安全仪表系统中参数满足某分布区间时的SIL评估方法

在安全仪表系统的安全完整性水平评估过程中,参数的不确定性是影响评估结果准确程度的重要原因之一.重点讨论当参数满足某种分布区间时的一种SIL评估方法,即基于cauchy分布的Monte Carlo方法,并通过实例分析该方法对提高评估结果准确性的作用,提出将Monte Carlo方法应用于区间计算.并在实践中推广.     

陶瓷断裂强度Weibull统计分析的可靠性

脆性陶瓷材料的断裂强度通常表现出显著的离散性,其统计性质需要借助于一个Weibull分布函数加以描述;而作为Weibull分布函数中的一个重要参数,Weibull模数则通常用于描述断裂强度实测值的离散程度。从统计学上说,对于同一种材料,采用点估计方法由不同的强度样本得到的Weibull模数估计值之间总是会存在一些偏差,这就导致了两个基本问题的出现,即：(1)如何评估Weibull模数估计值与其真实值之间的差异？(2)采用多大容量的强度样本才可能获得较为可靠的Weibull模数值？此外,断裂强度服从Weibull分布这一说法仅仅是一个假设,在断裂强度并不服从Weibull分布的情况下,采用Weibull分布描述强度数据是否可以对材料的可靠性给出准确评价？在过去几十年间,学者们借助于Monte Carlo模拟技术对上述问题进行了较为深入的研究。本文简要回顾了这些研究所取得的成果,以期对Weibull分布在陶瓷材料断裂强度统计性质研究中应用的可靠性做出一个较为完整的描述。     

基于失效估计的石化安全设备测试策略优化

针对利用传统的可靠性模型估计设备未来失效时间,因制定设备的检验与测试策略存在误差较大和计算复杂等工程困难,提出一种新的拓展波利亚过程模型。通过拓展波利亚过程描述设备的失效趋势,利用遗传算法得到拓展波利亚模型参数估计值;建立失效时间估计模型对设备失效时间进行估计;以催化裂化装置中滑阀为例进行数值模拟计算,得到该模型失效时间估计误差与传统的非齐次泊松过程和Weibull分布相比分别缩小了5.75%和8.46%。结果表明所提算法优化了催化裂化装置中滑阀设备的功能测试策略,可为设备的完整性管理提供理论指导。     

不确定条件下的湿法炼锌除铜过程机会约束优化控制

除铜过程是湿法炼锌净化工艺中的重要步骤,受生产环境多变、矿源多样、机理复杂等因素的影响,除铜过程存在不确定性,影响生产的稳定性和可靠性。针对除铜过程中入口溶液流量、底流返回量和入口铜离子浓度的不确定性,造成出口铜离子浓度不稳定的问题,研究不确定条件下的除铜过程机会约束优化控制方法。首先分析了除铜过程的不确定性,利用统计学方法分析不确定参数的分布特性,引入了机会约束的思想,将不确定条件下的除铜过程优化问题建模为机会约束优化问题。然后采用可行域映射方法,将机会约束优化问题转化为非线性规划问题。最后,使用序列二次规划求解该非线性规划问题。Monte Carlo仿真验证了该方法的有效性,可以提高系统的鲁棒性。     

基于热传导反问题的各向异性材料热物性预测方法

采用不同方法对基于热传导反问题的固体热导率预测进行了研究。分别采用采用不同方法对基于热传导反问题的固体热导率预测进行了研究。分别采用Bayesian统计方法、Levenberg-Marquardt和遗传算法对二维各向异性材料的热物性进行了预测;并进行了分析比较。研究结果表明;Bayesian方法中热传导反问题的解是其后验概率密度的数学期望;而后验概率密度函数（PPDF）通过测定的温度进行计算获得;用Markov chain Monte Carlo算法计算后验状态空间以得到未知热导率的统计估计;采用Metropolis-Hasting算法进行数据采样构造Markov chain;并截取收敛后的样本进行分析。遗传算法是一种相对较新的用于最优化估计的方法;也可以用于求解反问题。     

加速Monte Carlo分子模拟收敛的能量选择取样法

为提高Monte Carlo分子模拟的取样效率,加速模拟过程的收敛,本文提出了根据粒子能量进行取样的方法。通过对凝固点附近的L-J流体的模拟,将能量选择取样法与Metropolis取样法以及力偏倚取样法的收敛性和模拟结果作了比较,表明能量选择取样法的收敛速度显著高于Metropolis取样法,与力偏倚取样法相当,而计算量比力偏倚取样法小。     

基于改进不完全微分算法的ARM温度控制系统设计

为了使温度控制器的动态性能和稳态精度满足控制系统的要求,提出一种改进不完全微分控制算法,温度测量采用Pt100,采用LPC2103制作温度控制器。在Matlab仿真的基础上确定控制参数,电阻炉的温度控制实验结果表明该温度控制器满足系统控制要求。     

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。     

蒙皂石层间结构与性质关系的分子模拟研究进展

综述了计算机模拟中的分子力学、Monte Carlo和分子动力学模拟方法及其在蒙皂石层间结构中的应用进展,涉及粘土-水-离子体系的位能函数、粘土的水化和层间结构、热力学性质、物理机械性质和柱撑蒙脱石等各个方面.指出分子模拟对蒙皂石层间分子行为的基础研究将发挥重要作用.     

