This paper deals with the preblem of existence and uniqueness of the stationary distributions (abbr., s. d.'s) for the processes constructed in [4] .The main results are stated in § 1. For the reader's co...This paper deals with the preblem of existence and uniqueness of the stationary distributions (abbr., s. d.'s) for the processes constructed in [4] .The main results are stated in § 1. For the reader's convenience we first restate the existence theorems (Theorem 1 and 2) of the processes given in [4]. Then two existence theorems (Theorem 3 and 4) and a uniqueness theorem (Theorem 5) for the s. d.'s of the processes are presented. The last result (Theorem 6), as an application of the previous ones, is about the Schlgl model which comes from nonequilibrium statisticali physics. The details of the proofs of Theorem 3—6 are given in § 2—4.展开更多
Numerical simulation is employed to investigate the initial state of avalanche in polydisperse particle systems.Nucleation and propagation processes are illustrated for pentadisperse and triadisperse particle systems,...Numerical simulation is employed to investigate the initial state of avalanche in polydisperse particle systems.Nucleation and propagation processes are illustrated for pentadisperse and triadisperse particle systems,respectively.In these processes,particles involved in the avalanche grow slowly in the early stage and explosively in the later stage,which is clearly different from the continuous and steady growth trend in the monodisperse system.By examining the avalanche propagation,the number growth of particles involved in the avalanche and the slope of the number growth,the initial state can be divided into three stages:T1(nucleation stage),T2(propagation stage),T3(overall avalanche stage).We focus on the characteristics of the avalanche in the T2 stage,and find that propagation distances increase almost linearly in both axial and radial directions in polydisperse systems.We also consider the distribution characteristics of the average coordination number and average velocity for the moving particles.The results support that the polydisperse particle systems are more stable in the T2 stage.展开更多
It remains a great challenge to understand the hydrates involved in phenomena in practical oil and gas systems.The adhesion forces between hydrate particles,between hydrate particles and pipe walls,and between hydrate...It remains a great challenge to understand the hydrates involved in phenomena in practical oil and gas systems.The adhesion forces between hydrate particles,between hydrate particles and pipe walls,and between hydrate particles and reservoir particles are essential factors that control the behaviors of clathrate hydrates in different applications.In this review,we summarize the typical micro-force measurement apparatus and methods utilized to study hydrate particle systems.In addition,the adhesion test results,the related understandings,and the applied numerical calculation models are systematically discussed.展开更多
This paper reviews some of our recent works on phase behaviors of particulate systems with a soft-core interaction potential. The potential is purely repulsive and bounded, i.e., it is finite even when two particles c...This paper reviews some of our recent works on phase behaviors of particulate systems with a soft-core interaction potential. The potential is purely repulsive and bounded, i.e., it is finite even when two particles completely overlap. The one-sided linear spring (harmonic) potential is one of the representatives. This model system has been successively employed to study the jamming transition, i.e., the formation of rigid and disordered packings of hard particles, and establish the jamming physics. This is actually based on the "hard" aspect of the potential, because at low densities and when particle overlap is tiny the potential resembles the hard sphere limit. At high densities, the potential exhibits its "soft" aspect: with the increase of density, there are successive reentrant crystallizations with many types of solid phases. Taking advantage of the dual nature of the potential, we investigate the criticality of the jamming transition from different perspectives, extend the jamming scenario to high densities, reveal the novel density evolution of two-dimensional melting, and find unexpected formation of quasicrystals. It is surprising that such a simple potential can exhibit so rich and unexpected phenomena in phase transitions. The phase behaviors discussed in this paper are also highly regarded in polymer science, which may thus shed light on our understanding of polymeric systems or inspire new ideas in studies of polymers.展开更多
A physical-based particle system is employed for cloth modeling supported by two basic algorithms, between which one is the construction of the internal and external forces acting on the particle system in terms of KE...A physical-based particle system is employed for cloth modeling supported by two basic algorithms, between which one is the construction of the internal and external forces acting on the particle system in terms of KES-F bending and shearing tests, and the other is the collision algorithm of which the collision detection is carried by means of bi-section of time step and the collision response is handled according to the empirical law for frictionless collision With these algorithms. the geometric state of parcles can be expressed as ordinary differential equationswhich is numerically solved by fourth order Runge- Kutta integration. Different draping figures of cotton fabric and wool fabric prove that such a particle system is suitable for 3D cloth modeling and simulation.展开更多
Point-based surface has been widely used in computer graphics for modeling, animation, visualization, simulation of liq- uid and so on. Furthermore, particle-based approach can distribute the surface sampling points a...Point-based surface has been widely used in computer graphics for modeling, animation, visualization, simulation of liq- uid and so on. Furthermore, particle-based approach can distribute the surface sampling points and control its parameters according to the needs of the application. In this paper, we examine several kinds of algorithms presented over the last decades, with the main focus on particle sampling technologies for implicit surface. Therefore, we classify various algorithms into categories, describe main ideas behind each categories, and compare the advantages and shortcomings of the algorithms in each category.展开更多
