锗酸铋晶体光电导性质的研究

生长了六种掺杂锗酸铋(简称 BGO)晶体(分别掺 Fe、Cr、Mn、W、Pb 和 Ce)。在合适的测试条件下,测量了它们的光吸收系数、光电导参数和暗电导率,并与未掺杂样品进行了比较。计算出了样品的特征参量μφτ,为上述材料光折变性质的研究提供了必不可少的数据。在此基础上,对 BG0∶Cr、BGO∶Fe 和BGO∶Mn 晶体的光折变机制进行了简略的讨论,认为 BGO∶Cr 中的光折变中心可能是:Cr~(3+)作为施主,Cr~(4+)作为电子陷阱;或 Cr~(4+)作为受主,Cr~(3+)为空穴陷阱。     

光子传输过程中g因子的计算

在电离辐射空气比释动能基准量值复现过程中,g因子作为关键组成部分之一参与量值复现和不确定度计算,其量值的确定需要通过光子的质能传输系数和质能吸收系数计算得到.采用不同的软件,在不同参数设置条件下模拟计算并对结果进行比较.结果 显示采用EGSnrc计算结果更为合理,而且对于低能光子,尽管g因子相对较小,但在不同的参数设置...     

光波在由左手材料和激活介质构成的光子晶体中的传输

用特征矩阵法计算了光波在包含左手材料和激活介质的一维光子晶体中的传播规律,当左手材料和激活介质厚度相等时,出现了超窄通带和透射率大于1的高增益现象,受激辐射的增强总是发生在带隙的边缘附近。进一步论证了受激辐射增强现象与光子带隙边缘群速度异常存在关联。随着频率的增加,光增益呈e指数增大。光频率不变时,光在光子晶体中的透射率随光子晶体周期数的增加呈线性增加。当左手材料和激活介质厚度不相等时,通带宽度增加,带边仍存在大于1的透射峰。     

随机共振系统的电路模拟及在微弱信号增强传输中的应用

采用电子线路仿真双稳随机共振系统,建立微弱信号增强传输单元.实验结果表明,该装置适合于低信噪比条件下微弱正弦信号的检测,并且可以有效增强周期脉冲信号及二进制数字脉冲信号的传输,为微弱故障特征信号的提取以及数字信号的远程传输中提供了一种实用装置.     

A spectral representation based model for Monte Carlo simulation

A new model is proposed for generating samples of real-valued stationary Gaussian processes. The model is based on the spectral representation theorem stating that a weakly stationary process can be viewed as a superposition of harmonics with random properties. The classical use of this theorem for Monte Carlo simulation is based on models consisting of a superposition of harmonics with fixed frequencies but random amplitude and phase. The resulting samples have the same period depending on the discretization of the frequency band. In contrast, the proposed model consists of a superposition of harmonics with random amplitude, phase, and frequency so that different samples have different periods depending on the particular sample values of the harmonic frequencies.

A band limited Gaussian white noise process is used to illustrate the proposed Monte Carlo simulation algorithm and demonstrate that the estimates of the covariance function based on the samples of the proposed model are not periodic.     

磁性多层膜系统自旋重取向行为的Monte Carlo模拟

依据Heisenberg模型,利用Monte　Carlo方法模拟了磁性多层膜系统的自旋重取向行为,研究了各向异性、偶极相互作用以及外磁场对系统自旋取向的影响。通过模拟计算,获得了系统组态、磁分量等随偶极相互作用、外加磁场和温度的变化规律,重点研究了磁性多层膜系统在外磁场作用下的磁滞现象。     

Node placement for triangular mesh generation by Monte Carlo simulation

A new approach of node placement for unstructured mesh generation is proposed. It is based on the Monte Carlo method to position nodes for triangular or tetrahedral meshes. Surface or volume geometries to be meshed are treated as atomic systems, and mesh nodes are considered as interacting particles. By minimizing system potential energy with Monte Carlo simulation, particles are placed into a near‐optimal configuration. Well‐shaped triangles or tetrahedra can then be created after connecting the nodes by constrained Delaunay triangulation or tetrahedrization. The algorithm is simple, easy to implement, and works in an almost identical way for 2D and 3D meshing. Copyright © 2005 John Wiley & Sons, Ltd.     

Procedures of Monte Carlo transport simulation for applications in system engineering

Monte Carlo (MC) simulation is the most promising tool for performing realistic reliability and availability analysis of complex systems. Yet, the efficient use of MC simulation technique is not trivial in large scale applications.This paper considers the two commonly adopted approaches to MC simulation: the direct, component-based approach and the indirect, system-based approach. The mathematical details of the two approaches are worked out in detail, so as to show their probabilistic equivalence. The proper formulation for biasing the simulation is introduced, thus leading to the correct expressions for the statistical weights.Both approaches are applied, in an analog as well as in a biased scheme, to a simple system of the literature and comparisons are made with respect to the computing time and the goodness of the estimate, as measured by the variance of the results.     

