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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Commissioning of a Varian Clinac iX 6 MV photon beam using Monte Carlo simulation

Monte Carlo modelling of a linear accelerator is the first and most important step in Monte Carlo dose calculations in radiotherapy. Monte Carlo is considered today to be the most accurate and detailed calculation method in different fields of medical physics. In this research, we developed a photon beam model for Varian Clinac iX 6 MV equipped with MilleniumMLC120 for dose calculation purposes using BEAMnrc/DOSXYZnrc Monte Carlo system based on the underlying EGSnrc particle transport code. Monte Carlo simulation for this commissioning head LINAC divided in two stages are design head Linac model using BEAMnrc, characterize this model using BEAMDP and analyze the difference between simulation and measurement data using DOSXYZnrc. In the first step, to reduce simulation time, a virtual treatment head LINAC was built in two parts (patient-dependent component and patient-independent component). The incident electron energy varied 6.1 MeV, 6.2 MeV and 6.3 MeV, 6.4 MeV, and 6.6 MeV and the FWHM (full width at half maximum) of source is 1 mm. Phase-space file from the virtual model characterized using BEAMDP. The results of MC calculations using DOSXYZnrc in water phantom are percent depth doses (PDDs) and beam profiles at depths 10 cm were compared with measurements. This process has been completed if the dose difference of measured and calculated relative depth-dose data along the central-axis and dose profile at depths 10 cm is ≤ 5%. The effect of beam width on percentage depth doses and beam profiles was studied. Results of the virtual model were in close agreement with measurements in incident energy electron 6.4 MeV. Our results showed that photon beam width could be tuned using large field beam profile at the depth of maximum dose. The Monte Carlo model developed in this study accurately represents the Varian Clinac iX with millennium MLC 120 leaf and can be used for reliable patient dose calculations. In this commissioning process, the good criteria of dose difference in PDD and dose profiles were achieve using incident electron energy 6.4 MeV.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2014

Multilevel Monte Carlo simulation of Coulomb collisions

We present a new, for plasma physics, highly efficient multilevel Monte Carlo numerical method for simulating Coulomb collisions. The method separates and optimally minimizes the finite-timestep and finite-sampling errors inherent in the Langevin representation of the Landau–Fokker–Planck equation. It does so by combining multiple solutions to the underlying equations with varying numbers of timesteps. For a desired level of accuracy ε, the computational cost of the method is O(ε{sup −2}) or O(ε{sup −2}(lnε){sup 2}), depending on the underlying discretization, Milstein or Euler–Maruyama respectively. This is to be contrasted with a cost of O(ε{sup −3}) for direct simulation Monte Carlo or binary collision methods. We successfully demonstrate the method with a classic beam diffusion test case in 2D, making use of the Lévy area approximation for the correlated Milstein cross terms, and generating a computational saving of a factor of 100 for ε=10{sup −5}. We discuss the importance of the method for problems in which collisions constitute the computational rate limiting step, and its limitations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Floating Block Method for Quantum Monte Carlo Simulations

Quantum Monte Carlo simulations are powerful and versatile tools for the quantum many-body problem. In addition to the usual calculations of energies and eigenstate observables, quantum Monte Carlo simulations can in principle be used to build fast and accurate many-body emulators using eigenvector continuation or design time-dependent Hamiltonians for adiabatic quantum computing. Furthermore, these new applications require something that is missing from the published literature, an efficient quantum Monte Carlo scheme for computing the inner product of ground state eigenvectors corresponding to different Hamiltonians. In this work, we introduce an algorithm called the floating block method, which solves the problem by performing Euclidean time evolution with two different Hamiltonians and interleaving the corresponding time blocks. We use the floating block method and nuclear lattice simulations to build eigenvector continuation emulators for energies of 4 He, 8 Be, 12 C, and 16 O nuclei over a range of local and nonlocal interaction couplings. From the emulator data, we identify the quantum phase transition line from a Bose gas of alpha particles to a nuclear liquid.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2014

SU-E-T-314: The Application of Cloud Computing in Pencil Beam Scanning Proton Therapy Monte Carlo Simulation

