Monte carlo performance analysis computer program with programmed mixture ratio
Fortran program using Monte Carlo method to establish probability distribution for rocket stage residual and total payload
FORTRAN↗
SEARCH · Engineering Papers
Results for “Monte Carlo Methods”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Electron flow in low-density argon gas including space-charge and elastic collisions
Monte Carlo method for determining electron flow in low density argon gas including space charge and elastic collisions
MONTE CARLO METHOD↗
Tissue current-to-dose conversion factors for neutrons with energies from 0.5 to 60 MeV
Monte Carlo method for evaluation of high energy neutron exposure hazards
MONTE CARLO METHOD↗
A fast particle-based approach for calibrating a 3-D model of the Antarctic ice sheet
We consider the scientifically challenging and policy-relevant task of understanding the past and projecting the future dynamics of the Antarctic ice sheet. The Antarctic ice sheet has shown a highly nonlinear threshold response to past climate forcings. Triggering such a threshold response through anthropogenic greenhouse gas emissions would drive drastic and potentially fast sea level rise with important implications for coastal flood risks. Previous studies have combined information from ice sheet models and observations to calibrate model parameters. These studies have broken important new ground but have either adopted simple ice sheet models or have limited the number of parameters to allow for the use of more complex models. These limitations are largely due to the computational challenges posed by calibration as models become more computationally intensive or when the number of parameters increases. Here, we propose a method to alleviate this problem: a fast sequential Monte Carlo method that takes advantage of the massive parallelization afforded by modern high-performance computing systems. We use simulated examples to demonstrate how our sample-based approach provides accurate approximations to the posterior distributions of the calibrated parameters. The drastic reduction in computational times enables us to provide new insights into important scientific questions, for example, the impact of Pliocene era data and prior parameter information on sea level projections. These studies would be computationally prohibitive with other computational approaches for calibration such as Markov chain Monte Carlo or emulation-based methods. We also find considerable differences in the distributions of sea level projections when we account for a larger number of uncertain parameters. For example, based on the same ice sheet model and data set, the 99th percentile of the Antarctic ice sheet contribution to sea level rise in 2300 increases from 6.5 m to 13.1 m when we increase the number of calibrated parameters from three to 11. With previous calibration methods, it would be challenging to go beyond five parameters. Here, this work provides an important next step toward improving the uncertainty quantification of complex, computationally intensive and decision-relevant models.
54 ENVIRONMENTAL SCIENCES↗
An in vivo dose verification method for SBRT–VMAT delivery using the EPID
Purpose: Radiation treatments have become increasingly more complex with the development of volumetric modulated arc therapy (VMAT) and the use of stereotactic body radiation therapy (SBRT). SBRT involves the delivery of substantially larger doses over fewer fractions than conventional therapy. SBRT–VMAT treatments will strongly benefit from in vivo patient dose verification, as any errors in delivery can be more detrimental to the radiobiology of the patient as compared to conventional therapy. Electronic portal imaging devices (EPIDs) are available on most commercial linear accelerators (Linacs) and their documented use for dosimetry makes them valuable tools for patient dose verification. In this work, the authors customize and validate a physics-based model which utilizes on-treatment EPID images to reconstruct the 3D dose delivered to the patient during SBRT–VMAT delivery. Methods: The SBRT Linac head, including jaws, multileaf collimators, and flattening filter, were modeled using Monte Carlo methods and verified with measured data. The simulation provides energy spectrum data that are used by their “forward” model to then accurately predict fluence generated by a SBRT beam at a plane above the patient. This fluence is then transported through the patient and then the dose to the phosphor layer in the EPID is calculated. Their “inverse” model back-projects the EPID measured focal fluence to a plane upstream of the patient and recombines it with the extra-focal fluence predicted by the forward model. This estimate of total delivered fluence is then forward projected onto the patient’s density matrix and a collapsed cone convolution algorithm calculates the dose delivered to the patient. The model was tested by reconstructing the dose for two prostate, three lung, and two spine SBRT–VMAT treatment fractions delivered to an anthropomorphic phantom. It was further validated against actual patient data for a lung and spine SBRT–VMAT plan. The results were verified with the treatment planning system (TPS) (ECLIPSE AAA) dose calculation. Results: The SBRT–VMAT reconstruction model performed very well when compared to the TPS. A stringent 2%/2 mm χ-comparison calculation gave pass rates better than 91% for the prostate plans, 88% for the lung plans, and 86% for the spine plans for voxels containing 80% or more of the prescribed dose. Patient data were 86% for the lung and 95% for the spine. A 3%/3 mm χ-comparison was also performed and gave pass rates better than 93% for all plan types. Conclusions: The authors have customized and validated a robust, physics-based model that calculates the delivered dose to a patient for SBRT–VMAT delivery using on-treatment EPID images. The accuracy of the results indicates that this approach is suitable for clinical implementation. Future work will incorporate this model into both offline and real-time clinical adaptive radiotherapy.
