Monte Carlo方法在移动通信可靠性分析中的应用

文章主要探讨Monte Carlo方法在移动通信可靠性分析中的应用,并引入重要抽样技术对Monte Carlo方法进行优化。首先,文章介绍Monte Carlo方法的基本原理及其在移动通信可靠性分析中的应用。其次,引入重要抽样技术对该方法进行优化。最后,利用优化网络工程工具(Optimized Network Engineering Tools,OPNET)模拟平台构建相应的移动通信网络模型,并对比Monte Carlo方法和本文研究的优化方法在不同样本数量下的性能差异。结果表明,重要抽样技术的引入显著提高了Monte Carlo方法在移动通信可靠性分析中的准确性和效率,减少了方差,验证了该方法在移动通信可靠性分析中的有效性和实用性。

基于Monte Carlo的风力机叶片强度可靠性分析

随着风力机应用数量增多,以及应用规模扩大,风力机叶片可靠度的保证尤为关键。利用Monte Carlo客观分析叶片强度可靠性,为叶片安全状态长效维持提供依据,实现风力机的平稳运转。该文在介绍Monte Carlo的基础上,分析风力机类型及其叶片状态和叶片参数,并以有限元模型构建的方式分析风力机叶片载荷及强度,最后探究基于Monte Carlo的风力机叶片可靠性。

Method“Monte Carlo”in healthcare

In public health,simulation modeling stands as an invaluable asset,enabling the evaluation of new systems without their physical implementation,experimentation with existing systems without operational adjustments,and testing system limits without real-world repercussions.In simulation modeling,the Monte Carlo method emerges as a powerful yet underutilized tool.Although the Monte Carlo method has not yet gained widespread prominence in healthcare,its technological capabilities hold promise for substantial cost reduction and risk mitigation.In this review article,we aimed to explore the transformative potential of the Monte Carlo method in healthcare contexts.We underscore the significance of experiential insights derived from simulated experimentation,especially in resource-constrained scenarios where time,financial constraints,and limited resources necessitate innovative and efficient approaches.As public health faces increasing challenges,incorporating the Monte Carlo method presents an opportunity for enhanced system construction,analysis,and evaluation.

Safety analysis of wheel brake system based on STAMP/STPA and Monte Carlo simulation

The wheel brake system safety is a complex problem which refers to its technical state, operating environment, human factors, etc., in aircraft landing taxiing process. Usually, professors consider system safety with traditional probability techniques based on the linear chain of events. However, it could not comprehensively analyze system safety problems, especially in operating environment, interaction of subsystems, and human factors. Thus,we consider system safety as a control problem based on the system-theoretic accident model, the processes(STAMP) model and the system theoretic process analysis(STPA) technique to compensate the deficiency of traditional techniques. Meanwhile,system safety simulation is considered as system control simulation, and Monte Carlo methods are used which consider the range of uncertain parameters and operation deviation to quantitatively study system safety influence factors in control simulation. Firstly,we construct the STAMP model and STPA feedback control loop of the wheel brake system based on the system functional requirement. Then four unsafe control actions are identified, and causes of them are analyzed. Finally, we construct the Monte Carlo simulation model to analyze different scenarios under disturbance. The results provide a basis for choosing corresponding process model variables in constructing the context table and show that appropriate brake strategies could prevent hazards in aircraft landing taxiing.

Transformation of CSD When Crystal Shape Changes with Crystal Size into CLD from FBRM by Using Monte Carlo Analysis

In manufacturing process, it is necessary to measure change in CSD (Crystal Size Distribution) with time accurately because CSD is one of the most important indices that evaluate quality of products. FBRM (Focused Beam Reflectance Measurement) can measure CLD (Chord Length Distribution) in line, but CLD is different from CSD because of principle of FBRM. However, if CSD is determined beforehand, CLD can be calculated from the CSD with statistical method. First, when crystal shape is defined from the characteristic crystal size, the matrix of each crystal shape which transforms CSD into CLD in a uniform manner is calculated with Monte Carlo analysis. Characteristic crystal size is added to the variables defining chord length in order to avoid complex integrals and apply the change in crystal shape with characteristic crystal size to the transforming matrix. Secondly, CSD and CLD are actually measured in suspension of acetaminophen in ethanol and suspension of L-arginine in water to demonstrate the validity of 2 matrices. Lastly, these matrices are multiplied by some simple CSD models to test the properties of these matrices and demonstrate the utility of this transformation.

