Sample size adaptive strategy for time-dependent Monte Carlo particle transport simulation

When multiphysics coupling calculations contain time-dependent Monte Carlo particle transport simulations, these simulations often account for the largest part of the calculation time, which is insufferable in certain important cases. This study proposes an adaptive strategy for automatically adjusting the sample size to fulfil more reasonable simulations. This is realized based on an extension of the Shannon entropy concept and is essentially different from the popular methods in timeindependent Monte Carlo particle transport simulations, such as controlling the sample size according to the relative error of a target tally or by experience. The results of the two models show that this strategy can yield almost similar results while significantly reducing the calculation time. Considering the efficiency, the sample size should not be increased blindly if the efficiency cannot be enhanced further. The strategy proposed herein satisfies this requirement.

Direct Monte Carlo Method Simulation of the Synthesis of Carbon Particle Through Coagulation in the Detonation of Explosives

A model is constructed and used in computing the coagulation probability of free carbon during the detonation of explosives. A direct simulation Monte Carlo (DSMC) program is constructed to simulate the coagulation of free carbon particles. The evaluation of the distribution spectrum of particles in the system is obtained. The simulation result is consistent with the experimental curve.

Neutral Particle Transport in Cylindrical Plasma Simulated by a Monte Carlo Code

A Monte Carlo code （MCHGAS） has been developed to investigate the neutral particle transport. The code can calculate the radial profile and energy spectrum of neutral particles in cylindrical plasmas. The calculation time of the code is dramatically reduced when the Splitting and Roulette schemes are applied. The plasma model of an infinite cylinder is assumed in the code, which is very convenient in simulating neutral particle transports in small and middle-sized tokamaks. The design of the multi-channel neutral particle analyser （NPA） on HL-2A can be optimized by using this code.

Calculation of Neutral Particle Energy Spectra in Tokamak by Using the Monte Carlo Method

Neutral particle energy spectra in the HT-7 tokamak are calculated by using the Monte Carlo method. It can reproduce the spectra measured in experiment. Differences of neutral particle energy spectra in higher and lower electron density plasma are discussed. Results show that the ion temperature given by neutral particle energy spectra is lower than the real ion temperature, but the deviation is within 10% if the ion temperature is less than 800 eV and thecentral chord-averaged electron density does not exceed 3 ×1013 cm-3. But for ion temperature higher than 1000 eV at the central chord-averaged density limit up to 5 ×1013 cm-3, the neutral particle energy spectra can still give the ion temperature within 10% deviation.

Monte Carlo Method for the Uncertainty Evaluation of Spatial Straightness Error Based on New Generation Geometrical Product Specification

Straightness error is an important parameter in measuring high-precision shafts. New generation geometrical product speeifieation（GPS） requires the measurement uncertainty characterizing the reliability of the results should be given together when the measurement result is given. Nowadays most researches on straightness focus on error calculation and only several research projects evaluate the measurement uncertainty based on ＂The Guide to the Expression of Uncertainty in Measurement（GUM）＂. In order to compute spatial straightness error（SSE） accurately and rapidly and overcome the limitations of GUM, a quasi particle swarm optimization（QPSO） is proposed to solve the minimum zone SSE and Monte Carlo Method（MCM） is developed to estimate the measurement uncertainty. The mathematical model of minimum zone SSE is formulated. In QPSO quasi-random sequences are applied to the generation of the initial position and velocity of particles and their velocities are modified by the constriction factor approach. The flow of measurement uncertainty evaluation based on MCM is proposed, where the heart is repeatedly sampling from the probability density function（PDF） for every input quantity and evaluating the model in each case. The minimum zone SSE of a shaft measured on a Coordinate Measuring Machine（CMM） is calculated by QPSO and the measurement uncertainty is evaluated by MCM on the basis of analyzing the uncertainty contributors. The results show that the uncertainty directly influences the product judgment result. Therefore it is scientific and reasonable to consider the influence of the uncertainty in judging whether the parts are accepted or rejected, especially for those located in the uncertainty zone. The proposed method is especially suitable when the PDF of the measurand cannot adequately be approximated by a Gaussian distribution or a scaled and shifted t-distribution and the measurement model is non-linear.

Quantum Boltzmann equation solved by Monte Carlo method for nano-scale semiconductor devices simulation

A two-dimensional （2D） full band self-consistent ensemble Monte Carlo （MC） method for solving the quantum Boltzmann equation, including collision broadening and quantum potential corrections, is developed to extend the MC method to the study of nano-scale semiconductor devices with obvious quantum mechanical （QM） effects. The quantum effects both in real space and momentum space in nano-scale semiconductor devices can be simulated. The effective mobility in the inversion layer of n and p channel MOSFET is simulated and compared with experimental data to verify this method. With this method 50nm ultra thin body silicon on insulator MOSFET are simulated. Results indicate that this method can be used to simulate the 2D QM effects in semiconductor devices including tunnelling effect.