60 APPLIED LIFE SCIENCES↗
CPMC-Lab: A Matlab package for Constrained Path Monte Carlo calculations
We describe CPMC-Lab, a Matlab program for the constrained-path and phaseless auxiliary-field Monte Carlo methods. These methods have allowed applications ranging from the study of strongly correlated models, such as the Hubbard model, to ab initio calculations in molecules and solids. The present package implements the full ground-state constrained-path Monte Carlo (CPMC) method in Matlab with a graphical interface, using the Hubbard model as an example. The package can perform calculations in finite supercells in any dimensions, under periodic or twist boundary conditions. Importance sampling and all other algorithmic details of a total energy calculation are included and illustrated. This open-source tool allows users to experiment with various model and run parameters and visualize the results. It provides a direct and interactive environment to learn the method and study the code with minimal overhead for setup. Furthermore, the package can be easily generalized for auxiliary-field quantum Monte Carlo (AFQMC) calculations in many other models for correlated electron systems, and can serve as a template for developing a production code for AFQMC total energy calculations in real materials. Several illustrative studies are carried out in one- and two-dimensional lattices on total energy, kinetic energy, potential energy, and charge- and spin-gaps.
Computer Science↗
Monte Carlo simulations of surface reactions: NO reduction by CO or H{sub 2}
The development of surface science has given an opportunity to investigate the process of heterogeneous catalysis at a molecular level. In this way there has been a great progress in understanding the mechanism in NO decomposition. Modeling has been an very important tool in this goal. In this work we analyze the reactions NO+H{sub 2} and NO+CO. The extremely narrow production peak of N{sub 2} and CO{sub 2} which occurs in the reaction of NO+CO on Pt(100), a phenomenon known as “surface explosion,” is studied using a dynamic Monte Carlo method on a square lattice at low pressure under isothermal conditions. The catalytic reduction of nitric oxide by hydrogen over a Pt surface is also studied by using a dynamic Monte Carlo. Using a Langmuir-Hinshelwod mechanism of reaction, a simplified model with only four adsorbed species (NO, H, O, and N) is constructed. The effect on NO dissociation rate, the limiting step in the whole reaction, is inhibited by coadsorbed NO and H{sub 2} molecules, and is enhanced both by the presence of empty sites and adsorbed N atoms as nearest-neighbors. In these simulations experimental parameters values are included, such as: adsorption, desorption and diffusion of the reactants. The phenomenon is studied changing the temperature in the range of 300–550 K. The modeling reproduces well observed TPD and TPR experimental results and allows a visualization of the spatial development of the surface explosion.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Critical Properties of the Anisotropic Ising Model with Competitive Interactions in the Region of a Phase Transition from the Modulated Phase to the Paramagnetic One
Monte Carlo methods are used to study the anisotropic Ising model with competing interactions in the region of the phase transition from the modulated to the paramagnetic phase. Using histogram analysis of Monte Carlo data and the theory of finite-size scaling, it is shown that the transition from the modulated state to the paramagnetic one is a second-order phase transition. The critical parameters and temperatures of phase transitions in this region are calculated. It is shown that the modulated–paramagnetic phase transition cannot be described within the framework of the known universality classes of critical behavior.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
MO-FG-BRA-01: 4D Monte Carlo Simulations for Verification of Dose Delivered to a Moving Anatomy