Slope reliability analysis based on Monte Carlo simulation and sparse grid method

In order to solve the problem of the reliability of slope engineering due to complex uncertainties, the Monte Carlo simulation method is adopted. Based on the characteristics of sparse grid, an interpolation algorithm, which can be applied to high dimensional problems, is introduced. A surrogate model of high dimensional implicit function is established, which makes Monte Carlo method more adaptable. Finally, a reliability analysis method is proposed to evaluate the reliability of the slope engineering, and is applied in the Sau Mau Ping slope project in Hong Kong. The reliability analysis method has great theoretical and practical significance for engineering quality evaluation and natural disaster assessment.

Accuracy Analysis for 6-DOF PKM with Sobol Sequence Based Quasi Monte Carlo Method

To improve the precisions of pose error analysis for 6-dof parallel kinematic mechanism( PKM)during assembly quality control,a Sobol sequence based on Quasi Monte Carlo( QMC) method is introduced and implemented in pose accuracy analysis for the PKM in this paper. The Sobol sequence based on Quasi Monte Carlo with the regularity and uniformity of samples in high dimensions,can prevail traditional Monte Carlo method with up to 98. 59% and 98. 25% enhancement for computational precision of pose error statistics.Then a PKM tolerance design system integrating this method is developed and with it pose error distributions of the PKM within a prescribed workspace are finally obtained and analyzed.

LS-SVM and Monte Carlo methods based reliability analysis for settlement of soft clayey foundation

A method which adopts the combination of least squares support vector machine（LS-SVM） and Monte Carlo（MC） simulation is used to calculate the foundation settlement reliability.When using LS-SVM,choosing the training dataset and the values for LS-SVM parameters is the key.In a representative sense,the orthogonal experimental design with four factors and five levels is used to choose the inputs of the training dataset,and the outputs are calculated by using fast Lagrangian analysis continua（FLAC）.The decimal ant colony algorithm（DACA） is also used to determine the parameters.Calculation results show that the values of the two parameters,and δ2 have great effect on the performance of LS-SVM.After the training of LS-SVM,the inputs are sampled according to the probabilistic distribution,and the outputs are predicted with the trained LS-SVM,thus the reliability analysis can be performed by the MC method.A program compiled by Matlab is employed to calculate its reliability.Results show that the method of combining LS-SVM and MC simulation is applicable to the reliability analysis of soft foundation settlement.

Approach of technical decision-making by element flow analysis and Monte-Carlo simulation of municipal solid waste stream

This paper deals with the procedure and methodology which can be used to select the optimal treatment and disposal technology of municipal solid waste （MSW）, and to provide practical and effective technical support to policy-making, on the basis of study on solid waste management status and development trend in China and abroad. Focusing on various treatment and disposal technologies and processes of MSW, this study established a Monte-Carlo mathematical model of cost minimization for MSW handling subjected to environmental constraints. A new method of element stream （such as C, H, O, N, S） analysis in combination with economic stream analysis of MSW was developed. By following the streams of different treatment processes consisting of various techniques from generation, separation, transfer, transport, treatment, recycling and disposal of the wastes, the element constitution as well as its economic distribution in terms of possibility functions was identified. Every technique step was evaluated economically. The Mont-Carlo method was then conducted for model calibration. Sensitivity analysis was also carried out to identify the most sensitive factors. Model calibration indicated that landfill with power generation of landfill gas was economically the optimal technology at the present stage under the condition of more than 58% of C, H, O, N, S going to landfill. Whether or not to generate electricity was the most sensitive factor. If landfilling cost increases, MSW separation treatment was recommended by screening first followed with incinerating partially and composting partially with residue landfilling. The possibility of incineration model selection as the optimal technology was affected by the city scale. For big cities and metropolitans with large MSW generation, possibility for constructing large-scale incineration facilities increases, whereas, for middle and small cities, the effectiveness of incinerating waste decreases.

