Monte Carlo simulation of the homogeneous cooling state for a granular mixture

 The Direct Simulation Monte Carlo (DSMC) method is used to numerically solve the Enskog equation for a granular binary mixture in the homogeneous cooling state (HCS). The fourth velocity moments, the temperature ratio, and also the velocity distribution functions are obtained and compared with approximate analytical results derived recently from a Sonine polynomial expansion [V. Garzó and J. W. Dufty, Phys. Rev. E 60, 5706 (1999)]. The comparison shows an excellent agreement between both approaches, even for strong dissipation or disparate values of the mechanical parameters of the mixture. In contrast to previous studies, the partial temperatures of each species are clearly different, so that the total energy is not equally distributed between both species. Finally, in the same way as in the one-component case, the simulation as well as the theory show a high energy tail of the distribution functions. Received: 9 May 2001     

Time-domain electronic-noise generation for a Monte Carlo study of signal processing

A general technique to generate electronic noise was developed in a time-domain approach with the aid of a deconvolution technique in a discrete-time sampling system. We found that the technique is applicable even for a system in which the electronic-noise charge is not well defined. The generated noise train was reconstructed in terms of a sample-correlated function and the frequency spectrum.     

基于Monte-Carlo方法模拟分析NBI真空压力分布的研究

中性束注入装置是产生高能中性粒子以加热托卡马克等离子体的装置。NBI真空压力分布是影响中性束传输效率特别是再电离损失的关键因素之一。研究分析了超导托卡马克实验装置中NBI的工作原理和结构特点,建立了EAST NBI的几何与物理模型,利用Monte-Carlo方法建立NBI主真空室内分子运动及碰撞的数学模型,并运用Matlab软件编程实现对NBI主真空室内真空压力分布的模拟计算,得到主真空室内三段区域在进气过程中的气体分子三维分布图和平均压力变化曲线。研究可为EAST NBI主真空室内的中性化室、偏转系统、低温抽气系统的结构设计提供指导。     

Size and distribution prediction for nanoparticles produced by microemulsion precipitation: A Monte Carlo simulation study

A Monte Carlo simulation approach for BaSO(4) nanoparticle precipitation in microemulsions has been applied to a semi-batch reactor experiment. The simulation includes two technical process parameters, the feed rate and the initial volume ratio of the two reactants. A set of experiments with different initial reactant concentrations of BaCl(2) and K(2)SO(4) showed a significant change in the particle size. It was compared to the simulated final particle size and with an adaptation of one internal parameter of the Monte Carlo simulation a good agreement between simulated and experimental data was achieved. Using this set of parameters the feed rate and the initial volume ratio is varied. It is shown how these process parameters influence the particle size and the size distribution. The simulation results may help in finding appropriate control parameters in a scale-up approach of the microemulsion technology for nanoparticle production.     

Moisture distribution in granular material during drying in a fluidized bed

This paper gives the results of a determination of the moisture content gradient and an investigation of the moisture distribution in a granular material during drying in a fluidized bed.     

Monte Carlo study in physical adsorption II: A comparison of Monte Carlo and renormalization group results for localized monolayer adsorption on a triagular lattice

The localized monolayer adsorption of an atomic adsorbate on a triangular lattice was studied with the help of grand ensemble Monte Carlo simulations. The adsorbed atoms were assumed to interact with one another via a Lennard-Jones potential and interactions up to the sixth nearest neighbours were taken into account. The diameters of the adsorbed atoms (relative to the lattice unit cell size) were chosen such that a direct comparison could be made of the simulation results with the renormalization group calculations due to Ostlund and Berker. In particular, it was assumed that mutual occupation of adjacent sites is excluded because of the highly positive energy of interaction between the first nearest neighbours. In spite of the difficulties due to metastability, several phase diagrams for adsorbed films were constructed and compared with the phase diagrams obtained by the renormalization group method. A remarkable agreement between the results obtained by these two methods was found.     

