Novel reference radiation fields for pulsed photon radiation installed at PTB

Currently, ～70 % of the occupationally exposed persons in Germany are working in pulsed radiation fields, mainly in the medical sector. It has been known for a few years that active electronic dosemeters exhibit considerable deficits or can even fail completely in pulsed fields. Type test requirements for dosemeters exist only for continuous radiation. Owing to the need of a reference field for pulsed photon radiation and accordingly to the upcoming type test requirements for dosemeters in pulsed radiation, the Physikalisch-Technische Bundesanstalt has developed a novel X-ray reference field for pulsed photon radiation in cooperation with a manufacturer. This reference field, geared to the main applications in the field of medicine, has been well characterised and is now available for research and type testing of dosemeters in pulsed photon radiation.     

Uncertainties beyond statistics in Monte Carlo simulations

The Monte Carlo method has become an essential tool for the simulation of radiation and particle transport problems. The combination of its ease of use and the power of the method can create a temptation to use Monte Carlo as a 'black box' tool. In this paper, we shall mention a number of important issues that any user of a Monte Carlo computer code should keep firmly in mind when attempting a transport simulation, and we shall present a recent practical example to show the potential significance of such issues.     

Dynamic bounds coupled with Monte Carlo simulations

For the reliability analysis of engineering structures a variety of methods is known, of which Monte Carlo (MC) simulation is widely considered to be among the most robust and most generally applicable. To reduce simulation cost of the MC method, variance reduction methods are applied. This paper describes a method to reduce the simulation cost even further, while retaining the accuracy of Monte Carlo, by taking into account widely present monotonicity. For models exhibiting monotonic (decreasing or increasing) behavior, dynamic bounds (DB) are defined, which in a coupled Monte Carlo simulation are updated dynamically, resulting in a failure probability estimate, as well as a strict (non-probabilistic) upper and lower bounds. Accurate results are obtained at a much lower cost than an equivalent ordinary Monte Carlo simulation. In a two-dimensional and a four-dimensional numerical example, the cost reduction factors are 130 and 9, respectively, where the relative error is smaller than 5%. At higher accuracy levels, this factor increases, though this effect is expected to be smaller with increasing dimension. To show the application of DB method to real world problems, it is applied to a complex finite element model of a flood wall in New Orleans.     

Monte Carlo simulations of the Galileo energetic particle detector

Monte Carlo radiation transport studies have been performed for the Galileo spacecraft energetic particle detector (EPD) in order to study its response to energetic electrons and protons. Three-dimensional Monte Carlo radiation transport codes, MCNP version 4B (for electrons) and MCNPX version 2.2.3 (for protons), were used throughout the study. The results are presented in the form of “geometric factors” for the high-energy channels studied in this paper: B1, DC2, and DC3 for electrons and B0, DC0, and DC1 for protons. The geometric factor is the energy-dependent detector response function that relates the incident particle fluxes to instrument count rates. The trend of actual data measured by the EPD was successfully reproduced using the geometric factors obtained in this study.     

A Monte Carlo analysis of possible cell dose enhancement effects by uranium microparticles in photon fields

Uranium microparticles (radii: 50 nm-1.25 μm) were modelled surrounded by tissue and exposed to natural background radiation, in order to investigate potential dose enhancements from photon interactions. Generally, the results depended on the microparticle size. For a 0.5 μm radius microparticle in an isotropic field, it was found that the combined photon/electron doses deposited in 1 and 10 μm radii shells around it were raised by factors of ～3.8 and ～1.1, respectively; for a typical background photon fluence rate, these would correspond to increased energy depositions of a few 10s and a few 100s of eV y(-1), which are far less than the likely deposition rate resulting from the radioactive decay of a (238)U microparticle. The health hazard from uranium microparticle interactions with background photons was concluded to be negligible.     

Monte Carlo simulations of magnetic properties in multilayers

A Monte Carlo method has been used to simulate Heisenberg multilayer systems (L × L × 4P) consisting of alternating P ferromagnetic layers A and B with antiferromagnetic interface coupling J_AB. Finite-size effects on the specific heat and magnetisation thermal variation for two kinds of boundary conditions at the top and bottom planes are investigated. In particular, our Monte Carlo data evidence that the specific heat exhibits two peaks and a single phase transition occurs at the temperature which corresponds to the location of the high temperature peak (as L → ∞).     

Quantum Monte Carlo simulations of Hubbard type models

We present a review of recent Quantum Monte-Carlo results for one- and twodimensional Hubbard models. In one-dimension spectral properties are calculated with the maximum entropy method. At small doping, the one-particle excitations are characterized by a dispersive cosine-like band. Two different velocities for charge and spin-excitations are obtained which lead to a conformal charge c = 0.98 ± 0.05. In two-dimensions, we concentrate on two methods to detect superconducting ground states without prior knowledge of the symmetry of the underlying pair-pair correlations: flux quantization and the temperature derivative of the superfluid density. Both methods are based on extensions of quantum Monte-Carlo algorithms to incorporate magnetic fields. Our main results include numerical data which a) confirm the Kosterlitz-Thouless transition in the attractive Hubbard model b) show the absence of superconductivity in the quarter filled repulsive Hubbard model, and finally c) show no sign of a Kosterlitz-Thouless type transition in the three-band Hubbard model up to t_pd = 12.5 and hole doping = 0.25.     

