Research and development of the automatic modeling system for Monte Carlo particle transport simulation

在广泛调研和分析现有几何建模方法特点的基础上研发了具有可视化用户界面的自动建模程序系统MCAM。它可以实现多种商用软件CAD模型与McNP模型之间的相互转换，且提供了模型建立、预处理、属性分析等基本功能和计算结果可视化及基于医学映像建模接口等扩展功能。全面系统地介绍了MCAM的设计思想与原理、总体结构、主要功能和国际合作协议框架下的应用测试等情况。实践表明，它是一个实用的MCNP计算辅助工具和核设计与核分析质量保证工具。

A Modified Monte Carlo Model of Speckle Tracking of Shear Wave Induced by Acoustic Radiation Force for Acousto-Optic Elasticity Imaging

A modified Monte Carlo model of speckle tracking of shear wave propagation in scattering media is proposed. The established Monte Carlo model mainly concerns the variations of optical electric field and speckle. The two- dimensional intensity distribution and the time evolution of speckles in different probe locations are obtained. The fluctuation of speckle intensity tracks the acoustic-radiation-force shear wave propagation, and especially the reduction of speckle intensity implies attenuation of shear wave. Then, the shear wave velocity is estimated quantitatively on the basis of the time-to-peak algorithm and linear regression processing. The results reveal that a smaller sampling interval yields higher estimation precision and the shear wave velocity is estimated more efficiently by using speckle intensity difference than by using speckle contrast difference according to the estimation error. Hence, the shear wave velocity is estimated to be 2.25 m/s with relatively high accuracy for the estimation error reaches the minimum （0.071）.

A Monte Carlo Model of Light Propagation in Nontransparent Tissue

To sharpen the imaging of structures, it is vital to develop a convenient and efficient quantitative algorithm of the optical coherence tomography (OCT) sampling. In this paper a new Monte Carlo model is set up and how light propagates in bio-tissue is analyzed in virtue of mathematics and physics equations. The relations,in which light intensity of Class 1 and Class 2 light with different wavelengths changes with their permeation depth,and in which Class 1 light intensity (signal light intensity) changes with the probing depth, and in which angularly resolved diffuse reflectance and diffuse transmittance change with the exiting angle, are studied. The results show that Monte Carlo simulation results are consistent with the theory data.

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。

3-D Fracture Network Modelling in Hydropower Engineering Based on Optimal Monte Carlo Simulation

Effectively and accurately modelling the spatial relation of fracture surfaces is crucial in the design and construction of large hydropower dams having a complex underlying geology. However, fracture surfaces are randomly formed and vary greatly with respect to their spatial distribution, which makes the construction of accurate 3-D models challenging. In this study, we use an optimal Monte Carlo simulation and dynamic conditioning to construct a fracture network model. We found the optimal Monte Carlo simulation to effectively reduce the error associated with the Monte Carlo method and use dynamic conditioning to ensure the consistency of the model with the actual distribution of fractures on the excavation faces and outcrops. We applied this novel approach to a hydropower station on the Jinshajiang River, China. The simulation results matched the real sampled values well, confirming that the model is capable of effectively and accurately simulating the spatial relations in a fracture network. © 2017, Tianjin University and Springer-Verlag Berlin Heidelberg.

Using the Optical Glauber Monte Carlo Model to Calculate R_<i>AA</i>Related Results Produced by the ATLAS Collaboration

The energy loss during jet quenching due to the existence of Quark Gluon Plasma (QGP) is calculated by Optical Glaube Monte Carlo model with data collected by ATLAS Collaboration using the LHC detector. An energy loss formula for this situation was modeled and took the form . The nuclear modification factor, RAA, for jets in a 208Pb + 208Pb nucleus collision with rapidity interval of ∣у∣=2.8 and the initial transverse momentum of 50 GeV ≤ pT ≤ 1000 GeV, are compared with various data plots produced by ATLAS Collaboration. RAA results are plotted in different centrality bins, which are defined by the distribution of number of participating nucleons Npart. The RAA value was found to slowly increase at lower transverse momenta and flatten out at higher transverse momenta. The model’s theoretical calculation results turned out to be similar to the plots produced by the ATLAS Collaboration using data from the LHC with small differences for higher systematic uncertainty events.

