Implementation of the direct S ( α , β ) method in the KENO Monte Carlo code

DOE PAGES

Hart, Shane W. D.; Maldonado, G. Ivan

2016-11-25

The Monte Carlo code KENO contains thermal scattering data for a wide variety of thermal moderators. These data are processed from Evaluated Nuclear Data Files (ENDF) by AMPX and stored as double differential probability distribution functions. The method examined in this study uses S(α,β) probability distribution functions derived from the ENDF data files directly instead of being converted to double differential cross sections. This allows the size of the cross section data on the disk to be reduced substantially amount. KENO has also been updated to allow interpolation in temperature on these data so that problems can be run atmore » any temperature. Results are shown for several simplified problems for a variety of moderators. In addition, benchmark models based on the KRITZ reactor in Sweden were run, and the results are compared with the previous versions of KENO without the direct S(α,β) method. Results from the direct S(α,β) method compare favorably with the original results obtained using the double differential cross sections. Finally, sampling the data increases the run-time of the Monte Carlo calculation, but memory usage is decreased substantially.« less

Direct calculation of liquid-vapor phase equilibria from transition matrix Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Errington, Jeffrey R.

2003-06-01

An approach for directly determining the liquid-vapor phase equilibrium of a model system at any temperature along the coexistence line is described. The method relies on transition matrix Monte Carlo ideas developed by Fitzgerald, Picard, and Silver [Europhys. Lett. 46, 282 (1999)]. During a Monte Carlo simulation attempted transitions between states along the Markov chain are monitored as opposed to tracking the number of times the chain visits a given state as is done in conventional simulations. Data collection is highly efficient and very precise results are obtained. The method is implemented in both the grand canonical and isothermal-isobaric ensemble. The main result from a simulation conducted at a given temperature is a density probability distribution for a range of densities that includes both liquid and vapor states. Vapor pressures and coexisting densities are calculated in a straightforward manner from the probability distribution. The approach is demonstrated with the Lennard-Jones fluid. Coexistence properties are directly calculated at temperatures spanning from the triple point to the critical point.

Methodology of full-core Monte Carlo calculations with leakage parameter evaluations for benchmark critical experiment analysis

NASA Astrophysics Data System (ADS)

Sboev, A. G.; Ilyashenko, A. S.; Vetrova, O. A.

1997-02-01

The method of bucking evaluation, realized in the MOnte Carlo code MCS, is described. This method was applied for calculational analysis of well known light water experiments TRX-1 and TRX-2. The analysis of this comparison shows, that there is no coincidence between Monte Carlo calculations, obtained by different ways: the MCS calculations with given experimental bucklings; the MCS calculations with given bucklings evaluated on base of full core MCS direct simulations; the full core MCNP and MCS direct simulations; the MCNP and MCS calculations, where the results of cell calculations are corrected by the coefficients taking into the account the leakage from the core. Also the buckling values evaluated by full core MCS calculations have differed from experimental ones, especially in the case of TRX-1, when this difference has corresponded to 0.5 percent increase of Keff value.

A Modified Monte Carlo Method for Carrier Transport in Germanium, Free of Isotropic Rates

NASA Astrophysics Data System (ADS)

Sundqvist, Kyle

2010-03-01

We present a new method for carrier transport simulation, relevant for high-purity germanium < 100 > at a temperature of 40 mK. In this system, the scattering of electrons and holes is dominated by spontaneous phonon emission. Free carriers are always out of equilibrium with the lattice. We must also properly account for directional effects due to band structure, but there are many cautions in the literature about treating germanium in particular. These objections arise because the germanium electron system is anisotropic to an extreme degree, while standard Monte Carlo algorithms maintain a reliance on isotropic, integrated rates. We re-examine Fermi's Golden Rule to produce a Monte Carlo method free of isotropic rates. Traditional Monte Carlo codes implement particle scattering based on an isotropically averaged rate, followed by a separate selection of the particle's final state via a momentum-dependent probability. In our method, the kernel of Fermi's Golden Rule produces analytical, bivariate rates which allow for the simultaneous choice of scatter and final state selection. Energy and momentum are automatically conserved. We compare our results to experimental data.

Parameters Free Computational Characterization of Defects in Transition Metal Oxides with Diffusion Quantum Monte Carlo

NASA Astrophysics Data System (ADS)

Santana, Juan A.; Krogel, Jaron T.; Kent, Paul R.; Reboredo, Fernando

Materials based on transition metal oxides (TMO's) are among the most challenging systems for computational characterization. Reliable and practical computations are possible by directly solving the many-body problem for TMO's with quantum Monte Carlo (QMC) methods. These methods are very computationally intensive, but recent developments in algorithms and computational infrastructures have enabled their application to real materials. We will show our efforts on the application of the diffusion quantum Monte Carlo (DMC) method to study the formation of defects in binary and ternary TMO and heterostructures of TMO. We will also outline current limitations in hardware and algorithms. This work is supported by the Materials Sciences & Engineering Division of the Office of Basic Energy Sciences, U.S. Department of Energy (DOE).

Exact Dynamics via Poisson Process: a unifying Monte Carlo paradigm

NASA Astrophysics Data System (ADS)

Gubernatis, James

2014-03-01

A common computational task is solving a set of ordinary differential equations (o.d.e.'s). A little known theorem says that the solution of any set of o.d.e.'s is exactly solved by the expectation value over a set of arbitary Poisson processes of a particular function of the elements of the matrix that defines the o.d.e.'s. The theorem thus provides a new starting point to develop real and imaginary-time continous-time solvers for quantum Monte Carlo algorithms, and several simple observations enable various quantum Monte Carlo techniques and variance reduction methods to transfer to a new context. I will state the theorem, note a transformation to a very simple computational scheme, and illustrate the use of some techniques from the directed-loop algorithm in context of the wavefunction Monte Carlo method that is used to solve the Lindblad master equation for the dynamics of open quantum systems. I will end by noting that as the theorem does not depend on the source of the o.d.e.'s coming from quantum mechanics, it also enables the transfer of continuous-time methods from quantum Monte Carlo to the simulation of various classical equations of motion heretofore only solved deterministically.

Light-transmittance predictions under multiple-light-scattering conditions. I. Direct problem: hybrid-method approximation.

PubMed

Czerwiński, M; Mroczka, J; Girasole, T; Gouesbet, G; Gréhan, G

2001-03-20

Our aim is to present a method of predicting light transmittances through dense three-dimensional layered media. A hybrid method is introduced as a combination of the four-flux method with coefficients predicted from a Monte Carlo statistical model to take into account the actual three-dimensional geometry of the problem under study. We present the principles of the hybrid method, some exemplifying results of numerical simulations, and their comparison with results obtained from Bouguer-Lambert-Beer law and from Monte Carlo simulations.

Stochastic, real-space, imaginary-time evaluation of third-order Feynman-Goldstone diagrams

NASA Astrophysics Data System (ADS)

Willow, Soohaeng Yoo; Hirata, So

2014-01-01

A new, alternative set of interpretation rules of Feynman-Goldstone diagrams for many-body perturbation theory is proposed, which translates diagrams into algebraic expressions suitable for direct Monte Carlo integrations. A vertex of a diagram is associated with a Coulomb interaction (rather than a two-electron integral) and an edge with the trace of a Green's function in real space and imaginary time. With these, 12 diagrams of third-order many-body perturbation (MP3) theory are converted into 20-dimensional integrals, which are then evaluated by a Monte Carlo method. It uses redundant walkers for convergence acceleration and a weight function for importance sampling in conjunction with the Metropolis algorithm. The resulting Monte Carlo MP3 method has low-rank polynomial size dependence of the operation cost, a negligible memory cost, and a naturally parallel computational kernel, while reproducing the correct correlation energies of small molecules within a few mEh after 106 Monte Carlo steps.

High-order Path Integral Monte Carlo methods for solving strongly correlated fermion problems

NASA Astrophysics Data System (ADS)

Chin, Siu A.

2015-03-01

In solving for the ground state of a strongly correlated many-fermion system, the conventional second-order Path Integral Monte Carlo method is plagued with the sign problem. This is due to the large number of anti-symmetric free fermion propagators that are needed to extract the square of the ground state wave function at large imaginary time. In this work, I show that optimized fourth-order Path Integral Monte Carlo methods, which uses no more than 5 free-fermion propagators, in conjunction with the use of the Hamiltonian energy estimator, can yield accurate ground state energies for quantum dots with up to 20 polarized electrons. The correlations are directly built-in and no explicit wave functions are needed. This work is supported by the Qatar National Research Fund NPRP GRANT #5-674-1-114.

Large-cell Monte Carlo renormalization of irreversible growth processes

NASA Technical Reports Server (NTRS)

Nakanishi, H.; Family, F.

1985-01-01

Monte Carlo sampling is applied to a recently formulated direct-cell renormalization method for irreversible, disorderly growth processes. Large-cell Monte Carlo renormalization is carried out for various nonequilibrium problems based on the formulation dealing with relative probabilities. Specifically, the method is demonstrated by application to the 'true' self-avoiding walk and the Eden model of growing animals for d = 2, 3, and 4 and to the invasion percolation problem for d = 2 and 3. The results are asymptotically in agreement with expectations; however, unexpected complications arise, suggesting the possibility of crossovers, and in any case, demonstrating the danger of using small cells alone, because of the very slow convergence as the cell size b is extrapolated to infinity. The difficulty of applying the present method to the diffusion-limited-aggregation model, is commented on.

Molecular dynamics simulation of a piston driven shock wave in a hard sphere gas. Final Contractor ReportPh.D. Thesis

NASA Technical Reports Server (NTRS)

Woo, Myeung-Jouh; Greber, Isaac

1995-01-01

Molecular dynamics simulation is used to study the piston driven shock wave at Mach 1.5, 3, and 10. A shock tube, whose shape is a circular cylinder, is filled with hard sphere molecules having a Maxwellian thermal velocity distribution and zero mean velocity. The piston moves and a shock wave is generated. All collisions are specular, including those between the molecules and the computational boundaries, so that the shock development is entirely causal, with no imposed statistics. The structure of the generated shock is examined in detail, and the wave speed; profiles of density, velocity, and temperature; and shock thickness are determined. The results are compared with published results of other methods, especially the direct simulation Monte-Carlo method. Property profiles are similar to those generated by direct simulation Monte-Carlo method. The shock wave thicknesses are smaller than the direct simulation Monte-Carlo results, but larger than those of the other methods. Simulation of a shock wave, which is one-dimensional, is a severe test of the molecular dynamics method, which is always three-dimensional. A major challenge of the thesis is to examine the capability of the molecular dynamics methods by choosing a difficult task.

Fast Monte Carlo-assisted simulation of cloudy Earth backgrounds

NASA Astrophysics Data System (ADS)

Adler-Golden, Steven; Richtsmeier, Steven C.; Berk, Alexander; Duff, James W.

2012-11-01

A calculation method has been developed for rapidly synthesizing radiometrically accurate ultraviolet through longwavelengthinfrared spectral imagery of the Earth for arbitrary locations and cloud fields. The method combines cloudfree surface reflectance imagery with cloud radiance images calculated from a first-principles 3-D radiation transport model. The MCScene Monte Carlo code [1-4] is used to build a cloud image library; a data fusion method is incorporated to speed convergence. The surface and cloud images are combined with an upper atmospheric description with the aid of solar and thermal radiation transport equations that account for atmospheric inhomogeneity. The method enables a wide variety of sensor and sun locations, cloud fields, and surfaces to be combined on-the-fly, and provides hyperspectral wavelength resolution with minimal computational effort. The simulations agree very well with much more time-consuming direct Monte Carlo calculations of the same scene.

Monte Carlo-based Reconstruction in Water Cherenkov Detectors using Chroma

NASA Astrophysics Data System (ADS)

Seibert, Stanley; Latorre, Anthony

2012-03-01

We demonstrate the feasibility of event reconstruction---including position, direction, energy and particle identification---in water Cherenkov detectors with a purely Monte Carlo-based method. Using a fast optical Monte Carlo package we have written, called Chroma, in combination with several variance reduction techniques, we can estimate the value of a likelihood function for an arbitrary event hypothesis. The likelihood can then be maximized over the parameter space of interest using a form of gradient descent designed for stochastic functions. Although slower than more traditional reconstruction algorithms, this completely Monte Carlo-based technique is universal and can be applied to a detector of any size or shape, which is a major advantage during the design phase of an experiment. As a specific example, we focus on reconstruction results from a simulation of the 200 kiloton water Cherenkov far detector option for LBNE.

Monte Carlo derivation of filtered tungsten anode X-ray spectra for dose computation in digital mammography*

PubMed Central

Paixão, Lucas; Oliveira, Bruno Beraldo; Viloria, Carolina; de Oliveira, Marcio Alves; Teixeira, Maria Helena Araújo; Nogueira, Maria do Socorro

2015-01-01

Objective Derive filtered tungsten X-ray spectra used in digital mammography systems by means of Monte Carlo simulations. Materials and Methods Filtered spectra for rhodium filter were obtained for tube potentials between 26 and 32 kV. The half-value layer (HVL) of simulated filtered spectra were compared with those obtained experimentally with a solid state detector Unfors model 8202031-H Xi R/F & MAM Detector Platinum and 8201023-C Xi Base unit Platinum Plus w mAs in a Hologic Selenia Dimensions system using a direct radiography mode. Results Calculated HVL values showed good agreement as compared with those obtained experimentally. The greatest relative difference between the Monte Carlo calculated HVL values and experimental HVL values was 4%. Conclusion The results show that the filtered tungsten anode X-ray spectra and the EGSnrc Monte Carlo code can be used for mean glandular dose determination in mammography. PMID:26811553

Monte Carlo sampling in diffusive dynamical systems

NASA Astrophysics Data System (ADS)

Tapias, Diego; Sanders, David P.; Altmann, Eduardo G.

2018-05-01

We introduce a Monte Carlo algorithm to efficiently compute transport properties of chaotic dynamical systems. Our method exploits the importance sampling technique that favors trajectories in the tail of the distribution of displacements, where deviations from a diffusive process are most prominent. We search for initial conditions using a proposal that correlates states in the Markov chain constructed via a Metropolis-Hastings algorithm. We show that our method outperforms the direct sampling method and also Metropolis-Hastings methods with alternative proposals. We test our general method through numerical simulations in 1D (box-map) and 2D (Lorentz gas) systems.

Self-evolving atomistic kinetic Monte Carlo simulations of defects in materials

DOE PAGES

Xu, Haixuan; Beland, Laurent K.; Stoller, Roger E.; ...

2015-01-29

The recent development of on-the-fly atomistic kinetic Monte Carlo methods has led to an increased amount attention on the methods and their corresponding capabilities and applications. In this review, the framework and current status of Self-Evolving Atomistic Kinetic Monte Carlo (SEAKMC) are discussed. SEAKMC particularly focuses on defect interaction and evolution with atomistic details without assuming potential defect migration/interaction mechanisms and energies. The strength and limitation of using an active volume, the key concept introduced in SEAKMC, are discussed. Potential criteria for characterizing an active volume are discussed and the influence of active volume size on saddle point energies ismore » illustrated. A procedure starting with a small active volume followed by larger active volumes was found to possess higher efficiency. Applications of SEAKMC, ranging from point defect diffusion, to complex interstitial cluster evolution, to helium interaction with tungsten surfaces, are summarized. A comparison of SEAKMC with molecular dynamics and conventional object kinetic Monte Carlo is demonstrated. Overall, SEAKMC is found to be complimentary to conventional molecular dynamics, especially when the harmonic approximation of transition state theory is accurate. However it is capable of reaching longer time scales than molecular dynamics and it can be used to systematically increase the accuracy of other methods such as object kinetic Monte Carlo. Furthermore, the challenges and potential development directions are also outlined.« less

Direct simulation Monte Carlo method for the Uehling-Uhlenbeck-Boltzmann equation.

PubMed

Garcia, Alejandro L; Wagner, Wolfgang

2003-11-01

In this paper we describe a direct simulation Monte Carlo algorithm for the Uehling-Uhlenbeck-Boltzmann equation in terms of Markov processes. This provides a unifying framework for both the classical Boltzmann case as well as the Fermi-Dirac and Bose-Einstein cases. We establish the foundation of the algorithm by demonstrating its link to the kinetic equation. By numerical experiments we study its sensitivity to the number of simulation particles and to the discretization of the velocity space, when approximating the steady-state distribution.

Monte Carlo Transport for Electron Thermal Transport

NASA Astrophysics Data System (ADS)

Chenhall, Jeffrey; Cao, Duc; Moses, Gregory

2015-11-01

The iSNB (implicit Schurtz Nicolai Busquet multigroup electron thermal transport method of Cao et al. is adapted into a Monte Carlo transport method in order to better model the effects of non-local behavior. The end goal is a hybrid transport-diffusion method that combines Monte Carlo Transport with a discrete diffusion Monte Carlo (DDMC). The hybrid method will combine the efficiency of a diffusion method in short mean free path regions with the accuracy of a transport method in long mean free path regions. The Monte Carlo nature of the approach allows the algorithm to be massively parallelized. Work to date on the method will be presented. This work was supported by Sandia National Laboratory - Albuquerque and the University of Rochester Laboratory for Laser Energetics.

[Benchmark experiment to verify radiation transport calculations for dosimetry in radiation therapy].

PubMed

Renner, Franziska

2016-09-01

Monte Carlo simulations are regarded as the most accurate method of solving complex problems in the field of dosimetry and radiation transport. In (external) radiation therapy they are increasingly used for the calculation of dose distributions during treatment planning. In comparison to other algorithms for the calculation of dose distributions, Monte Carlo methods have the capability of improving the accuracy of dose calculations - especially under complex circumstances (e.g. consideration of inhomogeneities). However, there is a lack of knowledge of how accurate the results of Monte Carlo calculations are on an absolute basis. A practical verification of the calculations can be performed by direct comparison with the results of a benchmark experiment. This work presents such a benchmark experiment and compares its results (with detailed consideration of measurement uncertainty) with the results of Monte Carlo calculations using the well-established Monte Carlo code EGSnrc. The experiment was designed to have parallels to external beam radiation therapy with respect to the type and energy of the radiation, the materials used and the kind of dose measurement. Because the properties of the beam have to be well known in order to compare the results of the experiment and the simulation on an absolute basis, the benchmark experiment was performed using the research electron accelerator of the Physikalisch-Technische Bundesanstalt (PTB), whose beam was accurately characterized in advance. The benchmark experiment and the corresponding Monte Carlo simulations were carried out for two different types of ionization chambers and the results were compared. Considering the uncertainty, which is about 0.7 % for the experimental values and about 1.0 % for the Monte Carlo simulation, the results of the simulation and the experiment coincide. Copyright © 2015. Published by Elsevier GmbH.

Vectorized Monte Carlo methods for reactor lattice analysis

NASA Technical Reports Server (NTRS)

Brown, F. B.

1984-01-01

Some of the new computational methods and equivalent mathematical representations of physics models used in the MCV code, a vectorized continuous-enery Monte Carlo code for use on the CYBER-205 computer are discussed. While the principal application of MCV is the neutronics analysis of repeating reactor lattices, the new methods used in MCV should be generally useful for vectorizing Monte Carlo for other applications. For background, a brief overview of the vector processing features of the CYBER-205 is included, followed by a discussion of the fundamentals of Monte Carlo vectorization. The physics models used in the MCV vectorized Monte Carlo code are then summarized. The new methods used in scattering analysis are presented along with details of several key, highly specialized computational routines. Finally, speedups relative to CDC-7600 scalar Monte Carlo are discussed.

Recent advances and future prospects for Monte Carlo

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brown, Forrest B

2010-01-01

The history of Monte Carlo methods is closely linked to that of computers: The first known Monte Carlo program was written in 1947 for the ENIAC; a pre-release of the first Fortran compiler was used for Monte Carlo In 1957; Monte Carlo codes were adapted to vector computers in the 1980s, clusters and parallel computers in the 1990s, and teraflop systems in the 2000s. Recent advances include hierarchical parallelism, combining threaded calculations on multicore processors with message-passing among different nodes. With the advances In computmg, Monte Carlo codes have evolved with new capabilities and new ways of use. Production codesmore » such as MCNP, MVP, MONK, TRIPOLI and SCALE are now 20-30 years old (or more) and are very rich in advanced featUres. The former 'method of last resort' has now become the first choice for many applications. Calculations are now routinely performed on office computers, not just on supercomputers. Current research and development efforts are investigating the use of Monte Carlo methods on FPGAs. GPUs, and many-core processors. Other far-reaching research is exploring ways to adapt Monte Carlo methods to future exaflop systems that may have 1M or more concurrent computational processes.« less

Quasi-Monte Carlo Methods Applied to Tau-Leaping in Stochastic Biological Systems.

PubMed

Beentjes, Casper H L; Baker, Ruth E

2018-05-25

Quasi-Monte Carlo methods have proven to be effective extensions of traditional Monte Carlo methods in, amongst others, problems of quadrature and the sample path simulation of stochastic differential equations. By replacing the random number input stream in a simulation procedure by a low-discrepancy number input stream, variance reductions of several orders have been observed in financial applications. Analysis of stochastic effects in well-mixed chemical reaction networks often relies on sample path simulation using Monte Carlo methods, even though these methods suffer from typical slow [Formula: see text] convergence rates as a function of the number of sample paths N. This paper investigates the combination of (randomised) quasi-Monte Carlo methods with an efficient sample path simulation procedure, namely [Formula: see text]-leaping. We show that this combination is often more effective than traditional Monte Carlo simulation in terms of the decay of statistical errors. The observed convergence rate behaviour is, however, non-trivial due to the discrete nature of the models of chemical reactions. We explain how this affects the performance of quasi-Monte Carlo methods by looking at a test problem in standard quadrature.

A method for radiological characterization based on fluence conversion coefficients

NASA Astrophysics Data System (ADS)

Froeschl, Robert

2018-06-01

Radiological characterization of components in accelerator environments is often required to ensure adequate radiation protection during maintenance, transport and handling as well as for the selection of the proper disposal pathway. The relevant quantities are typical the weighted sums of specific activities with radionuclide-specific weighting coefficients. Traditional methods based on Monte Carlo simulations are radionuclide creation-event based or the particle fluences in the regions of interest are scored and then off-line weighted with radionuclide production cross sections. The presented method bases the radiological characterization on a set of fluence conversion coefficients. For a given irradiation profile and cool-down time, radionuclide production cross-sections, material composition and radionuclide-specific weighting coefficients, a set of particle type and energy dependent fluence conversion coefficients is computed. These fluence conversion coefficients can then be used in a Monte Carlo transport code to perform on-line weighting to directly obtain the desired radiological characterization, either by using built-in multiplier features such as in the PHITS code or by writing a dedicated user routine such as for the FLUKA code. The presented method has been validated against the standard event-based methods directly available in Monte Carlo transport codes.

Visual improvement for bad handwriting based on Monte-Carlo method

NASA Astrophysics Data System (ADS)

Shi, Cao; Xiao, Jianguo; Xu, Canhui; Jia, Wenhua

2014-03-01

A visual improvement algorithm based on Monte Carlo simulation is proposed in this paper, in order to enhance visual effects for bad handwriting. The whole improvement process is to use well designed typeface so as to optimize bad handwriting image. In this process, a series of linear operators for image transformation are defined for transforming typeface image to approach handwriting image. And specific parameters of linear operators are estimated by Monte Carlo method. Visual improvement experiments illustrate that the proposed algorithm can effectively enhance visual effect for handwriting image as well as maintain the original handwriting features, such as tilt, stroke order and drawing direction etc. The proposed visual improvement algorithm, in this paper, has a huge potential to be applied in tablet computer and Mobile Internet, in order to improve user experience on handwriting.

Advanced Computational Methods for Monte Carlo Calculations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brown, Forrest B.

This course is intended for graduate students who already have a basic understanding of Monte Carlo methods. It focuses on advanced topics that may be needed for thesis research, for developing new state-of-the-art methods, or for working with modern production Monte Carlo codes.

Theoretical Analysis of Penalized Maximum-Likelihood Patlak Parametric Image Reconstruction in Dynamic PET for Lesion Detection.

PubMed

Yang, Li; Wang, Guobao; Qi, Jinyi

2016-04-01

Detecting cancerous lesions is a major clinical application of emission tomography. In a previous work, we studied penalized maximum-likelihood (PML) image reconstruction for lesion detection in static PET. Here we extend our theoretical analysis of static PET reconstruction to dynamic PET. We study both the conventional indirect reconstruction and direct reconstruction for Patlak parametric image estimation. In indirect reconstruction, Patlak parametric images are generated by first reconstructing a sequence of dynamic PET images, and then performing Patlak analysis on the time activity curves (TACs) pixel-by-pixel. In direct reconstruction, Patlak parametric images are estimated directly from raw sinogram data by incorporating the Patlak model into the image reconstruction procedure. PML reconstruction is used in both the indirect and direct reconstruction methods. We use a channelized Hotelling observer (CHO) to assess lesion detectability in Patlak parametric images. Simplified expressions for evaluating the lesion detectability have been derived and applied to the selection of the regularization parameter value to maximize detection performance. The proposed method is validated using computer-based Monte Carlo simulations. Good agreements between the theoretical predictions and the Monte Carlo results are observed. Both theoretical predictions and Monte Carlo simulation results show the benefit of the indirect and direct methods under optimized regularization parameters in dynamic PET reconstruction for lesion detection, when compared with the conventional static PET reconstruction.

Discrete Diffusion Monte Carlo for Electron Thermal Transport

NASA Astrophysics Data System (ADS)

Chenhall, Jeffrey; Cao, Duc; Wollaeger, Ryan; Moses, Gregory

2014-10-01

The iSNB (implicit Schurtz Nicolai Busquet electron thermal transport method of Cao et al. is adapted to a Discrete Diffusion Monte Carlo (DDMC) solution method for eventual inclusion in a hybrid IMC-DDMC (Implicit Monte Carlo) method. The hybrid method will combine the efficiency of a diffusion method in short mean free path regions with the accuracy of a transport method in long mean free path regions. The Monte Carlo nature of the approach allows the algorithm to be massively parallelized. Work to date on the iSNB-DDMC method will be presented. This work was supported by Sandia National Laboratory - Albuquerque.

Direct simulation Monte Carlo method for gas flows in micro-channels with bends with added curvature

NASA Astrophysics Data System (ADS)

Tisovský, Tomáš; Vít, Tomáš

Gas flows in micro-channels are simulated using an open source Direct Simulation Monte Carlo (DSMC) code dsmcFOAM for general application to rarefied gas flow written within the framework of the open source C++ toolbox called OpenFOAM. Aim of this paper is to investigate the flow in micro-channel with bend with added curvature. Results are compared with flows in channel without added curvature and equivalent straight channel. Effects of micro-channel bend was already thoroughly investigated by White et al. Geometry proposed by White is also used here for refference.

CPMC-Lab: A MATLAB package for Constrained Path Monte Carlo calculations

NASA Astrophysics Data System (ADS)

Nguyen, Huy; Shi, Hao; Xu, Jie; Zhang, Shiwei

2014-12-01

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.

Monte Carlo Simulation for Perusal and Practice.

ERIC Educational Resources Information Center

Brooks, Gordon P.; Barcikowski, Robert S.; Robey, Randall R.

The meaningful investigation of many problems in statistics can be solved through Monte Carlo methods. Monte Carlo studies can help solve problems that are mathematically intractable through the analysis of random samples from populations whose characteristics are known to the researcher. Using Monte Carlo simulation, the values of a statistic are…

The Monte Carlo Method. Popular Lectures in Mathematics.

ERIC Educational Resources Information Center

Sobol', I. M.

The Monte Carlo Method is a method of approximately solving mathematical and physical problems by the simulation of random quantities. The principal goal of this booklet is to suggest to specialists in all areas that they will encounter problems which can be solved by the Monte Carlo Method. Part I of the booklet discusses the simulation of random…

The Direct Lighting Computation in Global Illumination Methods

NASA Astrophysics Data System (ADS)

Wang, Changyaw Allen

1994-01-01

Creating realistic images is a computationally expensive process, but it is very important for applications such as interior design, product design, education, virtual reality, and movie special effects. To generate realistic images, state-of-art rendering techniques are employed to simulate global illumination, which accounts for the interreflection of light among objects. In this document, we formalize the global illumination problem into a eight -dimensional integral and discuss various methods that can accelerate the process of approximating this integral. We focus on the direct lighting computation, which accounts for the light reaching the viewer from the emitting sources after exactly one reflection, Monte Carlo sampling methods, and light source simplification. Results include a new sample generation method, a framework for the prediction of the total number of samples used in a solution, and a generalized Monte Carlo approach for computing the direct lighting from an environment which for the first time makes ray tracing feasible for highly complex environments.

Path-integral Monte Carlo method for Rényi entanglement entropies.

PubMed

Herdman, C M; Inglis, Stephen; Roy, P-N; Melko, R G; Del Maestro, A

2014-07-01

We introduce a quantum Monte Carlo algorithm to measure the Rényi entanglement entropies in systems of interacting bosons in the continuum. This approach is based on a path-integral ground state method that can be applied to interacting itinerant bosons in any spatial dimension with direct relevance to experimental systems of quantum fluids. We demonstrate how it may be used to compute spatial mode entanglement, particle partitioned entanglement, and the entanglement of particles, providing insights into quantum correlations generated by fluctuations, indistinguishability, and interactions. We present proof-of-principle calculations and benchmark against an exactly soluble model of interacting bosons in one spatial dimension. As this algorithm retains the fundamental polynomial scaling of quantum Monte Carlo when applied to sign-problem-free models, future applications should allow for the study of entanglement entropy in large-scale many-body systems of interacting bosons.

Investigation of electronic and magnetic properties of FeS: First principle and Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Bouachraoui, Rachid; El Hachimi, Abdel Ghafour; Ziat, Younes; Bahmad, Lahoucine; Tahiri, Najim

2018-06-01

Electronic and magnetic properties of hexagonal Iron (II) Sulfide (hexagonal FeS) have been investigated by combining the Density functional theory (DFT) and Monte Carlo simulations (MCS). This compound is constituted by magnetic hexagonal lattice occupied by Fe2+ with spin state (S = 2). Based on ab initio method, we calculated the exchange coupling JFe-Fe between two magnetic atoms Fe-Fe in different directions. Also phase transitions, magnetic stability and magnetizations have been investigated in the framework of Monte Carlo simulations. Within this method, a second phase transition is observed at the Néel temperature TN = 450 K. This finding in good agreement with the reported data in the literature. The effect of the applied different parameters showed how can these parameters affect the critical temperature of this system. Moreover, we studied the density of states and found that the hexagonal FeS will be a promoting material for spintronic applications.

Application of the three-component bidirectional reflectance distribution function model to Monte Carlo calculation of spectral effective emissivities of nonisothermal blackbody cavities.

PubMed

Prokhorov, Alexander; Prokhorova, Nina I

2012-11-20

We applied the bidirectional reflectance distribution function (BRDF) model consisting of diffuse, quasi-specular, and glossy components to the Monte Carlo modeling of spectral effective emissivities for nonisothermal cavities. A method for extension of a monochromatic three-component (3C) BRDF model to a continuous spectral range is proposed. The initial data for this method are the BRDFs measured in the plane of incidence at a single wavelength and several incidence angles and directional-hemispherical reflectance measured at one incidence angle within a finite spectral range. We proposed the Monte Carlo algorithm for calculation of spectral effective emissivities for nonisothermal cavities whose internal surface is described by the wavelength-dependent 3C BRDF model. The results obtained for a cylindroconical nonisothermal cavity are discussed and compared with results obtained using the conventional specular-diffuse model.

Study of multi-dimensional radiative energy transfer in molecular gases

NASA Technical Reports Server (NTRS)

Liu, Jiwen; Tiwari, S. N.

1993-01-01

The Monte Carlo method (MCM) is applied to analyze radiative heat transfer in nongray gases. The nongray model employed is based on the statistical arrow band model with an exponential-tailed inverse intensity distribution. Consideration of spectral correlation results in some distinguishing features of the Monte Carlo formulations. Validation of the Monte Carlo formulations has been conducted by comparing results of this method with other solutions. Extension of a one-dimensional problem to a multi-dimensional problem requires some special treatments in the Monte Carlo analysis. Use of different assumptions results in different sets of Monte Carlo formulations. The nongray narrow band formulations provide the most accurate results.

Quantum Gibbs ensemble Monte Carlo

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fantoni, Riccardo, E-mail: rfantoni@ts.infn.it; Moroni, Saverio, E-mail: moroni@democritos.it

We present a path integral Monte Carlo method which is the full quantum analogue of the Gibbs ensemble Monte Carlo method of Panagiotopoulos to study the gas-liquid coexistence line of a classical fluid. Unlike previous extensions of Gibbs ensemble Monte Carlo to include quantum effects, our scheme is viable even for systems with strong quantum delocalization in the degenerate regime of temperature. This is demonstrated by an illustrative application to the gas-superfluid transition of {sup 4}He in two dimensions.

Statistical Analysis of a Class: Monte Carlo and Multiple Imputation Spreadsheet Methods for Estimation and Extrapolation

ERIC Educational Resources Information Center

Fish, Laurel J.; Halcoussis, Dennis; Phillips, G. Michael

2017-01-01

The Monte Carlo method and related multiple imputation methods are traditionally used in math, physics and science to estimate and analyze data and are now becoming standard tools in analyzing business and financial problems. However, few sources explain the application of the Monte Carlo method for individuals and business professionals who are…

Bayesian statistics and Monte Carlo methods

NASA Astrophysics Data System (ADS)

Koch, K. R.

2018-03-01

The Bayesian approach allows an intuitive way to derive the methods of statistics. Probability is defined as a measure of the plausibility of statements or propositions. Three rules are sufficient to obtain the laws of probability. If the statements refer to the numerical values of variables, the so-called random variables, univariate and multivariate distributions follow. They lead to the point estimation by which unknown quantities, i.e. unknown parameters, are computed from measurements. The unknown parameters are random variables, they are fixed quantities in traditional statistics which is not founded on Bayes' theorem. Bayesian statistics therefore recommends itself for Monte Carlo methods, which generate random variates from given distributions. Monte Carlo methods, of course, can also be applied in traditional statistics. The unknown parameters, are introduced as functions of the measurements, and the Monte Carlo methods give the covariance matrix and the expectation of these functions. A confidence region is derived where the unknown parameters are situated with a given probability. Following a method of traditional statistics, hypotheses are tested by determining whether a value for an unknown parameter lies inside or outside the confidence region. The error propagation of a random vector by the Monte Carlo methods is presented as an application. If the random vector results from a nonlinearly transformed vector, its covariance matrix and its expectation follow from the Monte Carlo estimate. This saves a considerable amount of derivatives to be computed, and errors of the linearization are avoided. The Monte Carlo method is therefore efficient. If the functions of the measurements are given by a sum of two or more random vectors with different multivariate distributions, the resulting distribution is generally not known. TheMonte Carlo methods are then needed to obtain the covariance matrix and the expectation of the sum.

A New Approach to Monte Carlo Simulations in Statistical Physics

NASA Astrophysics Data System (ADS)

Landau, David P.

2002-08-01

Monte Carlo simulations [1] have become a powerful tool for the study of diverse problems in statistical/condensed matter physics. Standard methods sample the probability distribution for the states of the system, most often in the canonical ensemble, and over the past several decades enormous improvements have been made in performance. Nonetheless, difficulties arise near phase transitions-due to critical slowing down near 2nd order transitions and to metastability near 1st order transitions, and these complications limit the applicability of the method. We shall describe a new Monte Carlo approach [2] that uses a random walk in energy space to determine the density of states directly. Once the density of states is known, all thermodynamic properties can be calculated. This approach can be extended to multi-dimensional parameter spaces and should be effective for systems with complex energy landscapes, e.g., spin glasses, protein folding models, etc. Generalizations should produce a broadly applicable optimization tool. 1. A Guide to Monte Carlo Simulations in Statistical Physics, D. P. Landau and K. Binder (Cambridge U. Press, Cambridge, 2000). 2. Fugao Wang and D. P. Landau, Phys. Rev. Lett. 86, 2050 (2001); Phys. Rev. E64, 056101-1 (2001).

Analysis of vibrational-translational energy transfer using the direct simulation Monte Carlo method

NASA Technical Reports Server (NTRS)

Boyd, Iain D.

1991-01-01

A new model is proposed for energy transfer between the vibrational and translational modes for use in the direct simulation Monte Carlo method (DSMC). The model modifies the Landau-Teller theory for a harmonic oscillator and the rate transition is related to an experimental correlation for the vibrational relaxation time. Assessment of the model is made with respect to three different computations: relaxation in a heat bath, a one-dimensional shock wave, and hypersonic flow over a two-dimensional wedge. These studies verify that the model achieves detailed balance, and excellent agreement with experimental data is obtained in the shock wave calculation. The wedge flow computation reveals that the usual phenomenological method for simulating vibrational nonequilibrium in the DSMC technique predicts much higher vibrational temperatures in the wake region.

CONTINUOUS-ENERGY MONTE CARLO METHODS FOR CALCULATING GENERALIZED RESPONSE SENSITIVITIES USING TSUNAMI-3D

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perfetti, Christopher M; Rearden, Bradley T

2014-01-01

This work introduces a new approach for calculating sensitivity coefficients for generalized neutronic responses to nuclear data uncertainties using continuous-energy Monte Carlo methods. The approach presented in this paper, known as the GEAR-MC method, allows for the calculation of generalized sensitivity coefficients for multiple responses in a single Monte Carlo calculation with no nuclear data perturbations or knowledge of nuclear covariance data. The theory behind the GEAR-MC method is presented here, and proof of principle is demonstrated by using the GEAR-MC method to calculate sensitivity coefficients for responses in several 3D, continuous-energy Monte Carlo applications.

Reconstruction of Human Monte Carlo Geometry from Segmented Images

NASA Astrophysics Data System (ADS)

Zhao, Kai; Cheng, Mengyun; Fan, Yanchang; Wang, Wen; Long, Pengcheng; Wu, Yican

2014-06-01

Human computational phantoms have been used extensively for scientific experimental analysis and experimental simulation. This article presented a method for human geometry reconstruction from a series of segmented images of a Chinese visible human dataset. The phantom geometry could actually describe detailed structure of an organ and could be converted into the input file of the Monte Carlo codes for dose calculation. A whole-body computational phantom of Chinese adult female has been established by FDS Team which is named Rad-HUMAN with about 28.8 billion voxel number. For being processed conveniently, different organs on images were segmented with different RGB colors and the voxels were assigned with positions of the dataset. For refinement, the positions were first sampled. Secondly, the large sums of voxels inside the organ were three-dimensional adjacent, however, there were not thoroughly mergence methods to reduce the cell amounts for the description of the organ. In this study, the voxels on the organ surface were taken into consideration of the mergence which could produce fewer cells for the organs. At the same time, an indexed based sorting algorithm was put forward for enhancing the mergence speed. Finally, the Rad-HUMAN which included a total of 46 organs and tissues was described by the cuboids into the Monte Carlo Monte Carlo Geometry for the simulation. The Monte Carlo geometry was constructed directly from the segmented images and the voxels was merged exhaustively. Each organ geometry model was constructed without ambiguity and self-crossing, its geometry information could represent the accuracy appearance and precise interior structure of the organs. The constructed geometry largely retaining the original shape of organs could easily be described into different Monte Carlo codes input file such as MCNP. Its universal property was testified and high-performance was experimentally verified

Accelerated Monte Carlo Simulation for Safety Analysis of the Advanced Airspace Concept

NASA Technical Reports Server (NTRS)

Thipphavong, David

2010-01-01

Safe separation of aircraft is a primary objective of any air traffic control system. An accelerated Monte Carlo approach was developed to assess the level of safety provided by a proposed next-generation air traffic control system. It combines features of fault tree and standard Monte Carlo methods. It runs more than one order of magnitude faster than the standard Monte Carlo method while providing risk estimates that only differ by about 10%. It also preserves component-level model fidelity that is difficult to maintain using the standard fault tree method. This balance of speed and fidelity allows sensitivity analysis to be completed in days instead of weeks or months with the standard Monte Carlo method. Results indicate that risk estimates are sensitive to transponder, pilot visual avoidance, and conflict detection failure probabilities.

Monte Carlo Calculations of Polarized Microwave Radiation Emerging from Cloud Structures

NASA Technical Reports Server (NTRS)

Kummerow, Christian; Roberti, Laura

1998-01-01

The last decade has seen tremendous growth in cloud dynamical and microphysical models that are able to simulate storms and storm systems with very high spatial resolution, typically of the order of a few kilometers. The fairly realistic distributions of cloud and hydrometeor properties that these models generate has in turn led to a renewed interest in the three-dimensional microwave radiative transfer modeling needed to understand the effect of cloud and rainfall inhomogeneities upon microwave observations. Monte Carlo methods, and particularly backwards Monte Carlo methods have shown themselves to be very desirable due to the quick convergence of the solutions. Unfortunately, backwards Monte Carlo methods are not well suited to treat polarized radiation. This study reviews the existing Monte Carlo methods and presents a new polarized Monte Carlo radiative transfer code. The code is based on a forward scheme but uses aliasing techniques to keep the computational requirements equivalent to the backwards solution. Radiative transfer computations have been performed using a microphysical-dynamical cloud model and the results are presented together with the algorithm description.

COMPARISON OF MONTE CARLO METHODS FOR NONLINEAR RADIATION TRANSPORT

DOE Office of Scientific and Technical Information (OSTI.GOV)

W. R. MARTIN; F. B. BROWN

2001-03-01

Five Monte Carlo methods for solving the nonlinear thermal radiation transport equations are compared. The methods include the well-known Implicit Monte Carlo method (IMC) developed by Fleck and Cummings, an alternative to IMC developed by Carter and Forest, an ''exact'' method recently developed by Ahrens and Larsen, and two methods recently proposed by Martin and Brown. The five Monte Carlo methods are developed and applied to the radiation transport equation in a medium assuming local thermodynamic equilibrium. Conservation of energy is derived and used to define appropriate material energy update equations for each of the methods. Details of the Montemore » Carlo implementation are presented, both for the random walk simulation and the material energy update. Simulation results for all five methods are obtained for two infinite medium test problems and a 1-D test problem, all of which have analytical solutions. Conclusions regarding the relative merits of the various schemes are presented.« less

Random Numbers and Monte Carlo Methods

NASA Astrophysics Data System (ADS)

Scherer, Philipp O. J.

Many-body problems often involve the calculation of integrals of very high dimension which cannot be treated by standard methods. For the calculation of thermodynamic averages Monte Carlo methods are very useful which sample the integration volume at randomly chosen points. After summarizing some basic statistics, we discuss algorithms for the generation of pseudo-random numbers with given probability distribution which are essential for all Monte Carlo methods. We show how the efficiency of Monte Carlo integration can be improved by sampling preferentially the important configurations. Finally the famous Metropolis algorithm is applied to classical many-particle systems. Computer experiments visualize the central limit theorem and apply the Metropolis method to the traveling salesman problem.

Comparison of Three Methods of Calculation, Experimental and Monte Carlo Simulation in Investigation of Organ Doses (Thyroid, Sternum, Cervical Vertebra) in Radioiodine Therapy

PubMed Central

Shahbazi-Gahrouei, Daryoush; Ayat, Saba

2012-01-01

Radioiodine therapy is an effective method for treating thyroid cancer carcinoma, but it has some affects on normal tissues, hence dosimetry of vital organs is important to weigh the risks and benefits of this method. The aim of this study is to measure the absorbed doses of important organs by Monte Carlo N Particle (MCNP) simulation and comparing the results of different methods of dosimetry by performing a t-paired test. To calculate the absorbed dose of thyroid, sternum, and cervical vertebra using the MCNP code, *F8 tally was used. Organs were simulated by using a neck phantom and Medical Internal Radiation Dosimetry (MIRD) method. Finally, the results of MCNP, MIRD, and Thermoluminescent dosimeter (TLD) measurements were compared by SPSS software. The absorbed dose obtained by Monte Carlo simulations for 100, 150, and 175 mCi administered 131I was found to be 388.0, 427.9, and 444.8 cGy for thyroid, 208.7, 230.1, and 239.3 cGy for sternum and 272.1, 299.9, and 312.1 cGy for cervical vertebra. The results of paired t-test were 0.24 for comparing TLD dosimetry and MIRD calculation, 0.80 for MCNP simulation and MIRD, and 0.19 for TLD and MCNP. The results showed no significant differences among three methods of Monte Carlo simulations, MIRD calculation and direct experimental dosimetry using TLD. PMID:23717806

Monte Carlo calculations of k{sub Q}, the beam quality conversion factor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Muir, B. R.; Rogers, D. W. O.

2010-11-15

Purpose: To use EGSnrc Monte Carlo simulations to directly calculate beam quality conversion factors, k{sub Q}, for 32 cylindrical ionization chambers over a range of beam qualities and to quantify the effect of systematic uncertainties on Monte Carlo calculations of k{sub Q}. These factors are required to use the TG-51 or TRS-398 clinical dosimetry protocols for calibrating external radiotherapy beams. Methods: Ionization chambers are modeled either from blueprints or manufacturers' user's manuals. The dose-to-air in the chamber is calculated using the EGSnrc user-code egs{sub c}hamber using 11 different tabulated clinical photon spectra for the incident beams. The dose to amore » small volume of water is also calculated in the absence of the chamber at the midpoint of the chamber on its central axis. Using a simple equation, k{sub Q} is calculated from these quantities under the assumption that W/e is constant with energy and compared to TG-51 protocol and measured values. Results: Polynomial fits to the Monte Carlo calculated k{sub Q} factors as a function of beam quality expressed as %dd(10){sub x} and TPR{sub 10}{sup 20} are given for each ionization chamber. Differences are explained between Monte Carlo calculated values and values from the TG-51 protocol or calculated using the computer program used for TG-51 calculations. Systematic uncertainties in calculated k{sub Q} values are analyzed and amount to a maximum of one standard deviation uncertainty of 0.99% if one assumes that photon cross-section uncertainties are uncorrelated and 0.63% if they are assumed correlated. The largest components of the uncertainty are the constancy of W/e and the uncertainty in the cross-section for photons in water. Conclusions: It is now possible to calculate k{sub Q} directly using Monte Carlo simulations. Monte Carlo calculations for most ionization chambers give results which are comparable to TG-51 values. Discrepancies can be explained using individual Monte Carlo calculations of various correction factors which are more accurate than previously used values. For small ionization chambers with central electrodes composed of high-Z materials, the effect of the central electrode is much larger than that for the aluminum electrodes in Farmer chambers.« less

Markov Chain Monte Carlo Methods for Bayesian Data Analysis in Astronomy

NASA Astrophysics Data System (ADS)

Sharma, Sanjib

2017-08-01

Markov Chain Monte Carlo based Bayesian data analysis has now become the method of choice for analyzing and interpreting data in almost all disciplines of science. In astronomy, over the last decade, we have also seen a steady increase in the number of papers that employ Monte Carlo based Bayesian analysis. New, efficient Monte Carlo based methods are continuously being developed and explored. In this review, we first explain the basics of Bayesian theory and discuss how to set up data analysis problems within this framework. Next, we provide an overview of various Monte Carlo based methods for performing Bayesian data analysis. Finally, we discuss advanced ideas that enable us to tackle complex problems and thus hold great promise for the future. We also distribute downloadable computer software (available at https://github.com/sanjibs/bmcmc/ ) that implements some of the algorithms and examples discussed here.

Fission matrix-based Monte Carlo criticality analysis of fuel storage pools

DOE Office of Scientific and Technical Information (OSTI.GOV)

Farlotti, M.; Ecole Polytechnique, Palaiseau, F 91128; Larsen, E. W.

2013-07-01

Standard Monte Carlo transport procedures experience difficulties in solving criticality problems in fuel storage pools. Because of the strong neutron absorption between fuel assemblies, source convergence can be very slow, leading to incorrect estimates of the eigenvalue and the eigenfunction. This study examines an alternative fission matrix-based Monte Carlo transport method that takes advantage of the geometry of a storage pool to overcome this difficulty. The method uses Monte Carlo transport to build (essentially) a fission matrix, which is then used to calculate the criticality and the critical flux. This method was tested using a test code on a simplemore » problem containing 8 assemblies in a square pool. The standard Monte Carlo method gave the expected eigenfunction in 5 cases out of 10, while the fission matrix method gave the expected eigenfunction in all 10 cases. In addition, the fission matrix method provides an estimate of the error in the eigenvalue and the eigenfunction, and it allows the user to control this error by running an adequate number of cycles. Because of these advantages, the fission matrix method yields a higher confidence in the results than standard Monte Carlo. We also discuss potential improvements of the method, including the potential for variance reduction techniques. (authors)« less

Response Matrix Monte Carlo for electron transport

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ballinger, C.T.; Nielsen, D.E. Jr.; Rathkopf, J.A.

1990-11-01

A Response Matrix Monte Carol (RMMC) method has been developed for solving electron transport problems. This method was born of the need to have a reliable, computationally efficient transport method for low energy electrons (below a few hundred keV) in all materials. Today, condensed history methods are used which reduce the computation time by modeling the combined effect of many collisions but fail at low energy because of the assumptions required to characterize the electron scattering. Analog Monte Carlo simulations are prohibitively expensive since electrons undergo coulombic scattering with little state change after a collision. The RMMC method attempts tomore » combine the accuracy of an analog Monte Carlo simulation with the speed of the condensed history methods. The combined effect of many collisions is modeled, like condensed history, except it is precalculated via an analog Monte Carol simulation. This avoids the scattering kernel assumptions associated with condensed history methods. Results show good agreement between the RMMC method and analog Monte Carlo. 11 refs., 7 figs., 1 tabs.« less

TH-E-18A-01: Developments in Monte Carlo Methods for Medical Imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Badal, A; Zbijewski, W; Bolch, W

Monte Carlo simulation methods are widely used in medical physics research and are starting to be implemented in clinical applications such as radiation therapy planning systems. Monte Carlo simulations offer the capability to accurately estimate quantities of interest that are challenging to measure experimentally while taking into account the realistic anatomy of an individual patient. Traditionally, practical application of Monte Carlo simulation codes in diagnostic imaging was limited by the need for large computational resources or long execution times. However, recent advancements in high-performance computing hardware, combined with a new generation of Monte Carlo simulation algorithms and novel postprocessing methods,more » are allowing for the computation of relevant imaging parameters of interest such as patient organ doses and scatter-to-primaryratios in radiographic projections in just a few seconds using affordable computational resources. Programmable Graphics Processing Units (GPUs), for example, provide a convenient, affordable platform for parallelized Monte Carlo executions that yield simulation times on the order of 10{sup 7} xray/ s. Even with GPU acceleration, however, Monte Carlo simulation times can be prohibitive for routine clinical practice. To reduce simulation times further, variance reduction techniques can be used to alter the probabilistic models underlying the x-ray tracking process, resulting in lower variance in the results without biasing the estimates. Other complementary strategies for further reductions in computation time are denoising of the Monte Carlo estimates and estimating (scoring) the quantity of interest at a sparse set of sampling locations (e.g. at a small number of detector pixels in a scatter simulation) followed by interpolation. Beyond reduction of the computational resources required for performing Monte Carlo simulations in medical imaging, the use of accurate representations of patient anatomy is crucial to the virtual generation of medical images and accurate estimation of radiation dose and other imaging parameters. For this, detailed computational phantoms of the patient anatomy must be utilized and implemented within the radiation transport code. Computational phantoms presently come in one of three format types, and in one of four morphometric categories. Format types include stylized (mathematical equation-based), voxel (segmented CT/MR images), and hybrid (NURBS and polygon mesh surfaces). Morphometric categories include reference (small library of phantoms by age at 50th height/weight percentile), patient-dependent (larger library of phantoms at various combinations of height/weight percentiles), patient-sculpted (phantoms altered to match the patient's unique outer body contour), and finally, patient-specific (an exact representation of the patient with respect to both body contour and internal anatomy). The existence and availability of these phantoms represents a very important advance for the simulation of realistic medical imaging applications using Monte Carlo methods. New Monte Carlo simulation codes need to be thoroughly validated before they can be used to perform novel research. Ideally, the validation process would involve comparison of results with those of an experimental measurement, but accurate replication of experimental conditions can be very challenging. It is very common to validate new Monte Carlo simulations by replicating previously published simulation results of similar experiments. This process, however, is commonly problematic due to the lack of sufficient information in the published reports of previous work so as to be able to replicate the simulation in detail. To aid in this process, the AAPM Task Group 195 prepared a report in which six different imaging research experiments commonly performed using Monte Carlo simulations are described and their results provided. The simulation conditions of all six cases are provided in full detail, with all necessary data on material composition, source, geometry, scoring and other parameters provided. The results of these simulations when performed with the four most common publicly available Monte Carlo packages are also provided in tabular form. The Task Group 195 Report will be useful for researchers needing to validate their Monte Carlo work, and for trainees needing to learn Monte Carlo simulation methods. In this symposium we will review the recent advancements in highperformance computing hardware enabling the reduction in computational resources needed for Monte Carlo simulations in medical imaging. We will review variance reduction techniques commonly applied in Monte Carlo simulations of medical imaging systems and present implementation strategies for efficient combination of these techniques with GPU acceleration. Trade-offs involved in Monte Carlo acceleration by means of denoising and “sparse sampling” will be discussed. A method for rapid scatter correction in cone-beam CT (<5 min/scan) will be presented as an illustration of the simulation speeds achievable with optimized Monte Carlo simulations. We will also discuss the development, availability, and capability of the various combinations of computational phantoms for Monte Carlo simulation of medical imaging systems. Finally, we will review some examples of experimental validation of Monte Carlo simulations and will present the AAPM Task Group 195 Report. Learning Objectives: Describe the advances in hardware available for performing Monte Carlo simulations in high performance computing environments. Explain variance reduction, denoising and sparse sampling techniques available for reduction of computational time needed for Monte Carlo simulations of medical imaging. List and compare the computational anthropomorphic phantoms currently available for more accurate assessment of medical imaging parameters in Monte Carlo simulations. Describe experimental methods used for validation of Monte Carlo simulations in medical imaging. Describe the AAPM Task Group 195 Report and its use for validation and teaching of Monte Carlo simulations in medical imaging.« less

Hybrid Monte Carlo/deterministic methods for radiation shielding problems

NASA Astrophysics Data System (ADS)

Becker, Troy L.

For the past few decades, the most common type of deep-penetration (shielding) problem simulated using Monte Carlo methods has been the source-detector problem, in which a response is calculated at a single location in space. Traditionally, the nonanalog Monte Carlo methods used to solve these problems have required significant user input to generate and sufficiently optimize the biasing parameters necessary to obtain a statistically reliable solution. It has been demonstrated that this laborious task can be replaced by automated processes that rely on a deterministic adjoint solution to set the biasing parameters---the so-called hybrid methods. The increase in computational power over recent years has also led to interest in obtaining the solution in a region of space much larger than a point detector. In this thesis, we propose two methods for solving problems ranging from source-detector problems to more global calculations---weight windows and the Transform approach. These techniques employ sonic of the same biasing elements that have been used previously; however, the fundamental difference is that here the biasing techniques are used as elements of a comprehensive tool set to distribute Monte Carlo particles in a user-specified way. The weight window achieves the user-specified Monte Carlo particle distribution by imposing a particular weight window on the system, without altering the particle physics. The Transform approach introduces a transform into the neutron transport equation, which results in a complete modification of the particle physics to produce the user-specified Monte Carlo distribution. These methods are tested in a three-dimensional multigroup Monte Carlo code. For a basic shielding problem and a more realistic one, these methods adequately solved source-detector problems and more global calculations. Furthermore, they confirmed that theoretical Monte Carlo particle distributions correspond to the simulated ones, implying that these methods can be used to achieve user-specified Monte Carlo distributions. Overall, the Transform approach performed more efficiently than the weight window methods, but it performed much more efficiently for source-detector problems than for global problems.

Discrete range clustering using Monte Carlo methods

NASA Technical Reports Server (NTRS)

Chatterji, G. B.; Sridhar, B.

1993-01-01

For automatic obstacle avoidance guidance during rotorcraft low altitude flight, a reliable model of the nearby environment is needed. Such a model may be constructed by applying surface fitting techniques to the dense range map obtained by active sensing using radars. However, for covertness, passive sensing techniques using electro-optic sensors are desirable. As opposed to the dense range map obtained via active sensing, passive sensing algorithms produce reliable range at sparse locations, and therefore, surface fitting techniques to fill the gaps in the range measurement are not directly applicable. Both for automatic guidance and as a display for aiding the pilot, these discrete ranges need to be grouped into sets which correspond to objects in the nearby environment. The focus of this paper is on using Monte Carlo methods for clustering range points into meaningful groups. One of the aims of the paper is to explore whether simulated annealing methods offer significant advantage over the basic Monte Carlo method for this class of problems. We compare three different approaches and present application results of these algorithms to a laboratory image sequence and a helicopter flight sequence.

Nuclear reactor transient analysis via a quasi-static kinetics Monte Carlo method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jo, YuGwon; Cho, Bumhee; Cho, Nam Zin, E-mail: nzcho@kaist.ac.kr

2015-12-31

The predictor-corrector quasi-static (PCQS) method is applied to the Monte Carlo (MC) calculation for reactor transient analysis. To solve the transient fixed-source problem of the PCQS method, fission source iteration is used and a linear approximation of fission source distributions during a macro-time step is introduced to provide delayed neutron source. The conventional particle-tracking procedure is modified to solve the transient fixed-source problem via MC calculation. The PCQS method with MC calculation is compared with the direct time-dependent method of characteristics (MOC) on a TWIGL two-group problem for verification of the computer code. Then, the results on a continuous-energy problemmore » are presented.« less

Monte Carlo simulation for kinetic chemotaxis model: An application to the traveling population wave

NASA Astrophysics Data System (ADS)

Yasuda, Shugo

2017-02-01

A Monte Carlo simulation of chemotactic bacteria is developed on the basis of the kinetic model and is applied to a one-dimensional traveling population wave in a microchannel. In this simulation, the Monte Carlo method, which calculates the run-and-tumble motions of bacteria, is coupled with a finite volume method to calculate the macroscopic transport of the chemical cues in the environment. The simulation method can successfully reproduce the traveling population wave of bacteria that was observed experimentally and reveal the microscopic dynamics of bacterium coupled with the macroscopic transports of the chemical cues and bacteria population density. The results obtained by the Monte Carlo method are also compared with the asymptotic solution derived from the kinetic chemotaxis equation in the continuum limit, where the Knudsen number, which is defined by the ratio of the mean free path of bacterium to the characteristic length of the system, vanishes. The validity of the Monte Carlo method in the asymptotic behaviors for small Knudsen numbers is numerically verified.

Physical Principle for Generation of Randomness

NASA Technical Reports Server (NTRS)

Zak, Michail

2009-01-01

A physical principle (more precisely, a principle that incorporates mathematical models used in physics) has been conceived as the basis of a method of generating randomness in Monte Carlo simulations. The principle eliminates the need for conventional random-number generators. The Monte Carlo simulation method is among the most powerful computational methods for solving high-dimensional problems in physics, chemistry, economics, and information processing. The Monte Carlo simulation method is especially effective for solving problems in which computational complexity increases exponentially with dimensionality. The main advantage of the Monte Carlo simulation method over other methods is that the demand on computational resources becomes independent of dimensionality. As augmented by the present principle, the Monte Carlo simulation method becomes an even more powerful computational method that is especially useful for solving problems associated with dynamics of fluids, planning, scheduling, and combinatorial optimization. The present principle is based on coupling of dynamical equations with the corresponding Liouville equation. The randomness is generated by non-Lipschitz instability of dynamics triggered and controlled by feedback from the Liouville equation. (In non-Lipschitz dynamics, the derivatives of solutions of the dynamical equations are not required to be bounded.)

Numerical integration of detector response functions via Monte Carlo simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kelly, Keegan John; O'Donnell, John M.; Gomez, Jaime A.

Calculations of detector response functions are complicated because they include the intricacies of signal creation from the detector itself as well as a complex interplay between the detector, the particle-emitting target, and the entire experimental environment. As such, these functions are typically only accessible through time-consuming Monte Carlo simulations. Furthermore, the output of thousands of Monte Carlo simulations can be necessary in order to extract a physics result from a single experiment. Here we describe a method to obtain a full description of the detector response function using Monte Carlo simulations. We also show that a response function calculated inmore » this way can be used to create Monte Carlo simulation output spectra a factor of ~1000× faster than running a new Monte Carlo simulation. A detailed discussion of the proper treatment of uncertainties when using this and other similar methods is provided as well. Here, this method is demonstrated and tested using simulated data from the Chi-Nu experiment, which measures prompt fission neutron spectra at the Los Alamos Neutron Science Center.« less

NOTE: Monte Carlo evaluation of kerma in an HDR brachytherapy bunker

NASA Astrophysics Data System (ADS)

Pérez-Calatayud, J.; Granero, D.; Ballester, F.; Casal, E.; Crispin, V.; Puchades, V.; León, A.; Verdú, G.

2004-12-01

In recent years, the use of high dose rate (HDR) after-loader machines has greatly increased due to the shift from traditional Cs-137/Ir-192 low dose rate (LDR) to HDR brachytherapy. The method used to calculate the required concrete and, where appropriate, lead shielding in the door is based on analytical methods provided by documents published by the ICRP, the IAEA and the NCRP. The purpose of this study is to perform a more realistic kerma evaluation at the entrance maze door of an HDR bunker using the Monte Carlo code GEANT4. The Monte Carlo results were validated experimentally. The spectrum at the maze entrance door, obtained with Monte Carlo, has an average energy of about 110 keV, maintaining a similar value along the length of the maze. The comparison of results from the aforementioned values with the Monte Carlo ones shows that results obtained using the albedo coefficient from the ICRP document more closely match those given by the Monte Carlo method, although the maximum value given by MC calculations is 30% greater.

Numerical integration of detector response functions via Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Kelly, K. J.; O'Donnell, J. M.; Gomez, J. A.; Taddeucci, T. N.; Devlin, M.; Haight, R. C.; White, M. C.; Mosby, S. M.; Neudecker, D.; Buckner, M. Q.; Wu, C. Y.; Lee, H. Y.

2017-09-01

Calculations of detector response functions are complicated because they include the intricacies of signal creation from the detector itself as well as a complex interplay between the detector, the particle-emitting target, and the entire experimental environment. As such, these functions are typically only accessible through time-consuming Monte Carlo simulations. Furthermore, the output of thousands of Monte Carlo simulations can be necessary in order to extract a physics result from a single experiment. Here we describe a method to obtain a full description of the detector response function using Monte Carlo simulations. We also show that a response function calculated in this way can be used to create Monte Carlo simulation output spectra a factor of ∼ 1000 × faster than running a new Monte Carlo simulation. A detailed discussion of the proper treatment of uncertainties when using this and other similar methods is provided as well. This method is demonstrated and tested using simulated data from the Chi-Nu experiment, which measures prompt fission neutron spectra at the Los Alamos Neutron Science Center.

Numerical integration of detector response functions via Monte Carlo simulations

DOE PAGES

Kelly, Keegan John; O'Donnell, John M.; Gomez, Jaime A.; ...

2017-06-13

Calculations of detector response functions are complicated because they include the intricacies of signal creation from the detector itself as well as a complex interplay between the detector, the particle-emitting target, and the entire experimental environment. As such, these functions are typically only accessible through time-consuming Monte Carlo simulations. Furthermore, the output of thousands of Monte Carlo simulations can be necessary in order to extract a physics result from a single experiment. Here we describe a method to obtain a full description of the detector response function using Monte Carlo simulations. We also show that a response function calculated inmore » this way can be used to create Monte Carlo simulation output spectra a factor of ~1000× faster than running a new Monte Carlo simulation. A detailed discussion of the proper treatment of uncertainties when using this and other similar methods is provided as well. Here, this method is demonstrated and tested using simulated data from the Chi-Nu experiment, which measures prompt fission neutron spectra at the Los Alamos Neutron Science Center.« less

Efficient Monte Carlo Methods for Biomolecular Simulations.