Purpose: To validate 4D Monte Carlo (MC) simulations of dose delivery by an Elekta Agility linear accelerator to a moving phantom. Methods: Monte Carlo simulations were performed using the 4DdefDOSXYZnrc/EGSnrc user code which samples a new geometry for each incident particle and calculates the dose in a continuously moving anatomy. A Quasar respiratory motion phantom with a lung insert containing a 3 cm diameter tumor was used for dose measurements on an Elekta Agility linac with the phantom in stationary and moving states. Dose to the center of tumor was measured using calibrated EBT3 film and the RADPOS 4D dosimetry system. A VMAT plan covering the tumor was created on the static CT scan of the phantom using Monaco V.5.10.02. A validated BEAMnrc model of our Elekta Agility linac was used for Monte Carlo simulations on stationary and moving anatomies. To compare the planned and delivered doses, linac log files recorded during measurements were used for the simulations. For 4D simulations, deformation vectors that modeled the rigid translation of the lung insert were generated as input to the 4DdefDOSXYZnrc code as well as the phantom motion trace recorded with RADPOS during the measurements. Results: Monte Carlo simulations and film measurements were found to agree within 2mm/2% for 97.7% of points in the film in the static phantom and 95.5% in the moving phantom. Dose values based on film and RADPOS measurements are within 2% of each other and within 2σ of experimental uncertainties with respect to simulations. Conclusion: Our 4D Monte Carlo simulation using the defDOSXYZnrc code accurately calculates dose delivered to a moving anatomy. Future work will focus on more investigation of VMAT delivery on a moving phantom to improve the agreement between simulation and measurements, as well as establishing the accuracy of our method in a deforming anatomy. This work was supported by the Ontario Consortium of Adaptive Interventions in Radiation Oncology (OCAIRO), funded by the Ontario Research Fund Research Excellence program.
60 APPLIED LIFE SCIENCES↗
Application of the GBFP Method to Electron Partial-Wave Expansion Elastic Scattering Differential Cross Sections Within the Geant4 Toolkit - Paper 69
Analog Monte Carlo simulation of electrons in complex material geometries is generally impractical because the long range Coulomb interactions result in highly peaked differential cross sections (DCS) for scattering and energy-loss and extremely small collision mean free paths (mfp). The condensed history (CH) Monte Carlo method attempts to alleviate this limitation by advancing electrons in fixed steps and sampling angular deflections and energy losses from precomputed distributions obtained from approximate solutions to the underlying transport equation that are valid only for thin layers. Though CH is efficient and is widely employed in production codes (ITS, MCNP, EGS, Geant), step size restrictions and inconsistent handling of material and free surface boundaries limit the ultimate accuracy possible with this approach, especially in applications to highly heterogeneous media. Recently proposed alternatives to the CH method, such as the Generalized Boltzmann Fokker-Planck (GBFP) method, restore the correct transport mechanics by simulating single events based on a Boltzmann transport equation but with efficiency and accuracy achieved through the use of reduced-physics interaction models. Motivated by Lewis theory, various moment-preserving strategies are employed in the GBFP approach to construct DCSs that are less singular, and with mfps shorter than analog. Specifically, the approximate cross sections are constructed to rigorously preserve a finite number of angular and energy-loss moments of the analog DCSs while all higher moments are approximated in terms of the exact lower moments. By systematically increasing the number of moments retained, any desired accuracy can be obtained for integrated quantities, such as dose, reflection and transmission yields, as well as distributed quantities such as energy and angular distributions. For relativistic Rutherford cross section models, the GBFP method has been demonstrated in Monte Carlo simulation to yield accuracy comparable to analog but at a fraction of the cost. One advantage of the GBFP approach is that angular deflection and energy-loss interactions depend only on Legendre moments and energy-loss moments and not the detailed form of the analog DCSs. This feature allows moment-preservation to be enforced through DCSs expressed as a superposition of discrete (i.e., using delta-functions) angular deflections and discrete energy losses. This promotes extremely efficient computation when compared to analog and completely continuous or hybrid discrete-continuous moment-based DCS reconstructions, while yielding highly accurate results for integrated and distributed quantities. In this paper, we demonstrate that the moment-preserving algorithms central to our fully discrete GBFP method can be readily extended to apply to tabulated DCS data, specifically to the partial-wave expansion (PWE) elastic scattering DCSs. Since data libraries for the PWE DCSs for energy and material combinations of interest can be prohibitively large, the GBFP method provides a means to reduce data storage requirements. We implemented our algorithm in the Geant4 Monte Carlo code and all numerical results are obtained using this implementation. (authors)
