Effects of physics change in Monte Carlo code on electron pencil beam dose distributions

Pencil beam algorithms used in computerized electron beam dose planning are usually described using the small angle multiple scattering theory. Alternatively, the pencil beams can be generated by Monte Carlo simulation of electron transport. In a previous work, the 4th version of the Electron Gamma Shower (EGS) Monte Carlo code was used to obtain dose distributions from monoenergetic electron pencil beam, with incident energy between 1 MeV and 50 MeV, interacting at the surface of a large cylindrical homogeneous water phantom. In 2000, a new version of this Monte Carlo code has been made available by the National Research Council of Canada (NRC), which includes various improvements in its electron-transport algorithms. In the present work, we were interested to see if the new physics in this version produces pencil beam dose distributions very different from those calculated with oldest one. The purpose of this study is to quantify as well as to understand these differences. We have compared a series of pencil beam dose distributions scored in cylindrical geometry, for electron energies between 1 MeV and 50 MeV calculated with two versions of the Electron Gamma Shower Monte Carlo Code. Data calculated and compared include isodose distributions, radial dose distributions and fractions of energy deposition. Our results for radial dose distributions show agreement within 10% between doses calculated by the two codes for voxels closer to the pencil beam central axis, while the differences are up to 30% for longer distances. For fractions of energy deposition, the results of the EGS4 are in good agreement (within 2%) with those calculated by EGSnrc at shallow depths for all energies, whereas a slightly worse agreement (15%) is observed at deeper distances. These differences may be mainly attributed to the different multiple scattering for electron transport adopted in these two codes and the inclusion of spin effect, which produces an increase of the effective range of electrons.     

A simple approach to treat anisotropic elastic collisions in Monte Carlo calculations of the electron energy distribution function in cold plasmas

A simplified method allowing one to treat anisotropic electron heavy species elastic scattering in MonteCarlo models of gas discharges with the proper value for collision frequency is proposed The method is applied to an electric discharge in a Ne · Xe/HCl mixture, and the results are compared with the solution of the two-term expansion of the Boltzmann equation under the same conditions. Methods for reduction of computational time in Monte Carlo codes and the use of the Monte Carlo flux method are also discussed.     

Applicability of the condensed-random-walk Monte Carlo method at low energies in high-Z materials

The predictions of several Monte Carlo codes were compared with each other and with experimental results pertaining to the penetration of through gold foils of electrons incident with energies from 128 to 8 keV. The main purpose was to demonstrate that reflection and transmission coefficients, for number and energy, can be estimated reliably with a simple Monte Carlo code based on the condensed-random-walk and continuous-slowing-down approximations.     

Monte Carlo simulation of bremsstrahlung emission by electrons

The basic components of Monte Carlo simulation of bremsstrahlung emission by electrons are presented. Various theoretical cross-sections that have been used in Monte Carlo codes are described and the emphasis is on the more accurate partial-wave cross-sections for which numerical databases are available. Sampling algorithms for a combination of numerical scaled energy-loss cross-sections and various analytical approximations to the intrinsic angular distribution are presented. Analogue simulation of the energy spectra and angular distribution of X rays from targets irradiated by electron beams is very inefficient and a simple variance-reduction technique, which is easy to implement and has proven to be particularly effective in speeding up these simulations, is described. Results from simulations of X-ray spectra with the general-purpose Monte Carlo code penelope are compared with experimental data for different materials and incident electrons with energies in the 20 keV to 1 GeV energy range.     

