mathematical model is developed for the magnetic leakage field of surface-breaking defects that are arbitrarily oriented inside ferromagnetic material. Firstly, a finite-length rectangular slot is used as a simplified and convenient representation of a surface-breaking defect. Then, the magnetic charge densities of slot walls in different surface-breaking orientations are analyzed theoretically. The distribution of the magnetic leakage field can ultimately be derived by vector synthesis. Both simulations and experiments are conducted to analyze the magnetic leakage field distributions in different magnetization orientations. The results show that with increasing the angle between the defect orientation and the magnetic field, the horizontal component of the leakage magnetic field increases as demonstrated by increasing the prominence of its single peak. At the same time, however, the vertical component shows a bimodal distribution. The proposed model can effectively describe the influence of defect orientation on MFL signals, which can offer practical guidelines for optimizing MFL detectors and improving defect assessment.
2017, 66 (23): 230503.
doi: 10.7498/aps.66.230503
Abstract +
Aiming at the data security problem in big data environment, in this paper we propose a new chaotic encryption algorithm based on both big data platform named Hadoop and non-degenerate high-dimensional discrete hyperchaotic system. The algorithm utilizes the chaotic stream cryptography and reads the data from HDFS of Hadoop platform. After fragmentation processing and MapReduce programming, the data are encrypted and decrypted by Map function in parallel. The Reduce function implements the merging operation of the data and stores them on the HDFS. The algorithm has a better execution efficiency. Compared with the low-dimensional chaotic system based encryption algorithm, the non-degenerate high-dimensional discrete chaotic system based encryption algorithm can improve the system security performance. It can pass the strict TESTU01 test with better statistical properties and make sure that the correlation with the parallel ciphertext is very small. Numerous key parameters increase the difficulty in making estimation or identification. Under the closed-loop feedback in ciphertext, it has the ability to resist the known and chosen plaintext attacks.
2017, 66 (5): 050201.
doi: 10.7498/aps.66.050201
Abstract +
In complex networks, the node importance evaluation is of great significance for studying the robustness of network. The existing methods of evaluating the node importance mainly focus on undirected and unweighted networks, which fail to reflect the real scenarios comprehensively and objectively. In this paper, according to the directed and weighted complex network model, by analyzing the local importance of the nodes and the dependencies among all the nodes in the whole network, a new method of evaluating the node importance based on a multiple influence matrix is proposed. Firstly, the method defines the concept of cross strength to characterize the local importance of the nodes. The index not only distinguishes between the in-strength and out-strength of the nodes, but also helps to discriminate the differences in importance among each with an in-degree of 0. In addition, to characterize the global importance of the nodes to be evaluated, we use the total important influence value of all the nodes exerted on the nodes, which makes up the deficiencies of the other evaluation methods which just depend on adjacent nodes. Emphatically, in the analysis of the influence ratio of source node on node to be evaluated, we not only take into account the distance factor between nodes, but also introduce the number of the shortest path factors. In order to make the evaluation algorithm more accurate, according to the number of the shortest paths, we present two perspectives to analyze how other factors affect the influence ratio. One is to evaluate how this source node exerts important influence on the other nodes to be evaluated. The other is to analyze how the other source nodes perform important influence on this node to be evaluated. In view of the above factors, three influence matrices are constructed, including the efficiency matrix, and the other two influence matrices from the perspectives of fixing source nodes and target nodes, respectively. Then, we use analytic hierarchy process to weight the three matrices, thereby obtaining the multiple influence matrix, which makes the global importance evaluation more comprehensive. Finally, the method is applied to typical directed weighted networks. It is found that compared with other methods, our method can effectively distinguish between nodes. Furthermore, we carry out simulation experiments of cascading failure on each method. The simulation results further verify the effectiveness of the proposed method.