61 RADIATION PROTECTION AND DOSIMETRY↗
Manifestations of Radiation Scattering in the Method of Pulsed Terahertz Spectroscopy
The scattering of broadband terahertz pulses on a rough surface of a semi-infinite medium has been analyzed by a modified Monte Carlo method, which takes into account the radiation phase. The results have been compared with a simplified analytic expression that allows generalization in the case of layered media and the presence of volumetric scattering. These results allow a simple way to exclude or reduce the scattering influence on the recovery of the media characteristics in the method of pulse terahertz spectroscopy to be suggested.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Optimization of energy window for {sup 90}Y bremsstrahlung SPECT imaging for detection tasks using the ideal observer with model-mismatch
Purpose: In yttrium-90 ({sup 90}Y) microsphere brachytherapy (radioembolization) of unresectable liver cancer, posttherapy {sup 90}Y bremsstrahlung single photon emission computed tomography (SPECT) has been used to document the distribution of microspheres in the patient and to help predict potential side effects. The energy window used during projection acquisition can have a significant effect on image quality. Thus, using an optimal energy window is desirable. However, there has been great variability in the choice of energy window due to the continuous and broad energy distribution of {sup 90}Y bremsstrahlung photons. The area under the receiver operating characteristic curve (AUC) for the ideal observer (IO) is a widely used figure of merit (FOM) for optimizing the imaging system for detection tasks. The IO implicitly assumes a perfect model of the image formation process. However, for {sup 90}Y bremsstrahlung SPECT there can be substantial model-mismatch (i.e., difference between the actual image formation process and the model of it assumed in reconstruction), and the amount of the model-mismatch depends on the energy window. It is thus important to account for the degradation of the observer performance due to model-mismatch in the optimization of the energy window. The purpose of this paper is to optimize the energy window for {sup 90}Y bremsstrahlung SPECT for a detection task while taking into account the effects of the model-mismatch. Methods: An observer, termed the ideal observer with model-mismatch (IO-MM), has been proposed previously to account for the effects of the model-mismatch on IO performance. In this work, the AUC for the IO-MM was used as the FOM for the optimization. To provide a clinically realistic object model and imaging simulation, the authors used a background-known-statistically and signal-known-statistically task. The background was modeled as multiple compartments in the liver with activity parameters independently following a Gaussian distribution; the signal was modeled as a tumor with a Gaussian-distributed activity parameter located randomly with equal probability at one of three positions. The IO test statistics (i.e., likelihood ratios) were estimated using Markov-chain Monte Carlo methods. The authors realistically modeled human anatomy using a digital phantom code, and realistically simulated {sup 90}Y bremsstrahlung SPECT imaging with a clinical SPECT system and typical imaging parameters using a previously validated Monte Carlo bremsstrahlung simulation method. Model-mismatch was included by modeling image formation process in the calculation of IO test statistics using an analytic modeling method previously developed for quantitative {sup 90}Y bremsstrahlung SPECT. To demonstrate the effects of the model-mismatch on the detection task, the authors optimized the energy window both with and without model-mismatch included in the IO. Results: For all the energy windows, the AUC values for the IO-MM were smaller than that for the IO. The optimal windows for the IO-MM and the IO were 80-180 and 60-400 keV, respectively. Conclusions: The authors have demonstrated the degradation of the ideal performance due to model-mismatch and optimized the energy window for {sup 90}Y bremsstrahlung SPECT for detection tasks by accounting for the effects of the model-mismatch. The obtained optimal window was much narrower when taking into account the model-mismatch and similar to that obtained previously for estimation tasks.
