An enhanced image binarization method incorporating with Monte-Carlo simulation

We proposed an enhanced image binarization method.The proposed solution incorporates Monte-Carlo simulation into the local thresholding method to address the essential issues with respect to complex background,spatially-changed illumination,and uncertainties of block size in traditional method.The proposed method first partitions the image into square blocks that reflect local characteristics of the image.After image partitioning,each block is binarized using Otsu’s thresholding method.To minimize the influence of the block size and the boundary effect,we incorporate Monte-Carlo simulation into the binarization algorithm.Iterative calculation with varying block sizes during Monte-Carlo simulation generates a probability map,which illustrates the probability of each pixel classified as foreground.By setting a probability threshold,and separating foreground and background of the source image,the final binary image can be obtained.The described method has been tested by benchmark tests.Results demonstrate that the proposed method performs well in dealing with the complex background and illumination condition.

An analysis of the radar backscatter from oil-covered sea surfaces using moment method and Monte-Carlo simulation: preliminary results

An analysis of the radar backscattering from the ocean surface covered by oil spill is presented using a mi- crowave scattering model and Monte-Carlo simulation. In the analysis, a one-dimensional rough sea sur- face is numerically generated with an ocean waveheight spectrum for a given wind velocity. A two-layered medium is then generated by adding a thin oil layer on the simulated rough sea surface. The electric fields backscattered from the sea surface with two-layered medium are computed with the method of moments （MoM）, and the backscattering coefficients are statistically obtained with N independent samples for each oil-spilled surface using the Monte-Carlo technique for various conditions of surface roughness, oil-layer thickness, frequency, polarization and incidence angle. The numerical simulation results are compared with theoretical models for clean sea surfaces and SAR images of an off-spilled sea surface caused by the Hebei （Hebei province, China） Spirit oil tanker in 2007. Further, conditions for better oil spill extraction are sought by the numerical simulation on the effects of wind speed and oil-layer thickness at different inci- dence angles on the backscattering coefficients.

Development of multi-group Monte-Carlo transport and depletion coupling calculation method and verification with metal-fueled fast reactor

The accurate modeling of depletion,intricately tied to the solution of the neutron transport equation,is crucial for the design,analysis,and licensing of nuclear reactors and their fuel cycles.This paper introduces a novel multi-group Monte-Carlo depletion calculation approach.Multi-group cross-sections(MGXS)are derived from both 3D whole-core model and 2D fuel subassembly model using the continuous-energy Monte-Carlo method.Core calculations employ the multi-group Monte-Carlo method,accommodating both homogeneous and specific local heterogeneous geometries.The proposed method has been validated against the MET-1000 metal-fueled fast reactors,using both the OECD/NEA benchmark and a new refueling benchmark introduced in this paper.Our findings suggest that microscopic MGXS,produced via the Monte-Carlo method,are viable for fast reactor depletion analyses.Furthermore,the locally heterogeneous model with angular-dependent MGXS offers robust predictions for core reactivity,control rod value,sodium void value,Doppler constants,power distribution,and concentration levels.

A new hybrid method—combined heat flux method with Monte-Carlo method to analyze thermal radiation

A new hybrid method, Monte-Carlo-Heat-Flux （MCHF） method, was presented to analyze the radiative heat transfer of participating medium in a three-dimensional rectangular enclosure using combined the Monte-Carlo method with the heat flux method. Its accuracy and reliability was proved by comparing the computational results with exact results from classical ＂Zone Method＂.

Monte-Carlo Method for Coalbed Methane Resource Assessment in Key Coal Mining Areas of China

Monte-Carlo method is used for estimating coalbed methane （CBM） resources in key coal mining areas of China. Monte-Carlo method is shown to be superior to the traditional volumetric method with constant parameters in the calculation of CBM resources. The focus of the article is to introduce the main algorithm and the realization of functions estimated by Monte-Carlo method, including selection of parameters, determination of distribution function, generation of pseudo-random numbers, and evaluation of the parameters corresponding to pseudo-random numbers. A specified software on the basis of Monte-Carlo method is developed using Visual C＋＋ for the assessment of the CBM resources. A case study shows that calculation results using Monte-Carlo method have smaller error range in comparison with those using volumetric method.

Reliability analysis of tunnel surrounding rock stability by Monte-Carlo method

Discussed advantages of improved Monte-Carlo method and feasibility about proposed approach applying in reliability analysis for tunnel surrounding rock stability.On the basis of deterministic parsing for tunnel surrounding rock,reliability computing method of surrounding rock stability was derived from improved Monte-Carlo method.The com- puting method considered random of related parameters,and therefore satisfies relativity among parameters.The proposed method can reasonably determine reliability of sur- rounding rock stability.Calculation results show that this method is a scientific method in discriminating and checking surrounding rock stability.

