In loosely coupled or large-scale problems with high dominance ratios,slow fission source convergence can take extremely long time,reducing Monte Carlo(MC)criticality calculation efficiency.Although various accelerati...In loosely coupled or large-scale problems with high dominance ratios,slow fission source convergence can take extremely long time,reducing Monte Carlo(MC)criticality calculation efficiency.Although various acceleration methods have been developed,some methods cannot reduce convergence times,whereas others have been limited to specific problem geometries.In this study,a new fission source convergence acceleration(FSCA)method,the forced propagation(FP)method,has been proposed,which forces the fission source to propagate and accelerate fission source convergence.Additionally,some stabilization techniques have been designed to render the method more practical.The resulting stabilized method was then successfully implemented in the MC transport code,and its feasibility and effectiveness were tested using the modified OECD/NEA,one-dimensional slab benchmark,and the Hoogenboom full-core problem.The comparison results showed that the FP method was able to achieve efficient FSCA.展开更多
On-the-fly Doppler broadening of cross sections is important in Monte Carlo simulations,particularly in Monte Carlo neutronics-thermal hydraulics coupling simulations.Methods such as Target Motion Sampling(TMS)and win...On-the-fly Doppler broadening of cross sections is important in Monte Carlo simulations,particularly in Monte Carlo neutronics-thermal hydraulics coupling simulations.Methods such as Target Motion Sampling(TMS)and windowed multipole as well as a method based on regression models have been developed to solve this problem.However,these methods have limitations such as the need for a cross section in an ACE format at a given temperature or a limited application energy range.In this study,a new on-the-fly Doppler broadening method based on a Back Propagation(BP)neural network,called hybrid windowed networks(HWN),is proposed to resolve the resonance energy range.In the HWN method,the resolved resonance energy range is divided into windows to guarantee an even distribution of resonance peaks.BP networks with specially designed structures and training parameters are trained to evaluate the cross section at a base temperature and the broadening coefficient.The HWN method is implemented in the Reactor Monte Carlo(RMC)code,and the microscopic cross sections and macroscopic results are compared.The results show that the HWN method can reduce the memory requirement for cross-sectional data by approximately 65%;moreover,it can generate keff,power distribution,and energy spectrum results with acceptable accuracy and a limited increase in the calculation time.The feasibility and effectiveness of the proposed HWN method are thus demonstrated.展开更多
作为一种很有前景的建模方法,逆向蒙特卡洛法(reverse Monte Carlo简称RMC法)在无定形碳结构研究中得到了广泛应用。本文阐述了RMC法对于无定形碳材料结构识别的意义,简介了该法的基本原理,综述了在使用RMC法建立无定形碳结构模型时的...作为一种很有前景的建模方法,逆向蒙特卡洛法(reverse Monte Carlo简称RMC法)在无定形碳结构研究中得到了广泛应用。本文阐述了RMC法对于无定形碳材料结构识别的意义,简介了该法的基本原理,综述了在使用RMC法建立无定形碳结构模型时的两大难点,即模拟结构的真实性问题和大尺寸孔网络的建模问题的改进方法和发展趋势。几何约束和能量约束的使用,提高了模拟结构的真实性;具有介孔的多孔碳模型的建立,将成为今后研究的热点。展开更多
基金supported by the National Natural Science Foundation of China(Nos.11775126,11545013,11605101)the Young Elite Scientists Sponsorship Program by CAST(No.2016QNRC001)+1 种基金Science Challenge Project by MIIT of China(No.TZ2018001)Tsinghua University,Initiative Scientific Research Program。
文摘In loosely coupled or large-scale problems with high dominance ratios,slow fission source convergence can take extremely long time,reducing Monte Carlo(MC)criticality calculation efficiency.Although various acceleration methods have been developed,some methods cannot reduce convergence times,whereas others have been limited to specific problem geometries.In this study,a new fission source convergence acceleration(FSCA)method,the forced propagation(FP)method,has been proposed,which forces the fission source to propagate and accelerate fission source convergence.Additionally,some stabilization techniques have been designed to render the method more practical.The resulting stabilized method was then successfully implemented in the MC transport code,and its feasibility and effectiveness were tested using the modified OECD/NEA,one-dimensional slab benchmark,and the Hoogenboom full-core problem.The comparison results showed that the FP method was able to achieve efficient FSCA.
基金supported by the Science Challenge Project(No.TZ2018001)the National Natural Science Foundation of China(Nos.11775126,11545013,11775127)+1 种基金Young Elite Scientists Sponsorship Program by CAST(No.2016QNRC001)Tsinghua University Initiative Scientific Research Program。
文摘On-the-fly Doppler broadening of cross sections is important in Monte Carlo simulations,particularly in Monte Carlo neutronics-thermal hydraulics coupling simulations.Methods such as Target Motion Sampling(TMS)and windowed multipole as well as a method based on regression models have been developed to solve this problem.However,these methods have limitations such as the need for a cross section in an ACE format at a given temperature or a limited application energy range.In this study,a new on-the-fly Doppler broadening method based on a Back Propagation(BP)neural network,called hybrid windowed networks(HWN),is proposed to resolve the resonance energy range.In the HWN method,the resolved resonance energy range is divided into windows to guarantee an even distribution of resonance peaks.BP networks with specially designed structures and training parameters are trained to evaluate the cross section at a base temperature and the broadening coefficient.The HWN method is implemented in the Reactor Monte Carlo(RMC)code,and the microscopic cross sections and macroscopic results are compared.The results show that the HWN method can reduce the memory requirement for cross-sectional data by approximately 65%;moreover,it can generate keff,power distribution,and energy spectrum results with acceptable accuracy and a limited increase in the calculation time.The feasibility and effectiveness of the proposed HWN method are thus demonstrated.
文摘作为一种很有前景的建模方法,逆向蒙特卡洛法(reverse Monte Carlo简称RMC法)在无定形碳结构研究中得到了广泛应用。本文阐述了RMC法对于无定形碳材料结构识别的意义,简介了该法的基本原理,综述了在使用RMC法建立无定形碳结构模型时的两大难点,即模拟结构的真实性问题和大尺寸孔网络的建模问题的改进方法和发展趋势。几何约束和能量约束的使用,提高了模拟结构的真实性;具有介孔的多孔碳模型的建立,将成为今后研究的热点。
