A Multiple Scattering Theory for Proton Penetration

We extend the electron small-angle multiple scattering theory to proton penetration. After introducing the concept of narrow energy spectra,the proton energy loss process is included in the proton deep penetration theory. It precisely describes the whole process of proton penetration.Compared to the Monte Carlo method,this method maintains the comparable precision and possesses much higher computational efficiency. Thus, it shows the real feasibility of applying this algorithm to proton clinical radiation therapy.     

MONTE CARLO TECHNIQUES

<正>Revised September 2011 by G.Cowan(RHUL).Monte Carlo techniques are often the only practical way to evaluate difficult integrals or to sample random variables governed by complicated probability density functions.Here we describe an assortment of methods for sampling some commonly occurring probability density functions.39.1.Sampling the uniform distribution Most Monte Carlo sampling or integration techniques assume a"random number generator,"which generates uniform statistically independent values on the half open interval[0.1);for reviews see,e.g..[1,2].Uniform random number generators are available in software libraries such as CERNLIB[3],CLHEP[4],and ROOT[5].For     

Calculation of the reactor neutron time of flight spectrum by convolution technique

It is a very complex and time-consuming process to simulate the nuclear reactor neutron spectrum from the reactor core to the export channel by applying a Monte Carlo program. This paper presents a new method to calculate the neutron spectrum by using the convolution technique which considers the channel transportation as a linear system and the transportation scattering as the response function. It also applies Monte Carlo Neutron and Photon Transport Code （MCNP） to simulate the response function numerically. With the application of convolution technique to calculate the spectrum distribution from the core to the channel, the process is then much more convenient only with the simple numerical integral numeration. This saves computer time and reduces some trouble in re-writing of the MCNP program.     

Justification of a Monte Carlo Algorithm for the Diffusion-Growth Simulation of Helium Clusters in Materials

A theoretical analysis of a Monte Carlo （MC） method for the simulation of the diffusion-growth of helium clusters in materials is presented. This analysis is based on an assumption that the diffusion-growth process consists of first stage, during which the clusters diffuse freely, and second stage in which the coalescence occurs with certain probability. Since the accuracy of MC simulation results is sensitive to the coalescence probability, the MC calculations in the second stage is studied in detail. Firstly, the coalescence probability is analytically formulated for the one-dimensional diffusion-growth ease. Thereafter, the one-dimensional results are employed to justify the MC simulation. The choice of time step and the random number generator used in the MC simulation are discussed.     

Ionization for Hf- and W-L-shell by electron impact

Electron-induced Hf-, W-L-shell partial, total production cross sections, mean ionization cross sections and Hf-L_3-shell ionization cross sections (at two energies) have been measured as functions of electron energies (from near threshold to 36keV). The influence of electrons reflected from the backing of the thin targets on measured results was corrected using a model to relate to the electron transport process. The mean paths of electron multi-scattered in the target itself (including forward and backward scattering) were calculated by means of Monte Carlo program (EGS4) and they were used to correct measured results. A comparison with both theoretical predictions was given.     

Influence of laser power density on damage of comb by photodynamic therapy—simulation and validation of mathematical models

Photodynamic therapy （PDT） has poor therapeutic outcomes for the treatment of port-wine stain （PWS） lesions with long drug-light intervals （DLIs）. This letter investigates the possibility of improving the treatment efficacy through increasing the laser power density using a computer simulation and a cock comb model. The computational model includes a Monte Carlo simulation for the laser distribution and a calculation of the singlet oxygen concentrations （102）. Both simulation and experimental results show that increasing the power density from i00 to 140 mW/cm^2 not only improves the PDT efficacy, but also results in the unwanted skin damage.     