Monte Carlo simulation of low density flows

The necessity for adopting a kinetic-theoretical approach to obtain aerodynamic characteristics in low density flow past space vehicles is highlighted in this paper; it is shown how long-standing difficulties in theoretically handling such flows can be circumvented by adopting a Monte Carlo technique. The principles underlying the technique are briefly described, and are first illustrated by applying the technique to the evaluation of the drag of cylinders and cones in collisionless flow. The Markoff process underlying the Monte Carlo simulation of the full Boltzmann equation with collisions is then described in detail. Instead of the time-counter strategy of Bird, a theoretically sounder ‘Random Collision Number’ (RCN) strategy has been adopted in the present simulation. In this strategy the number of collisions in each time-step in the computation is a random number drawn from an appropriate distribution. Computer programs using this strategy have been developed for calculating aerodynamic characteristics like drag and heat transfer for a cone in the transition regime between free molecule and continuum flow. The results obtained from these programs show that both time-counter and RCN strategies require almost the same computer time.     

Monte Carlo simulation of nucleation and growth of thin films

We study thin film growth using a lattice-gas, solid-on-solid model employing the Monte Carlo technique. The model is applied to chemical vapour deposition (CVD) by including the rate of arrival of the precursor molecules and their dissociation. We include several types of migration energies including the edge migration energy which allows the diffusive movement of the monomer along the interface of the growing film, as well as a migration energy which allows for motion transverse to the interface. Several well-known features of thin film growth are mimicked by this model, including some features of thin copper films growth by CVD. Other features reproduced are—compact clusters, fractal-like clusters, Frank-van der Merwe layer-by-layer growth and Volmer-Weber island growth. This method is applicable to film growth both by CVD and by physical vapour deposition (PVD).     

Genetic algorithms and Monte Carlo simulation for optimal plant design

We present an approach to the optimal plant design (choice of system layout and components) under conflicting safety and economic constraints, based upon the coupling of a Monte Carlo evaluation of plant operation with a Genetic Algorithms-maximization procedure. The Monte Carlo simulation model provides a flexible tool, which enables one to describe relevant aspects of plant design and operation, such as standby modes and deteriorating repairs, not easily captured by analytical models. The effects of deteriorating repairs are described by means of a modified Brown–Proschan model of imperfect repair which accounts for the possibility of an increased proneness to failure of a component after a repair. The transitions of a component from standby to active, and vice versa, are simulated using a multiplicative correlation model. The genetic algorithms procedure is demanded to optimize a profit function which accounts for the plant safety and economic performance and which is evaluated, for each possible design, by the above Monte Carlo simulation.In order to avoid an overwhelming use of computer time, for each potential solution proposed by the genetic algorithm, we perform only few hundreds Monte Carlo histories and, then, exploit the fact that during the genetic algorithm population evolution, the fit chromosomes appear repeatedly many times, so that the results for the solutions of interest (i.e. the best ones) attain statistical significance.     

A Monte Carlo simulation model for stationary non-Gaussian processes

A class of stationary non-Gaussian processes, referred to as the class of mixtures of translation processes, is defined by their finite dimensional distributions consisting of mixtures of finite dimensional distributions of translation processes. The class of mixtures of translation processes includes translation processes and is useful for both Monte Carlo simulation and analytical studies. As for translation processes, the mixture of translation processes can have a wide range of marginal distributions and correlation functions. Moreover, these processes can match a broader range of second order correlation functions than translation processes. The paper also develops an algorithm for generating samples of any non-Gaussian process in the class of mixtures of translation processes. The algorithm is based on the sampling representation theorem for stochastic processes and properties of the conditional distributions. Examples are presented to illustrate the proposed Monte Carlo algorithm and compare features of translation processes and mixture of translation processes.     

Defining the surface binding energy in dynamic Monte Carlo simulation for reactive sputtering of compounds

In Monte Carlo simulations of reactive sputtering, it is commonly assumed that the surface binding energy (SBE) for the different phases in the target exhibits a linear behaviour in the transition between the metal mode and the compound mode. In this work we study how the transition between the two modes takes place, and more specifically attempt to experimentally identify how the SBE for the different phases behaves in the transition between the two modes. In essence, this is done by comparing XPS measurements of the aluminium 2p binding energy on samples comprising pure aluminium, stoichiometric aluminium nitride and aluminium oxide with the corresponding measurements on understoichiometric aluminium nitride samples. In this work, it is assumed that the binding energy of the core level is directly correlated to the SBE of the phase in question. That is to say, if the aluminium 2p binding energy in aluminium nitride exhibits a constant and discrete value independent of the nitrogen concentration, the SBE for the compound exhibits a constant and discrete value independent of the surface concentration of nitrogen. It was found by the XPS measurement that the aluminium 2p binding energy in aluminium nitride exhibits a constant and discrete value independent of the nitrogen concentration in the samples and it was, therefore, concluded that the SBE for the different phases exhibits constant and discrete values independent of the surface concentration of nitrogen. The discrete behaviour of the SBE was implemented in the TRIDYN program and the results from these simulations were compared with simulations in which it is assumed that the SBE of the different phases exhibits a linear behaviour in the transition between the metal mode and the compound mode.