Conventional Monte Carlo Codes Research Articles

NECP-MCX: A hybrid Monte-Carlo-Deterministic particle-transport code for the simulation of deep-penetration problems

A new particle-transport code NECP-MCX has been developed by Nuclear Engineering Computational Physics (NECP) laboratory of Xi’an Jiaotong University. NECP-MCX is aimed at the simulation of deep-penetration problems, including reactor radiation-shielding calculation, fusion reactor blanket calculation, etc. These problems are challenging for the Monte Carlo (MC) method, which needs a huge number of particles to obtain reliable results. For the problems mentioned above, it is also challenging for the deterministic method to obtain results with high precision due to discretization errors. To overcome these challenges, NECP-MCX has been developed based on a hybrid Monte-Carlo-Deterministic method from scratch. The hybrid Monte-Carlo-Deterministic method utilizes the deterministic method to generate consistent mesh-based weight-window and source-biasing parameters for the MC method to reduce variance. The numerical results demonstrate that NECP-MCX is able to simulate deep-penetration problems with higher efficiency compared to the conventional MC codes.

Multi-Regional Delta-Tracking Method for Neutron Transport Tracking in Monte Carlo Criticality Calculation

The Monte Carlo method has been widely used as a standard method to perform neutron transport simulations in reactor physics. In conventional Monte Carlo codes corresponding to the neutron transport tracking with ray-tracing method, the distances to material boundaries must be computed frequently when the neutron changes its kinetic energy or moving into new material regions to determine the neutron transport length. However, if the neutron’s mean free path length, to some extent, is greater than the macro size of the model, a huge amount of distances need to be computed. As a result, the computational efficiency of the neutron transport tracking will be degraded. An improved multi-regional delta-tracking method based on domain decomposition was introduced to solve this problem, in which the original heterogeneous model would be decomposed into many sub-regions and each sub-region was tracked using a local delta-tracking method. Consequently, the computational efficiency of the neutron transport tracking can be improved theoretically without the unnecessary distance calculations. The improved multi-regional delta-tracking method was incorporated into the MOSRT system, which is a multi-objective modeling and simulation platform for radiation transport system. Finally, the method was validated using the criticality benchmarks and its accuracy and efficiency were demonstrated in Monte Carlo criticality calculation. The results indicated that the new method was consistent with the conventional methods, but with a more competitive run-time performance.

On the accuracy of Monte Carlo based beam dynamics models for the degrader in proton therapy facilities

In a cyclotron-based proton therapy facility, the energy changes are performed by means of a degrader of variable thickness. The interaction of the proton beam with the degrader creates energy tails and increases the beam emittance. An accurate model of the degraded beam properties is important not only to better understand the performance of a facility already in operation, but also to support the development of new proton therapy concepts. The precision of the degraded beam properties, in terms of energy spectrum and transverse phase space, is influenced by approximations in the model of the particle–matter interaction. In this work the model of a graphite degrader has been developed with four Monte Carlo codes: three conventional Monte Carlo codes (FLUKA, GEANT4 and MCNPX) and the multi-purpose particle tracking code OPAL equipped with a simplified Monte Carlo routine. From the comparison between the different codes, we can deduce how the accuracy of the degrader model influences the precision of the beam dynamics model of a possible transport line downstream of the degrader.

Latent uncertainties of the precalculated track Monte Carlo method.