Fast sinusoidal analysis algorithm based on energy of narrowband spectrum

A fast sinusoidal parameters extraction algorithm based on energy of narrowband spectrum is presented. To improve analysis accuracy and computational efficiency, the al- gorithm integrates the Fourier transforms of signal and its n-order signal derivatives. And energy of narrowband spectrum is used to approximate the energy of the whole spectrum of single sinusoidal signal, since most energy is concentrated in the main lobe of spectral windows. Experiment results show that compared with existing algorithms, the proposed algorithm improves analysis precision by 30%-60% and reduces computational complexity. Therefore it can be applied to real time signal analysis and speech communication.     

Low-temperature-cured highly conductive composite of Ag nanowires & polyvinyl alcohol

Flexible conductive films were fabricated from a low-temperature-cured, highly conductive composite of silver nanowires(as conducting filler) and polyvinyl alcohol(PVA, as binder). Sheet resistance of 0.12 ?/sq, conductivity of 2.63×10~4 S/cm, and contact resistance of 1.0 ?/cm~2 were measured in the films, along with excellent resistance to scratching and good flexibility, making them suitable electrical contact materials for flexible optoelectronic devices. Effects of curing temperature, curing duration, film thickness, and nanowire length on the film's electrical properties were studied.Due to the abundance of hydroxyl groups on its molecular chains, the addition of PVA improves the film's flexibility and resistance to scratching. Increased nanowire density and nanowire length benefit film conductance. Monte Carlo simulation was used to further explore the impact of these two parameters on the conductivity. It was observed that longer nanowires produce a higher length-ratio of conducting routes in the networks, giving better film conductivity.     

HPGe 探测器晶体尺寸及效率的研究

采用蒙特卡罗方法模拟计算光子的探测效率需对高纯锗( HPGe ) 探测器进行准确的建模。模拟计算研究了HPGe 晶体长度对探测效率的影响,并在空间不同的测量位置对放射源进行测量,将模拟计算与实验测量相结合,对探测器晶体的尺寸进行调整,获得了HPGe 探测器晶体的模拟计算的准确尺寸,并在122s1 332 keV 能量范围内对模拟结果进行了验证。结果表明,在此能量范围内HPGe 探测器的探测效率的模拟计算值与实验测量值的相对偏差大多数在5% 内,并建立点源探测效率与探测器轴向距离的关系。The accurate shape of HPGe detector is needed in order to calculate its detection efficiency with Monte Carlo methods. In our calculation, the influence of the HPGe crystal size on efficiency has been investigated; the final crystal sizes were determined by comparison with experiments and were validated by the experimental efficiency obtained at several source-to-detector positions. The results show that when the crystal dimensions determined are used to calculate the detection efficiency in the energy range 122s1 332 keV, the relative deviations between simulated and most experimental results were within 5%. In addition, the relationship between detection efficiency and axial distance to detector was established.     

Physical design and Monte Carlo simulations of a space radiation detector onboard the SJ-10 satellite

A radiation gene box (RGB) onboard the SJ-10 satellite is a device carrying mice and drosophila cells to determine the biological effects of space radiation environment. The shielded fluxes of different radioactive sources were calculated and the linear energy transfers of γ-rays, electrons, protons and α-particles in the tissue were acquired using A-150 tissue-equivalent plastic. Then, a conceptual model of a space radiation instrument employing three semiconductor sub-detectors for deriving the charged and uncharged radiation environment of the RGB was designed. The energy depositions in the three sub-detectors were classified into 15 channels (bins) in an algorithm derived from the Monte Carlo method. The physical feasibility of the conceptual instrument was also verified by Monte Carlo simulations.     

基于SALOME的蒙卡计算模型CAD反转可视化

基于开源SALOME平台,采用以体代面思想和栅元层次多叉树方法,开展蒙卡计算模型CAD反向转换及三维可视化研究。基于本文方法开发了CAD反转可视化程序模块SALOME-MC,模块可实现蒙卡计算模型几何建模、材料建模和三维可视化等功能。选取三种典型反应堆蒙卡计算模型对本文方法和程序进行测试验证,测试结果表明,本文方法和程序可妥善处理蒙卡计算模型的复杂几何体与大规模重复结构,并精准地实现蒙卡计算模型CAD三维反转可视化,证明SALOME-MC的蒙卡计算模型反转能力和可视化效果的正确性与可靠性,提高了蒙卡计算模型几何建模效率和展示度。     