NASA Astrophysics Data System (ADS)

Bouzida, Djamal

A new approach to efficient Monte Carlo simulations of biological molecules is presented. By relaxing the usual restriction to Markov processes, we are able to optimize performance while dealing directly with the inhomogeneity and anisotropy inherent in these systems. The advantage of this approach is that we can introduce a wide variety of Monte Carlo moves to deal with complicated motions of the molecule, while maintaining full optimization at every step. This enables the use of a variety of collective rotational moves that relax long-wavelength modes. We were able to show by explicit simulations that the resulting algorithms substantially increase the speed of the simulation while reproducing the correct equilibrium behavior. This approach is particularly intended for simulations of macromolecules, although we expect it to be useful in other situations. The dynamic optimization of the new Monte Carlo methods makes them very suitable for simulated annealing experiments on all systems whose state space is continuous in general, and to the protein folding problem in particular. We introduce an efficient annealing schedule using preferential bias moves. Our simulated annealing experiments yield structures whose free energies were lower than the equilibrated X-ray structure, which leads us to believe that the empirical energy function used does not fully represent the interatomic interactions. Furthermore, we believe that the largest discrepancies involve the solvent effects in particular.

Brownian dynamics and dynamic Monte Carlo simulations of isotropic and liquid crystal phases of anisotropic colloidal particles: a comparative study.

PubMed

Patti, Alessandro; Cuetos, Alejandro

2012-07-01

We report on the diffusion of purely repulsive and freely rotating colloidal rods in the isotropic, nematic, and smectic liquid crystal phases to probe the agreement between Brownian and Monte Carlo dynamics under the most general conditions. By properly rescaling the Monte Carlo time step, being related to any elementary move via the corresponding self-diffusion coefficient, with the acceptance rate of simultaneous trial displacements and rotations, we demonstrate the existence of a unique Monte Carlo time scale that allows for a direct comparison between Monte Carlo and Brownian dynamics simulations. To estimate the validity of our theoretical approach, we compare the mean square displacement of rods, their orientational autocorrelation function, and the self-intermediate scattering function, as obtained from Brownian dynamics and Monte Carlo simulations. The agreement between the results of these two approaches, even under the condition of heterogeneous dynamics generally observed in liquid crystalline phases, is excellent.

Role of Boundary Conditions in Monte Carlo Simulation of MEMS Devices

NASA Technical Reports Server (NTRS)

Nance, Robert P.; Hash, David B.; Hassan, H. A.

1997-01-01

A study is made of the issues surrounding prediction of microchannel flows using the direct simulation Monte Carlo method. This investigation includes the introduction and use of new inflow and outflow boundary conditions suitable for subsonic flows. A series of test simulations for a moderate-size microchannel indicates that a high degree of grid under-resolution in the streamwise direction may be tolerated without loss of accuracy. In addition, the results demonstrate the importance of physically correct boundary conditions, as well as possibilities for reducing the time associated with the transient phase of a simulation. These results imply that simulations of longer ducts may be more feasible than previously envisioned.

Ground state of excitonic molecules by the Green's-function Monte Carlo method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, M.A.; Vashishta, P.; Kalia, R.K.

1983-12-26

The ground-state energy of excitonic molecules is evaluated as a function of the ratio of electron and hole masses, sigma, with use of the Green's-function Monte Carlo method. For all sigma, the Green's-function Monte Carlo energies are significantly lower than the variational estimates and in favorable agreement with experiments. In excitonic rydbergs, the binding energy of the positronium molecule (sigma = 1) is predicted to be -0.06 and for sigma<<1, the Green's-function Monte Carlo energies agree with the ''exact'' limiting behavior, E = -2.346+0.764sigma.

Use of the FLUKA Monte Carlo code for 3D patient-specific dosimetry on PET-CT and SPECT-CT images*

PubMed Central

Botta, F; Mairani, A; Hobbs, R F; Vergara Gil, A; Pacilio, M; Parodi, K; Cremonesi, M; Coca Pérez, M A; Di Dia, A; Ferrari, M; Guerriero, F; Battistoni, G; Pedroli, G; Paganelli, G; Torres Aroche, L A; Sgouros, G

2014-01-01

Patient-specific absorbed dose calculation for nuclear medicine therapy is a topic of increasing interest. 3D dosimetry at the voxel level is one of the major improvements for the development of more accurate calculation techniques, as compared to the standard dosimetry at the organ level. This study aims to use the FLUKA Monte Carlo code to perform patient-specific 3D dosimetry through direct Monte Carlo simulation on PET-CT and SPECT-CT images. To this aim, dedicated routines were developed in the FLUKA environment. Two sets of simulations were performed on model and phantom images. Firstly, the correct handling of PET and SPECT images was tested under the assumption of homogeneous water medium by comparing FLUKA results with those obtained with the voxel kernel convolution method and with other Monte Carlo-based tools developed to the same purpose (the EGS-based 3D-RD software and the MCNP5-based MCID). Afterwards, the correct integration of the PET/SPECT and CT information was tested, performing direct simulations on PET/CT images for both homogeneous (water) and non-homogeneous (water with air, lung and bone inserts) phantoms. Comparison was performed with the other Monte Carlo tools performing direct simulation as well. The absorbed dose maps were compared at the voxel level. In the case of homogeneous water, by simulating 108 primary particles a 2% average difference with respect to the kernel convolution method was achieved; such difference was lower than the statistical uncertainty affecting the FLUKA results. The agreement with the other tools was within 3–4%, partially ascribable to the differences among the simulation algorithms. Including the CT-based density map, the average difference was always within 4% irrespective of the medium (water, air, bone), except for a maximum 6% value when comparing FLUKA and 3D-RD in air. The results confirmed that the routines were properly developed, opening the way for the use of FLUKA for patient-specific, image-based dosimetry in nuclear medicine. PMID:24200697

Massively parallelized Monte Carlo software to calculate the light propagation in arbitrarily shaped 3D turbid media

NASA Astrophysics Data System (ADS)

Zoller, Christian; Hohmann, Ansgar; Ertl, Thomas; Kienle, Alwin

2017-07-01

The Monte Carlo method is often referred as the gold standard to calculate the light propagation in turbid media [1]. Especially for complex shaped geometries where no analytical solutions are available the Monte Carlo method becomes very important [1, 2]. In this work a Monte Carlo software is presented, to simulate the light propagation in complex shaped geometries. To improve the simulation time the code is based on OpenCL such that graphics cards can be used as well as other computing devices. Within the software an illumination concept is presented to realize easily all kinds of light sources, like spatial frequency domain (SFD), optical fibers or Gaussian beam profiles. Moreover different objects, which are not connected to each other, can be considered simultaneously, without any additional preprocessing. This Monte Carlo software can be used for many applications. In this work the transmission spectrum of a tooth and the color reconstruction of a virtual object are shown, using results from the Monte Carlo software.

Extensions of the MCNP5 and TRIPOLI4 Monte Carlo Codes for Transient Reactor Analysis

NASA Astrophysics Data System (ADS)

Hoogenboom, J. Eduard; Sjenitzer, Bart L.

2014-06-01

To simulate reactor transients for safety analysis with the Monte Carlo method the generation and decay of delayed neutron precursors is implemented in the MCNP5 and TRIPOLI4 general purpose Monte Carlo codes. Important new variance reduction techniques like forced decay of precursors in each time interval and the branchless collision method are included to obtain reasonable statistics for the power production per time interval. For simulation of practical reactor transients also the feedback effect from the thermal-hydraulics must be included. This requires coupling of the Monte Carlo code with a thermal-hydraulics (TH) code, providing the temperature distribution in the reactor, which affects the neutron transport via the cross section data. The TH code also provides the coolant density distribution in the reactor, directly influencing the neutron transport. Different techniques for this coupling are discussed. As a demonstration a 3x3 mini fuel assembly with a moving control rod is considered for MCNP5 and a mini core existing of 3x3 PWR fuel assemblies with control rods and burnable poisons for TRIPOLI4. Results are shown for reactor transients due to control rod movement or withdrawal. The TRIPOLI4 transient calculation is started at low power and includes thermal-hydraulic feedback. The power rises about 10 decades and finally stabilises the reactor power at a much higher level than initial. The examples demonstrate that the modified Monte Carlo codes are capable of performing correct transient calculations, taking into account all geometrical and cross section detail.

Radiative transfer calculated from a Markov chain formalism

NASA Technical Reports Server (NTRS)

Esposito, L. W.; House, L. L.

1978-01-01

The theory of Markov chains is used to formulate the radiative transport problem in a general way by modeling the successive interactions of a photon as a stochastic process. Under the minimal requirement that the stochastic process is a Markov chain, the determination of the diffuse reflection or transmission from a scattering atmosphere is equivalent to the solution of a system of linear equations. This treatment is mathematically equivalent to, and thus has many of the advantages of, Monte Carlo methods, but can be considerably more rapid than Monte Carlo algorithms for numerical calculations in particular applications. We have verified the speed and accuracy of this formalism for the standard problem of finding the intensity of scattered light from a homogeneous plane-parallel atmosphere with an arbitrary phase function for scattering. Accurate results over a wide range of parameters were obtained with computation times comparable to those of a standard 'doubling' routine. The generality of this formalism thus allows fast, direct solutions to problems that were previously soluble only by Monte Carlo methods. Some comparisons are made with respect to integral equation methods.

Monte Carlo method for calculating the radiation skyshine produced by electron accelerators

NASA Astrophysics Data System (ADS)

Kong, Chaocheng; Li, Quanfeng; Chen, Huaibi; Du, Taibin; Cheng, Cheng; Tang, Chuanxiang; Zhu, Li; Zhang, Hui; Pei, Zhigang; Ming, Shenjin

2005-06-01

Using the MCNP4C Monte Carlo code, the X-ray skyshine produced by 9 MeV, 15 MeV and 21 MeV electron linear accelerators were calculated respectively with a new two-step method combined with the split and roulette variance reduction technique. Results of the Monte Carlo simulation, the empirical formulas used for skyshine calculation and the dose measurements were analyzed and compared. In conclusion, the skyshine dose measurements agreed reasonably with the results computed by the Monte Carlo method, but deviated from computational results given by empirical formulas. The effect on skyshine dose caused by different structures of accelerator head is also discussed in this paper.

Geometrically Constructed Markov Chain Monte Carlo Study of Quantum Spin-phonon Complex Systems

NASA Astrophysics Data System (ADS)

Suwa, Hidemaro

2013-03-01

We have developed novel Monte Carlo methods for precisely calculating quantum spin-boson models and investigated the critical phenomena of the spin-Peierls systems. Three significant methods are presented. The first is a new optimization algorithm of the Markov chain transition kernel based on the geometric weight allocation. This algorithm, for the first time, satisfies the total balance generally without imposing the detailed balance and always minimizes the average rejection rate, being better than the Metropolis algorithm. The second is the extension of the worm (directed-loop) algorithm to non-conserved particles, which cannot be treated efficiently by the conventional methods. The third is the combination with the level spectroscopy. Proposing a new gap estimator, we are successful in eliminating the systematic error of the conventional moment method. Then we have elucidated the phase diagram and the universality class of the one-dimensional XXZ spin-Peierls system. The criticality is totally consistent with the J1 -J2 model, an effective model in the antiadiabatic limit. Through this research, we have succeeded in investigating the critical phenomena of the effectively frustrated quantum spin system by the quantum Monte Carlo method without the negative sign. JSPS Postdoctoral Fellow for Research Abroad

Particle tracking acceleration via signed distance fields in direct-accelerated geometry Monte Carlo

DOE PAGES

Shriwise, Patrick C.; Davis, Andrew; Jacobson, Lucas J.; ...

2017-08-26

Computer-aided design (CAD)-based Monte Carlo radiation transport is of value to the nuclear engineering community for its ability to conduct transport on high-fidelity models of nuclear systems, but it is more computationally expensive than native geometry representations. This work describes the adaptation of a rendering data structure, the signed distance field, as a geometric query tool for accelerating CAD-based transport in the direct-accelerated geometry Monte Carlo toolkit. Demonstrations of its effectiveness are shown for several problems. The beginnings of a predictive model for the data structure's utilization based on various problem parameters is also introduced.

A histogram-free multicanonical Monte Carlo algorithm for the construction of analytical density of states

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eisenbach, Markus; Li, Ying Wai

We report a new multicanonical Monte Carlo (MC) algorithm to obtain the density of states (DOS) for physical systems with continuous state variables in statistical mechanics. Our algorithm is able to obtain an analytical form for the DOS expressed in a chosen basis set, instead of a numerical array of finite resolution as in previous variants of this class of MC methods such as the multicanonical (MUCA) sampling and Wang-Landau (WL) sampling. This is enabled by storing the visited states directly in a data set and avoiding the explicit collection of a histogram. This practice also has the advantage ofmore » avoiding undesirable artificial errors caused by the discretization and binning of continuous state variables. Our results show that this scheme is capable of obtaining converged results with a much reduced number of Monte Carlo steps, leading to a significant speedup over existing algorithms.« less

Monte Carlo modeling of spatial coherence: free-space diffraction

PubMed Central

Fischer, David G.; Prahl, Scott A.; Duncan, Donald D.

2008-01-01

We present a Monte Carlo method for propagating partially coherent fields through complex deterministic optical systems. A Gaussian copula is used to synthesize a random source with an arbitrary spatial coherence function. Physical optics and Monte Carlo predictions of the first- and second-order statistics of the field are shown for coherent and partially coherent sources for free-space propagation, imaging using a binary Fresnel zone plate, and propagation through a limiting aperture. Excellent agreement between the physical optics and Monte Carlo predictions is demonstrated in all cases. Convergence criteria are presented for judging the quality of the Monte Carlo predictions. PMID:18830335

DOE Office of Scientific and Technical Information (OSTI.GOV)

Costa, Liborio I., E-mail: liborio78@gmail.com

A new Markov Chain Monte Carlo method for simulating the dynamics of particle systems characterized by hard-core interactions is introduced. In contrast to traditional Kinetic Monte Carlo approaches, where the state of the system is associated with minima in the energy landscape, in the proposed method, the state of the system is associated with the set of paths traveled by the atoms and the transition probabilities for an atom to be displaced are proportional to the corresponding velocities. In this way, the number of possible state-to-state transitions is reduced to a discrete set, and a direct link between the Montemore » Carlo time step and true physical time is naturally established. The resulting rejection-free algorithm is validated against event-driven molecular dynamics: the equilibrium and non-equilibrium dynamics of hard disks converge to the exact results with decreasing displacement size.« less

Comparison of internal dose estimates obtained using organ-level, voxel S value, and Monte Carlo techniques

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grimes, Joshua, E-mail: grimes.joshua@mayo.edu; Celler, Anna

2014-09-15

Purpose: The authors’ objective was to compare internal dose estimates obtained using the Organ Level Dose Assessment with Exponential Modeling (OLINDA/EXM) software, the voxel S value technique, and Monte Carlo simulation. Monte Carlo dose estimates were used as the reference standard to assess the impact of patient-specific anatomy on the final dose estimate. Methods: Six patients injected with{sup 99m}Tc-hydrazinonicotinamide-Tyr{sup 3}-octreotide were included in this study. A hybrid planar/SPECT imaging protocol was used to estimate {sup 99m}Tc time-integrated activity coefficients (TIACs) for kidneys, liver, spleen, and tumors. Additionally, TIACs were predicted for {sup 131}I, {sup 177}Lu, and {sup 90}Y assuming themore » same biological half-lives as the {sup 99m}Tc labeled tracer. The TIACs were used as input for OLINDA/EXM for organ-level dose calculation and voxel level dosimetry was performed using the voxel S value method and Monte Carlo simulation. Dose estimates for {sup 99m}Tc, {sup 131}I, {sup 177}Lu, and {sup 90}Y distributions were evaluated by comparing (i) organ-level S values corresponding to each method, (ii) total tumor and organ doses, (iii) differences in right and left kidney doses, and (iv) voxelized dose distributions calculated by Monte Carlo and the voxel S value technique. Results: The S values for all investigated radionuclides used by OLINDA/EXM and the corresponding patient-specific S values calculated by Monte Carlo agreed within 2.3% on average for self-irradiation, and differed by as much as 105% for cross-organ irradiation. Total organ doses calculated by OLINDA/EXM and the voxel S value technique agreed with Monte Carlo results within approximately ±7%. Differences between right and left kidney doses determined by Monte Carlo were as high as 73%. Comparison of the Monte Carlo and voxel S value dose distributions showed that each method produced similar dose volume histograms with a minimum dose covering 90% of the volume (D90) agreeing within ±3%, on average. Conclusions: Several aspects of OLINDA/EXM dose calculation were compared with patient-specific dose estimates obtained using Monte Carlo. Differences in patient anatomy led to large differences in cross-organ doses. However, total organ doses were still in good agreement since most of the deposited dose is due to self-irradiation. Comparison of voxelized doses calculated by Monte Carlo and the voxel S value technique showed that the 3D dose distributions produced by the respective methods are nearly identical.« less

SU-F-T-111: Investigation of the Attila Deterministic Solver as a Supplement to Monte Carlo for Calculating Out-Of-Field Radiotherapy Dose

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mille, M; Lee, C; Failla, G

Purpose: To use the Attila deterministic solver as a supplement to Monte Carlo for calculating out-of-field organ dose in support of epidemiological studies looking at the risks of second cancers. Supplemental dosimetry tools are needed to speed up dose calculations for studies involving large-scale patient cohorts. Methods: Attila is a multi-group discrete ordinates code which can solve the 3D photon-electron coupled linear Boltzmann radiation transport equation on a finite-element mesh. Dose is computed by multiplying the calculated particle flux in each mesh element by a medium-specific energy deposition cross-section. The out-of-field dosimetry capability of Attila is investigated by comparing averagemore » organ dose to that which is calculated by Monte Carlo simulation. The test scenario consists of a 6 MV external beam treatment of a female patient with a tumor in the left breast. The patient is simulated by a whole-body adult reference female computational phantom. Monte Carlo simulations were performed using MCNP6 and XVMC. Attila can export a tetrahedral mesh for MCNP6, allowing for a direct comparison between the two codes. The Attila and Monte Carlo methods were also compared in terms of calculation speed and complexity of simulation setup. A key perquisite for this work was the modeling of a Varian Clinac 2100 linear accelerator. Results: The solid mesh of the torso part of the adult female phantom for the Attila calculation was prepared using the CAD software SpaceClaim. Preliminary calculations suggest that Attila is a user-friendly software which shows great promise for our intended application. Computational performance is related to the number of tetrahedral elements included in the Attila calculation. Conclusion: Attila is being explored as a supplement to the conventional Monte Carlo radiation transport approach for performing retrospective patient dosimetry. The goal is for the dosimetry to be sufficiently accurate for use in retrospective epidemiological investigations.« less

Deterministic theory of Monte Carlo variance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ueki, T.; Larsen, E.W.

1996-12-31

The theoretical estimation of variance in Monte Carlo transport simulations, particularly those using variance reduction techniques, is a substantially unsolved problem. In this paper, the authors describe a theory that predicts the variance in a variance reduction method proposed by Dwivedi. Dwivedi`s method combines the exponential transform with angular biasing. The key element of this theory is a new modified transport problem, containing the Monte Carlo weight w as an extra independent variable, which simulates Dwivedi`s Monte Carlo scheme. The (deterministic) solution of this modified transport problem yields an expression for the variance. The authors give computational results that validatemore » this theory.« less

Recommender engine for continuous-time quantum Monte Carlo methods

NASA Astrophysics Data System (ADS)

Huang, Li; Yang, Yi-feng; Wang, Lei

2017-03-01

Recommender systems play an essential role in the modern business world. They recommend favorable items such as books, movies, and search queries to users based on their past preferences. Applying similar ideas and techniques to Monte Carlo simulations of physical systems boosts their efficiency without sacrificing accuracy. Exploiting the quantum to classical mapping inherent in the continuous-time quantum Monte Carlo methods, we construct a classical molecular gas model to reproduce the quantum distributions. We then utilize powerful molecular simulation techniques to propose efficient quantum Monte Carlo updates. The recommender engine approach provides a general way to speed up the quantum impurity solvers.

Sample Size and Power Estimates for a Confirmatory Factor Analytic Model in Exercise and Sport: A Monte Carlo Approach

ERIC Educational Resources Information Center

Myers, Nicholas D.; Ahn, Soyeon; Jin, Ying

2011-01-01

Monte Carlo methods can be used in data analytic situations (e.g., validity studies) to make decisions about sample size and to estimate power. The purpose of using Monte Carlo methods in a validity study is to improve the methodological approach within a study where the primary focus is on construct validity issues and not on advancing…

Frequency-resolved Monte Carlo.

PubMed

López Carreño, Juan Camilo; Del Valle, Elena; Laussy, Fabrice P

2018-05-03

We adapt the Quantum Monte Carlo method to the cascaded formalism of quantum optics, allowing us to simulate the emission of photons of known energy. Statistical processing of the photon clicks thus collected agrees with the theory of frequency-resolved photon correlations, extending the range of applications based on correlations of photons of prescribed energy, in particular those of a photon-counting character. We apply the technique to autocorrelations of photon streams from a two-level system under coherent and incoherent pumping, including the Mollow triplet regime where we demonstrate the direct manifestation of leapfrog processes in producing an increased rate of two-photon emission events.

Variance reduction for Fokker–Planck based particle Monte Carlo schemes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gorji, M. Hossein, E-mail: gorjih@ifd.mavt.ethz.ch; Andric, Nemanja; Jenny, Patrick

Recently, Fokker–Planck based particle Monte Carlo schemes have been proposed and evaluated for simulations of rarefied gas flows [1–3]. In this paper, the variance reduction for particle Monte Carlo simulations based on the Fokker–Planck model is considered. First, deviational based schemes were derived and reviewed, and it is shown that these deviational methods are not appropriate for practical Fokker–Planck based rarefied gas flow simulations. This is due to the fact that the deviational schemes considered in this study lead either to instabilities in the case of two-weight methods or to large statistical errors if the direct sampling method is applied.more » Motivated by this conclusion, we developed a novel scheme based on correlated stochastic processes. The main idea here is to synthesize an additional stochastic process with a known solution, which is simultaneously solved together with the main one. By correlating the two processes, the statistical errors can dramatically be reduced; especially for low Mach numbers. To assess the methods, homogeneous relaxation, planar Couette and lid-driven cavity flows were considered. For these test cases, it could be demonstrated that variance reduction based on parallel processes is very robust and effective.« less

Hybrid Monte Carlo-Diffusion Method For Light Propagation in Tissue With a Low-Scattering Region

NASA Astrophysics Data System (ADS)

Hayashi, Toshiyuki; Kashio, Yoshihiko; Okada, Eiji

2003-06-01

The heterogeneity of the tissues in a head, especially the low-scattering cerebrospinal fluid (CSF) layer surrounding the brain has previously been shown to strongly affect light propagation in the brain. The radiosity-diffusion method, in which the light propagation in the CSF layer is assumed to obey the radiosity theory, has been employed to predict the light propagation in head models. Although the CSF layer is assumed to be a nonscattering region in the radiosity-diffusion method, fine arachnoid trabeculae cause faint scattering in the CSF layer in real heads. A novel approach, the hybrid Monte Carlo-diffusion method, is proposed to calculate the head models, including the low-scattering region in which the light propagation does not obey neither the diffusion approximation nor the radiosity theory. The light propagation in the high-scattering region is calculated by means of the diffusion approximation solved by the finite-element method and that in the low-scattering region is predicted by the Monte Carlo method. The intensity and mean time of flight of the detected light for the head model with a low-scattering CSF layer calculated by the hybrid method agreed well with those by the Monte Carlo method, whereas the results calculated by means of the diffusion approximation included considerable error caused by the effect of the CSF layer. In the hybrid method, the time-consuming Monte Carlo calculation is employed only for the thin CSF layer, and hence, the computation time of the hybrid method is dramatically shorter than that of the Monte Carlo method.

Hybrid Monte Carlo-diffusion method for light propagation in tissue with a low-scattering region.

PubMed

Hayashi, Toshiyuki; Kashio, Yoshihiko; Okada, Eiji

2003-06-01

The heterogeneity of the tissues in a head, especially the low-scattering cerebrospinal fluid (CSF) layer surrounding the brain has previously been shown to strongly affect light propagation in the brain. The radiosity-diffusion method, in which the light propagation in the CSF layer is assumed to obey the radiosity theory, has been employed to predict the light propagation in head models. Although the CSF layer is assumed to be a nonscattering region in the radiosity-diffusion method, fine arachnoid trabeculae cause faint scattering in the CSF layer in real heads. A novel approach, the hybrid Monte Carlo-diffusion method, is proposed to calculate the head models, including the low-scattering region in which the light propagation does not obey neither the diffusion approximation nor the radiosity theory. The light propagation in the high-scattering region is calculated by means of the diffusion approximation solved by the finite-element method and that in the low-scattering region is predicted by the Monte Carlo method. The intensity and mean time of flight of the detected light for the head model with a low-scattering CSF layer calculated by the hybrid method agreed well with those by the Monte Carlo method, whereas the results calculated by means of the diffusion approximation included considerable error caused by the effect of the CSF layer. In the hybrid method, the time-consuming Monte Carlo calculation is employed only for the thin CSF layer, and hence, the computation time of the hybrid method is dramatically shorter than that of the Monte Carlo method.

NUEN-618 Class Project: Actually Implicit Monte Carlo

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vega, R. M.; Brunner, T. A.

2017-12-14

This research describes a new method for the solution of the thermal radiative transfer (TRT) equations that is implicit in time which will be called Actually Implicit Monte Carlo (AIMC). This section aims to introduce the TRT equations, as well as the current workhorse method which is known as Implicit Monte Carlo (IMC). As the name of the method proposed here indicates, IMC is a misnomer in that it is only semi-implicit, which will be shown in this section as well.

Direct simulation Monte Carlo investigation of the Richtmyer-Meshkov instability

DOE PAGES

Gallis, Michail A.; Koehler, Timothy P.; Torczynski, John R.; ...

2015-08-14

The Rayleigh-Taylor instability (RTI) is investigated using the Direct Simulation Monte Carlo (DSMC) method of molecular gas dynamics. Here, fully resolved two-dimensional DSMC RTI simulations are performed to quantify the growth of flat and single-mode perturbed interfaces between two atmospheric-pressure monatomic gases as a function of the Atwood number and the gravitational acceleration. The DSMC simulations reproduce all qualitative features of the RTI and are in reasonable quantitative agreement with existing theoretical and empirical models in the linear, nonlinear, and self-similar regimes. At late times, the instability is seen to exhibit a self-similar behavior, in agreement with experimental observations. Formore » the conditions simulated, diffusion can influence the initial instability growth significantly.« less

Fixed-node quantum Monte Carlo

NASA Astrophysics Data System (ADS)

Anderson, James B.

Quantum Monte Carlo methods cannot at present provide exact solutions of the Schrödinger equation for systems with more than a few electrons. But, quantum Monte Carlo calculations can provide very low energy, highly accurate solutions for many systems ranging up to several hundred electrons. These systems include atoms such as Be and Fe, molecules such as H2O, CH4, and HF, and condensed materials such as solid N2 and solid silicon. The quantum Monte Carlo predictions of their energies and structures may not be `exact', but they are the best available. Most of the Monte Carlo calculations for these systems have been carried out using approximately correct fixed nodal hypersurfaces and they have come to be known as `fixed-node quantum Monte Carlo' calculations. In this paper we review these `fixed node' calculations and the accuracies they yield.

Analysis and Assessment of Operation Risk for Hybrid AC/DC Power System based on the Monte Carlo Method

NASA Astrophysics Data System (ADS)

Hu, Xiaojing; Li, Qiang; Zhang, Hao; Guo, Ziming; Zhao, Kun; Li, Xinpeng

2018-06-01

Based on the Monte Carlo method, an improved risk assessment method for hybrid AC/DC power system with VSC station considering the operation status of generators, converter stations, AC lines and DC lines is proposed. According to the sequential AC/DC power flow algorithm, node voltage and line active power are solved, and then the operation risk indices of node voltage over-limit and line active power over-limit are calculated. Finally, an improved two-area IEEE RTS-96 system is taken as a case to analyze and assessment its operation risk. The results show that the proposed model and method can intuitively and directly reflect the weak nodes and weak lines of the system, which can provide some reference for the dispatching department.

Use of a Monte Carlo technique to complete a fragmented set of H2S emission rates from a wastewater treatment plant.

PubMed

Schauberger, Günther; Piringer, Martin; Baumann-Stanzer, Kathrin; Knauder, Werner; Petz, Erwin

2013-12-15

The impact of ambient concentrations in the vicinity of a plant can only be assessed if the emission rate is known. In this study, based on measurements of ambient H2S concentrations and meteorological parameters, the a priori unknown emission rates of a tannery wastewater treatment plant are calculated by an inverse dispersion technique. The calculations are determined using the Gaussian Austrian regulatory dispersion model. Following this method, emission data can be obtained, though only for a measurement station that is positioned such that the wind direction at the measurement station is leeward of the plant. Using the inverse transform sampling, which is a Monte Carlo technique, the dataset can also be completed for those wind directions for which no ambient concentration measurements are available. For the model validation, the measured ambient concentrations are compared with the calculated ambient concentrations obtained from the synthetic emission data of the Monte Carlo model. The cumulative frequency distribution of this new dataset agrees well with the empirical data. This inverse transform sampling method is thus a useful supplement for calculating emission rates using the inverse dispersion technique. Copyright © 2013 Elsevier B.V. All rights reserved.

QMCPACK: an open source ab initio quantum Monte Carlo package for the electronic structure of atoms, molecules and solids

NASA Astrophysics Data System (ADS)

Kim, Jeongnim; Baczewski, Andrew D.; Beaudet, Todd D.; Benali, Anouar; Chandler Bennett, M.; Berrill, Mark A.; Blunt, Nick S.; Josué Landinez Borda, Edgar; Casula, Michele; Ceperley, David M.; Chiesa, Simone; Clark, Bryan K.; Clay, Raymond C., III; Delaney, Kris T.; Dewing, Mark; Esler, Kenneth P.; Hao, Hongxia; Heinonen, Olle; Kent, Paul R. C.; Krogel, Jaron T.; Kylänpää, Ilkka; Li, Ying Wai; Lopez, M. Graham; Luo, Ye; Malone, Fionn D.; Martin, Richard M.; Mathuriya, Amrita; McMinis, Jeremy; Melton, Cody A.; Mitas, Lubos; Morales, Miguel A.; Neuscamman, Eric; Parker, William D.; Pineda Flores, Sergio D.; Romero, Nichols A.; Rubenstein, Brenda M.; Shea, Jacqueline A. R.; Shin, Hyeondeok; Shulenburger, Luke; Tillack, Andreas F.; Townsend, Joshua P.; Tubman, Norm M.; Van Der Goetz, Brett; Vincent, Jordan E.; ChangMo Yang, D.; Yang, Yubo; Zhang, Shuai; Zhao, Luning

2018-05-01

QMCPACK is an open source quantum Monte Carlo package for ab initio electronic structure calculations. It supports calculations of metallic and insulating solids, molecules, atoms, and some model Hamiltonians. Implemented real space quantum Monte Carlo algorithms include variational, diffusion, and reptation Monte Carlo. QMCPACK uses Slater–Jastrow type trial wavefunctions in conjunction with a sophisticated optimizer capable of optimizing tens of thousands of parameters. The orbital space auxiliary-field quantum Monte Carlo method is also implemented, enabling cross validation between different highly accurate methods. The code is specifically optimized for calculations with large numbers of electrons on the latest high performance computing architectures, including multicore central processing unit and graphical processing unit systems. We detail the program’s capabilities, outline its structure, and give examples of its use in current research calculations. The package is available at http://qmcpack.org.

QMCPACK: an open source ab initio quantum Monte Carlo package for the electronic structure of atoms, molecules and solids.

PubMed

Kim, Jeongnim; Baczewski, Andrew T; Beaudet, Todd D; Benali, Anouar; Bennett, M Chandler; Berrill, Mark A; Blunt, Nick S; Borda, Edgar Josué Landinez; Casula, Michele; Ceperley, David M; Chiesa, Simone; Clark, Bryan K; Clay, Raymond C; Delaney, Kris T; Dewing, Mark; Esler, Kenneth P; Hao, Hongxia; Heinonen, Olle; Kent, Paul R C; Krogel, Jaron T; Kylänpää, Ilkka; Li, Ying Wai; Lopez, M Graham; Luo, Ye; Malone, Fionn D; Martin, Richard M; Mathuriya, Amrita; McMinis, Jeremy; Melton, Cody A; Mitas, Lubos; Morales, Miguel A; Neuscamman, Eric; Parker, William D; Pineda Flores, Sergio D; Romero, Nichols A; Rubenstein, Brenda M; Shea, Jacqueline A R; Shin, Hyeondeok; Shulenburger, Luke; Tillack, Andreas F; Townsend, Joshua P; Tubman, Norm M; Van Der Goetz, Brett; Vincent, Jordan E; Yang, D ChangMo; Yang, Yubo; Zhang, Shuai; Zhao, Luning

2018-05-16

QMCPACK is an open source quantum Monte Carlo package for ab initio electronic structure calculations. It supports calculations of metallic and insulating solids, molecules, atoms, and some model Hamiltonians. Implemented real space quantum Monte Carlo algorithms include variational, diffusion, and reptation Monte Carlo. QMCPACK uses Slater-Jastrow type trial wavefunctions in conjunction with a sophisticated optimizer capable of optimizing tens of thousands of parameters. The orbital space auxiliary-field quantum Monte Carlo method is also implemented, enabling cross validation between different highly accurate methods. The code is specifically optimized for calculations with large numbers of electrons on the latest high performance computing architectures, including multicore central processing unit and graphical processing unit systems. We detail the program's capabilities, outline its structure, and give examples of its use in current research calculations. The package is available at http://qmcpack.org.

A study of microkinetic adjustments required to match shock wave experiments and Monte Carlo Direct Simulation for a wide Mach number range

NASA Technical Reports Server (NTRS)

Pham-Van-diep, Gerald C.; Muntz, E. Phillip; Erwin, Daniel A.

1990-01-01

Shock wave thickness predictions from Monte Carlo Direct Simulations, using differential scattering and the Maitland-Smith-Aziz interatomic potential, underpredict experiments as shock Mach numbers increase above about 4. Examination of several sources of data has indicated that at relatively high energies the repulsive portion of accepted potentials such as the Maitland-Smith-Aziz may be too steep. An Exponential-6 potential due to Ross, based on high energy molecular beam scattering data and shock velocity measurements in liquid argon, has been combined with the lower energy portion of the Maitland-Smith-Aziz potential. When this hybrid potential is used in Monte Carlo Direct Simulations, agreement with experiments is improved over the previous predictions using the pure Maitland-Smith-Aziz form.

Evaluation of an analytic linear Boltzmann transport equation solver for high-density inhomogeneities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lloyd, S. A. M.; Ansbacher, W.; Department of Physics and Astronomy, University of Victoria, Victoria, British Columbia V8W 3P6

2013-01-15

Purpose: Acuros external beam (Acuros XB) is a novel dose calculation algorithm implemented through the ECLIPSE treatment planning system. The algorithm finds a deterministic solution to the linear Boltzmann transport equation, the same equation commonly solved stochastically by Monte Carlo methods. This work is an evaluation of Acuros XB, by comparison with Monte Carlo, for dose calculation applications involving high-density materials. Existing non-Monte Carlo clinical dose calculation algorithms, such as the analytic anisotropic algorithm (AAA), do not accurately model dose perturbations due to increased electron scatter within high-density volumes. Methods: Acuros XB, AAA, and EGSnrc based Monte Carlo are usedmore » to calculate dose distributions from 18 MV and 6 MV photon beams delivered to a cubic water phantom containing a rectangular high density (4.0-8.0 g/cm{sup 3}) volume at its center. The algorithms are also used to recalculate a clinical prostate treatment plan involving a unilateral hip prosthesis, originally evaluated using AAA. These results are compared graphically and numerically using gamma-index analysis. Radio-chromic film measurements are presented to augment Monte Carlo and Acuros XB dose perturbation data. Results: Using a 2% and 1 mm gamma-analysis, between 91.3% and 96.8% of Acuros XB dose voxels containing greater than 50% the normalized dose were in agreement with Monte Carlo data for virtual phantoms involving 18 MV and 6 MV photons, stainless steel and titanium alloy implants and for on-axis and oblique field delivery. A similar gamma-analysis of AAA against Monte Carlo data showed between 80.8% and 87.3% agreement. Comparing Acuros XB and AAA evaluations of a clinical prostate patient plan involving a unilateral hip prosthesis, Acuros XB showed good overall agreement with Monte Carlo while AAA underestimated dose on the upstream medial surface of the prosthesis due to electron scatter from the high-density material. Film measurements support the dose perturbations demonstrated by Monte Carlo and Acuros XB data. Conclusions: Acuros XB is shown to perform as well as Monte Carlo methods and better than existing clinical algorithms for dose calculations involving high-density volumes.« less

Estimating statistical uncertainty of Monte Carlo efficiency-gain in the context of a correlated sampling Monte Carlo code for brachytherapy treatment planning with non-normal dose distribution.

PubMed

Mukhopadhyay, Nitai D; Sampson, Andrew J; Deniz, Daniel; Alm Carlsson, Gudrun; Williamson, Jeffrey; Malusek, Alexandr

2012-01-01

Correlated sampling Monte Carlo methods can shorten computing times in brachytherapy treatment planning. Monte Carlo efficiency is typically estimated via efficiency gain, defined as the reduction in computing time by correlated sampling relative to conventional Monte Carlo methods when equal statistical uncertainties have been achieved. The determination of the efficiency gain uncertainty arising from random effects, however, is not a straightforward task specially when the error distribution is non-normal. The purpose of this study is to evaluate the applicability of the F distribution and standardized uncertainty propagation methods (widely used in metrology to estimate uncertainty of physical measurements) for predicting confidence intervals about efficiency gain estimates derived from single Monte Carlo runs using fixed-collision correlated sampling in a simplified brachytherapy geometry. A bootstrap based algorithm was used to simulate the probability distribution of the efficiency gain estimates and the shortest 95% confidence interval was estimated from this distribution. It was found that the corresponding relative uncertainty was as large as 37% for this particular problem. The uncertainty propagation framework predicted confidence intervals reasonably well; however its main disadvantage was that uncertainties of input quantities had to be calculated in a separate run via a Monte Carlo method. The F distribution noticeably underestimated the confidence interval. These discrepancies were influenced by several photons with large statistical weights which made extremely large contributions to the scored absorbed dose difference. The mechanism of acquiring high statistical weights in the fixed-collision correlated sampling method was explained and a mitigation strategy was proposed. Copyright © 2011 Elsevier Ltd. All rights reserved.

Self-learning Monte Carlo method

DOE PAGES

Liu, Junwei; Qi, Yang; Meng, Zi Yang; ...

2017-01-04

Monte Carlo simulation is an unbiased numerical tool for studying classical and quantum many-body systems. One of its bottlenecks is the lack of a general and efficient update algorithm for large size systems close to the phase transition, for which local updates perform badly. In this Rapid Communication, we propose a general-purpose Monte Carlo method, dubbed self-learning Monte Carlo (SLMC), in which an efficient update algorithm is first learned from the training data generated in trial simulations and then used to speed up the actual simulation. Lastly, we demonstrate the efficiency of SLMC in a spin model at the phasemore » transition point, achieving a 10–20 times speedup.« less

An Improved Method of Heterogeneity Compensation for the Convolution / Superposition Algorithm

NASA Astrophysics Data System (ADS)

Jacques, Robert; McNutt, Todd

2014-03-01

Purpose: To improve the accuracy of convolution/superposition (C/S) in heterogeneous material by developing a new algorithm: heterogeneity compensated superposition (HCS). Methods: C/S has proven to be a good estimator of the dose deposited in a homogeneous volume. However, near heterogeneities electron disequilibrium occurs, leading to the faster fall-off and re-buildup of dose. We propose to filter the actual patient density in a position and direction sensitive manner, allowing the dose deposited near interfaces to be increased or decreased relative to C/S. We implemented the effective density function as a multivariate first-order recursive filter and incorporated it into GPU-accelerated, multi-energetic C/S implementation. We compared HCS against C/S using the ICCR 2000 Monte-Carlo accuracy benchmark, 23 similar accuracy benchmarks and 5 patient cases. Results: Multi-energetic HCS increased the dosimetric accuracy for the vast majority of voxels; in many cases near Monte-Carlo results were achieved. We defined the per-voxel error, %|mm, as the minimum of the distance to agreement in mm and the dosimetric percentage error relative to the maximum MC dose. HCS improved the average mean error by 0.79 %|mm for the patient volumes; reducing the average mean error from 1.93 %|mm to 1.14 %|mm. Very low densities (i.e. < 0.1 g / cm3) remained problematic, but may be solvable with a better filter function. Conclusions: HCS improved upon C/S's density scaled heterogeneity correction with a position and direction sensitive density filter. This method significantly improved the accuracy of the GPU based algorithm reaching the accuracy levels of Monte Carlo based methods with performance in a few tenths of seconds per beam. Acknowledgement: Funding for this research was provided by the NSF Cooperative Agreement EEC9731748, Elekta / IMPAC Medical Systems, Inc. and the Johns Hopkins University. James Satterthwaite provided the Monte Carlo benchmark simulations.

Improved Monte Carlo Renormalization Group Method

DOE R&D Accomplishments Database

Gupta, R.; Wilson, K. G.; Umrigar, C.

1985-01-01

An extensive program to analyze critical systems using an Improved Monte Carlo Renormalization Group Method (IMCRG) being undertaken at LANL and Cornell is described. Here we first briefly review the method and then list some of the topics being investigated.

Polarized radiative transfer considering thermal emission in semitransparent media

NASA Astrophysics Data System (ADS)

Ben, Xun; Yi, Hong-Liang; Tan, He-Ping

2014-09-01

The characteristics of the polarization must be considered for a complete and correct description of radiation transfer in a scattering medium. Observing and identifying the polarizition characteristics of the thermal emission of a hot semitransparent medium have a major significance to analyze the optical responses of the medium for different temperatures. In this paper, a Monte Carlo method is developed for polarzied radiative transfer in a semitransparent medium. There are mainly two kinds of mechanisms leading to polarization of light: specular reflection on the Fresnel boundary and scattering by particles. The determination of scattering direction is the key to solve polarized radiative transfer problem using the Monte Carlo method. An optimized rejection method is used to calculate the scattering angles. In the model, the treatment of specular reflection is also considered, and in the process of tracing photons, the normalization must be applied to the Stokes vector when scattering, reflection, or transmission occurs. The vector radiative transfer matrix (VRTM) is defined and solved using Monte Carlo strategy, by which all four Stokes elements can be determined. Our results for Rayleigh scattering and Mie scattering are compared well with published data. The accuracy of the developed Monte Carlo method is shown to be good enough for the solution to vector radiative transfer. Polarization characteristics of thermal emission in a hot semitransparent medium is investigated, and results show that the U and V parameters of Stokes vector are equal to zero, an obvious peak always appear in the Q curve instead of the I curve, and refractive index has a completely different effect on I from Q.

Technical Note: A direct ray-tracing method to compute integral depth dose in pencil beam proton radiography with a multilayer ionization chamber.

PubMed

Farace, Paolo; Righetto, Roberto; Deffet, Sylvain; Meijers, Arturs; Vander Stappen, Francois

2016-12-01

To introduce a fast ray-tracing algorithm in pencil proton radiography (PR) with a multilayer ionization chamber (MLIC) for in vivo range error mapping. Pencil beam PR was obtained by delivering spots uniformly positioned in a square (45 × 45 mm 2 field-of-view) of 9 × 9 spots capable of crossing the phantoms (210 MeV). The exit beam was collected by a MLIC to sample the integral depth dose (IDD MLIC ). PRs of an electron-density and of a head phantom were acquired by moving the couch to obtain multiple 45 × 45 mm 2 frames. To map the corresponding range errors, the two-dimensional set of IDD MLIC was compared with (i) the integral depth dose computed by the treatment planning system (TPS) by both analytic (IDD TPS ) and Monte Carlo (IDD MC ) algorithms in a volume of water simulating the MLIC at the CT, and (ii) the integral depth dose directly computed by a simple ray-tracing algorithm (IDD direct ) through the same CT data. The exact spatial position of the spot pattern was numerically adjusted testing different in-plane positions and selecting the one that minimized the range differences between IDD direct and IDD MLIC . Range error mapping was feasible by both the TPS and the ray-tracing methods, but very sensitive to even small misalignments. In homogeneous regions, the range errors computed by the direct ray-tracing algorithm matched the results obtained by both the analytic and the Monte Carlo algorithms. In both phantoms, lateral heterogeneities were better modeled by the ray-tracing and the Monte Carlo algorithms than by the analytic TPS computation. Accordingly, when the pencil beam crossed lateral heterogeneities, the range errors mapped by the direct algorithm matched better the Monte Carlo maps than those obtained by the analytic algorithm. Finally, the simplicity of the ray-tracing algorithm allowed to implement a prototype procedure for automated spatial alignment. The ray-tracing algorithm can reliably replace the TPS method in MLIC PR for in vivo range verification and it can be a key component to develop software tools for spatial alignment and correction of CT calibration.

Quantum speedup of Monte Carlo methods.

PubMed

Montanaro, Ashley

2015-09-08

Monte Carlo methods use random sampling to estimate numerical quantities which are hard to compute deterministically. One important example is the use in statistical physics of rapidly mixing Markov chains to approximately compute partition functions. In this work, we describe a quantum algorithm which can accelerate Monte Carlo methods in a very general setting. The algorithm estimates the expected output value of an arbitrary randomized or quantum subroutine with bounded variance, achieving a near-quadratic speedup over the best possible classical algorithm. Combining the algorithm with the use of quantum walks gives a quantum speedup of the fastest known classical algorithms with rigorous performance bounds for computing partition functions, which use multiple-stage Markov chain Monte Carlo techniques. The quantum algorithm can also be used to estimate the total variation distance between probability distributions efficiently.

Quantum speedup of Monte Carlo methods

PubMed Central

Montanaro, Ashley

2015-01-01

Monte Carlo methods use random sampling to estimate numerical quantities which are hard to compute deterministically. One important example is the use in statistical physics of rapidly mixing Markov chains to approximately compute partition functions. In this work, we describe a quantum algorithm which can accelerate Monte Carlo methods in a very general setting. The algorithm estimates the expected output value of an arbitrary randomized or quantum subroutine with bounded variance, achieving a near-quadratic speedup over the best possible classical algorithm. Combining the algorithm with the use of quantum walks gives a quantum speedup of the fastest known classical algorithms with rigorous performance bounds for computing partition functions, which use multiple-stage Markov chain Monte Carlo techniques. The quantum algorithm can also be used to estimate the total variation distance between probability distributions efficiently. PMID:26528079

Parameter Accuracy in Meta-Analyses of Factor Structures

ERIC Educational Resources Information Center

Gnambs, Timo; Staufenbiel, Thomas

2016-01-01

Two new methods for the meta-analysis of factor loadings are introduced and evaluated by Monte Carlo simulations. The direct method pools each factor loading individually, whereas the indirect method synthesizes correlation matrices reproduced from factor loadings. The results of the two simulations demonstrated that the accuracy of…

Simulation of Satellite, Airborne and Terrestrial LiDAR with DART (I):Waveform Simulation with Quasi-Monte Carlo Ray Tracing

NASA Technical Reports Server (NTRS)

Gastellu-Etchegorry, Jean-Philippe; Yin, Tiangang; Lauret, Nicolas; Grau, Eloi; Rubio, Jeremy; Cook, Bruce D.; Morton, Douglas C.; Sun, Guoqing

2016-01-01

Light Detection And Ranging (LiDAR) provides unique data on the 3-D structure of atmosphere constituents and the Earth's surface. Simulating LiDAR returns for different laser technologies and Earth scenes is fundamental for evaluating and interpreting signal and noise in LiDAR data. Different types of models are capable of simulating LiDAR waveforms of Earth surfaces. Semi-empirical and geometric models can be imprecise because they rely on simplified simulations of Earth surfaces and light interaction mechanisms. On the other hand, Monte Carlo ray tracing (MCRT) models are potentially accurate but require long computational time. Here, we present a new LiDAR waveform simulation tool that is based on the introduction of a quasi-Monte Carlo ray tracing approach in the Discrete Anisotropic Radiative Transfer (DART) model. Two new approaches, the so-called "box method" and "Ray Carlo method", are implemented to provide robust and accurate simulations of LiDAR waveforms for any landscape, atmosphere and LiDAR sensor configuration (view direction, footprint size, pulse characteristics, etc.). The box method accelerates the selection of the scattering direction of a photon in the presence of scatterers with non-invertible phase function. The Ray Carlo method brings traditional ray-tracking into MCRT simulation, which makes computational time independent of LiDAR field of view (FOV) and reception solid angle. Both methods are fast enough for simulating multi-pulse acquisition. Sensitivity studies with various landscapes and atmosphere constituents are presented, and the simulated LiDAR signals compare favorably with their associated reflectance images and Laser Vegetation Imaging Sensor (LVIS) waveforms. The LiDAR module is fully integrated into DART, enabling more detailed simulations of LiDAR sensitivity to specific scene elements (e.g., atmospheric aerosols, leaf area, branches, or topography) and sensor configuration for airborne or satellite LiDAR sensors.

Accuracy of Monte Carlo simulations compared to in-vivo MDCT dosimetry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bostani, Maryam, E-mail: mbostani@mednet.ucla.edu; McMillan, Kyle; Cagnon, Chris H.

Purpose: The purpose of this study was to assess the accuracy of a Monte Carlo simulation-based method for estimating radiation dose from multidetector computed tomography (MDCT) by comparing simulated doses in ten patients to in-vivo dose measurements. Methods: MD Anderson Cancer Center Institutional Review Board approved the acquisition of in-vivo rectal dose measurements in a pilot study of ten patients undergoing virtual colonoscopy. The dose measurements were obtained by affixing TLD capsules to the inner lumen of rectal catheters. Voxelized patient models were generated from the MDCT images of the ten patients, and the dose to the TLD for allmore » exposures was estimated using Monte Carlo based simulations. The Monte Carlo simulation results were compared to the in-vivo dose measurements to determine accuracy. Results: The calculated mean percent difference between TLD measurements and Monte Carlo simulations was −4.9% with standard deviation of 8.7% and a range of −22.7% to 5.7%. Conclusions: The results of this study demonstrate very good agreement between simulated and measured doses in-vivo. Taken together with previous validation efforts, this work demonstrates that the Monte Carlo simulation methods can provide accurate estimates of radiation dose in patients undergoing CT examinations.« less

On the utility of graphics cards to perform massively parallel simulation of advanced Monte Carlo methods

PubMed Central

Lee, Anthony; Yau, Christopher; Giles, Michael B.; Doucet, Arnaud; Holmes, Christopher C.

2011-01-01

We present a case-study on the utility of graphics cards to perform massively parallel simulation of advanced Monte Carlo methods. Graphics cards, containing multiple Graphics Processing Units (GPUs), are self-contained parallel computational devices that can be housed in conventional desktop and laptop computers and can be thought of as prototypes of the next generation of many-core processors. For certain classes of population-based Monte Carlo algorithms they offer massively parallel simulation, with the added advantage over conventional distributed multi-core processors that they are cheap, easily accessible, easy to maintain, easy to code, dedicated local devices with low power consumption. On a canonical set of stochastic simulation examples including population-based Markov chain Monte Carlo methods and Sequential Monte Carlo methods, we nd speedups from 35 to 500 fold over conventional single-threaded computer code. Our findings suggest that GPUs have the potential to facilitate the growth of statistical modelling into complex data rich domains through the availability of cheap and accessible many-core computation. We believe the speedup we observe should motivate wider use of parallelizable simulation methods and greater methodological attention to their design. PMID:22003276

Data Analysis Recipes: Using Markov Chain Monte Carlo

NASA Astrophysics Data System (ADS)

Hogg, David W.; Foreman-Mackey, Daniel

2018-05-01

Markov Chain Monte Carlo (MCMC) methods for sampling probability density functions (combined with abundant computational resources) have transformed the sciences, especially in performing probabilistic inferences, or fitting models to data. In this primarily pedagogical contribution, we give a brief overview of the most basic MCMC method and some practical advice for the use of MCMC in real inference problems. We give advice on method choice, tuning for performance, methods for initialization, tests of convergence, troubleshooting, and use of the chain output to produce or report parameter estimates with associated uncertainties. We argue that autocorrelation time is the most important test for convergence, as it directly connects to the uncertainty on the sampling estimate of any quantity of interest. We emphasize that sampling is a method for doing integrals; this guides our thinking about how MCMC output is best used. .

Predicting absorption and dispersion in acoustics by direct simulation Monte Carlo: Quantum and classical models for molecular relaxation.

PubMed

Hanford, Amanda D; O'Connor, Patrick D; Anderson, James B; Long, Lyle N

2008-06-01

In the current study, real gas effects in the propagation of sound waves are simulated using the direct simulation Monte Carlo method for a wide range of frequencies. This particle method allows for treatment of acoustic phenomena at high Knudsen numbers, corresponding to low densities and a high ratio of the molecular mean free path to wavelength. Different methods to model the internal degrees of freedom of diatomic molecules and the exchange of translational, rotational and vibrational energies in collisions are employed in the current simulations of a diatomic gas. One of these methods is the fully classical rigid-rotor/harmonic-oscillator model for rotation and vibration. A second method takes into account the discrete quantum energy levels for vibration with the closely spaced rotational levels classically treated. This method gives a more realistic representation of the internal structure of diatomic and polyatomic molecules. Applications of these methods are investigated in diatomic nitrogen gas in order to study the propagation of sound and its attenuation and dispersion along with their dependence on temperature. With the direct simulation method, significant deviations from continuum predictions are also observed for high Knudsen number flows.

Stochastic sampling of quadrature grids for the evaluation of vibrational expectation values

NASA Astrophysics Data System (ADS)

López Ríos, Pablo; Monserrat, Bartomeu; Needs, Richard J.

2018-02-01

The thermal lines method for the evaluation of vibrational expectation values of electronic observables [B. Monserrat, Phys. Rev. B 93, 014302 (2016), 10.1103/PhysRevB.93.014302] was recently proposed as a physically motivated approximation offering balance between the accuracy of direct Monte Carlo integration and the low computational cost of using local quadratic approximations. In this paper we reformulate thermal lines as a stochastic implementation of quadrature-grid integration, analyze the analytical form of its bias, and extend the method to multiple-point quadrature grids applicable to any factorizable harmonic or anharmonic nuclear wave function. The bias incurred by thermal lines is found to depend on the local form of the expectation value, and we demonstrate that the use of finer quadrature grids along selected modes can eliminate this bias, while still offering an ˜30 % lower computational cost than direct Monte Carlo integration in our tests.

Radiation Modeling with Direct Simulation Monte Carlo

NASA Technical Reports Server (NTRS)

Carlson, Ann B.; Hassan, H. A.

1991-01-01

Improvements in the modeling of radiation in low density shock waves with direct simulation Monte Carlo (DSMC) are the subject of this study. A new scheme to determine the relaxation collision numbers for excitation of electronic states is proposed. This scheme attempts to move the DSMC programs toward a more detailed modeling of the physics and more reliance on available rate data. The new method is compared with the current modeling technique and both techniques are compared with available experimental data. The differences in the results are evaluated. The test case is based on experimental measurements from the AVCO-Everett Research Laboratory electric arc-driven shock tube of a normal shock wave in air at 10 km/s and .1 Torr. The new method agrees with the available data as well as the results from the earlier scheme and is more easily extrapolated to di erent ow conditions.

Monte Carlo Techniques for Nuclear Systems - Theory Lectures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brown, Forrest B.

These are lecture notes for a Monte Carlo class given at the University of New Mexico. The following topics are covered: course information; nuclear eng. review & MC; random numbers and sampling; computational geometry; collision physics; tallies and statistics; eigenvalue calculations I; eigenvalue calculations II; eigenvalue calculations III; variance reduction; parallel Monte Carlo; parameter studies; fission matrix and higher eigenmodes; doppler broadening; Monte Carlo depletion; HTGR modeling; coupled MC and T/H calculations; fission energy deposition. Solving particle transport problems with the Monte Carlo method is simple - just simulate the particle behavior. The devil is in the details, however. Thesemore » lectures provide a balanced approach to the theory and practice of Monte Carlo simulation codes. The first lectures provide an overview of Monte Carlo simulation methods, covering the transport equation, random sampling, computational geometry, collision physics, and statistics. The next lectures focus on the state-of-the-art in Monte Carlo criticality simulations, covering the theory of eigenvalue calculations, convergence analysis, dominance ratio calculations, bias in Keff and tallies, bias in uncertainties, a case study of a realistic calculation, and Wielandt acceleration techniques. The remaining lectures cover advanced topics, including HTGR modeling and stochastic geometry, temperature dependence, fission energy deposition, depletion calculations, parallel calculations, and parameter studies. This portion of the class focuses on using MCNP to perform criticality calculations for reactor physics and criticality safety applications. It is an intermediate level class, intended for those with at least some familiarity with MCNP. Class examples provide hands-on experience at running the code, plotting both geometry and results, and understanding the code output. The class includes lectures & hands-on computer use for a variety of Monte Carlo calculations. Beginning MCNP users are encouraged to review LA-UR-09-00380, "Criticality Calculations with MCNP: A Primer (3nd Edition)" (available at http:// mcnp.lanl.gov under "Reference Collection") prior to the class. No Monte Carlo class can be complete without having students write their own simple Monte Carlo routines for basic random sampling, use of the random number generator, and simplified particle transport simulation.« less

FW-CADIS Method for Global and Semi-Global Variance Reduction of Monte Carlo Radiation Transport Calculations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wagner, John C; Peplow, Douglas E.; Mosher, Scott W

2014-01-01

This paper presents a new hybrid (Monte Carlo/deterministic) method for increasing the efficiency of Monte Carlo calculations of distributions, such as flux or dose rate distributions (e.g., mesh tallies), as well as responses at multiple localized detectors and spectra. This method, referred to as Forward-Weighted CADIS (FW-CADIS), is an extension of the Consistent Adjoint Driven Importance Sampling (CADIS) method, which has been used for more than a decade to very effectively improve the efficiency of Monte Carlo calculations of localized quantities, e.g., flux, dose, or reaction rate at a specific location. The basis of this method is the development ofmore » an importance function that represents the importance of particles to the objective of uniform Monte Carlo particle density in the desired tally regions. Implementation of this method utilizes the results from a forward deterministic calculation to develop a forward-weighted source for a deterministic adjoint calculation. The resulting adjoint function is then used to generate consistent space- and energy-dependent source biasing parameters and weight windows that are used in a forward Monte Carlo calculation to obtain more uniform statistical uncertainties in the desired tally regions. The FW-CADIS method has been implemented and demonstrated within the MAVRIC sequence of SCALE and the ADVANTG/MCNP framework. Application of the method to representative, real-world problems, including calculation of dose rate and energy dependent flux throughout the problem space, dose rates in specific areas, and energy spectra at multiple detectors, is presented and discussed. Results of the FW-CADIS method and other recently developed global variance reduction approaches are also compared, and the FW-CADIS method outperformed the other methods in all cases considered.« less

Event-driven Monte Carlo: Exact dynamics at all time scales for discrete-variable models

NASA Astrophysics Data System (ADS)

Mendoza-Coto, Alejandro; Díaz-Méndez, Rogelio; Pupillo, Guido

2016-06-01

We present an algorithm for the simulation of the exact real-time dynamics of classical many-body systems with discrete energy levels. In the same spirit of kinetic Monte Carlo methods, a stochastic solution of the master equation is found, with no need to define any other phase-space construction. However, unlike existing methods, the present algorithm does not assume any particular statistical distribution to perform moves or to advance the time, and thus is a unique tool for the numerical exploration of fast and ultra-fast dynamical regimes. By decomposing the problem in a set of two-level subsystems, we find a natural variable step size, that is well defined from the normalization condition of the transition probabilities between the levels. We successfully test the algorithm with known exact solutions for non-equilibrium dynamics and equilibrium thermodynamical properties of Ising-spin models in one and two dimensions, and compare to standard implementations of kinetic Monte Carlo methods. The present algorithm is directly applicable to the study of the real-time dynamics of a large class of classical Markovian chains, and particularly to short-time situations where the exact evolution is relevant.

Renyi entanglement entropy of interacting fermions calculated using the continuous-time quantum Monte Carlo method.

PubMed

Wang, Lei; Troyer, Matthias

2014-09-12

We present a new algorithm for calculating the Renyi entanglement entropy of interacting fermions using the continuous-time quantum Monte Carlo method. The algorithm only samples the interaction correction of the entanglement entropy, which by design ensures the efficient calculation of weakly interacting systems. Combined with Monte Carlo reweighting, the algorithm also performs well for systems with strong interactions. We demonstrate the potential of this method by studying the quantum entanglement signatures of the charge-density-wave transition of interacting fermions on a square lattice.

Monte Carlo Bayesian inference on a statistical model of sub-gridcolumn moisture variability using high-resolution cloud observations. Part 1: Method.

PubMed

Norris, Peter M; da Silva, Arlindo M

2016-07-01

A method is presented to constrain a statistical model of sub-gridcolumn moisture variability using high-resolution satellite cloud data. The method can be used for large-scale model parameter estimation or cloud data assimilation. The gridcolumn model includes assumed probability density function (PDF) intra-layer horizontal variability and a copula-based inter-layer correlation model. The observables used in the current study are Moderate Resolution Imaging Spectroradiometer (MODIS) cloud-top pressure, brightness temperature and cloud optical thickness, but the method should be extensible to direct cloudy radiance assimilation for a small number of channels. The algorithm is a form of Bayesian inference with a Markov chain Monte Carlo (MCMC) approach to characterizing the posterior distribution. This approach is especially useful in cases where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach is not gradient-based and allows jumps into regions of non-zero cloud probability. The current study uses a skewed-triangle distribution for layer moisture. The article also includes a discussion of the Metropolis and multiple-try Metropolis versions of MCMC.

Implementation and testing of the on-the-fly thermal scattering Monte Carlo sampling method for graphite and light water in MCNP6

DOE PAGES

Pavlou, Andrew T.; Ji, Wei; Brown, Forrest B.

2016-01-23

Here, a proper treatment of thermal neutron scattering requires accounting for chemical binding through a scattering law S(α,β,T). Monte Carlo codes sample the secondary neutron energy and angle after a thermal scattering event from probability tables generated from S(α,β,T) tables at discrete temperatures, requiring a large amount of data for multiscale and multiphysics problems with detailed temperature gradients. We have previously developed a method to handle this temperature dependence on-the-fly during the Monte Carlo random walk using polynomial expansions in 1/T to directly sample the secondary energy and angle. In this paper, the on-the-fly method is implemented into MCNP6 andmore » tested in both graphite-moderated and light water-moderated systems. The on-the-fly method is compared with the thermal ACE libraries that come standard with MCNP6, yielding good agreement with integral reactor quantities like k-eigenvalue and differential quantities like single-scatter secondary energy and angle distributions. The simulation runtimes are comparable between the two methods (on the order of 5–15% difference for the problems tested) and the on-the-fly fit coefficients only require 5–15 MB of total data storage.« less

Monte Carlo Bayesian Inference on a Statistical Model of Sub-Gridcolumn Moisture Variability Using High-Resolution Cloud Observations. Part 1: Method

NASA Technical Reports Server (NTRS)

Norris, Peter M.; Da Silva, Arlindo M.