61 RADIATION PROTECTION AND DOSIMETRY↗
Diffusion-controlled reactions modeling in Geant4-DNA
Context Under irradiation, a biological system undergoes a cascade of chemical reactions that can lead to an alteration of its normal operation. There are different types of radiation and many competing reactions. As a result the kinetics of chemical species is extremely complex. The simulation becomes then a powerful tool which, by describing the basic principles of chemical reactions, can reveal the dynamics of the macroscopic system. To understand the dynamics of biological systems under radiation, since the 80s there have been on-going efforts carried out by several research groups to establish a mechanistic model that consists in describing all the physical, chemical and biological phenomena following the irradiation of single cells. This approach is generally divided into a succession of stages that follow each other in time: (1) the physical stage, where the ionizing particles interact directly with the biological material; (2) the physico-chemical stage, where the targeted molecules release their energy by dissociating, creating new chemical species; (3) the chemical stage, where the new chemical species interact with each other or with the biomolecules; (4) the biological stage, where the repairing mechanisms of the cell come into play. This article focuses on the modeling of the chemical stage. Method This article presents a general method of speeding-up chemical reaction simulations in fluids based on the Smoluchowski equation and Monte-Carlo methods, where all molecules are explicitly simulated and the solvent is treated as a continuum. The model describes diffusion-controlled reactions. This method has been implemented in Geant4-DNA. The keys to the new algorithm include: (1) the combination of a method to compute time steps dynamically with a Brownian bridge process to account for chemical reactions, which avoids costly fixed time step simulations; (2) a k–d tree data structure for quickly locating, for a given molecule, its closest reactants. The performance advantage is presented in terms of complexity, and the accuracy of the new algorithm is demonstrated by simulating radiation chemistry in the context of the Geant4-DNA project. Application The time-dependent radiolytic yields of the main chemical species formed after irradiation are computed for incident protons at different energies (from 50 MeV to 500 keV). Both the time-evolution and energy dependency of the yields are discussed. The evolution, at one microsecond, of the yields of hydroxyls and solvated electrons with respect to the linear energy transfer is compared to theoretical and experimental data. According to our results, at high linear energy transfer, modeling radiation chemistry in the trading compartment representation might be adopted.
60 APPLIED LIFE SCIENCES↗
Comparison of the MCNP6 and FLUKA Codes in Shielding Calculation at ProNova Proton Therapy Facility
The Monte Carlo method is a powerful tool to simulate particle transport in materials, and can be effectively used to design radiation shielding. The purpose of this study is to compare the results from two Monte Carlo codes (MCNP6 and FLUKA ) in shielding design. The calculation was also compared with the measured results from the ProNova Superconducting 360 degrees (SC360) installation at the Knoxville Provision Center for Proton Therapy (PCPT) facility. The SC360 230 MeV continue wave (CW) proton beam is produced by an isochronous cyclotron, the Sumitomo P235. The maximum beam that is extracted into the beamline is 300 nA, which is of 60% of the full current generated in cyclotron. The SC360 facility has an energy selection system for adjusting the proton range, one fixed beam and one gantry room for rotating the beam around the stationary patient. At the entrance to each treatment room beamline, a thickness adjustable Beryllium degrader inserted in the beam path is used to achieve the desirable beam energy. When protons interact with beamline components, the secondary neutrons become the dominant source to determine the radiation shielding. In this study, the dose rate outside the lateral wall of the beamline vault was discussed. The calculations from two Monte Carlo codes were compared and they agreed very well. The dose rates measured by a Wendi-II Neutron Detector agreed within a factor of less than seven compared with the calculation results. The difference may be explained by a variety of factors such as the uncertainty in knowing the exact composition of shielding materials, geometry difference, and the measurement uncertainty due to instrumentation. (authors)
61 RADIATION PROTECTION AND DOSIMETRY↗
Diffusion of low energy auroral electrons in the atmosphere
Monte Carlo method used on energy dissipation of electrons in air and applied to diffusion of low energy auroral electrons in atmosphere
