氨合成反应非解离机理的Monte Carlo模拟

用Ｍｏｎｔｅ Ｃａｒｌｏ方法对氨合成反应的非解离机理进行了模拟，模拟结果表明，当氨合成反应按非解机理进行时，将不存在动力学相奕和反应速率的自振荡现象；模拟得到的反应速率随反应物分压的变化规律与理论推导结果完全一致。     

Monte Carlo方法与计算机模拟应用研究

介绍了Monte Carlo方法,提出其在模拟Buffer问题时存在的一个问题,并给出改进的方法;提出了用Monte Carlo方法产生任意分布随机变量的原理及方法,并对Beta分布和标准正态分布随机变量进行了计算机模拟和效果检验。     

薄层中药物释放的Monte Carlo模拟

描述了一种用于研究药物由搽剂经角质层转运至受体过程的直接Monte Carlo模拟方法。对角质层药物浓度为零和搽剂与角质层药物浓度处于平衡两种初始条件下的药物转运过程进行了模拟。与解析Laplace变换结合数值求逆的结果比较表明,这种Monte Carlo模拟方法准确、可靠、方便,很容易用于更复杂的体系。     

Monte Carlo方法模拟超临界流体性质

综述了近年来Ｍｏｎｔｅ Ｃａｒｌｏ方法在计算超临界流体性质方面的应用。首先对计算过程涉及的系综选择、取样方法和参娄优化等问题进行了探讨，然后对各文献模拟计算超临界流体径向分布函数、团簇大小、化学位和溶解度的结果进行了比较。最后简述Ｍｏｎｔｅ Ｃａｒｌｏ方法在该领域广泛应用所存在的困难和前景。     

壳聚糖分子链序列分布的Monte Carlo模拟

为了掌握不同脱乙酰度壳聚糖分子链上不同结构单元的序列分布以及不同糖苷键的相对含量,通过Monte Carlo方法, 对壳聚糖分子的序列分布进行了计算机模拟,求出了(GlcNac)i、(GlcN)i的数量分布,并求出了GlcNatc-GlcNac、GlcNac-GlcN、GlcN-GlcN糖苷键的相对含量及其关联式(均为DD≥55%):FA-A9=9.949 49-2.001 61×DD+O.010 02×DD2、FA·D= 0.336 29+1.996 44×DD-0.019 96×DD2、FD-D=-0.168 09+0.002 78×DD+0.009 97×DD2。结果表明,随着脱乙酰度的提高,(ClcNac)i和(GlcN),分布的差别越来越明显,并且(GlcNac)i分布越来越窄,而(GlcN)i的分布则越来越宽;GlcNac-Gl cNac糖苷键的相对含量(FA-A)、GlcNac-GlcN糖苷键的相对含量(FA-D)均随着脱乙酰度(DD)的增大而减小,而GlcN-GlcN糖苷键的相对含量(FD-D)则随着DD的增大而增大,但它们都不呈线性关系。通过与文献值对比,表明模拟具有很高的精度。该算法为壳聚糖降解动力学以及降解产物分子量分布的研究提供了相应的基础。     

两平板间大分子吸附的Monte Carlo研究

采用Ｍｏｎｔｅ Ｃａｒｌｏ方法和立方格模型，分别模拟了限定在两平板之间的各种长度分子链构型，研究了它们在两平板表面的吸附行为，并指出了若干情况下的构型特点，所得结果与其他作者的数据进行了比较，并得出了相应的结论。     

大分子蠕动的Monte Carlo模型及计算方法

高分子链分子量巨大而且分散,结构复杂多变,存在大量不确定的问题,给理论和实验研究造成许多困难。本文建立了一种基于高分子Monte Carlo模拟算法,分析分子蠕动阻力的模型。用链动力学法构造8配位点键长涨落格子链多链体系,通过高分子链的运动使任意的初始有序态演化到平衡态,可同时获得体系的动态和静态性质。将重要性抽样法和高分子多链体系的链动力学构造法,在键长涨落模型中结合起来,形成多链体系的链动力学求解法。引入空格扩散算法,用以研究高浓度态的高分子体系。统计平衡后元胞内高分子多链体系在链动力学算法作用下蠕动失败机率,对高聚物多链体系内分子蠕动的困难程度的定量模拟,能更直观分析高分子玻璃化转变的现象。     

受限真实链的非格子模型Monte Carlo模拟

探讨用高分子链的实际键长、键角、旋转异构态和无扰链时的条件概率,逐链段生成样本高分子链,研究受限真实链分子构象统计的可能性。并就两板间、圆管内真实链的计算结果与标度律的一些理论推导结论比较。结果表明:刚性近似之下,用无扰态时的条件概率生成样本高分子链的Monte Carlo模拟,其样本库能真实地重现平衡态时受限真实链的构象分布,适用于受限真实链的构象统计研究。     

Monte Carlo simulation program for ecosystems

A Monte Carlo computer simulation program is designed in order to describe the spatial and time evolution of a population of living individuals under preassigned environmental conditions of energy. The simulation is inspired by previous techniques developed in physics--in particular, in molecular dynamics and simulations of liquids--and it already provides some new insights regarding macroscopic deterministic models in ecology and concerning eventual control of artificial biomass production plants.     