Monte Carlo,hypothesis-tests for rare events superimposed on a background

We describe two techniques to search for small numbers of counts under a peak of known shape and superimposed on a background with statistical fluctuations. Many comparisons of a single experimental spectrum with computer simulations of the peak and background are made. From these we calculate the probability that y hypothesized counts in the peaks of the simulations, will result in a number larger than that observed in a given energy interval (bin) in the experimental spectrum. This is done for many values of the hypothesized number y. One procedure is very similar to testing a statistical hypothesis and can be analytically applied. Another is presented which is related to pattern recognition techniques and is less sensitive to the uncertainty in the mean. Sample applications to double beta decay data are presented.     

Effect of size distribution on mixing of a polydisperse wet granular material in a belt-driven enclosure

We use a recently developed coupled fluid–particle discrete element model to study mixing of a wet granular material in a two dimensional setting. The particles are modeled as linearly elastic disks and are considered to be immersed in a Newtonian fluid. The fluid–particle interaction is modeled using a linear drag model under the assumption that the fluid inertia is small compared to particle inertia. The granular slurry is driven by a belt moving at constant velocity in a square cavity. In the simulations, we consider three types of size distributions: monodisperse, bidisperse with several particle size ratios, and polydisperse Gaussian distributions with several different standard deviations. Mixing is characterized using both strong and weak measures. Size segregation is observed only in the bidisperse simulations. The energy required for mixing polydisperse slurries decreases with increasing standard deviation of the particle sizes. Finally, we show the benefits of engineering certain polydisperse particle size distributions towards minimizing energy consumption.     

Variance Reduction Techniques for Monte Carlo Sampling from Student Distributions

A Monte Carlo design is presented for estimating the variance and cumulative distribution function of translation and scale invariant statistics based on independent Student random variables. One obvious application is studying estimates of the location parameter from a symmetric, possibly long-tailed distribution. The method itself amounts to suppressing some of the variability in the sampled objects by integrating these objects over appropriate regions of the underlying probability space. Indications are that, in cases of interest, the variability is thereby considerably reduced, as is illustrated in an application concerning trimmed and Winsorieed means.     

Finite element study of the effect of material properties on reaction forces produced by solitary wave propagation in granular chains

The response of a granular chain to impulse loading was investigated as a function of material properties. Using COMSOL Multiphysics, the elastic modulus and density of the grains were varied while the piston and force sensor properties remained fixed. The result of solitary wave propagation through the granular chain was recorded at the force sensor as a series of reaction force waves. It was found that wave velocity and amplitude increased with elastic modulus. Increasing density caused a decrease in wave velocity and an increase in amplitude. In addition, higher density granular chains exhibited a decrease in the number of waves in their respective reaction force wave trains. LS-DYNA was then used to explore the response of a variety of ceramic and metallic granular chains. Density, elastic modulus, and Poisson’s ratio were all set to representative values for the respective material. It was found that solitary wave development and decay occurred at different rates for different materials. In addition, the kinetic energy decay of the impactor was slower for glass compared with tungsten. Finally, it was shown that a single reaction force wave with no train could be produced by impacting a high density, high modulus chain such as tungsten with a glass piston, which has relatively low density and elastic modulus. Increasing impact velocity for this case resulted in a single high-amplitude wave with no train.     

Monte Carlo simulation of a control for cathodic sputtering

Subject is a set-up for gas pressure and discharge power regulation of a cathodic sputtering plant. It comprises two film thickness monitors and a control unit. The film thickness monitors measure the deposition rate at target and substrate level. By means of a computer the control unit calculates a quotient from the monitor data and compares it with a set value. Any change in gas pressure or discharge power leads to a deviation of the quotient from the set value. The control unit eliminates the deviation by a regulation of gas pressure or discharge power. The Monte Carlo method makes it possible to calculate the pressure dependence of the set-sup. It was not possible to determine a relationship between discharge power and the output signal of the control unit by the used theoretical model.     