2016-01-01

A method is presented to constrain a statistical model of sub-gridcolumn moisture variability using high-resolution satellite cloud data. The method can be used for large-scale model parameter estimation or cloud data assimilation. The gridcolumn model includes assumed probability density function (PDF) intra-layer horizontal variability and a copula-based inter-layer correlation model. The observables used in the current study are Moderate Resolution Imaging Spectroradiometer (MODIS) cloud-top pressure, brightness temperature and cloud optical thickness, but the method should be extensible to direct cloudy radiance assimilation for a small number of channels. The algorithm is a form of Bayesian inference with a Markov chain Monte Carlo (MCMC) approach to characterizing the posterior distribution. This approach is especially useful in cases where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach is not gradient-based and allows jumps into regions of non-zero cloud probability. The current study uses a skewed-triangle distribution for layer moisture. The article also includes a discussion of the Metropolis and multiple-try Metropolis versions of MCMC.

Monte Carlo Bayesian inference on a statistical model of sub-gridcolumn moisture variability using high-resolution cloud observations. Part 1: Method

PubMed Central

Norris, Peter M.; da Silva, Arlindo M.

2018-01-01

A method is presented to constrain a statistical model of sub-gridcolumn moisture variability using high-resolution satellite cloud data. The method can be used for large-scale model parameter estimation or cloud data assimilation. The gridcolumn model includes assumed probability density function (PDF) intra-layer horizontal variability and a copula-based inter-layer correlation model. The observables used in the current study are Moderate Resolution Imaging Spectroradiometer (MODIS) cloud-top pressure, brightness temperature and cloud optical thickness, but the method should be extensible to direct cloudy radiance assimilation for a small number of channels. The algorithm is a form of Bayesian inference with a Markov chain Monte Carlo (MCMC) approach to characterizing the posterior distribution. This approach is especially useful in cases where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach is not gradient-based and allows jumps into regions of non-zero cloud probability. The current study uses a skewed-triangle distribution for layer moisture. The article also includes a discussion of the Metropolis and multiple-try Metropolis versions of MCMC. PMID:29618847

SU-E-T-188: Film Dosimetry Verification of Monte Carlo Generated Electron Treatment Plans

DOE Office of Scientific and Technical Information (OSTI.GOV)

Enright, S; Asprinio, A; Lu, L

2014-06-01

Purpose: The purpose of this study was to compare dose distributions from film measurements to Monte Carlo generated electron treatment plans. Irradiation with electrons offers the advantages of dose uniformity in the target volume and of minimizing the dose to deeper healthy tissue. Using the Monte Carlo algorithm will improve dose accuracy in regions with heterogeneities and irregular surfaces. Methods: Dose distributions from GafChromic{sup ™} EBT3 films were compared to dose distributions from the Electron Monte Carlo algorithm in the Eclipse{sup ™} radiotherapy treatment planning system. These measurements were obtained for 6MeV, 9MeV and 12MeV electrons at two depths. Allmore » phantoms studied were imported into Eclipse by CT scan. A 1 cm thick solid water template with holes for bonelike and lung-like plugs was used. Different configurations were used with the different plugs inserted into the holes. Configurations with solid-water plugs stacked on top of one another were also used to create an irregular surface. Results: The dose distributions measured from the film agreed with those from the Electron Monte Carlo treatment plan. Accuracy of Electron Monte Carlo algorithm was also compared to that of Pencil Beam. Dose distributions from Monte Carlo had much higher pass rates than distributions from Pencil Beam when compared to the film. The pass rate for Monte Carlo was in the 80%–99% range, where the pass rate for Pencil Beam was as low as 10.76%. Conclusion: The dose distribution from Monte Carlo agreed with the measured dose from the film. When compared to the Pencil Beam algorithm, pass rates for Monte Carlo were much higher. Monte Carlo should be used over Pencil Beam for regions with heterogeneities and irregular surfaces.« less

Wang-Landau method for calculating Rényi entropies in finite-temperature quantum Monte Carlo simulations.

PubMed

Inglis, Stephen; Melko, Roger G

2013-01-01

We implement a Wang-Landau sampling technique in quantum Monte Carlo (QMC) simulations for the purpose of calculating the Rényi entanglement entropies and associated mutual information. The algorithm converges an estimate for an analog to the density of states for stochastic series expansion QMC, allowing a direct calculation of Rényi entropies without explicit thermodynamic integration. We benchmark results for the mutual information on two-dimensional (2D) isotropic and anisotropic Heisenberg models, a 2D transverse field Ising model, and a three-dimensional Heisenberg model, confirming a critical scaling of the mutual information in cases with a finite-temperature transition. We discuss the benefits and limitations of broad sampling techniques compared to standard importance sampling methods.

Simulation of Nuclear Reactor Kinetics by the Monte Carlo Method

NASA Astrophysics Data System (ADS)

Gomin, E. A.; Davidenko, V. D.; Zinchenko, A. S.; Kharchenko, I. K.

2017-12-01

The KIR computer code intended for calculations of nuclear reactor kinetics using the Monte Carlo method is described. The algorithm implemented in the code is described in detail. Some results of test calculations are given.

Monte Carlo methods for multidimensional integration for European option pricing

NASA Astrophysics Data System (ADS)

Todorov, V.; Dimov, I. T.

2016-10-01

In this paper, we illustrate examples of highly accurate Monte Carlo and quasi-Monte Carlo methods for multiple integrals related to the evaluation of European style options. The idea is that the value of the option is formulated in terms of the expectation of some random variable; then the average of independent samples of this random variable is used to estimate the value of the option. First we obtain an integral representation for the value of the option using the risk neutral valuation formula. Then with an appropriations change of the constants we obtain a multidimensional integral over the unit hypercube of the corresponding dimensionality. Then we compare a specific type of lattice rules over one of the best low discrepancy sequence of Sobol for numerical integration. Quasi-Monte Carlo methods are compared with Adaptive and Crude Monte Carlo techniques for solving the problem. The four approaches are completely different thus it is a question of interest to know which one of them outperforms the other for evaluation multidimensional integrals in finance. Some of the advantages and disadvantages of the developed algorithms are discussed.

Accuracy of Monte Carlo simulations compared to in-vivo MDCT dosimetry.

PubMed

Bostani, Maryam; Mueller, Jonathon W; McMillan, Kyle; Cody, Dianna D; Cagnon, Chris H; DeMarco, John J; McNitt-Gray, Michael F

2015-02-01

The purpose of this study was to assess the accuracy of a Monte Carlo simulation-based method for estimating radiation dose from multidetector computed tomography (MDCT) by comparing simulated doses in ten patients to in-vivo dose measurements. MD Anderson Cancer Center Institutional Review Board approved the acquisition of in-vivo rectal dose measurements in a pilot study of ten patients undergoing virtual colonoscopy. The dose measurements were obtained by affixing TLD capsules to the inner lumen of rectal catheters. Voxelized patient models were generated from the MDCT images of the ten patients, and the dose to the TLD for all exposures was estimated using Monte Carlo based simulations. The Monte Carlo simulation results were compared to the in-vivo dose measurements to determine accuracy. The calculated mean percent difference between TLD measurements and Monte Carlo simulations was -4.9% with standard deviation of 8.7% and a range of -22.7% to 5.7%. The results of this study demonstrate very good agreement between simulated and measured doses in-vivo. Taken together with previous validation efforts, this work demonstrates that the Monte Carlo simulation methods can provide accurate estimates of radiation dose in patients undergoing CT examinations.

Direct simulation Monte Carlo investigation of the Rayleigh-Taylor instability

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gallis, M. A.; Koehler, T. P.; Torczynski, J. R.

In this paper, the Rayleigh-Taylor instability (RTI) is investigated using the direct simulation Monte Carlo (DSMC) method of molecular gas dynamics. Here, fully resolved two-dimensional DSMC RTI simulations are performed to quantify the growth of flat and single-mode perturbed interfaces between two atmospheric-pressure monatomic gases as a function of the Atwood number and the gravitational acceleration. The DSMC simulations reproduce many qualitative features of the growth of the mixing layer and are in reasonable quantitative agreement with theoretical and empirical models in the linear, nonlinear, and self-similar regimes. In some of the simulations at late times, the instability enters themore » self-similar regime, in agreement with experimental observations. Finally, for the conditions simulated, diffusion can influence the initial instability growth significantly.« less

Direct simulation Monte Carlo investigation of the Rayleigh-Taylor instability

DOE PAGES

Gallis, M. A.; Koehler, T. P.; Torczynski, J. R.; ...

2016-08-31

In this paper, the Rayleigh-Taylor instability (RTI) is investigated using the direct simulation Monte Carlo (DSMC) method of molecular gas dynamics. Here, fully resolved two-dimensional DSMC RTI simulations are performed to quantify the growth of flat and single-mode perturbed interfaces between two atmospheric-pressure monatomic gases as a function of the Atwood number and the gravitational acceleration. The DSMC simulations reproduce many qualitative features of the growth of the mixing layer and are in reasonable quantitative agreement with theoretical and empirical models in the linear, nonlinear, and self-similar regimes. In some of the simulations at late times, the instability enters themore » self-similar regime, in agreement with experimental observations. Finally, for the conditions simulated, diffusion can influence the initial instability growth significantly.« less

Probabilistic learning of nonlinear dynamical systems using sequential Monte Carlo

NASA Astrophysics Data System (ADS)

Schön, Thomas B.; Svensson, Andreas; Murray, Lawrence; Lindsten, Fredrik

2018-05-01

Probabilistic modeling provides the capability to represent and manipulate uncertainty in data, models, predictions and decisions. We are concerned with the problem of learning probabilistic models of dynamical systems from measured data. Specifically, we consider learning of probabilistic nonlinear state-space models. There is no closed-form solution available for this problem, implying that we are forced to use approximations. In this tutorial we will provide a self-contained introduction to one of the state-of-the-art methods-the particle Metropolis-Hastings algorithm-which has proven to offer a practical approximation. This is a Monte Carlo based method, where the particle filter is used to guide a Markov chain Monte Carlo method through the parameter space. One of the key merits of the particle Metropolis-Hastings algorithm is that it is guaranteed to converge to the "true solution" under mild assumptions, despite being based on a particle filter with only a finite number of particles. We will also provide a motivating numerical example illustrating the method using a modeling language tailored for sequential Monte Carlo methods. The intention of modeling languages of this kind is to open up the power of sophisticated Monte Carlo methods-including particle Metropolis-Hastings-to a large group of users without requiring them to know all the underlying mathematical details.

Multilevel Monte Carlo simulation of Coulomb collisions

DOE PAGES

Rosin, M. S.; Ricketson, L. F.; Dimits, A. M.; ...

2014-05-29

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 –2) or (ε –2(lnε) 2), depending on the underlying discretization, Milstein or Euler–Maruyama respectively. This is to be contrasted with a cost of O(ε –3) for direct simulation Monte Carlomore » 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 –5. Lastly, we discuss the importance of the method for problems in which collisions constitute the computational rate limiting step, and its limitations.« less

QMCPACK : an open source ab initio quantum Monte Carlo package for the electronic structure of atoms, molecules and solids

DOE PAGES

Kim, Jeongnim; Baczewski, Andrew T.; Beaudet, Todd D.; ...

2018-04-19

QMCPACK is an open source quantum Monte Carlo package for ab-initio electronic structure calculations. It supports calculations of metallic and insulating solids, molecules, atoms, and some model Hamiltonians. Implemented real space quantum Monte Carlo algorithms include variational, diffusion, and reptation Monte Carlo. QMCPACK uses Slater-Jastrow type trial wave functions in conjunction with a sophisticated optimizer capable of optimizing tens of thousands of parameters. The orbital space auxiliary field quantum Monte Carlo method is also implemented, enabling cross validation between different highly accurate methods. The code is specifically optimized for calculations with large numbers of electrons on the latest high performancemore » computing architectures, including multicore central processing unit (CPU) and graphical processing unit (GPU) systems. We detail the program’s capabilities, outline its structure, and give examples of its use in current research calculations. The package is available at http://www.qmcpack.org.« less

QMCPACK : an open source ab initio quantum Monte Carlo package for the electronic structure of atoms, molecules and solids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Jeongnim; Baczewski, Andrew T.; Beaudet, Todd D.

QMCPACK is an open source quantum Monte Carlo package for ab-initio electronic structure calculations. It supports calculations of metallic and insulating solids, molecules, atoms, and some model Hamiltonians. Implemented real space quantum Monte Carlo algorithms include variational, diffusion, and reptation Monte Carlo. QMCPACK uses Slater-Jastrow type trial wave functions in conjunction with a sophisticated optimizer capable of optimizing tens of thousands of parameters. The orbital space auxiliary field quantum Monte Carlo method is also implemented, enabling cross validation between different highly accurate methods. The code is specifically optimized for calculations with large numbers of electrons on the latest high performancemore » computing architectures, including multicore central processing unit (CPU) and graphical processing unit (GPU) systems. We detail the program’s capabilities, outline its structure, and give examples of its use in current research calculations. The package is available at http://www.qmcpack.org.« less

Estimation of the four-wave mixing noise probability-density function by the multicanonical Monte Carlo method.

PubMed

Neokosmidis, Ioannis; Kamalakis, Thomas; Chipouras, Aristides; Sphicopoulos, Thomas

2005-01-01

The performance of high-powered wavelength-division multiplexed (WDM) optical networks can be severely degraded by four-wave-mixing- (FWM-) induced distortion. The multicanonical Monte Carlo method (MCMC) is used to calculate the probability-density function (PDF) of the decision variable of a receiver, limited by FWM noise. Compared with the conventional Monte Carlo method previously used to estimate this PDF, the MCMC method is much faster and can accurately estimate smaller error probabilities. The method takes into account the correlation between the components of the FWM noise, unlike the Gaussian model, which is shown not to provide accurate results.

Accurate quantification of fluorescent targets within turbid media based on a decoupled fluorescence Monte Carlo model.

PubMed

Deng, Yong; Luo, Zhaoyang; Jiang, Xu; Xie, Wenhao; Luo, Qingming

2015-07-01

We propose a method based on a decoupled fluorescence Monte Carlo model for constructing fluorescence Jacobians to enable accurate quantification of fluorescence targets within turbid media. The effectiveness of the proposed method is validated using two cylindrical phantoms enclosing fluorescent targets within homogeneous and heterogeneous background media. The results demonstrate that our method can recover relative concentrations of the fluorescent targets with higher accuracy than the perturbation fluorescence Monte Carlo method. This suggests that our method is suitable for quantitative fluorescence diffuse optical tomography, especially for in vivo imaging of fluorophore targets for diagnosis of different diseases and abnormalities.

On recontamination and directional-bias problems in Monte Carlo simulation of PDF turbulence models. [probability density function

NASA Technical Reports Server (NTRS)

Hsu, Andrew T.

1992-01-01

Turbulent combustion can not be simulated adequately by conventional moment closure turbulent models. The probability density function (PDF) method offers an attractive alternative: in a PDF model, the chemical source terms are closed and do not require additional models. Because the number of computational operations grows only linearly in the Monte Carlo scheme, it is chosen over finite differencing schemes. A grid dependent Monte Carlo scheme following J.Y. Chen and W. Kollmann has been studied in the present work. It was found that in order to conserve the mass fractions absolutely, one needs to add further restrictions to the scheme, namely alpha(sub j) + gamma(sub j) = alpha(sub j - 1) + gamma(sub j + 1). A new algorithm was devised that satisfied this restriction in the case of pure diffusion or uniform flow problems. Using examples, it is shown that absolute conservation can be achieved. Although for non-uniform flows absolute conservation seems impossible, the present scheme has reduced the error considerably.

Simulating complex atomistic processes: On-the-fly kinetic Monte Carlo scheme with selective active volumes

NASA Astrophysics Data System (ADS)

Xu, Haixuan; Osetsky, Yury N.; Stoller, Roger E.

2011-10-01

An accelerated atomistic kinetic Monte Carlo (KMC) approach for evolving complex atomistic structures has been developed. The method incorporates on-the-fly calculations of transition states (TSs) with a scheme for defining active volumes (AVs) in an off-lattice (relaxed) system. In contrast to conventional KMC models that require all reactions to be predetermined, this approach is self-evolving and any physically relevant motion or reaction may occur. Application of this self-evolving atomistic kinetic Monte Carlo (SEAK-MC) approach is illustrated by predicting the evolution of a complex defect configuration obtained in a molecular dynamics (MD) simulation of a displacement cascade in Fe. Over much longer times, it was shown that interstitial clusters interacting with other defects may change their structure, e.g., from glissile to sessile configuration. The direct comparison with MD modeling confirms the atomistic fidelity of the approach, while the longer time simulation demonstrates the unique capability of the model.

Molecular Simulation of the Phase Diagram of Methane Hydrate: Free Energy Calculations, Direct Coexistence Method, and Hyperparallel Tempering.

PubMed

Jin, Dongliang; Coasne, Benoit

2017-10-24

Different molecular simulation strategies are used to assess the stability of methane hydrate under various temperature and pressure conditions. First, using two water molecular models, free energy calculations consisting of the Einstein molecule approach in combination with semigrand Monte Carlo simulations are used to determine the pressure-temperature phase diagram of methane hydrate. With these calculations, we also estimate the chemical potentials of water and methane and methane occupancy at coexistence. Second, we also consider two other advanced molecular simulation techniques that allow probing the phase diagram of methane hydrate: the direct coexistence method in the Grand Canonical ensemble and the hyperparallel tempering Monte Carlo method. These two direct techniques are found to provide stability conditions that are consistent with the pressure-temperature phase diagram obtained using rigorous free energy calculations. The phase diagram obtained in this work, which is found to be consistent with previous simulation studies, is close to its experimental counterpart provided the TIP4P/Ice model is used to describe the water molecule.

A smart Monte Carlo procedure for production costing and uncertainty analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Parker, C.; Stremel, J.

1996-11-01

Electric utilities using chronological production costing models to decide whether to buy or sell power over the next week or next few weeks need to determine potential profits or losses under a number of uncertainties. A large amount of money can be at stake--often $100,000 a day or more--and one party of the sale must always take on the risk. In the case of fixed price ($/MWh) contracts, the seller accepts the risk. In the case of cost plus contracts, the buyer must accept the risk. So, modeling uncertainty and understanding the risk accurately can improve the competitive edge ofmore » the user. This paper investigates an efficient procedure for representing risks and costs from capacity outages. Typically, production costing models use an algorithm based on some form of random number generator to select resources as available or on outage. These algorithms allow experiments to be repeated and gains and losses to be observed in a short time. The authors perform several experiments to examine the capability of three unit outage selection methods and measures their results. Specifically, a brute force Monte Carlo procedure, a Monte Carlo procedure with Latin Hypercube sampling, and a Smart Monte Carlo procedure with cost stratification and directed sampling are examined.« less

[Evaluation of Organ Dose Estimation from Indices of CT Dose Using Dose Index Registry].

PubMed

Iriuchijima, Akiko; Fukushima, Yasuhiro; Ogura, Akio

Direct measurement of each patient organ dose from computed tomography (CT) is not possible. Most methods to estimate patient organ dose is using Monte Carlo simulation with dedicated software. However, dedicated software is too expensive for small scale hospitals. Not every hospital can estimate organ dose with dedicated software. The purpose of this study was to evaluate the simple method of organ dose estimation using some common indices of CT dose. The Monte Carlo simulation software Radimetrics (Bayer) was used for calculating organ dose and analysis relationship between indices of CT dose and organ dose. Multidetector CT scanners were compared with those from two manufactures (LightSpeed VCT, GE Healthcare; SOMATOM Definition Flash, Siemens Healthcare). Using stored patient data from Radimetrics, the relationships between indices of CT dose and organ dose were indicated as each formula for estimating organ dose. The accuracy of estimation method of organ dose was compared with the results of Monte Carlo simulation using the Bland-Altman plots. In the results, SSDE was the feasible index for estimation organ dose in almost organs because it reflected each patient size. The differences of organ dose between estimation and simulation were within 23%. In conclusion, our estimation method of organ dose using indices of CT dose is convenient for clinical with accuracy.

Depletion Calculations Based on Perturbations. Application to the Study of a Rep-Like Assembly at Beginning of Cycle with TRIPOLI-4®.

NASA Astrophysics Data System (ADS)

Dieudonne, Cyril; Dumonteil, Eric; Malvagi, Fausto; M'Backé Diop, Cheikh

2014-06-01

For several years, Monte Carlo burnup/depletion codes have appeared, which couple Monte Carlo codes to simulate the neutron transport to deterministic methods, which handle the medium depletion due to the neutron flux. Solving Boltzmann and Bateman equations in such a way allows to track fine 3-dimensional effects and to get rid of multi-group hypotheses done by deterministic solvers. The counterpart is the prohibitive calculation time due to the Monte Carlo solver called at each time step. In this paper we present a methodology to avoid the repetitive and time-expensive Monte Carlo simulations, and to replace them by perturbation calculations: indeed the different burnup steps may be seen as perturbations of the isotopic concentration of an initial Monte Carlo simulation. In a first time we will present this method, and provide details on the perturbative technique used, namely the correlated sampling. In a second time the implementation of this method in the TRIPOLI-4® code will be discussed, as well as the precise calculation scheme a meme to bring important speed-up of the depletion calculation. Finally, this technique will be used to calculate the depletion of a REP-like assembly, studied at beginning of its cycle. After having validated the method with a reference calculation we will show that it can speed-up by nearly an order of magnitude standard Monte-Carlo depletion codes.

DNA strand breaks induced by electrons simulated with Nanodosimetry Monte Carlo Simulation Code: NASIC.

PubMed

Li, Junli; Li, Chunyan; Qiu, Rui; Yan, Congchong; Xie, Wenzhang; Wu, Zhen; Zeng, Zhi; Tung, Chuanjong

2015-09-01

The method of Monte Carlo simulation is a powerful tool to investigate the details of radiation biological damage at the molecular level. In this paper, a Monte Carlo code called NASIC (Nanodosimetry Monte Carlo Simulation Code) was developed. It includes physical module, pre-chemical module, chemical module, geometric module and DNA damage module. The physical module can simulate physical tracks of low-energy electrons in the liquid water event-by-event. More than one set of inelastic cross sections were calculated by applying the dielectric function method of Emfietzoglou's optical-data treatments, with different optical data sets and dispersion models. In the pre-chemical module, the ionised and excited water molecules undergo dissociation processes. In the chemical module, the produced radiolytic chemical species diffuse and react. In the geometric module, an atomic model of 46 chromatin fibres in a spherical nucleus of human lymphocyte was established. In the DNA damage module, the direct damages induced by the energy depositions of the electrons and the indirect damages induced by the radiolytic chemical species were calculated. The parameters should be adjusted to make the simulation results be agreed with the experimental results. In this paper, the influence study of the inelastic cross sections and vibrational excitation reaction on the parameters and the DNA strand break yields were studied. Further work of NASIC is underway. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Teaching Ionic Solvation Structure with a Monte Carlo Liquid Simulation Program

ERIC Educational Resources Information Center

Serrano, Agostinho; Santos, Flavia M. T.; Greca, Ileana M.

2004-01-01

The use of molecular dynamics and Monte Carlo methods has provided efficient means to stimulate the behavior of molecular liquids and solutions. A Monte Carlo simulation program is used to compute the structure of liquid water and of water as a solvent to Na(super +), Cl(super -), and Ar on a personal computer to show that it is easily feasible to…

TU-H-CAMPUS-IeP1-01: Bias and Computational Efficiency of Variance Reduction Methods for the Monte Carlo Simulation of Imaging Detectors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sharma, D; Badano, A; Sempau, J

Purpose: Variance reduction techniques (VRTs) are employed in Monte Carlo simulations to obtain estimates with reduced statistical uncertainty for a given simulation time. In this work, we study the bias and efficiency of a VRT for estimating the response of imaging detectors. Methods: We implemented Directed Sampling (DS), preferentially directing a fraction of emitted optical photons directly towards the detector by altering the isotropic model. The weight of each optical photon is appropriately modified to maintain simulation estimates unbiased. We use a Monte Carlo tool called fastDETECT2 (part of the hybridMANTIS open-source package) for optical transport, modified for VRT. Themore » weight of each photon is calculated as the ratio of original probability (no VRT) and the new probability for a particular direction. For our analysis of bias and efficiency, we use pulse height spectra, point response functions, and Swank factors. We obtain results for a variety of cases including analog (no VRT, isotropic distribution), and DS with 0.2 and 0.8 optical photons directed towards the sensor plane. We used 10,000, 25-keV primaries. Results: The Swank factor for all cases in our simplified model converged fast (within the first 100 primaries) to a stable value of 0.9. The root mean square error per pixel for DS VRT for the point response function between analog and VRT cases was approximately 5e-4. Conclusion: Our preliminary results suggest that DS VRT does not affect the estimate of the mean for the Swank factor. Our findings indicate that it may be possible to design VRTs for imaging detector simulations to increase computational efficiency without introducing bias.« less

Baseball Monte Carlo Style.

ERIC Educational Resources Information Center

Houser, Larry L.

1981-01-01

Monte Carlo methods are used to simulate activities in baseball such as a team's "hot streak" and a hitter's "batting slump." Student participation in such simulations is viewed as a useful method of giving pupils a better understanding of the probability concepts involved. (MP)

Accelerate quasi Monte Carlo method for solving systems of linear algebraic equations through shared memory

NASA Astrophysics Data System (ADS)

Lai, Siyan; Xu, Ying; Shao, Bo; Guo, Menghan; Lin, Xiaola

2017-04-01

In this paper we study on Monte Carlo method for solving systems of linear algebraic equations (SLAE) based on shared memory. Former research demostrated that GPU can effectively speed up the computations of this issue. Our purpose is to optimize Monte Carlo method simulation on GPUmemoryachritecture specifically. Random numbers are organized to storein shared memory, which aims to accelerate the parallel algorithm. Bank conflicts can be avoided by our Collaborative Thread Arrays(CTA)scheme. The results of experiments show that the shared memory based strategy can speed up the computaions over than 3X at most.

Harnessing graphical structure in Markov chain Monte Carlo learning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stolorz, P.E.; Chew P.C.

1996-12-31

The Monte Carlo method is recognized as a useful tool in learning and probabilistic inference methods common to many datamining problems. Generalized Hidden Markov Models and Bayes nets are especially popular applications. However, the presence of multiple modes in many relevant integrands and summands often renders the method slow and cumbersome. Recent mean field alternatives designed to speed things up have been inspired by experience gleaned from physics. The current work adopts an approach very similar to this in spirit, but focusses instead upon dynamic programming notions as a basis for producing systematic Monte Carlo improvements. The idea is tomore » approximate a given model by a dynamic programming-style decomposition, which then forms a scaffold upon which to build successively more accurate Monte Carlo approximations. Dynamic programming ideas alone fail to account for non-local structure, while standard Monte Carlo methods essentially ignore all structure. However, suitably-crafted hybrids can successfully exploit the strengths of each method, resulting in algorithms that combine speed with accuracy. The approach relies on the presence of significant {open_quotes}local{close_quotes} information in the problem at hand. This turns out to be a plausible assumption for many important applications. Example calculations are presented, and the overall strengths and weaknesses of the approach are discussed.« less

Poster — Thur Eve — 45: Comparison of different Monte Carlo methods of scoring linear energy transfer in modulated proton therapy beams

DOE Office of Scientific and Technical Information (OSTI.GOV)

Granville, DA; Sawakuchi, GO

2014-08-15

In this work, we demonstrate inconsistencies in commonly used Monte Carlo methods of scoring linear energy transfer (LET) in proton therapy beams. In particle therapy beams, the LET is an important parameter because the relative biological effectiveness (RBE) depends on it. LET is often determined using Monte Carlo techniques. We used a realistic Monte Carlo model of a proton therapy nozzle to score proton LET in spread-out Bragg peak (SOBP) depth-dose distributions. We used three different scoring and calculation techniques to determine average LET at varying depths within a 140 MeV beam with a 4 cm SOBP and a 250more » MeV beam with a 10 cm SOBP. These techniques included fluence-weighted (Φ-LET) and dose-weighted average (D-LET) LET calculations from: 1) scored energy spectra converted to LET spectra through a lookup table, 2) directly scored LET spectra and 3) accumulated LET scored ‘on-the-fly’ during simulations. All protons (primary and secondary) were included in the scoring. Φ-LET was found to be less sensitive to changes in scoring technique than D-LET. In addition, the spectral scoring methods were sensitive to low-energy (high-LET) cutoff values in the averaging. Using cutoff parameters chosen carefully for consistency between techniques, we found variations in Φ-LET values of up to 1.6% and variations in D-LET values of up to 11.2% for the same irradiation conditions, depending on the method used to score LET. Variations were largest near the end of the SOBP, where the LET and energy spectra are broader.« less

Adjoint Fokker-Planck equation and runaway electron dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Chang; Brennan, Dylan P.; Bhattacharjee, Amitava

2016-01-15

The adjoint Fokker-Planck equation method is applied to study the runaway probability function and the expected slowing-down time for highly relativistic runaway electrons, including the loss of energy due to synchrotron radiation. In direct correspondence to Monte Carlo simulation methods, the runaway probability function has a smooth transition across the runaway separatrix, which can be attributed to effect of the pitch angle scattering term in the kinetic equation. However, for the same numerical accuracy, the adjoint method is more efficient than the Monte Carlo method. The expected slowing-down time gives a novel method to estimate the runaway current decay timemore » in experiments. A new result from this work is that the decay rate of high energy electrons is very slow when E is close to the critical electric field. This effect contributes further to a hysteresis previously found in the runaway electron population.« less

Multi-fidelity methods for uncertainty quantification in transport problems

NASA Astrophysics Data System (ADS)

Tartakovsky, G.; Yang, X.; Tartakovsky, A. M.; Barajas-Solano, D. A.; Scheibe, T. D.; Dai, H.; Chen, X.

2016-12-01

We compare several multi-fidelity approaches for uncertainty quantification in flow and transport simulations that have a lower computational cost than the standard Monte Carlo method. The cost reduction is achieved by combining a small number of high-resolution (high-fidelity) simulations with a large number of low-resolution (low-fidelity) simulations. We propose a new method, a re-scaled Multi Level Monte Carlo (rMLMC) method. The rMLMC is based on the idea that the statistics of quantities of interest depends on scale/resolution. We compare rMLMC with existing multi-fidelity methods such as Multi Level Monte Carlo (MLMC) and reduced basis methods and discuss advantages of each approach.

High-Throughput Computation and the Applicability of Monte Carlo Integration in Fatigue Load Estimation of Floating Offshore Wind Turbines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Graf, Peter A.; Stewart, Gordon; Lackner, Matthew

Long-term fatigue loads for floating offshore wind turbines are hard to estimate because they require the evaluation of the integral of a highly nonlinear function over a wide variety of wind and wave conditions. Current design standards involve scanning over a uniform rectangular grid of metocean inputs (e.g., wind speed and direction and wave height and period), which becomes intractable in high dimensions as the number of required evaluations grows exponentially with dimension. Monte Carlo integration offers a potentially efficient alternative because it has theoretical convergence proportional to the inverse of the square root of the number of samples, whichmore » is independent of dimension. In this paper, we first report on the integration of the aeroelastic code FAST into NREL's systems engineering tool, WISDEM, and the development of a high-throughput pipeline capable of sampling from arbitrary distributions, running FAST on a large scale, and postprocessing the results into estimates of fatigue loads. Second, we use this tool to run a variety of studies aimed at comparing grid-based and Monte Carlo-based approaches with calculating long-term fatigue loads. We observe that for more than a few dimensions, the Monte Carlo approach can represent a large improvement in computational efficiency, but that as nonlinearity increases, the effectiveness of Monte Carlo is correspondingly reduced. The present work sets the stage for future research focusing on using advanced statistical methods for analysis of wind turbine fatigue as well as extreme loads.« less

Self-Learning Monte Carlo Method

NASA Astrophysics Data System (ADS)

Liu, Junwei; Qi, Yang; Meng, Zi Yang; Fu, Liang

Monte Carlo simulation is an unbiased numerical tool for studying classical and quantum many-body systems. One of its bottlenecks is the lack of general and efficient update algorithm for large size systems close to phase transition or with strong frustrations, for which local updates perform badly. In this work, we propose a new general-purpose Monte Carlo method, dubbed self-learning Monte Carlo (SLMC), in which an efficient update algorithm is first learned from the training data generated in trial simulations and then used to speed up the actual simulation. We demonstrate the efficiency of SLMC in a spin model at the phase transition point, achieving a 10-20 times speedup. This work is supported by the DOE Office of Basic Energy Sciences, Division of Materials Sciences and Engineering under Award DE-SC0010526.

Fixed forced detection for fast SPECT Monte-Carlo simulation

NASA Astrophysics Data System (ADS)

Cajgfinger, T.; Rit, S.; Létang, J. M.; Halty, A.; Sarrut, D.

2018-03-01

Monte-Carlo simulations of SPECT images are notoriously slow to converge due to the large ratio between the number of photons emitted and detected in the collimator. This work proposes a method to accelerate the simulations based on fixed forced detection (FFD) combined with an analytical response of the detector. FFD is based on a Monte-Carlo simulation but forces the detection of a photon in each detector pixel weighted by the probability of emission (or scattering) and transmission to this pixel. The method was evaluated with numerical phantoms and on patient images. We obtained differences with analog Monte Carlo lower than the statistical uncertainty. The overall computing time gain can reach up to five orders of magnitude. Source code and examples are available in the Gate V8.0 release.

Fixed forced detection for fast SPECT Monte-Carlo simulation.

PubMed

Cajgfinger, T; Rit, S; Létang, J M; Halty, A; Sarrut, D

2018-03-02

Monte-Carlo simulations of SPECT images are notoriously slow to converge due to the large ratio between the number of photons emitted and detected in the collimator. This work proposes a method to accelerate the simulations based on fixed forced detection (FFD) combined with an analytical response of the detector. FFD is based on a Monte-Carlo simulation but forces the detection of a photon in each detector pixel weighted by the probability of emission (or scattering) and transmission to this pixel. The method was evaluated with numerical phantoms and on patient images. We obtained differences with analog Monte Carlo lower than the statistical uncertainty. The overall computing time gain can reach up to five orders of magnitude. Source code and examples are available in the Gate V8.0 release.

Off-diagonal expansion quantum Monte Carlo

NASA Astrophysics Data System (ADS)

Albash, Tameem; Wagenbreth, Gene; Hen, Itay

2017-12-01

We propose a Monte Carlo algorithm designed to simulate quantum as well as classical systems at equilibrium, bridging the algorithmic gap between quantum and classical thermal simulation algorithms. The method is based on a decomposition of the quantum partition function that can be viewed as a series expansion about its classical part. We argue that the algorithm not only provides a theoretical advancement in the field of quantum Monte Carlo simulations, but is optimally suited to tackle quantum many-body systems that exhibit a range of behaviors from "fully quantum" to "fully classical," in contrast to many existing methods. We demonstrate the advantages, sometimes by orders of magnitude, of the technique by comparing it against existing state-of-the-art schemes such as path integral quantum Monte Carlo and stochastic series expansion. We also illustrate how our method allows for the unification of quantum and classical thermal parallel tempering techniques into a single algorithm and discuss its practical significance.

Light propagation along the pericardium meridian at human wrist as evidenced by the optical experiment and Monte Carlo method.

PubMed

Jiang, Yi-fan; Chen, Chang-shui; Liu, Xiao-mei; Liu, Rong-ting; Liu, Song-hao

2015-04-01

To explore the characteristics of light propagation along the Pericardium Meridian and its surrounding areas at human wrist by using optical experiment and Monte Carlo method. An experiment was carried out to obtain the distribution of diffuse light on Pericardium Meridian line and its surrounding areas at the wrist, and then a simplified model based on the anatomical structure was proposed to simulate the light transportation within the same area by using Monte Carlo method. The experimental results showed strong accordance with the Monte Carlo simulation that the light propagation along the Pericardium Meridian had an advantage over its surrounding areas at the wrist. The advantage of light transport along Pericardium Merdian line was related to components and structure of tissue, also the anatomical structure of the area that the Pericardium Meridian line runs.

Optimised Iteration in Coupled Monte Carlo - Thermal-Hydraulics Calculations

NASA Astrophysics Data System (ADS)

Hoogenboom, J. Eduard; Dufek, Jan

2014-06-01

This paper describes an optimised iteration scheme for the number of neutron histories and the relaxation factor in successive iterations of coupled Monte Carlo and thermal-hydraulic reactor calculations based on the stochastic iteration method. The scheme results in an increasing number of neutron histories for the Monte Carlo calculation in successive iteration steps and a decreasing relaxation factor for the spatial power distribution to be used as input to the thermal-hydraulics calculation. The theoretical basis is discussed in detail and practical consequences of the scheme are shown, among which a nearly linear increase per iteration of the number of cycles in the Monte Carlo calculation. The scheme is demonstrated for a full PWR type fuel assembly. Results are shown for the axial power distribution during several iteration steps. A few alternative iteration method are also tested and it is concluded that the presented iteration method is near optimal.

Geometry and Dynamics for Markov Chain Monte Carlo

NASA Astrophysics Data System (ADS)

Barp, Alessandro; Briol, François-Xavier; Kennedy, Anthony D.; Girolami, Mark

2018-03-01

Markov Chain Monte Carlo methods have revolutionised mathematical computation and enabled statistical inference within many previously intractable models. In this context, Hamiltonian dynamics have been proposed as an efficient way of building chains which can explore probability densities efficiently. The method emerges from physics and geometry and these links have been extensively studied by a series of authors through the last thirty years. However, there is currently a gap between the intuitions and knowledge of users of the methodology and our deep understanding of these theoretical foundations. The aim of this review is to provide a comprehensive introduction to the geometric tools used in Hamiltonian Monte Carlo at a level accessible to statisticians, machine learners and other users of the methodology with only a basic understanding of Monte Carlo methods. This will be complemented with some discussion of the most recent advances in the field which we believe will become increasingly relevant to applied scientists.

Off-diagonal expansion quantum Monte Carlo.

PubMed

Albash, Tameem; Wagenbreth, Gene; Hen, Itay

2017-12-01

We propose a Monte Carlo algorithm designed to simulate quantum as well as classical systems at equilibrium, bridging the algorithmic gap between quantum and classical thermal simulation algorithms. The method is based on a decomposition of the quantum partition function that can be viewed as a series expansion about its classical part. We argue that the algorithm not only provides a theoretical advancement in the field of quantum Monte Carlo simulations, but is optimally suited to tackle quantum many-body systems that exhibit a range of behaviors from "fully quantum" to "fully classical," in contrast to many existing methods. We demonstrate the advantages, sometimes by orders of magnitude, of the technique by comparing it against existing state-of-the-art schemes such as path integral quantum Monte Carlo and stochastic series expansion. We also illustrate how our method allows for the unification of quantum and classical thermal parallel tempering techniques into a single algorithm and discuss its practical significance.

How Monte Carlo heuristics aid to identify the physical processes of drug release kinetics.

PubMed

Lecca, Paola

2018-01-01

We implement a Monte Carlo heuristic algorithm to model drug release from a solid dosage form. We show that with Monte Carlo simulations it is possible to identify and explain the causes of the unsatisfactory predictive power of current drug release models. It is well known that the power-law, the exponential models, as well as those derived from or inspired by them accurately reproduce only the first 60% of the release curve of a drug from a dosage form. In this study, by using Monte Carlo simulation approaches, we show that these models fit quite accurately almost the entire release profile when the release kinetics is not governed by the coexistence of different physico-chemical mechanisms. We show that the accuracy of the traditional models are comparable with those of Monte Carlo heuristics when these heuristics approximate and oversimply the phenomenology of drug release. This observation suggests to develop and use novel Monte Carlo simulation heuristics able to describe the complexity of the release kinetics, and consequently to generate data more similar to those observed in real experiments. Implementing Monte Carlo simulation heuristics of the drug release phenomenology may be much straightforward and efficient than hypothesizing and implementing from scratch complex mathematical models of the physical processes involved in drug release. Identifying and understanding through simulation heuristics what processes of this phenomenology reproduce the observed data and then formalize them in mathematics may allow avoiding time-consuming, trial-error based regression procedures. Three bullet points, highlighting the customization of the procedure. •An efficient heuristics based on Monte Carlo methods for simulating drug release from solid dosage form encodes is presented. It specifies the model of the physical process in a simple but accurate way in the formula of the Monte Carlo Micro Step (MCS) time interval.•Given the experimentally observed curve of drug release, we point out how Monte Carlo heuristics can be integrated in an evolutionary algorithmic approach to infer the mode of MCS best fitting the observed data, and thus the observed release kinetics.•The software implementing the method is written in R language, the free most used language in the bioinformaticians community.

SU-F-T-619: Dose Evaluation of Specific Patient Plans Based On Monte Carlo Algorithm for a CyberKnife Stereotactic Radiosurgery System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Piao, J; PLA 302 Hospital, Beijing; Xu, S

2016-06-15

Purpose: This study will use Monte Carlo to simulate the Cyberknife system, and intend to develop the third-party tool to evaluate the dose verification of specific patient plans in TPS. Methods: By simulating the treatment head using the BEAMnrc and DOSXYZnrc software, the comparison between the calculated and measured data will be done to determine the beam parameters. The dose distribution calculated in the Raytracing, Monte Carlo algorithms of TPS (Multiplan Ver4.0.2) and in-house Monte Carlo simulation method for 30 patient plans, which included 10 head, lung and liver cases in each, were analyzed. The γ analysis with the combinedmore » 3mm/3% criteria would be introduced to quantitatively evaluate the difference of the accuracy between three algorithms. Results: More than 90% of the global error points were less than 2% for the comparison of the PDD and OAR curves after determining the mean energy and FWHM.The relative ideal Monte Carlo beam model had been established. Based on the quantitative evaluation of dose accuracy for three algorithms, the results of γ analysis shows that the passing rates (84.88±9.67% for head,98.83±1.05% for liver,98.26±1.87% for lung) of PTV in 30 plans between Monte Carlo simulation and TPS Monte Carlo algorithms were good. And the passing rates (95.93±3.12%,99.84±0.33% in each) of PTV in head and liver plans between Monte Carlo simulation and TPS Ray-tracing algorithms were also good. But the difference of DVHs in lung plans between Monte Carlo simulation and Ray-tracing algorithms was obvious, and the passing rate (51.263±38.964%) of γ criteria was not good. It is feasible that Monte Carlo simulation was used for verifying the dose distribution of patient plans. Conclusion: Monte Carlo simulation algorithm developed in the CyberKnife system of this study can be used as a reference tool for the third-party tool, which plays an important role in dose verification of patient plans. This work was supported in part by the grant from Chinese Natural Science Foundation (Grant No. 11275105). Thanks for the support from Accuray Corp.« less

Low-Density Nozzle Flow by the Direct Simulation Monte Carlo and Continuum Methods

NASA Technical Reports Server (NTRS)

Chung, Chang-Hong; Kim, Sku C.; Stubbs, Robert M.; Dewitt, Kenneth J.

1994-01-01

Two different approaches, the direct simulation Monte Carlo (DSMC) method based on molecular gasdynamics, and a finite-volume approximation of the Navier-Stokes equations, which are based on continuum gasdynamics, are employed in the analysis of a low-density gas flow in a small converging-diverging nozzle. The fluid experiences various kinds of flow regimes including continuum, slip, transition, and free-molecular. Results from the two numerical methods are compared with Rothe's experimental data, in which density and rotational temperature variations along the centerline and at various locations inside a low-density nozzle were measured by the electron-beam fluorescence technique. The continuum approach showed good agreement with the experimental data as far as density is concerned. The results from the DSMC method showed good agreement with the experimental data, both in the density and the rotational temperature. It is also shown that the simulation parameters, such as the gas/surface interaction model, the energy exchange model between rotational and translational modes, and the viscosity-temperature exponent, have substantial effects on the results of the DSMC method.

Verification and Validation of Monte Carlo N-Particle 6 for Computing Gamma Protection Factors

DTIC Science & Technology

2015-03-26

methods for evaluating RPFs, which it used for the subsequent 30 years. These approaches included computational modeling, radioisotopes , and a high...1.2.1. Past Methods of Experimental Evaluation ........................................................ 2 1.2.2. Modeling Efforts...Other Considerations ......................................................................................... 14 2.4. Monte Carlo Methods

An improved target velocity sampling algorithm for free gas elastic scattering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Romano, Paul K.; Walsh, Jonathan A.

We present an improved algorithm for sampling the target velocity when simulating elastic scattering in a Monte Carlo neutron transport code that correctly accounts for the energy dependence of the scattering cross section. The algorithm samples the relative velocity directly, thereby avoiding a potentially inefficient rejection step based on the ratio of cross sections. Here, we have shown that this algorithm requires only one rejection step, whereas other methods of similar accuracy require two rejection steps. The method was verified against stochastic and deterministic reference results for upscattering percentages in 238U. Simulations of a light water reactor pin cell problemmore » demonstrate that using this algorithm results in a 3% or less penalty in performance when compared with an approximate method that is used in most production Monte Carlo codes« less

An improved target velocity sampling algorithm for free gas elastic scattering

DOE PAGES

Romano, Paul K.; Walsh, Jonathan A.

2018-02-03

We present an improved algorithm for sampling the target velocity when simulating elastic scattering in a Monte Carlo neutron transport code that correctly accounts for the energy dependence of the scattering cross section. The algorithm samples the relative velocity directly, thereby avoiding a potentially inefficient rejection step based on the ratio of cross sections. Here, we have shown that this algorithm requires only one rejection step, whereas other methods of similar accuracy require two rejection steps. The method was verified against stochastic and deterministic reference results for upscattering percentages in 238U. Simulations of a light water reactor pin cell problemmore » demonstrate that using this algorithm results in a 3% or less penalty in performance when compared with an approximate method that is used in most production Monte Carlo codes« less

Time-dependent integral equations of neutron transport for calculating the kinetics of nuclear reactors by the Monte Carlo method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Davidenko, V. D., E-mail: Davidenko-VD@nrcki.ru; Zinchenko, A. S., E-mail: zin-sn@mail.ru; Harchenko, I. K.

2016-12-15

Integral equations for the shape functions in the adiabatic, quasi-static, and improved quasi-static approximations are presented. The approach to solving these equations by the Monte Carlo method is described.

MR Imaging Based Treatment Planning for Radiotherapy of Prostate Cancer

DTIC Science & Technology

2007-02-01

developed practical methods for heterogeneity correction for MRI - based dose calculations (Chen et al 2007). 6) We will use existing Monte Carlo ... Monte Carlo verification of IMRT dose distributions from a commercial treatment planning optimization system, Phys. Med. Biol., 45:2483-95 (2000) Ma...accuracy and consistency for MR based IMRT treatment planning for prostate cancer. A short paper entitled “ Monte Carlo dose verification of MR image based

Monte Carlo: in the beginning and some great expectations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Metropolis, N.

1985-01-01

The central theme will be on the historical setting and origins of the Monte Carlo Method. The scene was post-war Los Alamos Scientific Laboratory. There was an inevitability about the Monte Carlo Event: the ENIAC had recently enjoyed its meteoric rise (on a classified Los Alamos problem); Stan Ulam had returned to Los Alamos; John von Neumann was a frequent visitor. Techniques, algorithms, and applications developed rapidly at Los Alamos. Soon, the fascination of the Method reached wider horizons. The first paper was submitted for publication in the spring of 1949. In the summer of 1949, the first open conferencemore » was held at the University of California at Los Angeles. Of some interst perhaps is an account of Fermi's earlier, independent application in neutron moderation studies while at the University of Rome. The quantum leap expected with the advent of massively parallel processors will provide stimuli for very ambitious applications of the Monte Carlo Method in disciplines ranging from field theories to cosmology, including more realistic models in the neurosciences. A structure of multi-instruction sets for parallel processing is ideally suited for the Monte Carlo approach. One may even hope for a modest hardening of the soft sciences.« less

Petit and grand ensemble Monte Carlo calculations of the thermodynamics of the lattice gas

DOE Office of Scientific and Technical Information (OSTI.GOV)

Murch, G.E.; Thorn, R.J.

1978-11-01

A direct Monte Carlo method for estimating the chemical potential in the petit canonical ensemble was applied to the simple cubic Ising-like lattice gas. The method is based on a simple relationship between the chemical potential and the potential energy distribution in a lattice gas at equilibrium as derived independently by Widom, and Jackson and Klein. Results are presented here for the chemical potential at various compositions and temperatures above and below the zero field ferromagnetic and antiferromagnetic critical points. The same lattice gas model was reconstructed in the form of a restricted grand canonical ensemble and results at severalmore » temperatures were compared with those from the petit canonical ensemble. The agreement was excellent in these cases.« less

The Development and Comparison of Molecular Dynamics Simulation and Monte Carlo Simulation

NASA Astrophysics Data System (ADS)

Chen, Jundong

2018-03-01

Molecular dynamics is an integrated technology that combines physics, mathematics and chemistry. Molecular dynamics method is a computer simulation experimental method, which is a powerful tool for studying condensed matter system. This technique not only can get the trajectory of the atom, but can also observe the microscopic details of the atomic motion. By studying the numerical integration algorithm in molecular dynamics simulation, we can not only analyze the microstructure, the motion of particles and the image of macroscopic relationship between them and the material, but can also study the relationship between the interaction and the macroscopic properties more conveniently. The Monte Carlo Simulation, similar to the molecular dynamics, is a tool for studying the micro-molecular and particle nature. In this paper, the theoretical background of computer numerical simulation is introduced, and the specific methods of numerical integration are summarized, including Verlet method, Leap-frog method and Velocity Verlet method. At the same time, the method and principle of Monte Carlo Simulation are introduced. Finally, similarities and differences of Monte Carlo Simulation and the molecular dynamics simulation are discussed.

Adaptive Stress Testing of Airborne Collision Avoidance Systems

NASA Technical Reports Server (NTRS)

Lee, Ritchie; Kochenderfer, Mykel J.; Mengshoel, Ole J.; Brat, Guillaume P.; Owen, Michael P.

2015-01-01

This paper presents a scalable method to efficiently search for the most likely state trajectory leading to an event given only a simulator of a system. Our approach uses a reinforcement learning formulation and solves it using Monte Carlo Tree Search (MCTS). The approach places very few requirements on the underlying system, requiring only that the simulator provide some basic controls, the ability to evaluate certain conditions, and a mechanism to control the stochasticity in the system. Access to the system state is not required, allowing the method to support systems with hidden state. The method is applied to stress test a prototype aircraft collision avoidance system to identify trajectories that are likely to lead to near mid-air collisions. We present results for both single and multi-threat encounters and discuss their relevance. Compared with direct Monte Carlo search, this MCTS method performs significantly better both in finding events and in maximizing their likelihood.

Backward and forward Monte Carlo method for vector radiative transfer in a two-dimensional graded index medium

NASA Astrophysics Data System (ADS)

Qian, Lin-Feng; Shi, Guo-Dong; Huang, Yong; Xing, Yu-Ming

2017-10-01

In vector radiative transfer, backward ray tracing is seldom used. We present a backward and forward Monte Carlo method to simulate vector radiative transfer in a two-dimensional graded index medium, which is new and different from the conventional Monte Carlo method. The backward and forward Monte Carlo method involves dividing the ray tracing into two processes backward tracing and forward tracing. In multidimensional graded index media, the trajectory of a ray is usually a three-dimensional curve. During the transport of a polarization ellipse, the curved ray trajectory will induce geometrical effects and cause Stokes parameters to continuously change. The solution processes for a non-scattering medium and an anisotropic scattering medium are analysed. We also analyse some parameters that influence the Stokes vector in two-dimensional graded index media. The research shows that the Q component of the Stokes vector cannot be ignored. However, the U and V components of the Stokes vector are very small.

Applying Quantum Monte Carlo to the Electronic Structure Problem

NASA Astrophysics Data System (ADS)

Powell, Andrew D.; Dawes, Richard

2016-06-01

Two distinct types of Quantum Monte Carlo (QMC) calculations are applied to electronic structure problems such as calculating potential energy curves and producing benchmark values for reaction barriers. First, Variational and Diffusion Monte Carlo (VMC and DMC) methods using a trial wavefunction subject to the fixed node approximation were tested using the CASINO code.[1] Next, Full Configuration Interaction Quantum Monte Carlo (FCIQMC), along with its initiator extension (i-FCIQMC) were tested using the NECI code.[2] FCIQMC seeks the FCI energy for a specific basis set. At a reduced cost, the efficient i-FCIQMC method can be applied to systems in which the standard FCIQMC approach proves to be too costly. Since all of these methods are statistical approaches, uncertainties (error-bars) are introduced for each calculated energy. This study tests the performance of the methods relative to traditional quantum chemistry for some benchmark systems. References: [1] R. J. Needs et al., J. Phys.: Condensed Matter 22, 023201 (2010). [2] G. H. Booth et al., J. Chem. Phys. 131, 054106 (2009).

Dynamic Monte Carlo description of thermal desorption processes

NASA Astrophysics Data System (ADS)

Weinketz, Sieghard

1994-07-01

The applicability of the dynamic Monte Carlo method of Fichthorn and Weinberg, in which the time evolution of a system is described in terms of the absolute number of different microscopic possible events and their associated transition rates, is discussed for the case of thermal desorption simulations. It is shown that the definition of the time increment at each successful event leads naturally to the macroscopic differential equation of desorption, in the case of simple first- and second-order processes in which the only possible events are desorption and diffusion. This equivalence is numerically demonstrated for a second-order case. In the sequence, the equivalence of this method with the Monte Carlo method of Sales and Zgrablich for more complex desorption processes, allowing for lateral interactions between adsorbates, is shown, even though the dynamic Monte Carlo method does not bear their limitation of a rapid surface diffusion condition, thus being able to describe a more complex ``kinetics'' of surface reactive processes, and therefore be applied to a wider class of phenomena, such as surface catalysis.

Transforming high-dimensional potential energy surfaces into sum-of-products form using Monte Carlo methods

NASA Astrophysics Data System (ADS)

Schröder, Markus; Meyer, Hans-Dieter

2017-08-01

We propose a Monte Carlo method, "Monte Carlo Potfit," for transforming high-dimensional potential energy surfaces evaluated on discrete grid points into a sum-of-products form, more precisely into a Tucker form. To this end we use a variational ansatz in which we replace numerically exact integrals with Monte Carlo integrals. This largely reduces the numerical cost by avoiding the evaluation of the potential on all grid points and allows a treatment of surfaces up to 15-18 degrees of freedom. We furthermore show that the error made with this ansatz can be controlled and vanishes in certain limits. We present calculations on the potential of HFCO to demonstrate the features of the algorithm. To demonstrate the power of the method, we transformed a 15D potential of the protonated water dimer (Zundel cation) in a sum-of-products form and calculated the ground and lowest 26 vibrationally excited states of the Zundel cation with the multi-configuration time-dependent Hartree method.

Multilevel sequential Monte Carlo samplers

DOE PAGES

Beskos, Alexandros; Jasra, Ajay; Law, Kody; ...

2016-08-24

Here, we study the approximation of expectations w.r.t. probability distributions associated to the solution of partial differential equations (PDEs); this scenario appears routinely in Bayesian inverse problems. In practice, one often has to solve the associated PDE numerically, using, for instance finite element methods and leading to a discretisation bias, with the step-size level h L. In addition, the expectation cannot be computed analytically and one often resorts to Monte Carlo methods. In the context of this problem, it is known that the introduction of the multilevel Monte Carlo (MLMC) method can reduce the amount of computational effort to estimate expectations, for a given level of error. This is achieved via a telescoping identity associated to a Monte Carlo approximation of a sequence of probability distributions with discretisation levelsmore » $${\\infty}$$ >h 0>h 1 ...>h L. In many practical problems of interest, one cannot achieve an i.i.d. sampling of the associated sequence of probability distributions. A sequential Monte Carlo (SMC) version of the MLMC method is introduced to deal with this problem. In conclusion, it is shown that under appropriate assumptions, the attractive property of a reduction of the amount of computational effort to estimate expectations, for a given level of error, can be maintained within the SMC context.« less

Multiple-time-stepping generalized hybrid Monte Carlo methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Escribano, Bruno, E-mail: bescribano@bcamath.org; Akhmatskaya, Elena; IKERBASQUE, Basque Foundation for Science, E-48013 Bilbao

2015-01-01

Performance of the generalized shadow hybrid Monte Carlo (GSHMC) method [1], which proved to be superior in sampling efficiency over its predecessors [2–4], molecular dynamics and hybrid Monte Carlo, can be further improved by combining it with multi-time-stepping (MTS) and mollification of slow forces. We demonstrate that the comparatively simple modifications of the method not only lead to better performance of GSHMC itself but also allow for beating the best performed methods, which use the similar force splitting schemes. In addition we show that the same ideas can be successfully applied to the conventional generalized hybrid Monte Carlo method (GHMC).more » The resulting methods, MTS-GHMC and MTS-GSHMC, provide accurate reproduction of thermodynamic and dynamical properties, exact temperature control during simulation and computational robustness and efficiency. MTS-GHMC uses a generalized momentum update to achieve weak stochastic stabilization to the molecular dynamics (MD) integrator. MTS-GSHMC adds the use of a shadow (modified) Hamiltonian to filter the MD trajectories in the HMC scheme. We introduce a new shadow Hamiltonian formulation adapted to force-splitting methods. The use of such Hamiltonians improves the acceptance rate of trajectories and has a strong impact on the sampling efficiency of the method. Both methods were implemented in the open-source MD package ProtoMol and were tested on a water and a protein systems. Results were compared to those obtained using a Langevin Molly (LM) method [5] on the same systems. The test results demonstrate the superiority of the new methods over LM in terms of stability, accuracy and sampling efficiency. This suggests that putting the MTS approach in the framework of hybrid Monte Carlo and using the natural stochasticity offered by the generalized hybrid Monte Carlo lead to improving stability of MTS and allow for achieving larger step sizes in the simulation of complex systems.« less

SU-G-201-06: Directional Low-Dose Rate Brachytherapy: Determination of the TG-43 Dose-Rate Constant Analog for a New Pd-103 Source

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aima, M; Culberson, W; Hammer, C

Purpose: The aim of this work is to determine the TG-43 dose-rate constant analog for a new directional low-dose rate brachytherapy source based on experimental methods and comparison to Monte Carlo simulations. The CivaSheet™ is a new commercially available planar source array comprised of a variable number of discrete directional source elements called “CivaDots”. Given the directional nature and non-conventional design of the source, modifications to the AAPM TG-43 protocol for dosimetry are required. As a result, various parameters of the TG-43 dosimetric formalism have to be adapted to accommodate this source. This work focuses on the dose-rate constant analogmore » determination for a CivaDot. Methods: Dose to water measurements of the CivaDot were performed in a polymethyl methacrylate phantom (20×20×12 cm{sup 3}) using thermoluminescent dosimeters (TLDs) and Gafchromic EBT3 film. The source was placed in the center of the phantom, and nine TLD micro-cubes were irradiated along its central axis at a distance of 1 cm. For the film measurements, the TLDs were substituted by a (3×3) cm{sup 2} EBT3 film. Primary air-kerma strength measurements of the source were performed using a variable-aperture free-air chamber. Finally, the source was modeled using the Monte Carlo N-Particle Transport Code 6. Results: Dose-rate constant analog observed for a total of eight CivaDots using TLDs and five CivaDots using EBT3 film was within ±7.0% and ±2.9% of the Monte Carlo predicted value respectively. The average difference observed was −4.8% and −0.1% with a standard deviation of 1.7% and 2.1% for the TLD and the film measurements respectively, which are both within the comparison uncertainty. Conclusion: A preliminary investigation to determine the doserate constant analog for a CivaDot was conducted successfully with good agreement between experimental and Monte Carlo based methods. This work will aid in the eventual realization of a clinically-viable dosimetric framework for the CivaSheet. This work was partially supported by NCI contract (HHSN261201200052C) through CivaTech Oncology Inc.« less

Monte Carlo modelling the dosimetric effects of electrode material on diamond detectors.

PubMed

Baluti, Florentina; Deloar, Hossain M; Lansley, Stuart P; Meyer, Juergen

2015-03-01

Diamond detectors for radiation dosimetry were modelled using the EGSnrc Monte Carlo code to investigate the influence of electrode material and detector orientation on the absorbed dose. The small dimensions of the electrode/diamond/electrode detector structure required very thin voxels and the use of non-standard DOSXYZnrc Monte Carlo model parameters. The interface phenomena was investigated by simulating a 6 MV beam and detectors with different electrode materials, namely Al, Ag, Cu and Au, with thickens of 0.1 µm for the electrodes and 0.1 mm for the diamond, in both perpendicular and parallel detector orientation with regards to the incident beam. The smallest perturbations were observed for the parallel detector orientation and Al electrodes (Z = 13). In summary, EGSnrc Monte Carlo code is well suited for modelling small detector geometries. The Monte Carlo model developed is a useful tool to investigate the dosimetric effects caused by different electrode materials. To minimise perturbations cause by the detector electrodes, it is recommended that the electrodes should be made from a low-atomic number material and placed parallel to the beam direction.

The structure of liquid water by polarized neutron diffraction and reverse Monte Carlo modelling.

PubMed

Temleitner, László; Pusztai, László; Schweika, Werner

2007-08-22

The coherent static structure factor of water has been investigated by polarized neutron diffraction. Polarization analysis allows us to separate the huge incoherent scattering background from hydrogen and to obtain high quality data of the coherent scattering from four different mixtures of liquid H(2)O and D(2)O. The information obtained by the variation of the scattering contrast confines the configurational space of water and is used by the reverse Monte Carlo technique to model the total structure factors. Structural characteristics have been calculated directly from the resulting sets of particle coordinates. Consistency with existing partial pair correlation functions, derived without the application of polarized neutrons, was checked by incorporating them into our reverse Monte Carlo calculations. We also performed Monte Carlo simulations of a hard sphere system, which provides an accurate estimate of the information content of the measured data. It is shown that the present combination of polarized neutron scattering and reverse Monte Carlo structural modelling is a promising approach towards a detailed understanding of the microscopic structure of water.

bhlight: General Relativistic Radiation Magnetohydrodynamics with Monte Carlo Transport

DOE PAGES

Ryan, Benjamin R; Dolence, Joshua C.; Gammie, Charles F.

2015-06-25

We present bhlight, a numerical scheme for solving the equations of general relativistic radiation magnetohydrodynamics using a direct Monte Carlo solution of the frequency-dependent radiative transport equation. bhlight is designed to evolve black hole accretion flows at intermediate accretion rate, in the regime between the classical radiatively efficient disk and the radiatively inefficient accretion flow (RIAF), in which global radiative effects play a sub-dominant but non-negligible role in disk dynamics. We describe the governing equations, numerical method, idiosyncrasies of our implementation, and a suite of test and convergence results. We also describe example applications to radiative Bondi accretion and tomore » a slowly accreting Kerr black hole in axisymmetry.« less

SUPREM-DSMC: A New Scalable, Parallel, Reacting, Multidimensional Direct Simulation Monte Carlo Flow Code

NASA Technical Reports Server (NTRS)

Campbell, David; Wysong, Ingrid; Kaplan, Carolyn; Mott, David; Wadsworth, Dean; VanGilder, Douglas

2000-01-01

An AFRL/NRL team has recently been selected to develop a scalable, parallel, reacting, multidimensional (SUPREM) Direct Simulation Monte Carlo (DSMC) code for the DoD user community under the High Performance Computing Modernization Office (HPCMO) Common High Performance Computing Software Support Initiative (CHSSI). This paper will introduce the JANNAF Exhaust Plume community to this three-year development effort and present the overall goals, schedule, and current status of this new code.