Elbow precision machining technology by abrasive flow based on direct Monte Carlo method

The investigation was carried out on the technical problems of finishing the inner surface of elbow parts and the action mechanism of particles in elbow precision machining by abrasive flow.This work was analyzed and researched by combining theory,numerical and experimental methods.The direct simulation Monte Carlo(DSMC)method and the finite element analysis method were combined to reveal the random collision of particles during the precision machining of abrasive flow.Under different inlet velocity,volume fraction and abrasive particle size,the dynamic pressure and turbulence flow energy of abrasive flow in elbow were analyzed,and the machining mechanism of particles on the wall and the influence of different machining parameters on the precision machining quality of abrasive flow were obtained.The test results show the order of the influence of different parameters on the quality of abrasive flow precision machining and establish the optimal process parameters.The results of the surface morphology before and after the precision machining of the inner surface of the elbow are discussed,and the surface roughness Ra value is reduced from 1.125μm to 0.295μm after the precision machining of the abrasive flow.The application of DSMC method provides special insights for the development of abrasive flow technology.

LIGHT ION REFLECTION STUDIED BY MONTE CARLO SIMULATION AND TRANSPORT THEORY

The reflection of light ions, such as H+,3He+ and 4He+, with energies of 0.1- 10 keV, from Cu and Ni surface has been studied by Monte Carlo simulation and transport theory. The Monte Carlo simulation gives the detail energy spectra for the reflected particles and their angular distribution for different incident angles. It shows that the reflected particle energy spectra can be approximately described by an analytical formula for the whole energy range, all the incident angles and different ion- target combination studied here. The reflected particle energy vs its average reflection angle to the surface normal can almost be expressed by a universal curve for all cases studied here. The reflection energy spectra are used for the calculation of the reflection coefficient by transport theory including the realistic surface correction. The present work is compared with both experimental measurement and other simulation codes.

Sequential Monte Carlo Method Toward Online RUL Assessment with Applications

Online assessment of remaining useful life(RUL) of a system or device has been widely studied for performance reliability, production safety, system conditional maintenance, and decision in remanufacturing engineering. However,there is no consistency framework to solve the RUL recursive estimation for the complex degenerate systems/device.In this paper, state space model(SSM) with Bayesian online estimation expounded from Markov chain Monte Carlo(MCMC) to Sequential Monte Carlo(SMC) algorithm is presented in order to derive the optimal Bayesian estimation.In the context of nonlinear & non-Gaussian dynamic systems, SMC(also named particle filter, PF) is quite capable of performing filtering and RUL assessment recursively. The underlying deterioration of a system/device is seen as a stochastic process with continuous, nonreversible degrading. The state of the deterioration tendency is filtered and predicted with updating observations through the SMC procedure. The corresponding remaining useful life of the system/device is estimated based on the state degradation and a predefined threshold of the failure with two-sided criterion. The paper presents an application on a milling machine for cutter tool RUL assessment by applying the above proposed methodology. The example shows the promising results and the effectiveness of SSM and SMC online assessment of RUL.

Monte Carlo Simulation of Laser-Ablated Particle Splitting Dynamic in a Low Pressure Inert Gas

A Monte Carlo simulation method with an instantaneous density dependent meanfree-path of the ablated particles and the Ar gas is developed for investigating the transport dynamics of the laser-ablated particles in a low pressure inert gas.The ablated-particle density and velocity distributions are analyzed.The force distributions acting on the ablated particles are investigated.The influence of the substrate on the ablated-particle velocity distribution and the force distribution acting on the ablated particles are discussed.The Monte Carlo simulation results approximately agree with the experimental data at the pressure of 8 Pa to 17 Pa.This is helpful to investigate the gas phase nucleation and growth mechanism of nanoparticles.

New Approach to Simulating the Absorption of Gamma Radiations Using the Monte-Carlo Method: A Computational Study

The following article has been retracted due to the investigation of complaints received against it. Mr. Mohammadali Ghorbani (corresponding author and also the last author) cheated the author’s name: Alireza Heidari. The scientific community takes a very strong view on this matter and we treat all unethical behavior such as plagiarism seriously. This paper published in Vol.3 No.3, 260-265, 2012, has been removed from this site.