Monte Carlo simulation on transputer arrays

A Monte Carlo simulation of a simple statistical physics model is decomposed onto a multi-processor (transputer) array in two essentially different ways: using ‘geometric’ and ‘algorithmic’ concurrency. The geometric decomposition (in which each processor handles a small sector of the physical system) is characterized by high efficiency in utilization of processors, and relative simplicity in programming. The algorithmic decomposition (in which each processor handles a small sub-task of the full algorithm, typically in a pipelined mode) is characterized by greater flexibility in the data-size (size of the physical system) and minimal memory requirements for a majority of the processors in the array. These assertions are made concrete in relation to our specific problem (a two-dimensional spin system simulation) which is, in many respects representative of a wide class of problems of interest to theoretical physicists.     

Interval approach challenges Monte Carlo simulation

Intervals are used to represent imprecise numerical values. Modelling uncertain values with precise bounds without considering their probability distribution is infeasible in many applications. As a solution, this paper proposes the use of probability density functions instead of intervals; we consider evaluation of an arithmetical function of random variables. Since the result density cannot in general be solved algebraically, an interval method for determining itsguaranteed bounds is developed. This possibility challenges traditional Monte Carlo methods in which only stochastic characterizations for the result distribution, such as confidence bounds for fractiles, can be determined.     

Performance modeling using Monte Carlo simulation

Cycle accurate simulation has long been the primary tool for micro-architecture design and evaluation. Though accurate, the slow speed often imposes constraints on the extent of design exploration. In this work, we propose a fast, accurate Monte-Carlo based model for predicting processor performance. We apply this technique to predict the CPI of in-order architectures and validate it against the Itanium-2. The Monte Carlo model uses micro-architecture independent application characteristics, and cache, branch predictor statistics to predict CPI with an average error of less than 7%. Since prediction is achieved in a few seconds, the model can be used for fast design space exploration that can efficiently cull the space for cycle-accurate simulations. Besides accurately predicting CPI, the model also breaks down CPI into various components, where each component quantifies the effect of a particular stall condition (branch misprediction, cache miss, etc.) on overall CPI. Such a CPI decomposition can help processor designers quickly identify and resolve critical performance bottlenecks.     

蒙特卡罗法在调制解调中的应用

在加性高斯噪声干扰条件下的2FSK和16QAM调制解调方法基础上,根据蒙特卡罗仿真方法基本思想,建立在加性噪声干扰下的相关检测系统蒙特卡罗仿真模型。模型通过Matlab软件方法实现,最终仿真结果与对应系统的理论误码率基本符合。     

Monte Carlo simulation of rock slope reliability

One of the most important problems encountered in probabilistic rock slope stability analysis is the correlation that exists among the random variables involved in the design equation. Some existing probabilistic models assume independence between the random variables by ignoring all possible correlations. Other models realize the importance of including the correlations in the mathematical formulation; however, the associated mathematical complications require inclusion of some simplifying assumptions, such as Gaussian distribution of all random variables involved in the design equation. Therefore, it is important to develop techniques to deal with the correlations while maintaining the desired accuracy.

This paper is concerned with reliability analysis of rock slopes against single plane sliding under the influence of water. A modified Monte Carlo Simulation is used to determine the reliability of rock slopes including possible correlations between the variables entering into the design equation. These variables do not have to be normally distributed and can have different probability density functions. Finally, a computer program has been developed to perform all the necessary calculations.     

单电子器件的仿真

该文介绍了一种利用正统理论与Ｍｏｎｔｅ Ｃａｒｌｏ方法模拟单电子隧空器件的认真程序。该程序可模拟电子通过包含小隧道结、电容和理想电压源的电路的输运过程,利用该程序,对单库仓岛和多库仓同的单电子晶体管（ＳＥＴ）系统进行了模拟。     

Monte Carlo simulation of circular double-stranded polymers

Double-helix structure of DNA provides an appropriate model system for studying equilibrium properties of macromolecule. In contrast to the models of linear polymers, the secondary structure as well as most of interaction parameters can be introduced into the model. We present studies of double-stranded twisted circular polymer chain by mean of computer simulation. The attention was focused on the effect of polymer chain twisting on the properties of macromolecule. We found that the number of double helical turns affects the scaling of the polymer chain and markedly changes system properties, for example, coil to globule transition temperature.     

二元自由基共聚合的Monte Carlo模拟

采用Monte Carlo模拟计算方法、可视化编程语言Visual Basic,以研究非稳态、考虑前末端效应、聚合反应可逆等情况下二元自由基共聚合反应,以期得到共聚物的瞬时组成、组成分布、序列分布等决定共聚物效能的重要参数。以数值模拟代替实际实验,不仅可节约成本,而且可减少工作量。模拟结果显示,Monte Carlo模拟值与实验值符合较好,说明本模拟过程模拟效果较好,结果可靠,可用来模拟未知共聚合体系,并为实际共聚物的合成提供帮助。