Traction power substation balance and losses estimation in AC railways using a power transfer device through Monte Carlo analysis

The high dynamic power requirements present in modern railway transportation systems raise research challenges for an optimal operation of railway electrification. This paper presents a Monte Carlo analysis on the application of a power transfer device installed in the neutral zone and exchanging active power between two sections. The main analyzed parameters are the active power balance in the two neighbor traction power substations and the system power losses. A simulation framework is presented to comprise the desired analysis and a universe of randomly distributed scenarios are tested to evaluate the effectiveness of the power transfer device system. The results show that the density of trains and the relative branch length of a traction power substation should be considered in the evaluation phase of the best place to install a power transfer device, towards the reduction of the operational power losses, while maintaining the two substations balanced in terms of active power.

Analysis of typhoon wind hazard in Shenzhen City by Monte-Carlo Simulation

As one of the most serious natural disasters,many typhoons affect southeastern China every year.Taking Shenzhen,a coastal city in southeast China as an example,we employed a Monte-Carlo simulation to generate a large number of virtual typhoons for wind hazard analysis.By analyzing 67-year historical typhoons data from 1949 to 2015 using the Best Track Dataset for Tropical Cyclones over the Western North Pacific recorded by the Shanghai Typhoon Institute,China Meteorological Administration(CMASTI),typhoon characteristic parameters were extracted and optimal statistical distributions established for the parameters in relation to Shenzhen.We employed the Monte-Carlo method to sample each distribution to generate the characteristic parameters of virtual typhoons.In addition,the Yah Meng(YM)wind field model was introduced,and the sensitivity of the YM model to several parameters discussed.Using the YM wind field model,extreme wind speeds were extracted from the virtual typhoons.The extreme wind speeds for different return periods were predicted and compared with the current structural code to provide improved wind load information for wind-resistant structural design.

Free Energy Level Correction by Monte Carlo Resampling with Weighted Histogram Analysis Method

Free energy calculations may provide vital information for studying various chemical and biological processes.Quantum mechanical methods are required to accurately describe interaction energies,but their computations are often too demanding for conformational sampling.As a remedy,level correction schemes that allow calculating high level free energies based on conformations from lower level simulations have been developed.Here,we present a variation of a Monte Carlo(MC)resampling approach in relation to the weighted histogram analysis method(WHAM).We show that our scheme can generate free energy surfaces that can practically converge to the exact one with sufficient sampling,and that it treats cases with insufficient sampling in a more stable manner than the conventional WHAM-based level correction scheme.It can also provide a guide for checking the uncertainty of the levelcorrected surface and a well-defined criterion for deciding the extent of smoothing on the free energy surface for its visual improvement.We demonstrate these aspects by obtaining the free energy maps associated with the alanine dipeptide and proton transfer network of the KillerRed protein in explicit water,and exemplify that the MC resampled WHAM scheme can be a practical tool for producing free energy surfaces of realistic systems.

A Gamma Analysis Approach to Determine Optimal Parameters for Monte Carlo Simulation of 6MV Varian Clinac iX Photon Beam

Monte Carlo （MC） method is the gold standard dose calculation algorithm. Determination of the electron beam parameters for MC simulation is often estimated using trial and error methods. However, this can be tedious and time-consuming. This paper aims to validate MC simulated data using 1D gamma analysis for 6MV photon beam to obtain the optimal parameters. BEAMnrc codes were used to generate phase space files for conventional field sizes 10 × 10 cm^2, 6 × 6 cm^2, 4 × 4 cm^2 and small field sizes 2 ×2 cm^2, 1 ×1 cm^2, 0.5 ×0.5 cm^2. For conventional field sizes, simulations were benchmarked against Golden Beam Data （GBD）. Simulations for small fields were benchmarked against measurements obtained using EDGE Detector and PTW Diode SRS detector in a Sun Nuclear 3D scanner. Dose profiles in water were calculated using DOSXYZnrc codes. Initial reference parameters were approximated using average percentage dose differences of different mean electron energy and electron beam radial distribution （Full Width at Half Maximum, FWHM）. Subsequently, the optimal parameters were validated by 1D gamma analysis using varying gamma criteria from γ3%%/0.3mm to γ2.0%/2.0mm for depth dose and lateral dose profiles. Comparisons were performed along the central region at depth dose 1.6 cm . Optimal parameters were found to be unique for small field sizes. As field size decreases, smaller FWHM were required to match measured data. By using 95% passing rate, a generic set of optimal electron beam parameters in a MC model for all field sizes could be accurately determined. Our findings provide MC users a set of optimal parameters with sufficient accuracy for MC simulation work.