3D calculation of absorbed dose for 131I-targeted radiotherapy: a Monte Carlo study

Various methods, such as those developed by the Medical Internal Radiation Dosimetry (MIRD) Committee of the Society of Nuclear Medicine or employing dose point kernels, have been applied to the radiation dosimetry of (131)I radionuclide therapy. However, studies have not shown a strong relationship between tumour absorbed dose and its overall therapeutic response, probably due in part to inaccuracies in activity and dose estimation. In the current study, the GATE Monte Carlo computer code was used to facilitate voxel-level radiation dosimetry for organ activities measured in an (131)I-treated thyroid cancer patient. This approach allows incorporation of the size, shape and composition of organs (in the current study, in the Zubal anthropomorphic phantom) and intra-organ and intra-tumour inhomogeneities in the activity distributions. The total activities of the tumours and their heterogeneous distributions were measured from the SPECT images to calculate the dose maps. For investigating the effect of activity distribution on dose distribution, a hypothetical homogeneous distribution of the same total activity was considered in the tumours. It was observed that the tumour mean absorbed dose rates per unit cumulated activity were 0.65E-5 and 0.61E-5 mGY MBq(-1) s(-1) for the uniform and non-uniform distributions in the tumour, respectively, which do not differ considerably. However, the dose-volume histograms (DVH) show that the tumour non-uniform activity distribution decreases the absorbed dose to portions of the tumour volume. In such a case, it can be misleading to quote the mean or maximum absorbed dose, because overall response is likely limited by the tumour volume that receives low (i.e. non-cytocidal) doses. Three-dimensional radiation dosimetry, and calculation of tumour DVHs, may lead to the derivation of clinically reliable dose-response relationships and therefore may ultimately improve treatment planning as well as response assessment for radionuclide therapy.     

挖掘机工作空间求解的蒙特卡洛法改进

对常规蒙特卡洛法求解挖掘机工作空间的原理、算法流程分析与仿真,发现大量随机点的分布在空间内部,边界随机点分布少,使得求解结果误差较大且效率低下。对挖掘机工作空间边界形成的内在机理分析,发现其边界的界定本质是其中两组油缸取极限值,另一组油缸为变量,而非三组油缸变量耦合,从而使得随机点的分布集中在工作空间边界。采用改进后的蒙特卡洛法对挖掘机的工作空间进行仿真,对比常规法求解,结果证明改进蒙特卡洛法求解高效且误差极小。     

基于弹塑性剪滞理论的单丝复合材料段裂过程的蒙特卡罗模拟

单丝复合材料段裂试验(SFCFT)中,随着外载荷的增加,纤维出现了随机脆断的现象,并在一定的载荷下纤维的段裂数达到"饱和"状态(即纤维段裂数目不再增加),该试验常用于表征纤维与基体间界面性能。针对该试验,本文中充分考虑了组分材料的真实性能(即基体材料的弹塑性性能),利用弹塑性剪滞理论进行纤维与基体间的应力传递分析,初步获得较真实的纤维轴向应力及界面剪应力分布形式;在此基础上,考虑纤维强度分布的非均匀性,利用蒙特卡罗(Monte Carlo)方法对试验中纤维的随机段裂过程进行了模拟预报,获得载荷与纤维的段裂数的关系。模拟预报与试验结果比较吻合,表明该应力分析及模拟方法的有效性。     

Monte Carlo study of a 3D Compton imaging device with GEANT4

In this paper we investigate, with a detailed Monte Carlo simulation based on Geant4, the novel approach of Lenti (2008) [1] to 3D imaging with photon scattering. A monochromatic and well collimated gamma beam is used to illuminate the object to be imaged and the photons Compton scattered are detected by means of a surrounding germanium strip detector. The impact position and the energy of the photons are measured with high precision and the scattering position along the beam axis is calculated. We study as an application of this technique the case of brain imaging but the results can be applied as well to situations where a lighter object, with localized variations of density, is embedded in a denser container. We report here the attainable sensitivity in the detection of density variations as a function of the beam energy, the depth inside the object and size and density of the inclusions. Using a 600 keV gamma beam, for an inclusion with a density increase of 30% with respect to the surrounding tissue and thickness along the beam of 5 mm, we obtain at midbrain position a resolution of about 2 mm and a contrast of 12%. In addition the simulation indicates that for the same gamma beam energy a complete brain scan would result in an effective dose of about 1 mSv.     