2017, 66 (17): 176112.
doi: 10.7498/aps.66.176112
Abstract +
Owing to the superior mechanical and physical properties, metallic glasses (MGs) have attracted tremendous attention as promising candidates for structural and functional applications. Unfortunately, the ability to form uncontrollable glasses, the poor stability and the unpredicted catastrophic failure stemming from the disordered structure, as the Achilles' heel of MGs, severely restrict their large-scale applications. A number of phenomenological models, such as free volume model, shear transformation zone (STZ) model, flow unit model, etc., have been proposed, intending to relate microstructures to properties of MGs. However, few sophisticated structure-property relationships are established due to a poor understanding of the microstructure of MGs. Recently, heterogeneity is commonly believed to be intrinsic to MGs, and it can be used to establish the structure-property relationship of MGs. In this paper, we review the recent progress of MGs from the angle of heterogeneity, including the static heterogeneities and dynamic heterogeneities. The perspectives of the scientific problems and the challenges of metallic glass researches are also discussed briefly.
2017, 66 (7): 074205.
doi: 10.7498/aps.66.074205
Abstract +
Fiber-optic ultrasonic sensors possess the ability to detect ultrasonic waves by recovery of light intensity, wavelength, phase, and polarization. Compared with traditional electrical ultrasonic transducers, fiber-optic ultrasonic sensors have several merits, such as broadband response, high sensitivity, disturbance resistance, and good reusability, which are helpful to improve the reliability and efficiency of ultrasonic detection in underwater defense security, bioimaging, nondestructive inspection, and imaging of seismic physical models.
To date, according to the principle, fiber-optic ultrasonic sensors can be classified into three types, including intensity modulation, fiber-optic interferometers and fiber gratings. For the intensity-modulated fiber-optic ultrasonic sensors, ultrasonic waves can be detected by measuring optical fiber coupling loss, fiber transmission-reflection loss, fiber reflection loss and fiber polarization loss. The phase difference in fiber-optic interferometers can be modulated by ultrasonic strain. According to the interference mechanism, fiber-optic interferometric ultrasonic sensors are generally based on Mach-Zehnder interference, Fabry-Perot interference, Michelson interference and Sagnac interference. For the ultrasonic sensors based on fiber gratings, the grating length is supposed to be shorter than the ultrasonic wavelength so that the ultrasonic stress presents constant along the fiber gratings. Currently, the approaches of spectral edge filtering and wavelength-matched filtering are utilized to transform optical signals into voltage signals, which highly depend on the slope of the grating spectra. Thus, the fiber gratings with extremely narrow 3-dB bandwidth, such as phase shifted fiber Bragg grating, are preferred for highly sensitive ultrasonic detection. Besides the fiber-optic passive sensing, the distributed feedback fiber laser and distributed Bragg reflector also exhibit outstanding advantages in ultrasonic detection.
Fiber-optic ultrasonic detecting technique is one of the hot topics in international research community, which is an effective method to evaluate the microstructure and related mechanical properties, and detect the microcosmic and macroscopic discontinuities of solid materials. In this paper, three typical applications of ultrasonic detection, i.e., monitoring of smart structure and health, biomedical imaging, and imaging of seismic physical models are reviewed, respectively. Our group has been engaged in the research fields of fiber-optic geophones and ultrasonic sensors for seismic exploration for decades. Several fiber-optic ultrasonic sensors with smart packaging are proposed and also used for the scanning imaging of two physical models.
In this paper we review the sensing mechanism, fabrication method, and current status of three types of fiber-optic ultrasonic sensors, respectively. Besides, the corresponding applications and technology challenges are also summarized. In particular, we present several kinds of home-made optical fiber ultrasonic sensors as a new technology applied in the imaging of seismic physical models. Overall, after decades of efforts, gratifying achievements have been achieved in the research of fiber-optic ultrasonic sensors. Further work needs to solve various technical issues, such as sensitivity, stability, structural microminiaturization, and multiplexing, etc. The next step will focus on the research issues in ultrasonic detection of seismic physical models, performance improvement, and multiplexing technology for distributed sensing. Miniaturization of fiber sensors and instrumentation of sensing system will also be the important research topic. The final objective of the research is to build a well integrated fiber-optic ultrasonic detecting system with high sensitivity and stability, networking construction, and proprietary intellectual property rights.