Spouted bed is a type of fluidized bed that has been widely used in various industrial processes because of its excellent mass and heat transfer efficiency.In practical applications,the fluidization of the multicompon...Spouted bed is a type of fluidized bed that has been widely used in various industrial processes because of its excellent mass and heat transfer efficiency.In practical applications,the fluidization of the multicomponent particle system containing non-spherical particles is frequently encountered in spouted beds.To better understand the spouting behaviors of the multicomponent particle system,therefore,this study employs a CFD-DEM(Computational Fluid Dynamics-Discrete Element Method)coupling approach to investigate the spouting behaviors.Spherical particles along with two types of ellipsoidal particles(i.e.,oblate ellipsoid,and prolate ellipsoid)are included in this paper.Through the combination of these three particle types,seven distinct systems(three monodisperse systems,three binary mixtures,and one ternary mixture)are simulated to analyze the effects of particle shape and composition of particle systems on spouting behaviors.The simulation results reveal that introducing non-spherical particles into systems containing either spherical or oblate ellipsoidal particles tends to enhance spouting behaviors,whereas adding spherical particles to prolate ellipsoidal particle systems inclines to suppress it.The addition of non-spherical particles into the spherical particle system can enhance the particle interlocks,and using the oblate particles should have more important influence than prolate particles.Moreover,the influence of particle shape on the spout deflection behaviors is quite complicated,and the use of prolate ellipsoidal particles versus oblate ellipsoidal particles may produce opposite effects.These findings should provide valuable insights for optimizing spouted bed operations involving complex particle mixtures.展开更多
In recent years, particle swarm optimization (PSO) has received widespread attention in feature selection due to its simplicity and potential for global search. However, in traditional PSO, particles primarily update ...In recent years, particle swarm optimization (PSO) has received widespread attention in feature selection due to its simplicity and potential for global search. However, in traditional PSO, particles primarily update based on two extreme values: personal best and global best, which limits the diversity of information. Ideally, particles should learn from multiple advantageous particles to enhance interactivity and optimization efficiency. Accordingly, this paper proposes a PSO that simulates the evolutionary dynamics of species survival in mountain peak ecology (PEPSO) for feature selection. Based on the pyramid topology, the algorithm simulates the features of mountain peak ecology in nature and the competitive-cooperative strategies among species. According to the principles of the algorithm, the population is first adaptively divided into many subgroups based on the fitness level of particles. Then, particles within each subgroup are divided into three different types based on their evolutionary levels, employing different adaptive inertia weight rules and dynamic learning mechanisms to define distinct learning modes. Consequently, all particles play their respective roles in promoting the global optimization performance of the algorithm, similar to different species in the ecological pattern of mountain peaks. Experimental validation of the PEPSO performance was conducted on 18 public datasets. The experimental results demonstrate that the PEPSO outperforms other PSO variant-based feature selection methods and mainstream feature selection methods based on intelligent optimization algorithms in terms of overall performance in global search capability, classification accuracy, and reduction of feature space dimensions. Wilcoxon signed-rank test also confirms the excellent performance of the PEPSO.展开更多
Complex autonomous dynamical systems require sophisticated optimization methods that encompass environment awareness,path planning,and decision-making.swarm intelligence algorithms,inspired by natural phenomena such a...Complex autonomous dynamical systems require sophisticated optimization methods that encompass environment awareness,path planning,and decision-making.swarm intelligence algorithms,inspired by natural phenomena such as bird flocks and fish schools,have undergone significant advancements over recent decades.This paper provides a comprehensive review of particle swarm optimization(PSO)in the context of autonomous systems.We specifically examine the application of PSO to multi-agent dynamical systems,reviewing how PSO variants are employed to tackle diverse optimization challenges across various platforms,including ground vehicles,autonomous underwater vehicles,and unmanned aerial vehicles.Additionally,we delve into the use of PSO within swarm robotics and multi-agent systems.The paper concludes with an outline of potential future research directions,particularly focusing on the application of PSO to the multi-agent rendezvous problem in autonomous systems.展开更多
Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion...Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion algorithm took advantage of the fast optimization ability of PSO to optimize the population screening link of GA.The Simulink simulation results showed that the convergence of the fitness function of the fusion algorithm was accelerated,the system response adjustment time was reduced,and the overshoot was almost zero.Then the algorithm was applied to the steering test of agricultural robot in various scenes.After modeling the steering system of agricultural robot,the steering test results in the unloaded suspended state showed that the PID control based on fusion algorithm reduced the rise time,response adjustment time and overshoot of the system,and improved the response speed and stability of the system,compared with the artificial trial and error PID control and the PID control based on GA.The actual road steering test results showed that the PID control response rise time based on the fusion algorithm was the shortest,about 4.43 s.When the target pulse number was set to 100,the actual mean value in the steady-state regulation stage was about 102.9,which was the closest to the target value among the three control methods,and the overshoot was reduced at the same time.The steering test results under various scene states showed that the PID control based on the proposed fusion algorithm had good anti-interference ability,it can adapt to the changes of environment and load and improve the performance of the control system.It was effective in the steering control of agricultural robot.This method can provide a reference for the precise steering control of other robots.展开更多