Microcanonical Monte Carlo Simulation of 2D 4-State Potts Model

Monte Carlo simulation of two dimensional 4 state Potts model has been carried out in microcanonical ensemble. The simulations were done on a 30 × 30 system with periodic boundary conditions. The temperature dependence of energy and order parameter has been calculated. The transition in 4-state Potts model is concluded to be first-order in nature. The transition temperature and latent heat of the first-order transition have been found to be 0.92 and 0.18, respectively.

Monte-Carlo Studies and Computer Modelling of Multi-wavelength Pyrometry

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Reverse Monte Carlo Modeling of the Rigidity Percolation Threshold in Ge<SUB>x</SUB>Se<SUB>1-x</SUB>Glassy Networks

Based on Maxwell’s constraint counting theory, rigidity percolation in GexSe1-x glasses occurs when the mean coordination number reaches the value of 2.4. This corresponds to Ge0.20Se0.80 glass. At this composition, the number of constraints experienced by an atom equals the number of degrees of freedom in three dimensions. Hence, at this composition, the network changes from a floppy phase to a rigid phase, and rigidity starts to percolate. In this work, we use reverse Monte Carlo (RMC) modeling to model the structure of Ge0.20Se0.80 glass by simulating its experimental total atomic pair distribution function (PDF) obtained via high energy synchrotron radiation. A three-dimensional configuration of 2836 atoms was obtained, from which we extracted the partial atomic pair distribution functions associated with Ge-Ge, Ge-Se and Se-Se real space correlations that are hard to extract experimentally from total scattering methods. Bond angle distributions, coordination numbers, mean coordination numbers and the number of floppy modes were also extracted and discussed. More structural insights about network topology at this composition were illustrated. The results indicate that in Ge0.20Se0.80 glass, Ge atoms break up and cross-link the Se chain structure, and form structural units that are four-fold coordinated (the GeSe4 tetrahedra). These tetrahedra form the basic building block and are connected via shared Se atoms or short Se chains. The extent of the intermediate ranged oscillations in real space (as extracted from the width of the first sharp diffraction peak) was found to be around 19.6 ?. The bonding schemes in this glass are consistent with the so-called “8-N” rule and can be interpreted in terms of a chemically ordered network model.

A Monte Carlo-Based Approach for Groundwater Chemistry Inverse Modeling

Inverse geochemical modeling of groundwater entails identifying a set of geochemical reactions which can explain observed changes in water chemistry between two samples that are spatially related in some sense, such as two points along a flow pathway. A common inversion approach is to solve a set of simultaneous mass and electron balance equations involving water-rock and oxidation-reduction reactions that are consistent with the changes in concentrations of various aqueous components. However, this mass-balance approach does not test the thermodynamic favorability of the resulting model and provides limited insight into the model uncertainties. In this context, a Monte Carlo-based forward-inverse modeling method is proposed that generates probability distributions for model parameters which best match the observed data using the Metro-polis-Hastings search strategy. The forward model is based on the well-vetted PHREEQC geochemical model. The proposed modeling approach is applied to two test applications, one involving an inverse modeling example supplied with the PHREEQC code that entails groundwater interactions with a granitic rock mineral assemblage, and the other concerning the impact of fuel hydrocarbon bioattenuation on groundwater chemistry. In both examples, the forward-inverse approach is able to approximately reproduce observed water quality changes invoking mass transfer reactions that are all thermodynamically favorable.