2017, 66 (3): 030501.
doi: 10.7498/aps.66.030501
Abstract +
With the development of online social networks, they rapidly become an ideal platform for information about social information diffusion, commodity marketing, shopping recommendation, opinion expression and social consensus. The social network information propagation has become a research hotspot correspondingly. Meanwhile, information diffusion contains complex dynamic genesis in online social networks. In view of the diversity of information transmission, the efficiency of propagation and the convenience of interaction, it is very important to regulate the accuracy, strengthen the public opinion monitoring and formulating the information control strategy.
The purpose of this study is to quantify the intensity of the influence, especially provides a theoretical basis for studying the state transition of different user groups in the evolution process. As existing epidemic model paid less attention to influence factors and previous research about influence calculation mainly focused on static network topology but ignored individual behavior characteristics, we propose an information diffusion dynamics model based on dynamic user behaviors and influence. Firstly, according to the multiple linear regression model, we put forward a method to analyze internal and external factors for influence formation from two aspects:personal memory and user interaction. Secondly, for a similar propagation mechanism of information diffusion and epidemics spreading, in this paper we present an improved SIR model based on mean-field theory by introducing influence factor.
The contribution of this paper can be summarized as follows. 1) For the influence quantification, different from the current research work that mainly focuses on network structure, we integrate the internal factors and external factors, and propose a user influence evaluation method based on the multiple linear regression model. The individual memory principle is analyzed by combining user attributes and individual behavior. User interaction is also studied by using the shortest path method in graph theory. 2) On modeling the information diffusion, by referring SIR model, we introduce the user influence factor as the parameter of the state change into the epidemic model. The mean-field theory is used to establish the differential equations. Subsequently, the novel information diffusion dynamics model and verification method are proposed. The method avoids the randomness of the artificial setting parameters within the model, and reveals the nature of multi-factors coupling in the information transmission.
Experimental results show that the optimized model can comprehend the principle and information diffusion mechanism of social influence from a more macroscopic level. The study can not only explain the internal and external dynamics genesis of information diffusion, but also explore the behavioral characteristics and behavior laws of human. In addition, we try to provide theoretical basis for situation awareness and control strategy of social information diffusion.
2017, 66 (11): 110701.
doi: 10.7498/aps.66.110701
Abstract +
refrigeration technology. It has been considered as one of promising alternatives to traditional vapor compression refrigeration technology. Magnetic refrigeration, in which solid magnetic materials instead of gaseous refrigerants are used, is based on the magnetocaloric effect. When magnetocaloric material moves in or out of magnetic field, it releases heat due to magnetization or absorbs heat due to demagnetization, respectively. In this paper, magnetocaloric effects (MCEs) and basic thermodynamic cycles are briefly described at first. Some typical magnetic refrigeration cycles are introduced from the viewpoint of thermodynamics, which include hybrid cycle, cycle based on the active magnetic regenerator and cycle based on the active magnetic regenerator coupled with gas regenerative refrigeration. Specifically, magnetic refrigeration cycle based on the active magnetic regenerator (AMR) coupled with gas regenerative refrigeration is a novel idea that combines the magnetocaloric effect with the regenerative gas expansion refrigeration. And it has been under the way to try to achieve greater refrigeration performance of the coupled refrigerator in the research institutions. Thereafter, the paper reviews the existing different numerical models of AMR refrigerator. Analyzing and optimizing an AMR magnetic refrigerator are typical complicated multi-physics problems, which include heat transfer, fluid dynamics and magnetics. The majority of models published are based on one-dimensional simplification, which requires shorter computation time and lower computation resources. Because a one-dimensional model idealizes many factors important for the system performance, two- or three- dimensional numerical models have been setup. Besides, some key items for the model are described in detail, such as magnetocaloric effect, thermal conduction, thermal losses, demagnetizing effect and magnetic hysteresis. Considering the accuracy, convergence and computation time, it is quite vital for numerical models to choose some influential factors reasonably. Then, the recent typical room magnetic refrigeration systems are listed and grouped into four types, i.e., reciprocating-magnet type, reciprocating-regenerator type, rotary-magnet type, and rotaryregenerators type. Different characteristics of these four types are compared. Reciprocating magnetic refrigerators have the advantages of simple construction and max magnetic field intensity difference. Rotary magnetic refrigerator due to compact construction, higher operational frequency and better performance is deemed as a more promising type, in the progress of magnetic refrigeration technology. Meanwhile there are still some key challenges in the practical implementation of magnetic refrigeration technology, such as the development and preparation technologies of high-performance MCE materials, powerful magnetic circuit system and flowing condition. Finally, possible applications are discussed and the tendency of future development is given.