组合几何Monte Carlo粒子输运支撑软件框架JCOGIN的研发

为实现核反应堆pin-by-pin精细Monte Carlo粒子输运模拟,研发了组合几何Monte Carlo粒子输运支撑软件框架JCOGIN以支撑千万个几何体、百亿个粒子的Monte Carlo粒子输运大规模并行计算。JCOGIN框架采用层次式、模块化的体系结构设计了适应现代高性能计算机体系结构特征的数据结构,在此基础上实现了对粒子并行与区域分解相耦合的两级并行计算的支撑。在JCOGIN框架下研发了JMCT程序,并进行性能测试,在2万个处理器核上并行效率达70%;基于区域分解完成了大亚湾全堆芯pin-by-pin模型模拟,几何体数达千万,粒子数达百亿。

考虑颗粒碰撞的多重Monte Carlo算法

从减少计算代价和改进碰撞算法出发,提出了考虑颗粒碰撞的多重MonteCarlo算法,它采用直接模拟MonteCarlo算法来考虑颗粒碰撞,并与求解颗粒拉氏Langevin方程的MonteCarlo算法耦合起来,跟踪比实际颗粒数目小得多的虚拟颗粒.提出了时间步长选定标准、虚拟碰撞伙伴所在控制容积的判断准则、颗粒碰撞发生的判断准则、虚拟碰撞伙伴的选择、基于随机碰撞角度的碰撞动力学,构成了考虑颗粒碰撞的完整多重MonteCarlo算法.对理想工况的细微颗粒流和粗重颗粒流进行了数值模拟,颗粒碰撞率的模拟结果与理论分析解和DNS结果均符合很好,颗粒场演变的细节信息,如时间平均和特定时刻的颗粒数密度,速度和颗粒湍动能等,均与DNS结果符合很好.数值模拟结果证明该算法不仅具有较低的计算代价,而且能够达到足够的计算精度.

电子在混合气体中输运的Monte Carlo研究

针对直流混合气体放电中碰撞分子种类的确定问题,研究了电子在混合气体中的平均碰撞频率、平均自由程与气体密度、配比的关系,给出了抽样确定碰撞分子种类的方法,为数值模拟放电动力学过程提供了理论基础。

基于特征粒子的Monte Carlo自定位方法

提出了一种基于Monte Carlo方法的多机器人自定位方法.该方法在机器人进行自定位时,对用来估计机器人位置的MCL(Monte Carlo Localization)粒子空间进行栅格划分,然后采用可变栅格法获得能代表所有粒子整体特性的特征粒子集.因为特征粒子的数量较粒子总数大大减少,该方法能避免直接将Monte Carlo方法应用于多机器人定位中产生的维数灾的问题,可以在保证精度的情况下降低运算复杂度.仿真结果表明,该方法能较好地满足多机器人自定位的要求.

气固两相流中颗粒碰撞的Monte-Carlo数值模拟

利用颗粒碰撞动力学模型和颗粒几何碰撞率模型,采用Monte-Carlo算法来模拟颗粒之间碰撞,把该算法与求解雷诺应力-概率密度函数模型的有限差分-MonteCarlo算法耦合起来,对轴对称突扩通道内的两相旋流场进行了数值模拟,模拟结果表明,由于颗粒碰撞使颗粒的动能和湍动能在三个坐标方向上进行了再分配,从而导致颗粒的动能和湍动能在三个坐标方向上趋于各向同性;另外,由于颗粒碰撞破坏了颗粒-颗粒、颗粒-流体微团之间的速度关联,从而造成颗粒湍动能及两相速度脉动关联的降低。

凝并和成核机理下颗粒尺度分布的Monte Carlo求解

颗粒的凝并和成核现象影响其尺度分布,现有的Monte Carlo方法描述颗粒尺度分布的时间演变过程存在若干困难.提出了一种新的多重Monte Carlo(MMC)算法,基于时间驱动,利用加权的虚拟颗粒的思想,在模拟过程中保持虚拟颗粒总数不变和计算区域体积不变.利用该算法对“常凝并核,一阶成核”的情况下颗粒尺度分布的时间演变过程进行了数值求解,所得结果与数值解相符,表明MMC算法具有高且稳定的计算精度.另外,MMC算法由于跟踪比实际颗粒数目少得多的虚拟颗粒而具有较低的计算代价.

模拟颗粒凝并过程的快速Monte Carlo方法

对常规异权值Monte Carlo(MC)方法进行改进,基于强核函数思想,通过颗粒群单重遍历即可求得强核函数最大值,采用接受-拒绝法随机搜寻凝并对,并利用搜寻过程中拒绝和接受的所有凝并对的信息来估计凝并事件的等待时间(时间步长),从而避免颗粒群的双重遍历,以提高MC的效率.对典型工况的模拟结果显示该快速方法计算代价仅为O(Ns),能够显著提高计算效率,同时保持足够的计算精度,较好地协调计算代价与计算精度之间的矛盾.

用差分和Monte Carlo求解相结合的方法计算有化学反应的活塞流

用差分和Monte Carlo求解相结合的方法对有化学反应的标量几率密度函数方程进行了求解,讨论了随机颗粒数和时间步长对计算结果的影响。计算结果表明,当化学反应速率是标量的线性函数时,结果与精确解很吻合;当反应速率满足Arrhenius定律时,结果也是合理的。