MONTE CARLO METHOD↗
Application of random sampling to the computation of spectrometer characteristics for gamma-radiation and fast neutrons
Monte Carlo method of analyzing gamma radiation and fast neutron spectrometer characteristics
SPECTROMETER↗
Sensitivity Coefficients for Diffusion Coefficients and Other Reactor Physics Parameters using CE TSUNAMI-3D
The TSUNAMI (Tools for Sensitivity and Uncertainty Analysis Methodology Implementation) capabilities within the SCALE code system leverage sensitivity coefficients for many criticality safety applications, including quantifying the data-induced uncertainty in the eigenvalue of critical systems, quantifying computational biases, and selecting applicable benchmark experiments. TSUNAMI sensitivity and uncertainty analysis tools have traditionally been limited to criticality safety application spaces, but the introduction of Generalized Perturbation Theory (GPT) sensitivity methods by Jessee in 2009 and Perfetti in 2013 has extended the scope of SCALE adjoint-weighted sensitivity and uncertainty analysis to include reactor physics applications. The continuous-energy (CE) TSUNAMI-3D GPT sensitivity analysis methods were originally developed to calculate sensitivity coefficients for a limited number of reaction-rate responses using CE Monte Carlo methods. These tools were recently applied in an Oak Ridge National Laboratory (ORNL)-directed research and development project to improve the efficiency of {sup 252}Cf production in the High Flux Isotope Reactor (HFIR) by understanding the sensitivity of key heavy actinide capture-to- fission ratios to potential system design changes. This work further extends the applicability of the CE TSUNAMI- 3D GPT methods to reactor physics applications by enabling the calculation of sensitivity coefficients for an expanded set of reaction rate responses-including a first-ever capability for conducting sensitivity analysis of neutron diffusion coefficients.
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
Precision and Accuracy in PDV and VISAR
This is a technical report discussing our current level of understanding of a wide and varying distribution of uncertainties in velocity results from Photonic Doppler Velocimetry in its application to gas gun experiments. Using propagation of errors methods with statistical averaging of photon number fluctuation in the detected photocurrent and subsequent addition of electronic recording noise, we learn that the velocity uncertainty in VISAR can be written in closed form. For PDV, the non-linear frequency transform and peak fitting methods employed make propagation of errors estimates notoriously more difficult to write down in closed form expect in the limit of constant velocity and low time resolution (large analysis-window width). An alternative method of error propagation in PDV is to use Monte Carlo methods with a simulation of the time domain signal based on results from the spectral domain. A key problem for Monte Carlo estimation for an experiment is a correct estimate of that portion of the time-domain noise associated with the peak-fitting region-of-interesting in the spectral domain. Using short-time Fourier transformation spectral analysis and working with the phase dependent real and imaginary parts allows removal of amplitude-noise cross terms that invariably show up when working with correlation-based methods or FFT power spectra. Estimation of the noise associated with a given spectral region of interest is then possible. At this level of progress, we learn that Monte Carlo trials with random recording noise and initial (uncontrolled) phase yields velocity uncertainties that are not as large as those observed. In a search for additional noise sources, a speckleinterference modulation contribution with off axis rays was investigated, and was found to add a velocity variation beyond that from the recording noise (due to random interference between off axis rays), but in our experiments the speckle modulation precision was not as important as the recording noise precision. But from these investigations we do appreciate that the velocity-uncertainty itself has a wide distribution of values that varies with signal-amplitude modulation (is not a single value). To provide a rough rule of thumb for the velocity uncertainty, we computed the average of the relative standard deviation distributions from 60 recorded traces (with distributions of uncertainties roughly between 0.1 % to 1 % in each trace) and found a mean of the distribution of uncertainties for our experiments is not better than 0.4 % at an analysis window width of 5 ns (although for brief intervals it can be as good as 0.1 %). Further imagination and testing may be needed to reveal other possible hydrodynamics-related sources of velocity error in PDV.
47 OTHER INSTRUMENTATION↗