2017, 66 (8): 084203.
doi: 10.7498/aps.66.084203
Abstract +
To overcome the limitation of existing algorithms for detecting moving objects from the dynamic scenes, a foreground detection algorithm based on optical flow field analysis is proposed. Firstly, the object boundary information is determined by detecting the differences in optical flow gradient magnitude and optical flow vector direction between foreground and background. Then, the pixels inside the objects are obtained based on the point-in-polygon problem from computational geometry. Finally, the superpixels per frame are acquired by over-segmenting method. And taking the superpixels as nodes, the Markov Random field model is built, in which the appearance information fitted by Gaussian Mixture Model is combined with spatiotemporal constraints of each superpixel. The final foreground detection result is obtained by finding the minimum value of the energy function. The proposed algorithm does not need any priori assumptions, and can effectively realize the moving object detection in dynamic and stationary background. The experimental results show that the proposed algorithm is superior to the existing state-of-the-art algorithms in the detection accuracy, robustness and time consuming.
2017, 66 (4): 040502.
doi: 10.7498/aps.66.040502
Abstract +
A memristor is a nonlinear nanoscale-sized element with memory function, and it has an italic type 8 voltage-current relation curve that looks like a pinched hysteresis loop characteristic. The memristor is utilized to construct chaotic circuit, which has attracted the attention of the researchers. At present, most of studies focus on applying one or two memristors to the chaotic circuit. In order to study the multi memristor chaotic circuit, in this work we propose a six-order chaotic circuit with two flux-controlled memristors and a charge-controlled memristor. A corresponding six-order nonlinear dynamic differential equation of the circuit state variables is established. The dynamic properties of the circuit are demonstrated in detail. The analyses of equilibria and equilibrium stability show that the circuit has an equilibrium located in the three-dimensional space which is constituted by memristor internal state variables, and it is found that the equilibrium stability is determined by the circuit parameters and the initial states of three memristors. The Lyapunov exponent spectra and bifurcation diagrams of the circuit imply that it can produce two bifurcation behaviors by adjusting its parameters, which are Hopf bifurcation and anti-period doubling bifurcation. The hyperchaos, transient chaos and intermittency cycle phenomena are found in the same system. The dynamical behavior of this circuit is dependent on the initial state of memristor, showing different orbits such as chaotic oscillation, periodic oscillation and stable sink under different initial states. Finally, the simulation results indicate that some strange attractors like lotus type and superposition type are observed when voltage and electricity signal in observing chaotic attractors are generalized to power and energy signal, respectively. And the attractor production between the energy signals of the memristors are studied. Specially, when different initial conditions of three memristors are used to simulate the circuit, we can find the coexistence phenomenon of chaotic attractors with different topological structures or quasi-periodic limit cycle and chaotic attractor.
The six-order chaotic oscillating circuit is mainly composed of three parts:the parallel connection between a flux-controlled memristor and capacitor, the serial connection between a charge-controlled memristor and inductor, and another flux-controlled memristor that is alone and floating, which enriches the application of memristor in high-order chaotic circuit. Compared with most of other chaotic systems, it has many circuit parameters and very complex topological structure, which enhances the complexity of chaotic system and the randomness of the generated signal. It is more difficult to decipher the encrypted information in chaotic secure communication, and thus it has better security performance and safety performance.
