The protection of downstream concrete slab is a key issue for the stability of overflow earth-rock cofferdam. The coupling effect between bedding layer and concrete slab was taken into account when the stability of do...The protection of downstream concrete slab is a key issue for the stability of overflow earth-rock cofferdam. The coupling effect between bedding layer and concrete slab was taken into account when the stability of downstream concrete slab was researched. The characteristics of overflow and seepage over the downstream concrete slab were investigated when floodwater passes over the cofferdam. Firstly a limit equation of seepage failure for the bedding layer was derived with the consideration of geometric and mechanical factors, and a reliability model was established and numerically simulated. Then based on the reliability calculation for the bedding layer, the coupling effect between bedding layer and downstream concrete slab was analyzed. Under the most unfavorable pressure condition for the concrete slab, its instability criterion was put forward, which offers a structural design tool of downstream concrete slab for overflow earth-rock cofferdam. Compared with model tests, it shows that the model of reliability calculation of bedding layer and the stability analysis of downstream concrete slab are effective.展开更多
Generation of wind power time series is an important foundational task for assisting electric power system planning and mak- ing decision. By analyzing the characteristics of wind power persistence and variation, th!....Generation of wind power time series is an important foundational task for assisting electric power system planning and mak- ing decision. By analyzing the characteristics of wind power persistence and variation, th!.s paper proposes an improved Mar- kov chain Monte Carlo （MCMC） method, identified as the PV-MC method, for the direct generation of a synthetic series of wind power output. On the basis of the MCMC method, duration time and variation features are concluded in PV-MC method, gaining a more comprehensive reflection of wind power characteristics in the generated wind power time series. First, the wind power state series is generated to meet the state transition matrix based on the definition of the wind power state. Then, the time duration of each state in the series is determined by its respective duration character. Finally, the variation characteristic is used to convert the state series to a wind power time series. A significant amount of simulations are performed based on the PV-MC and MCMC methods and are then compared for 25 wind farms at 6 different locations throughout the world. The sim- ulation results show that the PV-MC method offers an excellent fit for the time domain features （persistence and variation characteristic） while holding other statistic features （mean value, variance, autocorrelation coefficient （ACC） and probability density function （PDF）） close to the MCMC method.展开更多
In an earlier paper, we proved the existence of solutions to the Skorohod problem with oblique reflection in time-dependent domains and, subsequently, applied this result to the problem of constructing solutions, in t...In an earlier paper, we proved the existence of solutions to the Skorohod problem with oblique reflection in time-dependent domains and, subsequently, applied this result to the problem of constructing solutions, in time-dependent domains, to stochastic differential equations with oblique reflection. In this paper we use these results to construct weak approximations of solutions to stochastic differential equations with oblique reflection, in time-dependent domains in Rd, by means of a projected Euler scheme. We prove that the constructed method has, as is the case for normal reflection and time-independent domains, an order of convergence equal to 1/2 and we evaluate the method empirically by means of two numerical examples. Furthermore, using a well-known extension of the Feynman-Kac formula, to stochastic differential equations with reflection, our method gives, in addition, a Monte Carlo method for solving second order parabolic partial differential equations with Robin boundary conditions in time-dependent domains.展开更多
Multifocal multiphoton microscopy(MMM)has greatly improved the utilization of excitationlight and imaging speed due to parallel multiphoton excitation of the samples and simultaneousdetection of the signals,which allo...Multifocal multiphoton microscopy(MMM)has greatly improved the utilization of excitationlight and imaging speed due to parallel multiphoton excitation of the samples and simultaneousdetection of the signals,which allows it to perform three-dimensional fast fuorescence imaging.Stochastic scanming can provide continuous,uniform and high-speed excitation of the sample,which makes it a suitable scanning scheme for MMM.In this paper,the graphical programminglanguage,LabVIEW is used to achieve stochastic scanning of the two-dimensional galvo scanmers by using white noise signals to control the a and y mirrors independently.Moreover,thestochastic scanning process is simulated by using Monte Carlo method.Our results show that MMM can avoid oversampling or subsampling in the scanning area and meet the requirements of uniform sampling by stochastically scanning the individual units of the N×N foci array.Therefore,continuous and umiform scaning in the whole field of view is implemented.展开更多
Nonlinear filter problems arise in many applications such as communications and signal processing.Commonly used numerical simulation methods include Kalman filter method,particle filter method,etc.In this paper a nove...Nonlinear filter problems arise in many applications such as communications and signal processing.Commonly used numerical simulation methods include Kalman filter method,particle filter method,etc.In this paper a novel numerical algorithm is constructed based on samples of the current state obtained by solving the state equation implicitly.Numerical experiments demonstrate that our algorithm is more accurate than the Kalman filter and more stable than the particle filter.展开更多
随着智能电网的建设,大量分布式电源引入配电网后,配电网的供电情况发生了很大的变化,对其故障自愈策略也越来越重视。本文在计及风、光伏发电和负荷功率的随机性的基础上,建立最优孤岛划分模型,找出配电网各负荷点的可靠性指标的计算方...随着智能电网的建设,大量分布式电源引入配电网后,配电网的供电情况发生了很大的变化,对其故障自愈策略也越来越重视。本文在计及风、光伏发电和负荷功率的随机性的基础上,建立最优孤岛划分模型,找出配电网各负荷点的可靠性指标的计算方法,并使用蒙特卡洛对配电网可靠性进行求解。最后通过对IEEE-RBTS BUS 6系统进行分析,验证对含DG配电网采用最优孤岛划分的意义和其对系统可靠性评估的影响。本文从供电可靠性的角度,对含DG配电网的孤岛划分进行分析,为全面地评估含DG配电网供电可靠性和配电网故障自愈策略的制定提供了一定的理论依据。展开更多
基金supported by the National Natural Science Foundation of China (Grant No. 50579056)the Joint Fund of Yalong River Hydropower Development Researchthe National Natural Science Foundation of China(Grant No. 50539120)
文摘The protection of downstream concrete slab is a key issue for the stability of overflow earth-rock cofferdam. The coupling effect between bedding layer and concrete slab was taken into account when the stability of downstream concrete slab was researched. The characteristics of overflow and seepage over the downstream concrete slab were investigated when floodwater passes over the cofferdam. Firstly a limit equation of seepage failure for the bedding layer was derived with the consideration of geometric and mechanical factors, and a reliability model was established and numerically simulated. Then based on the reliability calculation for the bedding layer, the coupling effect between bedding layer and downstream concrete slab was analyzed. Under the most unfavorable pressure condition for the concrete slab, its instability criterion was put forward, which offers a structural design tool of downstream concrete slab for overflow earth-rock cofferdam. Compared with model tests, it shows that the model of reliability calculation of bedding layer and the stability analysis of downstream concrete slab are effective.