闪光X射线照相蒙特卡罗程序的并行化

研究了闪光X射线辐射照像蒙特卡罗程序(FXRMC)在MPI平台下的并行计算实现,给出了实现过程中并行随机数的产生方法。对并行程序的测试结果表明:并行程序与串行程序结果一致,加速比比较理想,呈线性增长,并行效率在16个处理器上可达80%以上。算例的结果说明了并行化可有效地解决程序计算散射技术性能时的耗时问题,从而有效化解FXRMC耗时和大规模计算的困难,提高了FXRMC程序的计算规模和计算速度,达到了研究要求。 (Institute of Fluid Physics, CAEP, P. O. Box 919-105, Mianyang 621900, China)     

MC程序并行设计及提高加速比措施

MC程序的并行设计涉及算法及模块划分,它直接关系到并行加速效率的高低,中子－γ耦合输运蒙特卡罗程序MCNP经过行改造,实现了PVM和MPI两种系统下的并行化,由于作了模块化设计,并行加速效率极佳,PVM版和MPI版并行程序在多个处理器下的加速比均呈线性增长,相比PVM,MPI的适应性列强,多数情况下其效率高于OPVM,并行MCNP程序的计算结果可靠,MPI并行程序在16、32和64个处理器上的并行效率分别达到99％、97％和89％。     

描述离散系统动力学演变的Monte Carlo方法分析

通用动力学方程通过描述离散系统中颗粒尺度分布的演变过程来量化颗粒动力学演变过程,而Monte Carlo(MC)算法是求解通用动力学方程的重要方法.目前几种主流的MC算法为Liffman的直接模拟Monte Carlo算法(DSMC)、阶梯式常体积法、常数目法和多重Monte Carlo(MMC)算法.利用这些MC算法描述理想的纯凝并工况和纯破碎工况,发现:由于避免了多个动力学事件之间的解耦过程,基于事件驱动的MC算法比基于时间驱动的MC算法具有更高的计算精度和更低的计算代价;由于尽量减少对整体系统的扰动,阶梯式恢复模拟颗粒数目的MC算法比连续式恢复模拟颗粒数目的MC算法具有更高的精度;由于始终保持计算区域体积,多重Monte Carlo算法具有更友好的扩展性.     

反应堆的大规模几何分层建模

工程上大型设备使用CSG建模时需要数量极大的三维体素, 例如组成大亚湾堆芯模型的体素就有数十万个。JLAMT是北京应用物理与计算数学研究所面向蒙特卡洛核子输运计算开发的大规模并行可视建模工具软件,本文面向粒子输运程序的自动、可视化建模,开发了分层建模管理模块,实现分层建模并管理图层,从而简化建模和参数设置的操作。模块还增加快速查找、属性批量编辑和局部检查等功能,提高面向蒙特卡洛核子输运计算的三维复杂模型的建模效率。     

Improved algorithms and coupled neutron-photon transport for auto-importance sampling method

The Auto-Importance Sampling(AIS) method is a Monte Carlo variance reduction technique proposed for deep penetration problems, which can significantly improve computational efficiency without pre-calculations for importance distribution. However, the AIS method is only validated with several simple examples, and cannot be used for coupled neutron-photon transport. This paper presents improved algorithms for the AIS method, including particle transport, fictitious particle creation and adjustment, fictitious surface geometry, random number allocation and calculation of the estimated relative error. These improvements allow the AIS method to be applied to complicated deep penetration problems with complex geometry and multiple materials. A Completely coupled Neutron-Photon Auto-Importance Sampling(CNP-AIS) method is proposed to solve the deep penetration problems of coupled neutron-photon transport using the improved algorithms. The NUREG/CR-6115 PWR benchmark was calculated by using the methods of CNP-AIS, geometry splitting with Russian roulette and analog Monte Carlo, respectively. The calculation results of CNP-AIS are in good agreement with those of geometry splitting with Russian roulette and the benchmark solutions. The computational efficiency of CNP-AIS for both neutron and photon is much better than that of geometry splitting with Russian roulette in most cases, and increased by several orders of magnitude compared with that of the analog Monte Carlo.     

