预测精馏塔板相界面积的时间Monte Carlo方法

采用时间Monte Carlo模拟技术,利用随机试验的方法计算精馏塔板上气泡的稳态粒度分布,预测的结果与实验测量的数据相当一致,证明时间Monte Carlo方法不仅计算简单,应用方便,而且能够较准确地预测精馏塔板的相界面积,是一个很有发展前景的方法.     

高分子构象模拟研究中的Monte Carlo方法

介绍了Monte Carlo方法及其特点,进而分析了Monte Carlo用于高分子模拟的优势,并描述了两类模拟模型。论文重点综述了近年来Monte Carlo方法在高分子构象模拟中的一些研究与应用,并展望了Monte Carlo方法在高分子构象模拟中的发展趋势和前景。     

基于Monte Carlo方法改进的化学反应动力学计算机模拟

在Monte Carlo方法及其改进方法的基础上,进一步改进了化学反应动力学方程计算机模拟算法.改进后的算法延续了原方法编制模拟程序方便等优点,并提高了计算机模拟的稳定性、精确性,克服了由于Monte Carlo方法是一种概率方法而导致模拟结果具有随机性的缺点.结合工业应用中常见的平行、连续、对峙和综合化学反应进行了模拟计算,模拟结果与这些化学反应的解析解相对误差小于0.1%.     

催化裂解过程分子尺度反应动力学模型研究

以工业数据为基础,运用结构导向集总方法来构造烃分子,对催化裂解原料油进行了分子尺度上的Monte Carlo模拟.在深入研究催化裂解反应机理的基础上,以原料油模拟产生的分子矩阵作为反应物分子,将结构导向集总方法与Monte Carlo方法相结合,建立了催化裂解过程分子尺度的反应动力学模型.结果表明:Monte Carlo方法可以在分子尺度上实现对催化裂解原料较好的模拟,产品产率和汽油组成与实际值能较好地拟合.且随着虚拟分子数的增加,对原料油性质和反应结果的模拟计算精度提高;模型具有较好的适应性和外推性.     

丙烯腈共聚物序列分布的Monte Carlo模拟

通过Monte Carlo方法，对不同共聚单体的聚丙烯腈组成进行了模拟。通过比较．与文献中提供的实验结果基本一致。同时模拟了衣康酸(1A)、丙烯酸(AA)、甲基丙烯酸(MAA)分别与丙烯腈(AN)在不同配比下共聚物的序列分布，结果表明：在Monte Carlo模型中，可以通过控制单体的配比来控制序列分布，而在实际的合成中，要获得均匀的序列结构，就可以通过降低第二单体投料比法或滴加单体法来实现。     

考虑参数相关的腐蚀管道可靠性评价

建立了腐蚀缺陷参数相关情况下长输管道腐蚀可靠性模型,以此基于Monte Carlo模拟计算管道失效概率.应用非参数型的秩相关系数综合考虑了参数本身的不确定性和模型所用公式联合作用的影响,对影响管道失效的因素进行参数敏感性分析.结果表明:简单假设缺陷初始深度和长度相互独立会得到较为乐观的结果.随着相关性增加,极限状态函数...     

硬球链流体在平板和硬球表面分布的密度泛函理论

采用Yethiraj和Woodward的密度泛函理论方法,结合胡英和刘洪来等发展的硬球链流体状态方程,得到了自由连接硬球链流体在平板狭缝中和球形固体颗粒表面附近的密度分布表达式,并计算了在两平行壁所组成的狭缝中和直径大小不同的球形固体颗粒周围硬球链分子的链节密度分布.理论计算结果与作者采用Dickman 和Hall 的方法进行Monte Carlo计算机模拟结果非常吻合.颗粒直径对链状分子的密度分布有一定的影响,随着固体颗粒直径的增加,靠近颗粒表面附近的链节密度降低.     

处理多分散颗粒凝并和冷凝/蒸发问题的多重Monte Carlo算法

提出一个新的多重Monte Carlo (MMC) 算法来求解同时考虑凝并和冷凝/蒸发的通用动力学方程 (GDE),该算法基于时间驱动, 模拟过程中保持模拟颗粒数目不变和计算区域体积不变. 描述了时间步长确定方法, 同时处理凝并和冷凝/蒸发的方案. 针对常凝并核和常冷凝核, 常凝并核和线性冷凝核, 线性凝并核和线性冷凝核三种特殊工况, MMC算法模拟了颗粒尺度分布函数的时间演变, 与理论分析解进行了比较, 表明MMC算法能解决普通Monte Carlo算法的计算精度和计算代价不能协调的矛盾, 具有较小的计算代价和较高的计算精度, 能够适用于工程应用.     