While significant progress has been made in speeding up Monte Carlo (MC) dose calculation methods, they remain too time-consuming for the purpose of inverse planning. To achieve clinically usable calculation speeds, a precalculated Monte Carlo (PMC) algorithm for proton and electron transport was developed to run on graphics processing units (GPUs). The algorithm utilizes pregenerated particle track data from conventional MC codes for different materials such as water, bone, and lung to produce dose distributions in voxelized phantoms. While PMC methods have been described in the past, an explicit quantification of the latent uncertainty arising from the limited number of unique tracks in the pregenerated track bank is missing from the paper. With a proper uncertainty analysis, an optimal number of tracks in the pregenerated track bank can be selected for a desired dose calculation uncertainty. Particle tracks were pregenerated for electrons and protons using EGSnrc and geant4 and saved in a database. The PMC algorithm for track selection, rotation, and transport was implemented on the Compute Unified Device Architecture (cuda) 4.0 programming framework. PMC dose distributions were calculated in a variety of media and compared to benchmark dose distributions simulated from the corresponding general-purpose MC codes in the same conditions. A latent uncertainty metric was defined and analysis was performed by varying the pregenerated track bank size and the number of simulated primary particle histories and comparing dose values to a "ground truth" benchmark dose distribution calculated to 0.04% average uncertainty in voxels with dose greater than 20% of Dmax. Efficiency metrics were calculated against benchmark MC codes on a single CPU core with no variance reduction. Dose distributions generated using PMC and benchmark MC codes were compared and found to be within 2% of each other in voxels with dose values greater than 20% of the maximum dose. In proton calculations, a small (≤ 1 mm) distance-to-agreement error was observed at the Bragg peak. Latent uncertainty was characterized for electrons and found to follow a Poisson distribution with the number of unique tracks per energy. A track bank of 12 energies and 60000 unique tracks per pregenerated energy in water had a size of 2.4 GB and achieved a latent uncertainty of approximately 1% at an optimal efficiency gain over DOSXYZnrc. Larger track banks produced a lower latent uncertainty at the cost of increased memory consumption. Using an NVIDIA GTX 590, efficiency analysis showed a 807 × efficiency increase over DOSXYZnrc for 16 MeV electrons in water and 508 × for 16 MeV electrons in bone. The PMC method can calculate dose distributions for electrons and protons to a statistical uncertainty of 1% with a large efficiency gain over conventional MC codes. Before performing clinical dose calculations, models to calculate dose contributions from uncharged particles must be implemented. Following the successful implementation of these models, the PMC method will be evaluated as a candidate for inverse planning of modulated electron radiation therapy and scanned proton beams.

Evaluation of PENFAST – A fast Monte Carlo code for dose calculations in photon and electron radiotherapy treatment planning

The aim of the present study is to demonstrate the potential of accelerated dose calculations, using the fast Monte Carlo (MC) code referred to as PENFAST, rather than the conventional MC code PENELOPE, without losing accuracy in the computed dose. For this purpose, experimental measurements of dose distributions in homogeneous and inhomogeneous phantoms were compared with simulated results using both PENELOPE and PENFAST. The simulations and experiments were performed using a Saturne 43 linac operated at 12 MV (photons), and at 18 MeV (electrons). Pre-calculated phase space files (PSFs) were used as input data to both the PENELOPE and PENFAST dose simulations. Since depth–dose and dose profile comparisons between simulations and measurements in water were found to be in good agreement (within ±1% to 1 mm), the PSF calculation is considered to have been validated. In addition, measured dose distributions were compared to simulated results in a set of clinically relevant, inhomogeneous phantoms, consisting of lung and bone heterogeneities in a water tank. In general, the PENFAST results agree to within a 1% to 1 mm difference with those produced by PENELOPE, and to within a 2% to 2 mm difference with measured values. Our study thus provides a pre-clinical validation of the PENFAST code. It also demonstrates that PENFAST provides accurate results for both photon and electron beams, equivalent to those obtained with PENELOPE. CPU time comparisons between both MC codes show that PENFAST is generally about 9–21 times faster than PENELOPE.

SU‐FF‐T‐327: Monte Carlo Dose Calculations in Homogeneous and Heterogeneous Media: A Comparison Between the PMCEPT Code and the MCNP5, EGS4, DPM Codes and Measurements

The Monte Carlo method for high‐energy photon and charged particle transport is the most accurate means for predicting dose distributions in radiation treatment of patients. Owing to rapid development of computer hardware and network technologies the use of this method is not restricted only to big research centers any more. A new parallel Monte Carlo electron and photon transport (PMCEPT) code [Kum and Lee, J. Kor. Phys. Soc. 47 (2005) 716] for calculating electron and photon beam doses has been developed based on a three dimensional geometry defined by computerized tomography (CT) images and implemented on the Beowulf PC cluster. The PMCEPT code was validated on the homogeneous and multi‐layered targets for megavoltage electron beams by comparing with the results of experiments and calculations from conventional Monte Carlo codes of the MCNP5, EGS4, and DPM. The computing time of the PMCEPT code was approximately twenty times faster than that of MCNP5 on the IBM ThinkPad X40 (laptop) with 1.2‐GHz CPU and 512‐MB ram memory operated by RedHat Linux 9. The PMCEPT results in general agreed well with others in homogeneous and heterogeneous media within a maximum of 2–3 % error. At the conference, we will show various benchmark results for the PMCEPT. This work was supported, in part, by the SRC/ERC program of MOST/KOSEF (grant number: R11‐1999‐054).