2017, 66 (6): 067701.
doi: 10.7498/aps.66.067701
Abstract +
Polypropylene (PP) is widely used as capacitor films due to its better dielectric, mechanical, and thermal performance. In order to reduce the cost and size of capacitor, high energy density for PP dielectric is pursued. Since energy density is in quadratic proportion to direct current (dc) breakdown strength for linear dielectric, the enhancement of dc breakdown strength for PP dielectric is a primary choice to improve the energy density. Considering that the incorporation of nano-Al2O3 is an effective method to improve the dc breakdown strength for polymer, it is required to study the dc breakdown strength of PP/Al2O3 nanodielectric.
In order to explore the breakdown mechanism, PP/Al2O3 nanodielectrics with different nano-particle contents are prepared by melt blending, and the samples are prepared by hot pressing. Their microstructures are observed by scanning electron microscopic. Isothermal surface potential decay, bulk resistivity, and dc breakdown strength of the samples are also measured. The experimental results show that the energy and density of deep traps, bulk resistivity, and dc breakdown strength first increase and then decrease with the increase in nano-Al2O3 content. The maximum values are obtained at a filer content value of 0.5 wt%, where dc breakdown strength can be increased by about 27%. Based on interface model, the relation between microstructure and trap is investigated. In view of space charge breakdown theory, the mechanism of dc breakdown for PP/Al2O3 nanodielectric is explored by trap parameters. It is indicated that the interface can provide more deep traps in PP/Al2O3 nanodielectric, while the decrease in the energy and density of deep traps can be attributed to the overlap of interfaces in electrical double layer. The increase in the energy and density of deep traps makes more carriers trapped near the injecting contact, thus reducing the effective field for carrier injection due to the internal field generated by the trapped carriers. The reduction of carrier injection can moderate the distortion of field in PP dielectric, consequently, resulting in enhancing the dc breakdown strength.
2017, 66 (7): 070707.
doi: 10.7498/aps.66.070707
Abstract +
Phase-sensitive optical time domain reflectometry (-OTDR) has the advantages of fast response and high sensitivity. Therefore, it can realize fully distributed monitoring of weak vibrations along an optical fiber, which is of great value in many applications such as perimeter security and structural health monitoring. However, the optical background noise in the -OTDR will disturb the extraction of effective signals and limit the performance of this system. The optical background noise mainly includes the laser center frequency drift, the polarization-relevance noise and the distortion measurement due to the nonlinear relationship between optical fiber strain and interference intensity. In this paper, the generating mechanism of these optical background noise was analyzed and the corresponding noise suppression methods were proposed. The experiment results showed that the proposed methods could suppress the optical background noise effectively and improve the sensing performance significantly.
2017, 66 (23): 238801.
doi: 10.7498/aps.66.238801
Abstract +
It is very important to accurately model Li-ion battery and estimate the corresponding parameters that can be used for battery management system (BMS) of electric vehicles (EVs). However, the rigorous pseudo-two-dimensional (P2D) model of Li-ion battery is too complicated to be adopted directly to online state estimation and real-time control of stage-of-charge in BMS applications. To solve this problem, in this study we present a simplified pseudo-two-dimensional (SP2D) model by the electrolyte dynamic behaviors of electrochemical battery model, which is based on the porous electrode theory and concentration theory. First, the classical concentration equations of Li-ion battery P2D model are investigated and introduced, based on which, the approximated method of describing the concentration distributions of Li-ion battery described by the SP2D model is given by ignoring the variation of Li-ion wall flux density across the electrode thickness; then, the Li-ion battery terminal output voltage, the solid phase concentration and potential diffusion, the electrolyte concentration and potential distribution can be calculated based on the averaged electrochemical dynamic behaviors of Li-ion battery. Moreover, by employing some concentration assumptions:1) the solid-phase lithium concentration in each electrode is constant in spatial coordinate x, and uniform in time; 2) the exchange current density can be approximated by its averaged value; 3) the total amount of lithium in the electrolyte and in the solid phase is conserved; with the averaged dynamics of SP2D model, the simplified calculation expression for Li-ion battery terminal voltage is derived. Finally, a case study of Sony NMC 18650 Li-ion battery is conducted, and the simulated comparisons among the battery voltages at different-C-rate galvanostatic discharges, and the related electrolyte concentration of Li-ion at 1 C-rate are conducted. Moreover, the proposed SP2D model is used to predict the battery voltage and electrolyte concentration distribution with respect to the P2D model under hybrid pulse power characterization condition and urban dynamometer driving schedule condition, and the corresponding test data are used to verify the accuracy of the SP2D model. It is observed that the simulated data of SP2D model are in good accord with those of the P2D model and test curve under these two operation conditions, which further validates the effectiveness of the proposed electrochemical model of Li-ion battery. Accordingly, the proposed SP2D model in this paper can be used to estimate real-time state information in advanced battery management system applications, and can improve the calculation efficiency significantly and still hold higher accuracy simultaneously than that from the P2D model.