高压反向人孔法兰结构的分析

参数化分析能准确地反映设计条件中各个参数变量对应力集中区域可靠性的影响,运用ANSYS分析软件对高压反向人孔法兰结构进行疲劳强度校核,再通过输入变量参数运用Monte Carlo method(蒙特·卡罗方法)进行变量的可靠性分析,在找到最主要的影响因素时将结构的失效概率控制在预定水平内,从而规避了常规设计无法控制的设计风险,在保证设计安全的条件下达到更加经济的效果。     

晶粒正常生长的Monte Carlo模拟

本文建立了晶界能各向同性情况下晶粒生长的二维Monte Carlo模型,并对等温情况下的晶粒生长过程进行了模拟。在模拟过程中,对传统Monte Carlo方法中能量与概率统计方法进行了改进。为了更加直观地显示出晶粒生长过程中系统能量的变化,统计了在整个晶粒生长过程中能量的变化趋势,结果与晶粒尺寸变化相符合。模拟得到的晶粒生长指数在0.35~0.45之间,与理论值相符,证明了改进方法的可靠性。     

Estimation of parameters in monte carlo modelling

This paper presents a general method for estimating model parameters from experimental data when the model relating the parameters and input variables to the output responses is a Monte Carlo simulation. From a statistical point of view a Bayesian approach is used in which the distribution of the parameters is handled in discretized form as elements of an array in computer storage. The stochastic nature of the Monte Carlo model allows only an estimate of the distribution to be calculated from which the true distribution must then be estimated. For this purpose an exponentiated polynomial function has been found to be useful. The method provides point estimates as well as joint probability regions. Marginal distributions and distributions of functions of the parameters can also be handled. The motivation for exploring this alternative parameter estimation technique comes from the recognition that for some systems, particularly when the underlying process is stochastic in nature, Monte Carlo simulation often is the most suitable way of modelling. As such, the Monte Carlo approach increases the range of problems which can be handled by mathematical modelling. The technique is applied to the modelling of binary copolymerization. Two models, the Mayo-Lewis and the Penultimate Group Effects models, are considered and a method for discriminating between these models in the light of sequence distribution data is proposed.     

在役LNG接收站的SIS系统再验证

广东大鹏LNG接收站作为中国最早投用的LNG接收站,在5年的高负荷运行后中新增并改造了部分设备及功能安全回路(SIF),为确保接收站功能安全仪表系统(SIS)的完整性与可靠性以及高负荷生产的可用性,对所有生产设施及管线场站进行了HAZOP分析,并在HAZOP分析的基础上进行了SIL定级及再验证(re-validation)工作。本文以SIL再验证工作为例介绍SIL验算/再验证在在役装置中的应用,以及如何通过敏感性分析优化SIS系统配置与校验管理,满足企业风险可接受标准,最后总结并展望了实施SIL验算工作中的技术难点和未来的技术方向。     

The use of Monte Carlo simulation to evaluate the optical properties of polyester fabric treated with titanium dioxide nanopigments

The current study utilises Monte Carlo simulation and Mie scattering theory to estimate the reflectance spectra of fabric coated with titanium dioxide nanopigments of various diameters and concentrations. Image processing was carried out and experimental data were gathered to evaluate the performance of Monte Carlo simulation. The distribution and location of the nanopigments on the surface of fabric were determined using the Monte Carlo method. Reflection of the fabric was calculated based on Monte Carlo simulation with the partitive mixing method and Mie theory. According to the experimental and simulation results, the reflectance of coated samples was increased by increasing the concentration and number of titanium dioxide nanoparticles. There was a good match between the results obtained by Monte Carlo simulation and the experimental results. For coated samples (dTiO₂: 500 nm), the root mean square error between measured and predicted reflectance by the Monte Carlo and partitive mixing method and by Monte Carlo and Mie theory was 0.022 and 0.0078, respectively. The results indicate that the performance of the Monte Carlo and Mie method was better than that of the Monte Carlo and partitive mixing method. According to t-test analysis, there was no statistically significant difference between the experimental data and Monte Carlo simulation.     