Purpose: Monte Carlo simulation plays an important role for proton Pencil Beam Scanning (PBS) technique. However, MC simulation demands high computing power and is limited to few large proton centers that can afford a computer cluster. We study the feasibility of utilizing cloud computing in the MC simulation of PBS beams. Methods: A GATE/GEANT4 based MC simulation software was installed on a commercial cloud computing virtual machine (Linux 64-bits, Amazon EC2). Single spot Integral Depth Dose (IDD) curves and in-air transverse profiles were used to tune the source parameters to simulate an IBA machine. With the use of StarCluster software developed at MIT, a Linux cluster with 2–100 nodes can be conveniently launched in the cloud. A proton PBS plan was then exported to the cloud where the MC simulation was run. Results: The simulated PBS plan has a field size of 10×10cm{sup 2}, 20cm range, 10cm modulation, and contains over 10,000 beam spots. EC2 instance type m1.medium was selected considering the CPU/memory requirement and 40 instances were used to form a Linux cluster. To minimize cost, master node was created with on-demand instance and worker nodes were created with spot-instance. The hourly cost for the 40-node cluster was $0.63 and the projected cost for a 100-node cluster was $1.41. Ten million events were simulated to plot PDD and profile, with each job containing 500k events. The simulation completed within 1 hour and an overall statistical uncertainty of < 2% was achieved. Good agreement between MC simulation and measurement was observed. Conclusion: Cloud computing is a cost-effective and easy to maintain platform to run proton PBS MC simulation. When proton MC packages such as GATE and TOPAS are combined with cloud computing, it will greatly facilitate the pursuing of PBS MC studies, especially for newly established proton centers or individual researchers.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2018

Ferromagnetic Nanoparticles of Ising Spin-1 with a Rubik’s Cube Structure: Monte Carlo Simulations

Using Monte Carlo simulations, magnetic properties of the ferromagnetic nanoparticles of Ising spin-1 are investigated in the framework of the Ising model. The system is considered to have a Rubik’s cube structure composed of nanocubes having an equivalent exchange coupling, while, between adjacent nanocubes, the exchange coupling is assumed to vary. Both size effects and system parameters’ influence on phase diagrams of the nanosystem are studied. Thus, the magnetic properties of the system such as the critical temperature, the magnetization, and the coercive field are computed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Reducing the Spatial Discretization Error of Thermal Emission in Implicit Monte Carlo Simulations

Implicit Monte Carlo simulations of thermal radiative transport can exhibit what is known as teleportation error in problems with strong coupling between radiation and matter. Teleportation error occurs when energy deposited in a localized region of a spatial zone is emitted throughout the zone in the next time step. Teleportation error is commonly reduced by biasing the positions of photon thermal emission using a fit to the spatial distribution of temperature to the fourth power. The current work samples and stores locations along photon paths based on absorption probabilities. These locations are used as sites for emission in the subsequent time step. This method of teleportation correction is demonstrated in several sample problems, and is validated against an Implicit Monte Carlo Diffusion Method, which does not exhibit teleportation error. We report the new method reduces teleportation error relative to the source tilting method, and enables the use of lower spatial resolutions than would be required to mitigate teleportation error using the source tilting method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Steady state likelihood ratio sensitivity analysis for stiff kinetic Monte Carlo simulations

Kinetic Monte Carlo simulation is an integral tool in the study of complex physical phenomena present in applications ranging from heterogeneous catalysis to biological systems to crystal growth and atmospheric sciences. Sensitivity analysis is useful for identifying important parameters and rate-determining steps, but the finite-difference application of sensitivity analysis is computationally demanding. Techniques based on the likelihood ratio method reduce the computational cost of sensitivity analysis by obtaining all gradient information in a single run. However, we show that disparity in time scales of microscopic events, which is ubiquitous in real systems, introduces drastic statistical noise into derivative estimates for parameters affecting the fast events. In this work, the steady-state likelihood ratio sensitivity analysis is extended to singularly perturbed systems by invoking partial equilibration for fast reactions, that is, by working on the fast and slow manifolds of the chemistry. Derivatives on each time scale are computed independently and combined to the desired sensitivity coefficients to considerably reduce the noise in derivative estimates for stiff systems. The approach is demonstrated in an analytically solvable linear system.