New Approach to Simulating the Absorption of Gamma Radiations Using the Monte-Carlo Method: A Computational Study

The following article has been retracted due to the investigation of complaints received against it. Mr. Mohammadali Ghorbani (corresponding author and also the last author) cheated the author’s name: Alireza Heidari. The scientific community takes a very strong view on this matter and we treat all unethical behavior such as plagiarism seriously. This paper published in Vol.3 No.3, 260-265, 2012, has been removed from this site.

基于Monte-Carlo方法的土石围堰挡水导流风险分析

运用Monte -Carlo方法模拟施工洪水入库过程和导流建筑物泄流的随机性 ,通过仿真分析确定上游围堰堰前水位变化过程及其分布函数。在此基础上 ,根据导流建筑物的设计规模确定导流系统的风险。通过实例验证分析说明 ,研究方法和计算模型是可靠的、适用的。

基于Neumann展开Monte-Carlo有限元法的随机温度场分析

利用Neumann展开Monte-Carlo随机有限元法,对导热系数、换热系数、热流密度、环境温度以及内热源等物理参数同时具有随机性的温度场问题进行了分析,给出了节点温度响应的均值、变异系数和节点温度落在某一区间内的概率计算公式.通过算例考察了各随机变量的变异性大小对节点温度响应的影响,并表明随着结构的自由度数目增大,文中方法呈现出计算效率高的优点.

Monte-Carlo随机有限元结构可靠度分析新方法

基于条件抽样、对偶抽样及Neumann展开技术,同时,为试图一定程度地解决"计算模型的不确定性"问题,考虑到岩石、混凝土等材料的单轴抗压强度σc和双轴等压强度σcc不同的特性,将3参数统一强度理论引入随机有限元程序,建立了Monte-Carlo三维非线性随机有限元结构可靠性分析模型。模拟成果表明,采用该模型的模拟收敛性良好,模拟效率较高、成本较低,可靠指标β值精度满足实用要求,在大型复杂结构的设计及可靠度分析研究中具有实用价值。

轮盘疲劳可靠性分析的Monte-Carlo数字仿真

低循环多轴疲劳失效是航空发动机低压压气机轮盘的主要失效形式。轮盘是一种价格昂贵的部件,对其进行部件的可靠性试验在经济上难以承受。据此以临界平面法为基础,通过Ansys有限元分析与材料的应变疲劳试验相结合,利用Monte-Carlo数字仿真方法,确定了轮盘寿命的分布形式,建立了轮盘疲劳可靠性模型,并编制了轮盘疲劳可靠性分析软件,对某型轮盘进行了疲劳可靠性分析。与传统的确定性方法相比更加符合轮盘的失效状况,与基于真实轮盘的试验相比则可以有效降低试验费用,缩短试验周期。

基于Monte-Carlo法的滑坡稳定可靠性分析

简述了可靠性分析的 Ｍｏｎｔｅ－Ｃａｒｌｏ法，结合简化的 Ｂｉｓｈｏｐ法提出了滑坡稳定可靠性分析的状态函数，并通过实例进行了计算分析。证明Ｍｏｎｔｅ－Ｃａｒｌｏ法是求解滑坡稳定可靠性指标和破坏概率的行之有效的方法。

球罐BLEVE碎片抛射的Monte-Carlo分析

多米诺效应是引发化工厂发生重大灾害性事故的主要原因之一,其总后果的严重性远远超过初始事故后果的严重性。目前研究多米诺效应主要考虑热辐射、超压和碎片3种扩展向量,其中爆炸碎片具有很大的随机性,而且破坏后果常常很严重。对爆炸碎片的研究是个热点和难题。本文以墨西哥城液化石油气爆炸事故中球罐发生沸腾液体扩展为蒸气云爆炸(BLEVE)为例,通过Monte-Carlo方法模拟,利用有关的数据和资料确定爆炸碎片产生和飞行中的不确定性参数的概率密度分布,从而计算出碎片的抛射范围。并在此基础上,考虑目标容器和风的影响,将二维轨迹方程扩展为三维方程,并计算得到在给定位置处的目标容器受到碎片冲击的概率。本文的研究结果对于定量评价球罐发生BLEVE之后碎片所造成的危险分析具有重要意义。