2017, 66 (14): 144101.
doi: 10.7498/aps.66.144101
Abstract +
As a fundamental property of waves, diffraction plays an important role in many physical problems. However, diffraction makes waves in free space unable to be focused into an arbitrarily small space, setting a fundamental limit (the so-called diffraction limit) to applications such as imaging, lithography, optical recording and waveguiding, etc. Although the diffraction effect can be suppressed by increasing the refractive index of the surrounding medium in which the electromagnetic and optical waves propagate, such a technology is restricted by the fact that natural medium has a limited refractive index. In the past decades, surface plasmon polaritons (SPPs) have received special attention, owing to its ability to break through the diffraction limit by shrinking the effective wavelength in the form of collective excitation of free electrons. By combining the short wavelength property of SPPs and subwavelength structure in the two-dimensional space, many exotic optical effects, such as extraordinary light transmission and optical spin Hall effect have been discovered and utilized to realize functionalities that control the electromagnetic characteristics (amplitudes, phases, and polarizations etc.) on demand. Based on SPPs and artificial subwavelength structures, a new discipline called subwavelength electromagnetics emerged in recent years, thus opening a door for the next-generation integrated and miniaturized electromagnetic and optical devices and systems.
In this paper, we review the theories and methods used to break through the diffraction limit by briefly introducing the history from the viewpoint of electromagnetic optics. It is shown that by constructing plasmonic metamaterials and metasurfaces on a subwavelength scale, one can realize the localized phase modulation and broadband dispersion engineering, which could surpass many limits of traditional theory and lay the basis of high-performance electromagnetic and optical functional devices. For instance, by constructing gradient phase on the metasurfaces, the traditional laws of reflection and refraction can be rewritten, while the electromagnetic and geometric shapes could be decoupled, both of which are essential for realizing the planar and conformal lenses and other functional devices. At the end of this paper, we discuss the future development trends of subwavelength electromagnetics. Based on the fact that different concepts, such as plasmonics, metamaterials and photonic crystals, are closely related to each other on a subwavelength scale, we think, the future advancements and even revolutions in subwavelength electromagnetics may rise from the in-depth intersection of physical, chemical and even biological areas. Additionally, we envision that the material genome initiative can be borrowed to promote the information exchange between different engineering and scientific teams and to enable the fast designing and implementing of subwavelength structured materials.
High sensitive scheme for methane remote sensor based on tunable diode laser absorption spectroscopy
2017, 66 (10): 100702.