Núñez, M.↗
DOE OSTI2014

Phase Behavior of Asymmetrically Charged Colloids Investigated by Monte Carlo Simulation

Using Monte Carlo simulations, we investigate the structural characteristics of an interacting hard sphere system with shifted charge. The focus is placed on understanding the dependence of its phase behavior on charge asymmetry. Two different phase transitions are discovered for this model system. Upon increasing the volume fraction, a liquid-to-crystal transition first occurs at a significantly lower volume fraction in comparison to that of the centro-charged system. This is due to the stronger effective inter-particle repulsion caused by the additional charge anisotropy. Moreover, within the crystal state at higher volume fraction, the system further undergoes a disorder-to-order transition with respect to the charge orientation. The dependence of crystal formation and orientational ordering on charge asymmetry and temperature was also examined. These model studies are essential to advance our future understanding regarding the fundamental physiochemical properties of novel Janus colloidal particles and protein crystallization conditions.

Chen, Wei-Ren↗
DOE OSTI2015

The effect of voxel size on dose distribution in Varian Clinac iX 6 MV photon beam using Monte Carlo simulation

Recently, Monte Carlo (MC) calculation method has reported as the most accurate method of predicting dose distributions in radiotherapy. The MC code system (especially DOSXYZnrc) has been used to investigate the different voxel (volume elements) sizes effect on the accuracy of dose distributions. To investigate this effect on dosimetry parameters, calculations were made with three different voxel sizes. The effects were investigated with dose distribution calculations for seven voxel sizes: 1 × 1 × 0.1 cm{sup 3}, 1 × 1 × 0.5 cm{sup 3}, and 1 × 1 × 0.8 cm{sup 3}. The 1 × 10{sup 9} histories were simulated in order to get statistical uncertainties of 2%. This simulation takes about 9-10 hours to complete. Measurements are made with field sizes 10 × 10 cm2 for the 6 MV photon beams with Gaussian intensity distribution FWHM 0.1 cm and SSD 100.1 cm. MC simulated and measured dose distributions in a water phantom. The output of this simulation i.e. the percent depth dose and dose profile in d{sub max} from the three sets of calculations are presented and comparisons are made with the experiment data from TTSH (Tan Tock Seng Hospital, Singapore) in 0-5 cm depth. Dose that scored in voxels is a volume averaged estimate of the dose at the center of a voxel. The results in this study show that the difference between Monte Carlo simulation and experiment data depend on the voxel size both for percent depth dose (PDD) and profile dose. PDD scan on Z axis (depth) of water phantom, the big difference obtain in the voxel size 1 × 1 × 0.8 cm{sup 3} about 17%. In this study, the profile dose focused on high gradient dose area. Profile dose scan on Y axis and the big difference get in the voxel size 1 × 1 × 0.1 cm{sup 3} about 12%. This study demonstrated that the arrange voxel in Monte Carlo simulation becomes important.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2014

Structure of Cu{sub 64.5}Zr{sub 35.5} metallic glass by reverse Monte Carlo simulations

Reverse Monte Carlo simulations (RMC) have been widely used to generate three dimensional (3D) atomistic models for glass systems. To examine the reliability of the method for metallic glass, we use RMC to predict the atomic configurations of a “known” structure from molecular dynamics (MD) simulations, and then compare the structure obtained from the RMC with the target structure from MD. We show that when the structure factors and partial pair correlation functions from the MD simulations are used as inputs for RMC simulations, the 3D atomistic structure of the glass obtained from the RMC gives the short- and medium-range order in good agreement with those from the target structure by the MD simulation. These results suggest that 3D atomistic structure model of the metallic glass alloys can be reasonably well reproduced by RMC method with a proper choice of input constraints.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2013