Million-body star cluster simulations: comparisons between Monte Carlo and direct N-body

NASA Astrophysics Data System (ADS)

Rodriguez, Carl L.; Morscher, Meagan; Wang, Long; Chatterjee, Sourav; Rasio, Frederic A.; Spurzem, Rainer

2016-12-01

We present the first detailed comparison between million-body globular cluster simulations computed with a Hénon-type Monte Carlo code, CMC, and a direct N-body code, NBODY6++GPU. Both simulations start from an identical cluster model with 106 particles, and include all of the relevant physics needed to treat the system in a highly realistic way. With the two codes `frozen' (no fine-tuning of any free parameters or internal algorithms of the codes) we find good agreement in the overall evolution of the two models. Furthermore, we find that in both models, large numbers of stellar-mass black holes (>1000) are retained for 12 Gyr. Thus, the very accurate direct N-body approach confirms recent predictions that black holes can be retained in present-day, old globular clusters. We find only minor disagreements between the two models and attribute these to the small-N dynamics driving the evolution of the cluster core for which the Monte Carlo assumptions are less ideal. Based on the overwhelming general agreement between the two models computed using these vastly different techniques, we conclude that our Monte Carlo approach, which is more approximate, but dramatically faster compared to the direct N-body, is capable of producing an accurate description of the long-term evolution of massive globular clusters even when the clusters contain large populations of stellar-mass black holes.

Modelling of electronic excitation and radiation in the Direct Simulation Monte Carlo Macroscopic Chemistry Method

NASA Astrophysics Data System (ADS)

Goldsworthy, M. J.

2012-10-01

One of the most useful tools for modelling rarefied hypersonic flows is the Direct Simulation Monte Carlo (DSMC) method. Simulator particle movement and collision calculations are combined with statistical procedures to model thermal non-equilibrium flow-fields described by the Boltzmann equation. The Macroscopic Chemistry Method for DSMC simulations was developed to simplify the inclusion of complex thermal non-equilibrium chemistry. The macroscopic approach uses statistical information which is calculated during the DSMC solution process in the modelling procedures. Here it is shown how inclusion of macroscopic information in models of chemical kinetics, electronic excitation, ionization, and radiation can enhance the capabilities of DSMC to model flow-fields where a range of physical processes occur. The approach is applied to the modelling of a 6.4 km/s nitrogen shock wave and results are compared with those from existing shock-tube experiments and continuum calculations. Reasonable agreement between the methods is obtained. The quality of the comparison is highly dependent on the set of vibrational relaxation and chemical kinetic parameters employed.

Direct simulation Monte Carlo modeling of relaxation processes in polyatomic gases

NASA Astrophysics Data System (ADS)

Pfeiffer, M.; Nizenkov, P.; Mirza, A.; Fasoulas, S.

2016-02-01

Relaxation processes of polyatomic molecules are modeled and implemented in an in-house Direct Simulation Monte Carlo code in order to enable the simulation of atmospheric entry maneuvers at Mars and Saturn's Titan. The description of rotational and vibrational relaxation processes is derived from basic quantum-mechanics using a rigid rotator and a simple harmonic oscillator, respectively. Strategies regarding the vibrational relaxation process are investigated, where good agreement for the relaxation time according to the Landau-Teller expression is found for both methods, the established prohibiting double relaxation method and the new proposed multi-mode relaxation. Differences and applications areas of these two methods are discussed. Consequently, two numerical methods used for sampling of energy values from multi-dimensional distribution functions are compared. The proposed random-walk Metropolis algorithm enables the efficient treatment of multiple vibrational modes within a time step with reasonable computational effort. The implemented model is verified and validated by means of simple reservoir simulations and the comparison to experimental measurements of a hypersonic, carbon-dioxide flow around a flat-faced cylinder.

The many-body Wigner Monte Carlo method for time-dependent ab-initio quantum simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sellier, J.M., E-mail: jeanmichel.sellier@parallel.bas.bg; Dimov, I.

2014-09-15

The aim of ab-initio approaches is the simulation of many-body quantum systems from the first principles of quantum mechanics. These methods are traditionally based on the many-body Schrödinger equation which represents an incredible mathematical challenge. In this paper, we introduce the many-body Wigner Monte Carlo method in the context of distinguishable particles and in the absence of spin-dependent effects. Despite these restrictions, the method has several advantages. First of all, the Wigner formalism is intuitive, as it is based on the concept of a quasi-distribution function. Secondly, the Monte Carlo numerical approach allows scalability on parallel machines that is practicallymore » unachievable by means of other techniques based on finite difference or finite element methods. Finally, this method allows time-dependent ab-initio simulations of strongly correlated quantum systems. In order to validate our many-body Wigner Monte Carlo method, as a case study we simulate a relatively simple system consisting of two particles in several different situations. We first start from two non-interacting free Gaussian wave packets. We, then, proceed with the inclusion of an external potential barrier, and we conclude by simulating two entangled (i.e. correlated) particles. The results show how, in the case of negligible spin-dependent effects, the many-body Wigner Monte Carlo method provides an efficient and reliable tool to study the time-dependent evolution of quantum systems composed of distinguishable particles.« less

NRMC - A GPU code for N-Reverse Monte Carlo modeling of fluids in confined media

NASA Astrophysics Data System (ADS)

Sánchez-Gil, Vicente; Noya, Eva G.; Lomba, Enrique

2017-08-01

NRMC is a parallel code for performing N-Reverse Monte Carlo modeling of fluids in confined media [V. Sánchez-Gil, E.G. Noya, E. Lomba, J. Chem. Phys. 140 (2014) 024504]. This method is an extension of the usual Reverse Monte Carlo method to obtain structural models of confined fluids compatible with experimental diffraction patterns, specifically designed to overcome the problem of slow diffusion that can appear under conditions of tight confinement. Most of the computational time in N-Reverse Monte Carlo modeling is spent in the evaluation of the structure factor for each trial configuration, a calculation that can be easily parallelized. Implementation of the structure factor evaluation in NVIDIA® CUDA so that the code can be run on GPUs leads to a speed up of up to two orders of magnitude.

Integration of Monte-Carlo ray tracing with a stochastic optimisation method: application to the design of solar receiver geometry.

PubMed

Asselineau, Charles-Alexis; Zapata, Jose; Pye, John

2015-06-01

A stochastic optimisation method adapted to illumination and radiative heat transfer problems involving Monte-Carlo ray-tracing is presented. A solar receiver shape optimisation case study illustrates the advantages of the method and its potential: efficient receivers are identified using a moderate computational cost.

Investigation of the SCS-CN initial abstraction ratio using a Monte Carlo simulation for the derived flood frequency curves

NASA Astrophysics Data System (ADS)

Caporali, E.; Chiarello, V.; Galeati, G.

2014-12-01

Peak discharges estimates for a given return period are of primary importance in engineering practice for risk assessment and hydraulic structure design. Different statistical methods are chosen here for the assessment of flood frequency curve: one indirect technique based on the extreme rainfall event analysis, the Peak Over Threshold (POT) model and the Annual Maxima approach as direct techniques using river discharge data. In the framework of the indirect method, a Monte Carlo simulation approach is adopted to determine a derived frequency distribution of peak runoff using a probabilistic formulation of the SCS-CN method as stochastic rainfall-runoff model. A Monte Carlo simulation is used to generate a sample of different runoff events from different stochastic combination of rainfall depth, storm duration, and initial loss inputs. The distribution of the rainfall storm events is assumed to follow the GP law whose parameters are estimated through GEV's parameters of annual maximum data. The evaluation of the initial abstraction ratio is investigated since it is one of the most questionable assumption in the SCS-CN model and plays a key role in river basin characterized by high-permeability soils, mainly governed by infiltration excess mechanism. In order to take into account the uncertainty of the model parameters, this modified approach, that is able to revise and re-evaluate the original value of the initial abstraction ratio, is implemented. In the POT model the choice of the threshold has been an essential issue, mainly based on a compromise between bias and variance. The Generalized Extreme Value (GEV) distribution fitted to the annual maxima discharges is therefore compared with the Pareto distributed peaks to check the suitability of the frequency of occurrence representation. The methodology is applied to a large dam in the Serchio river basin, located in the Tuscany Region. The application has shown as Monte Carlo simulation technique can be a useful tool to provide more robust estimation of the results obtained by direct statistical methods.

Monte Carlo derivation of filtered tungsten anode X-ray spectra for dose computation in digital mammography.

PubMed

Paixão, Lucas; Oliveira, Bruno Beraldo; Viloria, Carolina; de Oliveira, Marcio Alves; Teixeira, Maria Helena Araújo; Nogueira, Maria do Socorro

2015-01-01

Derive filtered tungsten X-ray spectra used in digital mammography systems by means of Monte Carlo simulations. Filtered spectra for rhodium filter were obtained for tube potentials between 26 and 32 kV. The half-value layer (HVL) of simulated filtered spectra were compared with those obtained experimentally with a solid state detector Unfors model 8202031-H Xi R/F & MAM Detector Platinum and 8201023-C Xi Base unit Platinum Plus w mAs in a Hologic Selenia Dimensions system using a direct radiography mode. Calculated HVL values showed good agreement as compared with those obtained experimentally. The greatest relative difference between the Monte Carlo calculated HVL values and experimental HVL values was 4%. The results show that the filtered tungsten anode X-ray spectra and the EGSnrc Monte Carlo code can be used for mean glandular dose determination in mammography.

Monte Carlo modeling of atomic oxygen attack of polymers with protective coatings on LDEF

NASA Technical Reports Server (NTRS)

Banks, Bruce A.; Degroh, Kim K.; Sechkar, Edward A.

1992-01-01

Characterization of the behavior of atomic oxygen interaction with materials on the Long Duration Exposure Facility (LDEF) will assist in understanding the mechanisms involved, and will lead to improved reliability in predicting in-space durability of materials based on ground laboratory testing. A computational simulation of atomic oxygen interaction with protected polymers was developed using Monte Carlo techniques. Through the use of assumed mechanistic behavior of atomic oxygen and results of both ground laboratory and LDEF data, a predictive Monte Carlo model was developed which simulates the oxidation processes that occur on polymers with applied protective coatings that have defects. The use of high atomic oxygen fluence-directed ram LDEF results has enabled mechanistic implications to be made by adjusting Monte Carlo modeling assumptions to match observed results based on scanning electron microscopy. Modeling assumptions, implications, and predictions are presented, along with comparison of observed ground laboratory and LDEF results.

Accurately modeling Gaussian beam propagation in the context of Monte Carlo techniques

NASA Astrophysics Data System (ADS)

Hokr, Brett H.; Winblad, Aidan; Bixler, Joel N.; Elpers, Gabriel; Zollars, Byron; Scully, Marlan O.; Yakovlev, Vladislav V.; Thomas, Robert J.

2016-03-01

Monte Carlo simulations are widely considered to be the gold standard for studying the propagation of light in turbid media. However, traditional Monte Carlo methods fail to account for diffraction because they treat light as a particle. This results in converging beams focusing to a point instead of a diffraction limited spot, greatly effecting the accuracy of Monte Carlo simulations near the focal plane. Here, we present a technique capable of simulating a focusing beam in accordance to the rules of Gaussian optics, resulting in a diffraction limited focal spot. This technique can be easily implemented into any traditional Monte Carlo simulation allowing existing models to be converted to include accurate focusing geometries with minimal effort. We will present results for a focusing beam in a layered tissue model, demonstrating that for different scenarios the region of highest intensity, thus the greatest heating, can change from the surface to the focus. The ability to simulate accurate focusing geometries will greatly enhance the usefulness of Monte Carlo for countless applications, including studying laser tissue interactions in medical applications and light propagation through turbid media.

Direct simulation Monte Carlo prediction of on-orbit contaminant deposit levels for HALOE

NASA Technical Reports Server (NTRS)

Woronowicz, Michael S.; Rault, Didier F. G.

1994-01-01

A three-dimensional version of the direct simulation Monte Carlo method is adapted to assess the contamination environment surrounding a highly detailed model of the Upper Atmosphere Research Satellite. Emphasis is placed on simulating a realistic, worst-case set of flow field and surface conditions and geometric orientations for the satellite in order to estimate an upper limit for the cumulative level of volatile organic molecular deposits at the aperture of the Halogen Occultation Experiment. A detailed description of the adaptation of this solution method to the study of the satellite's environment is also presented. Results pertaining to the satellite's environment are presented regarding contaminant cloud structure, cloud composition, and statistics of simulated molecules impinging on the target surface, along with data related to code performance. Using procedures developed in standard contamination analyses, along with many worst-case assumptions, the cumulative upper-limit level of volatile organic deposits on HALOE's aperture over the instrument's 35-month nominal data collection period is estimated at about 13,350 A.

Object-Oriented/Data-Oriented Design of a Direct Simulation Monte Carlo Algorithm

NASA Technical Reports Server (NTRS)

Liechty, Derek S.

2014-01-01

Over the past decade, there has been much progress towards improved phenomenological modeling and algorithmic updates for the direct simulation Monte Carlo (DSMC) method, which provides a probabilistic physical simulation of gas Rows. These improvements have largely been based on the work of the originator of the DSMC method, Graeme Bird. Of primary importance are improved chemistry, internal energy, and physics modeling and a reduction in time to solution. These allow for an expanded range of possible solutions In altitude and velocity space. NASA's current production code, the DSMC Analysis Code (DAC), is well-established and based on Bird's 1994 algorithms written in Fortran 77 and has proven difficult to upgrade. A new DSMC code is being developed in the C++ programming language using object-oriented and data-oriented design paradigms to facilitate the inclusion of the recent improvements and future development activities. The development efforts on the new code, the Multiphysics Algorithm with Particles (MAP), are described, and performance comparisons are made with DAC.

Modeling of the plasma extraction efficiency of an inductively coupled plasma-mass spectrometer interface using the direct simulation Monte Carlo method

NASA Astrophysics Data System (ADS)

Kivel, Niko; Potthast, Heiko-Dirk; Günther-Leopold, Ines; Vanhaecke, Frank; Günther, Detlef

The interface between the atmospheric pressure plasma ion source and the high vacuum mass spectrometer is a crucial part of an inductively coupled plasma-mass spectrometer. It influences the efficiency of the mass transfer into the mass spectrometer, it also contributes to the formation of interfering ions and to mass discrimination. This region was simulated using the Direct Simulation Monte Carlo method with respect to the formation of shock waves, mass transport and mass discrimination. The modeling results for shock waves and mass transport are in overall agreement with the literature. Insights into the effects and geometrical features causing mass discrimination could be gained. The overall observed collision based mass discrimination is lower than expected from measurements on real instruments, supporting the assumptions that inter-particle collisions play a minor role in this context published earlier. A full representation of the study, for two selected geometries, is given in form of a movie as supplementary data.

Pushing the limits of Monte Carlo simulations for the three-dimensional Ising model

NASA Astrophysics Data System (ADS)

Ferrenberg, Alan M.; Xu, Jiahao; Landau, David P.

2018-04-01

While the three-dimensional Ising model has defied analytic solution, various numerical methods like Monte Carlo, Monte Carlo renormalization group, and series expansion have provided precise information about the phase transition. Using Monte Carlo simulation that employs the Wolff cluster flipping algorithm with both 32-bit and 53-bit random number generators and data analysis with histogram reweighting and quadruple precision arithmetic, we have investigated the critical behavior of the simple cubic Ising Model, with lattice sizes ranging from 163 to 10243. By analyzing data with cross correlations between various thermodynamic quantities obtained from the same data pool, e.g., logarithmic derivatives of magnetization and derivatives of magnetization cumulants, we have obtained the critical inverse temperature Kc=0.221 654 626 (5 ) and the critical exponent of the correlation length ν =0.629 912 (86 ) with precision that exceeds all previous Monte Carlo estimates.

A modified Monte Carlo model for the ionospheric heating rates

NASA Technical Reports Server (NTRS)

Mayr, H. G.; Fontheim, E. G.; Robertson, S. C.

1972-01-01

A Monte Carlo method is adopted as a basis for the derivation of the photoelectron heat input into the ionospheric plasma. This approach is modified in an attempt to minimize the computation time. The heat input distributions are computed for arbitrarily small source elements that are spaced at distances apart corresponding to the photoelectron dissipation range. By means of a nonlinear interpolation procedure their individual heating rate distributions are utilized to produce synthetic ones that fill the gaps between the Monte Carlo generated distributions. By varying these gaps and the corresponding number of Monte Carlo runs the accuracy of the results is tested to verify the validity of this procedure. It is concluded that this model can reduce the computation time by more than a factor of three, thus improving the feasibility of including Monte Carlo calculations in self-consistent ionosphere models.

A CUMULATIVE MIGRATION METHOD FOR COMPUTING RIGOROUS TRANSPORT CROSS SECTIONS AND DIFFUSION COEFFICIENTS FOR LWR LATTICES WITH MONTE CARLO

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhaoyuan Liu; Kord Smith; Benoit Forget

2016-05-01

A new method for computing homogenized assembly neutron transport cross sections and dif- fusion coefficients that is both rigorous and computationally efficient is proposed in this paper. In the limit of a homogeneous hydrogen slab, the new method is equivalent to the long-used, and only-recently-published CASMO transport method. The rigorous method is used to demonstrate the sources of inaccuracy in the commonly applied “out-scatter” transport correction. It is also demonstrated that the newly developed method is directly applicable to lattice calculations per- formed by Monte Carlo and is capable of computing rigorous homogenized transport cross sections for arbitrarily heterogeneous lattices.more » Comparisons of several common transport cross section ap- proximations are presented for a simple problem of infinite medium hydrogen. The new method has also been applied in computing 2-group diffusion data for an actual PWR lattice from BEAVRS benchmark.« less

Monte Carlo treatment planning with modulated electron radiotherapy: framework development and application

NASA Astrophysics Data System (ADS)

Alexander, Andrew William

Within the field of medical physics, Monte Carlo radiation transport simulations are considered to be the most accurate method for the determination of dose distributions in patients. The McGill Monte Carlo treatment planning system (MMCTP), provides a flexible software environment to integrate Monte Carlo simulations with current and new treatment modalities. A developing treatment modality called energy and intensity modulated electron radiotherapy (MERT) is a promising modality, which has the fundamental capabilities to enhance the dosimetry of superficial targets. An objective of this work is to advance the research and development of MERT with the end goal of clinical use. To this end, we present the MMCTP system with an integrated toolkit for MERT planning and delivery of MERT fields. Delivery is achieved using an automated "few leaf electron collimator" (FLEC) and a controller. Aside from the MERT planning toolkit, the MMCTP system required numerous add-ons to perform the complex task of large-scale autonomous Monte Carlo simulations. The first was a DICOM import filter, followed by the implementation of DOSXYZnrc as a dose calculation engine and by logic methods for submitting and updating the status of Monte Carlo simulations. Within this work we validated the MMCTP system with a head and neck Monte Carlo recalculation study performed by a medical dosimetrist. The impact of MMCTP lies in the fact that it allows for systematic and platform independent large-scale Monte Carlo dose calculations for different treatment sites and treatment modalities. In addition to the MERT planning tools, various optimization algorithms were created external to MMCTP. The algorithms produced MERT treatment plans based on dose volume constraints that employ Monte Carlo pre-generated patient-specific kernels. The Monte Carlo kernels are generated from patient-specific Monte Carlo dose distributions within MMCTP. The structure of the MERT planning toolkit software and optimization algorithms are demonstrated. We investigated the clinical significance of MERT on spinal irradiation, breast boost irradiation, and a head and neck sarcoma cancer site using several parameters to analyze the treatment plans. Finally, we investigated the idea of mixed beam photon and electron treatment planning. Photon optimization treatment planning tools were included within the MERT planning toolkit for the purpose of mixed beam optimization. In conclusion, this thesis work has resulted in the development of an advanced framework for photon and electron Monte Carlo treatment planning studies and the development of an inverse planning system for photon, electron or mixed beam radiotherapy (MBRT). The justification and validation of this work is found within the results of the planning studies, which have demonstrated dosimetric advantages to using MERT or MBRT in comparison to clinical treatment alternatives.

Monte Carlo simulation of aorta autofluorescence

NASA Astrophysics Data System (ADS)

Kuznetsova, A. A.; Pushkareva, A. E.

2016-08-01

Results of numerical simulation of autofluorescence of the aorta by the method of Monte Carlo are reported. Two states of the aorta, normal and with atherosclerotic lesions, are studied. A model of the studied tissue is developed on the basis of information about optical, morphological, and physico-chemical properties. It is shown that the data obtained by numerical Monte Carlo simulation are in good agreement with experimental results indicating adequacy of the developed model of the aorta autofluorescence.

Monte Carlo Approach for Estimating Density and Atomic Number From Dual-Energy Computed Tomography Images of Carbonate Rocks

NASA Astrophysics Data System (ADS)

Victor, Rodolfo A.; Prodanović, Maša.; Torres-Verdín, Carlos

2017-12-01

We develop a new Monte Carlo-based inversion method for estimating electron density and effective atomic number from 3-D dual-energy computed tomography (CT) core scans. The method accounts for uncertainties in X-ray attenuation coefficients resulting from the polychromatic nature of X-ray beam sources of medical and industrial scanners, in addition to delivering uncertainty estimates of inversion products. Estimation of electron density and effective atomic number from CT core scans enables direct deterministic or statistical correlations with salient rock properties for improved petrophysical evaluation; this condition is specifically important in media such as vuggy carbonates where CT resolution better captures core heterogeneity that dominates fluid flow properties. Verification tests of the inversion method performed on a set of highly heterogeneous carbonate cores yield very good agreement with in situ borehole measurements of density and photoelectric factor.

Peelle's pertinent puzzle using the Monte Carlo technique

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kawano, Toshihiko; Talou, Patrick; Burr, Thomas

2009-01-01

We try to understand the long-standing problem of the Peelle's Pertinent Puzzle (PPP) using the Monte Carlo technique. We allow the probability density functions to be any kind of form to assume the impact of distribution, and obtain the least-squares solution directly from numerical simulations. We found that the standard least squares method gives the correct answer if a weighting function is properly provided. Results from numerical simulations show that the correct answer of PPP is 1.1 {+-} 0.25 if the common error is multiplicative. The thought-provoking answer of 0.88 is also correct, if the common error is additive, andmore » if the error is proportional to the measured values. The least squares method correctly gives us the most probable case, where the additive component has a negative value. Finally, the standard method fails for PPP due to a distorted (non Gaussian) joint distribution.« less

Communication: Calculation of interatomic forces and optimization of molecular geometry with auxiliary-field quantum Monte Carlo

NASA Astrophysics Data System (ADS)

Motta, Mario; Zhang, Shiwei

2018-05-01

We propose an algorithm for accurate, systematic, and scalable computation of interatomic forces within the auxiliary-field quantum Monte Carlo (AFQMC) method. The algorithm relies on the Hellmann-Feynman theorem and incorporates Pulay corrections in the presence of atomic orbital basis sets. We benchmark the method for small molecules by comparing the computed forces with the derivatives of the AFQMC potential energy surface and by direct comparison with other quantum chemistry methods. We then perform geometry optimizations using the steepest descent algorithm in larger molecules. With realistic basis sets, we obtain equilibrium geometries in agreement, within statistical error bars, with experimental values. The increase in computational cost for computing forces in this approach is only a small prefactor over that of calculating the total energy. This paves the way for a general and efficient approach for geometry optimization and molecular dynamics within AFQMC.

PRELIMINARY COUPLING OF THE MONTE CARLO CODE OPENMC AND THE MULTIPHYSICS OBJECT-ORIENTED SIMULATION ENVIRONMENT (MOOSE) FOR ANALYZING DOPPLER FEEDBACK IN MONTE CARLO SIMULATIONS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Matthew Ellis; Derek Gaston; Benoit Forget

In recent years the use of Monte Carlo methods for modeling reactors has become feasible due to the increasing availability of massively parallel computer systems. One of the primary challenges yet to be fully resolved, however, is the efficient and accurate inclusion of multiphysics feedback in Monte Carlo simulations. The research in this paper presents a preliminary coupling of the open source Monte Carlo code OpenMC with the open source Multiphysics Object-Oriented Simulation Environment (MOOSE). The coupling of OpenMC and MOOSE will be used to investigate efficient and accurate numerical methods needed to include multiphysics feedback in Monte Carlo codes.more » An investigation into the sensitivity of Doppler feedback to fuel temperature approximations using a two dimensional 17x17 PWR fuel assembly is presented in this paper. The results show a functioning multiphysics coupling between OpenMC and MOOSE. The coupling utilizes Functional Expansion Tallies to accurately and efficiently transfer pin power distributions tallied in OpenMC to unstructured finite element meshes used in MOOSE. The two dimensional PWR fuel assembly case also demonstrates that for a simplified model the pin-by-pin doppler feedback can be adequately replicated by scaling a representative pin based on pin relative powers.« less

Dynamic response analysis of structure under time-variant interval process model

NASA Astrophysics Data System (ADS)

Xia, Baizhan; Qin, Yuan; Yu, Dejie; Jiang, Chao

2016-10-01

Due to the aggressiveness of the environmental factor, the variation of the dynamic load, the degeneration of the material property and the wear of the machine surface, parameters related with the structure are distinctly time-variant. Typical model for time-variant uncertainties is the random process model which is constructed on the basis of a large number of samples. In this work, we propose a time-variant interval process model which can be effectively used to deal with time-variant uncertainties with limit information. And then two methods are presented for the dynamic response analysis of the structure under the time-variant interval process model. The first one is the direct Monte Carlo method (DMCM) whose computational burden is relative high. The second one is the Monte Carlo method based on the Chebyshev polynomial expansion (MCM-CPE) whose computational efficiency is high. In MCM-CPE, the dynamic response of the structure is approximated by the Chebyshev polynomials which can be efficiently calculated, and then the variational range of the dynamic response is estimated according to the samples yielded by the Monte Carlo method. To solve the dependency phenomenon of the interval operation, the affine arithmetic is integrated into the Chebyshev polynomial expansion. The computational effectiveness and efficiency of MCM-CPE is verified by two numerical examples, including a spring-mass-damper system and a shell structure.

A Monte Carlo Evaluation of Estimated Parameters of Five Shrinkage Estimate Formuli.

ERIC Educational Resources Information Center

Newman, Isadore; And Others

A Monte Carlo study was conducted to estimate the efficiency of and the relationship between five equations and the use of cross validation as methods for estimating shrinkage in multiple correlations. Two of the methods were intended to estimate shrinkage to population values and the other methods were intended to estimate shrinkage from sample…

Coarse-grained computation for particle coagulation and sintering processes by linking Quadrature Method of Moments with Monte-Carlo

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zou Yu, E-mail: yzou@Princeton.ED; Kavousanakis, Michail E., E-mail: mkavousa@Princeton.ED; Kevrekidis, Ioannis G., E-mail: yannis@Princeton.ED

2010-07-20

The study of particle coagulation and sintering processes is important in a variety of research studies ranging from cell fusion and dust motion to aerosol formation applications. These processes are traditionally simulated using either Monte-Carlo methods or integro-differential equations for particle number density functions. In this paper, we present a computational technique for cases where we believe that accurate closed evolution equations for a finite number of moments of the density function exist in principle, but are not explicitly available. The so-called equation-free computational framework is then employed to numerically obtain the solution of these unavailable closed moment equations bymore » exploiting (through intelligent design of computational experiments) the corresponding fine-scale (here, Monte-Carlo) simulation. We illustrate the use of this method by accelerating the computation of evolving moments of uni- and bivariate particle coagulation and sintering through short simulation bursts of a constant-number Monte-Carlo scheme.« less

Using hybrid implicit Monte Carlo diffusion to simulate gray radiation hydrodynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cleveland, Mathew A., E-mail: cleveland7@llnl.gov; Gentile, Nick

This work describes how to couple a hybrid Implicit Monte Carlo Diffusion (HIMCD) method with a Lagrangian hydrodynamics code to evaluate the coupled radiation hydrodynamics equations. This HIMCD method dynamically applies Implicit Monte Carlo Diffusion (IMD) [1] to regions of a problem that are opaque and diffusive while applying standard Implicit Monte Carlo (IMC) [2] to regions where the diffusion approximation is invalid. We show that this method significantly improves the computational efficiency as compared to a standard IMC/Hydrodynamics solver, when optically thick diffusive material is present, while maintaining accuracy. Two test cases are used to demonstrate the accuracy andmore » performance of HIMCD as compared to IMC and IMD. The first is the Lowrie semi-analytic diffusive shock [3]. The second is a simple test case where the source radiation streams through optically thin material and heats a thick diffusive region of material causing it to rapidly expand. We found that HIMCD proves to be accurate, robust, and computationally efficient for these test problems.« less

Mathematical modeling of a survey-meter used to measure radioactivity in human thyroids: Monte Carlo calculations of the device response and uncertainties

PubMed Central

Khrutchinsky, Arkady; Drozdovitch, Vladimir; Kutsen, Semion; Minenko, Victor; Khrouch, Valeri; Luckyanov, Nickolas; Voillequé, Paul; Bouville, André

2012-01-01

This paper presents results of Monte Carlo modeling of the SRP-68-01 survey meter used to measure exposure rates near the thyroid glands of persons exposed to radioactivity following the Chernobyl accident. This device was not designed to measure radioactivity in humans. To estimate the uncertainty associated with the measurement results, a mathematical model of the SRP-68-01 survey meter was developed and verified. A Monte Carlo method of numerical simulation of radiation transport has been used to calculate the calibration factor for the device and evaluate its uncertainty. The SRP-68-01 survey meter scale coefficient, an important characteristic of the device, was also estimated in this study. The calibration factors of the survey meter were calculated for 131I, 132I, 133I, and 135I content in the thyroid gland for six age groups of population: newborns; children aged 1 yr, 5 yr, 10 yr, 15 yr; and adults. A realistic scenario of direct thyroid measurements with an “extended” neck was used to calculate the calibration factors for newborns and one-year-olds. Uncertainties in the device calibration factors due to variability of the device scale coefficient, variability in thyroid mass and statistical uncertainty of Monte Carlo method were evaluated. Relative uncertainties in the calibration factor estimates were found to be from 0.06 for children aged 1 yr to 0.1 for 10-yr and 15-yr children. The positioning errors of the detector during measurements deviate mainly in one direction from the estimated calibration factors. Deviations of the device position from the proper geometry of measurements were found to lead to overestimation of the calibration factor by up to 24 percent for adults and up to 60 percent for 1-yr children. The results of this study improve the estimates of 131I thyroidal content and, consequently, thyroid dose estimates that are derived from direct thyroid measurements performed in Belarus shortly after the Chernobyl accident. PMID:22245289

Markov chain Monte Carlo techniques applied to parton distribution functions determination: Proof of concept

NASA Astrophysics Data System (ADS)

Gbedo, Yémalin Gabin; Mangin-Brinet, Mariane

2017-07-01

We present a new procedure to determine parton distribution functions (PDFs), based on Markov chain Monte Carlo (MCMC) methods. The aim of this paper is to show that we can replace the standard χ2 minimization by procedures grounded on statistical methods, and on Bayesian inference in particular, thus offering additional insight into the rich field of PDFs determination. After a basic introduction to these techniques, we introduce the algorithm we have chosen to implement—namely Hybrid (or Hamiltonian) Monte Carlo. This algorithm, initially developed for Lattice QCD, turns out to be very interesting when applied to PDFs determination by global analyses; we show that it allows us to circumvent the difficulties due to the high dimensionality of the problem, in particular concerning the acceptance. A first feasibility study is performed and presented, which indicates that Markov chain Monte Carlo can successfully be applied to the extraction of PDFs and of their uncertainties.

Two proposed convergence criteria for Monte Carlo solutions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Forster, R.A.; Pederson, S.P.; Booth, T.E.

1992-01-01

The central limit theorem (CLT) can be applied to a Monte Carlo solution if two requirements are satisfied: (1) The random variable has a finite mean and a finite variance; and (2) the number N of independent observations grows large. When these two conditions are satisfied, a confidence interval (CI) based on the normal distribution with a specified coverage probability can be formed. The first requirement is generally satisfied by the knowledge of the Monte Carlo tally being used. The Monte Carlo practitioner has a limited number of marginal methods to assess the fulfillment of the second requirement, such asmore » statistical error reduction proportional to 1/[radical]N with error magnitude guidelines. Two proposed methods are discussed in this paper to assist in deciding if N is large enough: estimating the relative variance of the variance (VOV) and examining the empirical history score probability density function (pdf).« less

A microstructural lattice model for strain oriented problems: A combined Monte Carlo finite element technique

NASA Technical Reports Server (NTRS)

Gayda, J.; Srolovitz, D. J.

1987-01-01

A specialized, microstructural lattice model, termed MCFET for combined Monte Carlo Finite Element Technique, was developed which simulates microstructural evolution in material systems where modulated phases occur and the directionality of the modulation is influenced by internal and external stresses. In this approach, the microstructure is discretized onto a fine lattice. Each element in the lattice is labelled in accordance with its microstructural identity. Diffusion of material at elevated temperatures is simulated by allowing exchanges of neighboring elements if the exchange lowers the total energy of the system. A Monte Carlo approach is used to select the exchange site while the change in energy associated with stress fields is computed using a finite element technique. The MCFET analysis was validated by comparing this approach with a closed form, analytical method for stress assisted, shape changes of a single particle in an infinite matrix. Sample MCFET analytical for multiparticle problems were also run and in general the resulting microstructural changes associated with the application of an external stress are similar to that observed in Ni-Al-Cr alloys at elevated temperature.

Measurements and Monte-Carlo simulations of the particle self-shielding effect of B4C grains in neutron shielding concrete

NASA Astrophysics Data System (ADS)

DiJulio, D. D.; Cooper-Jensen, C. P.; Llamas-Jansa, I.; Kazi, S.; Bentley, P. M.

2018-06-01

A combined measurement and Monte-Carlo simulation study was carried out in order to characterize the particle self-shielding effect of B4C grains in neutron shielding concrete. Several batches of a specialized neutron shielding concrete, with varying B4C grain sizes, were exposed to a 2 Å neutron beam at the R2D2 test beamline at the Institute for Energy Technology located in Kjeller, Norway. The direct and scattered neutrons were detected with a neutron detector placed behind the concrete blocks and the results were compared to Geant4 simulations. The particle self-shielding effect was included in the Geant4 simulations by calculating effective neutron cross-sections during the Monte-Carlo simulation process. It is shown that this method well reproduces the measured results. Our results show that shielding calculations for low-energy neutrons using such materials would lead to an underestimate of the shielding required for a certain design scenario if the particle self-shielding effect is not included in the calculations.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sudhyadhom, A; McGuinness, C; Descovich, M

Purpose: To develop a methodology for validation of a Monte-Carlo dose calculation model for robotic small field SRS/SBRT deliveries. Methods: In a robotic treatment planning system, a Monte-Carlo model was iteratively optimized to match with beam data. A two-part analysis was developed to verify this model. 1) The Monte-Carlo model was validated in a simulated water phantom versus a Ray-Tracing calculation on a single beam collimator-by-collimator calculation. 2) The Monte-Carlo model was validated to be accurate in the most challenging situation, lung, by acquiring in-phantom measurements. A plan was created and delivered in a CIRS lung phantom with film insert.more » Separately, plans were delivered in an in-house created lung phantom with a PinPoint chamber insert within a lung simulating material. For medium to large collimator sizes, a single beam was delivered to the phantom. For small size collimators (10, 12.5, and 15mm), a robotically delivered plan was created to generate a uniform dose field of irradiation over a 2×2cm{sup 2} area. Results: Dose differences in simulated water between Ray-Tracing and Monte-Carlo were all within 1% at dmax and deeper. Maximum dose differences occurred prior to dmax but were all within 3%. Film measurements in a lung phantom show high correspondence of over 95% gamma at the 2%/2mm level for Monte-Carlo. Ion chamber measurements for collimator sizes of 12.5mm and above were within 3% of Monte-Carlo calculated values. Uniform irradiation involving the 10mm collimator resulted in a dose difference of ∼8% for both Monte-Carlo and Ray-Tracing indicating that there may be limitations with the dose calculation. Conclusion: We have developed a methodology to validate a Monte-Carlo model by verifying that it matches in water and, separately, that it corresponds well in lung simulating materials. The Monte-Carlo model and algorithm tested may have more limited accuracy for 10mm fields and smaller.« less

Experimental verification of a CT-based Monte Carlo dose-calculation method in heterogeneous phantoms.

PubMed

Wang, L; Lovelock, M; Chui, C S

1999-12-01

To further validate the Monte Carlo dose-calculation method [Med. Phys. 25, 867-878 (1998)] developed at the Memorial Sloan-Kettering Cancer Center, we have performed experimental verification in various inhomogeneous phantoms. The phantom geometries included simple layered slabs, a simulated bone column, a simulated missing-tissue hemisphere, and an anthropomorphic head geometry (Alderson Rando Phantom). The densities of the inhomogeneity range from 0.14 to 1.86 g/cm3, simulating both clinically relevant lunglike and bonelike materials. The data are reported as central axis depth doses, dose profiles, dose values at points of interest, such as points at the interface of two different media and in the "nasopharynx" region of the Rando head. The dosimeters used in the measurement included dosimetry film, TLD chips, and rods. The measured data were compared to that of Monte Carlo calculations for the same geometrical configurations. In the case of the Rando head phantom, a CT scan of the phantom was used to define the calculation geometry and to locate the points of interest. The agreement between the calculation and measurement is generally within 2.5%. This work validates the accuracy of the Monte Carlo method. While Monte Carlo, at present, is still too slow for routine treatment planning, it can be used as a benchmark against which other dose calculation methods can be compared.

Analysis of Monte Carlo accelerated iterative methods for sparse linear systems: Analysis of Monte Carlo accelerated iterative methods for sparse linear systems

DOE PAGES

Benzi, Michele; Evans, Thomas M.; Hamilton, Steven P.; ...

2017-03-05

Here, we consider hybrid deterministic-stochastic iterative algorithms for the solution of large, sparse linear systems. Starting from a convergent splitting of the coefficient matrix, we analyze various types of Monte Carlo acceleration schemes applied to the original preconditioned Richardson (stationary) iteration. We expect that these methods will have considerable potential for resiliency to faults when implemented on massively parallel machines. We also establish sufficient conditions for the convergence of the hybrid schemes, and we investigate different types of preconditioners including sparse approximate inverses. Numerical experiments on linear systems arising from the discretization of partial differential equations are presented.

Inventory Uncertainty Quantification using TENDL Covariance Data in Fispact-II

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eastwood, J.W.; Morgan, J.G.; Sublet, J.-Ch., E-mail: jean-christophe.sublet@ccfe.ac.uk

2015-01-15

The new inventory code Fispact-II provides predictions of inventory, radiological quantities and their uncertainties using nuclear data covariance information. Central to the method is a novel fast pathways search algorithm using directed graphs. The pathways output provides (1) an aid to identifying important reactions, (2) fast estimates of uncertainties, (3) reduced models that retain important nuclides and reactions for use in the code's Monte Carlo sensitivity analysis module. Described are the methods that are being implemented for improving uncertainty predictions, quantification and propagation using the covariance data that the recent nuclear data libraries contain. In the TENDL library, above themore » upper energy of the resolved resonance range, a Monte Carlo method in which the covariance data come from uncertainties of the nuclear model calculations is used. The nuclear data files are read directly by FISPACT-II without any further intermediate processing. Variance and covariance data are processed and used by FISPACT-II to compute uncertainties in collapsed cross sections, and these are in turn used to predict uncertainties in inventories and all derived radiological data.« less

Direct simulation Monte Carlo modeling of relaxation processes in polyatomic gases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pfeiffer, M., E-mail: mpfeiffer@irs.uni-stuttgart.de; Nizenkov, P., E-mail: nizenkov@irs.uni-stuttgart.de; Mirza, A., E-mail: mirza@irs.uni-stuttgart.de

2016-02-15

Relaxation processes of polyatomic molecules are modeled and implemented in an in-house Direct Simulation Monte Carlo code in order to enable the simulation of atmospheric entry maneuvers at Mars and Saturn’s Titan. The description of rotational and vibrational relaxation processes is derived from basic quantum-mechanics using a rigid rotator and a simple harmonic oscillator, respectively. Strategies regarding the vibrational relaxation process are investigated, where good agreement for the relaxation time according to the Landau-Teller expression is found for both methods, the established prohibiting double relaxation method and the new proposed multi-mode relaxation. Differences and applications areas of these two methodsmore » are discussed. Consequently, two numerical methods used for sampling of energy values from multi-dimensional distribution functions are compared. The proposed random-walk Metropolis algorithm enables the efficient treatment of multiple vibrational modes within a time step with reasonable computational effort. The implemented model is verified and validated by means of simple reservoir simulations and the comparison to experimental measurements of a hypersonic, carbon-dioxide flow around a flat-faced cylinder.« less

Radial-based tail methods for Monte Carlo simulations of cylindrical interfaces

NASA Astrophysics Data System (ADS)

Goujon, Florent; Bêche, Bruno; Malfreyt, Patrice; Ghoufi, Aziz

2018-03-01

In this work, we implement for the first time the radial-based tail methods for Monte Carlo simulations of cylindrical interfaces. The efficiency of this method is then evaluated through the calculation of surface tension and coexisting properties. We show that the inclusion of tail corrections during the course of the Monte Carlo simulation impacts the coexisting and the interfacial properties. We establish that the long range corrections to the surface tension are the same order of magnitude as those obtained from planar interface. We show that the slab-based tail method does not amend the localization of the Gibbs equimolar dividing surface. Additionally, a non-monotonic behavior of surface tension is exhibited as a function of the radius of the equimolar dividing surface.

A surrogate accelerated multicanonical Monte Carlo method for uncertainty quantification

NASA Astrophysics Data System (ADS)

Wu, Keyi; Li, Jinglai

2016-09-01

In this work we consider a class of uncertainty quantification problems where the system performance or reliability is characterized by a scalar parameter y. The performance parameter y is random due to the presence of various sources of uncertainty in the system, and our goal is to estimate the probability density function (PDF) of y. We propose to use the multicanonical Monte Carlo (MMC) method, a special type of adaptive importance sampling algorithms, to compute the PDF of interest. Moreover, we develop an adaptive algorithm to construct local Gaussian process surrogates to further accelerate the MMC iterations. With numerical examples we demonstrate that the proposed method can achieve several orders of magnitudes of speedup over the standard Monte Carlo methods.

On predicting contamination levels of HALOE optics aboard UARS using direct simulation Monte Carlo

NASA Technical Reports Server (NTRS)

Woronowicz, Michael S.; Rault, Didier F. G.

1993-01-01

A three-dimensional version of the direct simulation Monte Carlo method is adapted to assess the contamination environment surrounding a highly detailed model of the Upper Atmosphere Research Satellite. Emphasis is placed on simulating a realistic, worst-case set of flowfield and surface conditions and geometric orientations in order to estimate an upper limit for the cumulative level of volatile organic molecular deposits at the aperture of the Halogen Occultation Experiment. Problems resolving species outgassing and vent flux rates that varied over many orders of magnitude were handled using species weighting factors. Results relating to contaminant cloud structure, cloud composition, and statistics of simulated molecules impinging on the target surface are presented, along with data related to code performance. Using procedures developed in standard contamination analyses, the cumulative level of volatile organic deposits on HALOE's aperture over the instrument's 35-month nominal data collection period is estimated to be about 2700A.

High-pT Physics in the Heavy Ion Era

NASA Astrophysics Data System (ADS)

Rak, Jan; Tannenbaum, Michael J.

2013-04-01

1. Introduction and overview; 2. Basic observables; 3. Some experimental techniques; 4. The search for structure; 5. Origins of high pT physics - the search for the W boson; 6. Discovery of hard scattering in p-p collisions; 7. Direct single lepton production and the discovery of charm; 8. J/ ψ, u and Drell-Yan pair production; 9. Two particle correlations; 10. Direct photon production; 11. The search for jets; 12. QCD in hard scattering; 13. Heavy ion physics in the high pT era; 14. RHIC and LHC; Appendix A. Probability and statistics; Appendix B. Methods of Monte Carlo calculations; Appendix C. TAB and the Glauber Monte Carlo calculation; Appendix D. Fits including systematic errors; Appendix E. The shape of the xE distribution triggered by a jet fragment, for example, π0; Appendix F. kT phenomenology and Gaussian smearing; References; Index.

Application of dynamic Monte Carlo technique in proton beam radiotherapy using Geant4 simulation toolkit

NASA Astrophysics Data System (ADS)

Guan, Fada

Monte Carlo method has been successfully applied in simulating the particles transport problems. Most of the Monte Carlo simulation tools are static and they can only be used to perform the static simulations for the problems with fixed physics and geometry settings. Proton therapy is a dynamic treatment technique in the clinical application. In this research, we developed a method to perform the dynamic Monte Carlo simulation of proton therapy using Geant4 simulation toolkit. A passive-scattering treatment nozzle equipped with a rotating range modulation wheel was modeled in this research. One important application of the Monte Carlo simulation is to predict the spatial dose distribution in the target geometry. For simplification, a mathematical model of a human body is usually used as the target, but only the average dose over the whole organ or tissue can be obtained rather than the accurate spatial dose distribution. In this research, we developed a method using MATLAB to convert the medical images of a patient from CT scanning into the patient voxel geometry. Hence, if the patient voxel geometry is used as the target in the Monte Carlo simulation, the accurate spatial dose distribution in the target can be obtained. A data analysis tool---root was used to score the simulation results during a Geant4 simulation and to analyze the data and plot results after simulation. Finally, we successfully obtained the accurate spatial dose distribution in part of a human body after treating a patient with prostate cancer using proton therapy.

Development of a generalized perturbation theory method for sensitivity analysis using continuous-energy Monte Carlo methods

DOE PAGES

Perfetti, Christopher M.; Rearden, Bradley T.

2016-03-01

The sensitivity and uncertainty analysis tools of the ORNL SCALE nuclear modeling and simulation code system that have been developed over the last decade have proven indispensable for numerous application and design studies for nuclear criticality safety and reactor physics. SCALE contains tools for analyzing the uncertainty in the eigenvalue of critical systems, but cannot quantify uncertainty in important neutronic parameters such as multigroup cross sections, fuel fission rates, activation rates, and neutron fluence rates with realistic three-dimensional Monte Carlo simulations. A more complete understanding of the sources of uncertainty in these design-limiting parameters could lead to improvements in processmore » optimization, reactor safety, and help inform regulators when setting operational safety margins. A novel approach for calculating eigenvalue sensitivity coefficients, known as the CLUTCH method, was recently explored as academic research and has been found to accurately and rapidly calculate sensitivity coefficients in criticality safety applications. The work presented here describes a new method, known as the GEAR-MC method, which extends the CLUTCH theory for calculating eigenvalue sensitivity coefficients to enable sensitivity coefficient calculations and uncertainty analysis for a generalized set of neutronic responses using high-fidelity continuous-energy Monte Carlo calculations. Here, several criticality safety systems were examined to demonstrate proof of principle for the GEAR-MC method, and GEAR-MC was seen to produce response sensitivity coefficients that agreed well with reference direct perturbation sensitivity coefficients.« less

Quantum Monte Carlo Methods for First Principles Simulation of Liquid Water

ERIC Educational Resources Information Center

Gergely, John Robert

2009-01-01

Obtaining an accurate microscopic description of water structure and dynamics is of great interest to molecular biology researchers and in the physics and quantum chemistry simulation communities. This dissertation describes efforts to apply quantum Monte Carlo methods to this problem with the goal of making progress toward a fully "ab initio"…

Variational Approach to Monte Carlo Renormalization Group

NASA Astrophysics Data System (ADS)

Wu, Yantao; Car, Roberto

2017-12-01

We present a Monte Carlo method for computing the renormalized coupling constants and the critical exponents within renormalization theory. The scheme, which derives from a variational principle, overcomes critical slowing down, by means of a bias potential that renders the coarse grained variables uncorrelated. The two-dimensional Ising model is used to illustrate the method.

Experimental and Monte Carlo evaluation of Eclipse treatment planning system for effects on dose distribution of the hip prostheses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Çatlı, Serap, E-mail: serapcatli@hotmail.com; Tanır, Güneş

2013-10-01

The present study aimed to investigate the effects of titanium, titanium alloy, and stainless steel hip prostheses on dose distribution based on the Monte Carlo simulation method, as well as the accuracy of the Eclipse treatment planning system (TPS) at 6 and 18 MV photon energies. In the present study the pencil beam convolution (PBC) method implemented in the Eclipse TPS was compared to the Monte Carlo method and ionization chamber measurements. The present findings show that if high-Z material is used in prosthesis, large dose changes can occur due to scattering. The variance in dose observed in the presentmore » study was dependent on material type, density, and atomic number, as well as photon energy; as photon energy increased back scattering decreased. The dose perturbation effect of hip prostheses was significant and could not be predicted accurately by the PBC method for hip prostheses. The findings show that for accurate dose calculation the Monte Carlo-based TPS should be used in patients with hip prostheses.« less

Determination of correction factors in beta radiation beams using Monte Carlo method.

PubMed

Polo, Ivón Oramas; Santos, William de Souza; Caldas, Linda V E

2018-06-15

The absorbed dose rate is the main characterization quantity for beta radiation. The extrapolation chamber is considered the primary standard instrument. To determine absorbed dose rates in beta radiation beams, it is necessary to establish several correction factors. In this work, the correction factors for the backscatter due to the collecting electrode and to the guard ring, and the correction factor for Bremsstrahlung in beta secondary standard radiation beams are presented. For this purpose, the Monte Carlo method was applied. The results obtained are considered acceptable, and they agree within the uncertainties. The differences between the backscatter factors determined by the Monte Carlo method and those of the ISO standard were 0.6%, 0.9% and 2.04% for 90 Sr/ 90 Y, 85 Kr and 147 Pm sources respectively. The differences between the Bremsstrahlung factors determined by the Monte Carlo method and those of the ISO were 0.25%, 0.6% and 1% for 90 Sr/ 90 Y, 85 Kr and 147 Pm sources respectively. Copyright © 2018 Elsevier Ltd. All rights reserved.

Theoretically informed Monte Carlo simulation of liquid crystals by sampling of alignment-tensor fields.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Armas-Perez, Julio C.; Londono-Hurtado, Alejandro; Guzman, Orlando

2015-07-27

A theoretically informed coarse-grained Monte Carlo method is proposed for studying liquid crystals. The free energy functional of the system is described in the framework of the Landau-de Gennes formalism. The alignment field and its gradients are approximated by finite differences, and the free energy is minimized through a stochastic sampling technique. The validity of the proposed method is established by comparing the results of the proposed approach to those of traditional free energy minimization techniques. Its usefulness is illustrated in the context of three systems, namely, a nematic liquid crystal confined in a slit channel, a nematic liquid crystalmore » droplet, and a chiral liquid crystal in the bulk. It is found that for systems that exhibit multiple metastable morphologies, the proposed Monte Carlo method is generally able to identify lower free energy states that are often missed by traditional approaches. Importantly, the Monte Carlo method identifies such states from random initial configurations, thereby obviating the need for educated initial guesses that can be difficult to formulate.« less

Theoretically informed Monte Carlo simulation of liquid crystals by sampling of alignment-tensor fields

DOE Office of Scientific and Technical Information (OSTI.GOV)

Armas-Pérez, Julio C.; Londono-Hurtado, Alejandro; Guzmán, Orlando

2015-07-28

A theoretically informed coarse-grained Monte Carlo method is proposed for studying liquid crystals. The free energy functional of the system is described in the framework of the Landau-de Gennes formalism. The alignment field and its gradients are approximated by finite differences, and the free energy is minimized through a stochastic sampling technique. The validity of the proposed method is established by comparing the results of the proposed approach to those of traditional free energy minimization techniques. Its usefulness is illustrated in the context of three systems, namely, a nematic liquid crystal confined in a slit channel, a nematic liquid crystalmore » droplet, and a chiral liquid crystal in the bulk. It is found that for systems that exhibit multiple metastable morphologies, the proposed Monte Carlo method is generally able to identify lower free energy states that are often missed by traditional approaches. Importantly, the Monte Carlo method identifies such states from random initial configurations, thereby obviating the need for educated initial guesses that can be difficult to formulate.« less

Performance of quantum Monte Carlo for calculating molecular bond lengths

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cleland, Deidre M., E-mail: deidre.cleland@csiro.au; Per, Manolo C., E-mail: manolo.per@csiro.au

2016-03-28

This work investigates the accuracy of real-space quantum Monte Carlo (QMC) methods for calculating molecular geometries. We present the equilibrium bond lengths of a test set of 30 diatomic molecules calculated using variational Monte Carlo (VMC) and diffusion Monte Carlo (DMC) methods. The effect of different trial wavefunctions is investigated using single determinants constructed from Hartree-Fock (HF) and Density Functional Theory (DFT) orbitals with LDA, PBE, and B3LYP functionals, as well as small multi-configurational self-consistent field (MCSCF) multi-determinant expansions. When compared to experimental geometries, all DMC methods exhibit smaller mean-absolute deviations (MADs) than those given by HF, DFT, and MCSCF.more » The most accurate MAD of 3 ± 2 × 10{sup −3} Å is achieved using DMC with a small multi-determinant expansion. However, the more computationally efficient multi-determinant VMC method has a similar MAD of only 4.0 ± 0.9 × 10{sup −3} Å, suggesting that QMC forces calculated from the relatively simple VMC algorithm may often be sufficient for accurate molecular geometries.« less

Towards predicting the encoding capability of MR fingerprinting sequences.

PubMed

Sommer, K; Amthor, T; Doneva, M; Koken, P; Meineke, J; Börnert, P

2017-09-01

Sequence optimization and appropriate sequence selection is still an unmet need in magnetic resonance fingerprinting (MRF). The main challenge in MRF sequence design is the lack of an appropriate measure of the sequence's encoding capability. To find such a measure, three different candidates for judging the encoding capability have been investigated: local and global dot-product-based measures judging dictionary entry similarity as well as a Monte Carlo method that evaluates the noise propagation properties of an MRF sequence. Consistency of these measures for different sequence lengths as well as the capability to predict actual sequence performance in both phantom and in vivo measurements was analyzed. While the dot-product-based measures yielded inconsistent results for different sequence lengths, the Monte Carlo method was in a good agreement with phantom experiments. In particular, the Monte Carlo method could accurately predict the performance of different flip angle patterns in actual measurements. The proposed Monte Carlo method provides an appropriate measure of MRF sequence encoding capability and may be used for sequence optimization. Copyright © 2017 Elsevier Inc. All rights reserved.

Multiscale Monte Carlo equilibration: Pure Yang-Mills theory

DOE PAGES

Endres, Michael G.; Brower, Richard C.; Orginos, Kostas; ...

2015-12-29

In this study, we present a multiscale thermalization algorithm for lattice gauge theory, which enables efficient parallel generation of uncorrelated gauge field configurations. The algorithm combines standard Monte Carlo techniques with ideas drawn from real space renormalization group and multigrid methods. We demonstrate the viability of the algorithm for pure Yang-Mills gauge theory for both heat bath and hybrid Monte Carlo evolution, and show that it ameliorates the problem of topological freezing up to controllable lattice spacing artifacts.

Adaptive Monte Carlo methods

NASA Astrophysics Data System (ADS)

Fasnacht, Marc

We develop adaptive Monte Carlo methods for the calculation of the free energy as a function of a parameter of interest. The methods presented are particularly well-suited for systems with complex energy landscapes, where standard sampling techniques have difficulties. The Adaptive Histogram Method uses a biasing potential derived from histograms recorded during the simulation to achieve uniform sampling in the parameter of interest. The Adaptive Integration method directly calculates an estimate of the free energy from the average derivative of the Hamiltonian with respect to the parameter of interest and uses it as a biasing potential. We compare both methods to a state of the art method, and demonstrate that they compare favorably for the calculation of potentials of mean force of dense Lennard-Jones fluids. We use the Adaptive Integration Method to calculate accurate potentials of mean force for different types of simple particles in a Lennard-Jones fluid. Our approach allows us to separate the contributions of the solvent to the potential of mean force from the effect of the direct interaction between the particles. With contributions of the solvent determined, we can find the potential of mean force directly for any other direct interaction without additional simulations. We also test the accuracy of the Adaptive Integration Method on a thermodynamic cycle, which allows us to perform a consistency check between potentials of mean force and chemical potentials calculated using the Adaptive Integration Method. The results demonstrate a high degree of consistency of the method.

Knot probability of polygons subjected to a force: a Monte Carlo study

NASA Astrophysics Data System (ADS)

Janse van Rensburg, E. J.; Orlandini, E.; Tesi, M. C.; Whittington, S. G.

2008-01-01

We use Monte Carlo methods to study the knot probability of lattice polygons on the cubic lattice in the presence of an external force f. The force is coupled to the span of the polygons along a lattice direction, say the z-direction. If the force is negative polygons are squeezed (the compressive regime), while positive forces tend to stretch the polygons along the z-direction (the tensile regime). For sufficiently large positive forces we verify that the Pincus scaling law in the force-extension curve holds. At a fixed number of edges n the knot probability is a decreasing function of the force. For a fixed force the knot probability approaches unity as 1 - exp(-α0(f)n + o(n)), where α0(f) is positive and a decreasing function of f. We also examine the average of the absolute value of the writhe and we verify the square root growth law (known for f = 0) for all values of f.

3D Monte Carlo model with direct photon flux recording for optimal optogenetic light delivery

NASA Astrophysics Data System (ADS)

Shin, Younghoon; Kim, Dongmok; Lee, Jihoon; Kwon, Hyuk-Sang

2017-02-01

Configuring the light power emitted from the optical fiber is an essential first step in planning in-vivo optogenetic experiments. However, diffusion theory, which was adopted for optogenetic research, precluded accurate estimates of light intensity in the semi-diffusive region where the primary locus of the stimulation is located. We present a 3D Monte Carlo model that provides an accurate and direct solution for light distribution in this region. Our method directly records the photon trajectory in the separate volumetric grid planes for the near-source recording efficiency gain, and it incorporates a 3D brain mesh to support both homogeneous and heterogeneous brain tissue. We investigated the light emitted from optical fibers in brain tissue in 3D, and we applied the results to design optimal light delivery parameters for precise optogenetic manipulation by considering the fiber output power, wavelength, fiber-to-target distance, and the area of neural tissue activation.

Collisional Evolution of the Enceladus Neutral Cloud

NASA Technical Reports Server (NTRS)

Cassidy, T. A.; Johnson, R. E.; Hendrix, A. R.

2011-01-01

Water vapor ejected from Saturn's small moon Enceladus easily escapes its meager gravity to form a Saturn-encircling cloud with a low collision rate. Observations show that the cloud is quite broad in the radial direction, and we show here that collisions, though quite rare, may be largely responsible for this radial spreading. We modeled this cloud using the Direct Simulation Monte Carlo method, as fluid methods would be inappropriate for such a tenuous gas.

A Lattice Kinetic Monte Carlo Solver for First-Principles Microkinetic Trend Studies

DOE PAGES

Hoffmann, Max J.; Bligaard, Thomas

2018-01-22

Here, mean-field microkinetic models in combination with Brønsted–Evans–Polanyi like scaling relations have proven highly successful in identifying catalyst materials with good or promising reactivity and selectivity. Analysis of the microkinetic model by means of lattice kinetic Monte Carlo promises a faithful description of a range of atomistic features involving short-range ordering of species in the vicinity of an active site. In this paper, we use the “fruit fly” example reaction of CO oxidation on fcc(111) transition and coinage metals to motivate and develop a lattice kinetic Monte Carlo solver suitable for the numerically challenging case of vastly disparate rate constants.more » As a result, we show that for the case of infinitely fast diffusion and absence of adsorbate-adsorbate interaction it is, in fact, possible to match the prediction of the mean-field-theory method and the lattice kinetic Monte Carlo method. As a corollary, we conclude that lattice kinetic Monte Carlo simulations of surface chemical reactions are most likely to provide additional insight over mean-field simulations if diffusion limitations or adsorbate–adsorbate interactions have a significant influence on the mixing of the adsorbates.« less

A Monte Carlo method for the simulation of coagulation and nucleation based on weighted particles and the concepts of stochastic resolution and merging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kotalczyk, G., E-mail: Gregor.Kotalczyk@uni-due.de; Kruis, F.E.

Monte Carlo simulations based on weighted simulation particles can solve a variety of population balance problems and allow thus to formulate a solution-framework for many chemical engineering processes. This study presents a novel concept for the calculation of coagulation rates of weighted Monte Carlo particles by introducing a family of transformations to non-weighted Monte Carlo particles. The tuning of the accuracy (named ‘stochastic resolution’ in this paper) of those transformations allows the construction of a constant-number coagulation scheme. Furthermore, a parallel algorithm for the inclusion of newly formed Monte Carlo particles due to nucleation is presented in the scope ofmore » a constant-number scheme: the low-weight merging. This technique is found to create significantly less statistical simulation noise than the conventional technique (named ‘random removal’ in this paper). Both concepts are combined into a single GPU-based simulation method which is validated by comparison with the discrete-sectional simulation technique. Two test models describing a constant-rate nucleation coupled to a simultaneous coagulation in 1) the free-molecular regime or 2) the continuum regime are simulated for this purpose.« less

A Lattice Kinetic Monte Carlo Solver for First-Principles Microkinetic Trend Studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hoffmann, Max J.; Bligaard, Thomas

Here, mean-field microkinetic models in combination with Brønsted–Evans–Polanyi like scaling relations have proven highly successful in identifying catalyst materials with good or promising reactivity and selectivity. Analysis of the microkinetic model by means of lattice kinetic Monte Carlo promises a faithful description of a range of atomistic features involving short-range ordering of species in the vicinity of an active site. In this paper, we use the “fruit fly” example reaction of CO oxidation on fcc(111) transition and coinage metals to motivate and develop a lattice kinetic Monte Carlo solver suitable for the numerically challenging case of vastly disparate rate constants.more » As a result, we show that for the case of infinitely fast diffusion and absence of adsorbate-adsorbate interaction it is, in fact, possible to match the prediction of the mean-field-theory method and the lattice kinetic Monte Carlo method. As a corollary, we conclude that lattice kinetic Monte Carlo simulations of surface chemical reactions are most likely to provide additional insight over mean-field simulations if diffusion limitations or adsorbate–adsorbate interactions have a significant influence on the mixing of the adsorbates.« less

Molecular Monte Carlo Simulations Using Graphics Processing Units: To Waste Recycle or Not?

PubMed

Kim, Jihan; Rodgers, Jocelyn M; Athènes, Manuel; Smit, Berend

2011-10-11

In the waste recycling Monte Carlo (WRMC) algorithm, (1) multiple trial states may be simultaneously generated and utilized during Monte Carlo moves to improve the statistical accuracy of the simulations, suggesting that such an algorithm may be well posed for implementation in parallel on graphics processing units (GPUs). In this paper, we implement two waste recycling Monte Carlo algorithms in CUDA (Compute Unified Device Architecture) using uniformly distributed random trial states and trial states based on displacement random-walk steps, and we test the methods on a methane-zeolite MFI framework system to evaluate their utility. We discuss the specific implementation details of the waste recycling GPU algorithm and compare the methods to other parallel algorithms optimized for the framework system. We analyze the relationship between the statistical accuracy of our simulations and the CUDA block size to determine the efficient allocation of the GPU hardware resources. We make comparisons between the GPU and the serial CPU Monte Carlo implementations to assess speedup over conventional microprocessors. Finally, we apply our optimized GPU algorithms to the important problem of determining free energy landscapes, in this case for molecular motion through the zeolite LTA.

