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.

Extension of the Viscous Collision Limiting Direct Simulation Monte Carlo Technique to Multiple Species

NASA Technical Reports Server (NTRS)

Liechty, Derek S.; Burt, Jonathan M.

2016-01-01

There are many flows fields that span a wide range of length scales where regions of both rarefied and continuum flow exist and neither direct simulation Monte Carlo (DSMC) nor computational fluid dynamics (CFD) provide the appropriate solution everywhere. Recently, a new viscous collision limited (VCL) DSMC technique was proposed to incorporate effects of physical diffusion into collision limiter calculations to make the low Knudsen number regime normally limited to CFD more tractable for an all-particle technique. This original work had been derived for a single species gas. The current work extends the VCL-DSMC technique to gases with multiple species. Similar derivations were performed to equate numerical and physical transport coefficients. However, a more rigorous treatment of determining the mixture viscosity is applied. In the original work, consideration was given to internal energy non-equilibrium, and this is also extended in the current work to chemical non-equilibrium.

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.

An ab initio chemical reaction model for the direct simulation Monte Carlo study of non-equilibrium nitrogen flows.

PubMed

Mankodi, T K; Bhandarkar, U V; Puranik, B P

2017-08-28

A new ab initio based chemical model for a Direct Simulation Monte Carlo (DSMC) study suitable for simulating rarefied flows with a high degree of non-equilibrium is presented. To this end, Collision Induced Dissociation (CID) cross sections for N 2 +N 2 →N 2 +2N are calculated and published using a global complete active space self-consistent field-complete active space second order perturbation theory N 4 potential energy surface and quasi-classical trajectory algorithm for high energy collisions (up to 30 eV). CID cross sections are calculated for only a selected set of ro-vibrational combinations of the two nitrogen molecules, and a fitting scheme based on spectroscopic weights is presented to interpolate the CID cross section for all possible ro-vibrational combinations. The new chemical model is validated by calculating equilibrium reaction rate coefficients that can be compared well with existing shock tube and computational results. High-enthalpy hypersonic nitrogen flows around a cylinder in the transition flow regime are simulated using DSMC to compare the predictions of the current ab initio based chemical model with the prevailing phenomenological model (the total collision energy model). The differences in the predictions are discussed.

Vectorization of a particle code used in the simulation of rarefied hypersonic flow

NASA Technical Reports Server (NTRS)

Baganoff, D.

1990-01-01

A limitation of the direct simulation Monte Carlo (DSMC) method is that it does not allow efficient use of vector architectures that predominate in current supercomputers. Consequently, the problems that can be handled are limited to those of one- and two-dimensional flows. This work focuses on a reformulation of the DSMC method with the objective of designing a procedure that is optimized to the vector architectures found on machines such as the Cray-2. In addition, it focuses on finding a better balance between algorithmic complexity and the total number of particles employed in a simulation so that the overall performance of a particle simulation scheme can be greatly improved. Simulations of the flow about a 3D blunt body are performed with 10 to the 7th particles and 4 x 10 to the 5th mesh cells. Good statistics are obtained with time averaging over 800 time steps using 4.5 h of Cray-2 single-processor CPU time.

DSMC simulation of the interaction between rarefied free jets

NASA Technical Reports Server (NTRS)

Dagum, Leonardo; Zhu, S. H. K.

1993-01-01

This paper presents a direct simulation Monte Carlo (DSMC) calculation of two interacting free jets exhausting into vacuum. The computed flow field is compared against available experimental data and shows excellent agreement everywhere except in the very near field (less than one orifice diameter downstream of the jet exhaust plane). The lack of agreement in this region is attributed to having assumed an inviscid boundary condition for the orifice lip. The results serve both to validate the DSMC code for a very complex, three dimensional non-equilibrium flow field, and to provide some insight as to the complicated nature of this flow.

A 3-D Coupled CFD-DSMC Solution Method With Application to the Mars Sample Return Orbiter

NASA Technical Reports Server (NTRS)

Glass, Christopher E.; Gnoffo, Peter A.

2000-01-01

A method to obtain coupled Computational Fluid Dynamics-Direct Simulation Monte Carlo (CFD-DSMC), 3-D flow field solutions for highly blunt bodies at low incidence is presented and applied to one concept of the Mars Sample Return Orbiter vehicle as a demonstration of the technique. CFD is used to solve the high-density blunt forebody flow defining an inflow boundary condition for a DSMC solution of the afterbody wake flow. By combining the two techniques in flow regions where most applicable, the entire mixed flow field is modeled in an appropriate manner.

