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Particle-based hybrid and multiscale methods for nonequilibrium gas flows 被引量:10
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作者 Jun Zhang Benzi John +2 位作者 Marcel Pfeiffer Fei Fei Dongsheng Wen 《Advances in Aerodynamics》 2019年第1期239-253,共15页
Over the past half century,a variety of computational fluid dynamics(CFD)methods and the direct simulation Monte Carlo(DSMC)method have been widely and successfully applied to the simulation of gas flows for the conti... Over the past half century,a variety of computational fluid dynamics(CFD)methods and the direct simulation Monte Carlo(DSMC)method have been widely and successfully applied to the simulation of gas flows for the continuum and rarefied regime,respectively.However,they both encounter difficulties when dealing with multiscale gas flows in modern engineering problems,where the whole system is on the macroscopic scale but the nonequilibrium effects play an important role.In this paper,we review two particle-based strategies developed for the simulation of multiscale nonequilibrium gas flows,i.e.,DSMC-CFD hybrid methods and multiscale particle methods.The principles,advantages,disadvantages,and applications for each method are described.The latest progress in the modelling of multiscale gas flows including the unified multiscale particle method proposed by the authors is presented. 展开更多
关键词 Nonequilibrium gas flow Multiscale simulation Hybrid method DSMC Fokker-Planck equation Boltzmann equation Unified statistical particle method
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A novel statistically tracked particle swarm optimization method for automatic generation control 被引量:1
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作者 Cheshta JAIN H.K.VERMA L.D.ARYA 《Journal of Modern Power Systems and Clean Energy》 SCIE EI 2014年第4期396-410,共15页
Particle swarm optimization(PSO)is one of the popular stochastic optimization based on swarm intelligence algorithm.This simple and promising algorithm has applications in many research fields.In PSO,each particle can... Particle swarm optimization(PSO)is one of the popular stochastic optimization based on swarm intelligence algorithm.This simple and promising algorithm has applications in many research fields.In PSO,each particle can adjust its‘flying’according to its own flying experience and its companions’flying experience.This paper proposes a new PSO variant,called the statistically tracked PSO,which uses group statistical characteristics to update the velocity of the particle after certain iterations,thus avoiding localminima and helping particles to explore global optimum with an improved convergence.The performance of the proposed algorithm is tested on a deregulated automatic generation control problem in power systems and encouraging results are obtained. 展开更多
关键词 Statistically tracked particle swarm optimization(STPSO) Group statistical characteristics Deregulated automatic generation control(AGC)
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