Monte Carlo simulation of the high energy cosmic muon background in a resonant gravitational wave antenna

We present the results of a Monte Carlo simulation for the energy loss distribution of high energy cosmic muons crossing a Weber-type gravitational wave (g.w.) antenna. The number of events per day of energy greater than an assigned value, generated in the antenna by the muons, is deduced.

The simulation shows that a rate of 60 events per week due to the cosmic background is expected in a sea-level g.w. detector with an energy sensitivity ten times greater than that of the present antennas. With the sensitivity of the resonant detectors approaching the quantum limit value the rate will increase to 5 × 10⁴ events per days. Therefore it seems unavoidable to carry on the experiment in an underground laboratory.     

Monte Carlo simulation of light transport in tissue: unscattered absorption events

A source of error in the Monte Carlo simulation of the fluence rate in turbid media is the inaccurate recording of unscattered absorption events. The form and magnitude of the error have been studied for Gaussian and uniform beam profiles simulated in cylindrical and Cartesian coordinates. In each case the error decreases as the lateral sampling lattice spacing decreases and is less than 2% of the incident peak irradiance when the beam radius is greater than five lattice spacings. To avoid the error, one may calculate analytically the fluence rate caused by unscattered absorption events.     

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.     

Monte Carlo modeling for individual monitoring

Thanks to the continuously increasing computer power, Monte Carlo techniques are progressively playing a key role in radiation dosimetry, in the field of dose assessment from internal and external exposures. Internal dosimetry aspects are presented in a separate paper in the same issue. For external exposure, individual monitoring techniques provide suitable tools to estimate the personal dose equivalent Hp(d), that should be a conservative estimate of the effective dose. Personal dosemeters should be designed and type tested in terms of Hp(d) and also irradiations facilities should be characterised in terms of the same operational quantity. This paper provides a concise overview on the role played by monte Carlo techniques in the field.     

Assessment of low probability events of dynamical systems by controlled Monte Carlo simulation

Various procedures to extend the applicability and to increase the efficiency of Monte Carlo simulation (MCS) for the analysis of complex dynamical systems are discussed. In particular, the capabilities of the methods denoted Russian Roulette and Splitting (RR&S) and Double and Clump (D&C) are reviewed with regard to their capabilities to analyze such systems. In this context, the difficulties in identifying the ‘important' regions for simulation are detailed. It is shown that these difficulties may be circumvented by a newly introduced ‘distance controlled' MCS. This procedure, which allows the prediction of very low probability events and the analysis of systems of higher dimension, is applicable not only to mechanical systems and structures but also to complex dynamical systems encountered, for example, in economics, physics, etc. The procedure is shown to be particularly suited to cases where exact analytical methods and direct Monte Carlo simulation are infeasible, hence, being well suited for practical application.     

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。     

Monte Carlo methods for pricing financial options

Pricing financial options is amongst the most important and challenging problems in the modern financial industry. Except in the simplest cases, the prices of options do not have a simple closed form solution and efficient computational methods are needed to determine them. Monte Carlo methods have increasingly become a popular computational tool to price complex financial options, especially when the underlying space of assets has a large dimensionality, as the performance of other numerical methods typically suffer from the ‘curse of dimensionality’. However, even Monte-Carlo techniques can be quite slow as the problem-size increases, motivating research in variance reduction techniques to increase the efficiency of the simulations. In this paper, we review some of the popular variance reduction techniques and their application to pricing options. We particularly focus on the recent Monte-Carlo techniques proposed to tackle the difficult problem of pricing American options. These include: regression-based methods, random tree methods and stochastic mesh methods. Further, we show how importance sampling, a popular variance reduction technique, may be combined with these methods to enhance their effectiveness. We also briefly review the evolving options market in India.     

Monte Carlo evaluated parameters for internal dosimetry

The radiation doses received by individuals from radionuclides which enter the human body cannot be measured directly but must be inferred. In these calculations, several measurable quantities (such as the internal whole body burden or urine daily excretion) and quantities derived from models are employed. The Radiation Protection Quantities for internal dosimetry are, in principle, the same as for external dosimetry with the addition of quantities taking into account that the doses in the body are protracted. Other parameters are also necessary for the dose assessment, such as the SAFs (Specific Absorbed Fractions). All these quantities are calculated using Monte Carlo codes and complex anthropomorphic phantoms. Monte Carlo codes are also widely employed as useful tools during the calibration procedure for in vivo measurements. This paper summarises the role played by Monte Carlo modelling in these fields.     