Importance Sampling of Word Patterns in DNA and Protein Sequences

PubMed Central

Chan, Hock Peng; Chen, Louis H.Y.

2010-01-01

Abstract Monte Carlo methods can provide accurate p-value estimates of word counting test statistics and are easy to implement. They are especially attractive when an asymptotic theory is absent or when either the search sequence or the word pattern is too short for the application of asymptotic formulae. Naive direct Monte Carlo is undesirable for the estimation of small probabilities because the associated rare events of interest are seldom generated. We propose instead efficient importance sampling algorithms that use controlled insertion of the desired word patterns on randomly generated sequences. The implementation is illustrated on word patterns of biological interest: palindromes and inverted repeats, patterns arising from position-specific weight matrices (PSWMs), and co-occurrences of pairs of motifs. PMID:21128856

TU-F-17A-08: The Relative Accuracy of 4D Dose Accumulation for Lung Radiotherapy Using Rigid Dose Projection Versus Dose Recalculation On Every Breathing Phase

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lamb, J; Lee, C; Tee, S

2014-06-15

Purpose: To investigate the accuracy of 4D dose accumulation using projection of dose calculated on the end-exhalation, mid-ventilation, or average intensity breathing phase CT scan, versus dose accumulation performed using full Monte Carlo dose recalculation on every breathing phase. Methods: Radiotherapy plans were analyzed for 10 patients with stage I-II lung cancer planned using 4D-CT. SBRT plans were optimized using the dose calculated by a commercially-available Monte Carlo algorithm on the end-exhalation 4D-CT phase. 4D dose accumulations using deformable registration were performed with a commercially available tool that projected the planned dose onto every breathing phase without recalculation, as wellmore » as with a Monte Carlo recalculation of the dose on all breathing phases. The 3D planned dose (3D-EX), the 3D dose calculated on the average intensity image (3D-AVE), and the 4D accumulations of the dose calculated on the end-exhalation phase CT (4D-PR-EX), the mid-ventilation phase CT (4D-PR-MID), and the average intensity image (4D-PR-AVE), respectively, were compared against the accumulation of the Monte Carlo dose recalculated on every phase. Plan evaluation metrics relating to target volumes and critical structures relevant for lung SBRT were analyzed. Results: Plan evaluation metrics tabulated using 4D-PR-EX, 4D-PR-MID, and 4D-PR-AVE differed from those tabulated using Monte Carlo recalculation on every phase by an average of 0.14±0.70 Gy, - 0.11±0.51 Gy, and 0.00±0.62 Gy, respectively. Deviations of between 8 and 13 Gy were observed between the 4D-MC calculations and both 3D methods for the proximal bronchial trees of 3 patients. Conclusions: 4D dose accumulation using projection without re-calculation may be sufficiently accurate compared to 4D dose accumulated from Monte Carlo recalculation on every phase, depending on institutional protocols. Use of 4D dose accumulation should be considered when evaluating normal tissue complication probabilities as well as in clinical situations where target volumes are directly inferior to mobile critical structures.« less

Ex Post Facto Monte Carlo Variance Reduction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Booth, Thomas E.

The variance in Monte Carlo particle transport calculations is often dominated by a few particles whose importance increases manyfold on a single transport step. This paper describes a novel variance reduction method that uses a large importance change as a trigger to resample the offending transport step. That is, the method is employed only after (ex post facto) a random walk attempts a transport step that would otherwise introduce a large variance in the calculation.Improvements in two Monte Carlo transport calculations are demonstrated empirically using an ex post facto method. First, the method is shown to reduce the variance inmore » a penetration problem with a cross-section window. Second, the method empirically appears to modify a point detector estimator from an infinite variance estimator to a finite variance estimator.« less

Automatic variance reduction for Monte Carlo simulations via the local importance function transform

DOE Office of Scientific and Technical Information (OSTI.GOV)

Turner, S.A.

1996-02-01

The author derives a transformed transport problem that can be solved theoretically by analog Monte Carlo with zero variance. However, the Monte Carlo simulation of this transformed problem cannot be implemented in practice, so he develops a method for approximating it. The approximation to the zero variance method consists of replacing the continuous adjoint transport solution in the transformed transport problem by a piecewise continuous approximation containing local biasing parameters obtained from a deterministic calculation. He uses the transport and collision processes of the transformed problem to bias distance-to-collision and selection of post-collision energy groups and trajectories in a traditionalmore » Monte Carlo simulation of ``real`` particles. He refers to the resulting variance reduction method as the Local Importance Function Transform (LIFI) method. He demonstrates the efficiency of the LIFT method for several 3-D, linearly anisotropic scattering, one-group, and multigroup problems. In these problems the LIFT method is shown to be more efficient than the AVATAR scheme, which is one of the best variance reduction techniques currently available in a state-of-the-art Monte Carlo code. For most of the problems considered, the LIFT method produces higher figures of merit than AVATAR, even when the LIFT method is used as a ``black box``. There are some problems that cause trouble for most variance reduction techniques, and the LIFT method is no exception. For example, the author demonstrates that problems with voids, or low density regions, can cause a reduction in the efficiency of the LIFT method. However, the LIFT method still performs better than survival biasing and AVATAR in these difficult cases.« less

Stabilizing canonical-ensemble calculations in the auxiliary-field Monte Carlo method

NASA Astrophysics Data System (ADS)

Gilbreth, C. N.; Alhassid, Y.

2015-03-01

Quantum Monte Carlo methods are powerful techniques for studying strongly interacting Fermi systems. However, implementing these methods on computers with finite-precision arithmetic requires careful attention to numerical stability. In the auxiliary-field Monte Carlo (AFMC) method, low-temperature or large-model-space calculations require numerically stabilized matrix multiplication. When adapting methods used in the grand-canonical ensemble to the canonical ensemble of fixed particle number, the numerical stabilization increases the number of required floating-point operations for computing observables by a factor of the size of the single-particle model space, and thus can greatly limit the systems that can be studied. We describe an improved method for stabilizing canonical-ensemble calculations in AFMC that exhibits better scaling, and present numerical tests that demonstrate the accuracy and improved performance of the method.

Rapid Monte Carlo Simulation of Gravitational Wave Galaxies

NASA Astrophysics Data System (ADS)

Breivik, Katelyn; Larson, Shane L.

2015-01-01

With the detection of gravitational waves on the horizon, astrophysical catalogs produced by gravitational wave observatories can be used to characterize the populations of sources and validate different galactic population models. Efforts to simulate gravitational wave catalogs and source populations generally focus on population synthesis models that require extensive time and computational power to produce a single simulated galaxy. Monte Carlo simulations of gravitational wave source populations can also be used to generate observation catalogs from the gravitational wave source population. Monte Carlo simulations have the advantes of flexibility and speed, enabling rapid galactic realizations as a function of galactic binary parameters with less time and compuational resources required. We present a Monte Carlo method for rapid galactic simulations of gravitational wave binary populations.

Propagation of uncertainty in nasal spray in vitro performance models using Monte Carlo simulation: Part II. Error propagation during product performance modeling.

PubMed

Guo, Changning; Doub, William H; Kauffman, John F

2010-08-01

Monte Carlo simulations were applied to investigate the propagation of uncertainty in both input variables and response measurements on model prediction for nasal spray product performance design of experiment (DOE) models in the first part of this study, with an initial assumption that the models perfectly represent the relationship between input variables and the measured responses. In this article, we discard the initial assumption, and extended the Monte Carlo simulation study to examine the influence of both input variable variation and product performance measurement variation on the uncertainty in DOE model coefficients. The Monte Carlo simulations presented in this article illustrate the importance of careful error propagation during product performance modeling. Our results show that the error estimates based on Monte Carlo simulation result in smaller model coefficient standard deviations than those from regression methods. This suggests that the estimated standard deviations from regression may overestimate the uncertainties in the model coefficients. Monte Carlo simulations provide a simple software solution to understand the propagation of uncertainty in complex DOE models so that design space can be specified with statistically meaningful confidence levels. (c) 2010 Wiley-Liss, Inc. and the American Pharmacists Association

OBJECT KINETIC MONTE CARLO SIMULATIONS OF CASCADE ANNEALING IN TUNGSTEN

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nandipati, Giridhar; Setyawan, Wahyu; Heinisch, Howard L.

2014-03-31

The objective of this work is to study the annealing of primary cascade damage created by primary knock-on atoms (PKAs) of various energies, at various temperatures in bulk tungsten using the object kinetic Monte Carlo (OKMC) method.

Monte Carlo Method for Determining Earthquake Recurrence Parameters from Short Paleoseismic Catalogs: Example Calculations for California

USGS Publications Warehouse

Parsons, Tom

2008-01-01

Paleoearthquake observations often lack enough events at a given site to directly define a probability density function (PDF) for earthquake recurrence. Sites with fewer than 10-15 intervals do not provide enough information to reliably determine the shape of the PDF using standard maximum-likelihood techniques [e.g., Ellsworth et al., 1999]. In this paper I present a method that attempts to fit wide ranges of distribution parameters to short paleoseismic series. From repeated Monte Carlo draws, it becomes possible to quantitatively estimate most likely recurrence PDF parameters, and a ranked distribution of parameters is returned that can be used to assess uncertainties in hazard calculations. In tests on short synthetic earthquake series, the method gives results that cluster around the mean of the input distribution, whereas maximum likelihood methods return the sample means [e.g., NIST/SEMATECH, 2006]. For short series (fewer than 10 intervals), sample means tend to reflect the median of an asymmetric recurrence distribution, possibly leading to an overestimate of the hazard should they be used in probability calculations. Therefore a Monte Carlo approach may be useful for assessing recurrence from limited paleoearthquake records. Further, the degree of functional dependence among parameters like mean recurrence interval and coefficient of variation can be established. The method is described for use with time-independent and time-dependent PDF?s, and results from 19 paleoseismic sequences on strike-slip faults throughout the state of California are given.

Monte Carlo method for determining earthquake recurrence parameters from short paleoseismic catalogs: Example calculations for California

USGS Publications Warehouse

Parsons, T.

2008-01-01

Paleoearthquake observations often lack enough events at a given site to directly define a probability density function (PDF) for earthquake recurrence. Sites with fewer than 10-15 intervals do not provide enough information to reliably determine the shape of the PDF using standard maximum-likelihood techniques (e.g., Ellsworth et al., 1999). In this paper I present a method that attempts to fit wide ranges of distribution parameters to short paleoseismic series. From repeated Monte Carlo draws, it becomes possible to quantitatively estimate most likely recurrence PDF parameters, and a ranked distribution of parameters is returned that can be used to assess uncertainties in hazard calculations. In tests on short synthetic earthquake series, the method gives results that cluster around the mean of the input distribution, whereas maximum likelihood methods return the sample means (e.g., NIST/SEMATECH, 2006). For short series (fewer than 10 intervals), sample means tend to reflect the median of an asymmetric recurrence distribution, possibly leading to an overestimate of the hazard should they be used in probability calculations. Therefore a Monte Carlo approach may be useful for assessing recurrence from limited paleoearthquake records. Further, the degree of functional dependence among parameters like mean recurrence interval and coefficient of variation can be established. The method is described for use with time-independent and time-dependent PDFs, and results from 19 paleoseismic sequences on strike-slip faults throughout the state of California are given.

The Wang-Landau Sampling Algorithm

NASA Astrophysics Data System (ADS)

Landau, David P.

2003-03-01

Over the past several decades Monte Carlo simulations[1] have evolved into a powerful tool for the study of wide-ranging problems in statistical/condensed matter physics. Standard methods sample the probability distribution for the states of the system, usually in the canonical ensemble, and enormous improvements have been made in performance through the implementation of novel algorithms. Nonetheless, difficulties arise near phase transitions, either due to critical slowing down near 2nd order transitions or to metastability near 1st order transitions, thus limiting the applicability of the method. We shall describe a new and different Monte Carlo approach [2] that uses a random walk in energy space to determine the density of states directly. Once the density of states is estimated, all thermodynamic properties can be calculated at all temperatures. This approach can be extended to multi-dimensional parameter spaces and has already found use in classical models of interacting particles including systems with complex energy landscapes, e.g., spin glasses, protein folding models, etc., as well as for quantum models. 1. A Guide to Monte Carlo Simulations in Statistical Physics, D. P. Landau and K. Binder (Cambridge U. Press, Cambridge, 2000). 2. Fugao Wang and D. P. Landau, Phys. Rev. Lett. 86, 2050 (2001); Phys. Rev. E64, 056101-1 (2001).

Molecular gas dynamics applied to low-thrust propulsion

NASA Astrophysics Data System (ADS)

Zelesnik, Donna; Penko, Paul F.; Boyd, Iain D.

1993-11-01

The Direct Simulation Monte Carlo method is currently being applied to study flowfields of small thrusters, including both the internal nozzle and the external plume flow. The DSMC method is employed because of its inherent ability to capture nonequilibrium effects and proper boundary physics in low-density flow that are not readily obtained by continuum methods. Accurate prediction of both the internal and external nozzle flow is important in determining plume expansion which, in turn, bears directly on impingement and contamination effects.

Molecular gas dynamics applied to low-thrust propulsion

NASA Technical Reports Server (NTRS)

Zelesnik, Donna; Penko, Paul F.; Boyd, Iain D.

1993-01-01

The Direct Simulation Monte Carlo method is currently being applied to study flowfields of small thrusters, including both the internal nozzle and the external plume flow. The DSMC method is employed because of its inherent ability to capture nonequilibrium effects and proper boundary physics in low-density flow that are not readily obtained by continuum methods. Accurate prediction of both the internal and external nozzle flow is important in determining plume expansion which, in turn, bears directly on impingement and contamination effects.

Improved Convergence Rate of Multi-Group Scattering Moment Tallies for Monte Carlo Neutron Transport Codes

NASA Astrophysics Data System (ADS)

Nelson, Adam

Multi-group scattering moment matrices are critical to the solution of the multi-group form of the neutron transport equation, as they are responsible for describing the change in direction and energy of neutrons. These matrices, however, are difficult to correctly calculate from the measured nuclear data with both deterministic and stochastic methods. Calculating these parameters when using deterministic methods requires a set of assumptions which do not hold true in all conditions. These quantities can be calculated accurately with stochastic methods, however doing so is computationally expensive due to the poor efficiency of tallying scattering moment matrices. This work presents an improved method of obtaining multi-group scattering moment matrices from a Monte Carlo neutron transport code. This improved method of tallying the scattering moment matrices is based on recognizing that all of the outgoing particle information is known a priori and can be taken advantage of to increase the tallying efficiency (therefore reducing the uncertainty) of the stochastically integrated tallies. In this scheme, the complete outgoing probability distribution is tallied, supplying every one of the scattering moment matrices elements with its share of data. In addition to reducing the uncertainty, this method allows for the use of a track-length estimation process potentially offering even further improvement to the tallying efficiency. Unfortunately, to produce the needed distributions, the probability functions themselves must undergo an integration over the outgoing energy and scattering angle dimensions. This integration is too costly to perform during the Monte Carlo simulation itself and therefore must be performed in advance by way of a pre-processing code. The new method increases the information obtained from tally events and therefore has a significantly higher efficiency than the currently used techniques. The improved method has been implemented in a code system containing a new pre-processor code, NDPP, and a Monte Carlo neutron transport code, OpenMC. This method is then tested in a pin cell problem and a larger problem designed to accentuate the importance of scattering moment matrices. These tests show that accuracy was retained while the figure-of-merit for generating scattering moment matrices and fission energy spectra was significantly improved.

Monte Carlo calculation of large and small-angle electron scattering in air

NASA Astrophysics Data System (ADS)

Cohen, B. I.; Higginson, D. P.; Eng, C. D.; Farmer, W. A.; Friedman, A.; Grote, D. P.; Larson, D. J.

2017-11-01

A Monte Carlo method for angle scattering of electrons in air that accommodates the small-angle multiple scattering and larger-angle single scattering limits is introduced. The algorithm is designed for use in a particle-in-cell simulation of electron transport and electromagnetic wave effects in air. The method is illustrated in example calculations.

Estimation of parameters and basic reproduction ratio for Japanese encephalitis transmission in the Philippines using sequential Monte Carlo filter

USDA-ARS?s Scientific Manuscript database

We developed a sequential Monte Carlo filter to estimate the states and the parameters in a stochastic model of Japanese Encephalitis (JE) spread in the Philippines. This method is particularly important for its adaptability to the availability of new incidence data. This method can also capture the...

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hiller, Mauritius M.; Veinot, Kenneth G.; Easterly, Clay E.

In this study, methods are addressed to reduce the computational time to compute organ-dose rate coefficients using Monte Carlo techniques. Several variance reduction techniques are compared including the reciprocity method, importance sampling, weight windows and the use of the ADVANTG software package. For low-energy photons, the runtime was reduced by a factor of 10 5 when using the reciprocity method for kerma computation for immersion of a phantom in contaminated water. This is particularly significant since impractically long simulation times are required to achieve reasonable statistical uncertainties in organ dose for low-energy photons in this source medium and geometry. Althoughmore » the MCNP Monte Carlo code is used in this paper, the reciprocity technique can be used equally well with other Monte Carlo codes.« less

Conserved directed percolation: exact quasistationary distribution of small systems and Monte Carlo simulations

NASA Astrophysics Data System (ADS)

César Mansur Filho, Júlio; Dickman, Ronald

2011-05-01

We study symmetric sleepy random walkers, a model exhibiting an absorbing-state phase transition in the conserved directed percolation (CDP) universality class. Unlike most examples of this class studied previously, this model possesses a continuously variable control parameter, facilitating analysis of critical properties. We study the model using two complementary approaches: analysis of the numerically exact quasistationary (QS) probability distribution on rings of up to 22 sites, and Monte Carlo simulation of systems of up to 32 000 sites. The resulting estimates for critical exponents β, \\beta /\

Monte Carlo Simulations of Microchannel Plate Based, Fast-Gated X-Ray Imagers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu., M., Kruschwitz, C.

2011-02-01

This is a chapter in a book titled Applications of Monte Carlo Method in Science and Engineering Edited by: Shaul Mordechai ISBN 978-953-307-691-1, Hard cover, 950 pages Publisher: InTech Publication date: February 2011

MODELING LEACHING OF VIRUSES BY THE MONTE CARLO METHOD

EPA Science Inventory

A predictive screening model was developed for fate and transport
of viruses in the unsaturated zone. A database of input parameters
allowed Monte Carlo analysis with the model. The resulting kernel
densities of predicted attenuation during percolation indicated very ...

Probabilistic power flow using improved Monte Carlo simulation method with correlated wind sources

NASA Astrophysics Data System (ADS)

Bie, Pei; Zhang, Buhan; Li, Hang; Deng, Weisi; Wu, Jiasi

2017-01-01

Probabilistic Power Flow (PPF) is a very useful tool for power system steady-state analysis. However, the correlation among different random injection power (like wind power) brings great difficulties to calculate PPF. Monte Carlo simulation (MCS) and analytical methods are two commonly used methods to solve PPF. MCS has high accuracy but is very time consuming. Analytical method like cumulants method (CM) has high computing efficiency but the cumulants calculating is not convenient when wind power output does not obey any typical distribution, especially when correlated wind sources are considered. In this paper, an Improved Monte Carlo simulation method (IMCS) is proposed. The joint empirical distribution is applied to model different wind power output. This method combines the advantages of both MCS and analytical method. It not only has high computing efficiency, but also can provide solutions with enough accuracy, which is very suitable for on-line analysis.

A comparative study of Conroy and Monte Carlo methods applied to multiple quadratures and multiple scattering

NASA Technical Reports Server (NTRS)

Deepak, A.; Fluellen, A.

1978-01-01

An efficient numerical method of multiple quadratures, the Conroy method, is applied to the problem of computing multiple scattering contributions in the radiative transfer through realistic planetary atmospheres. A brief error analysis of the method is given and comparisons are drawn with the more familiar Monte Carlo method. Both methods are stochastic problem-solving models of a physical or mathematical process and utilize the sampling scheme for points distributed over a definite region. In the Monte Carlo scheme the sample points are distributed randomly over the integration region. In the Conroy method, the sample points are distributed systematically, such that the point distribution forms a unique, closed, symmetrical pattern which effectively fills the region of the multidimensional integration. The methods are illustrated by two simple examples: one, of multidimensional integration involving two independent variables, and the other, of computing the second order scattering contribution to the sky radiance.

Comparisons of Wilks’ and Monte Carlo Methods in Response to the 10CFR50.46(c) Proposed Rulemaking

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Hongbin; Szilard, Ronaldo; Zou, Ling

The Nuclear Regulatory Commission (NRC) is proposing a new rulemaking on emergency core system/loss-of-coolant accident (LOCA) performance analysis. In the proposed rulemaking, designated as 10CFR50.46(c), the US NRC put forward an equivalent cladding oxidation criterion as a function of cladding pre-transient hydrogen content. The proposed rulemaking imposes more restrictive and burnup-dependent cladding embrittlement criteria; consequently nearly all the fuel rods in a reactor core need to be analyzed under LOCA conditions to demonstrate compliance to the safety limits. New analysis methods are required to provide a thorough characterization of the reactor core in order to identify the locations of themore » limiting rods as well as to quantify the safety margins under LOCA conditions. With the new analysis method presented in this work, the limiting transient case and the limiting rods can be easily identified to quantify the safety margins in response to the proposed new rulemaking. In this work, the best-estimate plus uncertainty (BEPU) analysis capability for large break LOCA with the new cladding embrittlement criteria using the RELAP5-3D code is established and demonstrated with a reduced set of uncertainty parameters. Both the direct Monte Carlo method and the Wilks’ nonparametric statistical method can be used to perform uncertainty quantification. Wilks’ method has become the de-facto industry standard to perform uncertainty quantification in BEPU LOCA analyses. Despite its widespread adoption by the industry, the use of small sample sizes to infer statement of compliance to the existing 10CFR50.46 rule, has been a major cause of unrealized operational margin in today’s BEPU methods. Moreover the debate on the proper interpretation of the Wilks’ theorem in the context of safety analyses is not fully resolved yet, even more than two decades after its introduction in the frame of safety analyses in the nuclear industry. This represents both a regulatory and application risk in rolling out new methods. With the 10CFR50.46(c) proposed rulemaking, the deficiencies of the Wilks’ approach are further exacerbated. The direct Monte Carlo approach offers a robust alternative to perform uncertainty quantification within the context of BEPU analyses. In this work, the Monte Carlo method is compared with the Wilks’ method in response to the NRC 10CFR50.46(c) proposed rulemaking.« less

SU-E-T-455: Characterization of 3D Printed Materials for Proton Beam Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zou, W; Siderits, R; McKenna, M

2014-06-01

Purpose: The widespread availability of low cost 3D printing technologies provides an alternative fabrication method for customized proton range modifying accessories such as compensators and boluses. However the material properties of the printed object are dependent on the printing technology used. In order to facilitate the application of 3D printing in proton therapy, this study investigated the stopping power of several printed materials using both proton pencil beam measurements and Monte Carlo simulations. Methods: Five 3–4 cm cubes fabricated using three 3D printing technologies (selective laser sintering, fused-deposition modeling and stereolithography) from five printers were investigated. The cubes were scannedmore » on a CT scanner and the depth dose curves for a mono-energetic pencil beam passing through the material were measured using a large parallel plate ion chamber in a water tank. Each cube was measured from two directions (perpendicular and parallel to printing plane) to evaluate the effects of the anisotropic material layout. The results were compared with GEANT4 Monte Carlo simulation using the manufacturer specified material density and chemical composition data. Results: Compared with water, the differences from the range pull back by the printed blocks varied and corresponded well with the material CT Hounsfield unit. The measurement results were in agreement with Monte Carlo simulation. However, depending on the technology, inhomogeneity existed in the printed cubes evidenced from CT images. The effect of such inhomogeneity on the proton beam is to be investigated. Conclusion: Printed blocks by three different 3D printing technologies were characterized for proton beam with measurements and Monte Carlo simulation. The effects of the printing technologies in proton range and stopping power were studied. The derived results can be applied when specific devices are used in proton radiotherapy.« less

Impact of reconstruction parameters on quantitative I-131 SPECT

NASA Astrophysics Data System (ADS)

van Gils, C. A. J.; Beijst, C.; van Rooij, R.; de Jong, H. W. A. M.

2016-07-01

Radioiodine therapy using I-131 is widely used for treatment of thyroid disease or neuroendocrine tumors. Monitoring treatment by accurate dosimetry requires quantitative imaging. The high energy photons however render quantitative SPECT reconstruction challenging, potentially requiring accurate correction for scatter and collimator effects. The goal of this work is to assess the effectiveness of various correction methods on these effects using phantom studies. A SPECT/CT acquisition of the NEMA IEC body phantom was performed. Images were reconstructed using the following parameters: (1) without scatter correction, (2) with triple energy window (TEW) scatter correction and (3) with Monte Carlo-based scatter correction. For modelling the collimator-detector response (CDR), both (a) geometric Gaussian CDRs as well as (b) Monte Carlo simulated CDRs were compared. Quantitative accuracy, contrast to noise ratios and recovery coefficients were calculated, as well as the background variability and the residual count error in the lung insert. The Monte Carlo scatter corrected reconstruction method was shown to be intrinsically quantitative, requiring no experimentally acquired calibration factor. It resulted in a more accurate quantification of the background compartment activity density compared with TEW or no scatter correction. The quantification error relative to a dose calibrator derived measurement was found to be  <1%,-26% and 33%, respectively. The adverse effects of partial volume were significantly smaller with the Monte Carlo simulated CDR correction compared with geometric Gaussian or no CDR modelling. Scatter correction showed a small effect on quantification of small volumes. When using a weighting factor, TEW correction was comparable to Monte Carlo reconstruction in all measured parameters, although this approach is clinically impractical since this factor may be patient dependent. Monte Carlo based scatter correction including accurately simulated CDR modelling is the most robust and reliable method to reconstruct accurate quantitative iodine-131 SPECT images.

Fast multipurpose Monte Carlo simulation for proton therapy using multi- and many-core CPU architectures.

PubMed

Souris, Kevin; Lee, John Aldo; Sterpin, Edmond

2016-04-01

Accuracy in proton therapy treatment planning can be improved using Monte Carlo (MC) simulations. However the long computation time of such methods hinders their use in clinical routine. This work aims to develop a fast multipurpose Monte Carlo simulation tool for proton therapy using massively parallel central processing unit (CPU) architectures. A new Monte Carlo, called MCsquare (many-core Monte Carlo), has been designed and optimized for the last generation of Intel Xeon processors and Intel Xeon Phi coprocessors. These massively parallel architectures offer the flexibility and the computational power suitable to MC methods. The class-II condensed history algorithm of MCsquare provides a fast and yet accurate method of simulating heavy charged particles such as protons, deuterons, and alphas inside voxelized geometries. Hard ionizations, with energy losses above a user-specified threshold, are simulated individually while soft events are regrouped in a multiple scattering theory. Elastic and inelastic nuclear interactions are sampled from ICRU 63 differential cross sections, thereby allowing for the computation of prompt gamma emission profiles. MCsquare has been benchmarked with the gate/geant4 Monte Carlo application for homogeneous and heterogeneous geometries. Comparisons with gate/geant4 for various geometries show deviations within 2%-1 mm. In spite of the limited memory bandwidth of the coprocessor simulation time is below 25 s for 10(7) primary 200 MeV protons in average soft tissues using all Xeon Phi and CPU resources embedded in a single desktop unit. MCsquare exploits the flexibility of CPU architectures to provide a multipurpose MC simulation tool. Optimized code enables the use of accurate MC calculation within a reasonable computation time, adequate for clinical practice. MCsquare also simulates prompt gamma emission and can thus be used also for in vivo range verification.

WE-AB-204-11: Development of a Nuclear Medicine Dosimetry Module for the GPU-Based Monte Carlo Code ARCHER

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, T; Lin, H; Xu, X

Purpose: To develop a nuclear medicine dosimetry module for the GPU-based Monte Carlo code ARCHER. Methods: We have developed a nuclear medicine dosimetry module for the fast Monte Carlo code ARCHER. The coupled electron-photon Monte Carlo transport kernel included in ARCHER is built upon the Dose Planning Method code (DPM). The developed module manages the radioactive decay simulation by consecutively tracking several types of radiation on a per disintegration basis using the statistical sampling method. Optimization techniques such as persistent threads and prefetching are studied and implemented. The developed module is verified against the VIDA code, which is based onmore » Geant4 toolkit and has previously been verified against OLINDA/EXM. A voxelized geometry is used in the preliminary test: a sphere made of ICRP soft tissue is surrounded by a box filled with water. Uniform activity distribution of I-131 is assumed in the sphere. Results: The self-absorption dose factors (mGy/MBqs) of the sphere with varying diameters are calculated by ARCHER and VIDA respectively. ARCHER’s result is in agreement with VIDA’s that are obtained from a previous publication. VIDA takes hours of CPU time to finish the computation, while it takes ARCHER 4.31 seconds for the 12.4-cm uniform activity sphere case. For a fairer CPU-GPU comparison, more effort will be made to eliminate the algorithmic differences. Conclusion: The coupled electron-photon Monte Carlo code ARCHER has been extended to radioactive decay simulation for nuclear medicine dosimetry. The developed code exhibits good performance in our preliminary test. The GPU-based Monte Carlo code is developed with grant support from the National Institute of Biomedical Imaging and Bioengineering through an R01 grant (R01EB015478)« less

Multiscale Mathematics for Biomass Conversion to Renewable Hydrogen

DOE Office of Scientific and Technical Information (OSTI.GOV)

Katsoulakis, Markos

2014-08-09

Our two key accomplishments in the first three years were towards the development of, (1) a mathematically rigorous and at the same time computationally flexible framework for parallelization of Kinetic Monte Carlo methods, and its implementation on GPUs, and (2) spatial multilevel coarse-graining methods for Monte Carlo sampling and molecular simulation. A common underlying theme in both these lines of our work is the development of numerical methods which are at the same time both computationally efficient and reliable, the latter in the sense that they provide controlled-error approximations for coarse observables of the simulated molecular systems. Finally, our keymore » accomplishment in the last year of the grant is that we started developing (3) pathwise information theory-based and goal-oriented sensitivity analysis and parameter identification methods for complex high-dimensional dynamics and in particular of nonequilibrium extended (high-dimensional) systems. We discuss these three research directions in some detail below, along with the related publications.« less

Particle Methods for Simulating Atomic Radiation in Hypersonic Reentry Flows

NASA Astrophysics Data System (ADS)

Ozawa, T.; Wang, A.; Levin, D. A.; Modest, M.

2008-12-01

With a fast reentry speed, the Stardust vehicle generates a strong shock region ahead of its blunt body with a temperature above 60,000 K. These extreme Mach number flows are sufficiently energetic to initiate gas ionization processes and thermal and chemical ablation processes. The nonequilibrium gaseous radiation from the shock layer is so strong that it affects the flowfield macroparameter distributions. In this work, we present the first loosely coupled direct simulation Monte Carlo (DSMC) simulations with the particle-based photon Monte Carlo (p-PMC) method to simulate high-Mach number reentry flows in the near-continuum flow regime. To efficiently capture the highly nonequilibrium effects, emission and absorption cross section databases using the Nonequilibrium Air Radiation (NEQAIR) were generated, and atomic nitrogen and oxygen radiative transport was calculated by the p-PMC method. The radiation energy change calculated by the p-PMC method has been coupled in the DSMC calculations, and the atomic radiation was found to modify the flow field and heat flux at the wall.

Maximum-entropy reconstruction method for moment-based solution of the Boltzmann equation

NASA Astrophysics Data System (ADS)

Summy, Dustin; Pullin, Dale

2013-11-01

We describe a method for a moment-based solution of the Boltzmann equation. This starts with moment equations for a 10 + 9 N , N = 0 , 1 , 2 . . . -moment representation. The partial-differential equations (PDEs) for these moments are unclosed, containing both higher-order moments and molecular-collision terms. These are evaluated using a maximum-entropy construction of the velocity distribution function f (c , x , t) , using the known moments, within a finite-box domain of single-particle-velocity (c) space. Use of a finite-domain alleviates known problems (Junk and Unterreiter, Continuum Mech. Thermodyn., 2002) concerning existence and uniqueness of the reconstruction. Unclosed moments are evaluated with quadrature while collision terms are calculated using a Monte-Carlo method. This allows integration of the moment PDEs in time. Illustrative examples will include zero-space- dimensional relaxation of f (c , t) from a Mott-Smith-like initial condition toward equilibrium and one-space dimensional, finite Knudsen number, planar Couette flow. Comparison with results using the direct-simulation Monte-Carlo method will be presented.

Chemical accuracy from quantum Monte Carlo for the benzene dimer.

PubMed

Azadi, Sam; Cohen, R E

2015-09-14

We report an accurate study of interactions between benzene molecules using variational quantum Monte Carlo (VMC) and diffusion quantum Monte Carlo (DMC) methods. We compare these results with density functional theory using different van der Waals functionals. In our quantum Monte Carlo (QMC) calculations, we use accurate correlated trial wave functions including three-body Jastrow factors and backflow transformations. We consider two benzene molecules in the parallel displaced geometry, and find that by highly optimizing the wave function and introducing more dynamical correlation into the wave function, we compute the weak chemical binding energy between aromatic rings accurately. We find optimal VMC and DMC binding energies of -2.3(4) and -2.7(3) kcal/mol, respectively. The best estimate of the coupled-cluster theory through perturbative triplets/complete basis set limit is -2.65(2) kcal/mol [Miliordos et al., J. Phys. Chem. A 118, 7568 (2014)]. Our results indicate that QMC methods give chemical accuracy for weakly bound van der Waals molecular interactions, comparable to results from the best quantum chemistry methods.

Monte Carlo based approach to the LS-NaI 4πβ-γ anticoincidence extrapolation and uncertainty

PubMed Central

Fitzgerald, R.

2016-01-01

The 4πβ-γ anticoincidence method is used for the primary standardization of β−, β+, electron capture (EC), α, and mixed-mode radionuclides. Efficiency extrapolation using one or more γ ray coincidence gates is typically carried out by a low-order polynomial fit. The approach presented here is to use a Geant4-based Monte Carlo simulation of the detector system to analyze the efficiency extrapolation. New code was developed to account for detector resolution, direct γ ray interaction with the PMT, and implementation of experimental β-decay shape factors. The simulation was tuned to 57Co and 60Co data, then tested with 99mTc data, and used in measurements of 18F, 129I, and 124I. The analysis method described here offers a more realistic activity value and uncertainty than those indicated from a least-squares fit alone. PMID:27358944

Calculation of radiation therapy dose using all particle Monte Carlo transport

DOEpatents

Chandler, William P.; Hartmann-Siantar, Christine L.; Rathkopf, James A.

1999-01-01

The actual radiation dose absorbed in the body is calculated using three-dimensional Monte Carlo transport. Neutrons, protons, deuterons, tritons, helium-3, alpha particles, photons, electrons, and positrons are transported in a completely coupled manner, using this Monte Carlo All-Particle Method (MCAPM). The major elements of the invention include: computer hardware, user description of the patient, description of the radiation source, physical databases, Monte Carlo transport, and output of dose distributions. This facilitated the estimation of dose distributions on a Cartesian grid for neutrons, photons, electrons, positrons, and heavy charged-particles incident on any biological target, with resolutions ranging from microns to centimeters. Calculations can be extended to estimate dose distributions on general-geometry (non-Cartesian) grids for biological and/or non-biological media.

Monte Carlo simulation: Its status and future

DOE Office of Scientific and Technical Information (OSTI.GOV)

Murtha, J.A.

1997-04-01

Monte Carlo simulation is a statistics-based analysis tool that yields probability-vs.-value relationships for key parameters, including oil and gas reserves, capital exposure, and various economic yardsticks, such as net present value (NPV) and return on investment (ROI). Monte Carlo simulation is a part of risk analysis and is sometimes performed in conjunction with or as an alternative to decision [tree] analysis. The objectives are (1) to define Monte Carlo simulation in a more general context of risk and decision analysis; (2) to provide some specific applications, which can be interrelated; (3) to respond to some of the criticisms; (4) tomore » offer some cautions about abuses of the method and recommend how to avoid the pitfalls; and (5) to predict what the future has in store.« less

Calculation of radiation therapy dose using all particle Monte Carlo transport

DOEpatents

Chandler, W.P.; Hartmann-Siantar, C.L.; Rathkopf, J.A.

1999-02-09

The actual radiation dose absorbed in the body is calculated using three-dimensional Monte Carlo transport. Neutrons, protons, deuterons, tritons, helium-3, alpha particles, photons, electrons, and positrons are transported in a completely coupled manner, using this Monte Carlo All-Particle Method (MCAPM). The major elements of the invention include: computer hardware, user description of the patient, description of the radiation source, physical databases, Monte Carlo transport, and output of dose distributions. This facilitated the estimation of dose distributions on a Cartesian grid for neutrons, photons, electrons, positrons, and heavy charged-particles incident on any biological target, with resolutions ranging from microns to centimeters. Calculations can be extended to estimate dose distributions on general-geometry (non-Cartesian) grids for biological and/or non-biological media. 57 figs.

Multistep Lattice-Voxel method utilizing lattice function for Monte-Carlo treatment planning with pixel based voxel model.

PubMed

Kumada, H; Saito, K; Nakamura, T; Sakae, T; Sakurai, H; Matsumura, A; Ono, K

2011-12-01

Treatment planning for boron neutron capture therapy generally utilizes Monte-Carlo methods for calculation of the dose distribution. The new treatment planning system JCDS-FX employs the multi-purpose Monte-Carlo code PHITS to calculate the dose distribution. JCDS-FX allows to build a precise voxel model consisting of pixel based voxel cells in the scale of 0.4×0.4×2.0 mm(3) voxel in order to perform high-accuracy dose estimation, e.g. for the purpose of calculating the dose distribution in a human body. However, the miniaturization of the voxel size increases calculation time considerably. The aim of this study is to investigate sophisticated modeling methods which can perform Monte-Carlo calculations for human geometry efficiently. Thus, we devised a new voxel modeling method "Multistep Lattice-Voxel method," which can configure a voxel model that combines different voxel sizes by utilizing the lattice function over and over. To verify the performance of the calculation with the modeling method, several calculations for human geometry were carried out. The results demonstrated that the Multistep Lattice-Voxel method enabled the precise voxel model to reduce calculation time substantially while keeping the high-accuracy of dose estimation. Copyright © 2011 Elsevier Ltd. All rights reserved.

Path Toward a Unified Geometry for Radiation Transport

NASA Astrophysics Data System (ADS)

Lee, Kerry

The Direct Accelerated Geometry for Radiation Analysis and Design (DAGRAD) element of the RadWorks Project under Advanced Exploration Systems (AES) within the Space Technology Mission Directorate (STMD) of NASA will enable new designs and concepts of operation for radiation risk assessment, mitigation and protection. This element is designed to produce a solution that will allow NASA to calculate the transport of space radiation through complex CAD models using the state-of-the-art analytic and Monte Carlo radiation transport codes. Due to the inherent hazard of astronaut and spacecraft exposure to ionizing radiation in low-Earth orbit (LEO) or in deep space, risk analyses must be performed for all crew vehicles and habitats. Incorporating these analyses into the design process can minimize the mass needed solely for radiation protection. Transport of the radiation fields as they pass through shielding and body materials can be simulated using Monte Carlo techniques or described by the Boltzmann equation, which is obtained by balancing changes in particle fluxes as they traverse a small volume of material with the gains and losses caused by atomic and nuclear collisions. Deterministic codes that solve the Boltzmann transport equation, such as HZETRN (high charge and energy transport code developed by NASA LaRC), are generally computationally faster than Monte Carlo codes such as FLUKA, GEANT4, MCNP(X) or PHITS; however, they are currently limited to transport in one dimension, which poorly represents the secondary light ion and neutron radiation fields. NASA currently uses HZETRN space radiation transport software, both because it is computationally efficient and because proven methods have been developed for using this software to analyze complex geometries. Although Monte Carlo codes describe the relevant physics in a fully three-dimensional manner, their computational costs have thus far prevented their widespread use for analysis of complex CAD models, leading to the creation and maintenance of toolkit specific simplistic geometry models. The work presented here builds on the Direct Accelerated Geometry Monte Carlo (DAGMC) toolkit developed for use with the Monte Carlo N-Particle (MCNP) transport code. The work-flow for doing radiation transport on CAD models using MCNP and FLUKA has been demonstrated and the results of analyses on realistic spacecraft/habitats will be presented. Future work is planned that will further automate this process and enable the use of multiple radiation transport codes on identical geometry models imported from CAD. This effort will enhance the modeling tools used by NASA to accurately evaluate the astronaut space radiation risk and accurately determine the protection provided by as-designed exploration mission vehicles and habitats.

Monte Carlo Simulation of a Segmented Detector for Low-Energy Electron Antineutrinos

NASA Astrophysics Data System (ADS)

Qomi, H. Akhtari; Safari, M. J.; Davani, F. Abbasi

2017-11-01

Detection of low-energy electron antineutrinos is of importance for several purposes, such as ex-vessel reactor monitoring, neutrino oscillation studies, etc. The inverse beta decay (IBD) is the interaction that is responsible for detection mechanism in (organic) plastic scintillation detectors. Here, a detailed study will be presented dealing with the radiation and optical transport simulation of a typical segmented antineutrino detector withMonte Carlo method using MCNPX and FLUKA codes. This study shows different aspects of the detector, benefiting from inherent capabilities of the Monte Carlo simulation codes.

Shielding analyses of an AB-BNCT facility using Monte Carlo simulations and simplified methods

NASA Astrophysics Data System (ADS)

Lai, Bo-Lun; Sheu, Rong-Jiun

2017-09-01

Accurate Monte Carlo simulations and simplified methods were used to investigate the shielding requirements of a hypothetical accelerator-based boron neutron capture therapy (AB-BNCT) facility that included an accelerator room and a patient treatment room. The epithermal neutron beam for BNCT purpose was generated by coupling a neutron production target with a specially designed beam shaping assembly (BSA), which was embedded in the partition wall between the two rooms. Neutrons were produced from a beryllium target bombarded by 1-mA 30-MeV protons. The MCNP6-generated surface sources around all the exterior surfaces of the BSA were established to facilitate repeated Monte Carlo shielding calculations. In addition, three simplified models based on a point-source line-of-sight approximation were developed and their predictions were compared with the reference Monte Carlo results. The comparison determined which model resulted in better dose estimation, forming the basis of future design activities for the first ABBNCT facility in Taiwan.

Semi-stochastic full configuration interaction quantum Monte Carlo

NASA Astrophysics Data System (ADS)

Holmes, Adam; Petruzielo, Frank; Khadilkar, Mihir; Changlani, Hitesh; Nightingale, M. P.; Umrigar, C. J.

2012-02-01

In the recently proposed full configuration interaction quantum Monte Carlo (FCIQMC) [1,2], the ground state is projected out stochastically, using a population of walkers each of which represents a basis state in the Hilbert space spanned by Slater determinants. The infamous fermion sign problem manifests itself in the fact that walkers of either sign can be spawned on a given determinant. We propose an improvement on this method in the form of a hybrid stochastic/deterministic technique, which we expect will improve the efficiency of the algorithm by ameliorating the sign problem. We test the method on atoms and molecules, e.g., carbon, carbon dimer, N2 molecule, and stretched N2. [4pt] [1] Fermion Monte Carlo without fixed nodes: a Game of Life, death and annihilation in Slater Determinant space. George Booth, Alex Thom, Ali Alavi. J Chem Phys 131, 050106, (2009).[0pt] [2] Survival of the fittest: Accelerating convergence in full configuration-interaction quantum Monte Carlo. Deidre Cleland, George Booth, and Ali Alavi. J Chem Phys 132, 041103 (2010).

Monte-Carlo-based phase retardation estimator for polarization sensitive optical coherence tomography

NASA Astrophysics Data System (ADS)

Duan, Lian; Makita, Shuichi; Yamanari, Masahiro; Lim, Yiheng; Yasuno, Yoshiaki

2011-08-01

A Monte-Carlo-based phase retardation estimator is developed to correct the systematic error in phase retardation measurement by polarization sensitive optical coherence tomography (PS-OCT). Recent research has revealed that the phase retardation measured by PS-OCT has a distribution that is neither symmetric nor centered at the true value. Hence, a standard mean estimator gives us erroneous estimations of phase retardation, and it degrades the performance of PS-OCT for quantitative assessment. In this paper, the noise property in phase retardation is investigated in detail by Monte-Carlo simulation and experiments. A distribution transform function is designed to eliminate the systematic error by using the result of the Monte-Carlo simulation. This distribution transformation is followed by a mean estimator. This process provides a significantly better estimation of phase retardation than a standard mean estimator. This method is validated both by numerical simulations and experiments. The application of this method to in vitro and in vivo biological samples is also demonstrated.

A collision history-based approach to Sensitivity/Perturbation calculations in the continuous energy Monte Carlo code SERPENT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Giuseppe Palmiotti

In this work, the implementation of a collision history-based approach to sensitivity/perturbation calculations in the Monte Carlo code SERPENT is discussed. The proposed methods allow the calculation of the eects of nuclear data perturbation on several response functions: the eective multiplication factor, reaction rate ratios and bilinear ratios (e.g., eective kinetics parameters). SERPENT results are compared to ERANOS and TSUNAMI Generalized Perturbation Theory calculations for two fast metallic systems and for a PWR pin-cell benchmark. New methods for the calculation of sensitivities to angular scattering distributions are also presented, which adopts fully continuous (in energy and angle) Monte Carlo estimators.

Efficient Application of Continuous Fractional Component Monte Carlo in the Reaction Ensemble

PubMed Central

2017-01-01

A new formulation of the Reaction Ensemble Monte Carlo technique (RxMC) combined with the Continuous Fractional Component Monte Carlo method is presented. This method is denoted by serial Rx/CFC. The key ingredient is that fractional molecules of either reactants or reaction products are present and that chemical reactions always involve fractional molecules. Serial Rx/CFC has the following advantages compared to other approaches: (1) One directly obtains chemical potentials of all reactants and reaction products. Obtained chemical potentials can be used directly as an independent check to ensure that chemical equilibrium is achieved. (2) Independent biasing is applied to the fractional molecules of reactants and reaction products. Therefore, the efficiency of the algorithm is significantly increased, compared to the other approaches. (3) Changes in the maximum scaling parameter of intermolecular interactions can be chosen differently for reactants and reaction products. (4) The number of fractional molecules is reduced. As a proof of principle, our method is tested for Lennard-Jones systems at various pressures and for various chemical reactions. Excellent agreement was found both for average densities and equilibrium mixture compositions computed using serial Rx/CFC, RxMC/CFCMC previously introduced by Rosch and Maginn (Journal of Chemical Theory and Computation, 2011, 7, 269–279), and the conventional RxMC approach. The serial Rx/CFC approach is also tested for the reaction of ammonia synthesis at various temperatures and pressures. Excellent agreement was found between results obtained from serial Rx/CFC, experimental results from literature, and thermodynamic modeling using the Peng–Robinson equation of state. The efficiency of reaction trial moves is improved by a factor of 2 to 3 (depending on the system) compared to the RxMC/CFCMC formulation by Rosch and Maginn. PMID:28737933

RECORDS: improved Reporting of montE CarlO RaDiation transport Studies: Report of the AAPM Research Committee Task Group 268.

PubMed

Sechopoulos, Ioannis; Rogers, D W O; Bazalova-Carter, Magdalena; Bolch, Wesley E; Heath, Emily C; McNitt-Gray, Michael F; Sempau, Josep; Williamson, Jeffrey F

2018-01-01

Studies involving Monte Carlo simulations are common in both diagnostic and therapy medical physics research, as well as other fields of basic and applied science. As with all experimental studies, the conditions and parameters used for Monte Carlo simulations impact their scope, validity, limitations, and generalizability. Unfortunately, many published peer-reviewed articles involving Monte Carlo simulations do not provide the level of detail needed for the reader to be able to properly assess the quality of the simulations. The American Association of Physicists in Medicine Task Group #268 developed guidelines to improve reporting of Monte Carlo studies in medical physics research. By following these guidelines, manuscripts submitted for peer-review will include a level of relevant detail that will increase the transparency, the ability to reproduce results, and the overall scientific value of these studies. The guidelines include a checklist of the items that should be included in the Methods, Results, and Discussion sections of manuscripts submitted for peer-review. These guidelines do not attempt to replace the journal reviewer, but rather to be a tool during the writing and review process. Given the varied nature of Monte Carlo studies, it is up to the authors and the reviewers to use this checklist appropriately, being conscious of how the different items apply to each particular scenario. It is envisioned that this list will be useful both for authors and for reviewers, to help ensure the adequate description of Monte Carlo studies in the medical physics literature. © 2017 American Association of Physicists in Medicine.

Deterministic absorbed dose estimation in computed tomography using a discrete ordinates method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Norris, Edward T.; Liu, Xin, E-mail: xinliu@mst.edu; Hsieh, Jiang

Purpose: Organ dose estimation for a patient undergoing computed tomography (CT) scanning is very important. Although Monte Carlo methods are considered gold-standard in patient dose estimation, the computation time required is formidable for routine clinical calculations. Here, the authors instigate a deterministic method for estimating an absorbed dose more efficiently. Methods: Compared with current Monte Carlo methods, a more efficient approach to estimating the absorbed dose is to solve the linear Boltzmann equation numerically. In this study, an axial CT scan was modeled with a software package, Denovo, which solved the linear Boltzmann equation using the discrete ordinates method. Themore » CT scanning configuration included 16 x-ray source positions, beam collimators, flat filters, and bowtie filters. The phantom was the standard 32 cm CT dose index (CTDI) phantom. Four different Denovo simulations were performed with different simulation parameters, including the number of quadrature sets and the order of Legendre polynomial expansions. A Monte Carlo simulation was also performed for benchmarking the Denovo simulations. A quantitative comparison was made of the simulation results obtained by the Denovo and the Monte Carlo methods. Results: The difference in the simulation results of the discrete ordinates method and those of the Monte Carlo methods was found to be small, with a root-mean-square difference of around 2.4%. It was found that the discrete ordinates method, with a higher order of Legendre polynomial expansions, underestimated the absorbed dose near the center of the phantom (i.e., low dose region). Simulations of the quadrature set 8 and the first order of the Legendre polynomial expansions proved to be the most efficient computation method in the authors’ study. The single-thread computation time of the deterministic simulation of the quadrature set 8 and the first order of the Legendre polynomial expansions was 21 min on a personal computer. Conclusions: The simulation results showed that the deterministic method can be effectively used to estimate the absorbed dose in a CTDI phantom. The accuracy of the discrete ordinates method was close to that of a Monte Carlo simulation, and the primary benefit of the discrete ordinates method lies in its rapid computation speed. It is expected that further optimization of this method in routine clinical CT dose estimation will improve its accuracy and speed.« less

Monte Carlo simulation of photon migration in a cloud computing environment with MapReduce

PubMed Central

Pratx, Guillem; Xing, Lei

2011-01-01

Monte Carlo simulation is considered the most reliable method for modeling photon migration in heterogeneous media. However, its widespread use is hindered by the high computational cost. The purpose of this work is to report on our implementation of a simple MapReduce method for performing fault-tolerant Monte Carlo computations in a massively-parallel cloud computing environment. We ported the MC321 Monte Carlo package to Hadoop, an open-source MapReduce framework. In this implementation, Map tasks compute photon histories in parallel while a Reduce task scores photon absorption. The distributed implementation was evaluated on a commercial compute cloud. The simulation time was found to be linearly dependent on the number of photons and inversely proportional to the number of nodes. For a cluster size of 240 nodes, the simulation of 100 billion photon histories took 22 min, a 1258 × speed-up compared to the single-threaded Monte Carlo program. The overall computational throughput was 85,178 photon histories per node per second, with a latency of 100 s. The distributed simulation produced the same output as the original implementation and was resilient to hardware failure: the correctness of the simulation was unaffected by the shutdown of 50% of the nodes. PMID:22191916

Markov chains of infinite order and asymptotic satisfaction of balance: application to the adaptive integration method.

PubMed

Earl, David J; Deem, Michael W

2005-04-14

Adaptive Monte Carlo methods can be viewed as implementations of Markov chains with infinite memory. We derive a general condition for the convergence of a Monte Carlo method whose history dependence is contained within the simulated density distribution. In convergent cases, our result implies that the balance condition need only be satisfied asymptotically. As an example, we show that the adaptive integration method converges.

Monte Carlo calculation of large and small-angle electron scattering in air

DOE PAGES

Cohen, B. I.; Higginson, D. P.; Eng, C. D.; ...

2017-08-12

A Monte Carlo method for angle scattering of electrons in air that accommodates the small-angle multiple scattering and larger-angle single scattering limits is introduced. In this work, the algorithm is designed for use in a particle-in-cell simulation of electron transport and electromagnetic wave effects in air. The method is illustrated in example calculations.

An Educational MONTE CARLO Simulation/Animation Program for the Cosmic Rays Muons and a Prototype Computer-Driven Hardware Display.

ERIC Educational Resources Information Center

Kalkanis, G.; Sarris, M. M.

1999-01-01

Describes an educational software program for the study of and detection methods for the cosmic ray muons passing through several light transparent materials (i.e., water, air, etc.). Simulates muons and Cherenkov photons' paths and interactions and visualizes/animates them on the computer screen using Monte Carlo methods/techniques which employ…

Monte Carlo method for magnetic impurities in metals

NASA Technical Reports Server (NTRS)

Hirsch, J. E.; Fye, R. M.

1986-01-01

The paper discusses a Monte Carlo algorithm to study properties of dilute magnetic alloys; the method can treat a small number of magnetic impurities interacting wiith the conduction electrons in a metal. Results for the susceptibility of a single Anderson impurity in the symmetric case show the expected universal behavior at low temperatures. Some results for two Anderson impurities are also discussed.

An NCME Instructional Module on Estimating Item Response Theory Models Using Markov Chain Monte Carlo Methods

ERIC Educational Resources Information Center

Kim, Jee-Seon; Bolt, Daniel M.

2007-01-01

The purpose of this ITEMS module is to provide an introduction to Markov chain Monte Carlo (MCMC) estimation for item response models. A brief description of Bayesian inference is followed by an overview of the various facets of MCMC algorithms, including discussion of prior specification, sampling procedures, and methods for evaluating chain…

Comparison of deterministic and stochastic methods for time-dependent Wigner simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shao, Sihong, E-mail: sihong@math.pku.edu.cn; Sellier, Jean Michel, E-mail: jeanmichel.sellier@parallel.bas.bg

2015-11-01

Recently a Monte Carlo method based on signed particles for time-dependent simulations of the Wigner equation has been proposed. While it has been thoroughly validated against physical benchmarks, no technical study about its numerical accuracy has been performed. To this end, this paper presents the first step towards the construction of firm mathematical foundations for the signed particle Wigner Monte Carlo method. An initial investigation is performed by means of comparisons with a cell average spectral element method, which is a highly accurate deterministic method and utilized to provide reference solutions. Several different numerical tests involving the time-dependent evolution ofmore » a quantum wave-packet are performed and discussed in deep details. In particular, this allows us to depict a set of crucial criteria for the signed particle Wigner Monte Carlo method to achieve a satisfactory accuracy.« less

Many-body optimization using an ab initio monte carlo method.

PubMed

Haubein, Ned C; McMillan, Scott A; Broadbelt, Linda J

2003-01-01

Advances in computing power have made it possible to study solvated molecules using ab initio quantum chemistry. Inclusion of discrete solvent molecules is required to determine geometric information about solute/solvent clusters. Monte Carlo methods are well suited to finding minima in many-body systems, and ab initio methods are applicable to the widest range of systems. A first principles Monte Carlo (FPMC) method was developed to find minima in many-body systems, and emphasis was placed on implementing moves that increase the likelihood of finding minimum energy structures. Partial optimization and molecular interchange moves aid in finding minima and overcome the incomplete sampling that is unavoidable when using ab initio methods. FPMC was validated by studying the boron trifluoride-water system, and then the method was used to examine the methyl carbenium ion in water to demonstrate its application to solvation problems.

The Robustness of the Studentized Range Statistic to Violations of the Normality and Homogeneity of Variance Assumptions.

ERIC Educational Resources Information Center

Ramseyer, Gary C.; Tcheng, Tse-Kia

The present study was directed at determining the extent to which the Type I Error rate is affected by violations in the basic assumptions of the q statistic. Monte Carlo methods were employed, and a variety of departures from the assumptions were examined. (Author)

Modeling of carbon dioxide condensation in the high pressure flows using the statistical BGK approach

NASA Astrophysics Data System (ADS)

Kumar, Rakesh; Li, Zheng; Levin, Deborah A.

2011-05-01

In this work, we propose a new heat accommodation model to simulate freely expanding homogeneous condensation flows of gaseous carbon dioxide using a new approach, the statistical Bhatnagar-Gross-Krook method. The motivation for the present work comes from the earlier work of Li et al. [J. Phys. Chem. 114, 5276 (2010)] in which condensation models were proposed and used in the direct simulation Monte Carlo method to simulate the flow of carbon dioxide from supersonic expansions of small nozzles into near-vacuum conditions. Simulations conducted for stagnation pressures of one and three bar were compared with the measurements of gas and cluster number densities, cluster size, and carbon dioxide rotational temperature obtained by Ramos et al. [Phys. Rev. A 72, 3204 (2005)]. Due to the high computational cost of direct simulation Monte Carlo method, comparison between simulations and data could only be performed for these stagnation pressures, with good agreement obtained beyond the condensation onset point, in the farfield. As the stagnation pressure increases, the degree of condensation also increases; therefore, to improve the modeling of condensation onset, one must be able to simulate higher stagnation pressures. In simulations of an expanding flow of argon through a nozzle, Kumar et al. [AIAA J. 48, 1531 (2010)] found that the statistical Bhatnagar-Gross-Krook method provides the same accuracy as direct simulation Monte Carlo method, but, at one half of the computational cost. In this work, the statistical Bhatnagar-Gross-Krook method was modified to account for internal degrees of freedom for multi-species polyatomic gases. With the computational approach in hand, we developed and tested a new heat accommodation model for a polyatomic system to properly account for the heat release of condensation. We then developed condensation models in the framework of the statistical Bhatnagar-Gross-Krook method. Simulations were found to agree well with the experiment for all stagnation pressure cases (1-5 bar), validating the accuracy of the Bhatnagar-Gross-Krook based condensation model in capturing the physics of condensation.

The Use of Monte Carlo Techniques to Teach Probability.

ERIC Educational Resources Information Center

Newell, G. J.; MacFarlane, J. D.

1985-01-01

Presents sports-oriented examples (cricket and football) in which Monte Carlo methods are used on microcomputers to teach probability concepts. Both examples include computer programs (with listings) which utilize the microcomputer's random number generator. Instructional strategies, with further challenges to help students understand the role of…

Monte Carlo Simulation of Microscopic Stock Market Models

NASA Astrophysics Data System (ADS)

Stauffer, Dietrich

Computer simulations with random numbers, that is, Monte Carlo methods, have been considerably applied in recent years to model the fluctuations of stock market or currency exchange rates. Here we concentrate on the percolation model of Cont and Bouchaud, to simulate, not to predict, the market behavior.

Studies of Low Luminosity Active Galactic Nuclei with Monte Carlo and Magnetohydrodynamic Simulations

NASA Astrophysics Data System (ADS)

Hilburn, Guy Louis

Results from several studies are presented which detail explorations of the physical and spectral properties of low luminosity active galactic nuclei. An initial Sagittarius A* general relativistic magnetohydrodynamic simulation and Monte Carlo radiation transport model suggests accretion rate changes as the dominant flaring method. A similar study on M87 introduces new methods to the Monte Carlo model for increased consistency in highly energetic sources. Again, accretion rate variation seems most appropriate to explain spectral transients. To more closely resolve the methods of particle energization in active galactic nuclei accretion disks, a series of localized shearing box simulations explores the effect of numerical resolution on the development of current sheets. A particular focus on numerically describing converged current sheet formation will provide new methods for consideration of turbulence in accretion disks.

MCMC multilocus lod scores: application of a new approach.

PubMed

George, Andrew W; Wijsman, Ellen M; Thompson, Elizabeth A

2005-01-01

On extended pedigrees with extensive missing data, the calculation of multilocus likelihoods for linkage analysis is often beyond the computational bounds of exact methods. Growing interest therefore surrounds the implementation of Monte Carlo estimation methods. In this paper, we demonstrate the speed and accuracy of a new Markov chain Monte Carlo method for the estimation of linkage likelihoods through an analysis of real data from a study of early-onset Alzheimer's disease. For those data sets where comparison with exact analysis is possible, we achieved up to a 100-fold increase in speed. Our approach is implemented in the program lm_bayes within the framework of the freely available MORGAN 2.6 package for Monte Carlo genetic analysis (http://www.stat.washington.edu/thompson/Genepi/MORGAN/Morgan.shtml).

Reducing statistical uncertainties in simulated organ doses of phantoms immersed in water

DOE PAGES

Hiller, Mauritius M.; Veinot, Kenneth G.; Easterly, Clay E.; ...

2016-08-13

In this study, methods are addressed to reduce the computational time to compute organ-dose rate coefficients using Monte Carlo techniques. Several variance reduction techniques are compared including the reciprocity method, importance sampling, weight windows and the use of the ADVANTG software package. For low-energy photons, the runtime was reduced by a factor of 10 5 when using the reciprocity method for kerma computation for immersion of a phantom in contaminated water. This is particularly significant since impractically long simulation times are required to achieve reasonable statistical uncertainties in organ dose for low-energy photons in this source medium and geometry. Althoughmore » the MCNP Monte Carlo code is used in this paper, the reciprocity technique can be used equally well with other Monte Carlo codes.« less

Bayesian modelling of uncertainties of Monte Carlo radiative-transfer simulations

NASA Astrophysics Data System (ADS)

Beaujean, Frederik; Eggers, Hans C.; Kerzendorf, Wolfgang E.

2018-04-01

One of the big challenges in astrophysics is the comparison of complex simulations to observations. As many codes do not directly generate observables (e.g. hydrodynamic simulations), the last step in the modelling process is often a radiative-transfer treatment. For this step, the community relies increasingly on Monte Carlo radiative transfer due to the ease of implementation and scalability with computing power. We show how to estimate the statistical uncertainty given the output of just a single radiative-transfer simulation in which the number of photon packets follows a Poisson distribution and the weight (e.g. energy or luminosity) of a single packet may follow an arbitrary distribution. Our Bayesian approach produces a posterior distribution that is valid for any number of packets in a bin, even zero packets, and is easy to implement in practice. Our analytic results for large number of packets show that we generalise existing methods that are valid only in limiting cases. The statistical problem considered here appears in identical form in a wide range of Monte Carlo simulations including particle physics and importance sampling. It is particularly powerful in extracting information when the available data are sparse or quantities are small.

Bayesian modelling of uncertainties of Monte Carlo radiative-transfer simulations

NASA Astrophysics Data System (ADS)

Beaujean, Frederik; Eggers, Hans C.; Kerzendorf, Wolfgang E.

2018-07-01

One of the big challenges in astrophysics is the comparison of complex simulations to observations. As many codes do not directly generate observables (e.g. hydrodynamic simulations), the last step in the modelling process is often a radiative-transfer treatment. For this step, the community relies increasingly on Monte Carlo radiative transfer due to the ease of implementation and scalability with computing power. We consider simulations in which the number of photon packets is Poisson distributed, while the weight assigned to a single photon packet follows any distribution of choice. We show how to estimate the statistical uncertainty of the sum of weights in each bin from the output of a single radiative-transfer simulation. Our Bayesian approach produces a posterior distribution that is valid for any number of packets in a bin, even zero packets, and is easy to implement in practice. Our analytic results for large number of packets show that we generalize existing methods that are valid only in limiting cases. The statistical problem considered here appears in identical form in a wide range of Monte Carlo simulations including particle physics and importance sampling. It is particularly powerful in extracting information when the available data are sparse or quantities are small.