This paper proposes an equivalent modeling method for photovoltaic(PV)power stations via a particle swarm optimization(PSO)K-means clustering(KMC)algorithm with passive filter parameter clustering to address the compl...This paper proposes an equivalent modeling method for photovoltaic(PV)power stations via a particle swarm optimization(PSO)K-means clustering(KMC)algorithm with passive filter parameter clustering to address the complexities,simulation time cost and convergence problems of detailed PV power station models.First,the amplitude–frequency curves of different filter parameters are analyzed.Based on the results,a grouping parameter set for characterizing the external filter characteristics is established.These parameters are further defined as clustering parameters.A single PV inverter model is then established as a prerequisite foundation.The proposed equivalent method combines the global search capability of PSO with the rapid convergence of KMC,effectively overcoming the tendency of KMC to become trapped in local optima.This approach enhances both clustering accuracy and numerical stability when determining equivalence for PV inverter units.Using the proposed clustering method,both a detailed PV power station model and an equivalent model are developed and compared.Simulation and hardwarein-loop(HIL)results based on the equivalent model verify that the equivalent method accurately represents the dynamic characteristics of PVpower stations and adapts well to different operating conditions.The proposed equivalent modeling method provides an effective analysis tool for future renewable energy integration research.展开更多
Multi-label feature selection(MFS)is a crucial dimensionality reduction technique aimed at identifying informative features associated with multiple labels.However,traditional centralized methods face significant chal...Multi-label feature selection(MFS)is a crucial dimensionality reduction technique aimed at identifying informative features associated with multiple labels.However,traditional centralized methods face significant challenges in privacy-sensitive and distributed settings,often neglecting label dependencies and suffering from low computational efficiency.To address these issues,we introduce a novel framework,Fed-MFSDHBCPSO—federated MFS via dual-layer hybrid breeding cooperative particle swarm optimization algorithm with manifold and sparsity regularization(DHBCPSO-MSR).Leveraging the federated learning paradigm,Fed-MFSDHBCPSO allows clients to perform local feature selection(FS)using DHBCPSO-MSR.Locally selected feature subsets are encrypted with differential privacy(DP)and transmitted to a central server,where they are securely aggregated and refined through secure multi-party computation(SMPC)until global convergence is achieved.Within each client,DHBCPSO-MSR employs a dual-layer FS strategy.The inner layer constructs sample and label similarity graphs,generates Laplacian matrices to capture the manifold structure between samples and labels,and applies L2,1-norm regularization to sparsify the feature subset,yielding an optimized feature weight matrix.The outer layer uses a hybrid breeding cooperative particle swarm optimization algorithm to further refine the feature weight matrix and identify the optimal feature subset.The updated weight matrix is then fed back to the inner layer for further optimization.Comprehensive experiments on multiple real-world multi-label datasets demonstrate that Fed-MFSDHBCPSO consistently outperforms both centralized and federated baseline methods across several key evaluation metrics.展开更多
During electrochemical machining(ECM),the passivation film formed on the surface of titanium alloy can lead to uneven dissolution and pitting.Solid particle erosion can effectively remove this passivation film.In this...During electrochemical machining(ECM),the passivation film formed on the surface of titanium alloy can lead to uneven dissolution and pitting.Solid particle erosion can effectively remove this passivation film.In this paper,the electrochemical dissolution behavior of Ti-6.5Al-2Zr-1Mo-1V(TA15)titanium alloy at without particle impact,low(15°)and high(90°)angle particle impact was investigated,and the influence of Al_(2)O_(3)particles on ECM was systematically expounded.It was found that under the condition of no particle erosion,the surface of electrochemically processed titanium alloy had serious pitting corrosion due to the influence of the passivation film,and the surface roughness(Sa)of the local area reached 10.088μm.Under the condition of a high-impact angle(90°),due to the existence of strain hardening and particle embedding,only the edge of the surface is dissolved,while the central area is almost insoluble,with the surface roughness(S_(a))reaching 16.086μm.On the contrary,under the condition of a low-impact angle(15°),the machining efficiency and surface quality of the material were significantly improved due to the ploughing effect and galvanic corrosion,and the surface roughness(S_(a))reached 2.823μm.Based on these findings,the electrochemical dissolution model of TA15 titanium alloy under different particle erosion conditions was established.展开更多
In this study,a fifth-degree cubature particle filter(5CPF)is proposed to address the limited estimation accuracy in traditional particle filter algorithms for bearings-only tracking(BOT).This algorithm calculates the...In this study,a fifth-degree cubature particle filter(5CPF)is proposed to address the limited estimation accuracy in traditional particle filter algorithms for bearings-only tracking(BOT).This algorithm calculates the recommended density function by introducing a fifth-degree cubature Kalman filter algorithm to guide particle sampling,which effectively alleviates the problem of particle degradation and significantly improves the estimation accuracy of the filter.However,the 5CPF algorithm exhibits high computational complexity,particularly in scenarios with a large number of particles.Therefore,we propose the extended Kalman filter(EKF)-5CPF algorithm,which employs an EKF to replace the time update step for each particle in the 5CPF.This enhances the algorithm’s real-time capability while maintaining the high precision advantage of the 5CPF algorithm.In addition,we construct bearing-only dual-station and single-motion station target tracking systems,and the filtering performances of 5CPF and EKF-5CPF algorithms under different conditions are analyzed.The results show that both the 5CPF algorithm and EKF-5CPF have strong robustness and can adapt to different noise environments.Furthermore,both algorithms significantly outperform traditional nonlinear filtering algorithms in terms of convergence speed,tracking accuracy,and overall stability.展开更多
Imidazole(IM)particles in the atmosphere affect climate,atmospheric chemical reactions,and human health.However,research on IM particles in the Sichuan Basin(SCB),one of the areas of China affected most heavily by haz...Imidazole(IM)particles in the atmosphere affect climate,atmospheric chemical reactions,and human health.However,research on IM particles in the Sichuan Basin(SCB),one of the areas of China affected most heavily by haze,remains very scarce.This study used single-particle aerosol mass spectrometry to investigate IM-containing particles in Chengdu,one of the megacities in the SCB,during summer and winter before and after implemen-tation of the Three-year Action Plan to Win the Blue-Sky Defense War(BSDW).We found that IM-containing particles accounted for 1.2%–12.0%of all detected particles,and they highly mixed with carbonaceous com-ponents,secondary inorganic species,and organic nitrogen.From before to after the BSDW,the proportion of IM-containing particles decreased by 1.8%in summer,but increased by 9.6%in winter.Ammonium/amines and carbonyl compounds were closely related to IM-containing particles;the highest proportion of IM-containing particles occurred in particles mixed with amines and carbonyls.The number fraction of IM-containing particles in all seasons was higher at night than during daytime.The potential source areas of IM-containing particles showed notable narrowing after the BSDW,and the high-value areas were found distributed closer to Chengdu and its surrounding areas.In the winter before the BSDW,most IM-containing particles(>70%)were mixed with organic carbon(OC)particles,and the contributions of OC and mixed organic–elemental carbon(OC-EC)particles increased with aggravation of pollution,whereas OC-EC and Metal particles played a more crucial role in the winter after the BSDW.展开更多