Monte Carlo study of the ion-induced electron current tunneling through a metal-insulator-metal junction

A Monte Carlo program is developed to investigate the kinetically excited electrons passing through a realistic Ag-Al₂O₃-Al junction when Ar⁺ ions impact on the top Ag layer. The program includes excitation of the target electrons (by projectile ions, recoiling target atoms and fast primary electrons) and subsequent transport of these excited electrons from Ag to bottom Al layer of the metal-insulator-metal (MIM) junction. The calculated tunneling electron yield is consistent with the recently reported experimental results. The simulation, however, enables the calculation of partial tunneling electron yields of the electrons excited by the projectile ions, recoil atoms and cascade electrons, the depth distribution of the electron excitation points in the MIM junction and energy distribution of the tunneling electrons. Our calculation showed that the electrons excited by fast cascade electrons are the major contributor to the tunneling electron yield while the direct contribution of projectile ions to tunneling electron yield is evident only at the projectile energies greater than 10 keV. The tunneling electrons have their origin close to the bottom end of the Ag layer and bulk of the tunneling electrons have energies around 2 eV.     

Monte Carlo study for physiological interference reduction in near-infrared spectroscopy based on empirical mode decomposition

Near-infrared spectroscopy (NIRS) can be used as the basis of non-invasive neuroimaging that may allow the measurement of haemodynamic changes in the human brain evoked by applied stimuli. Since this technique is very sensitive, physiological interference arising from the cardiac cycle and breathing can significantly affect the signal quality. Such interference is difficult to remove by conventional techniques because it occurs not only in the extracerebral layer but also in the brain tissue itself. Previous work on this problem employing temporal filtering, spatial filtering, and adaptive filtering have exhibited good performance for recovering brain activity data in evoked response studies. However, in this study, we present a time-frequency adaptive method for physiological interference reduction based on the combination of empirical mode decomposition (EMD) and Hilbert spectral analysis (HSA). Monte Carlo simulations based on a five-layered slab model of a human adult head were implemented to evaluate our methodology. We applied an EMD algorithm to decompose the NIRS time series derived from Monte Carlo simulations into a series of intrinsic mode functions (IMFs). In order to identify the IMFs associated with symmetric interference, the extracted components were then Hilbert transformed from which the instantaneous frequencies could be acquired. By reconstructing the NIRS signal by properly selecting IMFs, we determined that the evoked brain response is effectively filtered out with even higher signal-to-noise ratio (SNR). The results obtained demonstrated that EMD, combined with HSA, can effectively separate, identify and remove the contamination from the evoked brain response obtained with NIRS using a simple single source–detector pair.     

Spatial distribution of thorium fission rate in a fast spallation and fission neutron field: An experimental and Monte Carlo study

The Energy plus Transmutation (EpT) set-up of the Joint Institute for Nuclear Research (JINR), Dubna, Russia is composed of a lead spallation target surrounded by a blanket of natural uranium. The resultant neutron spectrum is a combination of spallation and fission spectra, modified by a reflective external layer of polyethylene and an internal absorbing layer of cadmium. The EpT set-up was irradiated with a beam of 4 GeV deuterons from the Nuclotron Accelerator at JINR. The spatial distribution of thorium fission rate within the assembly was determined experimentally, using a fission track detector technique, and compared with Monte Carlo predictions of the MCNPX code. Contributions of neutrons, protons, deuterons, photons and pions to total fission were taken into account. Close agreement between the experimental and calculated results was found.     

Monte Carlo simulation approach for a modified FMECA in a power plant

This paper presents a new tool for failure mode and effect analysis developed for a new Integrated Gasification and Combined Cycle plant in an important Italian oil refinery. The methodology is based on the integration between a modified Failure Mode Effect and Criticality Analysis (FMECA) and a Monte Carlo simulation as a method for testing the weights assigned to the measure of the risk priority numbers (RPNs). The RPN proposed consists of a weighted sum of six parameters (safety, machine importance for the process, maintenance costs, failure frequency, downtime length, and operating conditions) multiplied by a seventh factor (the machine access difficulty). Adopting this tool and considering the budget constraints, the best maintenance policy has been selected for each plant facility (about 140 in total). Copyright © 2000 John Wiley & Sons, Ltd.