A Monte Carlo method using octree structure in photon and electron transport

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ogawa, K.; Maeda, S.

Most of the early Monte Carlo calculations in medical physics were used to calculate absorbed dose distributions, and detector responses and efficiencies. Recently, data acquisition in Single Photon Emission CT (SPECT) has been simulated by a Monte Carlo method to evaluate scatter photons generated in a human body and a collimator. Monte Carlo simulations in SPECT data acquisition are generally based on the transport of photons only because the photons being simulated are low energy, and therefore the bremsstrahlung productions by the electrons generated are negligible. Since the transport calculation of photons without electrons is much simpler than that withmore » electrons, it is possible to accomplish the high-speed simulation in a simple object with one medium. Here, object description is important in performing the photon and/or electron transport using a Monte Carlo method efficiently. The authors propose a new description method using an octree representation of an object. Thus even if the boundaries of each medium are represented accurately, high-speed calculation of photon transport can be accomplished because the number of voxels is much fewer than that of the voxel-based approach which represents an object by a union of the voxels of the same size. This Monte Carlo code using the octree representation of an object first establishes the simulation geometry by reading octree string, which is produced by forming an octree structure from a set of serial sections for the object before the simulation; then it transports photons in the geometry. Using the code, if the user just prepares a set of serial sections for the object in which he or she wants to simulate photon trajectories, he or she can perform the simulation automatically using the suboptimal geometry simplified by the octree representation without forming the optimal geometry by handwriting.« less

Fast multipurpose Monte Carlo simulation for proton therapy using multi- and many-core CPU architectures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Souris, Kevin, E-mail: kevin.souris@uclouvain.be; Lee, John Aldo; Sterpin, Edmond

2016-04-15

Purpose: Accuracy in proton therapy treatment planning can be improved using Monte Carlo (MC) simulations. However the long computation time of such methods hinders their use in clinical routine. This work aims to develop a fast multipurpose Monte Carlo simulation tool for proton therapy using massively parallel central processing unit (CPU) architectures. Methods: A new Monte Carlo, called MCsquare (many-core Monte Carlo), has been designed and optimized for the last generation of Intel Xeon processors and Intel Xeon Phi coprocessors. These massively parallel architectures offer the flexibility and the computational power suitable to MC methods. The class-II condensed history algorithmmore » of MCsquare provides a fast and yet accurate method of simulating heavy charged particles such as protons, deuterons, and alphas inside voxelized geometries. Hard ionizations, with energy losses above a user-specified threshold, are simulated individually while soft events are regrouped in a multiple scattering theory. Elastic and inelastic nuclear interactions are sampled from ICRU 63 differential cross sections, thereby allowing for the computation of prompt gamma emission profiles. MCsquare has been benchmarked with the GATE/GEANT4 Monte Carlo application for homogeneous and heterogeneous geometries. Results: Comparisons with GATE/GEANT4 for various geometries show deviations within 2%–1 mm. In spite of the limited memory bandwidth of the coprocessor simulation time is below 25 s for 10{sup 7} primary 200 MeV protons in average soft tissues using all Xeon Phi and CPU resources embedded in a single desktop unit. Conclusions: MCsquare exploits the flexibility of CPU architectures to provide a multipurpose MC simulation tool. Optimized code enables the use of accurate MC calculation within a reasonable computation time, adequate for clinical practice. MCsquare also simulates prompt gamma emission and can thus be used also for in vivo range verification.« less

Multilevel Monte Carlo and improved timestepping methods in atmospheric dispersion modelling

NASA Astrophysics Data System (ADS)

Katsiolides, Grigoris; Müller, Eike H.; Scheichl, Robert; Shardlow, Tony; Giles, Michael B.; Thomson, David J.

2018-02-01

A common way to simulate the transport and spread of pollutants in the atmosphere is via stochastic Lagrangian dispersion models. Mathematically, these models describe turbulent transport processes with stochastic differential equations (SDEs). The computational bottleneck is the Monte Carlo algorithm, which simulates the motion of a large number of model particles in a turbulent velocity field; for each particle, a trajectory is calculated with a numerical timestepping method. Choosing an efficient numerical method is particularly important in operational emergency-response applications, such as tracking radioactive clouds from nuclear accidents or predicting the impact of volcanic ash clouds on international aviation, where accurate and timely predictions are essential. In this paper, we investigate the application of the Multilevel Monte Carlo (MLMC) method to simulate the propagation of particles in a representative one-dimensional dispersion scenario in the atmospheric boundary layer. MLMC can be shown to result in asymptotically superior computational complexity and reduced computational cost when compared to the Standard Monte Carlo (StMC) method, which is currently used in atmospheric dispersion modelling. To reduce the absolute cost of the method also in the non-asymptotic regime, it is equally important to choose the best possible numerical timestepping method on each level. To investigate this, we also compare the standard symplectic Euler method, which is used in many operational models, with two improved timestepping algorithms based on SDE splitting methods.

SU-E-T-569: Neutron Shielding Calculation Using Analytical and Multi-Monte Carlo Method for Proton Therapy Facility

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cho, S; Shin, E H; Kim, J

2015-06-15

Purpose: To evaluate the shielding wall design to protect patients, staff and member of the general public for secondary neutron using a simply analytic solution, multi-Monte Carlo code MCNPX, ANISN and FLUKA. Methods: An analytical and multi-Monte Carlo method were calculated for proton facility (Sumitomo Heavy Industry Ltd.) at Samsung Medical Center in Korea. The NCRP-144 analytical evaluation methods, which produced conservative estimates on the dose equivalent values for the shielding, were used for analytical evaluations. Then, the radiation transport was simulated with the multi-Monte Carlo code. The neutron dose at evaluation point is got by the value using themore » production of the simulation value and the neutron dose coefficient introduced in ICRP-74. Results: The evaluation points of accelerator control room and control room entrance are mainly influenced by the point of the proton beam loss. So the neutron dose equivalent of accelerator control room for evaluation point is 0.651, 1.530, 0.912, 0.943 mSv/yr and the entrance of cyclotron room is 0.465, 0.790, 0.522, 0.453 mSv/yr with calculation by the method of NCRP-144 formalism, ANISN, FLUKA and MCNP, respectively. The most of Result of MCNPX and FLUKA using the complicated geometry showed smaller values than Result of ANISN. Conclusion: The neutron shielding for a proton therapy facility has been evaluated by the analytic model and multi-Monte Carlo methods. We confirmed that the setting of shielding was located in well accessible area to people when the proton facility is operated.« less

A Machine Learning Method for the Prediction of Receptor Activation in the Simulation of Synapses

PubMed Central

Montes, Jesus; Gomez, Elena; Merchán-Pérez, Angel; DeFelipe, Javier; Peña, Jose-Maria

2013-01-01

Chemical synaptic transmission involves the release of a neurotransmitter that diffuses in the extracellular space and interacts with specific receptors located on the postsynaptic membrane. Computer simulation approaches provide fundamental tools for exploring various aspects of the synaptic transmission under different conditions. In particular, Monte Carlo methods can track the stochastic movements of neurotransmitter molecules and their interactions with other discrete molecules, the receptors. However, these methods are computationally expensive, even when used with simplified models, preventing their use in large-scale and multi-scale simulations of complex neuronal systems that may involve large numbers of synaptic connections. We have developed a machine-learning based method that can accurately predict relevant aspects of the behavior of synapses, such as the percentage of open synaptic receptors as a function of time since the release of the neurotransmitter, with considerably lower computational cost compared with the conventional Monte Carlo alternative. The method is designed to learn patterns and general principles from a corpus of previously generated Monte Carlo simulations of synapses covering a wide range of structural and functional characteristics. These patterns are later used as a predictive model of the behavior of synapses under different conditions without the need for additional computationally expensive Monte Carlo simulations. This is performed in five stages: data sampling, fold creation, machine learning, validation and curve fitting. The resulting procedure is accurate, automatic, and it is general enough to predict synapse behavior under experimental conditions that are different to the ones it has been trained on. Since our method efficiently reproduces the results that can be obtained with Monte Carlo simulations at a considerably lower computational cost, it is suitable for the simulation of high numbers of synapses and it is therefore an excellent tool for multi-scale simulations. PMID:23894367

Path integral Monte Carlo and the electron gas

NASA Astrophysics Data System (ADS)

Brown, Ethan W.

Path integral Monte Carlo is a proven method for accurately simulating quantum mechanical systems at finite-temperature. By stochastically sampling Feynman's path integral representation of the quantum many-body density matrix, path integral Monte Carlo includes non-perturbative effects like thermal fluctuations and particle correlations in a natural way. Over the past 30 years, path integral Monte Carlo has been successfully employed to study the low density electron gas, high-pressure hydrogen, and superfluid helium. For systems where the role of Fermi statistics is important, however, traditional path integral Monte Carlo simulations have an exponentially decreasing efficiency with decreased temperature and increased system size. In this thesis, we work towards improving this efficiency, both through approximate and exact methods, as specifically applied to the homogeneous electron gas. We begin with a brief overview of the current state of atomic simulations at finite-temperature before we delve into a pedagogical review of the path integral Monte Carlo method. We then spend some time discussing the one major issue preventing exact simulation of Fermi systems, the sign problem. Afterwards, we introduce a way to circumvent the sign problem in PIMC simulations through a fixed-node constraint. We then apply this method to the homogeneous electron gas at a large swatch of densities and temperatures in order to map out the warm-dense matter regime. The electron gas can be a representative model for a host of real systems, from simple medals to stellar interiors. However, its most common use is as input into density functional theory. To this end, we aim to build an accurate representation of the electron gas from the ground state to the classical limit and examine its use in finite-temperature density functional formulations. The latter half of this thesis focuses on possible routes beyond the fixed-node approximation. As a first step, we utilize the variational principle inherent in the path integral Monte Carlo method to optimize the nodal surface. By using a ansatz resembling a free particle density matrix, we make a unique connection between a nodal effective mass and the traditional effective mass of many-body quantum theory. We then propose and test several alternate nodal ansatzes and apply them to single atomic systems. Finally, we propose a method to tackle the sign problem head on, by leveraging the relatively simple structure of permutation space. Using this method, we find we can perform exact simulations this of the electron gas and 3He that were previously impossible.

OBJECT KINETIC MONTE CARLO SIMULATIONS OF RADIATION DAMAGE ACCUMULATION IN TUNGSTEN

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nandipati, Giridhar; Setyawan, Wahyu; Roche, Kenneth J.

2016-09-01

The objective of this work is to understand the accumulation of radiation damage created by primary knock-on atoms (PKAs) of various energies, at 300 K and for a dose rate of 10-4 dpa/s in bulk tungsten using the object kinetic Monte Carlo (OKMC) method.

Play It Again: Teaching Statistics with Monte Carlo Simulation

ERIC Educational Resources Information Center

Sigal, Matthew J.; Chalmers, R. Philip

2016-01-01

Monte Carlo simulations (MCSs) provide important information about statistical phenomena that would be impossible to assess otherwise. This article introduces MCS methods and their applications to research and statistical pedagogy using a novel software package for the R Project for Statistical Computing constructed to lessen the often steep…

SIMCA T 1.0: A SAS Computer Program for Simulating Computer Adaptive Testing

ERIC Educational Resources Information Center

Raiche, Gilles; Blais, Jean-Guy

2006-01-01

Monte Carlo methodologies are frequently applied to study the sampling distribution of the estimated proficiency level in adaptive testing. These methods eliminate real situational constraints. However, these Monte Carlo methodologies are not currently supported by the available software programs, and when these programs are available, their…

Simulation of Thermal Neutron Transport Processes Directly from the Evaluated Nuclear Data Files

NASA Astrophysics Data System (ADS)

Androsenko, P. A.; Malkov, M. R.

The main idea of the method proposed in this paper is to directly extract thetrequired information for Monte-Carlo calculations from nuclear data files. The met od being developed allows to directly utilize the data obtained from libraries and seehs to be the most accurate technique. Direct simulation of neutron scattering in themmal energy range using file 7 ENDF-6 format in terms of code system BRAND has beer achieved. Simulation algorithms have been verified using the criterion x2

Path integral Monte Carlo ground state approach: formalism, implementation, and applications

NASA Astrophysics Data System (ADS)

Yan, Yangqian; Blume, D.

2017-11-01

Monte Carlo techniques have played an important role in understanding strongly correlated systems across many areas of physics, covering a wide range of energy and length scales. Among the many Monte Carlo methods applicable to quantum mechanical systems, the path integral Monte Carlo approach with its variants has been employed widely. Since semi-classical or classical approaches will not be discussed in this review, path integral based approaches can for our purposes be divided into two categories: approaches applicable to quantum mechanical systems at zero temperature and approaches applicable to quantum mechanical systems at finite temperature. While these two approaches are related to each other, the underlying formulation and aspects of the algorithm differ. This paper reviews the path integral Monte Carlo ground state (PIGS) approach, which solves the time-independent Schrödinger equation. Specifically, the PIGS approach allows for the determination of expectation values with respect to eigen states of the few- or many-body Schrödinger equation provided the system Hamiltonian is known. The theoretical framework behind the PIGS algorithm, implementation details, and sample applications for fermionic systems are presented.

The X-43A Six Degree of Freedom Monte Carlo Analysis

NASA Technical Reports Server (NTRS)

Baumann, Ethan; Bahm, Catherine; Strovers, Brian; Beck, Roger

2008-01-01

This report provides an overview of the Hyper-X research vehicle Monte Carlo analysis conducted with the six-degree-of-freedom simulation. The methodology and model uncertainties used for the Monte Carlo analysis are presented as permitted. In addition, the process used to select hardware validation test cases from the Monte Carlo data is described. The preflight Monte Carlo analysis indicated that the X-43A control system was robust to the preflight uncertainties and provided the Hyper-X project an important indication that the vehicle would likely be successful in accomplishing the mission objectives. The X-43A inflight performance is compared to the preflight Monte Carlo predictions and shown to exceed the Monte Carlo bounds in several instances. Possible modeling shortfalls are presented that may account for these discrepancies. The flight control laws and guidance algorithms were robust enough as a result of the preflight Monte Carlo analysis that the unexpected in-flight performance did not have undue consequences. Modeling and Monte Carlo analysis lessons learned are presented.

The X-43A Six Degree of Freedom Monte Carlo Analysis

NASA Technical Reports Server (NTRS)

Baumann, Ethan; Bahm, Catherine; Strovers, Brian; Beck, Roger; Richard, Michael

2007-01-01

This report provides an overview of the Hyper-X research vehicle Monte Carlo analysis conducted with the six-degree-of-freedom simulation. The methodology and model uncertainties used for the Monte Carlo analysis are presented as permitted. In addition, the process used to select hardware validation test cases from the Monte Carlo data is described. The preflight Monte Carlo analysis indicated that the X-43A control system was robust to the preflight uncertainties and provided the Hyper-X project an important indication that the vehicle would likely be successful in accomplishing the mission objectives. The X-43A in-flight performance is compared to the preflight Monte Carlo predictions and shown to exceed the Monte Carlo bounds in several instances. Possible modeling shortfalls are presented that may account for these discrepancies. The flight control laws and guidance algorithms were robust enough as a result of the preflight Monte Carlo analysis that the unexpected in-flight performance did not have undue consequences. Modeling and Monte Carlo analysis lessons learned are presented.

A comparison of Monte Carlo-based Bayesian parameter estimation methods for stochastic models of genetic networks

PubMed Central

Zaikin, Alexey; Míguez, Joaquín

2017-01-01

We compare three state-of-the-art Bayesian inference methods for the estimation of the unknown parameters in a stochastic model of a genetic network. In particular, we introduce a stochastic version of the paradigmatic synthetic multicellular clock model proposed by Ullner et al., 2007. By introducing dynamical noise in the model and assuming that the partial observations of the system are contaminated by additive noise, we enable a principled mechanism to represent experimental uncertainties in the synthesis of the multicellular system and pave the way for the design of probabilistic methods for the estimation of any unknowns in the model. Within this setup, we tackle the Bayesian estimation of a subset of the model parameters. Specifically, we compare three Monte Carlo based numerical methods for the approximation of the posterior probability density function of the unknown parameters given a set of partial and noisy observations of the system. The schemes we assess are the particle Metropolis-Hastings (PMH) algorithm, the nonlinear population Monte Carlo (NPMC) method and the approximate Bayesian computation sequential Monte Carlo (ABC-SMC) scheme. We present an extensive numerical simulation study, which shows that while the three techniques can effectively solve the problem there are significant differences both in estimation accuracy and computational efficiency. PMID:28797087

The unbiasedness of a generalized mirage boundary correction method for Monte Carlo integration estimators of volume

Treesearch

Thomas B. Lynch; Jeffrey H. Gove

2014-01-01

The typical "double counting" application of the mirage method of boundary correction cannot be applied to sampling systems such as critical height sampling (CHS) that are based on a Monte Carlo sample of a tree (or debris) attribute because the critical height (or other random attribute) sampled from a mirage point is generally not equal to the critical...

SU-F-I-53: Coded Aperture Coherent Scatter Spectral Imaging of the Breast: A Monte Carlo Evaluation of Absorbed Dose

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morris, R; Lakshmanan, M; Fong, G

Purpose: Coherent scatter based imaging has shown improved contrast and molecular specificity over conventional digital mammography however the biological risks have not been quantified due to a lack of accurate information on absorbed dose. This study intends to characterize the dose distribution and average glandular dose from coded aperture coherent scatter spectral imaging of the breast. The dose deposited in the breast from this new diagnostic imaging modality has not yet been quantitatively evaluated. Here, various digitized anthropomorphic phantoms are tested in a Monte Carlo simulation to evaluate the absorbed dose distribution and average glandular dose using clinically feasible scanmore » protocols. Methods: Geant4 Monte Carlo radiation transport simulation software is used to replicate the coded aperture coherent scatter spectral imaging system. Energy sensitive, photon counting detectors are used to characterize the x-ray beam spectra for various imaging protocols. This input spectra is cross-validated with the results from XSPECT, a commercially available application that yields x-ray tube specific spectra for the operating parameters employed. XSPECT is also used to determine the appropriate number of photons emitted per mAs of tube current at a given kVp tube potential. With the implementation of the XCAT digital anthropomorphic breast phantom library, a variety of breast sizes with differing anatomical structure are evaluated. Simulations were performed with and without compression of the breast for dose comparison. Results: Through the Monte Carlo evaluation of a diverse population of breast types imaged under real-world scan conditions, a clinically relevant average glandular dose for this new imaging modality is extrapolated. Conclusion: With access to the physical coherent scatter imaging system used in the simulation, the results of this Monte Carlo study may be used to directly influence the future development of the modality to keep breast dose to a minimum while still maintaining clinically viable image quality.« less

A variational Monte Carlo study of different spin configurations of electron-hole bilayer

NASA Astrophysics Data System (ADS)

Sharma, Rajesh O.; Saini, L. K.; Bahuguna, Bhagwati Prasad

2018-05-01

We report quantum Monte Carlo results for mass-asymmetric electron-hole bilayer (EHBL) system with different-different spin configurations. Particularly, we apply a variational Monte Carlo method to estimate the ground-state energy, condensate fraction and pair-correlations function at fixed density rs = 5 and interlayer distance d = 1 a.u. We find that spin-configuration of EHBL system, which consists of only up-electrons in one layer and down-holes in other i.e. ferromagnetic arrangement within layers and anti-ferromagnetic across the layers, is more stable than the other spin-configurations considered in this study.

MC3: Multi-core Markov-chain Monte Carlo code

NASA Astrophysics Data System (ADS)

Cubillos, Patricio; Harrington, Joseph; Lust, Nate; Foster, AJ; Stemm, Madison; Loredo, Tom; Stevenson, Kevin; Campo, Chris; Hardin, Matt; Hardy, Ryan

2016-10-01

MC3 (Multi-core Markov-chain Monte Carlo) is a Bayesian statistics tool that can be executed from the shell prompt or interactively through the Python interpreter with single- or multiple-CPU parallel computing. It offers Markov-chain Monte Carlo (MCMC) posterior-distribution sampling for several algorithms, Levenberg-Marquardt least-squares optimization, and uniform non-informative, Jeffreys non-informative, or Gaussian-informative priors. MC3 can share the same value among multiple parameters and fix the value of parameters to constant values, and offers Gelman-Rubin convergence testing and correlated-noise estimation with time-averaging or wavelet-based likelihood estimation methods.

Monte Carlo simulations of coherent backscatter for identification of the optical coefficients of biological tissues in vivo

NASA Astrophysics Data System (ADS)

Eddowes, M. H.; Mills, T. N.; Delpy, D. T.

1995-05-01

A Monte Carlo model of light backscattered from turbid media has been used to simulate the effects of weak localization in biological tissues. A validation technique is used that implies that for the scattering and absorption coefficients and for refractive index mismatches found in tissues, the Monte Carlo method is likely to provide more accurate results than the methods previously used. The model also has the ability to simulate the effects of various illumination profiles and other laboratory-imposed conditions. A curve-fitting routine has been developed that might be used to extract the optical coefficients from the angular intensity profiles seen in experiments on turbid biological tissues, data that could be obtained in vivo.

Comparison of doses calculated by the Monte Carlo method and measured by LiF TLD in the buildup region for a 60Co photon beam.

PubMed

Budanec, M; Knezević, Z; Bokulić, T; Mrcela, I; Vrtar, M; Vekić, B; Kusić, Z

2008-12-01

This work studied the percent depth doses of (60)Co photon beams in the buildup region of a plastic phantom by LiF TLD measurements and by Monte Carlo calculations. An agreement within +/-1.5% was found between PDDs measured by TLD and calculated by the Monte Carlo method with the TLD in a plastic phantom. The dose in the plastic phantom was scored in voxels, with thickness scaled by physical and electron density. PDDs calculated by electron density scaling showed a better match with PDD(TLD)(MC); the difference is within +/-1.5% in the buildup region for square and rectangular field sizes.

Split Orthogonal Group: A Guiding Principle for Sign-Problem-Free Fermionic Simulations

NASA Astrophysics Data System (ADS)

Wang, Lei; Liu, Ye-Hua; Iazzi, Mauro; Troyer, Matthias; Harcos, Gergely

2015-12-01

We present a guiding principle for designing fermionic Hamiltonians and quantum Monte Carlo (QMC) methods that are free from the infamous sign problem by exploiting the Lie groups and Lie algebras that appear naturally in the Monte Carlo weight of fermionic QMC simulations. Specifically, rigorous mathematical constraints on the determinants involving matrices that lie in the split orthogonal group provide a guideline for sign-free simulations of fermionic models on bipartite lattices. This guiding principle not only unifies the recent solutions of the sign problem based on the continuous-time quantum Monte Carlo methods and the Majorana representation, but also suggests new efficient algorithms to simulate physical systems that were previously prohibitive because of the sign problem.

Online sequential Monte Carlo smoother for partially observed diffusion processes

NASA Astrophysics Data System (ADS)

Gloaguen, Pierre; Étienne, Marie-Pierre; Le Corff, Sylvain

2018-12-01

This paper introduces a new algorithm to approximate smoothed additive functionals of partially observed diffusion processes. This method relies on a new sequential Monte Carlo method which allows to compute such approximations online, i.e., as the observations are received, and with a computational complexity growing linearly with the number of Monte Carlo samples. The original algorithm cannot be used in the case of partially observed stochastic differential equations since the transition density of the latent data is usually unknown. We prove that it may be extended to partially observed continuous processes by replacing this unknown quantity by an unbiased estimator obtained for instance using general Poisson estimators. This estimator is proved to be consistent and its performance are illustrated using data from two models.

CTRANS: A Monte Carlo program for radiative transfer in plane parallel atmospheres with imbedded finite clouds: Development, testing and user's guide

NASA Technical Reports Server (NTRS)

1976-01-01

The program called CTRANS is described which was designed to perform radiative transfer computations in an atmosphere with horizontal inhomogeneities (clouds). Since the atmosphere-ground system was to be richly detailed, the Monte Carlo method was employed. This means that results are obtained through direct modeling of the physical process of radiative transport. The effects of atmopheric or ground albedo pattern detail are essentially built up from their impact upon the transport of individual photons. The CTRANS program actually tracks the photons backwards through the atmosphere, initiating them at a receiver and following them backwards along their path to the Sun. The pattern of incident photons generated through backwards tracking automatically reflects the importance to the receiver of each region of the sky. Further, through backwards tracking, the impact of the finite field of view of the receiver and variations in its response over the field of view can be directly simulated.

Monte Carlo simulation to investigate the formation of molecular hydrogen and its deuterated forms

NASA Astrophysics Data System (ADS)

Sahu, Dipen; Das, Ankan; Majumdar, Liton; Chakrabarti, Sandip K.

2015-07-01

H2 is the most abundant interstellar species, and its deuterated forms (HD and D2) are also present in high abundance. The high abundance of these molecules could be explained by considering the chemistry that occurs on interstellar dust. Because of its simplicity, the rate equation method is widely used to study the formation of grain-surface species. However, because the recombination efficiency for the formation of any surface species is highly dependent on various physical and chemical parameters, the Monte Carlo method is best suited for addressing the randomness of the processes. We perform Monte Carlo simulations to study the formation of H2, HD and D2 on interstellar ice. The adsorption energies of surface species are the key inputs for the formation of any species on interstellar dusts, but the binding energies of deuterated species have yet to be determined with certainty. A zero-point energy correction exists between hydrogenated and deuterated species, which should be considered during modeling of the chemistry on interstellar dusts. Following some previous studies, we consider various sets of adsorption energies to investigate the formation of these species under diverse physical conditions. As expected, notable differences in these two approaches (rate equation method and Monte Carlo method) are observed for the production of these simple molecules on interstellar ice. We introduce two factors, namely, Sf and β , to explain these discrepancies: Sf is a scaling factor, which can be used to correlate the discrepancies between the rate equation and Monte Carlo methods, and β indicates the formation efficiency under various conditions. Higher values of β indicate a lower production efficiency. We observed that β increases with a decrease in the rate of accretion from the gas phase to the grain phase.

Statistical Analysis of the Uncertainty in Pre-Flight Aerodynamic Database of a Hypersonic Vehicle

NASA Astrophysics Data System (ADS)

Huh, Lynn

The objective of the present research was to develop a new method to derive the aerodynamic coefficients and the associated uncertainties for flight vehicles via post- flight inertial navigation analysis using data from the inertial measurement unit. Statistical estimates of vehicle state and aerodynamic coefficients are derived using Monte Carlo simulation. Trajectory reconstruction using the inertial navigation system (INS) is a simple and well used method. However, deriving realistic uncertainties in the reconstructed state and any associated parameters is not so straight forward. Extended Kalman filters, batch minimum variance estimation and other approaches have been used. However, these methods generally depend on assumed physical models, assumed statistical distributions (usually Gaussian) or have convergence issues for non-linear problems. The approach here assumes no physical models, is applicable to any statistical distribution, and does not have any convergence issues. The new approach obtains the statistics directly from a sufficient number of Monte Carlo samples using only the generally well known gyro and accelerometer specifications and could be applied to the systems of non-linear form and non-Gaussian distribution. When redundant data are available, the set of Monte Carlo simulations are constrained to satisfy the redundant data within the uncertainties specified for the additional data. The proposed method was applied to validate the uncertainty in the pre-flight aerodynamic database of the X-43A Hyper-X research vehicle. In addition to gyro and acceleration data, the actual flight data include redundant measurements of position and velocity from the global positioning system (GPS). The criteria derived from the blend of the GPS and INS accuracy was used to select valid trajectories for statistical analysis. The aerodynamic coefficients were derived from the selected trajectories by either direct extraction method based on the equations in dynamics, or by the inquiry of the pre-flight aerodynamic database. After the application of the proposed method to the case of the X-43A Hyper-X research vehicle, it was found that 1) there were consistent differences in the aerodynamic coefficients from the pre-flight aerodynamic database and post-flight analysis, 2) the pre-flight estimation of the pitching moment coefficients was significantly different from the post-flight analysis, 3) the type of distribution of the states from the Monte Carlo simulation were affected by that of the perturbation parameters, 4) the uncertainties in the pre-flight model were overestimated, 5) the range where the aerodynamic coefficients from the pre-flight aerodynamic database and post-flight analysis are in closest agreement is between Mach *.* and *.* and more data points may be needed between Mach * and ** in the pre-flight aerodynamic database, 6) selection criterion for valid trajectories from the Monte Carlo simulations was mostly driven by the horizontal velocity error, 7) the selection criterion must be based on reasonable model to ensure the validity of the statistics from the proposed method, and 8) the results from the proposed method applied to the two different flights with the identical geometry and similar flight profile were consistent.

Radiative interactions in multi-dimensional chemically reacting flows using Monte Carlo simulations

NASA Technical Reports Server (NTRS)

Liu, Jiwen; Tiwari, Surendra N.

1994-01-01

The Monte Carlo method (MCM) is applied to analyze radiative heat transfer in nongray gases. The nongray model employed is based on the statistical narrow band model with an exponential-tailed inverse intensity distribution. The amount and transfer of the emitted radiative energy in a finite volume element within a medium are considered in an exact manner. The spectral correlation between transmittances of two different segments of the same path in a medium makes the statistical relationship different from the conventional relationship, which only provides the non-correlated results for nongray methods is discussed. Validation of the Monte Carlo formulations is conducted by comparing results of this method of other solutions. In order to further establish the validity of the MCM, a relatively simple problem of radiative interactions in laminar parallel plate flows is considered. One-dimensional correlated Monte Carlo formulations are applied to investigate radiative heat transfer. The nongray Monte Carlo solutions are also obtained for the same problem and they also essentially match the available analytical solutions. the exact correlated and non-correlated Monte Carlo formulations are very complicated for multi-dimensional systems. However, by introducing the assumption of an infinitesimal volume element, the approximate correlated and non-correlated formulations are obtained which are much simpler than the exact formulations. Consideration of different problems and comparison of different solutions reveal that the approximate and exact correlated solutions agree very well, and so do the approximate and exact non-correlated solutions. However, the two non-correlated solutions have no physical meaning because they significantly differ from the correlated solutions. An accurate prediction of radiative heat transfer in any nongray and multi-dimensional system is possible by using the approximate correlated formulations. Radiative interactions are investigated in chemically reacting compressible flows of premixed hydrogen and air in an expanding nozzle. The governing equations are based on the fully elliptic Navier-Stokes equations. Chemical reaction mechanisms were described by a finite rate chemistry model. The correlated Monte Carlo method developed earlier was employed to simulate multi-dimensional radiative heat transfer. Results obtained demonstrate that radiative effects on the flowfield are minimal but radiative effects on the wall heat transfer are significant. Extensive parametric studies are conducted to investigate the effects of equivalence ratio, wall temperature, inlet flow temperature, and nozzle size on the radiative and conductive wall fluxes.

Monte Carlo Methods in Materials Science Based on FLUKA and ROOT

NASA Technical Reports Server (NTRS)

Pinsky, Lawrence; Wilson, Thomas; Empl, Anton; Andersen, Victor

2003-01-01

A comprehensive understanding of mitigation measures for space radiation protection necessarily involves the relevant fields of nuclear physics and particle transport modeling. One method of modeling the interaction of radiation traversing matter is Monte Carlo analysis, a subject that has been evolving since the very advent of nuclear reactors and particle accelerators in experimental physics. Countermeasures for radiation protection from neutrons near nuclear reactors, for example, were an early application and Monte Carlo methods were quickly adapted to this general field of investigation. The project discussed here is concerned with taking the latest tools and technology in Monte Carlo analysis and adapting them to space applications such as radiation shielding design for spacecraft, as well as investigating how next-generation Monte Carlos can complement the existing analytical methods currently used by NASA. We have chosen to employ the Monte Carlo program known as FLUKA (A legacy acronym based on the German for FLUctuating KAscade) used to simulate all of the particle transport, and the CERN developed graphical-interface object-oriented analysis software called ROOT. One aspect of space radiation analysis for which the Monte Carlo s are particularly suited is the study of secondary radiation produced as albedoes in the vicinity of the structural geometry involved. This broad goal of simulating space radiation transport through the relevant materials employing the FLUKA code necessarily requires the addition of the capability to simulate all heavy-ion interactions from 10 MeV/A up to the highest conceivable energies. For all energies above 3 GeV/A the Dual Parton Model (DPM) is currently used, although the possible improvement of the DPMJET event generator for energies 3-30 GeV/A is being considered. One of the major tasks still facing us is the provision for heavy ion interactions below 3 GeV/A. The ROOT interface is being developed in conjunction with the CERN ALICE (A Large Ion Collisions Experiment) software team through an adaptation of their existing AliROOT (ALICE Using ROOT) architecture. In order to check our progress against actual data, we have chosen to simulate the ATIC14 (Advanced Thin Ionization Calorimeter) cosmic-ray astrophysics balloon payload as well as neutron fluences in the Mir spacecraft. This paper contains a summary of status of this project, and a roadmap to its successful completion.

Monte Carlo investigation of transient acoustic fields in partially or completely bounded medium. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Thanedar, B. D.

1972-01-01

A simple repetitive calculation was used to investigate what happens to the field in terms of the signal paths of disturbances originating from the energy source. The computation allowed the field to be reconstructed as a function of space and time on a statistical basis. The suggested Monte Carlo method is in response to the need for a numerical method to supplement analytical methods of solution which are only valid when the boundaries have simple shapes, rather than for a medium that is bounded. For the analysis, a suitable model was created from which was developed an algorithm for the estimation of acoustic pressure variations in the region under investigation. The validity of the technique was demonstrated by analysis of simple physical models with the aid of a digital computer. The Monte Carlo method is applicable to a medium which is homogeneous and is enclosed by either rectangular or curved boundaries.

Coupled particle-in-cell and Monte Carlo transport modeling of intense radiographic sources

NASA Astrophysics Data System (ADS)

Rose, D. V.; Welch, D. R.; Oliver, B. V.; Clark, R. E.; Johnson, D. L.; Maenchen, J. E.; Menge, P. R.; Olson, C. L.; Rovang, D. C.

2002-03-01

Dose-rate calculations for intense electron-beam diodes using particle-in-cell (PIC) simulations along with Monte Carlo electron/photon transport calculations are presented. The electromagnetic PIC simulations are used to model the dynamic operation of the rod-pinch and immersed-B diodes. These simulations include algorithms for tracking electron scattering and energy loss in dense materials. The positions and momenta of photons created in these materials are recorded and separate Monte Carlo calculations are used to transport the photons to determine the dose in far-field detectors. These combined calculations are used to determine radiographer equations (dose scaling as a function of diode current and voltage) that are compared directly with measured dose rates obtained on the SABRE generator at Sandia National Laboratories.

Full System Model of Magnetron Sputter Chamber - Proof-of-Principle Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Walton, C; Gilmer, G; Zepeda-Ruiz, L

2007-05-04

The lack of detailed knowledge of internal process conditions remains a key challenge in magnetron sputtering, both for chamber design and for process development. Fundamental information such as the pressure and temperature distribution of the sputter gas, and the energies and arrival angles of the sputtered atoms and other energetic species is often missing, or is only estimated from general formulas. However, open-source or low-cost tools are available for modeling most steps of the sputter process, which can give more accurate and complete data than textbook estimates, using only desktop computations. To get a better understanding of magnetron sputtering, wemore » have collected existing models for the 5 major process steps: the input and distribution of the neutral background gas using Direct Simulation Monte Carlo (DSMC), dynamics of the plasma using Particle In Cell-Monte Carlo Collision (PIC-MCC), impact of ions on the target using molecular dynamics (MD), transport of sputtered atoms to the substrate using DSMC, and growth of the film using hybrid Kinetic Monte Carlo (KMC) and MD methods. Models have been tested against experimental measurements. For example, gas rarefaction as observed by Rossnagel and others has been reproduced, and it is associated with a local pressure increase of {approx}50% which may strongly influence film properties such as stress. Results on energies and arrival angles of sputtered atoms and reflected gas neutrals are applied to the Kinetic Monte Carlo simulation of film growth. Model results and applications to growth of dense Cu and Be films are presented.« less

Comparison of discrete ordinate and Monte Carlo simulations of polarized radiative transfer in two coupled slabs with different refractive indices.

PubMed

Cohen, D; Stamnes, S; Tanikawa, T; Sommersten, E R; Stamnes, J J; Lotsberg, J K; Stamnes, K

2013-04-22

A comparison is presented of two different methods for polarized radiative transfer in coupled media consisting of two adjacent slabs with different refractive indices, each slab being a stratified medium with no change in optical properties except in the direction of stratification. One of the methods is based on solving the integro-differential radiative transfer equation for the two coupled slabs using the discrete ordinate approximation. The other method is based on probabilistic and statistical concepts and simulates the propagation of polarized light using the Monte Carlo approach. The emphasis is on non-Rayleigh scattering for particles in the Mie regime. Comparisons with benchmark results available for a slab with constant refractive index show that both methods reproduce these benchmark results when the refractive index is set to be the same in the two slabs. Computed results for test cases with coupling (different refractive indices in the two slabs) show that the two methods produce essentially identical results for identical input in terms of absorption and scattering coefficients and scattering phase matrices.

DSMC Modeling of Flows with Recombination Reactions

DTIC Science & Technology

2017-06-23

Rogasinsky, “Analysis of the numerical techniques of the direct simulation Monte Carlo method in the rarefied gas dynamics,” Russ. J. Numer. Anal. Math ...reflection in steady flows,” Comput. Math . Appl. 35(1-2), 113–126 (1998). 45K. L. Wray, “Shock-tube study of the recombination of O atoms by Ar catalysts at

Computation of Neutral Gas Flow from a Hall Thruster into a Vacuum Chamber

DTIC Science & Technology

2002-10-18

try to quantify these effects, the direct simulation Monte Carlo method is applied to model a cold flow of xenon gas expanding from a Hall thruster into...a vacuum chamber. The simulations are performed for the P5 Hall thruster operating in a large vacuum tank at the University of Michigan. Comparison

Impact Ionization: Beyond the Golden Rule

DTIC Science & Technology

1992-01-01

3]. Hence, the use electronic kinetic energy, H. is the phonon bath Hamil- of Monte Carlo methods combined with density matrix tonian, HA, is the...0 o5 () Wace i.a (bN w...,,,ae (W ( Ib) k- Figure 2. (a) Ionization rate in the 1 11 > direction. Figure 3. (a) Equal ionization rate curves in the k

Development of Monte Carlo based real-time treatment planning system with fast calculation algorithm for boron neutron capture therapy.

PubMed

Takada, Kenta; Kumada, Hiroaki; Liem, Peng Hong; Sakurai, Hideyuki; Sakae, Takeji

2016-12-01

We simulated the effect of patient displacement on organ doses in boron neutron capture therapy (BNCT). In addition, we developed a faster calculation algorithm (NCT high-speed) to simulate irradiation more efficiently. We simulated dose evaluation for the standard irradiation position (reference position) using a head phantom. Cases were assumed where the patient body is shifted in lateral directions compared to the reference position, as well as in the direction away from the irradiation aperture. For three groups of neutron (thermal, epithermal, and fast), flux distribution using NCT high-speed with a voxelized homogeneous phantom was calculated. The three groups of neutron fluxes were calculated for the same conditions with Monte Carlo code. These calculated results were compared. In the evaluations of body movements, there were no significant differences even with shifting up to 9mm in the lateral directions. However, the dose decreased by about 10% with shifts of 9mm in a direction away from the irradiation aperture. When comparing both calculations in the phantom surface up to 3cm, the maximum differences between the fluxes calculated by NCT high-speed with those calculated by Monte Carlo code for thermal neutrons and epithermal neutrons were 10% and 18%, respectively. The time required for NCT high-speed code was about 1/10th compared to Monte Carlo calculation. In the evaluation, the longitudinal displacement has a considerable effect on the organ doses. We also achieved faster calculation of depth distribution of thermal neutron flux using NCT high-speed calculation code. Copyright © 2016 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Monte Carlo Bayesian Inference on a Statistical Model of Sub-Gridcolumn Moisture Variability using High-Resolution Cloud Observations

NASA Astrophysics Data System (ADS)

Norris, P. M.; da Silva, A. M., Jr.

2016-12-01

Norris and da Silva recently published a method to constrain a statistical model of sub-gridcolumn moisture variability using high-resolution satellite cloud data. The method can be used for large-scale model parameter estimation or cloud data assimilation (CDA). The gridcolumn model includes assumed-PDF intra-layer horizontal variability and a copula-based inter-layer correlation model. The observables used are MODIS cloud-top pressure, brightness temperature and cloud optical thickness, but the method should be extensible to direct cloudy radiance assimilation for a small number of channels. The algorithm is a form of Bayesian inference with a Markov chain Monte Carlo (MCMC) approach to characterizing the posterior distribution. This approach is especially useful in cases where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach is not gradient-based and allows jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast where the background state has a clear swath. The new approach not only significantly reduces mean and standard deviation biases with respect to the assimilated observables, but also improves the simulated rotational-Ramman scattering cloud optical centroid pressure against independent (non-assimilated) retrievals from the OMI instrument. One obvious difficulty for the method, and other CDA methods, is the lack of information content in passive cloud observables on cloud vertical structure, beyond cloud-top and thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification due to Riishojgaard is helpful, better honoring inversion structures in the background state.

Theoretical Grounds for the Propagation of Uncertainties in Monte Carlo Particle Transport

NASA Astrophysics Data System (ADS)

Saracco, Paolo; Pia, Maria Grazia; Batic, Matej

2014-04-01

We introduce a theoretical framework for the calculation of uncertainties affecting observables produced by Monte Carlo particle transport, which derive from uncertainties in physical parameters input into simulation. The theoretical developments are complemented by a heuristic application, which illustrates the method of calculation in a streamlined simulation environment.

A Monte Carlo Approach for Adaptive Testing with Content Constraints

ERIC Educational Resources Information Center

Belov, Dmitry I.; Armstrong, Ronald D.; Weissman, Alexander

2008-01-01

This article presents a new algorithm for computerized adaptive testing (CAT) when content constraints are present. The algorithm is based on shadow CAT methodology to meet content constraints but applies Monte Carlo methods and provides the following advantages over shadow CAT: (a) lower maximum item exposure rates, (b) higher utilization of the…

Testing the Intervention Effect in Single-Case Experiments: A Monte Carlo Simulation Study

ERIC Educational Resources Information Center

Heyvaert, Mieke; Moeyaert, Mariola; Verkempynck, Paul; Van den Noortgate, Wim; Vervloet, Marlies; Ugille, Maaike; Onghena, Patrick

2017-01-01

This article reports on a Monte Carlo simulation study, evaluating two approaches for testing the intervention effect in replicated randomized AB designs: two-level hierarchical linear modeling (HLM) and using the additive method to combine randomization test "p" values (RTcombiP). Four factors were manipulated: mean intervention effect,…

Asteroid mass estimation with Markov-chain Monte Carlo

NASA Astrophysics Data System (ADS)

Siltala, L.; Granvik, M.

2017-09-01

We have developed a new Markov-chain Monte Carlo-based algorithm for asteroid mass estimation based on mutual encounters and tested it for several different asteroids. Our results are in line with previous literature values but suggest that uncertainties of prior estimates may be misleading as a consequence of using linearized methods.

WARP

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bergmann, Ryan M.; Rowland, Kelly L.

2017-04-12

WARP, which can stand for ``Weaving All the Random Particles,'' is a three-dimensional (3D) continuous energy Monte Carlo neutron transport code developed at UC Berkeley to efficiently execute on NVIDIA graphics processing unit (GPU) platforms. WARP accelerates Monte Carlo simulations while preserving the benefits of using the Monte Carlo method, namely, that very few physical and geometrical simplifications are applied. WARP is able to calculate multiplication factors, neutron flux distributions (in both space and energy), and fission source distributions for time-independent neutron transport problems. It can run in both criticality or fixed source modes, but fixed source mode is currentlymore » not robust, optimized, or maintained in the newest version. WARP can transport neutrons in unrestricted arrangements of parallelepipeds, hexagonal prisms, cylinders, and spheres. The goal of developing WARP is to investigate algorithms that can grow into a full-featured, continuous energy, Monte Carlo neutron transport code that is accelerated by running on GPUs. The crux of the effort is to make Monte Carlo calculations faster while producing accurate results. Modern supercomputers are commonly being built with GPU coprocessor cards in their nodes to increase their computational efficiency and performance. GPUs execute efficiently on data-parallel problems, but most CPU codes, including those for Monte Carlo neutral particle transport, are predominantly task-parallel. WARP uses a data-parallel neutron transport algorithm to take advantage of the computing power GPUs offer.« less

A Finite Element Projection Method for the Solution of Particle Transport Problems with Anisotropic Scattering.

DTIC Science & Technology

1984-07-01

piecewise constant energy dependence. This is a seven-dimensional problem with time dependence, three spatial and two angular or directional variables and...in extending the computer implementation of the method to time and energy dependent problems, and to solving and validating this technique on a...problems they have severe limitations. The Monte Carlo method, usually requires the use of many hours of expensive computer time , and for deep

Stopping power and dose calculations with analytical and Monte Carlo methods for protons and prompt gamma range verification

NASA Astrophysics Data System (ADS)

Usta, Metin; Tufan, Mustafa Çağatay; Aydın, Güral; Bozkurt, Ahmet

2018-07-01

In this study, we have performed the calculations stopping power, depth dose, and range verification for proton beams using dielectric and Bethe-Bloch theories and FLUKA, Geant4 and MCNPX Monte Carlo codes. In the framework, as analytical studies, Drude model was applied for dielectric theory and effective charge approach with Roothaan-Hartree-Fock charge densities was used in Bethe theory. In the simulations different setup parameters were selected to evaluate the performance of three distinct Monte Carlo codes. The lung and breast tissues were investigated are considered to be related to the most common types of cancer throughout the world. The results were compared with each other and the available data in literature. In addition, the obtained results were verified with prompt gamma range data. In both stopping power values and depth-dose distributions, it was found that the Monte Carlo values give better results compared with the analytical ones while the results that agree best with ICRU data in terms of stopping power are those of the effective charge approach between the analytical methods and of the FLUKA code among the MC packages. In the depth dose distributions of the examined tissues, although the Bragg curves for Monte Carlo almost overlap, the analytical ones show significant deviations that become more pronounce with increasing energy. Verifications with the results of prompt gamma photons were attempted for 100-200 MeV protons which are regarded important for proton therapy. The analytical results are within 2%-5% and the Monte Carlo values are within 0%-2% as compared with those of the prompt gammas.

Finite element model updating using the shadow hybrid Monte Carlo technique

NASA Astrophysics Data System (ADS)

Boulkaibet, I.; Mthembu, L.; Marwala, T.; Friswell, M. I.; Adhikari, S.

2015-02-01

Recent research in the field of finite element model updating (FEM) advocates the adoption of Bayesian analysis techniques to dealing with the uncertainties associated with these models. However, Bayesian formulations require the evaluation of the Posterior Distribution Function which may not be available in analytical form. This is the case in FEM updating. In such cases sampling methods can provide good approximations of the Posterior distribution when implemented in the Bayesian context. Markov Chain Monte Carlo (MCMC) algorithms are the most popular sampling tools used to sample probability distributions. However, the efficiency of these algorithms is affected by the complexity of the systems (the size of the parameter space). The Hybrid Monte Carlo (HMC) offers a very important MCMC approach to dealing with higher-dimensional complex problems. The HMC uses the molecular dynamics (MD) steps as the global Monte Carlo (MC) moves to reach areas of high probability where the gradient of the log-density of the Posterior acts as a guide during the search process. However, the acceptance rate of HMC is sensitive to the system size as well as the time step used to evaluate the MD trajectory. To overcome this limitation we propose the use of the Shadow Hybrid Monte Carlo (SHMC) algorithm. The SHMC algorithm is a modified version of the Hybrid Monte Carlo (HMC) and designed to improve sampling for large-system sizes and time steps. This is done by sampling from a modified Hamiltonian function instead of the normal Hamiltonian function. In this paper, the efficiency and accuracy of the SHMC method is tested on the updating of two real structures; an unsymmetrical H-shaped beam structure and a GARTEUR SM-AG19 structure and is compared to the application of the HMC algorithm on the same structures.

Evaluation of gamma-ray attenuation properties of bismuth borate glass systems using Monte Carlo method

NASA Astrophysics Data System (ADS)

Tarim, Urkiye Akar; Ozmutlu, Emin N.; Yalcin, Sezai; Gundogdu, Ozcan; Bradley, D. A.; Gurler, Orhan

2017-11-01

A Monte Carlo method was developed to investigate radiation shielding properties of bismuth borate glass. The mass attenuation coefficients and half-value layer parameters were determined for different fractional amounts of Bi2O3 in the glass samples for the 356, 662, 1173 and 1332 keV photon energies. A comparison of the theoretical and experimental attenuation coefficients is presented.

Monte Carlo calculation of dynamical properties of the two-dimensional Hubbard model

NASA Technical Reports Server (NTRS)

White, S. R.; Scalapino, D. J.; Sugar, R. L.; Bickers, N. E.

1989-01-01

A new method is introduced for analytically continuing imaginary-time data from quantum Monte Carlo calculations to the real-frequency axis. The method is based on a least-squares-fitting procedure with constraints of positivity and smoothness on the real-frequency quantities. Results are shown for the single-particle spectral-weight function and density of states for the half-filled, two-dimensional Hubbard model.

MONTE CARLO METHODS. A Bibliography covering the Period 1949 to June 1961

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kraft, R.; Wensrich, C.J.

1961-09-11

A partially annotated bibliography is presented containing 508 references to Monte Carlo methods, covering the period from 1947 to June 1961. The references are arranged alphabetically by author. The sources consulted include: Abstracts of Classified Reports; Applied Science and Technology Index; Armed Services Technical Information Agency; Bibliographic Index; Bibliographie der Fremsprachigen Zeitschrifften Literatur; Mathematical Reviews; Nuclear Science Abstracts; and Operations Research, an Annotated Bibliography. (T.F.H.)

Inverse Monte Carlo method in a multilayered tissue model for diffuse reflectance spectroscopy

NASA Astrophysics Data System (ADS)

Fredriksson, Ingemar; Larsson, Marcus; Strömberg, Tomas

2012-04-01

Model based data analysis of diffuse reflectance spectroscopy data enables the estimation of optical and structural tissue parameters. The aim of this study was to present an inverse Monte Carlo method based on spectra from two source-detector distances (0.4 and 1.2 mm), using a multilayered tissue model. The tissue model variables include geometrical properties, light scattering properties, tissue chromophores such as melanin and hemoglobin, oxygen saturation and average vessel diameter. The method utilizes a small set of presimulated Monte Carlo data for combinations of different levels of epidermal thickness and tissue scattering. The path length distributions in the different layers are stored and the effect of the other parameters is added in the post-processing. The accuracy of the method was evaluated using Monte Carlo simulations of tissue-like models containing discrete blood vessels, evaluating blood tissue fraction and oxygenation. It was also compared to a homogeneous model. The multilayer model performed better than the homogeneous model and all tissue parameters significantly improved spectral fitting. Recorded in vivo spectra were fitted well at both distances, which we previously found was not possible with a homogeneous model. No absolute intensity calibration is needed and the algorithm is fast enough for real-time processing.

Generalizing the self-healing diffusion Monte Carlo approach to finite temperature: a path for the optimization of low-energy many-body bases.

PubMed

Reboredo, Fernando A; Kim, Jeongnim

2014-02-21

A statistical method is derived for the calculation of thermodynamic properties of many-body systems at low temperatures. This method is based on the self-healing diffusion Monte Carlo method for complex functions [F. A. Reboredo, J. Chem. Phys. 136, 204101 (2012)] and some ideas of the correlation function Monte Carlo approach [D. M. Ceperley and B. Bernu, J. Chem. Phys. 89, 6316 (1988)]. In order to allow the evolution in imaginary time to describe the density matrix, we remove the fixed-node restriction using complex antisymmetric guiding wave functions. In the process we obtain a parallel algorithm that optimizes a small subspace of the many-body Hilbert space to provide maximum overlap with the subspace spanned by the lowest-energy eigenstates of a many-body Hamiltonian. We show in a model system that the partition function is progressively maximized within this subspace. We show that the subspace spanned by the small basis systematically converges towards the subspace spanned by the lowest energy eigenstates. Possible applications of this method for calculating the thermodynamic properties of many-body systems near the ground state are discussed. The resulting basis can also be used to accelerate the calculation of the ground or excited states with quantum Monte Carlo.

Generalizing the self-healing diffusion Monte Carlo approach to finite temperature: A path for the optimization of low-energy many-body bases

NASA Astrophysics Data System (ADS)

Reboredo, Fernando A.; Kim, Jeongnim

2014-02-01

A statistical method is derived for the calculation of thermodynamic properties of many-body systems at low temperatures. This method is based on the self-healing diffusion Monte Carlo method for complex functions [F. A. Reboredo, J. Chem. Phys. 136, 204101 (2012)] and some ideas of the correlation function Monte Carlo approach [D. M. Ceperley and B. Bernu, J. Chem. Phys. 89, 6316 (1988)]. In order to allow the evolution in imaginary time to describe the density matrix, we remove the fixed-node restriction using complex antisymmetric guiding wave functions. In the process we obtain a parallel algorithm that optimizes a small subspace of the many-body Hilbert space to provide maximum overlap with the subspace spanned by the lowest-energy eigenstates of a many-body Hamiltonian. We show in a model system that the partition function is progressively maximized within this subspace. We show that the subspace spanned by the small basis systematically converges towards the subspace spanned by the lowest energy eigenstates. Possible applications of this method for calculating the thermodynamic properties of many-body systems near the ground state are discussed. The resulting basis can also be used to accelerate the calculation of the ground or excited states with quantum Monte Carlo.

Acuros CTS: A fast, linear Boltzmann transport equation solver for computed tomography scatter - Part I: Core algorithms and validation.

PubMed

Maslowski, Alexander; Wang, Adam; Sun, Mingshan; Wareing, Todd; Davis, Ian; Star-Lack, Josh

2018-05-01

To describe Acuros ® CTS, a new software tool for rapidly and accurately estimating scatter in x-ray projection images by deterministically solving the linear Boltzmann transport equation (LBTE). The LBTE describes the behavior of particles as they interact with an object across spatial, energy, and directional (propagation) domains. Acuros CTS deterministically solves the LBTE by modeling photon transport associated with an x-ray projection in three main steps: (a) Ray tracing photons from the x-ray source into the object where they experience their first scattering event and form scattering sources. (b) Propagating photons from their first scattering sources across the object in all directions to form second scattering sources, then repeating this process until all high-order scattering sources are computed using the source iteration method. (c) Ray-tracing photons from scattering sources within the object to the detector, accounting for the detector's energy and anti-scatter grid responses. To make this process computationally tractable, a combination of analytical and discrete methods is applied. The three domains are discretized using the Linear Discontinuous Finite Elements, Multigroup, and Discrete Ordinates methods, respectively, which confer the ability to maintain the accuracy of a continuous solution. Furthermore, through the implementation in CUDA, we sought to exploit the parallel computing capabilities of graphics processing units (GPUs) to achieve the speeds required for clinical utilization. Acuros CTS was validated against Geant4 Monte Carlo simulations using two digital phantoms: (a) a water phantom containing lung, air, and bone inserts (WLAB phantom) and (b) a pelvis phantom derived from a clinical CT dataset. For these studies, we modeled the TrueBeam ® (Varian Medical Systems, Palo Alto, CA) kV imaging system with a source energy of 125 kVp. The imager comprised a 600 μm-thick Cesium Iodide (CsI) scintillator and a 10:1 one-dimensional anti-scatter grid. For the WLAB studies, the full-fan geometry without a bowtie filter was used (with and without the anti-scatter grid). For the pelvis phantom studies, a half-fan geometry with bowtie was used (with the anti-scatter grid). Scattered and primary photon fluences and energies deposited in the detector were recorded. The Acuros CTS and Monte Carlo results demonstrated excellent agreement. For the WLAB studies, the average percent difference between the Monte Carlo- and Acuros-generated scattered photon fluences at the face of the detector was -0.7%. After including the detector response, the average percent differences between the Monte Carlo- and Acuros-generated scatter fractions (SF) were -0.1% without the grid and 0.6% with the grid. For the digital pelvis simulation, the Monte Carlo- and Acuros-generated SFs agreed to within 0.1% on average, despite the scatter-to-primary ratios (SPRs) being as high as 5.5. The Acuros CTS computation time for each scatter image was ~1 s using a single GPU. Acuros CTS enables a fast and accurate calculation of scatter images by deterministically solving the LBTE thus offering a computationally attractive alternative to Monte Carlo methods. Part II describes the application of Acuros CTS to scatter correction of CBCT scans on the TrueBeam system. © 2018 American Association of Physicists in Medicine.

Radiance and polarization of multiple scattered light from haze and clouds.

PubMed

Kattawar, G W; Plass, G N

1968-08-01

The radiance and polarization of multiple scattered light is calculated from the Stokes' vectors by a Monte Carlo method. The exact scattering matrix for a typical haze and for a cloud whose spherical drops have an average radius of 12 mu is calculated from the Mie theory. The Stokes' vector is transformed in a collision by this scattering matrix and the rotation matrix. The two angles that define the photon direction after scattering are chosen by a random process that correctly simulates the actual distribution functions for both angles. The Monte Carlo results for Rayleigh scattering compare favorably with well known tabulated results. Curves are given of the reflected and transmitted radiances and polarizations for both the haze and cloud models and for several solar angles, optical thicknesses, and surface albedos. The dependence on these various parameters is discussed.

Solving the master equation without kinetic Monte Carlo: Tensor train approximations for a CO oxidation model

NASA Astrophysics Data System (ADS)

Gelß, Patrick; Matera, Sebastian; Schütte, Christof

2016-06-01

In multiscale modeling of heterogeneous catalytic processes, one crucial point is the solution of a Markovian master equation describing the stochastic reaction kinetics. Usually, this is too high-dimensional to be solved with standard numerical techniques and one has to rely on sampling approaches based on the kinetic Monte Carlo method. In this study we break the curse of dimensionality for the direct solution of the Markovian master equation by exploiting the Tensor Train Format for this purpose. The performance of the approach is demonstrated on a first principles based, reduced model for the CO oxidation on the RuO2(110) surface. We investigate the complexity for increasing system size and for various reaction conditions. The advantage over the stochastic simulation approach is illustrated by a problem with increased stiffness.

Capturing nonlocal interaction effects in the Hubbard model: Optimal mappings and limits of applicability

NASA Astrophysics Data System (ADS)

van Loon, E. G. C. P.; Schüler, M.; Katsnelson, M. I.; Wehling, T. O.

2016-10-01

We investigate the Peierls-Feynman-Bogoliubov variational principle to map Hubbard models with nonlocal interactions to effective models with only local interactions. We study the renormalization of the local interaction induced by nearest-neighbor interaction and assess the quality of the effective Hubbard models in reproducing observables of the corresponding extended Hubbard models. We compare the renormalization of the local interactions as obtained from numerically exact determinant quantum Monte Carlo to approximate but more generally applicable calculations using dual boson, dynamical mean field theory, and the random phase approximation. These more approximate approaches are crucial for any application with real materials in mind. Furthermore, we use the dual boson method to calculate observables of the extended Hubbard models directly and benchmark these against determinant quantum Monte Carlo simulations of the effective Hubbard model.

Quantitative, depth-resolved determination of particle motion using multi-exposure, spatial frequency domain laser speckle imaging.

PubMed

Rice, Tyler B; Kwan, Elliott; Hayakawa, Carole K; Durkin, Anthony J; Choi, Bernard; Tromberg, Bruce J

2013-01-01

Laser Speckle Imaging (LSI) is a simple, noninvasive technique for rapid imaging of particle motion in scattering media such as biological tissue. LSI is generally used to derive a qualitative index of relative blood flow due to unknown impact from several variables that affect speckle contrast. These variables may include optical absorption and scattering coefficients, multi-layer dynamics including static, non-ergodic regions, and systematic effects such as laser coherence length. In order to account for these effects and move toward quantitative, depth-resolved LSI, we have developed a method that combines Monte Carlo modeling, multi-exposure speckle imaging (MESI), spatial frequency domain imaging (SFDI), and careful instrument calibration. Monte Carlo models were used to generate total and layer-specific fractional momentum transfer distributions. This information was used to predict speckle contrast as a function of exposure time, spatial frequency, layer thickness, and layer dynamics. To verify with experimental data, controlled phantom experiments with characteristic tissue optical properties were performed using a structured light speckle imaging system. Three main geometries were explored: 1) diffusive dynamic layer beneath a static layer, 2) static layer beneath a diffuse dynamic layer, and 3) directed flow (tube) submerged in a dynamic scattering layer. Data fits were performed using the Monte Carlo model, which accurately reconstructed the type of particle flow (diffusive or directed) in each layer, the layer thickness, and absolute flow speeds to within 15% or better.

Multimodel Ensemble Methods for Prediction of Wake-Vortex Transport and Decay Originating NASA

NASA Technical Reports Server (NTRS)

Korner, Stephan; Ahmad, Nashat N.; Holzapfel, Frank; VanValkenburg, Randal L.

2017-01-01

Several multimodel ensemble methods are selected and further developed to improve the deterministic and probabilistic prediction skills of individual wake-vortex transport and decay models. The different multimodel ensemble methods are introduced, and their suitability for wake applications is demonstrated. The selected methods include direct ensemble averaging, Bayesian model averaging, and Monte Carlo simulation. The different methodologies are evaluated employing data from wake-vortex field measurement campaigns conducted in the United States and Germany.

High order methods for the integration of the Bateman equations and other problems of the form of y‧ = F(y,t)y

NASA Astrophysics Data System (ADS)

Josey, C.; Forget, B.; Smith, K.

2017-12-01

This paper introduces two families of A-stable algorithms for the integration of y‧ = F (y , t) y: the extended predictor-corrector (EPC) and the exponential-linear (EL) methods. The structure of the algorithm families are described, and the method of derivation of the coefficients presented. The new algorithms are then tested on a simple deterministic problem and a Monte Carlo isotopic evolution problem. The EPC family is shown to be only second order for systems of ODEs. However, the EPC-RK45 algorithm had the highest accuracy on the Monte Carlo test, requiring at least a factor of 2 fewer function evaluations to achieve a given accuracy than a second order predictor-corrector method (center extrapolation / center midpoint method) with regards to Gd-157 concentration. Members of the EL family can be derived to at least fourth order. The EL3 and the EL4 algorithms presented are shown to be third and fourth order respectively on the systems of ODE test. In the Monte Carlo test, these methods did not overtake the accuracy of EPC methods before statistical uncertainty dominated the error. The statistical properties of the algorithms were also analyzed during the Monte Carlo problem. The new methods are shown to yield smaller standard deviations on final quantities as compared to the reference predictor-corrector method, by up to a factor of 1.4.

Uncertainty Analysis Based on Sparse Grid Collocation and Quasi-Monte Carlo Sampling with Application in Groundwater Modeling

NASA Astrophysics Data System (ADS)

Zhang, G.; Lu, D.; Ye, M.; Gunzburger, M.