Simulation of the infrared radiation characteristics of high-temperature exhaust plume including particles using the backward Monte Carlo method

The analysis of the infrared radiation characteristics of high-temperature free-stream flow including particles is very significant for the field of target detection, combustion diagnosis and temperature measurement of flame. In this paper, the infrared radiation characteristics of high-temperature free-stream flow are calculated and analyzed using the backward Monte Carlo method, considering the effect of the directional radiation heat flux due to the particle scattering and the different boundary conditions. The calculation results of emitting, absorbing and anisotropically scattering media are compared with the forward Monte Carlo and finite-volume methods results, which shows the superiority on computational efficiency with the backward Monte Carlo method.     

热辐射输运问题的高效蒙特卡罗模拟方法

惯性约束聚变研究中,热辐射光子在介质中的输运以及热辐射光子与介质的相互作用是重要研究课题,蒙特卡罗方法是该类问题的重要研究手段之一.隐式蒙特卡罗方法虽然能正确地模拟热辐射在介质中的输运过程,但当模拟重介质(材料的吸收系数大)问题时,该方法花费的计算时间将变得很长,导致模拟效率很低.本文以离散扩散蒙特卡罗方法为基础,开发了"离散扩散蒙特卡罗方法辐射输运模拟程序",可以较好地解决重介质区的计算效率问题,但是离散扩散蒙卡罗方法在模拟轻介质区时精度不够高.辐射输运问题中通常既有轻介质也有重介质,为了能同时解决蒙特卡罗方法模拟的效率和精度问题,本文研究了离散扩散蒙特卡罗方法与隐式蒙特卡罗方法相结合的模拟方法,并提出了新的扩散区与输运区界面处理方法,研制了混合蒙特卡罗方法的辐射输运模拟程序.典型辐射输运问题模拟显示:在模拟重介质问题时,该程序能大幅缩短模拟时间,且能取得与隐式蒙特卡罗方法一致的结果;在模拟轻重介质均存在的问题时,与隐式蒙特卡罗方法相比,混合蒙特卡罗方法的模拟精度与其相当且计算效率同样能够得到显著提升.     

用Monte Carlo方法预测油水分离旋流器的分级效率

对油滴在水力旋流器中非线性随机运动的特点进行了分析,运用随机过程理论,建立了油滴运动的随机模型,并采用Monte Carlo方法进行模拟,预测旋流器的分级效率。结果表明,Monte Carlo法的预测结果与实际值吻合得较好,用这种方法来预测油水分离旋流器的分级效率是非常可靠的,它能够根据旋流器的结构和工艺参数,直接给出旋流器的分级效率。     

Computational complexity of impact size estimation for spreading processes on networks

Spreading processes on networks are often analyzed to understand how the outcome of the process (e.g. the number of affected nodes) depends on structural properties of the underlying network. Most available results are ensemble averages over certain interesting graph classes such as random graphs or graphs with a particular degree distributions. In this paper, we focus instead on determining the expected spreading size and the probability of large spreadings for a single (but arbitrary) given network and study the computational complexity of these problems using reductions from well-known network reliability problems. We show that computing both quantities exactly is intractable, but that the expected spreading size can be efficiently approximated with Monte Carlo sampling. When nodes are weighted to reflect their importance, the problem becomes as hard as the s-t reliability problem, which is not known to yield an efficient randomized approximation scheme up to now. Finally, we give a formal complexity-theoretic argument why there is most likely no randomized constant-factor approximation for the probability of large spreadings, even for the unweighted case. A hybrid Monte Carlo sampling algorithm is proposed that resorts to specialized s-t reliability algorithms for accurately estimating the infection probability of those nodes that are rarely affected by the spreading process.