Al2O3p-Al composites were synthesized using an in-situ reaction in the 80%Al-20%CuO （mass fraction） system. The effects of the CuO particle size on the synthesis temperature and microstructure of the composites were...Al2O3p-Al composites were synthesized using an in-situ reaction in the 80%Al-20%CuO （mass fraction） system. The effects of the CuO particle size on the synthesis temperature and microstructure of the composites were investigated by various methods. The results indicate that the CuO particle size has a significant effect on the temperature at which the complete reaction in the Al-CuO system occurs：the temperature is 200 ℃ lower in the Al-CuO system containing CuO particles with sizes less than 6μm than that containing CuO particles with sizes less than 100μm. The interfacial bonding between Al2O3 particles and Al is not complete when the temperature is below a critical value. The morphology of the Al2O3 particles varies from ribbon-like shape to near spherical shape when the temperature is above a critical value. These two critical temperatures are affected by the particle size of CuO, and the critical temperature of the sample containing CuO particles with sizes less than 6μm is 100 ℃ lower than that of the sample containing CuO particles with sizes less than 100μm.展开更多
Application of particle image velocity (PIV) techniques for measuringparticle size distribution and total number in an activation chamber of desulfurization system isintroduced. Watersheld algorithm is used to choose ...Application of particle image velocity (PIV) techniques for measuringparticle size distribution and total number in an activation chamber of desulfurization system isintroduced. Watersheld algorithm is used to choose the suitable initial gray level threshold whichis used to change the gray level images taken by PIV to black and white ones, then every particle inan image is isolated totally. For every isolating particle, its contour is tracked by the edgeenhancement filter function and kept by Freeman s chain code. Based on a set of particle s chincode, its size and size distribution are calculated and sorted. Finally, the experimental data ofcalcium particles and water drops, separately injected into the activation chamber, and the erroranalysis of data are given out.展开更多
A parallel algorithm suitable for simulating multi-sized particle systems and multi-phase fluid systems is proposed based on macro-scale pseudo-particle modeling(MaPPM).The algorithm employs space-decomposition of the...A parallel algorithm suitable for simulating multi-sized particle systems and multi-phase fluid systems is proposed based on macro-scale pseudo-particle modeling(MaPPM).The algorithm employs space-decomposition of the computational load among the processing ele-ments(PEs)and multi-level cell-subdivision technique for particle indexing.In this algorithm,a 2D gas-solid system is simulated with the temporal variations of drags on solids,inter-phase slip velocities and solids concentration elaborately monitored.Analysis of the results shows that the algorithm is of good parallel efficiency and scalability,demonstrating the unique advantage of MaPPM in simulating complex flows.展开更多
Lithium ion batteries are complicated distributed parameter systems that can be described preferably by partial differential equations and a field theory. To reduce the solution difficulty and the calculation amount, ...Lithium ion batteries are complicated distributed parameter systems that can be described preferably by partial differential equations and a field theory. To reduce the solution difficulty and the calculation amount, if a distributed parameter system is described by ordinary differential equations （ODE） during the analysis and the design of distributed parameter system, the reliability of the system description will be reduced, and the systemic errors will be introduced. Studies on working condition real-time monitoring can improve the security because the rechargeable LIBs are widely used in many electronic systems and electromechanical equipment. Single particle model （SPM） is the simplification of LIB under some approximations, and can estimate the working parameters of a LIB at the faster simulation speed. A LIB modelling algorithm based on PDEs and SPM is proposed to monitor the working condition of LIBs in real time. Although the lithium ion concentration is an unmeasurable distributed parameter in the anode of LIB, the working condition monitoring model can track the real time lithium ion concentration in the anode of LIB, and calculate the residual which is the difference between the ideal data and the measured data. A fault alarm can be triggered when the residual is beyond the preset threshold. A simulation example verifies that the effectiveness and the accuracy of the working condition real-time monitoring model of LIB based on PDEs and SPM.展开更多
We study the scaling limit for a catalytic branching particle system whose particles perform random walks on Z and can branch at 0 only. Varying the initial （finite） number of particles, we get for this system diffe...We study the scaling limit for a catalytic branching particle system whose particles perform random walks on Z and can branch at 0 only. Varying the initial （finite） number of particles, we get for this system different limiting distributions. To be more specific, suppose that initially there are n^β particles and consider the scaled process Zt^n（·） = Znt（√n·）, where Zt is the measure-valued process 1 and to a representing the original particle system. We prove that Ztn converges to 0 when β 〈1/4 and to a nondegenerate discrete distribution when β=1/4.In addition,if 1/4〈β〈1/2 then n-^（2β-1/2）Zt^n converges to a random limit,while if β 〉21then n^-βZtn converges to a deterministic limit.展开更多
文摘This paper deals with the preblem of existence and uniqueness of the stationary distributions (abbr., s. d.'s) for the processes constructed in [4] .The main results are stated in § 1. For the reader's convenience we first restate the existence theorems (Theorem 1 and 2) of the processes given in [4]. Then two existence theorems (Theorem 3 and 4) and a uniqueness theorem (Theorem 5) for the s. d.'s of the processes are presented. The last result (Theorem 6), as an application of the previous ones, is about the Schlgl model which comes from nonequilibrium statisticali physics. The details of the proofs of Theorem 3—6 are given in § 2—4.