2011-12-01

Markov Chain Monte Carlo (MCMC) methods have been widely used in many fields of uncertainty analysis to estimate the posterior distributions of parameters and credible intervals of predictions in the Bayesian framework. However, in practice, MCMC may be computationally unaffordable due to slow convergence and the excessive number of forward model executions required, especially when the forward model is expensive to compute. Both disadvantages arise from the curse of dimensionality, i.e., the posterior distribution is usually a multivariate function of parameters. Recently, sparse grid method has been demonstrated to be an effective technique for coping with high-dimensional interpolation or integration problems. Thus, in order to accelerate the forward model and avoid the slow convergence of MCMC, we propose a new method for uncertainty analysis based on sparse grid interpolation and quasi-Monte Carlo sampling. First, we construct a polynomial approximation of the forward model in the parameter space by using the sparse grid interpolation. This approximation then defines an accurate surrogate posterior distribution that can be evaluated repeatedly at minimal computational cost. Second, instead of using MCMC, a quasi-Monte Carlo method is applied to draw samples in the parameter space. Then, the desired probability density function of each prediction is approximated by accumulating the posterior density values of all the samples according to the prediction values. Our method has the following advantages: (1) the polynomial approximation of the forward model on the sparse grid provides a very efficient evaluation of the surrogate posterior distribution; (2) the quasi-Monte Carlo method retains the same accuracy in approximating the PDF of predictions but avoids all disadvantages of MCMC. The proposed method is applied to a controlled numerical experiment of groundwater flow modeling. The results show that our method attains the same accuracy much more efficiently than traditional MCMC.

Solutions of the two-dimensional Hubbard model: Benchmarks and results from a wide range of numerical algorithms

DOE PAGES

LeBlanc, J. P. F.; Antipov, Andrey E.; Becca, Federico; ...

2015-12-14

Numerical results for ground-state and excited-state properties (energies, double occupancies, and Matsubara-axis self-energies) of the single-orbital Hubbard model on a two-dimensional square lattice are presented, in order to provide an assessment of our ability to compute accurate results in the thermodynamic limit. Many methods are employed, including auxiliary-field quantum Monte Carlo, bare and bold-line diagrammatic Monte Carlo, method of dual fermions, density matrix embedding theory, density matrix renormalization group, dynamical cluster approximation, diffusion Monte Carlo within a fixed-node approximation, unrestricted coupled cluster theory, and multireference projected Hartree-Fock methods. Comparison of results obtained by different methods allows for the identification ofmore » uncertainties and systematic errors. The importance of extrapolation to converged thermodynamic-limit values is emphasized. Furthermore, cases where agreement between different methods is obtained establish benchmark results that may be useful in the validation of new approaches and the improvement of existing methods.« less

Steady-State Electrodiffusion from the Nernst-Planck Equation Coupled to Local Equilibrium Monte Carlo Simulations.

PubMed

Boda, Dezső; Gillespie, Dirk

2012-03-13

We propose a procedure to compute the steady-state transport of charged particles based on the Nernst-Planck (NP) equation of electrodiffusion. To close the NP equation and to establish a relation between the concentration and electrochemical potential profiles, we introduce the Local Equilibrium Monte Carlo (LEMC) method. In this method, Grand Canonical Monte Carlo simulations are performed using the electrochemical potential specified for the distinct volume elements. An iteration procedure that self-consistently solves the NP and flux continuity equations with LEMC is shown to converge quickly. This NP+LEMC technique can be used in systems with diffusion of charged or uncharged particles in complex three-dimensional geometries, including systems with low concentrations and small applied voltages that are difficult for other particle simulation techniques.

A Christoffel function weighted least squares algorithm for collocation approximations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Narayan, Akil; Jakeman, John D.; Zhou, Tao

Here, we propose, theoretically investigate, and numerically validate an algorithm for the Monte Carlo solution of least-squares polynomial approximation problems in a collocation framework. Our investigation is motivated by applications in the collocation approximation of parametric functions, which frequently entails construction of surrogates via orthogonal polynomials. A standard Monte Carlo approach would draw samples according to the density defining the orthogonal polynomial family. Our proposed algorithm instead samples with respect to the (weighted) pluripotential equilibrium measure of the domain, and subsequently solves a weighted least-squares problem, with weights given by evaluations of the Christoffel function. We present theoretical analysis tomore » motivate the algorithm, and numerical results that show our method is superior to standard Monte Carlo methods in many situations of interest.« less

A Christoffel function weighted least squares algorithm for collocation approximations

DOE PAGES

Narayan, Akil; Jakeman, John D.; Zhou, Tao

2016-11-28

Here, we propose, theoretically investigate, and numerically validate an algorithm for the Monte Carlo solution of least-squares polynomial approximation problems in a collocation framework. Our investigation is motivated by applications in the collocation approximation of parametric functions, which frequently entails construction of surrogates via orthogonal polynomials. A standard Monte Carlo approach would draw samples according to the density defining the orthogonal polynomial family. Our proposed algorithm instead samples with respect to the (weighted) pluripotential equilibrium measure of the domain, and subsequently solves a weighted least-squares problem, with weights given by evaluations of the Christoffel function. We present theoretical analysis tomore » motivate the algorithm, and numerical results that show our method is superior to standard Monte Carlo methods in many situations of interest.« less

Correlated uncertainties in Monte Carlo reaction rate calculations

NASA Astrophysics Data System (ADS)

Longland, Richard

2017-07-01

Context. Monte Carlo methods have enabled nuclear reaction rates from uncertain inputs to be presented in a statistically meaningful manner. However, these uncertainties are currently computed assuming no correlations between the physical quantities that enter those calculations. This is not always an appropriate assumption. Astrophysically important reactions are often dominated by resonances, whose properties are normalized to a well-known reference resonance. This insight provides a basis from which to develop a flexible framework for including correlations in Monte Carlo reaction rate calculations. Aims: The aim of this work is to develop and test a method for including correlations in Monte Carlo reaction rate calculations when the input has been normalized to a common reference. Methods: A mathematical framework is developed for including correlations between input parameters in Monte Carlo reaction rate calculations. The magnitude of those correlations is calculated from the uncertainties typically reported in experimental papers, where full correlation information is not available. The method is applied to four illustrative examples: a fictional 3-resonance reaction, 27Al(p, γ)28Si, 23Na(p, α)20Ne, and 23Na(α, p)26Mg. Results: Reaction rates at low temperatures that are dominated by a few isolated resonances are found to minimally impacted by correlation effects. However, reaction rates determined from many overlapping resonances can be significantly affected. Uncertainties in the 23Na(α, p)26Mg reaction, for example, increase by up to a factor of 5. This highlights the need to take correlation effects into account in reaction rate calculations, and provides insight into which cases are expected to be most affected by them. The impact of correlation effects on nucleosynthesis is also investigated.

Path Toward a Unifid Geometry for Radiation Transport

NASA Technical Reports Server (NTRS)

Lee, Kerry; Barzilla, Janet; Davis, Andrew; Zachmann

2014-01-01

The Direct Accelerated Geometry for Radiation Analysis and Design (DAGRAD) element of the RadWorks Project under Advanced Exploration Systems (AES) within the Space Technology Mission Directorate (STMD) of NASA will enable new designs and concepts of operation for radiation risk assessment, mitigation and protection. This element is designed to produce a solution that will allow NASA to calculate the transport of space radiation through complex computer-aided design (CAD) models using the state-of-the-art analytic and Monte Carlo radiation transport codes. Due to the inherent hazard of astronaut and spacecraft exposure to ionizing radiation in low-Earth orbit (LEO) or in deep space, risk analyses must be performed for all crew vehicles and habitats. Incorporating these analyses into the design process can minimize the mass needed solely for radiation protection. Transport of the radiation fields as they pass through shielding and body materials can be simulated using Monte Carlo techniques or described by the Boltzmann equation, which is obtained by balancing changes in particle fluxes as they traverse a small volume of material with the gains and losses caused by atomic and nuclear collisions. Deterministic codes that solve the Boltzmann transport equation, such as HZETRN [high charge and energy transport code developed by NASA Langley Research Center (LaRC)], are generally computationally faster than Monte Carlo codes such as FLUKA, GEANT4, MCNP(X) or PHITS; however, they are currently limited to transport in one dimension, which poorly represents the secondary light ion and neutron radiation fields. NASA currently uses HZETRN space radiation transport software, both because it is computationally efficient and because proven methods have been developed for using this software to analyze complex geometries. Although Monte Carlo codes describe the relevant physics in a fully three-dimensional manner, their computational costs have thus far prevented their widespread use for analysis of complex CAD models, leading to the creation and maintenance of toolkit-specific simplistic geometry models. The work presented here builds on the Direct Accelerated Geometry Monte Carlo (DAGMC) toolkit developed for use with the Monte Carlo N-Particle (MCNP) transport code. The workflow for achieving radiation transport on CAD models using MCNP and FLUKA has been demonstrated and the results of analyses on realistic spacecraft/habitats will be presented. Future work is planned that will further automate this process and enable the use of multiple radiation transport codes on identical geometry models imported from CAD. This effort will enhance the modeling tools used by NASA to accurately evaluate the astronaut space radiation risk and accurately determine the protection provided by as-designed exploration mission vehicles and habitats

Efficient Monte Carlo sampling of inverse problems using a neural network-based forward—applied to GPR crosshole traveltime inversion

NASA Astrophysics Data System (ADS)

Hansen, T. M.; Cordua, K. S.

2017-12-01

Probabilistically formulated inverse problems can be solved using Monte Carlo-based sampling methods. In principle, both advanced prior information, based on for example, complex geostatistical models and non-linear forward models can be considered using such methods. However, Monte Carlo methods may be associated with huge computational costs that, in practice, limit their application. This is not least due to the computational requirements related to solving the forward problem, where the physical forward response of some earth model has to be evaluated. Here, it is suggested to replace a numerical complex evaluation of the forward problem, with a trained neural network that can be evaluated very fast. This will introduce a modeling error that is quantified probabilistically such that it can be accounted for during inversion. This allows a very fast and efficient Monte Carlo sampling of the solution to an inverse problem. We demonstrate the methodology for first arrival traveltime inversion of crosshole ground penetrating radar data. An accurate forward model, based on 2-D full-waveform modeling followed by automatic traveltime picking, is replaced by a fast neural network. This provides a sampling algorithm three orders of magnitude faster than using the accurate and computationally expensive forward model, and also considerably faster and more accurate (i.e. with better resolution), than commonly used approximate forward models. The methodology has the potential to dramatically change the complexity of non-linear and non-Gaussian inverse problems that have to be solved using Monte Carlo sampling techniques.

Lognormal Approximations of Fault Tree Uncertainty Distributions.

PubMed

El-Shanawany, Ashraf Ben; Ardron, Keith H; Walker, Simon P

2018-01-26

Fault trees are used in reliability modeling to create logical models of fault combinations that can lead to undesirable events. The output of a fault tree analysis (the top event probability) is expressed in terms of the failure probabilities of basic events that are input to the model. Typically, the basic event probabilities are not known exactly, but are modeled as probability distributions: therefore, the top event probability is also represented as an uncertainty distribution. Monte Carlo methods are generally used for evaluating the uncertainty distribution, but such calculations are computationally intensive and do not readily reveal the dominant contributors to the uncertainty. In this article, a closed-form approximation for the fault tree top event uncertainty distribution is developed, which is applicable when the uncertainties in the basic events of the model are lognormally distributed. The results of the approximate method are compared with results from two sampling-based methods: namely, the Monte Carlo method and the Wilks method based on order statistics. It is shown that the closed-form expression can provide a reasonable approximation to results obtained by Monte Carlo sampling, without incurring the computational expense. The Wilks method is found to be a useful means of providing an upper bound for the percentiles of the uncertainty distribution while being computationally inexpensive compared with full Monte Carlo sampling. The lognormal approximation method and Wilks's method appear attractive, practical alternatives for the evaluation of uncertainty in the output of fault trees and similar multilinear models. © 2018 Society for Risk Analysis.

Fast quantum Monte Carlo on a GPU

NASA Astrophysics Data System (ADS)

Lutsyshyn, Y.

2015-02-01

We present a scheme for the parallelization of quantum Monte Carlo method on graphical processing units, focusing on variational Monte Carlo simulation of bosonic systems. We use asynchronous execution schemes with shared memory persistence, and obtain an excellent utilization of the accelerator. The CUDA code is provided along with a package that simulates liquid helium-4. The program was benchmarked on several models of Nvidia GPU, including Fermi GTX560 and M2090, and the Kepler architecture K20 GPU. Special optimization was developed for the Kepler cards, including placement of data structures in the register space of the Kepler GPUs. Kepler-specific optimization is discussed.

Heterogeneous Hardware Parallelism Review of the IN2P3 2016 Computing School

NASA Astrophysics Data System (ADS)

Lafage, Vincent

2017-11-01

Parallel and hybrid Monte Carlo computation. The Monte Carlo method is the main workhorse for computation of particle physics observables. This paper provides an overview of various HPC technologies that can be used today: multicore (OpenMP, HPX), manycore (OpenCL). The rewrite of a twenty years old Fortran 77 Monte Carlo will illustrate the various programming paradigms in use beyond language implementation. The problem of parallel random number generator will be addressed. We will give a short report of the one week school dedicated to these recent approaches, that took place in École Polytechnique in May 2016.

Discrete ordinates-Monte Carlo coupling: A comparison of techniques in NERVA radiation analysis

NASA Technical Reports Server (NTRS)

Lindstrom, D. G.; Normand, E.; Wilcox, A. D.

1972-01-01

In the radiation analysis of the NERVA nuclear rocket system, two-dimensional discrete ordinates calculations are sufficient to provide detail in the pressure vessel and reactor assembly. Other parts of the system, however, require three-dimensional Monte Carlo analyses. To use these two methods in a single analysis, a means of coupling was developed whereby the results of a discrete ordinates calculation can be used to produce source data for a Monte Carlo calculation. Several techniques for producing source detail were investigated. Results of calculations on the NERVA system are compared and limitations and advantages of the coupling techniques discussed.

Neoclassical toroidal viscosity calculations in tokamaks using a δf Monte Carlo simulation and their verifications.

PubMed

Satake, S; Park, J-K; Sugama, H; Kanno, R

2011-07-29

Neoclassical toroidal viscosities (NTVs) in tokamaks are investigated using a δf Monte Carlo simulation, and are successfully verified with a combined analytic theory over a wide range of collisionality. A Monte Carlo simulation has been required in the study of NTV since the complexities in guiding-center orbits of particles and their collisions cannot be fully investigated by any means of analytic theories alone. Results yielded the details of the complex NTV dependency on particle precessions and collisions, which were predicted roughly in a combined analytic theory. Both numerical and analytic methods can be utilized and extended based on these successful verifications.

Monte Carlo simulation of cutaneous absorption and reflectance for clear, matt and dark biological tissue with varicosities: an investigation for dermatological laser

NASA Astrophysics Data System (ADS)

Klouch, Nawel; Riane, Houaria; Hamdache, Fatima; Addi, Djamel

2013-05-01

We are interested in modeling the interaction between light and biological tissue from the Monte Carlo method which is an approach used to solve modeling problems in different physical domains. Through the Monte Carlo approach we are going to try to interpret the spectral response absorption, reflectance, transmittance of normal human tissue under its three dominant tints in the visible range (350-700) nm. Then we will focus on the spectral response of the human tissue with varicosities in order to determinate the optimal conditions of operating the semiconductor laser for esthetic aim.

State-to-state models of vibrational relaxation in Direct Simulation Monte Carlo (DSMC)

NASA Astrophysics Data System (ADS)

Oblapenko, G. P.; Kashkovsky, A. V.; Bondar, Ye A.

2017-02-01

In the present work, the application of state-to-state models of vibrational energy exchanges to the Direct Simulation Monte Carlo (DSMC) is considered. A state-to-state model for VT transitions of vibrational energy in nitrogen and oxygen, based on the application of the inverse Laplace transform to results of quasiclassical trajectory calculations (QCT) of vibrational energy transitions, along with the Forced Harmonic Oscillator (FHO) state-to-state model is implemented in DSMC code and applied to flows around blunt bodies. Comparisons are made with the widely used Larsen-Borgnakke model and the in uence of multi-quantum VT transitions is assessed.

Mosaicing of airborne LiDAR bathymetry strips based on Monte Carlo matching

NASA Astrophysics Data System (ADS)

Yang, Fanlin; Su, Dianpeng; Zhang, Kai; Ma, Yue; Wang, Mingwei; Yang, Anxiu

2017-09-01

This study proposes a new methodology for mosaicing airborne light detection and ranging (LiDAR) bathymetry (ALB) data based on Monte Carlo matching. Various errors occur in ALB data due to imperfect system integration and other interference factors. To account for these errors, a Monte Carlo matching algorithm based on a nonlinear least-squares adjustment model is proposed. First, the raw data of strip overlap areas were filtered according to their relative drift of depths. Second, a Monte Carlo model and nonlinear least-squares adjustment model were combined to obtain seven transformation parameters. Then, the multibeam bathymetric data were used to correct the initial strip during strip mosaicing. Finally, to evaluate the proposed method, the experimental results were compared with the results of the Iterative Closest Points (ICP) and three-dimensional Normal Distributions Transform (3D-NDT) algorithms. The results demonstrate that the algorithm proposed in this study is more robust and effective. When the quality of the raw data is poor, the Monte Carlo matching algorithm can still achieve centimeter-level accuracy for overlapping areas, which meets the accuracy of bathymetry required by IHO Standards for Hydrographic Surveys Special Publication No.44.

Coupling of kinetic Monte Carlo simulations of surface reactions to transport in a fluid for heterogeneous catalytic reactor modeling.

PubMed

Schaefer, C; Jansen, A P J

2013-02-07

We have developed a method to couple kinetic Monte Carlo simulations of surface reactions at a molecular scale to transport equations at a macroscopic scale. This method is applicable to steady state reactors. We use a finite difference upwinding scheme and a gap-tooth scheme to efficiently use a limited amount of kinetic Monte Carlo simulations. In general the stochastic kinetic Monte Carlo results do not obey mass conservation so that unphysical accumulation of mass could occur in the reactor. We have developed a method to perform mass balance corrections that is based on a stoichiometry matrix and a least-squares problem that is reduced to a non-singular set of linear equations that is applicable to any surface catalyzed reaction. The implementation of these methods is validated by comparing numerical results of a reactor simulation with a unimolecular reaction to an analytical solution. Furthermore, the method is applied to two reaction mechanisms. The first is the ZGB model for CO oxidation in which inevitable poisoning of the catalyst limits the performance of the reactor. The second is a model for the oxidation of NO on a Pt(111) surface, which becomes active due to lateral interaction at high coverages of oxygen. This reaction model is based on ab initio density functional theory calculations from literature.

Monte Carlo and Molecular Dynamics in the Multicanonical Ensemble: Connections between Wang-Landau Sampling and Metadynamics

NASA Astrophysics Data System (ADS)

Vogel, Thomas; Perez, Danny; Junghans, Christoph

2014-03-01

We show direct formal relationships between the Wang-Landau iteration [PRL 86, 2050 (2001)], metadynamics [PNAS 99, 12562 (2002)] and statistical temperature molecular dynamics [PRL 97, 050601 (2006)], the major Monte Carlo and molecular dynamics work horses for sampling from a generalized, multicanonical ensemble. We aim at helping to consolidate the developments in the different areas by indicating how methodological advancements can be transferred in a straightforward way, avoiding the parallel, largely independent, developments tracks observed in the past.

Monte Carlo Evaluation of Tritium Beta Spectrum Energy Deposition in Gallium Nitride (GaN) Direct Energy Conversion Devices

DTIC Science & Technology

2014-09-01

information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. 1. REPORT DATE (DD...MM-YYYY) September 2014 2. REPORT TYPE Final 3. DATES COVERED (From - To) January–July 2014 4. TITLE AND SUBTITLE Monte Carlo Evaluation of...generated is typical of energy harvesting levels of power.11 Radioisotope power sources differ from typical renewable energy/power levels in that they

Remarks on a financial inverse problem by means of Monte Carlo Methods

NASA Astrophysics Data System (ADS)

Cuomo, Salvatore; Di Somma, Vittorio; Sica, Federica

2017-10-01

Estimating the price of a barrier option is a typical inverse problem. In this paper we present a numerical and statistical framework for a market with risk-free interest rate and a risk asset, described by a Geometric Brownian Motion (GBM). After approximating the risk asset with a numerical method, we find the final option price by following an approach based on sequential Monte Carlo methods. All theoretical results are applied to the case of an option whose underlying is a real stock.

Hierarchical multistage MCMC follow-up of continuous gravitational wave candidates

NASA Astrophysics Data System (ADS)

Ashton, G.; Prix, R.

2018-05-01

Leveraging Markov chain Monte Carlo optimization of the F statistic, we introduce a method for the hierarchical follow-up of continuous gravitational wave candidates identified by wide-parameter space semicoherent searches. We demonstrate parameter estimation for continuous wave sources and develop a framework and tools to understand and control the effective size of the parameter space, critical to the success of the method. Monte Carlo tests of simulated signals in noise demonstrate that this method is close to the theoretical optimal performance.

Improving the Ar I and II branching ratio calibration method: Monte Carlo simulations of effects from photon scattering/reflecting in hollow cathodes

NASA Astrophysics Data System (ADS)

Lawler, J. E.; Den Hartog, E. A.

2018-03-01

The Ar I and II branching ratio calibration method is discussed with the goal of improving the technique. This method of establishing a relative radiometric calibration is important in ongoing research to improve atomic transition probabilities for quantitative spectroscopy in astrophysics and other fields. Specific suggestions are presented along with Monte Carlo simulations of wavelength dependent effects from scattering/reflecting of photons in a hollow cathode.

Propagating probability distributions of stand variables using sequential Monte Carlo methods

Treesearch

Jeffrey H. Gove

2009-01-01

A general probabilistic approach to stand yield estimation is developed based on sequential Monte Carlo filters, also known as particle filters. The essential steps in the development of the sampling importance resampling (SIR) particle filter are presented. The SIR filter is then applied to simulated and observed data showing how the 'predictor - corrector'...

Recovery of Graded Response Model Parameters: A Comparison of Marginal Maximum Likelihood and Markov Chain Monte Carlo Estimation

ERIC Educational Resources Information Center

Kieftenbeld, Vincent; Natesan, Prathiba

2012-01-01

Markov chain Monte Carlo (MCMC) methods enable a fully Bayesian approach to parameter estimation of item response models. In this simulation study, the authors compared the recovery of graded response model parameters using marginal maximum likelihood (MML) and Gibbs sampling (MCMC) under various latent trait distributions, test lengths, and…

A systematic framework for Monte Carlo simulation of remote sensing errors map in carbon assessments

Treesearch

S. Healey; P. Patterson; S. Urbanski

2014-01-01

Remotely sensed observations can provide unique perspective on how management and natural disturbance affect carbon stocks in forests. However, integration of these observations into formal decision support will rely upon improved uncertainty accounting. Monte Carlo (MC) simulations offer a practical, empirical method of accounting for potential remote sensing errors...

OBJECT KINETIC MONTE CARLO SIMULATIONS OF RADIATION DAMAGE IN TUNGSTEN SUBJECTED TO NEUTRON FLUX WITH PKA SPECTRUM CORRESPONDING TO THE HFIR

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nandipati, Giridhar; Setyawan, Wahyu; Heinisch, Howard L.

2015-12-31

The objective of this work is to study the damage accumulation in pure tungsten (W) subjected to neutron bombardment with a primary knock-on atom (PKA) spectrum corresponding to the High Flux Isotope Reactor (HFIR), using the object kinetic Monte Carlo (OKMC) method.

An Analysis of Polynomial Chaos Approximations for Modeling Single-Fluid-Phase Flow in Porous Medium Systems

PubMed Central

Rupert, C.P.; Miller, C.T.

2008-01-01

We examine a variety of polynomial-chaos-motivated approximations to a stochastic form of a steady state groundwater flow model. We consider approaches for truncating the infinite dimensional problem and producing decoupled systems. We discuss conditions under which such decoupling is possible and show that to generalize the known decoupling by numerical cubature, it would be necessary to find new multivariate cubature rules. Finally, we use the acceleration of Monte Carlo to compare the quality of polynomial models obtained for all approaches and find that in general the methods considered are more efficient than Monte Carlo for the relatively small domains considered in this work. A curse of dimensionality in the series expansion of the log-normal stochastic random field used to represent hydraulic conductivity provides a significant impediment to efficient approximations for large domains for all methods considered in this work, other than the Monte Carlo method. PMID:18836519

CO oxidation reaction on Pt(111) studied by the dynamic Monte Carlo method including lateral interactions of adsorbates.

PubMed

Nagasaka, Masanari; Kondoh, Hiroshi; Nakai, Ikuyo; Ohta, Toshiaki

2007-01-28

The dynamics of adsorbate structures during CO oxidation on Pt(111) surfaces and its effects on the reaction were studied by the dynamic Monte Carlo method including lateral interactions of adsorbates. The lateral interaction energies between adsorbed species were calculated by the density functional theory method. Dynamic Monte Carlo simulations were performed for the oxidation reaction over a mesoscopic scale, where the experimentally determined activation energies of elementary paths were altered by the calculated lateral interaction energies. The simulated results reproduced the characteristics of the microscopic and mesoscopic scale adsorbate structures formed during the reaction, and revealed that the complicated reaction kinetics is comprehensively explained by a single reaction path affected by the surrounding adsorbates. We also propose from the simulations that weakly adsorbed CO molecules at domain boundaries promote the island-periphery specific reaction.

Monte Carlo studies of ocean wind vector measurements by SCATT: Objective criteria and maximum likelihood estimates for removal of aliases, and effects of cell size on accuracy of vector winds

NASA Technical Reports Server (NTRS)

Pierson, W. J.

1982-01-01

The scatterometer on the National Oceanic Satellite System (NOSS) is studied by means of Monte Carlo techniques so as to determine the effect of two additional antennas for alias (or ambiguity) removal by means of an objective criteria technique and a normalized maximum likelihood estimator. Cells nominally 10 km by 10 km, 10 km by 50 km, and 50 km by 50 km are simulated for winds of 4, 8, 12 and 24 m/s and incidence angles of 29, 39, 47, and 53.5 deg for 15 deg changes in direction. The normalized maximum likelihood estimate (MLE) is correct a large part of the time, but the objective criterion technique is recommended as a reserve, and more quickly computed, procedure. Both methods for alias removal depend on the differences in the present model function at upwind and downwind. For 10 km by 10 km cells, it is found that the MLE method introduces a correlation between wind speed errors and aspect angle (wind direction) errors that can be as high as 0.8 or 0.9 and that the wind direction errors are unacceptably large, compared to those obtained for the SASS for similar assumptions.

Analysis and modeling of localized heat generation by tumor-targeted nanoparticles (Monte Carlo methods)

NASA Astrophysics Data System (ADS)

Sanattalab, Ehsan; SalmanOgli, Ahmad; Piskin, Erhan

2016-04-01

We investigated the tumor-targeted nanoparticles that influence heat generation. We suppose that all nanoparticles are fully functionalized and can find the target using active targeting methods. Unlike the commonly used methods, such as chemotherapy and radiotherapy, the treatment procedure proposed in this study is purely noninvasive, which is considered to be a significant merit. It is found that the localized heat generation due to targeted nanoparticles is significantly higher than other areas. By engineering the optical properties of nanoparticles, including scattering, absorption coefficients, and asymmetry factor (cosine scattering angle), the heat generated in the tumor's area reaches to such critical state that can burn the targeted tumor. The amount of heat generated by inserting smart agents, due to the surface Plasmon resonance, will be remarkably high. The light-matter interactions and trajectory of incident photon upon targeted tissues are simulated by MIE theory and Monte Carlo method, respectively. Monte Carlo method is a statistical one by which we can accurately probe the photon trajectories into a simulation area.

Excitation variance matching with limited configuration interaction expansions in variational Monte Carlo

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robinson, Paul J.; Pineda Flores, Sergio D.; Neuscamman, Eric

In the regime where traditional approaches to electronic structure cannot afford to achieve accurate energy differences via exhaustive wave function flexibility, rigorous approaches to balancing different states’ accuracies become desirable. As a direct measure of a wave function’s accuracy, the energy variance offers one route to achieving such a balance. Here, we develop and test a variance matching approach for predicting excitation energies within the context of variational Monte Carlo and selective configuration interaction. In a series of tests on small but difficult molecules, we demonstrate that the approach it is effective at delivering accurate excitation energies when the wavemore » function is far from the exhaustive flexibility limit. Results in C3, where we combine this approach with variational Monte Carlo orbital optimization, are especially encouraging.« less

Excitation variance matching with limited configuration interaction expansions in variational Monte Carlo

DOE PAGES

Robinson, Paul J.; Pineda Flores, Sergio D.; Neuscamman, Eric

2017-10-28

In the regime where traditional approaches to electronic structure cannot afford to achieve accurate energy differences via exhaustive wave function flexibility, rigorous approaches to balancing different states’ accuracies become desirable. As a direct measure of a wave function’s accuracy, the energy variance offers one route to achieving such a balance. Here, we develop and test a variance matching approach for predicting excitation energies within the context of variational Monte Carlo and selective configuration interaction. In a series of tests on small but difficult molecules, we demonstrate that the approach it is effective at delivering accurate excitation energies when the wavemore » function is far from the exhaustive flexibility limit. Results in C3, where we combine this approach with variational Monte Carlo orbital optimization, are especially encouraging.« less

Hypersonic shock structure with Burnett terms in the viscous stress and heat flux

NASA Technical Reports Server (NTRS)

Chapman, Dean R.; Fiscko, Kurt A.

1988-01-01

The continuum Navier-Stokes and Burnett equations are solved for one-dimensional shock structure in various monatomic gases. A new numerical method is employed which utilizes the complete time-dependent continuum equations and obtains the steady-state shock structure by allowing the system to relax from arbitrary initial conditions. Included is discussion of numerical difficulties encountered when solving the Burnett equations. Continuum solutions are compared to those obtained utilizing the Direct Simulation Monte Carlo method. Shock solutions are obtained for a hard sphere gas and for argon from Mach 1.3 to Mach 50. Solutions for a Maxwellian gas are obtained from Mach 1.3 to Mach 3.8. It is shown that the Burnett equations yield shock structure solutions in much closer agreement to both Monte Carlo and experimental results than do the Navier-Stokes equations. Shock density thickness, density asymmetry, and density-temperature separation are all more accurately predicted by the Burnett equations than by the Navier-Stokes equations.

Application of Monte Carlo techniques to transient thermal modeling of cavity radiometers having diffuse-specular surfaces

NASA Technical Reports Server (NTRS)

Mahan, J. R.; Eskin, L. D.

1981-01-01

A viable alternative to the net exchange method of radiative analysis which is equally applicable to diffuse and diffuse-specular enclosures is presented. It is particularly more advantageous to use than the net exchange method in the case of a transient thermal analysis involving conduction and storage of energy as well as radiative exchange. A new quantity, called the distribution factor is defined which replaces the angle factor and the configuration factor. Once obtained, the array of distribution factors for an ensemble of surface elements which define an enclosure permits the instantaneous net radiative heat fluxes to all of the surfaces to be computed directly in terms of the known surface temperatures at that instant. The formulation of the thermal model is described, as is the determination of distribution factors by application of a Monte Carlo analysis. The results show that when fewer than 10,000 packets are emitted, an unsatisfactory approximation for the distribution factors is obtained, but that 10,000 packets is sufficient.

Quantum Monte Carlo studies of solvated systems

NASA Astrophysics Data System (ADS)

Schwarz, Kathleen; Letchworth Weaver, Kendra; Arias, T. A.; Hennig, Richard G.

2011-03-01

Solvation qualitatively alters the energetics of diverse processes from protein folding to reactions on catalytic surfaces. An explicit description of the solvent in quantum-mechanical calculations requires both a large number of electrons and exploration of a large number of configurations in the phase space of the solvent. These problems can be circumvented by including the effects of solvent through a rigorous classical density-functional description of the liquid environment, thereby yielding free energies and thermodynamic averages directly, while eliminating the need for explicit consideration of the solvent electrons. We have implemented and tested this approach within the CASINO Quantum Monte Carlo code. Our method is suitable for calculations in any basis within CASINO, including b-spline and plane wave trial wavefunctions, and is equally applicable to molecules, surfaces, and crystals. For our preliminary test calculations, we use a simplified description of the solvent in terms of an isodensity continuum dielectric solvation approach, though the method is fully compatible with more reliable descriptions of the solvent we shall employ in the future.

Accurate Exchange-Correlation Energies for the Warm Dense Electron Gas.

PubMed

Malone, Fionn D; Blunt, N S; Brown, Ethan W; Lee, D K K; Spencer, J S; Foulkes, W M C; Shepherd, James J

2016-09-09

The density matrix quantum Monte Carlo (DMQMC) method is used to sample exact-on-average N-body density matrices for uniform electron gas systems of up to 10^{124} matrix elements via a stochastic solution of the Bloch equation. The results of these calculations resolve a current debate over the accuracy of the data used to parametrize finite-temperature density functionals. Exchange-correlation energies calculated using the real-space restricted path-integral formalism and the k-space configuration path-integral formalism disagree by up to ∼10% at certain reduced temperatures T/T_{F}≤0.5 and densities r_{s}≤1. Our calculations confirm the accuracy of the configuration path-integral Monte Carlo results available at high density and bridge the gap to lower densities, providing trustworthy data in the regime typical of planetary interiors and solids subject to laser irradiation. We demonstrate that the DMQMC method can calculate free energies directly and present exact free energies for T/T_{F}≥1 and r_{s}≤2.

Coupled Neutron Transport for HZETRN

NASA Technical Reports Server (NTRS)

Slaba, Tony C.; Blattnig, Steve R.

2009-01-01

Exposure estimates inside space vehicles, surface habitats, and high altitude aircrafts exposed to space radiation are highly influenced by secondary neutron production. The deterministic transport code HZETRN has been identified as a reliable and efficient tool for such studies, but improvements to the underlying transport models and numerical methods are still necessary. In this paper, the forward-backward (FB) and directionally coupled forward-backward (DC) neutron transport models are derived, numerical methods for the FB model are reviewed, and a computationally efficient numerical solution is presented for the DC model. Both models are compared to the Monte Carlo codes HETC-HEDS, FLUKA, and MCNPX, and the DC model is shown to agree closely with the Monte Carlo results. Finally, it is found in the development of either model that the decoupling of low energy neutrons from the light particle transport procedure adversely affects low energy light ion fluence spectra and exposure quantities. A first order correction is presented to resolve the problem, and it is shown to be both accurate and efficient.

Noninvasive spectral imaging of skin chromophores based on multiple regression analysis aided by Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Nishidate, Izumi; Wiswadarma, Aditya; Hase, Yota; Tanaka, Noriyuki; Maeda, Takaaki; Niizeki, Kyuichi; Aizu, Yoshihisa

2011-08-01

In order to visualize melanin and blood concentrations and oxygen saturation in human skin tissue, a simple imaging technique based on multispectral diffuse reflectance images acquired at six wavelengths (500, 520, 540, 560, 580 and 600nm) was developed. The technique utilizes multiple regression analysis aided by Monte Carlo simulation for diffuse reflectance spectra. Using the absorbance spectrum as a response variable and the extinction coefficients of melanin, oxygenated hemoglobin, and deoxygenated hemoglobin as predictor variables, multiple regression analysis provides regression coefficients. Concentrations of melanin and total blood are then determined from the regression coefficients using conversion vectors that are deduced numerically in advance, while oxygen saturation is obtained directly from the regression coefficients. Experiments with a tissue-like agar gel phantom validated the method. In vivo experiments with human skin of the human hand during upper limb occlusion and of the inner forearm exposed to UV irradiation demonstrated the ability of the method to evaluate physiological reactions of human skin tissue.

Development of the MCNPX depletion capability: A Monte Carlo linked depletion method that automates the coupling between MCNPX and CINDER90 for high fidelity burnup calculations

NASA Astrophysics Data System (ADS)

Fensin, Michael Lorne

Monte Carlo-linked depletion methods have gained recent interest due to the ability to more accurately model complex 3-dimesional geometries and better track the evolution of temporal nuclide inventory by simulating the actual physical process utilizing continuous energy coefficients. The integration of CINDER90 into the MCNPX Monte Carlo radiation transport code provides a high-fidelity completely self-contained Monte-Carlo-linked depletion capability in a well established, widely accepted Monte Carlo radiation transport code that is compatible with most nuclear criticality (KCODE) particle tracking features in MCNPX. MCNPX depletion tracks all necessary reaction rates and follows as many isotopes as cross section data permits in order to achieve a highly accurate temporal nuclide inventory solution. This work chronicles relevant nuclear history, surveys current methodologies of depletion theory, details the methodology in applied MCNPX and provides benchmark results for three independent OECD/NEA benchmarks. Relevant nuclear history, from the Oklo reactor two billion years ago to the current major United States nuclear fuel cycle development programs, is addressed in order to supply the motivation for the development of this technology. A survey of current reaction rate and temporal nuclide inventory techniques is then provided to offer justification for the depletion strategy applied within MCNPX. The MCNPX depletion strategy is then dissected and each code feature is detailed chronicling the methodology development from the original linking of MONTEBURNS and MCNP to the most recent public release of the integrated capability (MCNPX 2.6.F). Calculation results of the OECD/NEA Phase IB benchmark, H. B. Robinson benchmark and OECD/NEA Phase IVB are then provided. The acceptable results of these calculations offer sufficient confidence in the predictive capability of the MCNPX depletion method. This capability sets up a significant foundation, in a well established and supported radiation transport code, for further development of a Monte Carlo-linked depletion methodology which is essential to the future development of advanced reactor technologies that exceed the limitations of current deterministic based methods.

Radial secondary electron dose profiles and biological effects in light-ion beams based on analytical and Monte Carlo calculations using distorted wave cross sections.

PubMed

Wiklund, Kristin; Olivera, Gustavo H; Brahme, Anders; Lind, Bengt K

2008-07-01

To speed up dose calculation, an analytical pencil-beam method has been developed to calculate the mean radial dose distributions due to secondary electrons that are set in motion by light ions in water. For comparison, radial dose profiles calculated using a Monte Carlo technique have also been determined. An accurate comparison of the resulting radial dose profiles of the Bragg peak for (1)H(+), (4)He(2+) and (6)Li(3+) ions has been performed. The double differential cross sections for secondary electron production were calculated using the continuous distorted wave-eikonal initial state method (CDW-EIS). For the secondary electrons that are generated, the radial dose distribution for the analytical case is based on the generalized Gaussian pencil-beam method and the central axis depth-dose distributions are calculated using the Monte Carlo code PENELOPE. In the Monte Carlo case, the PENELOPE code was used to calculate the whole radial dose profile based on CDW data. The present pencil-beam and Monte Carlo calculations agree well at all radii. A radial dose profile that is shallower at small radii and steeper at large radii than the conventional 1/r(2) is clearly seen with both the Monte Carlo and pencil-beam methods. As expected, since the projectile velocities are the same, the dose profiles of Bragg-peak ions of 0.5 MeV (1)H(+), 2 MeV (4)He(2+) and 3 MeV (6)Li(3+) are almost the same, with about 30% more delta electrons in the sub keV range from (4)He(2+)and (6)Li(3+) compared to (1)H(+). A similar behavior is also seen for 1 MeV (1)H(+), 4 MeV (4)He(2+) and 6 MeV (6)Li(3+), all classically expected to have the same secondary electron cross sections. The results are promising and indicate a fast and accurate way of calculating the mean radial dose profile.

Monte Carlo simulation of expert judgments on human errors in chemical analysis--a case study of ICP-MS.

PubMed

Kuselman, Ilya; Pennecchi, Francesca; Epstein, Malka; Fajgelj, Ales; Ellison, Stephen L R

2014-12-01

Monte Carlo simulation of expert judgments on human errors in a chemical analysis was used for determination of distributions of the error quantification scores (scores of likelihood and severity, and scores of effectiveness of a laboratory quality system in prevention of the errors). The simulation was based on modeling of an expert behavior: confident, reasonably doubting and irresolute expert judgments were taken into account by means of different probability mass functions (pmfs). As a case study, 36 scenarios of human errors which may occur in elemental analysis of geological samples by ICP-MS were examined. Characteristics of the score distributions for three pmfs of an expert behavior were compared. Variability of the scores, as standard deviation of the simulated score values from the distribution mean, was used for assessment of the score robustness. A range of the score values, calculated directly from elicited data and simulated by a Monte Carlo method for different pmfs, was also discussed from the robustness point of view. It was shown that robustness of the scores, obtained in the case study, can be assessed as satisfactory for the quality risk management and improvement of a laboratory quality system against human errors. Copyright © 2014 Elsevier B.V. All rights reserved.

Computational Fluid Dynamics for Atmospheric Entry

DTIC Science & Technology

2009-09-01

equations. This method is a parallelizable variant of the Gauss - Seidel line-relaxation method of MacCormack (Ref. 33, 35), and is at the core of the...G.V. Candler, “The Solution of the Navier-Stokes Equations Gauss - Seidel Line Relaxation,” Computers and Fluids, Vol. 17, No. 1, 1989, pp. 135-150. 35... solution differs by 5% from the results obtained using the direct simulation Monte Carlo method . 3 Some authors advocate the use of higher-order continuum

Impulsive solar X-ray bursts. 4: Polarization, directivity and spectrum of the reflected and total bremsstrahlung radiation from a beam of electrons directed toward the photosphere

NASA Technical Reports Server (NTRS)

Langer, S. H.; Petrosian, V.

1976-01-01

A Monte Carlo method is described for evaluation of the spectrum, directivity and polarization of X-rays diffusely reflected from stellar photospheres. the accuracy of the technique is evaluated through comparison with analytic results. Using the characteristics of the incident X-rays of the model for solar X-ray flares, the spectrum, directivity and polarization of the reflected and the total X-ray fluxes are evaluated. The results are compared with observations.

Monte Carlo Modeling of Non-Local Electron Conduction in High Energy Density Plasmas

NASA Astrophysics Data System (ADS)

Chenhall, Jeffrey John

The implicit SNB (iSNB) non-local multigroup thermal electron conduction method of Schurtz et. al. [Phys. Plasmas 7, 4238 (2000)] and Cao et. al. [Phys. Plasmas 22, 082308 (2015)] is adapted into an electron thermal transport Monte Carlo (ETTMC) transport method to better model higher order angular and long mean free path non-local effects. The ETTMC model is used to simulate the electron thermal transport within inertial confinement fusion (ICF) type problems. The new model aims to improve upon the currently used iSNB, in particular by using finite particle ranges in comparison to the exponential solution of a diffusion method and by improved higher order angular modeling. The new method has been implemented in the 1D LILAC and 2D DRACO multiphysics production codes developed by the University of Rochester Laboratory for Laser Energetics. The ETTMC model is compared to iSNB for several direct drive ICF type simulations: Omega shot 60303 a shock timing experiment, Omega shot 59529 a shock timing experiment, Omega shot 68951 a cryogenic target implosion and a NIF polar direct drive phase plate design. Overall, the ETTMC method performs at least as well as the iSNB method and predicts lower preheating ahead of the shock fronts. This research was supported by University of Rochester Laboratory for Laser Energetics, Sandia National Laboratories and the University of Wisconsin-Madison Foundation.

Lattice Boltzmann accelerated direct simulation Monte Carlo for dilute gas flow simulations.

PubMed

Di Staso, G; Clercx, H J H; Succi, S; Toschi, F

2016-11-13

Hybrid particle-continuum computational frameworks permit the simulation of gas flows by locally adjusting the resolution to the degree of non-equilibrium displayed by the flow in different regions of space and time. In this work, we present a new scheme that couples the direct simulation Monte Carlo (DSMC) with the lattice Boltzmann (LB) method in the limit of isothermal flows. The former handles strong non-equilibrium effects, as they typically occur in the vicinity of solid boundaries, whereas the latter is in charge of the bulk flow, where non-equilibrium can be dealt with perturbatively, i.e. according to Navier-Stokes hydrodynamics. The proposed concurrent multiscale method is applied to the dilute gas Couette flow, showing major computational gains when compared with the full DSMC scenarios. In addition, it is shown that the coupling with LB in the bulk flow can speed up the DSMC treatment of the Knudsen layer with respect to the full DSMC case. In other words, LB acts as a DSMC accelerator.This article is part of the themed issue 'Multiscale modelling at the physics-chemistry-biology interface'. © 2016 The Author(s).

Simulations of hypersonic, high-enthalpy separated flow over a 'tick' configuration

NASA Astrophysics Data System (ADS)

Moss, J. N.; O'Byrne, S.; Deepak, N. R.; Gai, S. L.

2012-11-01

The effect of slip is investigated in direct simulation Monte Carlo and Navier-Stokes-based computations of the separated flow between an expansion and a following compression surface, a geometry we call the 'tick' configuration. This configuration has been chosen as a test of separated flow with zero initial boundary layer thickness, a flowfield well suited to Chapman's analytical separated flow theories. The predicted size of the separated region is different for the two codes, although both codes meet their respective particle or grid resolution requirements. Unlike previous comparisons involving cylinder flares or double cones, the separation does not occur in a region of elevated density, and is therefore well suited to the direct simulation Monte Carlo method because the effect of slip at the surface is significant. The reasons for the difference between the two calculations are hypothesized to be a combination of significant rarefaction effects near the expansion surface and the non-zero radius of the leading edge. When the leading edge radius is accounted for, the rarefaction effect at the leading edge is less significant and the behavior of the flowfields predicted by the two methods becomes more similar.

Investigation of the Klinkenberg effect in a micro/nanoporous medium by direct simulation Monte Carlo method

NASA Astrophysics Data System (ADS)

Yang, Guang; Weigand, Bernhard

2018-04-01

The pressure-driven gas transport characteristics through a porous medium consisting of arrays of discrete elements is investigated by using the direct simulation Monte Carlo (DSMC) method. Different porous structures are considered, accounting for both two- and three-dimensional arrangements of basic microscale and nanoscale elements. The pore scale flow patterns in the porous medium are obtained, and the Knudsen diffusion in the pores is studied in detail for slip and transition flow regimes. A new effective pore size of the porous medium is defined, which is a function of the porosity, the tortuosity, the contraction factor, and the intrinsic permeability of the porous medium. It is found that the Klinkenberg effect in different porous structures can be fully described by the Knudsen number characterized by the effective pore size. The accuracies of some widely used Klinkenberg correlations are evaluated by the present DSMC results. It is also found that the available correlations for apparent permeability, most of which are derived from simple pipe or channel flows, can still be applicative for more complex porous media flows, by using the effective pore size defined in this study.

Tolerance allocation for an electronic system using neural network/Monte Carlo approach

NASA Astrophysics Data System (ADS)

Al-Mohammed, Mohammed; Esteve, Daniel; Boucher, Jaque

2001-12-01

The intense global competition to produce quality products at a low cost has led many industrial nations to consider tolerances as a key factor to bring about cost as well as to remain competitive. In actually, Tolerance allocation stays widely applied on the Mechanic System. It is known that to study the tolerances in an electronic domain, Monte-Carlo method well be used. But the later method spends a long time. This paper reviews several methods (Worst-case, Statistical Method, Least Cost Allocation by Optimization methods) that can be used for treating the tolerancing problem for an Electronic System and explains their advantages and their limitations. Then, it proposes an efficient method based on the Neural Networks associated with Monte-Carlo method as basis data. The network is trained using the Error Back Propagation Algorithm to predict the individual part tolerances, minimizing the total cost of the system by a method of optimization. This proposed approach has been applied on Small-Signal Amplifier Circuit as an example. This method can be easily extended to a complex system of n-components.

Optimization of the Monte Carlo code for modeling of photon migration in tissue.

PubMed

Zołek, Norbert S; Liebert, Adam; Maniewski, Roman

2006-10-01

The Monte Carlo method is frequently used to simulate light transport in turbid media because of its simplicity and flexibility, allowing to analyze complicated geometrical structures. Monte Carlo simulations are, however, time consuming because of the necessity to track the paths of individual photons. The time consuming computation is mainly associated with the calculation of the logarithmic and trigonometric functions as well as the generation of pseudo-random numbers. In this paper, the Monte Carlo algorithm was developed and optimized, by approximation of the logarithmic and trigonometric functions. The approximations were based on polynomial and rational functions, and the errors of these approximations are less than 1% of the values of the original functions. The proposed algorithm was verified by simulations of the time-resolved reflectance at several source-detector separations. The results of the calculation using the approximated algorithm were compared with those of the Monte Carlo simulations obtained with an exact computation of the logarithm and trigonometric functions as well as with the solution of the diffusion equation. The errors of the moments of the simulated distributions of times of flight of photons (total number of photons, mean time of flight and variance) are less than 2% for a range of optical properties, typical of living tissues. The proposed approximated algorithm allows to speed up the Monte Carlo simulations by a factor of 4. The developed code can be used on parallel machines, allowing for further acceleration.

Integer lattice gas with Monte Carlo collision operator recovers the lattice Boltzmann method with Poisson-distributed fluctuations

NASA Astrophysics Data System (ADS)

Blommel, Thomas; Wagner, Alexander J.

2018-02-01

We examine a new kind of lattice gas that closely resembles modern lattice Boltzmann methods. This new kind of lattice gas, which we call a Monte Carlo lattice gas, has interesting properties that shed light on the origin of the multirelaxation time collision operator, and it derives the equilibrium distribution for an entropic lattice Boltzmann. Furthermore these lattice gas methods have Galilean invariant fluctuations given by a Poisson statistics, giving further insight into the properties that we should expect for fluctuating lattice Boltzmann methods.

Validation of a personalized dosimetric evaluation tool (Oedipe) for targeted radiotherapy based on the Monte Carlo MCNPX code

NASA Astrophysics Data System (ADS)

Chiavassa, S.; Aubineau-Lanièce, I.; Bitar, A.; Lisbona, A.; Barbet, J.; Franck, D.; Jourdain, J. R.; Bardiès, M.

2006-02-01

Dosimetric studies are necessary for all patients treated with targeted radiotherapy. In order to attain the precision required, we have developed Oedipe, a dosimetric tool based on the MCNPX Monte Carlo code. The anatomy of each patient is considered in the form of a voxel-based geometry created using computed tomography (CT) images or magnetic resonance imaging (MRI). Oedipe enables dosimetry studies to be carried out at the voxel scale. Validation of the results obtained by comparison with existing methods is complex because there are multiple sources of variation: calculation methods (different Monte Carlo codes, point kernel), patient representations (model or specific) and geometry definitions (mathematical or voxel-based). In this paper, we validate Oedipe by taking each of these parameters into account independently. Monte Carlo methodology requires long calculation times, particularly in the case of voxel-based geometries, and this is one of the limits of personalized dosimetric methods. However, our results show that the use of voxel-based geometry as opposed to a mathematically defined geometry decreases the calculation time two-fold, due to an optimization of the MCNPX2.5e code. It is therefore possible to envisage the use of Oedipe for personalized dosimetry in the clinical context of targeted radiotherapy.

Monte Carlo method for photon heating using temperature-dependent optical properties.

PubMed

Slade, Adam Broadbent; Aguilar, Guillermo

2015-02-01

The Monte Carlo method for photon transport is often used to predict the volumetric heating that an optical source will induce inside a tissue or material. This method relies on constant (with respect to temperature) optical properties, specifically the coefficients of scattering and absorption. In reality, optical coefficients are typically temperature-dependent, leading to error in simulation results. The purpose of this study is to develop a method that can incorporate variable properties and accurately simulate systems where the temperature will greatly vary, such as in the case of laser-thawing of frozen tissues. A numerical simulation was developed that utilizes the Monte Carlo method for photon transport to simulate the thermal response of a system that allows temperature-dependent optical and thermal properties. This was done by combining traditional Monte Carlo photon transport with a heat transfer simulation to provide a feedback loop that selects local properties based on current temperatures, for each moment in time. Additionally, photon steps are segmented to accurately obtain path lengths within a homogenous (but not isothermal) material. Validation of the simulation was done using comparisons to established Monte Carlo simulations using constant properties, and a comparison to the Beer-Lambert law for temperature-variable properties. The simulation is able to accurately predict the thermal response of a system whose properties can vary with temperature. The difference in results between variable-property and constant property methods for the representative system of laser-heated silicon can become larger than 100K. This simulation will return more accurate results of optical irradiation absorption in a material which undergoes a large change in temperature. This increased accuracy in simulated results leads to better thermal predictions in living tissues and can provide enhanced planning and improved experimental and procedural outcomes. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema

PubMed Central

Chiang, Chia-Wen; Wang, Yong; Sun, Peng; Lin, Tsen-Hsuan; Trinkaus, Kathryn; Cross, Anne H.; Song, Sheng-Kwei

2014-01-01

The effect of extra-fiber structural and pathological components confounding diffusion tensor imaging (DTI) computation was quantitatively investigated using data generated by both Monte-Carlo simulations and tissue phantoms. Increased extent of vasogenic edema, by addition of various amount of gel to fixed normal mouse trigeminal nerves or by increasing non-restricted isotropic diffusion tensor components in Monte-Carlo simulations, significantly decreased fractional anisotropy (FA), increased radial diffusivity, while less significantly increased axial diffusivity derived by DTI. Increased cellularity, mimicked by graded increase of the restricted isotropic diffusion tensor component in Monte-Carlo simulations, significantly decreased FA and axial diffusivity with limited impact on radial diffusivity derived by DTI. The MC simulation and tissue phantom data were also analyzed by the recently developed diffusion basis spectrum imaging (DBSI) to simultaneously distinguish and quantify the axon/myelin integrity and extra-fiber diffusion components. Results showed that increased cellularity or vasogenic edema did not affect the DBSI-derived fiber FA, axial or radial diffusivity. Importantly, the extent of extra-fiber cellularity and edema estimated by DBSI correlated with experimentally added gel and Monte-Carlo simulations. We also examined the feasibility of applying 25-direction diffusion encoding scheme for DBSI analysis on coherent white matter tracts. Results from both phantom experiments and simulations suggested that the 25-direction diffusion scheme provided comparable DBSI estimation of both fiber diffusion parameters and extra-fiber cellularity/edema extent as those by 99-direction scheme. An in vivo 25-direction DBSI analysis was performed on experimental autoimmune encephalomyelitis (EAE, an animal model of human multiple sclerosis) optic nerve as an example to examine the validity of derived DBSI parameters with post-imaging immunohistochemistry verification. Results support that in vivo DBSI using 25-direction diffusion scheme correctly reflect the underlying axonal injury, demyelination, and inflammation of optic nerves in EAE mice. PMID:25017446

Diffusion Monte Carlo approach versus adiabatic computation for local Hamiltonians

NASA Astrophysics Data System (ADS)

Bringewatt, Jacob; Dorland, William; Jordan, Stephen P.; Mink, Alan

2018-02-01

Most research regarding quantum adiabatic optimization has focused on stoquastic Hamiltonians, whose ground states can be expressed with only real non-negative amplitudes and thus for whom destructive interference is not manifest. This raises the question of whether classical Monte Carlo algorithms can efficiently simulate quantum adiabatic optimization with stoquastic Hamiltonians. Recent results have given counterexamples in which path-integral and diffusion Monte Carlo fail to do so. However, most adiabatic optimization algorithms, such as for solving MAX-k -SAT problems, use k -local Hamiltonians, whereas our previous counterexample for diffusion Monte Carlo involved n -body interactions. Here we present a 6-local counterexample which demonstrates that even for these local Hamiltonians there are cases where diffusion Monte Carlo cannot efficiently simulate quantum adiabatic optimization. Furthermore, we perform empirical testing of diffusion Monte Carlo on a standard well-studied class of permutation-symmetric tunneling problems and similarly find large advantages for quantum optimization over diffusion Monte Carlo.

Direct simulation of high-vorticity gas flows

NASA Technical Reports Server (NTRS)

Bird, G. A.

1987-01-01

The computational limitations associated with the molecular dynamics (MD) method and the direct simulation Monte Carlo (DSMC) method are reviewed in the context of the computation of dilute gas flows with high vorticity. It is concluded that the MD method is generally limited to the dense gas case in which the molecular diameter is one-tenth or more of the mean free path. It is shown that the cell size in DSMC calculations should be small in comparison with the mean free path, and that this may be facilitated by a new subcell procedure for the selection of collision partners.

Thermal Characterization of the Air Force Institute of Technology Solar Simulation Thermal Vacuum Chamber

DTIC Science & Technology

2014-03-27

mass and surface area, Equation 12 demonstrates an energy balance for the material, assuming the rest of the surfaces of the material are isothermal...radiation in order to dissipate heat from 18 the spacecraft [8]. As discussed in the system thermal energy balance defined previously, emission of IR... energy balance calculations will be utilized. The Monte Carlo/Ray Trace Radiation Method The Monte Carlo/Ray Trace method is utilized in order to

Generalizing the self-healing diffusion Monte Carlo approach to finite temperature: A path for the optimization of low-energy many-body bases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reboredo, Fernando A.; Kim, Jeongnim

A statistical method is derived for the calculation of thermodynamic properties of many-body systems at low temperatures. This method is based on the self-healing diffusion Monte Carlo method for complex functions [F. A. Reboredo, J. Chem. Phys. 136, 204101 (2012)] and some ideas of the correlation function Monte Carlo approach [D. M. Ceperley and B. Bernu, J. Chem. Phys. 89, 6316 (1988)]. In order to allow the evolution in imaginary time to describe the density matrix, we remove the fixed-node restriction using complex antisymmetric guiding wave functions. In the process we obtain a parallel algorithm that optimizes a small subspacemore » of the many-body Hilbert space to provide maximum overlap with the subspace spanned by the lowest-energy eigenstates of a many-body Hamiltonian. We show in a model system that the partition function is progressively maximized within this subspace. We show that the subspace spanned by the small basis systematically converges towards the subspace spanned by the lowest energy eigenstates. Possible applications of this method for calculating the thermodynamic properties of many-body systems near the ground state are discussed. The resulting basis can also be used to accelerate the calculation of the ground or excited states with quantum Monte Carlo.« less

A linear stability analysis for nonlinear, grey, thermal radiative transfer problems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wollaber, Allan B., E-mail: wollaber@lanl.go; Larsen, Edward W., E-mail: edlarsen@umich.ed

2011-02-20

We present a new linear stability analysis of three time discretizations and Monte Carlo interpretations of the nonlinear, grey thermal radiative transfer (TRT) equations: the widely used 'Implicit Monte Carlo' (IMC) equations, the Carter Forest (CF) equations, and the Ahrens-Larsen or 'Semi-Analog Monte Carlo' (SMC) equations. Using a spatial Fourier analysis of the 1-D Implicit Monte Carlo (IMC) equations that are linearized about an equilibrium solution, we show that the IMC equations are unconditionally stable (undamped perturbations do not exist) if {alpha}, the IMC time-discretization parameter, satisfies 0.5 < {alpha} {<=} 1. This is consistent with conventional wisdom. However, wemore » also show that for sufficiently large time steps, unphysical damped oscillations can exist that correspond to the lowest-frequency Fourier modes. After numerically confirming this result, we develop a method to assess the stability of any time discretization of the 0-D, nonlinear, grey, thermal radiative transfer problem. Subsequent analyses of the CF and SMC methods then demonstrate that the CF method is unconditionally stable and monotonic, but the SMC method is conditionally stable and permits unphysical oscillatory solutions that can prevent it from reaching equilibrium. This stability theory provides new conditions on the time step to guarantee monotonicity of the IMC solution, although they are likely too conservative to be used in practice. Theoretical predictions are tested and confirmed with numerical experiments.« less

Hamiltonian Monte Carlo Inversion of Seismic Sources in Complex Media

NASA Astrophysics Data System (ADS)

Fichtner, A.; Simutė, S.

2017-12-01

We present a probabilistic seismic source inversion method that properly accounts for 3D heterogeneous Earth structure and provides full uncertainty information on the timing, location and mechanism of the event. Our method rests on two essential elements: (1) reciprocity and spectral-element simulations in complex media, and (2) Hamiltonian Monte Carlo sampling that requires only a small amount of test models. Using spectral-element simulations of 3D, visco-elastic, anisotropic wave propagation, we precompute a data base of the strain tensor in time and space by placing sources at the positions of receivers. Exploiting reciprocity, this receiver-side strain data base can be used to promptly compute synthetic seismograms at the receiver locations for any hypothetical source within the volume of interest. The rapid solution of the forward problem enables a Bayesian solution of the inverse problem. For this, we developed a variant of Hamiltonian Monte Carlo (HMC) sampling. Taking advantage of easily computable derivatives, HMC converges to the posterior probability density with orders of magnitude less samples than derivative-free Monte Carlo methods. (Exact numbers depend on observational errors and the quality of the prior). We apply our method to the Japanese Islands region where we previously constrained 3D structure of the crust and upper mantle using full-waveform inversion with a minimum period of around 15 s.

New approach based on tetrahedral-mesh geometry for accurate 4D Monte Carlo patient-dose calculation

NASA Astrophysics Data System (ADS)

Han, Min Cheol; Yeom, Yeon Soo; Kim, Chan Hyeong; Kim, Seonghoon; Sohn, Jason W.

2015-02-01

In the present study, to achieve accurate 4D Monte Carlo dose calculation in radiation therapy, we devised a new approach that combines (1) modeling of the patient body using tetrahedral-mesh geometry based on the patient’s 4D CT data, (2) continuous movement/deformation of the tetrahedral patient model by interpolation of deformation vector fields acquired through deformable image registration, and (3) direct transportation of radiation particles during the movement and deformation of the tetrahedral patient model. The results of our feasibility study show that it is certainly possible to construct 4D patient models (= phantoms) with sufficient accuracy using the tetrahedral-mesh geometry and to directly transport radiation particles during continuous movement and deformation of the tetrahedral patient model. This new approach not only produces more accurate dose distribution in the patient but also replaces the current practice of using multiple 3D voxel phantoms and combining multiple dose distributions after Monte Carlo simulations. For routine clinical application of our new approach, the use of fast automatic segmentation algorithms is a must. In order to achieve, simultaneously, both dose accuracy and computation speed, the number of tetrahedrons for the lungs should be optimized. Although the current computation speed of our new 4D Monte Carlo simulation approach is slow (i.e. ~40 times slower than that of the conventional dose accumulation approach), this problem is resolvable by developing, in Geant4, a dedicated navigation class optimized for particle transportation in tetrahedral-mesh geometry.

Integration within the Felsenstein equation for improved Markov chain Monte Carlo methods in population genetics

PubMed Central

Hey, Jody; Nielsen, Rasmus

2007-01-01

In 1988, Felsenstein described a framework for assessing the likelihood of a genetic data set in which all of the possible genealogical histories of the data are considered, each in proportion to their probability. Although not analytically solvable, several approaches, including Markov chain Monte Carlo methods, have been developed to find approximate solutions. Here, we describe an approach in which Markov chain Monte Carlo simulations are used to integrate over the space of genealogies, whereas other parameters are integrated out analytically. The result is an approximation to the full joint posterior density of the model parameters. For many purposes, this function can be treated as a likelihood, thereby permitting likelihood-based analyses, including likelihood ratio tests of nested models. Several examples, including an application to the divergence of chimpanzee subspecies, are provided. PMID:17301231

Hamiltonian Markov Chain Monte Carlo Methods for the CUORE Neutrinoless Double Beta Decay Sensitivity

NASA Astrophysics Data System (ADS)

Graham, Eleanor; Cuore Collaboration

2017-09-01

The CUORE experiment is a large-scale bolometric detector seeking to observe the never-before-seen process of neutrinoless double beta decay. Predictions for CUORE's sensitivity to neutrinoless double beta decay allow for an understanding of the half-life ranges that the detector can probe, and also to evaluate the relative importance of different detector parameters. Currently, CUORE uses a Bayesian analysis based in BAT, which uses Metropolis-Hastings Markov Chain Monte Carlo, for its sensitivity studies. My work evaluates the viability and potential improvements of switching the Bayesian analysis to Hamiltonian Monte Carlo, realized through the program Stan and its Morpho interface. I demonstrate that the BAT study can be successfully recreated in Stan, and perform a detailed comparison between the results and computation times of the two methods.