基于Monte-Carlo方法的施工导流系统综合风险分析

施工期导流动态风险不仅与水文不确定性、水力不确定性有关,而且与坝体施工进度及其完工工期的不确定性有关。以风险分析为核心,将各种不确定性因素耦合起来研究施工导流系统的综合风险,提出施工进度计划风险分析模型和假定坝体施工进度确定条件下的施工导流风险分析模型,在此基础上,建立基于Monte-Carlo方法全面考虑水文水力不确定性以及施工进度不确定性的施工导流系统综合风险分析模型。实例分析说明,该施工导流系统综合风险研究方法和分析模型是可靠的、适用的。

基于Monte-Carlo方法的风电功率预测不确定性估计

风电功率预测的不确定性估计是实现对风电场优化调度的基础。为此,提出了1种定性分析风电功率预测敏感气象因子的方法,采用2种方式分别对敏感气象因子的误差分布函数进行了估计,并采用Monte-Carlo随机抽样实现了对风电功率预测不确定性的估计,最后进行了算例验证。研究结果表明:不同预报时刻对应气象参数预报误差的不确定性差别较大;基于气象参数不确定性随机抽样的方法可实现对功率预测的不确定性估计,且在相同的置信度下,逐小时样本估计优于总体样本估计。与传统风电功率预测不确定性估计方法相比,该方法对风电场历史运行数据要求低,且不需要单独建模,具有较高的工程实用性。

基于Monte-Carlo法的冻土路基随机温度场分析

对青藏铁路沿线岩土热学参数进行统计分析,得出岩土的基本统计值及概率分布模式,采用基于Monte-Carlo法的随机有限元方法计算冻土区的路基随机温度场,得出随机温度场的均值和标准差.结果表明:路基的温度场均值和标准差分布趋势基本相似,且在路基上部和路基边坡面附近,其绝对值较大;温度的标准差在边界附近出现最大值,且沿边界向内而逐渐减小;在边界浅层区域,温度的标准差出现局部变化,到达一定深度后趋于稳定,并随着时间增加而增大,路基标准差区域从边界向内而逐渐扩大.

基于Monte-Carlo方法的施工截流风险率估计方法研究

在综合考虑截流过程的水文及水力不确定性因素的基础上,建立了截流风险数学分析模型,该模型包括天然来流量和分流建筑物泄流能力、龙口泄流流量、戗堤渗流流量的模拟。通过分析模型中存在的不确定性因素,构建了相应的概率模型及其抽样公式。采用Monte-Carlo方法对模型进行随机抽样,通过统计分析,获得截流风险率的估计值。最后,采用中心极限定理,依据模拟的次数,给出截流风险率估计值的绝对误差和置信度。通过实例计算分析,验证了所建的模型正确合理。

基于性能退化和Monte-Carlo仿真的系统性能可靠性评估

以往性能可靠性的研究主要针对元器件或系统整体单独开展,缺乏将两者有效结合的研究方法,元器件厂家和用户的大量性能退化数据无法在系统早期设计中得到充分应用。为此,提出基于性能退化和电路仿真相结合的电子产品性能可靠性评估方法。首先根据电子系统原理建立电路仿真模型,再通过灵敏度分析确定导致系统性能参数变化的敏感元器件;之后,根据退化数据建立敏感元器件的性能参数退化模型,利用Monte-Carlo抽样和电路仿真获取系统性能参数的退化数据,进而实现性能可靠性评估。最后,以某型装备上的恒流电源为例具体说明实现过程,以验证该方法的有效性。

基于Monte-Carlo模拟的公路黄土高边坡可靠性研究

本文分析了Monte-Carlo模拟法的基本原理,建立了基于简化Bishop圆弧法的极限状态方程;以陕西公路某黄土路堑高边坡为例,分析了模拟次数、计算模型以及土性参数的变异系数对可靠指标的不同影响,从而为公路黄土路堑高边坡可靠性分析提供了参考依据。

随机温度场Monte-Carlo法的一类近似处理

以非线性热辐射边界条件下多种材料构成的层叠板为研究对象,利用伽辽金法得到了瞬态非线性热传导微分方程组。考虑结构所有物理、几何和环境参数均具有随机性时,通过引入随机因子并提出一类关于热传导矩阵和热容矩阵的近似处理方法,实现了对随机温度场Monte-Carlo数值模拟时间的节省;并通过灵敏度和一阶泰勒展开线性化的方法去近似求解由于前面近似处理所造成的温度场数字特征的误差;算例表明了所给方法能节省大量的Monte-Carlo数值模拟时间,且给出的误差估计具有一定的精度。