Analysis of light-emitting diodes by Monte Carlo photon simulation

A Monte Carlo photon simulation method, which is based on statistical tracing of photons inside the chip, has been developed for analysis of LED's in quantitative terms. Also included in the analysis is practical modeling of textured surfaces, which are often employed for enhanced light output. The method with its unique versatility is applicable to virtually any chip geometry and measures various important parameters such as photon-output-coupling efficiency, detailed photon flight statistics, and photon-output distribution patterns. It is speculated that the method can easily be extended to development of LED lamps and packages.     

Monte Carlo simulations for the shielding of the future high-intensity accelerator facility FAIR at GSI

The Gesellschaft für Schwerionenforschung (GSI) is planning a significant expansion of its accelerator facilities. Compared to the present GSI facility, a factor of 100 in primary beam intensities and up to a factor of 10,000 in secondary radioactive beam intensities are key technical goals of the proposal. The second branch of the so-called Facility for Antiproton and Ion Research (FAIR) is the production of antiprotons and their storage in rings and traps. The facility will provide beam energies a factor of approximately 15 higher than presently available at the GSI for all ions, from protons to uranium. The shielding design of the synchrotron SIS 100/300 is shown exemplarily by using Monte Carlo calculations with the FLUKA code. The experimental area serving the investigation of compressed baryonic matter is analysed in the same way. In addition, a dose comparison is made for an experimental area operated with medium energy heavy-ion beams. Here, Monte Carlo calculations are performed by using either heavy-ion primary particles or proton beams with intensities scaled by the mass number of the corresponding heavy-ion beam.     

Monte Carlo simulations of magnetovolume instabilities in anti-Invar systems

We perform constant pressure Monte Carlo simulations of a spin-analogous model which describes coupled spatial and magnetic degrees of freedom on an fcc lattice. Our calculations qualitatively reproduce magnetovolume effects observed in some rare earth manganese compounds, especially in the anti-Invar material YMn₂. These are a sudden collapse of the magnetic moment which is connected with a huge volume change, and a largely enhanced thermal expansion coefficient.     

光子在闪烁晶体中传输的蒙特卡罗模拟

为了找到构筑闪烁晶体探测器的优化方法,使用蒙特卡罗方法对闪烁晶体BGO（Bi4Ge3O12,锗酸铋）的光收集效率进行了模拟研究。模拟结果表明：入射面为粗糙面,其余为抛光面,同时外层包装上高反射率的材料,可得到最大的光输出（约59．1％的光子被收集）;耦合剂的折射率的得到高的光输出也起着非常重要的作用。     

Monte Carlo calibration of avalanches described as Coulomb fluid flows

The idea that snow avalanches might behave as granular flows, and thus be described as Coulomb fluid flows, came up very early in the scientific study of avalanches, but it is not until recently that field evidence has been provided that demonstrates the reliability of this idea. This paper aims to specify the bulk frictional behaviour of snow avalanches by seeking a universal friction law. Since the bulk friction coefficient cannot be measured directly in the field, the friction coefficient must be calibrated by adjusting the model outputs to closely match the recorded data. Field data are readily available but are of poor quality and accuracy. We used Bayesian inference techniques to specify the model uncertainty relative to data uncertainty and to robustly and efficiently solve the inverse problem. A sample of 173 events taken from seven paths in the French Alps was used. The first analysis showed that the friction coefficient behaved as a random variable with a smooth and bell-shaped empirical distribution function. Evidence was provided that the friction coefficient varied with the avalanche volume, but any attempt to adjust a one-to-one relationship relating friction to volume produced residual errors that could be as large as three times the maximum uncertainty of field data. A tentative universal friction law is proposed: the friction coefficient is a random variable, the distribution of which can be approximated by a normal distribution with a volume-dependent mean.     

Monte Carlo simulation of the photon beam characteristics from medical linear accelerators

The MCNPX code has been employed on a personal computer to calculate the dosimetric characteristics of the photon beams from the 6 MV Siemens MX2 and the 10 MV Varian Clinac 2100C linear accelerators. A model of the treatment head includes the major geometric structure within the beam path. The model was used to calculate the energy spectra of the photon beam, percentage depth dose and the dose profiles. The accuracy of the calculated results is examined by comparing them with the measured dose distributions for the two machines. The computed and measured depth dose curves agree to within 2% for all the depths beyond the build-up region for both treatment machines. The calculations agree to within 2% of the measured profiles within the 100-50% dose level. It has been found that the MCNPX code is an effective tool for simulating the clinical photon beam.     