Study on kinetics of subcritical system: Contribution of delayed neutrons to the transient after a reactivity insertion

It is generally difficult to employ three dimensional spaces and time dependent kinetics by using a Monte Carlo method for nuclear reactor kinetics, because the random work analysis of a neutron becomes extremely difficult when conditions for neutron transport change with time. However, in most cases of kinetic analysis, in particular relevant to ADS systems, we meet with many cases, where the lifetime of prompt neutron is much shorter than that of the neutron transport condition. In calculating the kinetic evolution of a subcritical (SC) system, in this paper we propose a new calculation technique where a steady state equation for the neutron flux and a time-dependent one for the delayed neutron precursor density will be treated. In this paper, the accuracy of this theory is investigated by using a simple point reactor equation for several cases typical for ADS system. We obtained strict solution Φ∗ as a reference solution, Φ1 as a solution by the present method, and Φ2 as a solution where both neutrons and delayed neutron precursors are treated by using static equations. The obtained results show a good agreement between Φ1 and Φ∗, though the Φ2 agrees with Φ∗ poorly in all our cases. Finally, we can employ a conventional Monte Carlo code for neutron transport and analysis many kinetics problems of ADS systems with the help of delayed neutron precursor analysis.

Comparison of measured and Monte Carlo calculated dose distributions in inhomogeneous phantoms in clinical electron beams

Calculations of dose distributions in heterogeneous phantoms in clinical electron beams, carried out using the fast voxel Monte Carlo (MC) system XVMC and the conventional MC code EGSnrc, were compared with measurements. Irradiations were performed using the 9 MeV and 15 MeV beams from a Varian Clinac-18 accelerator with a 10 × 10 cm2 applicator and an SSD of 100 cm. Depth doses were measured with thermoluminescent dosimetry techniques (TLD 700) in phantoms consisting of slabs of Solid Water™ (SW) and bone and slabs of SW and lung tissue-equivalent materials. Lateral profiles in water were measured using an electron diode at different depths behind one and two immersed aluminium rods. The accelerator was modelled using the EGS4/BEAM system and optimized phase-space files were used as input to the EGSnrc and the XVMC calculations. Also, for the XVMC, an experiment-based beam model was used. All measurements were corrected by the EGSnrc-calculated stopping power ratios. Overall, there is excellent agreement between the corrected experimental and the two MC dose distributions. Small remaining discrepancies may be due to the non-equivalence between physical and simulated tissue-equivalent materials and to detector fluence perturbation effect correction factors that were calculated for the 9 MeV beam at selected depths in the heterogeneous phantoms.

MMC-a high-performance Monte Carlo code for electron beam treatment planning

The macro Monte Carlo (MMC) method has been developed to improve the speed of traditional Monte Carlo (MC) high-energy electron transport calculations without loss in accuracy. The MMC algorithm uses results derived from conventional MC simulations of electron transport through macroscopic spheres of various radii and consisting of a variety of media. Based on these results, electrons are transported in macroscopic steps through the absorber. The absorber geometry is represented by a three-dimensional (3D) density matrix, typically derived from computer tomographic (CT) data. Energy lost by the electrons along their paths through the absorber is scored in a 3D dose matrix. Transport of secondary electrons and bremsstrahlung photons is taken into account. Major modifications of the original implementation of the MMC algorithm have resulted in an improved version of the code, resolving earlier problems with electron transport across interfaces of different materials, and running at a substantially higher speed. Furthermore, the code has been integrated into a clinical 3D treatment planning system. MMC results are in good agreement with results from conventional MC codes and are obtained with a speed gain of about one order of magnitude for clinically relevant irradiation situations. Calculation times to obtain a relative statistical accuracy of 2% per dose grid voxel for small electron field sizes are short enough to be routinely useful in radiotherapy clinics on present day affordable workstation computers. Considering speed, accuracy and memory requirements, MMC is a promising alternative to currently available electron dose planning algorithms.