基金Project supported by the Qingdao National Laboratory for Marine Science and Technology(Grant No.2015ASKJ01)the National Natural Science Foundation of China(Grant Nos.11972212,12072200,and 12002213).
文摘Numerical simulation is employed to investigate the initial state of avalanche in polydisperse particle systems.Nucleation and propagation processes are illustrated for pentadisperse and triadisperse particle systems,respectively.In these processes,particles involved in the avalanche grow slowly in the early stage and explosively in the later stage,which is clearly different from the continuous and steady growth trend in the monodisperse system.By examining the avalanche propagation,the number growth of particles involved in the avalanche and the slope of the number growth,the initial state can be divided into three stages:T1(nucleation stage),T2(propagation stage),T3(overall avalanche stage).We focus on the characteristics of the avalanche in the T2 stage,and find that propagation distances increase almost linearly in both axial and radial directions in polydisperse systems.We also consider the distribution characteristics of the average coordination number and average velocity for the moving particles.The results support that the polydisperse particle systems are more stable in the T2 stage.
基金supported by the National Key Research and Development Project (No.2018YFE0126400)Key Program of Marine Economy Development (Six Marine Industries)Special Foundation of Department of Natural Resources of Guangdong Province (GDNRC[2020]047)。
文摘It remains a great challenge to understand the hydrates involved in phenomena in practical oil and gas systems.The adhesion forces between hydrate particles,between hydrate particles and pipe walls,and between hydrate particles and reservoir particles are essential factors that control the behaviors of clathrate hydrates in different applications.In this review,we summarize the typical micro-force measurement apparatus and methods utilized to study hydrate particle systems.In addition,the adhesion test results,the related understandings,and the applied numerical calculation models are systematically discussed.
基金the support from the National Natural Science Foundation of China (Nos. 11734014, 11574278, 21325418, 11074228, and 91027001)the National Basic Research Program of China (973 Program) (No. 2012CB821500)+1 种基金CAS 100Talent Program (No. 2030020004)Fundamental Research Funds for the Central Universities (Nos. 2340000034 and 2030020028)
文摘This paper reviews some of our recent works on phase behaviors of particulate systems with a soft-core interaction potential. The potential is purely repulsive and bounded, i.e., it is finite even when two particles completely overlap. The one-sided linear spring (harmonic) potential is one of the representatives. This model system has been successively employed to study the jamming transition, i.e., the formation of rigid and disordered packings of hard particles, and establish the jamming physics. This is actually based on the "hard" aspect of the potential, because at low densities and when particle overlap is tiny the potential resembles the hard sphere limit. At high densities, the potential exhibits its "soft" aspect: with the increase of density, there are successive reentrant crystallizations with many types of solid phases. Taking advantage of the dual nature of the potential, we investigate the criticality of the jamming transition from different perspectives, extend the jamming scenario to high densities, reveal the novel density evolution of two-dimensional melting, and find unexpected formation of quasicrystals. It is surprising that such a simple potential can exhibit so rich and unexpected phenomena in phase transitions. The phase behaviors discussed in this paper are also highly regarded in polymer science, which may thus shed light on our understanding of polymeric systems or inspire new ideas in studies of polymers.
文摘A physical-based particle system is employed for cloth modeling supported by two basic algorithms, between which one is the construction of the internal and external forces acting on the particle system in terms of KES-F bending and shearing tests, and the other is the collision algorithm of which the collision detection is carried by means of bi-section of time step and the collision response is handled according to the empirical law for frictionless collision With these algorithms. the geometric state of parcles can be expressed as ordinary differential equationswhich is numerically solved by fourth order Runge- Kutta integration. Different draping figures of cotton fabric and wool fabric prove that such a particle system is suitable for 3D cloth modeling and simulation.
基金supported by the National Nature Science Foundation of China (61020106001,60903109,61103150)National Research Foundation for the Doctoral Program of Higher Education of China (20110131130004)
文摘Point-based surface has been widely used in computer graphics for modeling, animation, visualization, simulation of liq- uid and so on. Furthermore, particle-based approach can distribute the surface sampling points and control its parameters according to the needs of the application. In this paper, we examine several kinds of algorithms presented over the last decades, with the main focus on particle sampling technologies for implicit surface. Therefore, we classify various algorithms into categories, describe main ideas behind each categories, and compare the advantages and shortcomings of the algorithms in each category.