Modelling maximum river flow by using Bayesian Markov Chain Monte Carlo

NASA Astrophysics Data System (ADS)

Cheong, R. Y.; Gabda, D.

2017-09-01

Analysis of flood trends is vital since flooding threatens human living in terms of financial, environment and security. The data of annual maximum river flows in Sabah were fitted into generalized extreme value (GEV) distribution. Maximum likelihood estimator (MLE) raised naturally when working with GEV distribution. However, previous researches showed that MLE provide unstable results especially in small sample size. In this study, we used different Bayesian Markov Chain Monte Carlo (MCMC) based on Metropolis-Hastings algorithm to estimate GEV parameters. Bayesian MCMC method is a statistical inference which studies the parameter estimation by using posterior distribution based on Bayes’ theorem. Metropolis-Hastings algorithm is used to overcome the high dimensional state space faced in Monte Carlo method. This approach also considers more uncertainty in parameter estimation which then presents a better prediction on maximum river flow in Sabah.

Quantum Monte Carlo calculations of light nuclei with local chiral two- and three-nucleon interactions

DOE PAGES

Lynn, J. E.; Tews, I.; Carlson, J.; ...

2017-11-30

Local chiral effective field theory interactions have recently been developed and used in the context of quantum Monte Carlo few- and many-body methods for nuclear physics. In this paper, we go over detailed features of local chiral nucleon-nucleon interactions and examine their effect on properties of the deuteron, paying special attention to the perturbativeness of the expansion. We then turn to three-nucleon interactions, focusing on operator ambiguities and their interplay with regulator effects. We then discuss the nuclear Green's function Monte Carlo method, going over both wave-function correlations and approximations for the two- and three-body propagators. Finally, following this, wemore » present a range of results on light nuclei: Binding energies and distribution functions are contrasted and compared, starting from several different microscopic interactions.« less

An Evaluation of a Markov Chain Monte Carlo Method for the Two-Parameter Logistic Model.

ERIC Educational Resources Information Center

Kim, Seock-Ho; Cohen, Allan S.

The accuracy of the Markov Chain Monte Carlo (MCMC) procedure Gibbs sampling was considered for estimation of item parameters of the two-parameter logistic model. Data for the Law School Admission Test (LSAT) Section 6 were analyzed to illustrate the MCMC procedure. In addition, simulated data sets were analyzed using the MCMC, marginal Bayesian…

Shielding analyses: the rabbit vs the turtle?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Broadhead, B.L.

1996-12-31

This paper compares solutions using Monte Carlo and discrete- ordinates methods applied to two actual shielding situations in order to make some general observations concerning the efficiency and advantages/disadvantages of the two approaches. The discrete- ordinates solutions are performed using two-dimensional geometries, while the Monte Carlo approaches utilize three-dimensional geometries with both multigroup and point cross-section data.

Recovery of Item Parameters in the Nominal Response Model: A Comparison of Marginal Maximum Likelihood Estimation and Markov Chain Monte Carlo Estimation.

ERIC Educational Resources Information Center

Wollack, James A.; Bolt, Daniel M.; Cohen, Allan S.; Lee, Young-Sun

2002-01-01

Compared the quality of item parameter estimates for marginal maximum likelihood (MML) and Markov Chain Monte Carlo (MCMC) with the nominal response model using simulation. The quality of item parameter recovery was nearly identical for MML and MCMC, and both methods tended to produce good estimates. (SLD)

Modeling 2D and 3D diffusion.

PubMed

Saxton, Michael J

2007-01-01

Modeling obstructed diffusion is essential to the understanding of diffusion-mediated processes in the crowded cellular environment. Simple Monte Carlo techniques for modeling obstructed random walks are explained and related to Brownian dynamics and more complicated Monte Carlo methods. Random number generation is reviewed in the context of random walk simulations. Programming techniques and event-driven algorithms are discussed as ways to speed simulations.

Dose specification for radiation therapy: dose to water or dose to medium?

NASA Astrophysics Data System (ADS)

Ma, C.-M.; Li, Jinsheng

2011-05-01

The Monte Carlo method enables accurate dose calculation for radiation therapy treatment planning and has been implemented in some commercial treatment planning systems. Unlike conventional dose calculation algorithms that provide patient dose information in terms of dose to water with variable electron density, the Monte Carlo method calculates the energy deposition in different media and expresses dose to a medium. This paper discusses the differences in dose calculated using water with different electron densities and that calculated for different biological media and the clinical issues on dose specification including dose prescription and plan evaluation using dose to water and dose to medium. We will demonstrate that conventional photon dose calculation algorithms compute doses similar to those simulated by Monte Carlo using water with different electron densities, which are close (<4% differences) to doses to media but significantly different (up to 11%) from doses to water converted from doses to media following American Association of Physicists in Medicine (AAPM) Task Group 105 recommendations. Our results suggest that for consistency with previous radiation therapy experience Monte Carlo photon algorithms report dose to medium for radiotherapy dose prescription, treatment plan evaluation and treatment outcome analysis.

Thermal helium clusters at 3.2 Kelvin in classical and semiclassical simulations

NASA Astrophysics Data System (ADS)

Schulte, J.

1993-03-01

The thermodynamic stability of4He4-13 at 3.2 K is investigated with the classical Monte Carlo method, with the semiclassical path-integral Monte Carlo (PIMC) method, and with the semiclassical all-order many-body method. In the all-order many-body simulation the dipole-dipole approximation including short-range correction is used. The resulting stability plots are discussed and related to recent TOF experiments by Stephens and King. It is found that with classical Monte Carlo of course the characteristics of the measured mass spectrum cannot be resolved. With PIMC, switching on more and more quantum mechanics. by raising the number of virtual time steps results in more structure in the stability plot, but this did not lead to sufficient agreement with the TOF experiment. Only the all-order many-body method resolved the characteristic structures of the measured mass spectrum, including magic numbers. The result shows the influence of quantum statistics and quantum mechanics on the stability of small neutral helium clusters.

Hybrid Monte Carlo approach to the entanglement entropy of interacting fermions

NASA Astrophysics Data System (ADS)

Drut, Joaquín E.; Porter, William J.

2015-09-01

The Monte Carlo calculation of Rényi entanglement entropies Sn of interacting fermions suffers from a well-known signal-to-noise problem, even for a large number of situations in which the infamous sign problem is absent. A few methods have been proposed to overcome this issue, such as ensemble switching and the use of auxiliary partition-function ratios. Here, we present an approach that builds on the recently proposed free-fermion decomposition method; it incorporates entanglement in the probability measure in a natural way; it takes advantage of the hybrid Monte Carlo algorithm (an essential tool in lattice quantum chromodynamics and other gauge theories with dynamical fermions); and it does not suffer from noise problems. This method displays no sign problem for the same cases as other approaches and is therefore useful for a wide variety of systems. As a proof of principle, we calculate S2 for the one-dimensional, half-filled Hubbard model and compare with results from exact diagonalization and the free-fermion decomposition method.

Solving the master equation without kinetic Monte Carlo: Tensor train approximations for a CO oxidation model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gelß, Patrick, E-mail: p.gelss@fu-berlin.de; Matera, Sebastian, E-mail: matera@math.fu-berlin.de; Schütte, Christof, E-mail: schuette@mi.fu-berlin.de

2016-06-01

In multiscale modeling of heterogeneous catalytic processes, one crucial point is the solution of a Markovian master equation describing the stochastic reaction kinetics. Usually, this is too high-dimensional to be solved with standard numerical techniques and one has to rely on sampling approaches based on the kinetic Monte Carlo method. In this study we break the curse of dimensionality for the direct solution of the Markovian master equation by exploiting the Tensor Train Format for this purpose. The performance of the approach is demonstrated on a first principles based, reduced model for the CO oxidation on the RuO{sub 2}(110) surface.more » We investigate the complexity for increasing system size and for various reaction conditions. The advantage over the stochastic simulation approach is illustrated by a problem with increased stiffness.« less

Phase Diagram of Hydrogen and a Hydrogen-Helium Mixture at Planetary Conditions by Quantum Monte Carlo Simulations

NASA Astrophysics Data System (ADS)

Mazzola, Guglielmo; Helled, Ravit; Sorella, Sandro

2018-01-01

Understanding planetary interiors is directly linked to our ability of simulating exotic quantum mechanical systems such as hydrogen (H) and hydrogen-helium (H-He) mixtures at high pressures and temperatures. Equation of state (EOS) tables based on density functional theory are commonly used by planetary scientists, although this method allows only for a qualitative description of the phase diagram. Here we report quantum Monte Carlo (QMC) molecular dynamics simulations of pure H and H-He mixture. We calculate the first QMC EOS at 6000 K for a H-He mixture of a protosolar composition, and show the crucial influence of He on the H metallization pressure. Our results can be used to calibrate other EOS calculations and are very timely given the accurate determination of Jupiter's gravitational field from the NASA Juno mission and the effort to determine its structure.

Calibration with MCNP of NaI detector for the determination of natural radioactivity levels in the field.

PubMed

Cinelli, Giorgia; Tositti, Laura; Mostacci, Domiziano; Baré, Jonathan

2016-05-01

In view of assessing natural radioactivity with on-site quantitative gamma spectrometry, efficiency calibration of NaI(Tl) detectors is investigated. A calibration based on Monte Carlo simulation of detector response is proposed, to render reliable quantitative analysis practicable in field campaigns. The method is developed with reference to contact geometry, in which measurements are taken placing the NaI(Tl) probe directly against the solid source to be analyzed. The Monte Carlo code used for the simulations was MCNP. Experimental verification of the calibration goodness is obtained by comparison with appropriate standards, as reported. On-site measurements yield a quick quantitative assessment of natural radioactivity levels present ((40)K, (238)U and (232)Th). On-site gamma spectrometry can prove particularly useful insofar as it provides information on materials from which samples cannot be taken. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Monte Carlo simulation for Neptun 10 PC medical linear accelerator and calculations of output factor for electron beam

PubMed Central

Bahreyni Toossi, Mohammad Taghi; Momennezhad, Mehdi; Hashemi, Seyed Mohammad

2012-01-01

Aim Exact knowledge of dosimetric parameters is an essential pre-requisite of an effective treatment in radiotherapy. In order to fulfill this consideration, different techniques have been used, one of which is Monte Carlo simulation. Materials and methods This study used the MCNP-4Cb to simulate electron beams from Neptun 10 PC medical linear accelerator. Output factors for 6, 8 and 10 MeV electrons applied to eleven different conventional fields were both measured and calculated. Results The measurements were carried out by a Wellhofler-Scanditronix dose scanning system. Our findings revealed that output factors acquired by MCNP-4C simulation and the corresponding values obtained by direct measurements are in a very good agreement. Conclusion In general, very good consistency of simulated and measured results is a good proof that the goal of this work has been accomplished. PMID:24377010

Monte Carlo simulation of a near-continuum shock-shock interaction problem

NASA Technical Reports Server (NTRS)

Carlson, Ann B.; Wilmoth, Richard G.

1992-01-01

A complex shock interaction is calculated with direct simulation Monte Carlo (DSMC). The calculation is performed for the near-continuum flow produced when an incident shock impinges on the bow shock of a 0.1 in. radius cowl lip for freestream conditions of approximately Mach 15 and 35 km altitude. Solutions are presented both for a full finite-rate chemistry calculation and for a case with chemical reactions suppressed. In each case, both the undisturbed flow about the cowl lip and the full shock interaction flowfields are calculated. Good agreement has been obtained between the no-chemistry simulation of the undisturbed flow and a perfect gas solution obtained with the viscous shock-layer method. Large differences in calculated surface properties when different chemical models are used demonstrate the necessity of adequately representing the chemistry when making surface property predictions. Preliminary grid refinement studies make it possible to estimate the accuracy of the solutions.

A Monte Carlo program to calculate the exposure rate from airborne radioactive gases inside a nuclear reactor containment building.

PubMed

Sherbini, S; Tamasanis, D; Sykes, J; Porter, S W

1986-12-01

A program was developed to calculate the exposure rate resulting from airborne gases inside a reactor containment building. The calculations were performed at the location of a wall-mounted area radiation monitor. The program uses Monte Carlo techniques and accounts for both the direct and scattered components of the radiation field at the detector. The scattered component was found to contribute about 30% of the total exposure rate at 50 keV and dropped to about 7% at 2000 keV. The results of the calculations were normalized to unit activity per unit volume of air in the containment. This allows the exposure rate readings of the area monitor to be used to estimate the airborne activity in containment in the early phases of an accident. Such estimates, coupled with containment leak rates, provide a method to obtain a release rate for use in offsite dose projection calculations.

Monte Carlo Perturbation Theory Estimates of Sensitivities to System Dimensions

DOE PAGES

Burke, Timothy P.; Kiedrowski, Brian C.

2017-12-11

Here, Monte Carlo methods are developed using adjoint-based perturbation theory and the differential operator method to compute the sensitivities of the k-eigenvalue, linear functions of the flux (reaction rates), and bilinear functions of the forward and adjoint flux (kinetics parameters) to system dimensions for uniform expansions or contractions. The calculation of sensitivities to system dimensions requires computing scattering and fission sources at material interfaces using collisions occurring at the interface—which is a set of events with infinitesimal probability. Kernel density estimators are used to estimate the source at interfaces using collisions occurring near the interface. The methods for computing sensitivitiesmore » of linear and bilinear ratios are derived using the differential operator method and adjoint-based perturbation theory and are shown to be equivalent to methods previously developed using a collision history–based approach. The methods for determining sensitivities to system dimensions are tested on a series of fast, intermediate, and thermal critical benchmarks as well as a pressurized water reactor benchmark problem with iterated fission probability used for adjoint-weighting. The estimators are shown to agree within 5% and 3σ of reference solutions obtained using direct perturbations with central differences for the majority of test problems.« less

Girsanov's transformation based variance reduced Monte Carlo simulation schemes for reliability estimation in nonlinear stochastic dynamics

NASA Astrophysics Data System (ADS)

Kanjilal, Oindrila; Manohar, C. S.

2017-07-01

The study considers the problem of simulation based time variant reliability analysis of nonlinear randomly excited dynamical systems. Attention is focused on importance sampling strategies based on the application of Girsanov's transformation method. Controls which minimize the distance function, as in the first order reliability method (FORM), are shown to minimize a bound on the sampling variance of the estimator for the probability of failure. Two schemes based on the application of calculus of variations for selecting control signals are proposed: the first obtains the control force as the solution of a two-point nonlinear boundary value problem, and, the second explores the application of the Volterra series in characterizing the controls. The relative merits of these schemes, vis-à-vis the method based on ideas from the FORM, are discussed. Illustrative examples, involving archetypal single degree of freedom (dof) nonlinear oscillators, and a multi-degree of freedom nonlinear dynamical system, are presented. The credentials of the proposed procedures are established by comparing the solutions with pertinent results from direct Monte Carlo simulations.

Neutron Transport Models and Methods for HZETRN and Coupling to Low Energy Light Ion Transport

NASA Technical Reports Server (NTRS)

Blattnig, S.R.; Slaba, T.C.; Heinbockel, J.H.

2008-01-01

Exposure estimates inside space vehicles, surface habitats, and high altitude aircraft exposed to space radiation are highly influenced by secondary neutron production. The deterministic transport code HZETRN has been identified as a reliable and efficient tool for such studies, but improvements to the underlying transport models and numerical methods are still necessary. In this paper, the forward-backward (FB) and directionally coupled forward-backward (DC) neutron transport models are derived, numerical methods for the FB model are reviewed, and a computationally efficient numerical solution is presented for the DC model. Both models are compared to the Monte Carlo codes HETCHEDS and FLUKA, and the DC model is shown to agree closely with the Monte Carlo results. Finally, it is found in the development of either model that the decoupling of low energy neutrons from the light ion (A<4) transport procedure adversely affects low energy light ion fluence spectra and exposure quantities. A first order correction is presented to resolve the problem, and it is shown to be both accurate and efficient.

Particle in cell/Monte Carlo collision analysis of the problem of identification of impurities in the gas by the plasma electron spectroscopy method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kusoglu Sarikaya, C.; Rafatov, I., E-mail: rafatov@metu.edu.tr; Kudryavtsev, A. A.

2016-06-15

The work deals with the Particle in Cell/Monte Carlo Collision (PIC/MCC) analysis of the problem of detection and identification of impurities in the nonlocal plasma of gas discharge using the Plasma Electron Spectroscopy (PLES) method. For this purpose, 1d3v PIC/MCC code for numerical simulation of glow discharge with nonlocal electron energy distribution function is developed. The elastic, excitation, and ionization collisions between electron-neutral pairs and isotropic scattering and charge exchange collisions between ion-neutral pairs and Penning ionizations are taken into account. Applicability of the numerical code is verified under the Radio-Frequency capacitively coupled discharge conditions. The efficiency of the codemore » is increased by its parallelization using Open Message Passing Interface. As a demonstration of the PLES method, parallel PIC/MCC code is applied to the direct current glow discharge in helium doped with a small amount of argon. Numerical results are consistent with the theoretical analysis of formation of nonlocal EEDF and existing experimental data.« less

An analysis on the theory of pulse oximetry by Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Fan, Shangchun; Cai, Rui; Xing, Weiwei; Liu, Changting; Chen, Guangfei; Wang, Junfeng

2008-10-01

The pulse oximetry is a kind of electronic instrument that measures the oxygen saturation of arterial blood and pulse rate by non-invasive techniques. It enables prompt recognition of hypoxemia. In a conventional transmittance type pulse oximeter, the absorption of light by oxygenated and reduced hemoglobin is measured at two wavelength 660nm and 940nm. But the accuracy and measuring range of the pulse oximeter can not meet the requirement of clinical application. There are limitations in the theory of pulse oximetry, which is proved by Monte Carlo method. The mean paths are calculated in the Monte Carlo simulation. The results prove that the mean paths are not the same between the different wavelengths.

ME(SSY)**2: Monte Carlo Code for Star Cluster Simulations

NASA Astrophysics Data System (ADS)

Freitag, Marc Dewi

2013-02-01

ME(SSY)**2 stands for “Monte-carlo Experiments with Spherically SYmmetric Stellar SYstems." This code simulates the long term evolution of spherical clusters of stars; it was devised specifically to treat dense galactic nuclei. It is based on the pioneering Monte Carlo scheme proposed by Hénon in the 70's and includes all relevant physical ingredients (2-body relaxation, stellar mass spectrum, collisions, tidal disruption, ldots). It is basically a Monte Carlo resolution of the Fokker-Planck equation. It can cope with any stellar mass spectrum or velocity distribution. Being a particle-based method, it also allows one to take stellar collisions into account in a very realistic way. This unique code, featuring most important physical processes, allows million particle simulations, spanning a Hubble time, in a few CPU days on standard personal computers and provides a wealth of data only rivalized by N-body simulations. The current version of the software requires the use of routines from the "Numerical Recipes in Fortran 77" (http://www.nrbook.com/a/bookfpdf.php).

A novel algorithm for solving the true coincident counting issues in Monte Carlo simulations for radiation spectroscopy.

PubMed

Guan, Fada; Johns, Jesse M; Vasudevan, Latha; Zhang, Guoqing; Tang, Xiaobin; Poston, John W; Braby, Leslie A

2015-06-01

Coincident counts can be observed in experimental radiation spectroscopy. Accurate quantification of the radiation source requires the detection efficiency of the spectrometer, which is often experimentally determined. However, Monte Carlo analysis can be used to supplement experimental approaches to determine the detection efficiency a priori. The traditional Monte Carlo method overestimates the detection efficiency as a result of omitting coincident counts caused mainly by multiple cascade source particles. In this study, a novel "multi-primary coincident counting" algorithm was developed using the Geant4 Monte Carlo simulation toolkit. A high-purity Germanium detector for ⁶⁰Co gamma-ray spectroscopy problems was accurately modeled to validate the developed algorithm. The simulated pulse height spectrum agreed well qualitatively with the measured spectrum obtained using the high-purity Germanium detector. The developed algorithm can be extended to other applications, with a particular emphasis on challenging radiation fields, such as counting multiple types of coincident radiations released from nuclear fission or used nuclear fuel.

Neutrality and evolvability of designed protein sequences

NASA Astrophysics Data System (ADS)

Bhattacherjee, Arnab; Biswas, Parbati

2010-07-01

The effect of foldability on protein’s evolvability is analyzed by a two-prong approach consisting of a self-consistent mean-field theory and Monte Carlo simulations. Theory and simulation models representing protein sequences with binary patterning of amino acid residues compatible with a particular foldability criteria are used. This generalized foldability criterion is derived using the high temperature cumulant expansion approximating the free energy of folding. The effect of cumulative point mutations on these designed proteins is studied under neutral condition. The robustness, protein’s ability to tolerate random point mutations is determined with a selective pressure of stability (ΔΔG) for the theory designed sequences, which are found to be more robust than that of Monte Carlo and mean-field-biased Monte Carlo generated sequences. The results show that this foldability criterion selects viable protein sequences more effectively compared to the Monte Carlo method, which has a marked effect on how the selective pressure shapes the evolutionary sequence space. These observations may impact de novo sequence design and its applications in protein engineering.

VARIAN CLINAC 6 MeV Photon Spectra Unfolding using a Monte Carlo Meshed Model

NASA Astrophysics Data System (ADS)

Morató, S.; Juste, B.; Miró, R.; Verdú, G.

2017-09-01

Energy spectrum is the best descriptive function to determine photon beam quality of a Medical Linear Accelerator (LinAc). The use of realistic photon spectra in Monte Carlo simulations has a great importance to obtain precise dose calculations in Radiotherapy Treatment Planning (RTP). Reconstruction of photon spectra emitted by medical accelerators from measured depth dose distributions in a water cube is an important tool for commissioning a Monte Carlo treatment planning system. Regarding this, the reconstruction problem is an inverse radiation transport function which is ill conditioned and its solution may become unstable due to small perturbations in the input data. This paper presents a more stable spectral reconstruction method which can be used to provide an independent confirmation of source models for a given machine without any prior knowledge of the spectral distribution. Monte Carlo models used in this work are built with unstructured meshes to simulate with realism the linear accelerator head geometry.

Poster — Thur Eve — 47: Monte Carlo Simulation of Scp, Sc and Sp

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhan, Lixin; Jiang, Runqing; Osei, Ernest K.

The in-water output ratio (Scp), in-air output ratio (Sc), and phantom scattering factor (Sp) are important parameters for radiotherapy dose calculation. Experimentally, Scp is obtained by measuring the dose rate ratio in water phantom, and Sc the water Kerma rate ratio in air. There is no method that allows direct measurement of Sp. Monte Carlo (MC) method has been used to simulate Scp and Sc in literatures, similar to experimental setup, but no MC direct simulation of Sp available yet to the best of our knowledge. We propose in this report a method of performing direct MC simulation of Sp.more » Starting from the definition, we derived that Sp of a clinical photon beam can be approximated by the ratio of the dose rates contributed from the primary beam for a given field size to the reference field size. Since only the primary beam is used, any Linac head scattering should be excluded from the simulation, which can be realized by using the incident electron as a scoring parameter for MU. We performed MC simulations for Scp, Sc and Sp. Scp matches well with golden beam data. Sp obtained by the proposed method agrees well with what is obtained using the traditional method, Sp=Scp/Sc. Since the smaller the field size, the more the primary beam dominates, our Sp simulation method is accurate for small field. By analyzing the calculated data, we found that this method can be used with no problem for large fields. The difference it introduced is clinically insignificant.« less

A response to Yu et al. "A forward-backward fragment assembling algorithm for the identification of genomic amplification and deletion breakpoints using high-density single nucleotide polymorphism (SNP) array", BMC Bioinformatics 2007, 8: 145.

PubMed

Rueda, Oscar M; Diaz-Uriarte, Ramon

2007-10-16

Yu et al. (BMC Bioinformatics 2007,8: 145+) have recently compared the performance of several methods for the detection of genomic amplification and deletion breakpoints using data from high-density single nucleotide polymorphism arrays. One of the methods compared is our non-homogenous Hidden Markov Model approach. Our approach uses Markov Chain Monte Carlo for inference, but Yu et al. ran the sampler for a severely insufficient number of iterations for a Markov Chain Monte Carlo-based method. Moreover, they did not use the appropriate reference level for the non-altered state. We rerun the analysis in Yu et al. using appropriate settings for both the Markov Chain Monte Carlo iterations and the reference level. Additionally, to show how easy it is to obtain answers to additional specific questions, we have added a new analysis targeted specifically to the detection of breakpoints. The reanalysis shows that the performance of our method is comparable to that of the other methods analyzed. In addition, we can provide probabilities of a given spot being a breakpoint, something unique among the methods examined. Markov Chain Monte Carlo methods require using a sufficient number of iterations before they can be assumed to yield samples from the distribution of interest. Running our method with too small a number of iterations cannot be representative of its performance. Moreover, our analysis shows how our original approach can be easily adapted to answer specific additional questions (e.g., identify edges).

EDITORIAL: Special section: Selected papers from the Second European Workshop on Monte Carlo Treatment Planning (MCTP2009) Special section: Selected papers from the Second European Workshop on Monte Carlo Treatment Planning (MCTP2009)

NASA Astrophysics Data System (ADS)

Spezi, Emiliano

2010-08-01

Sixty years after the paper 'The Monte Carlo method' by N Metropolis and S Ulam in The Journal of the American Statistical Association (Metropolis and Ulam 1949), use of the most accurate algorithm for computer modelling of radiotherapy linear accelerators, radiation detectors and three dimensional patient dose was discussed in Wales (UK). The Second European Workshop on Monte Carlo Treatment Planning (MCTP2009) was held at the National Museum of Wales in Cardiff. The event, organized by Velindre NHS Trust, Cardiff University and Cancer Research Wales, lasted two and a half days, during which leading experts and contributing authors presented and discussed the latest advances in the field of Monte Carlo treatment planning (MCTP). MCTP2009 was highly successful, judging from the number of participants which was in excess of 140. Of the attendees, 24% came from the UK, 46% from the rest of Europe, 12% from North America and 18% from the rest of the World. Fifty-three oral presentations and 24 posters were delivered in a total of 12 scientific sessions. MCTP2009 follows the success of previous similar initiatives (Verhaegen and Seuntjens 2005, Reynaert 2007, Verhaegen and Seuntjens 2008), and confirms the high level of interest in Monte Carlo technology for radiotherapy treatment planning. The 13 articles selected for this special section (following Physics in Medicine and Biology's usual rigorous peer-review procedure) give a good picture of the high quality of the work presented at MCTP2009. The book of abstracts can be downloaded from http://www.mctp2009.org. I wish to thank the IOP Medical Physics and Computational Physics Groups for their financial support, Elekta Ltd and Dosisoft for sponsoring MCTP2009, and leading manufacturers such as BrainLab, Nucletron and Varian for showcasing their latest MC-based radiotherapy solutions during a dedicated technical session. I am also very grateful to the eight invited speakers who kindly accepted to give keynote presentations which contributed significantly to raising the quality of the event and capturing the interest of the medical physics community. I also wish to thank all those who contributed to the success of MCTP2009: the members of the local Organizing Committee and the Workshop Management Team who managed the event very efficiently, the members of the European Working Group in Monte Carlo Treatment Planning (EWG-MCTP) who acted as Guest Associate Editors for the MCTP2009 abstracts reviewing process, and all the authors who generated new, high quality work. Finally, I hope that you find the contents of this special section enjoyable and informative. Emiliano Spezi Chairman of MCTP2009 Organizing Committee and Guest Editor References Metropolis N and Ulam S 1949 The Monte Carlo method J. Amer. Stat. Assoc. 44 335-41 Reynaert N 2007 First European Workshop on Monte Carlo Treatment Planning J. Phys.: Conf. Ser. 74 011001 Verhaegen F and Seuntjens J 2005 International Workshop on Current Topics in Monte Carlo Treatment Planning Phys. Med. Biol. 50 Verhaegen F and Seuntjens J 2008 International Workshop on Monte Carlo Techniques in Radiotherapy Delivery and Verification J. Phys.: Conf. Ser. 102 011001

Monte Carlo modeling of the Siemens Optifocus multileaf collimator.

PubMed

Laliena, Victor; García-Romero, Alejandro

2015-05-01

We have developed a new component module for the BEAMnrc software package, called SMLC, which models the tongue-and-groove structure of the Siemens Optifocus multileaf collimator. The ultimate goal is to perform accurate Monte Carlo simulations of the IMRT treatments carried out with Optifocus. SMLC has been validated by direct geometry checks and by comparing quantitatively the results of simulations performed with it and with the component module VARMLC. Measurements and Monte Carlo simulations of absorbed dose distributions of radiation fields sensitive to the tongue-and-groove effect have been performed to tune the free parameters of SMLC. The measurements cannot be accurately reproduced with VARMLC. Finally, simulations of a typical IMRT field showed that SMLC improves the agreement with experimental measurements with respect to VARMLC in clinically relevant cases. 87.55. K. Copyright © 2015 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Molecular dynamics and Monte Carlo simulations resolve apparent diffusion rate differences for proteins confined in nanochannels

DOE PAGES

Tringe, J. W.; Ileri, N.; Levie, H. W.; ...

2015-08-01

We use Molecular Dynamics and Monte Carlo simulations to examine molecular transport phenomena in nanochannels, explaining four orders of magnitude difference in wheat germ agglutinin (WGA) protein diffusion rates observed by fluorescence correlation spectroscopy (FCS) and by direct imaging of fluorescently-labeled proteins. We first use the ESPResSo Molecular Dynamics code to estimate the surface transport distance for neutral and charged proteins. We then employ a Monte Carlo model to calculate the paths of protein molecules on surfaces and in the bulk liquid transport medium. Our results show that the transport characteristics depend strongly on the degree of molecular surface coverage.more » Atomic force microscope characterization of surfaces exposed to WGA proteins for 1000 s show large protein aggregates consistent with the predicted coverage. These calculations and experiments provide useful insight into the details of molecular motion in confined geometries.« less

Monte Carlo Simulations of Arterial Imaging with Optical Coherence Tomography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Amendt, P.; Estabrook, K.; Everett, M.

2000-02-01

The laser-tissue interaction code LATIS [London et al., Appl. Optics 36, 9068 ( 1998)] is used to analyze photon scattering histories representative of optical coherence tomography (OCT) experiment performed at Lawrence Livermore National Laboratory. Monte Carlo photonics with Henyey-Greenstein anisotropic scattering is implemented and used to simulate signal discrimination of intravascular structure. An analytic model is developed and used to obtain a scaling law relation for optimization of the OCT signal and to validate Monte Carlo photonics. The appropriateness of the Henyey-Greenstein phase function is studied by direct comparison with more detailed Mie scattering theory using an ensemble of sphericalmore » dielectric scatterers. Modest differences are found between the two prescriptions for describing photon angular scattering in tissue. In particular, the Mie scattering phase functions provide less overall reflectance signal but more signal contrast compared to the Henyey-Greenstein formulation.« less

Thermodynamics and simulation of hard-sphere fluid and solid: Kinetic Monte Carlo method versus standard Metropolis scheme

NASA Astrophysics Data System (ADS)

Ustinov, E. A.

2017-01-01

The paper aims at a comparison of techniques based on the kinetic Monte Carlo (kMC) and the conventional Metropolis Monte Carlo (MC) methods as applied to the hard-sphere (HS) fluid and solid. In the case of the kMC, an alternative representation of the chemical potential is explored [E. A. Ustinov and D. D. Do, J. Colloid Interface Sci. 366, 216 (2012)], which does not require any external procedure like the Widom test particle insertion method. A direct evaluation of the chemical potential of the fluid and solid without thermodynamic integration is achieved by molecular simulation in an elongated box with an external potential imposed on the system in order to reduce the particle density in the vicinity of the box ends. The existence of rarefied zones allows one to determine the chemical potential of the crystalline phase and substantially increases its accuracy for the disordered dense phase in the central zone of the simulation box. This method is applicable to both the Metropolis MC and the kMC, but in the latter case, the chemical potential is determined with higher accuracy at the same conditions and the number of MC steps. Thermodynamic functions of the disordered fluid and crystalline face-centered cubic (FCC) phase for the hard-sphere system have been evaluated with the kinetic MC and the standard MC coupled with the Widom procedure over a wide range of density. The melting transition parameters have been determined by the point of intersection of the pressure-chemical potential curves for the disordered HS fluid and FCC crystal using the Gibbs-Duhem equation as a constraint. A detailed thermodynamic analysis of the hard-sphere fluid has provided a rigorous verification of the approach, which can be extended to more complex systems.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Haugen, Carl C.; Forget, Benoit; Smith, Kord S.

Most high performance computing systems being deployed currently and envisioned for the future are based on making use of heavy parallelism across many computational nodes and many concurrent cores. These types of heavily parallel systems often have relatively little memory per core but large amounts of computing capability. This places a significant constraint on how data storage is handled in many Monte Carlo codes. This is made even more significant in fully coupled multiphysics simulations, which requires simulations of many physical phenomena be carried out concurrently on individual processing nodes, which further reduces the amount of memory available for storagemore » of Monte Carlo data. As such, there has been a move towards on-the-fly nuclear data generation to reduce memory requirements associated with interpolation between pre-generated large nuclear data tables for a selection of system temperatures. Methods have been previously developed and implemented in MIT’s OpenMC Monte Carlo code for both the resolved resonance regime and the unresolved resonance regime, but are currently absent for the thermal energy regime. While there are many components involved in generating a thermal neutron scattering cross section on-the-fly, this work will focus on a proposed method for determining the energy and direction of a neutron after a thermal incoherent inelastic scattering event. This work proposes a rejection sampling based method using the thermal scattering kernel to determine the correct outgoing energy and angle. The goal of this project is to be able to treat the full S (a, ß) kernel for graphite, to assist in high fidelity simulations of the TREAT reactor at Idaho National Laboratory. The method is, however, sufficiently general to be applicable in other thermal scattering materials, and can be initially validated with the continuous analytic free gas model.« less

Multi-pass Monte Carlo simulation method in nuclear transmutations.

PubMed

Mateescu, Liviu; Kadambi, N Prasad; Ravindra, Nuggehalli M

2016-12-01

Monte Carlo methods, in their direct brute simulation incarnation, bring realistic results if the involved probabilities, be they geometrical or otherwise, remain constant for the duration of the simulation. However, there are physical setups where the evolution of the simulation represents a modification of the simulated system itself. Chief among such evolving simulated systems are the activation/transmutation setups. That is, the simulation starts with a given set of probabilities, which are determined by the geometry of the system, the components and by the microscopic interaction cross-sections. However, the relative weight of the components of the system changes along with the steps of the simulation. A natural measure would be adjusting probabilities after every step of the simulation. On the other hand, the physical system has typically a number of components of the order of Avogadro's number, usually 10 25 or 10 26 members. A simulation step changes the characteristics for just a few of these members; a probability will therefore shift by a quantity of 1/10 25 . Such a change cannot be accounted for within a simulation, because then the simulation should have then a number of at least 10 28 steps in order to have some significance. This is not feasible, of course. For our computing devices, a simulation of one million steps is comfortable, but a further order of magnitude becomes too big a stretch for the computing resources. We propose here a method of dealing with the changing probabilities, leading to the increasing of the precision. This method is intended as a fast approximating approach, and also as a simple introduction (for the benefit of students) in the very branched subject of Monte Carlo simulations vis-à-vis nuclear reactors. Copyright © 2016 Elsevier Ltd. All rights reserved.

Calculation of the Curie temperature of Ni using first principles based Wang-Landau Monte-Carlo

NASA Astrophysics Data System (ADS)

Eisenbach, Markus; Yin, Junqi; Li, Ying Wai; Nicholson, Don

2015-03-01

We combine constrained first principles density functional with a Wang-Landau Monte Carlo algorithm to calculate the Curie temperature of Ni. Mapping the magnetic interactions in Ni onto a Heisenberg like model to underestimates the Curie temperature. Using a model we show that the addition of the magnitude of the local magnetic moments can account for the difference in the calculated Curie temperature. For ab initio calculations, we have extended our Locally Selfconsistent Multiple Scattering (LSMS) code to constrain the magnitude of the local moments in addition to their direction and apply the Replica Exchange Wang-Landau method to sample the larger phase space efficiently to investigate Ni where the fluctuation in the magnitude of the local magnetic moments is of importance equal to their directional fluctuations. We will present our results for Ni where we compare calculations that consider only the moment directions and those including fluctuations of the magnetic moment magnitude on the Curie temperature. This research was sponsored by the Department of Energy, Offices of Basic Energy Science and Advanced Computing. We used Oak Ridge Leadership Computing Facility resources at Oak Ridge National Laboratory, supported by US DOE under contract DE-AC05-00OR22725.

Learning of state-space models with highly informative observations: A tempered sequential Monte Carlo solution

NASA Astrophysics Data System (ADS)

Svensson, Andreas; Schön, Thomas B.; Lindsten, Fredrik

2018-05-01

Probabilistic (or Bayesian) modeling and learning offers interesting possibilities for systematic representation of uncertainty using probability theory. However, probabilistic learning often leads to computationally challenging problems. Some problems of this type that were previously intractable can now be solved on standard personal computers thanks to recent advances in Monte Carlo methods. In particular, for learning of unknown parameters in nonlinear state-space models, methods based on the particle filter (a Monte Carlo method) have proven very useful. A notoriously challenging problem, however, still occurs when the observations in the state-space model are highly informative, i.e. when there is very little or no measurement noise present, relative to the amount of process noise. The particle filter will then struggle in estimating one of the basic components for probabilistic learning, namely the likelihood p (data | parameters). To this end we suggest an algorithm which initially assumes that there is substantial amount of artificial measurement noise present. The variance of this noise is sequentially decreased in an adaptive fashion such that we, in the end, recover the original problem or possibly a very close approximation of it. The main component in our algorithm is a sequential Monte Carlo (SMC) sampler, which gives our proposed method a clear resemblance to the SMC2 method. Another natural link is also made to the ideas underlying the approximate Bayesian computation (ABC). We illustrate it with numerical examples, and in particular show promising results for a challenging Wiener-Hammerstein benchmark problem.

Calculation of out-of-field dose distribution in carbon-ion radiotherapy by Monte Carlo simulation.

PubMed

Yonai, Shunsuke; Matsufuji, Naruhiro; Namba, Masao

2012-08-01

Recent radiotherapy technologies including carbon-ion radiotherapy can improve the dose concentration in the target volume, thereby not only reducing side effects in organs at risk but also the secondary cancer risk within or near the irradiation field. However, secondary cancer risk in the low-dose region is considered to be non-negligible, especially for younger patients. To achieve a dose estimation of the whole body of each patient receiving carbon-ion radiotherapy, which is essential for risk assessment and epidemiological studies, Monte Carlo simulation plays an important role because the treatment planning system can provide dose distribution only in∕near the irradiation field and the measured data are limited. However, validation of Monte Carlo simulations is necessary. The primary purpose of this study was to establish a calculation method using the Monte Carlo code to estimate the dose and quality factor in the body and to validate the proposed method by comparison with experimental data. Furthermore, we show the distributions of dose equivalent in a phantom and identify the partial contribution of each radiation type. We proposed a calculation method based on a Monte Carlo simulation using the PHITS code to estimate absorbed dose, dose equivalent, and dose-averaged quality factor by using the Q(L)-L relationship based on the ICRP 60 recommendation. The values obtained by this method in modeling the passive beam line at the Heavy-Ion Medical Accelerator in Chiba were compared with our previously measured data. It was shown that our calculation model can estimate the measured value within a factor of 2, which included not only the uncertainty of this calculation method but also those regarding the assumptions of the geometrical modeling and the PHITS code. Also, we showed the differences in the doses and the partial contributions of each radiation type between passive and active carbon-ion beams using this calculation method. These results indicated that it is essentially important to include the dose by secondary neutrons in the assessment of the secondary cancer risk of patients receiving carbon-ion radiotherapy with active as well as passive beams. We established a calculation method with a Monte Carlo simulation to estimate the distribution of dose equivalent in the body as a first step toward routine risk assessment and an epidemiological study of carbon-ion radiotherapy at NIRS. This method has the advantage of being verifiable by the measurement.

Discrete Fractional Component Monte Carlo Simulation Study of Dilute Nonionic Surfactants at the Air-Water Interface.

PubMed

Yoo, Brian; Marin-Rimoldi, Eliseo; Mullen, Ryan Gotchy; Jusufi, Arben; Maginn, Edward J

2017-09-26

We present a newly developed Monte Carlo scheme to predict bulk surfactant concentrations and surface tensions at the air-water interface for various surfactant interfacial coverages. Since the concentration regimes of these systems of interest are typically very dilute (≪10 -5 mol. frac.), Monte Carlo simulations with the use of insertion/deletion moves can provide the ability to overcome finite system size limitations that often prohibit the use of modern molecular simulation techniques. In performing these simulations, we use the discrete fractional component Monte Carlo (DFCMC) method in the Gibbs ensemble framework, which allows us to separate the bulk and air-water interface into two separate boxes and efficiently swap tetraethylene glycol surfactants C 10 E 4 between boxes. Combining this move with preferential translations, volume biased insertions, and Wang-Landau biasing vastly enhances sampling and helps overcome the classical "insertion problem", often encountered in non-lattice Monte Carlo simulations. We demonstrate that this methodology is both consistent with the original molecular thermodynamic theory (MTT) of Blankschtein and co-workers, as well as their recently modified theory (MD/MTT), which incorporates the results of surfactant infinite dilution transfer free energies and surface tension calculations obtained from molecular dynamics simulations.

Free energy and phase equilibria for the restricted primitive model of ionic fluids from Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Orkoulas, Gerassimos; Panagiotopoulos, Athanassios Z.

1994-07-01

In this work, we investigate the liquid-vapor phase transition of the restricted primitive model of ionic fluids. We show that at the low temperatures where the phase transition occurs, the system cannot be studied by conventional molecular simulation methods because convergence to equilibrium is slow. To accelerate convergence, we propose cluster Monte Carlo moves capable of moving more than one particle at a time. We then address the issue of charged particle transfers in grand canonical and Gibbs ensemble Monte Carlo simulations, for which we propose a biased particle insertion/destruction scheme capable of sampling short interparticle distances. We compute the chemical potential for the restricted primitive model as a function of temperature and density from grand canonical Monte Carlo simulations and the phase envelope from Gibbs Monte Carlo simulations. Our calculated phase coexistence curve is in agreement with recent results of Caillol obtained on the four-dimensional hypersphere and our own earlier Gibbs ensemble simulations with single-ion transfers, with the exception of the critical temperature, which is lower in the current calculations. Our best estimates for the critical parameters are T*c=0.053, ρ*c=0.025. We conclude with possible future applications of the biased techniques developed here for phase equilibrium calculations for ionic fluids.

Applying Monte Carlo Simulation to Launch Vehicle Design and Requirements Analysis

NASA Technical Reports Server (NTRS)

Hanson, J. M.; Beard, B. B.

2010-01-01

This Technical Publication (TP) is meant to address a number of topics related to the application of Monte Carlo simulation to launch vehicle design and requirements analysis. Although the focus is on a launch vehicle application, the methods may be applied to other complex systems as well. The TP is organized so that all the important topics are covered in the main text, and detailed derivations are in the appendices. The TP first introduces Monte Carlo simulation and the major topics to be discussed, including discussion of the input distributions for Monte Carlo runs, testing the simulation, how many runs are necessary for verification of requirements, what to do if results are desired for events that happen only rarely, and postprocessing, including analyzing any failed runs, examples of useful output products, and statistical information for generating desired results from the output data. Topics in the appendices include some tables for requirements verification, derivation of the number of runs required and generation of output probabilistic data with consumer risk included, derivation of launch vehicle models to include possible variations of assembled vehicles, minimization of a consumable to achieve a two-dimensional statistical result, recontact probability during staging, ensuring duplicated Monte Carlo random variations, and importance sampling.

A Large-Particle Monte Carlo Code for Simulating Non-Linear High-Energy Processes Near Compact Objects

NASA Technical Reports Server (NTRS)

Stern, Boris E.; Svensson, Roland; Begelman, Mitchell C.; Sikora, Marek

1995-01-01

High-energy radiation processes in compact cosmic objects are often expected to have a strongly non-linear behavior. Such behavior is shown, for example, by electron-positron pair cascades and the time evolution of relativistic proton distributions in dense radiation fields. Three independent techniques have been developed to simulate these non-linear problems: the kinetic equation approach; the phase-space density (PSD) Monte Carlo method; and the large-particle (LP) Monte Carlo method. In this paper, we present the latest version of the LP method and compare it with the other methods. The efficiency of the method in treating geometrically complex problems is illustrated by showing results of simulations of 1D, 2D and 3D systems. The method is shown to be powerful enough to treat non-spherical geometries, including such effects as bulk motion of the background plasma, reflection of radiation from cold matter, and anisotropic distributions of radiating particles. It can therefore be applied to simulate high-energy processes in such astrophysical systems as accretion discs with coronae, relativistic jets, pulsar magnetospheres and gamma-ray bursts.

Direct Simulation Monte Carlo Investigation of Noncontinuum Couette Flow

NASA Astrophysics Data System (ADS)

Torczynski, J. R.; Gallis, M. A.

2009-11-01

The Direct Simulation Monte Carlo (DSMC) method of molecular gas dynamics is used to study noncontinuum effects in Couette flow. The walls have equal temperatures and equal accommodation coefficients but unequal tangential velocities. Simulations are performed for near-free-molecular to near-continuum gas pressures with accommodation coefficients of 0.25, 0.5, and 1. Ten gases are examined: argon, helium, nitrogen, sea-level air, and six Inverse-Power-Law (IPL) gases with viscosity temperature exponents of 0.5, 0.6, 0.7, 0.8, 0.9, and 1.0, as represented by the Variable Soft Sphere (VSS) interaction. In all cases, the wall shear stress is proportional to the slip velocity. The momentum transfer coefficient relating these two quantities can be accurately correlated in terms of the Knudsen number based on the wall separation. The two dimensionless parameters in the correlation are similar for all gases examined. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Leveraging Gibbs Ensemble Molecular Dynamics and Hybrid Monte Carlo/Molecular Dynamics for Efficient Study of Phase Equilibria.

PubMed

Gartner, Thomas E; Epps, Thomas H; Jayaraman, Arthi

2016-11-08

We describe an extension of the Gibbs ensemble molecular dynamics (GEMD) method for studying phase equilibria. Our modifications to GEMD allow for direct control over particle transfer between phases and improve the method's numerical stability. Additionally, we found that the modified GEMD approach had advantages in computational efficiency in comparison to a hybrid Monte Carlo (MC)/MD Gibbs ensemble scheme in the context of the single component Lennard-Jones fluid. We note that this increase in computational efficiency does not compromise the close agreement of phase equilibrium results between the two methods. However, numerical instabilities in the GEMD scheme hamper GEMD's use near the critical point. We propose that the computationally efficient GEMD simulations can be used to map out the majority of the phase window, with hybrid MC/MD used as a follow up for conditions under which GEMD may be unstable (e.g., near-critical behavior). In this manner, we can capitalize on the contrasting strengths of these two methods to enable the efficient study of phase equilibria for systems that present challenges for a purely stochastic GEMC method, such as dense or low temperature systems, and/or those with complex molecular topologies.

Monte Carlo renormalization-group study of the Baxter-Wu model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Novotny, M.A.; Landau, D.P.; Swendsen, R.H.

1982-07-01

The effectiveness of a Monte Carlo renormalization-group method is studied by applying it to the Baxter-Wu model (Ising spins on a triangular lattice with three-spin interactions). The calculations yield three relevent eigenvalues in good agreement with exact or conjectured results. We demonstrate that the method is capable of distinguishing between models expected to be in the same universality class, when one of them (four-state Potts) exhibits logarithmic corrections to the usual power-law singularities and the other (Baxter-Wu) does not.

Using the Monte Carlo method for assessing the tissue and organ doses of patients in dental radiography

NASA Astrophysics Data System (ADS)

Makarevich, K. O.; Minenko, V. F.; Verenich, K. A.; Kuten, S. A.

2016-05-01

This work is dedicated to modeling dental radiographic examinations to assess the absorbed doses of patients and effective doses. For simulating X-ray spectra, the TASMIP empirical model is used. Doses are assessed on the basis of the Monte Carlo method by using MCNP code for voxel phantoms of ICRP. The results of the assessment of doses to individual organs and effective doses for different types of dental examinations and features of X-ray tube are presented.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kalugin, A. V., E-mail: Kalugin-AV@nrcki.ru; Tebin, V. V.

The specific features of calculation of the effective multiplication factor using the Monte Carlo method for weakly coupled and non-asymptotic multiplying systems are discussed. Particular examples are considered and practical recommendations on detection and Monte Carlo calculation of systems typical in numerical substantiation of nuclear safety for VVER fuel management problems are given. In particular, the problems of the choice of parameters for the batch mode and the method for normalization of the neutron batch, as well as finding and interpretation of the eigenvalue spectrum for the integral fission matrix, are discussed.

KMCThinFilm: A C++ Framework for the Rapid Development of Lattice Kinetic Monte Carlo (kMC) Simulations of Thin Film Growth

DTIC Science & Technology

2015-09-01

direction, so if the simulation domain is set to be a certain size, then that presents a hard ceiling on the thickness of a film that may be grown in...FFA, Los J, Cuppen HM, Bennema P, Meekes H. MONTY:  Monte Carlo crystal growth on any crystal structure in any crystallographic orientation...mhoffman.github.io/kmos/. 23. Kiravittaya S, Schmidt OG. Quantum-dot crystal defects. Applied Physics Letters. 2008;93:173109. 24. Leetmaa M

SU-E-T-586: Field Size Dependence of Output Factor for Uniform Scanning Proton Beams: A Comparison of TPS Calculation, Measurement and Monte Carlo Simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zheng, Y; Singh, H; Islam, M

2014-06-01

Purpose: Output dependence on field size for uniform scanning beams, and the accuracy of treatment planning system (TPS) calculation are not well studied. The purpose of this work is to investigate the dependence of output on field size for uniform scanning beams and compare it among TPS calculation, measurements and Monte Carlo simulations. Methods: Field size dependence was studied using various field sizes between 2.5 cm diameter to 10 cm diameter. The field size factor was studied for a number of proton range and modulation combinations based on output at the center of spread out Bragg peak normalized to amore » 10 cm diameter field. Three methods were used and compared in this study: 1) TPS calculation, 2) ionization chamber measurement, and 3) Monte Carlos simulation. The XiO TPS (Electa, St. Louis) was used to calculate the output factor using a pencil beam algorithm; a pinpoint ionization chamber was used for measurements; and the Fluka code was used for Monte Carlo simulations. Results: The field size factor varied with proton beam parameters, such as range, modulation, and calibration depth, and could decrease over 10% from a 10 cm to 3 cm diameter field for a large range proton beam. The XiO TPS predicted the field size factor relatively well at large field size, but could differ from measurements by 5% or more for small field and large range beams. Monte Carlo simulations predicted the field size factor within 1.5% of measurements. Conclusion: Output factor can vary largely with field size, and needs to be accounted for accurate proton beam delivery. This is especially important for small field beams such as in stereotactic proton therapy, where the field size dependence is large and TPS calculation is inaccurate. Measurements or Monte Carlo simulations are recommended for output determination for such cases.« less

Direct Simulation Monte Carlo Application of the Three Dimensional Forced Harmonic Oscillator Model

DTIC Science & Technology

2017-12-07

quasi -classical scattering theory [3,4] or trajectory [5] calculations, semiclassical, as well as close-coupled [6,7] or full [8] quantum mechanical...the quasi -classical trajectory (QCT) calculations approach for ab initio modeling of collision processes. The DMS method builds on an earlier work...nu ar y 30 , 2 01 8 | h ttp :// ar c. ai aa .o rg | D O I: 1 0. 25 14 /1 .T 52 28 to directly use quasi -classical or quantum mechanic

PyMercury: Interactive Python for the Mercury Monte Carlo Particle Transport Code

DOE Office of Scientific and Technical Information (OSTI.GOV)

Iandola, F N; O'Brien, M J; Procassini, R J

2010-11-29

Monte Carlo particle transport applications are often written in low-level languages (C/C++) for optimal performance on clusters and supercomputers. However, this development approach often sacrifices straightforward usability and testing in the interest of fast application performance. To improve usability, some high-performance computing applications employ mixed-language programming with high-level and low-level languages. In this study, we consider the benefits of incorporating an interactive Python interface into a Monte Carlo application. With PyMercury, a new Python extension to the Mercury general-purpose Monte Carlo particle transport code, we improve application usability without diminishing performance. In two case studies, we illustrate how PyMercury improvesmore » usability and simplifies testing and validation in a Monte Carlo application. In short, PyMercury demonstrates the value of interactive Python for Monte Carlo particle transport applications. In the future, we expect interactive Python to play an increasingly significant role in Monte Carlo usage and testing.« less

Latin hypercube sampling and geostatistical modeling of spatial uncertainty in a spatially explicit forest landscape model simulation

Treesearch

Chonggang Xu; Hong S. He; Yuanman Hu; Yu Chang; Xiuzhen Li; Rencang Bu

2005-01-01

Geostatistical stochastic simulation is always combined with Monte Carlo method to quantify the uncertainty in spatial model simulations. However, due to the relatively long running time of spatially explicit forest models as a result of their complexity, it is always infeasible to generate hundreds or thousands of Monte Carlo simulations. Thus, it is of great...

Accurate Theoretical Predictions of the Properties of Energetic Materials

DTIC Science & Technology

2008-09-18

decomposition, Monte Carlo, molecular dynamics, supercritical fluids, solvation and separation, quantum Monte Carlo, potential energy surfaces, RDX , TNAZ...labs, who are contributing to the theoretical efforts, providing data for testing of the models, or aiding in the transition of the methods, models...and results to DoD applications. The major goals of the project are: • Models that describe phase transitions and chemical reactions in

McStas 1.1: a tool for building neutron Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Lefmann, K.; Nielsen, K.; Tennant, A.; Lake, B.

2000-03-01

McStas is a project to develop general tools for the creation of simulations of neutron scattering experiments. In this paper, we briefly introduce McStas and describe a particular application of the program: the Monte Carlo calculation of the resolution function of a standard triple-axis neutron scattering instrument. The method compares well with the analytical calculations of Popovici.

Quantitative analysis of optical properties of flowing blood using a photon-cell interactive Monte Carlo code: effects of red blood cells' orientation on light scattering.

PubMed

Sakota, Daisuke; Takatani, Setsuo

2012-05-01

Optical properties of flowing blood were analyzed using a photon-cell interactive Monte Carlo (pciMC) model with the physical properties of the flowing red blood cells (RBCs) such as cell size, shape, refractive index, distribution, and orientation as the parameters. The scattering of light by flowing blood at the He-Ne laser wavelength of 632.8 nm was significantly affected by the shear rate. The light was scattered more in the direction of flow as the flow rate increased. Therefore, the light intensity transmitted forward in the direction perpendicular to flow axis decreased. The pciMC model can duplicate the changes in the photon propagation due to moving RBCs with various orientations. The resulting RBC's orientation that best simulated the experimental results was with their long axis perpendicular to the direction of blood flow. Moreover, the scattering probability was dependent on the orientation of the RBCs. Finally, the pciMC code was used to predict the hematocrit of flowing blood with accuracy of approximately 1.0 HCT%. The photon-cell interactive Monte Carlo (pciMC) model can provide optical properties of flowing blood and will facilitate the development of the non-invasive monitoring of blood in extra corporeal circulatory systems.

Feasibility of antihydrogen atom containment in helium: a problem of electron-positron correlation investigated by the Monte Carol method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jackman, T.M.

1987-01-01

A theoretical investigation of the interaction potential between the helium atom and the antihydrogen atom was performed for the purpose of determining the feasibility of antihydrogen atom containment. The interaction potential showed an energy barrier to collapse of this system. A variational estimate of the height of this energy barrier and estimates of lifetime with respect to electron-positron annihilation were determined by the Variational Monte Carlo method. This calculation allowed for an improvement over an SCF result through the inclusion of explicit correlation factors in the trial wave function. An estimate of the correlation energy of this system was determinedmore » by the Green's Function Monte Carlo (GFMC) method.« less

Intrinsic fluorescence of protein in turbid media using empirical relation based on Monte Carlo lookup table

NASA Astrophysics Data System (ADS)

Einstein, Gnanatheepam; Udayakumar, Kanniyappan; Aruna, Prakasarao; Ganesan, Singaravelu

2017-03-01

Fluorescence of Protein has been widely used in diagnostic oncology for characterizing cellular metabolism. However, the intensity of fluorescence emission is affected due to the absorbers and scatterers in tissue, which may lead to error in estimating exact protein content in tissue. Extraction of intrinsic fluorescence from measured fluorescence has been achieved by different methods. Among them, Monte Carlo based method yields the highest accuracy for extracting intrinsic fluorescence. In this work, we have attempted to generate a lookup table for Monte Carlo simulation of fluorescence emission by protein. Furthermore, we fitted the generated lookup table using an empirical relation. The empirical relation between measured and intrinsic fluorescence is validated using tissue phantom experiments. The proposed relation can be used for estimating intrinsic fluorescence of protein for real-time diagnostic applications and thereby improving the clinical interpretation of fluorescence spectroscopic data.

A comparison of maximum likelihood and other estimators of eigenvalues from several correlated Monte Carlo samples

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beer, M.

1980-12-01

The maximum likelihood method for the multivariate normal distribution is applied to the case of several individual eigenvalues. Correlated Monte Carlo estimates of the eigenvalue are assumed to follow this prescription and aspects of the assumption are examined. Monte Carlo cell calculations using the SAM-CE and VIM codes for the TRX-1 and TRX-2 benchmark reactors, and SAM-CE full core results are analyzed with this method. Variance reductions of a few percent to a factor of 2 are obtained from maximum likelihood estimation as compared with the simple average and the minimum variance individual eigenvalue. The numerical results verify that themore » use of sample variances and correlation coefficients in place of the corresponding population statistics still leads to nearly minimum variance estimation for a sufficient number of histories and aggregates.« less

Multilevel Monte Carlo for two phase flow and Buckley–Leverett transport in random heterogeneous porous media

DOE Office of Scientific and Technical Information (OSTI.GOV)

Müller, Florian, E-mail: florian.mueller@sam.math.ethz.ch; Jenny, Patrick, E-mail: jenny@ifd.mavt.ethz.ch; Meyer, Daniel W., E-mail: meyerda@ethz.ch

2013-10-01

Monte Carlo (MC) is a well known method for quantifying uncertainty arising for example in subsurface flow problems. Although robust and easy to implement, MC suffers from slow convergence. Extending MC by means of multigrid techniques yields the multilevel Monte Carlo (MLMC) method. MLMC has proven to greatly accelerate MC for several applications including stochastic ordinary differential equations in finance, elliptic stochastic partial differential equations and also hyperbolic problems. In this study, MLMC is combined with a streamline-based solver to assess uncertain two phase flow and Buckley–Leverett transport in random heterogeneous porous media. The performance of MLMC is compared tomore » MC for a two dimensional reservoir with a multi-point Gaussian logarithmic permeability field. The influence of the variance and the correlation length of the logarithmic permeability on the MLMC performance is studied.« less

McSnow: A Monte-Carlo Particle Model for Riming and Aggregation of Ice Particles in a Multidimensional Microphysical Phase Space

NASA Astrophysics Data System (ADS)

Brdar, S.; Seifert, A.

2018-01-01

We present a novel Monte-Carlo ice microphysics model, McSnow, to simulate the evolution of ice particles due to deposition, aggregation, riming, and sedimentation. The model is an application and extension of the super-droplet method of Shima et al. (2009) to the more complex problem of rimed ice particles and aggregates. For each individual super-particle, the ice mass, rime mass, rime volume, and the number of monomers are predicted establishing a four-dimensional particle-size distribution. The sensitivity of the model to various assumptions is discussed based on box model and one-dimensional simulations. We show that the Monte-Carlo method provides a feasible approach to tackle this high-dimensional problem. The largest uncertainty seems to be related to the treatment of the riming processes. This calls for additional field and laboratory measurements of partially rimed snowflakes.

Simulation of radiation damping in rings, using stepwise ray-tracing methods

DOE PAGES

Meot, F.

2015-06-26

The ray-tracing code Zgoubi computes particle trajectories in arbitrary magnetic and/or electric field maps or analytical field models. It includes a built-in fitting procedure, spin tracking many Monte Carlo processes. The accuracy of the integration method makes it an efficient tool for multi-turn tracking in periodic machines. Energy loss by synchrotron radiation, based on Monte Carlo techniques, had been introduced in Zgoubi in the early 2000s for studies regarding the linear collider beam delivery system. However, only recently has this Monte Carlo tool been used for systematic beam dynamics and spin diffusion studies in rings, including eRHIC electron-ion collider projectmore » at the Brookhaven National Laboratory. Some beam dynamics aspects of this recent use of Zgoubi capabilities, including considerations of accuracy as well as further benchmarking in the presence of synchrotron radiation in rings, are reported here.« less

Monte Carlo method for computing density of states and quench probability of potential energy and enthalpy landscapes.

PubMed

Mauro, John C; Loucks, Roger J; Balakrishnan, Jitendra; Raghavan, Srikanth

2007-05-21

The thermodynamics and kinetics of a many-body system can be described in terms of a potential energy landscape in multidimensional configuration space. The partition function of such a landscape can be written in terms of a density of states, which can be computed using a variety of Monte Carlo techniques. In this paper, a new self-consistent Monte Carlo method for computing density of states is described that uses importance sampling and a multiplicative update factor to achieve rapid convergence. The technique is then applied to compute the equilibrium quench probability of the various inherent structures (minima) in the landscape. The quench probability depends on both the potential energy of the inherent structure and the volume of its corresponding basin in configuration space. Finally, the methodology is extended to the isothermal-isobaric ensemble in order to compute inherent structure quench probabilities in an enthalpy landscape.

Study of optical and electronic properties of nickel from reflection electron energy loss spectra

NASA Astrophysics Data System (ADS)

Xu, H.; Yang, L. H.; Da, B.; Tóth, J.; Tőkési, K.; Ding, Z. J.

2017-09-01

We use the classical Monte Carlo transport model of electrons moving near the surface and inside solids to reproduce the measured reflection electron energy-loss spectroscopy (REELS) spectra. With the combination of the classical transport model and the Markov chain Monte Carlo (MCMC) sampling of oscillator parameters the so-called reverse Monte Carlo (RMC) method was developed, and used to obtain optical constants of Ni in this work. A systematic study of the electronic and optical properties of Ni has been performed in an energy loss range of 0-200 eV from the measured REELS spectra at primary energies of 1000 eV, 2000 eV and 3000 eV. The reliability of our method was tested by comparing our results with the previous data. Moreover, the accuracy of our optical data has been confirmed by applying oscillator strength-sum rule and perfect-screening-sum rule.

The difference between LSMC and replicating portfolio in insurance liability modeling.

PubMed

Pelsser, Antoon; Schweizer, Janina

2016-01-01

Solvency II requires insurers to calculate the 1-year value at risk of their balance sheet. This involves the valuation of the balance sheet in 1 year's time. As for insurance liabilities, closed-form solutions to their value are generally not available, insurers turn to estimation procedures. While pure Monte Carlo simulation set-ups are theoretically sound, they are often infeasible in practice. Therefore, approximation methods are exploited. Among these, least squares Monte Carlo (LSMC) and portfolio replication are prominent and widely applied in practice. In this paper, we show that, while both are variants of regression-based Monte Carlo methods, they differ in one significant aspect. While the replicating portfolio approach only contains an approximation error, which converges to zero in the limit, in LSMC a projection error is additionally present, which cannot be eliminated. It is revealed that the replicating portfolio technique enjoys numerous advantages and is therefore an attractive model choice.