基金supported by the National Natural Science Foundation of China(Grant No.51377027)the National Basic Research Program of China("973"Project)(Grant No.2012CB215104)ABB(China)Ltd
文摘Generation of wind power time series is an important foundational task for assisting electric power system planning and mak- ing decision. By analyzing the characteristics of wind power persistence and variation, th!.s paper proposes an improved Mar- kov chain Monte Carlo （MCMC） method, identified as the PV-MC method, for the direct generation of a synthetic series of wind power output. On the basis of the MCMC method, duration time and variation features are concluded in PV-MC method, gaining a more comprehensive reflection of wind power characteristics in the generated wind power time series. First, the wind power state series is generated to meet the state transition matrix based on the definition of the wind power state. Then, the time duration of each state in the series is determined by its respective duration character. Finally, the variation characteristic is used to convert the state series to a wind power time series. A significant amount of simulations are performed based on the PV-MC and MCMC methods and are then compared for 25 wind farms at 6 different locations throughout the world. The sim- ulation results show that the PV-MC method offers an excellent fit for the time domain features （persistence and variation characteristic） while holding other statistic features （mean value, variance, autocorrelation coefficient （ACC） and probability density function （PDF）） close to the MCMC method.
文摘In an earlier paper, we proved the existence of solutions to the Skorohod problem with oblique reflection in time-dependent domains and, subsequently, applied this result to the problem of constructing solutions, in time-dependent domains, to stochastic differential equations with oblique reflection. In this paper we use these results to construct weak approximations of solutions to stochastic differential equations with oblique reflection, in time-dependent domains in Rd, by means of a projected Euler scheme. We prove that the constructed method has, as is the case for normal reflection and time-independent domains, an order of convergence equal to 1/2 and we evaluate the method empirically by means of two numerical examples. Furthermore, using a well-known extension of the Feynman-Kac formula, to stochastic differential equations with reflection, our method gives, in addition, a Monte Carlo method for solving second order parabolic partial differential equations with Robin boundary conditions in time-dependent domains.
基金partially supported,by,the National Natural Science Foundation of China(11204226)the Fundamental Research Fundsfor,the Central Universities(K5051005006,K5051305002).
文摘Multifocal multiphoton microscopy(MMM)has greatly improved the utilization of excitationlight and imaging speed due to parallel multiphoton excitation of the samples and simultaneousdetection of the signals,which allows it to perform three-dimensional fast fuorescence imaging.Stochastic scanming can provide continuous,uniform and high-speed excitation of the sample,which makes it a suitable scanning scheme for MMM.In this paper,the graphical programminglanguage,LabVIEW is used to achieve stochastic scanning of the two-dimensional galvo scanmers by using white noise signals to control the a and y mirrors independently.Moreover,thestochastic scanning process is simulated by using Monte Carlo method.Our results show that MMM can avoid oversampling or subsampling in the scanning area and meet the requirements of uniform sampling by stochastically scanning the individual units of the N×N foci array.Therefore,continuous and umiform scaning in the whole field of view is implemented.
基金supported by National Science Foundation under grant number DMS0914554,AFOSR under grant number FA9550-12-1-0281,and by Guangdong Provin F.Bao,Y.Cao and X.Han/Commun.Comput.Phys.,16(2014),pp.382-402401。
文摘Nonlinear filter problems arise in many applications such as communications and signal processing.Commonly used numerical simulation methods include Kalman filter method,particle filter method,etc.In this paper a novel numerical algorithm is constructed based on samples of the current state obtained by solving the state equation implicitly.Numerical experiments demonstrate that our algorithm is more accurate than the Kalman filter and more stable than the particle filter.
文摘随着智能电网的建设,大量分布式电源引入配电网后,配电网的供电情况发生了很大的变化,对其故障自愈策略也越来越重视。本文在计及风、光伏发电和负荷功率的随机性的基础上,建立最优孤岛划分模型,找出配电网各负荷点的可靠性指标的计算方法,并使用蒙特卡洛对配电网可靠性进行求解。最后通过对IEEE-RBTS BUS 6系统进行分析,验证对含DG配电网采用最优孤岛划分的意义和其对系统可靠性评估的影响。本文从供电可靠性的角度,对含DG配电网的孤岛划分进行分析,为全面地评估含DG配电网供电可靠性和配电网故障自愈策略的制定提供了一定的理论依据。