安全仪表系统的功能安全评估现状

通过对比国内外安全仪表系统功能安全评估的发展状况,从功能安全标准、HAZOP(Hazard and Operability)分析、SIL(Safety Integrity Level)定级、SIL验证和SIL评估与认证5个方面进行了研究。发现我国缺乏与自身实际情况相结合的功能安全标准;在HAZOP、SIL定级和SIL验证方面,仍处在定性研究阶段,缺乏相关的失效数据库和与实际相结合的研究;还没有建立与功能安全评估相关的认证与服务机构。研究结果可为功能安全评估今后的发展提供一定的指导作用。     

Confidence interval estimation of Weibull lower percentiles in small samples via Bayesian inference

Weibull distribution has been vastly used for modeling fracture strength of ceramic and composite materials. Confidence interval estimation of Weibull parameters and percentiles in small samples has been an important concern due to high experimental costs. It was shown previously that in classical inference the Maximum Likelihood Estimation Method is the best method among several alternatives for estimating 95% one-sided confidence lower bounds on the 1st and 10th Weibull percentiles, namely A-basis and B-basis material properties. This study proposes the Bayesian Weibull Method as an alternative using the information that ceramic and composite materials have increasing failure rates, which requires the Weibull shape parameter to be at least 1. Through Monte Carlo simulations, it is shown that the performance of the Bayesian Weibull Method is superior in that it achieves the precision levels of the Maximum Likelihood Estimation Method with significantly smaller sample sizes.     

Analysis of four Monte Carlo methods for the solution of population balances in dispersed systems

Monte Carlo (MC) constitutes an important class of methods for the numerical solution of the general dynamic equation (GDE) in particulate systems. We compare four such methods in a series of seven test cases that cover typical particulate mechanisms. The four MC methods studied are: time-driven direct simulation Monte Carlo (DSMC), stepwise constant-volume Monte Carlo, constant number Monte Carlo, and multi-Monte Carlo (MMC) method. These MC's are introduced briefly and applied numerically to simulate pure coagulation, breakage, condensation/evaporation (surface growth/dissolution), nucleation, and settling (deposition). We find that when run with comparable number of particles, all methods compute the size distribution within comparable levels of error. Because each method uses different approaches for advancing time, a wider margin of error is observed in the time evolution of the number and mass concentration, with event-driven methods generally providing better accuracy than time-driven methods. The computational cost depends on algorithmic details but generally, event-driven methods perform faster than time-driven methods. Overall, very good accuracy can be achieved using reasonably small numbers of simulation particles, O(10³), requiring computational times of the order 10²−10³ s on a typical desktop computer.     

Reducing Statistical Noise and Extending the Size Spectrum by Applying Weighted Simulation Particles in Monte Carlo Simulation of Coagulation

The direct simulation Monte Carlo (DSMC) method is widely utilized to simulate microscopic dynamic processes in dispersed systems that give rise to the population balance equation. In conventional DSMC approaches, simulation particles are equally weighted, even for broad size distributions where number concentrations in different size intervals are significantly different. The resulting statistical noise and limited size spectrum severely restrict the application of these DSMC methods. This study proposes a new Monte Carlo (MC) method, the differentially weighted time-driven method, which captures the coagulation dynamics in dispersed systems with low noise and is simultaneously able to track the size distribution over the full size range. Key elements of this method include constructing a new jump Markov process based on a new coagulation rule for two differentially weighted simulation particles, and restricting the number of simulation particles in each size interval within prescribed bounds. The method is validated by using an ideal coagulation kernel with a known analytical solution and a real coagulation kernel for which an accurate solution can be found numerically (self-preserving particle size distribution in the continuum regime).     

Comparative study of estimation methods for continuous time stochastic processes

In this paper we investigate the finite sample performances of five estimation methods for a continuous-time stochastic process from discrete observations. Applying these methods to two examples of stochastic differential equations, one with linear drift and state-dependent diffusion coefficients and the other with nonlinear drift and constant diffusion coefficients, Monte Carlo experiments are carried out to evaluate the finite sample performance of each method. The Monte Carlo results indicate that the differences between the methods are large when the discrete- time interval is large. In addition, these differences are noticeable in estimations of the diffusion coefficients.     

高炉鼓风引风系统安全完整性等级评估

对某化工装置脱酸炉鼓风引风系统进行安全仪表系统的安全完整性等级评估。采用保护层分析方法进行等级确定,利用可靠性框图进行验证,得出现有安全仪表联锁回路的安全完整性等级没有达到要求的安全完整性等级目标的结论,并提出了对应的安装建议和维护要求。     

基于最小维修的石化安全设备区间截尾寿命数据分析

在石化安全关键设备寿命截尾数据的可靠性评估过程中,为避免传统可靠性评估方法未考虑维修对故障间隔时间的影响,以及中值填充法误差较大的缺点,本文提出了一种逆变换区间截尾数据填充方法。首先,在可修系统基于最小维修的假设下,通过非齐次泊松过程描述系统的故障趋势,利用逆变换填充得到监测区间的缺失数据;随后根据蒙特卡罗期望最大化算法,获得填充数据的参数估计值。通过蜡油加氢装置紧急泄压阀的案例分析,该算法能够很好地融合已有数据,得到的形状参数估计值偏差与中值填充法相比缩小4%以上,从而验证了该算法的有效性;这有助于安全关键设备的定量化完整性管理,保障石化装置平稳运行。