Investigating Performances of Some Statistical Tests for Heteroscedasticity Assumption in Generalized Linear Model: A Monte Carlo Simulations Study

In a linear regression model, testing for uniformity of the variance of the residuals is a significant integral part of statistical analysis. This is a crucial assumption that requires statistical confirmation via the use of some statistical tests mostly before carrying out the Analysis of Variance (ANOVA) technique. Many academic researchers have published series of papers (articles) on some tests for detecting variance heterogeneity assumption in multiple linear regression models. So many comparisons on these tests have been made using various statistical techniques like biases, error rates as well as powers. Aside comparisons, modifications of some of these statistical tests for detecting variance heterogeneity have been reported in some literatures in recent years. In a multiple linear regression situation, much work has not been done on comparing some selected statistical tests for homoscedasticity assumption when linear, quadratic, square root, and exponential forms of heteroscedasticity are injected into the residuals. As a result of this fact, the present study intends to work extensively on all these areas of interest with a view to filling the gap. The paper aims at providing a comprehensive comparative analysis of asymptotic behaviour of some selected statistical tests for homoscedasticity assumption in order to hunt for the best statistical test for detecting heteroscedasticity in a multiple linear regression scenario with varying variances and levels of significance. In the literature, several tests for homoscedasticity are available but only nine: Breusch-Godfrey test, studentized Breusch-Pagan test, White’s test, Nonconstant Variance Score test, Park test, Spearman Rank, Glejser test, Goldfeld-Quandt test, Harrison-McCabe test were considered for this study;this is with a view to examining, by Monte Carlo simulations, their asymptotic behaviours. However, four different forms of heteroscedastic structures: exponential and linear (generalize of square-root and quadratic structures) were injected into the residual part of the multiple linear regression models at different categories of sample sizes: 30, 50, 100, 200, 500 and 1000. Evaluations of the performances were done within R environment. Among other findings, our investigations revealed that Glejser and Park tests returned the best test to employ to check for heteroscedasticity in EHS and LHS respectively also White and Harrison-McCabe tests returned the best test to employ to check for homoscedasticity in EHS and LHS respectively for sample size less than 50.

Validation of the Ability of Full Configuration Interaction Quantum Monte Carlo for Studying the 2D Hubbard Model

To validate the ability of full configuration interaction quantum Monte Carlo （FCIQMC） for studying the 2D Hubbard model near half-filling regime, the ground state energies of a 4×44×4 square lattice system with various interaction strengths are calculated. It is found that the calculated results are in good agreement with those obtained by exact diagonalization （i.e., the exact values for a given basis set） when the population of psi particles （psips） is higher than the critical population required to correctly sample the ground state wave function. In addition, the variations of the average computational time per 20 Monte Carlo cycles with the coupling strength and the number of processors are also analyzed. The calculated results show that the computational efficiency of an FCIQMC calculation is mainly affected by the total population of psips and the communication between processors. These results can provide useful references for understanding the FCIQMC algorithm, studying the ground state properties of the 2D Hubbard model for the larger system size by the FCIQMC method and using a computational budget as effectively as possible.

Search of New Higgs Boson in B-L Model at the LHC Using Monte Carlo Simulation

The aim of this work is to search for a new heavy Higgs boson in the B-L extension of the Standard Model at LHC using the data produced from simulated collisions between two protons at different center of mass energies by Monte Carlo event generator programs to find new Higgs boson signatures at the LHC. Also, we study the production and decay channels for Higgs boson in this model and its interactions with the other new particles of this model namely the new neutral gauge massive boson and the new fermionic right-handed heavy neutrinos νh.

Monte Carlo study of single-barrier structure based on exclusion model full counting statistics

Different from the usual full counting statistics theoretical work that focuses on the higher order cumulants computation by using cumulant generating function in electrical structures, Monte Carlo simulation of single-barrier structure is performed to obtain time series for two types of widely applicable exclusion models, counter-flows model, and tunnel model. With high-order spectrum analysis of Matlab, the validation of Monte Carlo methods is shown through the extracted first four cumulants from the time series, which are in agreement with those from cumulant generating function. After the comparison between the counter-flows model and the tunnel model in a single barrier structure, it is found that the essential difference between them consists in the strictly holding of Pauli principle in the former and in the statistical consideration of Pauli principle in the latter.

Quasi-Monte Carlo Approximations for Exponentiated Quadratic Kernel in Latent Force Models

In this project, we consider obtaining Fourier features via more efficient sampling schemes to approximate the kernel in LFMs. A latent force model (LFM) is a Gaussian process whose covariance functions follow an Exponentiated Quadratic (EQ) form, and the solutions for the cross-covariance are expensive due to the computational complexity. To reduce the complexity of mathematical expressions, random Fourier features (RFF) are applied to approximate the EQ kernel. Usually, the random Fourier features are implemented with Monte Carlo sampling, but this project proposes replacing the Monte-Carlo method with the Quasi-Monte Carlo (QMC) method. The first-order and second-order models’ experiment results demonstrate the decrease in NLPD and NMSE, which revealed that the models with QMC approximation have better performance.