An atlas of selected beta-ray spectra and depth-dose distributions in lithium fluoride and soft tissue generated by a fast Monte Carlo-based sampling method

A method to generate depth-dose distributions due to beta radiation in LiF and soft tissue is proposed. In this method, the EGS4 Monte Carlo radiation transport code is initially used to generate a library of monoenergetic electron depth-dose distributions in the material for electron energies in the range of 10 keV to 5 MeV in 10 keV increments. A polynomial least-squares fit is applied to each distribution. In addition, a theoretical model is developed to generate beta-ray energy spectra of selected radionuclides. A standard Monte Carlo random sampling technique is then employed to sample the spectra and generate the depth-dose distributions in LiF and soft tissue. The proposed method has an advantage over more traditional methods in that the actual radiation transport in the media is performed only once for a set of monoenergetic cases and the beta depth-dose distributions are easily generated by sampling this previously-acquired database in a matter of minutes. This method therefore reduces the demand on computer resources and time. The method can be used to calculate depth-dose distribution due to any beta-emitting nuclide or combination of nuclides with up to ten beta components.     

Advantages of mesh tallying in MCNP5 for soil analysis calculations

The Monte Carlo code, MCNP5, includes a mesh and lattice tally option useful for large matrix calculations. Recently, a fast lattice tally (FLT) was developed for MCNPX. We used these two codes to model an in-situ soil analysis system based on inelastic neutron scattering. The tallies were utilized to calculate the reaction rates of fast neutrons with carbon via inelastic reactions. The results of these three tallies and their respective computational times are compared, and the advantages of these methodologies discussed.     

Study of size, type and the kerma approximation for thermoluminescent dosimetry

This study aimed to investigate effects of the thermoluminescent dosimeter (TLD) size and type on the absorbed dose value by using of Monte Carlo calculations. The options in creating conditions to establish the kerma approximation were also studied. The Monte Carlo N-Particle (MCNPX 2.4.0) transport code was used to design simulations. Results of this work indicate that if common mineral materials of TLDs are replaced by air and a huge volume is applied for the TLD, the accurate assessment of absorbed doses is possible while the photon energy fluence in the TLD cell is convoluted with mass energy absorption coefficients of the real TLD material. In this method the simulation run-time is strongly decreased.     

Monte Carlo simulation and thermodynamic integration applied to protein charge transfer

We introduce a combination of Monte Carlo simulation and thermodynamic integration methods to address a model problem in free energy computations, electron transfer in proteins. The feasibility of this approach is tested using the ferredoxin protein from Clostridium acidurici. The results are compared to numerical solutions of the Poisson-Boltzmann equation and data from recent molecular dynamics simulations on charge transfer in a protein complex, the NrfHA nitrite reductase of Desulfovibrio vulgaris. Despite the conceptual and computational simplicity of the Monte Carlo approach, the data agree well with those obtained by other methods. A link to experiments is established via the cytochrome subunit of the bacterial photosynthetic reaction center of Rhodopseudomonas viridis.     

Radial dose profiles for pencil electron beams

The relationship between the Boltzmann and Fermi-Eyges-Yang equations governing electron transport is examined. Radial dose profiles for a pencil beam obtained by numerical solution of the Boltzmann equation in the small angle approximation are compared with both the Gaussian approximation and with Monte Carlo simulations for a carbon medium. For energies ranging from 5 to 20 MeV and penetration depths up to 75% of the range the numerical results are within 10% of the Monte Carlo results for the radial distance encompassing 63% of the energy deposition.     

Application of EPMA data for the development of the code systems TRANSURANUS and ALEPH.

In the present article, electron probe microanalysis data for Pu and Nd is being used for validating the predictions of the radial power profile in a nuclear fuel rod at an ultrahigh burn-up of 95 and 102 MWd/kgHM. As such the validation of both the new Monte Carlo burn-up code ALEPH and the simpler TUBRNP model of the fuel rod performance code TRANSURANUS has been extended. The analysis of the absolute concentrations and individual isotopes also indicates potential improvements in the predictive capabilities of the simple TUBRNP model, based on the one-group cross sections inferred from the neutron transport calculations in the ALEPH code. This is a first important step toward extending the application range of the fuel rod performance code to burn-up values projected in nuclear power rods based on current trends.     