CO_2/CH_4在活性炭上吸附与分离的分子模拟

Monte Carlo模拟（GCMC）研究了CO2和CH4在活性炭中的吸附情况。氢气和二氧化碳分子被模拟作Ken-nard-Jones球体,活性炭用一个裂缝气孔模型代替。研究了压力、温度、孔径活性炭对CO2（以CH4为基准）的选择性的影响。结果表明,低压、低温、孔径越小,选择性越大,即对分离CO2和CH4有利;233 K、孔径为2.29 nm以及低压下选择性达到10,此时分离效果较好。     

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。     

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.     

Model Development and Parameter Estimation for the Oxidation of Pyrrhotite‐Containing Rock Surfaces

A novel experimental method was developed for the evaluation of the biotic oxidation rate of waste rock containing sulphide minerals. Sized waste rock samples were inoculated with an Acidithiobacillus ferrooxidans suspension and sparged with discontinuing humidified air to yield the oxygen consumption rate. A kinetic/mass transport model was proposed based on oxidation of pyrrhotite. Bayesian statistical analysis using the Metropolis‐Hastings algorithm showed that at ambient oxygen concentration the mean (i.e., estimated) values of the initial oxygen flux, the reaction order, the oxygen diffusion coefficient through the oxidation product layer, and the surface reaction rate constant were 1.3×10^?7 mol/m².s, 0.55, 2.91×10^?13 m²/s and 3.23×10^?7 mol^0.45/m^0.35.s, respectively.     

A general framework for preventive maintenance optimization in chemical process operations

Chemical process reliability has become more recognized both in terms of its impact on economics, and for providing academically challenging problems. In this work, we give an overview of some of the major challenges in formulating and optimizing preventive maintenance. As a result, we propose a general framework for preventive maintenance optimization that combines Monte Carlo simulation with a genetic algorithm.

This proposed approach has distinct advantages. When applied to opportunistic maintenance problems, the method developed overcomes demonstrated shortcomings with analytic or Markov techniques in terms of solution accuracy, versatility, and tractability. The framework is easily integrable with general process planning and scheduling, and it provides sensitivity analysis. Furthermore, a genetic algorithm combines well with Monte Carlo simulation to optimize a non-deterministic objective function.     

Application of Monte‐Carlo simulation to estimate the kinetic parameters for pyrolysis—Part I

A mathematical model was developed to represent pyrolysis. The components of primary and secondary pyrolysis reactions were simply lump into different groups and were represented through a set of pseudo‐first‐order reactions. This study presents an algorithm to estimate the kinetic parameters using Monte‐Carlo (MC) simulation. The combination of an analytical reaction model and the MC simulation technique rapidly generates a large number of numerical values. Results show that MC‐simulated data and experimental data are in fair agreement. Though the technique developed in this study proved to have potential, more experimental data are needed to check the robustness of the model. © 2011 Canadian Society for Chemical Engineering     

Monte Carlo simulations of properties of side‐chain liquid‐crystal polymers

This paper presents a computational conformational study of side‐chain liquid‐crystal polymers to predict the optical and liquid‐crystalline properties of a series of polyepicholorohrdrin, polyacrylate, poly(methyl acrylate), and polystyrene‐based side‐chain polymers using a Monte Carlo simulation method. Some of the simulated side‐chain polymers were synthesised by chemical modification or polymerisation. The predictive capability of the orientational order parameter has been utilised to predict the liquid‐crystalline isotropic transition temperature of the investigated polymers, which was used to infer the type of distribution in the synthesised polymers. The predictive possibilities of this criterion are explored in the estimation of the nematic–isotropic transition temperatures of the simulated polymers. Evidence is presented to suggest that for side‐chain liquid‐crystalline polymer molecules the nematic to isotropic transition occurs when the order parameter reaches a value of 0.43 according to Maier–Saupe mean‐field theory. Copyright © 2006 Society of Chemical Industry     

矿柱的可靠度分析

采用蒙特卡洛法对矿柱的可靠度进行了分析计算。根据莫尔强度理论建立了矿柱在多向应力状态下的极限状态方程,据矿和实测结果,采用柯尔莫柯洛夫法拟合检验了矿柱应力的变量分布类型和参数估计。     

SIMULATION AND ESTIMATION OF LONG MEMORY CONTINUOUS TIME MODELS

Abstract. Some general properties of long memory continuous time processes are recalled or proved. Methods of simulation are studied. A comparison with the usual discrete time autoregressive fractionally integrated moving-average filter is made and illustrations are provided. Then, two methods of estimation of the parameters of such a model from a discrete sample are studied, both theoretically and empirically, with Monte Carlo experiments.     

基于有限元法的高压球罐强度可靠性分析

根据可靠性理论和蒙特卡罗法原理,结合ANSYS软件,以高压球罐为研究对象进行可靠性分析。依据实际工况,判定该研究对象的设计参数服从正态分布,通过对建立的模型进行500次随机抽样分析,求得对其可靠性影响较大的因素是屈服强度和工作压力。结果表明,该模型可以有效地反映压力容器的实际情况,为其结构可靠性分析提供参考。