Monte Carlo Simulations of the Corrosion of Aluminoborosilicate Glasses

Aluminum is one of the most common components included in nuclear waste glasses. Therefore, Monte Carlo (MC) simulations were carried out to investigate the influence of aluminum on the rate and mechanism of dissolution of sodium borosilicate glasses in static conditions. The glasses studied were in the compositional range (70-2x)% SiO2 x% Al2O3 15% B2O3 (15+x)% Na2O, where 0 ≤ x ≤ 15%. The simulation results show that increasing amounts of aluminum in the pristine glasses slow down the initial rate of dissolution as determined from the rate of boron release. However, the extent of corrosion - as measured by the total amount of boron release - initially increases with addition of Al2O3, up to 5 Al2O3 mol%, but subsequently decreases with further Al2O3 addition. The MC simulations reveal that this behavior is due to the interplay between two opposing mechanisms: (1) aluminum slows down the kinetics of hydrolysis/condensation reactions that drive the reorganization of the glass surface and eventual formation of a blocking layer; and (2) aluminum strengthens the glass thereby increasing the lifetime of the upper part of its surface and allowing for more rapid formation of a blocking layer. Additional MC simulations were performed whereby a process representing the formation of a secondary aluminosilicate phase was included. Secondary phase formation draws dissolved glass components out of the aqueous solution, thereby diminishing the rate of condensation and delaying the formation of a blocking layer. As a result, the extent of corrosion is found to increase continuously with increasing Al2O3 content, as observed experimentally. For Al2O3 < 10 mol%, the MC simulations also indicate that, because the secondary phase solubility eventually controls the aluminum content in the part of the altered layer in contact with the bulk aqueous solution, the dissolved aluminum and silicon concentrations at steady state are not dependent on the Al2O3 content of the pristine aluminoborosilicate glass.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2015

Estimation of beryllium ground state energy by Monte Carlo simulation

Quantum Monte Carlo method represent a powerful and broadly applicable computational tool for finding very accurate solution of the stationary Schrödinger equation for atoms, molecules, solids and a variety of model systems. Using variational Monte Carlo method we have calculated the ground state energy of the Beryllium atom. Our calculation are based on using a modified four parameters trial wave function which leads to good result comparing with the few parameters trial wave functions presented before. Based on random Numbers we can generate a large sample of electron locations to estimate the ground state energy of Beryllium. Our calculation gives good estimation for the ground state energy of the Beryllium atom comparing with the corresponding exact data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Monte Carlo Simulation of Electron Thermalization in Scintillator Materials: Implications for Scintillator Nonproportionality

The lack of reliable quantitative estimates of the length and time scales associated with hot electron thermalization after a gamma-ray induced energy cascade obscures the interplay of various microscopic processes controlling scintillator performance and hampers the search for improved detector materials. We apply a detailed microscopic kinetic Monte Carlo model of the creation and subsequent thermalization of hot electrons produced by gamma irradiation of six important scintillating crystals to determine the spatial extent of the cloud of excitations produced by gamma rays and the time required for the cloud to thermalize with the host lattice. The main ingredients of the model are ensembles of microscopic track structures produced upon gamma excitation (including the energy distribution of the excited carriers), numerical estimates of electron-phonon scattering rates, and a calculated particle dispersion to relate the speed and energy of excited carriers. All these ingredients are based on first-principles density functional theory calculations of the electronic and phonon band structures of the materials. Details of the Monte Carlo model are presented along with results for thermalization time and distance distributions. These results are discussed in light of previous work. It is found that among the studied materials, calculated thermalization distances are positively correlated with measured nonproportionality. In the important class of halide scintillators, the particle dispersion is found to be more influential than the largest phonon energy in determining the thermalization distance.

Phonons, radiation detection, scintillators, thema↗
DOE OSTI2015

Oxygen transport properties estimation by classical trajectory–direct simulation Monte Carlo

Coupling direct simulation Monte Carlo (DSMC) simulations with classical trajectory calculations is a powerful tool to improve predictive capabilities of computational dilute gas dynamics. The considerable increase in computational effort outlined in early applications of the method can be compensated by running simulations on massively parallel computers. In particular, Graphics Processing Unit acceleration has been found quite effective in reducing computing time of classical trajectory (CT)-DSMC simulations. The aim of the present work is to study dilute molecular oxygen flows by modeling binary collisions, in the rigid rotor approximation, through an accurate Potential Energy Surface (PES), obtained by molecular beams scattering. The PES accuracy is assessed by calculating molecular oxygen transport properties by different equilibrium and non-equilibrium CT-DSMC based simulations that provide close values of the transport properties. Comparisons with available experimental data are presented and discussed in the temperature range 300–900 K, where vibrational degrees of freedom are expected to play a limited (but not always negligible) role.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