基金the National Natural Science Foundation of China(grant No.52264042)Jiangxi Provincial Natural Science Foundation(grant Nos.20242BAB23034,20242BAB20162,20223AAG01009,and 20214BBG74005)Taishan Scholars Program(grant No.tsqn202408001)for financial supports to this work。
文摘Spouted bed is a type of fluidized bed that has been widely used in various industrial processes because of its excellent mass and heat transfer efficiency.In practical applications,the fluidization of the multicomponent particle system containing non-spherical particles is frequently encountered in spouted beds.To better understand the spouting behaviors of the multicomponent particle system,therefore,this study employs a CFD-DEM(Computational Fluid Dynamics-Discrete Element Method)coupling approach to investigate the spouting behaviors.Spherical particles along with two types of ellipsoidal particles(i.e.,oblate ellipsoid,and prolate ellipsoid)are included in this paper.Through the combination of these three particle types,seven distinct systems(three monodisperse systems,three binary mixtures,and one ternary mixture)are simulated to analyze the effects of particle shape and composition of particle systems on spouting behaviors.The simulation results reveal that introducing non-spherical particles into systems containing either spherical or oblate ellipsoidal particles tends to enhance spouting behaviors,whereas adding spherical particles to prolate ellipsoidal particle systems inclines to suppress it.The addition of non-spherical particles into the spherical particle system can enhance the particle interlocks,and using the oblate particles should have more important influence than prolate particles.Moreover,the influence of particle shape on the spout deflection behaviors is quite complicated,and the use of prolate ellipsoidal particles versus oblate ellipsoidal particles may produce opposite effects.These findings should provide valuable insights for optimizing spouted bed operations involving complex particle mixtures.
文摘In recent years, particle swarm optimization (PSO) has received widespread attention in feature selection due to its simplicity and potential for global search. However, in traditional PSO, particles primarily update based on two extreme values: personal best and global best, which limits the diversity of information. Ideally, particles should learn from multiple advantageous particles to enhance interactivity and optimization efficiency. Accordingly, this paper proposes a PSO that simulates the evolutionary dynamics of species survival in mountain peak ecology (PEPSO) for feature selection. Based on the pyramid topology, the algorithm simulates the features of mountain peak ecology in nature and the competitive-cooperative strategies among species. According to the principles of the algorithm, the population is first adaptively divided into many subgroups based on the fitness level of particles. Then, particles within each subgroup are divided into three different types based on their evolutionary levels, employing different adaptive inertia weight rules and dynamic learning mechanisms to define distinct learning modes. Consequently, all particles play their respective roles in promoting the global optimization performance of the algorithm, similar to different species in the ecological pattern of mountain peaks. Experimental validation of the PEPSO performance was conducted on 18 public datasets. The experimental results demonstrate that the PEPSO outperforms other PSO variant-based feature selection methods and mainstream feature selection methods based on intelligent optimization algorithms in terms of overall performance in global search capability, classification accuracy, and reduction of feature space dimensions. Wilcoxon signed-rank test also confirms the excellent performance of the PEPSO.
基金supported in part by the NASA South Carolina Space Grant Consortium(5121383-UG-SC-006).Recommended by Associate Editor Xin Luo.
文摘Complex autonomous dynamical systems require sophisticated optimization methods that encompass environment awareness,path planning,and decision-making.swarm intelligence algorithms,inspired by natural phenomena such as bird flocks and fish schools,have undergone significant advancements over recent decades.This paper provides a comprehensive review of particle swarm optimization(PSO)in the context of autonomous systems.We specifically examine the application of PSO to multi-agent dynamical systems,reviewing how PSO variants are employed to tackle diverse optimization challenges across various platforms,including ground vehicles,autonomous underwater vehicles,and unmanned aerial vehicles.Additionally,we delve into the use of PSO within swarm robotics and multi-agent systems.The paper concludes with an outline of potential future research directions,particularly focusing on the application of PSO to the multi-agent rendezvous problem in autonomous systems.
文摘Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion algorithm took advantage of the fast optimization ability of PSO to optimize the population screening link of GA.The Simulink simulation results showed that the convergence of the fitness function of the fusion algorithm was accelerated,the system response adjustment time was reduced,and the overshoot was almost zero.Then the algorithm was applied to the steering test of agricultural robot in various scenes.After modeling the steering system of agricultural robot,the steering test results in the unloaded suspended state showed that the PID control based on fusion algorithm reduced the rise time,response adjustment time and overshoot of the system,and improved the response speed and stability of the system,compared with the artificial trial and error PID control and the PID control based on GA.The actual road steering test results showed that the PID control response rise time based on the fusion algorithm was the shortest,about 4.43 s.When the target pulse number was set to 100,the actual mean value in the steady-state regulation stage was about 102.9,which was the closest to the target value among the three control methods,and the overshoot was reduced at the same time.The steering test results under various scene states showed that the PID control based on the proposed fusion algorithm had good anti-interference ability,it can adapt to the changes of environment and load and improve the performance of the control system.It was effective in the steering control of agricultural robot.This method can provide a reference for the precise steering control of other robots.
基金supported by the Research Project of China Southern Power Grid(No.056200KK52222031).
