应用Monte Carlo算法研究大分子蠕动阻力的影响因素

采用一种基于高分子Monte Carlo模拟算法分析分子蠕动阻力的软件,借助于二维空间中的8配位点键长涨落的格子链模型,对不同温度、分子量、共混小分子时的大分子蠕动行为进行了模拟分析,考察了温度、分子长、共混小分子等因素对蠕动阻力的影响,得到了随着温度增加、分子长减小和共混浓度增加,大分子蠕动阻力减小的结果,这与传统经验理论相符合。这些结果为选择大分子量添加剂黄原胶作为抗结块剂,以及选择β-环糊抑制玻璃化转变等提供了理论依据。     

化学介质对PBO纤维统计强度的影响

以Weibull分布和最弱连接理论为基础,研究了经6种化学介质处理的5cm长PBO单纤维的统计强度及强度分布,并与未经处理的相比较,指出其变化情况,并通过电镜分析其强度变化的原因.     

模拟频域滤波重构直方图均衡的图像增强方法

针对传统图像增强方法的不足,提出一种基于模拟频域滤波重构直方图均衡的图像增强方法.将频率域滤波的思想引入空间域直方图运算当中,在模拟频率直方图统计中进行频率信息的统计,利用这些频率信息建立模拟频率域坐标,进行模拟频域滤波,对滤波处理后的直方图进行均衡化处理.实验表明:与传统方法相比,该算法优化了灰度级的动态分布范围,能得到更清晰的增强效果,且在图像中没有视觉明显的噪声放大.     

钠钙玻璃的缺口弯曲强度

钠钙玻璃的缺日弯曲强度与试样的应力集中系数K_t成反比;而缺口根部断裂应力与K_t无关．如弯曲强度服从Weibull分布,其模量m是材料常数,而标度因子σ₀与K_t成反比．如弯曲强度服从正态分布,其平均值及标准差均与K_t成反比,而变异系数为常数．     

准二维4×4量子点磁化动力学特性的Monte Carlo模拟

基于Monte Carlo模拟,研究了准二维4×4量子点阵列中交换相互作用常数J、偶极相互作用常数D、磁晶各向异性常数K对自旋组态和相关磁特性的影响.模拟结果表明,量子点阵列和单个量子点表现出完全不同的磁特性,即量子点阵列表现为顺磁性,而单个量子点则为铁磁性;分析不同外磁场下体系自旋组态的变化可以很好地解释模拟结果.     

ZG230-450铸钢的重构疲劳可靠性S-N曲线

给定若干概率水平的常规疲劳可靠性曲线只能做相应概率水平的疲劳设计与寿命预测,要实现任意可靠性水平的疲劳设计、寿命预测和可靠性评定,需要重构全概率疲劳可靠性S-N曲线。首先应用Monte Carlo模拟技术在可接受的误差范围重构了铁道车辆ZG230-450车轮铸钢的疲劳极限和成组法S-N数据。然后应用广义极大似然法测定了其中短寿命范围的可靠性S-N曲线。最后应用概率疲劳极限外推法获得了该材料中短和长寿命范围的合理疲劳概率S-N曲线。并进一步发展了适于车辆结构用万公里单位表征的可靠性曲线。应用该曲线可实现任意可靠性水平的疲劳可靠性设计、寿命预测和可靠性评价。     

氧化物异质外延薄膜生长的计算机模拟

利用Monte Carlo方法分别模拟了在SrTiO3基底上沉积MgO薄膜和在MgO基底上沉积SrTiO3薄膜.模拟中,选取与实验中薄膜生长相近的参数条件,引入了新的参数扩散势垒,得到了在晶格正失配(张应力)和负失配(压应力)下薄膜生长的形貌图以及薄膜粗糙度的变化曲线图,分析了张应力和压应力对薄膜生长形貌的影响.模拟结果与文献报道的外延薄膜生长模式的实验观察结果一致.     

Monte－Carlo法研究大环高分子的分子尺寸

通过三维非晶格无规行走，对线型和环型自由连接链（ＦＪ）及具有硬核势能的自由连接链（ＦＪ－ＨＣ）进行了模拟。采用Ｍｏｎｔｅ－Ｃａｒｌｏ法获得的大量和系统的运算结果表明，具有相同结构单元和相同分子量的线型和环型高分子链的均方回旋半径比ｇｓ与不同学派的理论值和实验值完全吻合。     

玄武岩纤维丝束强度的Weibull和Gauss分布统计分析

通过假设检验验证了Weibull及Gauss分布模型对玄武岩纤维丝束强度统计分析的适用性,并用2种分布模型对BF-CSH-01、BF-CMD-02和BF-CAH-01 等3种纤维不同长度丝束的拉伸强度分布进行了统计分析。当纤维种类和试样长度变化时,采用2种模型统计的丝束强度的变化规律一致,即3种纤维中BF-CSH-01强度最高,BF-CMD-02的强度分散性最小;同种纤维中,随着试样长度的增加,丝束强度下降,强度分散性减小。2种分布模型相比,采用Weibull 模型计算的丝束强度略高于 Gauss模型,但强度分散性稍大。      

潜艇目标强度起伏统计模型

研究潜艇目标强度动态起伏规律,从统计意义上对目标强度进行分析,建立合适的目标强度起伏统计预报模型,并获得其统计参数。依据水下目标亮点理论,从散射截面起伏统计模型推导出目标强度起伏统计模型(Ts分布模型),并通过单壳体和双壳体Benchmark潜艇模型进行实验验证。目标强度动态起伏规律实验结果与Ts分布模型吻合较好,得出Ts分布模型能够准确地描述潜艇目标强度起伏特性。     