Computational steering in Monte Carlo simulations of thin film polystyrene

High molecular weight polymer systems show very long relaxation times, of the order of milliseconds or more. This time-scale proves practically inaccessible for atomic-scale dynamical simulation such as molecular dynamics. Even with a Monte Carlo (MC) simulation, the generation of statistically independent configurations is non-trivial. Many moves have been proposed to enhance the efficiency of MC simulation of polymers. Each is described by a proposal density Q(x'; x): the probability of selecting the trial state x' given that the system is in the current state x. This proposal density must be parametrized for a particular chain length, chemistry and temperature. Choosing the correct set of parameters can greatly increase the rate at which the system explores its configuration space. Computational steering (CS) provides a new methodology for a systematic search to optimize the proposal densities for individual moves, and to combine groups of moves to greatly improve the equilibration of a model polymer system. We show that monitoring the correlation time of the system is an ideal single parameter for characterizing the efficiency of a proposal density function, and that this is best evaluated by a distributed network of replicas of the system, with the operator making decisions based on the averages generated over these replicas. We have developed an MC code for simulating an anisotropic atomistic bead model which implements the CS paradigm. We report simulations of thin film polystyrene.     

Monte Carlo simulations of very low pressure chemical vapor deposition

Summary Simulation strategies for chemical vapor deposition (CVD) of thin solid films are presented, with emphasis on direct simulation Monte Carlo methods for analyzing and predicting physical phenomena occurring at low pressures and in micron-sized substrate features. The Monte Carlo approach is placed in perspective, relative to standard continuum mechanics-based strategies for modeling of CVD systems. Design issues that may be addressed through the developed methods are exemplified with computations for a new, technologically important CVD process for epitaxy of Si and Si_xGe_1-x alloys. Specifically, radiative heat transfer, rarefied gas-flow characteristics, species separation caused by pressure and thermal diffusion, growth-rate uniformity vs. surface reactivity, and deposition in microscopic features are addressed as parts of the overall CVD reactor-design approach. Process implications of rarefied transport effects unique to very low pressure CVD conditions are described. A new profile evolution technique is also introduced which predicts film topology, as well as the microstructure of the film.     

Three-dimensional Monte Carlo simulations of electromigration in polycrystalline thin films

The effects of electromigration in metal thin films is studied by means of atomistic Monte Carlo simulations. The simulator is based on a model of atom diffusion particularly suited to deal with polycrystalline three-dimensional films. Interatomic interactions are estimated by means of a simplified Morse potential while the driving force exerted by the charge carrier flux is represented as a perturbation on the diffusion activation barrier. The local current density is calculated using an equivalent resistor network. The results of simulated stress applied to various samples including a triple point are presented demonstrating the possibility of reproducing the initial stage of void formation with an atomistic model.     

Probabilistic calibration of discrete element simulations using the sequential quasi-Monte Carlo filter

The calibration of discrete element method (DEM) simulations is typically accomplished in a trial-and-error manner. It generally lacks objectivity and is filled with uncertainties. To deal with these issues, the sequential quasi-Monte Carlo (SQMC) filter is employed as a novel approach to calibrating the DEM models of granular materials. Within the sequential Bayesian framework, the posterior probability density functions (PDFs) of micromechanical parameters, conditioned to the experimentally obtained stress–strain behavior of granular soils, are approximated by independent model trajectories. In this work, two different contact laws are employed in DEM simulations and a granular soil specimen is modeled as polydisperse packing using various numbers of spherical grains. Knowing the evolution of physical states of the material, the proposed probabilistic calibration method can recursively update the posterior PDFs in a five-dimensional parameter space based on the Bayes’ rule. Both the identified parameters and posterior PDFs are analyzed to understand the effect of grain configuration and loading conditions. Numerical predictions using parameter sets with the highest posterior probabilities agree well with the experimental results. The advantage of the SQMC filter lies in the estimation of posterior PDFs, from which the robustness of the selected contact laws, the uncertainties of the micromechanical parameters and their interactions are all analyzed. The micro–macro correlations, which are byproducts of the probabilistic calibration, are extracted to provide insights into the multiscale mechanics of dense granular materials.     

Path integral Monte Carlo simulations of the melting of molecular hydrogen surfaces

We have used Path Integral Monte Carlo to study the surface melting of molecular hydrogen. Density profiles perpendicular and parallel to the bare H₂ surface are computed showing the formation of a liquid adlayer at 6 K, less than half the bulk melting temperature of para-hydrogen, 13.8 K. To estimate the onset temperature and depth of H₂ surface melting we determine the static structure factor within the individual H₂-layers for wave vectors in the plane and find no crystalline order down to 3 K in a partially filled H₂ adlayer at the free surface. We find quantum effects amplify the melting point depression at the free H₂ surface compared to bulk by a factor of five over classical Lennard-Jones solids and find that the zero-point fluctuations of molecules at the surface are much enhanced over their bulk values. We see vacancy formation in the solid before melting.