doi: 10.7498/aps.66.100702
Abstract +
Methane is an important raw material for various petrochemicals in industrial fields and as also a clean fuel in daily life. However, as an inflammable and explosive material, methane leak can lead to disastrous consequences such as fire and explosion. Furthermore, as a kind of greenhouse gas, methane has stronger influence on global warming than carbon dioxide. In this paper, we present a new high sensitive scheme for methane remote sensing, which can facilitate detection and location of methane leakage. And the 2v3 band (near 1653.7 nm) of methane is chosen as the target transition which is free from the absorption of the other molecule in atmosphere. A tunable distributed-feedback diode laser is adapted to scan across the target transition. A Fresnel lens with a diameter of 150 mm is employed to collect the ambient backscattering light from natural features such as the buildings. The first harmonic signal is used to normalize the second harmonic signal to remove the influence introduced by the unknown reflectance factor of the actual target, therefore no retro-reflector is needed. Traditional tunable diode laser absorption spectroscopy (TDLAS) method has difficulty in locating the second harmonic signal peak position in low concentration conditions because of low signal-noise-ratio (SNR). To improve the SNR especially in low concentration environment, a scheme named baseline-offset TDLAS is presented in the paper, in which a reference cell filled with standard methane sample is inserted into the measuring optical path. The reference cell can also be used to calibrate the sensor. Furthermore, the reference cell can be used to lock the central frequency of the diode laser to the absorption peak position to monitor concentration fluctuation continuously. In the peak-locking mode, the sensor demodulates the third harmonic signal as error signal to control the injection current of the laser source with PID control. Moreover, one advantage of peak-locking mode is that the measurement frequency is about two orders of magnitude higher than the traditional TDLAS method. With baseline-offset TDLAS, the remote sensor described in this paper obtains SNRs as high as 19 and 16 at a stand-off distance of 10 m and 20 m, respectively. With such a high SNR, there is no necessity for complex algorithm in absorption peak position location. By defining the standard deviation of the measuring concentration as the detection limit, experimental results show that the proposed methane remote sensor has detection limits of 5 ppm m at a distance of 10 m and 16 ppmm for 20 m, respectively, while measuring the ambient methane. In peak-locked mode, the experimental system has a detection limit of 22 ppmm at a distance up to 37 m and can monitor rapid concentration fluctuation in.
2017, 66 (10): 107501.
doi: 10.7498/aps.66.107501
Abstract +
Plastic deformation is one of the most important features that affect the hysteresis magnetic properties of steels, because it changes the dislocation density and affects domain-wall movement and pinning. In order to model the effect of plastic deformation on the magnetic properties, the prevailing Jiles-Atherton (J-A) theory is extensively used. However, the J-A models in a series of papers published by Jiles et al. are not completely consistent. As a result, there exists no uniform formula of magneto-plastic model established by different researchers, based on different J-A models, and various versions given by different mathematic expressions of magneto-plastic model often create difficulty in discriminating the accuracies and effectivenesses of the analyzed results. Therefore, it is necessary to establish an accurate and reasonable magneto-plastic model. In this paper, on the basis of magnetization mechanism of ferrimagnet and plastic deformation model, the effects of plastic deformation on the magnetic characteristic parameters adopted in magneto-plastic model, such as dislocation density, pinning coefficient and scaling constant, are analyzed and the relationship between them is first established. Then, by contrasting the fitting formula of the anhysteretic magnetization curve, the energy conservation equation and the effective magnetic field equation established by different researchers, several queries are proposed, and the irrationality and inaccuracy of the existing magneto-plastic model are elucidated, such as the mixing of anhysteresis magnetization and magnetization, the unreasonably regarding the irreversible magnetization energy as actual total magnetization energy. Thus, the energy conservation equation, the effective magnetic field equation and the anhysteretic magnetization equation are modified, and the differential expression of the magneto-plastic model is re-derived finally. Comparing the results calculated by the existing magneto-plastic models with the experimental results, it is seen indeed that a more sharp change of magnetization appears at small plastic deformation, then, the values of magnetization decrease more slowly with the increase of plastic deformation than those from the models respectively proposed by Li Jian-Wei, Leng Jian-Cheng and Wang Zheng-Dao; the saturation magnetization and residual magnetization decrease with the increase of plastic deformation, the coercive force is increased oppositely and the trend to reach the saturation magnetization becomes gentler, which is more exactly consonant with experiment observation than that calculated by the Sablik's model; additionally, the hysteresis loops of the plastically deformed carbon-steel samples calculated by the modified magneto-plastic model are also in better agreement with the experimental results than those from the existing models. Consequently, the modification is effective, and the modified magneto-plastic model is more accurate to simulate the plastic deformation effect on the magnetic property of ferromagnetic material.
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