文摘This paper proposes an equivalent modeling method for photovoltaic(PV)power stations via a particle swarm optimization(PSO)K-means clustering(KMC)algorithm with passive filter parameter clustering to address the complexities,simulation time cost and convergence problems of detailed PV power station models.First,the amplitude–frequency curves of different filter parameters are analyzed.Based on the results,a grouping parameter set for characterizing the external filter characteristics is established.These parameters are further defined as clustering parameters.A single PV inverter model is then established as a prerequisite foundation.The proposed equivalent method combines the global search capability of PSO with the rapid convergence of KMC,effectively overcoming the tendency of KMC to become trapped in local optima.This approach enhances both clustering accuracy and numerical stability when determining equivalence for PV inverter units.Using the proposed clustering method,both a detailed PV power station model and an equivalent model are developed and compared.Simulation and hardwarein-loop(HIL)results based on the equivalent model verify that the equivalent method accurately represents the dynamic characteristics of PVpower stations and adapts well to different operating conditions.The proposed equivalent modeling method provides an effective analysis tool for future renewable energy integration research.
文摘Multi-label feature selection(MFS)is a crucial dimensionality reduction technique aimed at identifying informative features associated with multiple labels.However,traditional centralized methods face significant challenges in privacy-sensitive and distributed settings,often neglecting label dependencies and suffering from low computational efficiency.To address these issues,we introduce a novel framework,Fed-MFSDHBCPSO—federated MFS via dual-layer hybrid breeding cooperative particle swarm optimization algorithm with manifold and sparsity regularization(DHBCPSO-MSR).Leveraging the federated learning paradigm,Fed-MFSDHBCPSO allows clients to perform local feature selection(FS)using DHBCPSO-MSR.Locally selected feature subsets are encrypted with differential privacy(DP)and transmitted to a central server,where they are securely aggregated and refined through secure multi-party computation(SMPC)until global convergence is achieved.Within each client,DHBCPSO-MSR employs a dual-layer FS strategy.The inner layer constructs sample and label similarity graphs,generates Laplacian matrices to capture the manifold structure between samples and labels,and applies L2,1-norm regularization to sparsify the feature subset,yielding an optimized feature weight matrix.The outer layer uses a hybrid breeding cooperative particle swarm optimization algorithm to further refine the feature weight matrix and identify the optimal feature subset.The updated weight matrix is then fed back to the inner layer for further optimization.Comprehensive experiments on multiple real-world multi-label datasets demonstrate that Fed-MFSDHBCPSO consistently outperforms both centralized and federated baseline methods across several key evaluation metrics.
基金supported by the National Natural Science Foundation of China(No.52175414)the Natural Science Foundation of Jiangsu Province of China(No.BK20220134)+1 种基金the Fundamental Research Funds for the Central Universities,China(No.NE2023002)the Postgraduate Research&Practice Innovation Program of Jiangsu Province,China(No.KYCX24_0559)。
文摘During electrochemical machining(ECM),the passivation film formed on the surface of titanium alloy can lead to uneven dissolution and pitting.Solid particle erosion can effectively remove this passivation film.In this paper,the electrochemical dissolution behavior of Ti-6.5Al-2Zr-1Mo-1V(TA15)titanium alloy at without particle impact,low(15°)and high(90°)angle particle impact was investigated,and the influence of Al_(2)O_(3)particles on ECM was systematically expounded.It was found that under the condition of no particle erosion,the surface of electrochemically processed titanium alloy had serious pitting corrosion due to the influence of the passivation film,and the surface roughness(Sa)of the local area reached 10.088μm.Under the condition of a high-impact angle(90°),due to the existence of strain hardening and particle embedding,only the edge of the surface is dissolved,while the central area is almost insoluble,with the surface roughness(S_(a))reaching 16.086μm.On the contrary,under the condition of a low-impact angle(15°),the machining efficiency and surface quality of the material were significantly improved due to the ploughing effect and galvanic corrosion,and the surface roughness(S_(a))reached 2.823μm.Based on these findings,the electrochemical dissolution model of TA15 titanium alloy under different particle erosion conditions was established.
基金Supported by the Guangxi Special Program for Technological Innovation Guidance(No.GuiKeAC25069006).
文摘In this study,a fifth-degree cubature particle filter(5CPF)is proposed to address the limited estimation accuracy in traditional particle filter algorithms for bearings-only tracking(BOT).This algorithm calculates the recommended density function by introducing a fifth-degree cubature Kalman filter algorithm to guide particle sampling,which effectively alleviates the problem of particle degradation and significantly improves the estimation accuracy of the filter.However,the 5CPF algorithm exhibits high computational complexity,particularly in scenarios with a large number of particles.Therefore,we propose the extended Kalman filter(EKF)-5CPF algorithm,which employs an EKF to replace the time update step for each particle in the 5CPF.This enhances the algorithm’s real-time capability while maintaining the high precision advantage of the 5CPF algorithm.In addition,we construct bearing-only dual-station and single-motion station target tracking systems,and the filtering performances of 5CPF and EKF-5CPF algorithms under different conditions are analyzed.The results show that both the 5CPF algorithm and EKF-5CPF have strong robustness and can adapt to different noise environments.Furthermore,both algorithms significantly outperform traditional nonlinear filtering algorithms in terms of convergence speed,tracking accuracy,and overall stability.
基金supported by Sichuan Science and Technology Program(No.2024NSFSC0060)the National Natural Science Foundation of China(No.U23A2030)the Basic Research Cultivation Support Plan of Southwest Jiaotong University(No.2682023ZTPY016).