Gradient estimation for applied Monte Carlo analyses

For many practical applications of system analysis by Monte Carlo simulation, an important piece of information is the sensitivity of the outcome to input information. One matter of interest is the sensitivity of the outcome of the variables controlling it, that is the gradients with respect to the (usually implicit) performance function. Typically, analytical first (and higher) derivatives are not available and the usual numerical approach requires major computational effort. The present paper proposes estimation of gradients using a simplified (linear) response surface, which is a function of the random variables, and which is constructed after the Monte Carlo simulation has been performed. It uses all, or a subset of, the simulation run outcomes. No extra simulation runs are required. There are few restrictions on the form of the performance function and the gradients are estimated at small computational cost. The present paper is restricted to normal random variables.     

Monte Carlo method for transient eddy-current calculations

This paper deals with the calculation of transient eddy currents by a Markov chain Monte Carlo (MCMC) method. After we illustrate the principle in a one-dimensional calculation, we treat a two-dimensional problem. Then, we show simulation results and we discuss advantages and disadvantages of this method. An important advantage is that MCMC methods can be more efficient than finite-element methods in transient problems because they give an estimate of the solution at a point in space without calculation of the whole field distribution.     

g因子的蒙特卡罗模拟计算

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,而且对于低能光子来说,尽管g因子相对较小,但在不同的参数设置条件下所得到的数值差异较大。因此在涉及到低能光子的质能传输系数和质能吸收系数的计算和使用过程中,需对有关的相互作用的物理机制予以重视。     

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.     

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.     

Magnetism in Nanoislands: a Monte Carlo Study

The properties of nanoislands consisting of mixed spins-2 and -5/2 have been investigated using Monte Carlo simulations. Some interesting phenomena have been found in the thermal variations of the nanoisland system. The shapes of total magnetization and total magnetic susceptibility are greatly influenced by the exchange couplings. The reduced transition temperature of the nanoisland is deduced. The magnetic hysteresis cycles are obtained for different temperatures, crystal fields, and exchange interactions. Some results obtained in the nanoisland may have potential applications in different research fields, such as electronics, optics, mechanics, and even biomedicine and molecular devices.     

Monte Carlo modelling of a simple accident dosemeter

A simple dosemeter made of a sulphur tablet, bare and cadmium-covered indium foils and a cadmium-covered copper foil has been modelled using MCNP5. Studies of the model without phantom or other confounding factors have shown that the cross sections and fluence-to-dose factors generated by the Monte Carlo method agree with those generated by analytic expressions for the high energy component. In this study, a comparison of the effect of location on phantoms and an extension to low and intermediate energies is done. The activities expected from exposure to four critical assemblies on phantom is calculated and compared with observations.     

Monte Carlo simulation of a medical linear accelerator for radiotherapy use

A Monte Carlo code MCNPX (Monte Carlo N-particle) was used to model a 25 MV photon beam from a PRIMUS (KD2-Siemens) medical linear electron accelerator at the Centre Antoine Lacassagne in Nice. The entire geometry including the accelerator head and the water phantom was simulated to calculate the dose profile and the relative depth-dose distribution. The measurements were done using an ionisation chamber in water for different square field ranges. The first results show that the mean electron beam energy is not 19 MeV as mentioned by Siemens. The adjustment between the Monte Carlo calculated and measured data is obtained when the mean electron beam energy is approximately 15 MeV. These encouraging results will permit to check calculation data given by the treatment planning system, especially for small fields in high gradient heterogeneous zones, typical for intensity modulated radiation therapy technique.     

Monte Carlo simulation of a transition radiation detector

This paper employs Monte Carlo simulations of the performance of a transition radiation detector (TRD). The program has been written for the TRD in the ZEUS spectrometer, which separates electrons from hadrons in the momentum range between 1 and 30 GeV/c. Both, total charge method and cluster counting method were simulated taking into account various experimental parameters. In particular, it was found that the cluster counting method relies on a quantitative understanding of the background originating from the production of δ-electrons by charged particles. The results of the Monte Carlo calculations are in agreement with experimental data obtained with prototypes within a systematic uncertainty of 20%. We applied our Monte Carlo program to studies in order to find an optimum layout for the TRD within available space in the ZEUS spectrometer. In this context, the performance of TRD layouts with different geometries and materials has been evaluated comprehensively. The geometry found by optimization promises an improvement on hadron suppression by a factor of about two for both methods compared with present results from test measurements. Applying algorithms for a detailed analysis of the energy and space distributions of the clusters in the TRD, hadrons in the momentum range from 1 to 30 GeV/c can be suppressed to a level of less than 2%. This method of cluster analysing improves the suppression of hadrons by a factor of about two compared to the total charge method.