Monte Carlo模拟在建设用地需求预测中的应用

在建设用地需求预测中 ,以自变量的分布函数为基础 ,建立未来各年用地规模函数 ,通过MonteCarlo模型模拟 ,可以有效地预测未来年份的用地规模 。

Monte Carlo多源模式在广东核电站大气环境评价中的应用

发展了ＭｏｎｔｅＣａｒｌｏ多源模式并用于模拟广东核电站排放的放射性污染物浓度分布和干湿沉积量。数值实验和六氟化硫（ＳＦ６）示踪实验表明，模式能很好地反映复杂地形和生态下垫面对污染物的输送、扩散和干湿沉积的影响；与观测值相比，浓度计算值的准确率大于等于５０％的概率为５８４％。

Monte Carlo法在多元肥效模型参数估计和推荐施肥中的应用

针对多元肥效模型大量存在非典型式的事实,本文应用"3414"田间试验结果,详细介绍Monte Carlo法的原理以及在多元肥效模型参数估计、非典型肥效模型推荐施肥等方面的应用方法和步骤。结果表明,采用最小二乘法回归建模,67个二元和59个三元肥效模型的典型式出现几率分别为23.1%和16.9%;而改用Monte Carlo法参数寻优,典型式出现几率分别提高到56.7%和37.3%,是最小二乘法的2.5倍和2.2倍。与最小二乘法相比,Monte Carlo法是在参数寻优时牺牲数学上偏差平方和最小的最优性,使待估参数达到专业上最优而数学上较优,从而提高典型肥效模型的出现几率。对Monte Carlo法也不能得到典型式的晚稻磷钾非典型肥效模型,用产量频率分析法计算推荐施肥量,表明只有一组磷钾肥用量组合入选,导致磷肥推荐用量偏高而钾肥偏低。在相同目标产量下,改用Monte Carlo法,平均推荐用量介于相同试验地所建立的氮磷、氮钾和氮磷钾典型肥效模型的推荐用量之间,结果明显优于产量频率分析法。因此,Monte Carlo法为多元肥效模型参数估计和非典型肥效模型推荐施肥提供了一种新方法,提高了当前测土配方施肥田间试验的成功率。

基于MONTE-CARLO模型的细胞传感器纳米颗粒表面处理分析

离体生物传感器的微型和集成化为细胞电生理研究提供了有力手段。当前微电极阵列表面纳米粒子处理的相关量化分析尚为欠缺。着重采用Monte-Carlo模型判断单层/多层纳米粒子膜与电极耦合的有效性,讨论异质的单一或不同粒径分散度(50～500 nm)的纳米粒子分层贴附处理于电极上,从二维、三维模型角度分析纳米粒子表面处理的有效性。多种结果显示,粒径分散度较大,且在一个数量级内的纳米颗粒能有效增大电极贴附率与处理均一性,以提高后期细胞-电极结合的重复性。相关金微阵列电极电镀的交流阻抗实验也说明纳米颗粒的沉积对于降低电极体阻抗及增大表面活化处理的作用。表面处理技术的量化评估,有利于建立基于高通量平台的实验和计算生物学、信息处理技术有机结合的研究方法。

两嵌段共聚高分子在固液界面吸附的Monte Carlo模拟(Ⅰ)吸附链的构型分布

用 Monte Carlo方法对两嵌段共聚高分子在固液界面的吸附进行模拟 ,获得了固液界面区吸附链节的分布和吸附构型大小分布等微观信息 .考察了吸附性链节的吸附能 εAa和两嵌段共聚高分子中吸附性链节比例 f对固液界面区高分子链节的分布和各种吸附构型大小的影响 .结果表明 ,吸附层厚度主要由两嵌段共聚高分子中非吸附性链段的长度决定 .