Advantages of mesh tallying in MCNPX for 3D dose calculations in radiotherapy

The energy deposition mesh tally option of MCNPX Monte Carlo code is very useful for 3-Dimentional (3D) dose calculations. In this study, the 3D dose calculation was done for CT-based Monte Carlo treatment planning in which the energy deposition mesh tally were superimposed on merged voxel model. The results were compared with those of obtained from the common energy deposition (*F8) tally method for all cells of non-merged voxel model. The results of these two tallies and their respective computational times are compared, and the advantages of the proposed method are discussed. For this purpose, a graphical user interface (GUI) application was developed for reading CT slice data of patient, creating voxelized model of patient, optionally merging adjacent cells with the same material to reduce the total number of cells, reading beam configuration from commercial treatment planning system transferred in DICOM-RT format, and showing the isodose distribution on the CT images. To compare the results of Monte Carlo calculated and TiGRT planning system (LinaTech LLC, USA), treatment head of the Siemens ONCOR Impression accelerator was also simulated and the phase-space data on the scoring plane just above the Y-jaws was created and used. The results for a real prostate intensity-modulated radiation therapy (IMRT) plan showed that the proposed method was fivefold faster while the precision was almost the same.     

Computing the energy of a water molecule using multideterminants: a simple, efficient algorithm

Quantum Monte Carlo (QMC) methods such as variational Monte Carlo and fixed node diffusion Monte Carlo depend heavily on the quality of the trial wave function. Although Slater-Jastrow wave functions are the most commonly used variational ansatz in electronic structure, more sophisticated wave functions are critical to ascertaining new physics. One such wave function is the multi-Slater-Jastrow wave function which consists of a Jastrow function multiplied by the sum of Slater determinants. In this paper we describe a method for working with these wave functions in QMC codes that is easy to implement, efficient both in computational speed as well as memory, and easily parallelized. The computational cost scales quadratically with particle number making this scaling no worse than the single determinant case and linear with the total number of excitations. Additionally, we implement this method and use it to compute the ground state energy of a water molecule.     

Computer simulations of ligand–protein binding with ensembles of protein conformations: A Monte Carlo study of HIV‐1 protease binding energy landscapes

We present the results of molecular docking simulations with HIV‐1 protease for the sb203386 and skf107457 inhibitors by Monte Carlo simulated annealing. A simplified piecewise linear energy function, the standard AMBER force field, and the AMBER force field with solvation and a soft‐core smoothing component are employed in simulations with a single‐protein conformation to determine the relationship between docking simulations with a simple energy function and more realistic force fields. The temperature‐dependent binding free energy profiles of the inhibitors interacting with a single protein conformation provide a detailed picture of relative thermodynamic stability and a distribution of ligand binding modes in agreement with experimental crystallographic data. Using the simplified piecewise linear energy function, we also performed Monte Carlo docking simulations with an ensemble of protein conformations employing preferential biased sampling of low‐energy protein conformations, and the results are analyzed in connection with the free energy profiles. ©1999 John Wiley & Sons, Inc. Int J Quant Chem 72: 73–84, 1999     

Energy deposition in the plasma-facing components of Ignitor

The large fluxes of fusion neutrons produced in the Ignitor experiment can cause severe damage to the most exposed components of the tokamak or of the diagnostic system. In a simplified geometry model, the FLUKA and the MCNP-4B Monte Carlo codes are used to evaluate the influence of the neutron source energy and the material composition on the energy deposition in these components.     

Assessment of the suitability of Monte Carlo simulation for activity measurements of extended sources

Monte Carlo simulations can be a powerful tool in calibrating high-resolution gamma-ray spectrometry based on high pure germanium (HPGe) detectors. The purpose of this work is to examine the applicability of Monte Carlo simulations for the computation of the efficiency transfer in various measurement geometries on the basis of the detected efficiency for point source geometry. For this, GEANT4 code was applied for the computation of the detection efficiency for incident gamma energy of radionuclide placed at different distances from HPGe detector from 50 to 2,000 keV in addition for volume sources of different compositions and densities. The experimental efficiency curves were compared with the prediction of the GEANT4 code. Efficiency is computed at discrete values of point and volume sources in different distances to derive new efficiencies values for other distances.     