文摘Imidazole(IM)particles in the atmosphere affect climate,atmospheric chemical reactions,and human health.However,research on IM particles in the Sichuan Basin(SCB),one of the areas of China affected most heavily by haze,remains very scarce.This study used single-particle aerosol mass spectrometry to investigate IM-containing particles in Chengdu,one of the megacities in the SCB,during summer and winter before and after implemen-tation of the Three-year Action Plan to Win the Blue-Sky Defense War(BSDW).We found that IM-containing particles accounted for 1.2%–12.0%of all detected particles,and they highly mixed with carbonaceous com-ponents,secondary inorganic species,and organic nitrogen.From before to after the BSDW,the proportion of IM-containing particles decreased by 1.8%in summer,but increased by 9.6%in winter.Ammonium/amines and carbonyl compounds were closely related to IM-containing particles;the highest proportion of IM-containing particles occurred in particles mixed with amines and carbonyls.The number fraction of IM-containing particles in all seasons was higher at night than during daytime.The potential source areas of IM-containing particles showed notable narrowing after the BSDW,and the high-value areas were found distributed closer to Chengdu and its surrounding areas.In the winter before the BSDW,most IM-containing particles(>70%)were mixed with organic carbon(OC)particles,and the contributions of OC and mixed organic–elemental carbon(OC-EC)particles increased with aggravation of pollution,whereas OC-EC and Metal particles played a more crucial role in the winter after the BSDW.
基金Project(2012MS0801)supported by the Natural Science Foundation of Inner Mongolia,China
文摘Al2O3p-Al composites were synthesized using an in-situ reaction in the 80%Al-20%CuO （mass fraction） system. The effects of the CuO particle size on the synthesis temperature and microstructure of the composites were investigated by various methods. The results indicate that the CuO particle size has a significant effect on the temperature at which the complete reaction in the Al-CuO system occurs：the temperature is 200 ℃ lower in the Al-CuO system containing CuO particles with sizes less than 6μm than that containing CuO particles with sizes less than 100μm. The interfacial bonding between Al2O3 particles and Al is not complete when the temperature is below a critical value. The morphology of the Al2O3 particles varies from ribbon-like shape to near spherical shape when the temperature is above a critical value. These two critical temperatures are affected by the particle size of CuO, and the critical temperature of the sample containing CuO particles with sizes less than 6μm is 100 ℃ lower than that of the sample containing CuO particles with sizes less than 100μm.
基金The Special Funds for State Key Projects for Fun- damental Research (G1999022201-04).
文摘Application of particle image velocity (PIV) techniques for measuringparticle size distribution and total number in an activation chamber of desulfurization system isintroduced. Watersheld algorithm is used to choose the suitable initial gray level threshold whichis used to change the gray level images taken by PIV to black and white ones, then every particle inan image is isolated totally. For every isolating particle, its contour is tracked by the edgeenhancement filter function and kept by Freeman s chain code. Based on a set of particle s chincode, its size and size distribution are calculated and sorted. Finally, the experimental data ofcalcium particles and water drops, separately injected into the activation chamber, and the erroranalysis of data are given out.
基金This work was supported by the National Key Program for Developing Basic Sciences(Grant No.G1999032801)the National Natural Science Foundation of China(Grant Nos.20336040and 20221603)the Chinese Academy of Sciences(Grant No.INF105-SCE-2-07).
文摘A parallel algorithm suitable for simulating multi-sized particle systems and multi-phase fluid systems is proposed based on macro-scale pseudo-particle modeling(MaPPM).The algorithm employs space-decomposition of the computational load among the processing ele-ments(PEs)and multi-level cell-subdivision technique for particle indexing.In this algorithm,a 2D gas-solid system is simulated with the temporal variations of drags on solids,inter-phase slip velocities and solids concentration elaborately monitored.Analysis of the results shows that the algorithm is of good parallel efficiency and scalability,demonstrating the unique advantage of MaPPM in simulating complex flows.
文摘Lithium ion batteries are complicated distributed parameter systems that can be described preferably by partial differential equations and a field theory. To reduce the solution difficulty and the calculation amount, if a distributed parameter system is described by ordinary differential equations （ODE） during the analysis and the design of distributed parameter system, the reliability of the system description will be reduced, and the systemic errors will be introduced. Studies on working condition real-time monitoring can improve the security because the rechargeable LIBs are widely used in many electronic systems and electromechanical equipment. Single particle model （SPM） is the simplification of LIB under some approximations, and can estimate the working parameters of a LIB at the faster simulation speed. A LIB modelling algorithm based on PDEs and SPM is proposed to monitor the working condition of LIBs in real time. Although the lithium ion concentration is an unmeasurable distributed parameter in the anode of LIB, the working condition monitoring model can track the real time lithium ion concentration in the anode of LIB, and calculate the residual which is the difference between the ideal data and the measured data. A fault alarm can be triggered when the residual is beyond the preset threshold. A simulation example verifies that the effectiveness and the accuracy of the working condition real-time monitoring model of LIB based on PDEs and SPM.
基金DFGgrants RFBR 02-01-00266+2 种基金Russian Scientific School 1758.2003.1NSAAlexander von Humboldt Foundation
文摘We study the scaling limit for a catalytic branching particle system whose particles perform random walks on Z and can branch at 0 only. Varying the initial （finite） number of particles, we get for this system different limiting distributions. To be more specific, suppose that initially there are n^β particles and consider the scaled process Zt^n（·） = Znt（√n·）, where Zt is the measure-valued process 1 and to a representing the original particle system. We prove that Ztn converges to 0 when β 〈1/4 and to a nondegenerate discrete distribution when β=1/4.In addition,if 1/4〈β〈1/2 then n-^（2β-1/2）Zt^n converges to a random limit,while if β 〉21then n^-βZtn converges to a deterministic limit.