Monte Carlo Analysis of Nodes Deployment in Wireless Sensor Network Using Range-Free Location Methods

A Monte Carlo Analysis of nodes deployment for large-scale and non-homogeneous wireless sensor networks, has been done. Through simulations of random deployments of nodes over a square area using different densities, assuming that our network is composed by Anchor nodes （special sensors with known position） and simple Sensor nodes, the latter are supposed to estimate their own position after being placed within the coverage area with the minimum Anchor nodes needed to ＇feed＇ them with the necessary information. The goal is then to assist decision-makers in selecting among different alternatives to deploy the networks, according to resources features and availability, hence this method provides an estimate value of how many Anchor nodes should be deployed in a given area to trigger the location algorithm in the greatest possible number of Sensor nodes in the network.

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。

大型复杂系统平均寿命评定的Monte Carlo方法

随着现代武器系统和工程系统的大型化与复杂化趋势,大型复杂系统可靠性评定是急待解决的问题,工程中常用可靠性指标有可靠度和平均寿命,平均寿命指标由于直观、物理概念清晰,使用更加方便。基于可靠性框图建模,采用最小路集计算分析,提出了大型复杂系统平均寿命评定的Monte Carlo方法。解决了有限样本条件下,大型复杂系统平均寿命评定问题,对工程中大型复杂系统平均寿命评定具有重要应用价值。

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。

基于Monte-Carlo模拟的土壤环境重金属污染评价法与实例研究

综合分析了现行确定性土壤环境质量评价中的不足,将Monte-Carlo模拟引入地累积指数模型中,并进一步通过数据的挖掘和对土壤中各重金属的生态风险差异的考量,构建了基于不确定性理论的土壤环境质量评价法.将所建方法应用于实例区域,分别构建重金属的实测含量参数和其对应背景值参数的概率分布模型,设定模拟中最大实验量为1 000,置信区间为95%,抽样方法为拉丁超立方(Latin hypercube sampling),得到基于不确定性理论的土壤环境质量评价结果:评价区域土壤中各重金属的污染排序为Cd>Ni>Zn>Cu>Cr,其中,Cd隶属于严重污染等级的概率高达98.1%;Ni和Zn有着明显的空间分布差异,并且属于严重污染的概率也分别达84.5%和87%;Cr和Cu的污染等级相对较低.而后,将所得结果与现行的确定性模型评价结果进行了对比分析,结果表明:所建基于不确定性的评价模型具有更好的评级分辨力,并可更全面、真实地表征该区域土壤重金属的污染特征和概率风险水平.

元分析中统计异质性的检验:一项Monte Carlo研究

元分析中,异质性检验常为模型的选择和调节分析提供重要的参考依据.有多种方法和途径对异质性进行评价,包括Q,H,I2和似然比检验.通过模拟研究比较,发现单一的Q统计量可能导致错误的模型选择,H和I2值没有因为估计方法(矩估计和似然估计)的不同而对异质性的检验结果存有较大差异,是一个有效可靠的辅助统计量;Q统计量与似然比检验相比,在I类错误率上控制较严格,但统计功效不如似然比检验.研究结果表明,可以选用Q统计量结合报告H或I2值的方式作为异质性检验的最佳方案.

影响b值计算误差的Monte Carlo实验研究

本文假设地震的发生与时间的关系遵循稳态泊松模型,假设地震震级M服从参数为1/β的指数分布,其中β=b/loge,在此基础上生成地震目录。用最小二乘法估算b值,分别从样本数量、震级间隔、震级误差三方面分析b值误差的大小。统计分析结果表明,b值的标准偏差随着样本数量的增多而减小;随着震级间隔的增大而减小;震级误差使b值的标准误差变大。本文可以为利用真实地震目录求b值时选择适当的方法提供参考。