Super-Monte Carlo: A photon/electron dose calculation algorithm for radiotherapy

Super-Monte Carlo (SMC) is a method of dose calculation for radiotherapy which combines both analytical calculations and Monte Carlo electron transport. Analytical calculations are used where possible, such as the determination of photon interaction density, to decrease computation time. A Monte Carlo method is used for the electron transport in order to obtain high accuracy of results. To further speed computation, Monte Carlo is used once only, to form an electron track kernel (etk). The etk is a dataset containing the lengths and energy deposition of each step of a number of electron tracks. The etk is transported from each incident particle interaction site, from which the dose is calculated. Dose distributions calculated in heterogeneous media show SMC results similar to those of Monte Carlo. For the same statistical uncertainty, SMC takes an order of magnitude less computation time than a full Monte Carlo simulation. SMC has only been implemented for photons and electrons, however the same basic method could be used for the transport of other particles. Current development includes the optimisation of the etks and the code in order to decrease computation time, and also the inclusion of SMC onto a clinical planning system.     

Coarse-graining Calcium Dynamics on Stochastic Reaction-diffusion Lattice Model

We develop a coarse grained (CG) approach for efficiently simulating calcium dynamics in the endoplasmic reticulum membrane based on a fine stochastic lattice gas model. By grouping neighboring microscopic sites together into CG cells and deriving CG reaction rates using local mean field approximation, we perform CG kinetic Monte Carlo (kMC) simulations and find the results of CG-kMC simulations are in excellent agreement with that of the microscopic ones. Strikingly, there is an appropriate range of coarse proportion m, corresponding to the minimal deviation of the phase transition point compared to the microscopic one. For fixed m, the critical point increases monotonously as the system size increases, especially, there exists scaling law between the deviations of the phase transition point and the system size. Moreover, the CG approach provides significantly faster Monte Carlo simulations which are easy to implement and are directly related to the microscopics, so that one can study the system size effects at the cost of reasonable computational time.     

储能材料的模拟与设计

综述了近年来常用的计算模拟方法, 如第一原理计算, 分子动力学和蒙特-卡罗模拟. 介绍了应用这些方法在锂离子电池材料和储氢材料等储能材料研究中取得的成果和最新的进展, 展望了计算材料学和材料设计学在该领域中的应用前景.     

A rare event sampling method for diffusion Monte Carlo using smart darting

We identify a set of multidimensional potential energy surfaces sufficiently complex to cause both the classical parallel tempering and the guided or unguided diffusion Monte Carlo methods to converge too inefficiently for practical applications. The mathematical model is constructed as a linear combination of decoupled Double Wells [(DDW)(n)]. We show that the set (DDW)(n) provides a serious test for new methods aimed at addressing rare event sampling in stochastic simulations. Unlike the typical numerical tests used in these cases, the thermodynamics and the quantum dynamics for (DDW)(n) can be solved deterministically. We use the potential energy set (DDW)(n) to explore and identify methods that can enhance the diffusion Monte Carlo algorithm. We demonstrate that the smart darting method succeeds at reducing quasiergodicity for n ? 100 using just 1 × 10(6) moves in classical simulations (DDW)(n). Finally, we prove that smart darting, when incorporated into the regular or the guided diffusion Monte Carlo algorithm, drastically improves its convergence. The new method promises to significantly extend the range of systems computationally tractable by the diffusion Monte Carlo algorithm.     

Gas-liquid phase separation in oppositely charged colloids: stability and interfacial tension

We study the phase behavior and the interfacial tension of the screened Coulomb (Yukawa) restricted primitive model (YRPM) of oppositely charged hard spheres with diameter sigma using Monte Carlo simulations. We determine the gas-liquid and gas-solid phase transitions using free energy calculations and grand-canonical Monte Carlo simulations for varying inverse Debye screening length kappa. We find that the gas-liquid phase separation is stable for kappasigma相似文献