非线性函数协方差传播的Stein Monte Carlo方法

基于泰勒级数展开的近似函数法在求解非线性函数的中误差时需要进行复杂的导数计算,已有的Monte Carlo法虽然可以避免导数运算,但在模拟次数的选择上不具有客观性,且无法直接控制模拟结果。因此,将Stein两阶段法融入非线性函数的协方差传播理论中,并与Monte Carlo方法结合,设计了一套非线性函数协方差传播的Stein Monte Carlo算法流程。将该方法用于二维多项式函数和GNSS基线向量的协方差传播计算中,实验结果验证了其有效性,为非线性模型协方差传播的计算提供了一种新思路。     

用蒙特卡洛模拟法求机器的更新函数

分析了现行求更新函数解析法所存在的不足之处,探讨采用蒙特卡洛模拟法求机器在常用寿命分布情况下的更新函数,并以对数正态分布为例介绍其应用过程。     

Monte Carlo simulation of scintillation crystal detector for formation element logging

Formation elements logging is a neutron gamma spectroscopy logging technique used to acquire the content of elements and minerals by recording the gamma ray produced by the reaction of neutron and elemental nucleus in the formation. It has a wide usage in discriminating complex lithology and evaluating unconventional reservoir. The Monte Carlo simulation model of formation elements logging tool is established in this paper, with which the effects of tool parameters including the material and length of the scintillation crystal and source spacing on logging responses are modeled. The results show that the energy response of LaBr_3: Ce crystal is better than others, and the detection efficiency increases with the crystal length but decrease with source spacing. The above results may be used as a reference for optimizing the tool structure design.     

A temporal sliding procedure for ocean wave variational data assimilation and its application

For sequential performance of wave variational data assimilation, we proposed a temporal sliding method in which the temporal overlap is considered. The advantage of this method is that the initial wave spectrum of the optimization process is modified by the observations in latter and former times. This temporal sliding procedure is important for marginal region, such as the China seas, where the duration of assimilation effectiveness is 2-3 days. Experiments were performed in the whole course of Cyclone 9403 (Russ). Around the cyclone center, the maximum value of wave elements did not change much by assimilation, because the extreme value was determined by wind energy input that was not yet optimized. In the area outside the cyclone center, this modification is evident especially for wind wave growth.     

Calculation of significant wave height using the linear mean square estimation method

Significant wave height is an important criterion in designing coastal and offshore structures. Based on the orthogonality principle, the linear mean square estimation method is applied to calculate significant wave height in this paper. Twenty-eight-year time series of wave data collected from three ocean buoys near San Francisco along the California coast are analyzed. It is proved theoretically that the computation error will be reduced by using as many measured data as possible for the calculation of significant wave height. Measured significant wave height at one buoy location is compared with the calculated value based on the data from two other adjacent buoys. The results indicate that the linear mean square estimation method can be well applied to the calculation and prediction of significant wave height in coastal regions.     

Monte carlo simulation of in situ gamma-spectra recorded by NaI (Tl) detector in the marine environment

To develop a Na I(Tl) detector for in situ radioactivity monitoring in the marine environment and enhance the confidence of the probability of the gamma-spectrum analysis, Monte Carlo simulations using the Monte Carlo N-Particle( MNCP) code were performed to provide the response spectra of some interested radionuclides and the background spectra originating from the natural radionuclides in seawater recorded by a Na I(Tl) detector. A newly developed 75 mm × 75 mm Na I(Tl) detector was calibrated using four reference radioactive sources 137 Cs, 60 Co, 40 K and 54 Mn in the laboratory before the field measurements in seawater. A simulation model was established for the detector immersed in seawater. The simulated spectra were all broadened with Gaussian pulses to reflect the statistical fluctuations and electrical noise in the real measurement. The simulated spectra show that the single-energy photons into the detector are mostly scattering low-energy photons and the high background in the low energy region mainly originates from the Compton effect of the high energy γ-rays of natural radionuclides in seawater. The simulated background spectrum was compared with the experimental one recorded in field measurement and they seem to be in good agreement. The simulation method and spectra can be used for the accurate analysis of the filed measurement results of low concentration radioactivity in seawater.     

A wave modulation model of ripples over long surface waves

A study is presented on the modulation of ripples induced by a long surface wave (LW) and a new theoretical modulation model is proposed. In this model, the wind surface stress modulation is related to the modulation of ripple spectrum. The model results show that in the case of LW propagating in the wind direction with the wave age parameter of LW increasing, the area with enhanced shear stress shifts from the region near the LW crest on the upwind slope to the LW trough. With a smaller wave age parameter of LW, the ripple modulation has the maximum on the upwind slope in the vicinity of LW crest, while with a larger parameter the enhancement of ripple spectrum does not occur in that region. At low winds the amplitude of ripple modulation transfer function (MTF) is larger in the gravity wave range, while at moderate or high winds it changes little in the range from short gravity waves to capillary waves.     

A time-dependent stochastic grassland fire ignition probability model for Hulun Buir Grassland of China

Grassland fire is one of the most important disturbance factors in the natural ecosystems.This paper focuses on the spatial distribution of long-term grassland fire patterns in the Hulun Buir Grassland located in the northeast of Inner Mongolia Autonomous Region in China.The density or ratio of ignition can reflect the relationship between grassland fire and different ignition factors.Based on the relationship between the density or ratio of ignition in different range of each ignition factor and grassland fire events,an ignition probability model was developed by using binary logistic regression function and its overall accuracy averaged up to 81.7%.Meanwhile it was found that daily relative humidity,daily temperature,elevation,vegetation type,distance to county-level road,distance to town are more important determinants of spatial distribution of fire ignitions.Using Monte Carlo method,we developed a time-dependent stochastic ignition probability model based on the distribution of inter-annual daily relative humidity and daily temperature.Through this model,it is possible to estimate the spatial patterns of ignition probability for grassland fire,which will be helpful to the quantitative evaluation of grassland fire risk and its management in the future.