考虑力学机制和不确定性影响的钢筋混凝土柱概率抗剪承载力模型

为了克服传统确定性抗剪承载力模型无法合理考虑不确定性因素影响所存在的缺陷,研究建立了一种能够综合考虑力学机制和不确定性影响的钢筋混凝土（RC）柱概率抗剪承载力模型。首先基于桁架-拱模型,综合考虑混凝土、箍筋和拱作用的抗剪承载力贡献以及不确定性的影响,建立了RC柱概率抗剪承载力模型的解析表达式;然后结合贝叶斯理论和马尔科夫链蒙特卡洛（MCMC）法,确定了概率模型参数的后验分布信息,并分析了概率模型参数的先验分布信息以及更新批次对概率模型参数后验分布的稳定性和收敛性的影响;最后利用试验数据验证了该概率模型的有效性。分析表明,随着试验数据的增加,概率模型参数的后验分布可以实现不断更新;概率抗剪承载力模型不仅可以合理描述抗剪承载力的概率分布特性,而且可以校准分析传统确定性抗剪承载力模型的计算精度。     

混凝土疲劳损伤强度可靠度置信限分析

以三参数Weibull概型为基础,结合大量C15混凝土试件的试验和某混凝土重力坝的原型观测反演结果,建立了描述高应力水平区域的混凝土在较低损伤量下低周疲劳强度的置信限分析模型,得到了具有给定置信度的疲劳强度、疲劳寿命和疲劳损伤三者间的关系曲线,NSP---g和DSP---g曲线。利用本文方法可方便地在给定置信限内计算混凝土在给定应力水平条件下的疲劳寿命、损伤量和剩余强度, 对混凝土做考虑损伤的可靠度设计,以及对已建结构进行可靠度评价。     

模糊分布参数的全局灵敏度分析新方法

为合理度量随机输入变量分布参数的模糊性对输出性能统计特征的影响,提出了模糊分布参数的全局灵敏度效应指标,并研究了指标的高效求解方法。首先,分析了不确定性从模糊分布参数至模型输出响应统计特征的传递机理,以输出性能期望响应为例,利用输出均值的无条件隶属函数与给定模糊分布参数取值条件下的隶属函数的平均差异来度量模糊分布参数的影响,建立了模糊分布参数的全局灵敏度效应指标。其次,为减少所提指标的计算成本、提高计算效率,采用了扩展蒙特卡罗模拟法(EMCS)来估算输入变量分布参数与模型输出响应统计特征的函数关系。最后通过对算例的计算,验证该文所提方法的准确性和高效性。     

Robust optimization of concrete strength estimation using response surface methodology and Monte Carlo simulation

A new approach is proposed for the robust optimization of concrete strength estimation using response surface methodology and Monte Carlo simulation. The essence of the suggested procedure lies in the reliable prediction of concrete strength as a simple function of unit mass, water/cement ratio, age and superplasticizer content. The derived model provides sufficiently accurate results for the calibration and verification phases, the latter of which is conducted using data that were not used for model development. The results of additional analysis indicate that residuals in the calibration and verification stages have a normal distribution. Is its also shown that the uncertainty of estimated coefficient values has a statistically insignificant effect on concrete strength, confirming the reliability of the proposed model. Moreover, analysis of the effect of laboratory measurement errors indicates the robustness of concrete compressive strength against the variation in measured parameter values.     

LIFE PREDICTION BY SIMULATION OF CRACK GROWTH IN NOTCHED COMPONENTS WITH DIFFERENT MICROSTRUCTURES AND UNDER MULTIAXIAL FATIGUE

A modelling procedure was developed which is applicable to crack growth in notched components subjected to multiaxial fatigue for materials with different microstructures. An algorithm for crack growth, in a microstructure that was modelled as hexagons, was established as a competition between growth by crack linkages during the crack initiation and propagation stages and the propagation of a dominant crack as a single crack. Analytical results simulated by using the developed model were compared with experimental results from fatigue tests which had been conducted using notched specimens of pure copper, carbon steel and two kinds of titanium alloy. Cracking morphology, which was experimentally observed to depend on the microstructure and the loading mode, was well simulated using the present model. The fatigue failure life of a notched specimen was statistically estimated by a Monte Carlo procedure based on the model. The simulated life with a statistical scatter-band almost coincided with the experimental data.     

Robust estimation of mean and variance using environmental data sets with below detection limit observations

Scientists, especially environmental scientists, often encounter trace level concentrations that are typically reported as less than a certain limit of detection, L. Type I left-censored data arises when certain low values lying below L are ignored or unknown as they cannot be measured accurately. In many environmental quality assurance and quality control (QA/QC), and groundwater monitoring applications of the United States Environmental Protection Agency (USEPA), values smaller than L are not required to be reported. However, practitioners still need to obtain reliable estimates of the population mean μ, and the standard deviation (S.D.) σ. The problem gets complex when a small number of high concentrations are observed with a substantial number of concentrations below the detection limit. The high-outlying values contaminate the underlying censored sample, leading to distorted estimates of μ and σ. The USEPA, through the National Exposure Research Laboratory-Las Vegas (NERL-LV), under the Office of Research and Development (ORD), has research interests in developing statistically rigorous robust estimation procedures for contaminated left-censored data sets. Robust estimation procedures based upon a proposed (PROP) influence function are shown to result in reliable estimates of population parameters of mean and S.D. using contaminated left-censored samples. It is also observed that the robust estimates thus obtained with or without the outliers are in close agreement with the corresponding classical estimates after the removal of outliers. Several classical and robust methods for the estimation of μ and σ using left-censored (truncated) data sets with potential outliers have been reviewed and evaluated.