Validation of DSMC results for chemically nonequilibrium air flows against measurements of the electron number density in RAM-C II flight experiment

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

Shevyrin, Alexander A.; Vashchenkov, Pavel V.; Bondar, Yevgeniy A.

An ionized flow around the RAM C-II vehicle in the range of altitudes from 73 to 81 km is studied by the Direct Simulation Monte Carlo (DSMC) method with three models of chemical reactions. It is demonstrated that vibration favoring in reactions of dissociation of neutral molecules affects significantly the predicted values of plasma density in the shock layer, and good agreement between the results of experiments and DSMC computations can be achieved in terms of the plasma density as a function of the flight altitude.

DSMC Simulation and Experimental Validation of Shock Interaction in Hypersonic Low Density Flow

PubMed Central

2014-01-01

Direct simulation Monte Carlo (DSMC) of shock interaction in hypersonic low density flow is developed. Three collision molecular models, including hard sphere (HS), variable hard sphere (VHS), and variable soft sphere (VSS), are employed in the DSMC study. The simulations of double-cone and Edney's type IV hypersonic shock interactions in low density flow are performed. Comparisons between DSMC and experimental data are conducted. Investigation of the double-cone hypersonic flow shows that three collision molecular models can predict the trend of pressure coefficient and the Stanton number. HS model shows the best agreement between DSMC simulation and experiment among three collision molecular models. Also, it shows that the agreement between DSMC and experiment is generally good for HS and VHS models in Edney's type IV shock interaction. However, it fails in the VSS model. Both double-cone and Edney's type IV shock interaction simulations show that the DSMC errors depend on the Knudsen number and the models employed for intermolecular interaction. With the increase in the Knudsen number, the DSMC error is decreased. The error is the smallest in HS compared with those in the VHS and VSS models. When the Knudsen number is in the level of 10−4, the DSMC errors, for pressure coefficient, the Stanton number, and the scale of interaction region, are controlled within 10%. PMID:24672360

DSMC Shock Simulation of Saturn Entry Probe Conditions

NASA Technical Reports Server (NTRS)

Higdon, Kyle J.; Cruden, Brett A.; Brandis, Aaron; Liechty, Derek S.; Goldstein, David B.; Varghese, Philip L.

2016-01-01

This work describes the direct simulation Monte Carlo (DSMC) investigation of Saturn entry probe scenarios and the influence of non-equilibrium phenomena on Saturn entry conditions. The DSMC simulations coincide with rarefied hypersonic shock tube experiments of a hydrogen-helium mixture performed in the Electric Arc Shock Tube (EAST) at NASA Ames Research Center. The DSMC simulations are post-processed through the NEQAIR line-by-line radiation code to compare directly to the experimental results. Improved collision cross-sections, inelastic collision parameters, and reaction rates are determined for a high temperature DSMC simulation of a 7-species H2-He mixture and an electronic excitation model is implemented in the DSMC code. Simulation results for 27.8 and 27.4 kms shock waves are obtained at 0.2 and 0.1 Torr respectively and compared to measured spectra in the VUV, UV, visible, and IR ranges. These results confirm the persistence of non-equilibrium for several centimeters behind the shock and the diffusion of atomic hydrogen upstream of the shock wave. Although the magnitude of the radiance did not match experiments and an ionization inductance period was not observed in the simulations, the discrepancies indicated where improvements are needed in the DSMC and NEQAIR models.

DSMC Shock Simulation of Saturn Entry Probe Conditions

NASA Technical Reports Server (NTRS)

Higdon, Kyle J.; Cruden, Brett A.; Brandis, Aaron M.; Liechty, Derek S.; Goldstein, David B.; Varghese, Philip L.

2016-01-01

This work describes the direct simulation Monte Carlo (DSMC) investigation of Saturn entry probe scenarios and the influence of non-equilibrium phenomena on Saturn entry conditions. The DSMC simulations coincide with rarefied hypersonic shock tube experiments of a hydrogen-helium mixture performed in the Electric Arc Shock Tube (EAST) at the NASA Ames Research Center. The DSMC simulations are post-processed through the NEQAIR line-by-line radiation code to compare directly to the experimental results. Improved collision cross-sections, inelastic collision parameters, and reaction rates are determined for a high temperature DSMC simulation of a 7-species H2-He mixture and an electronic excitation model is implemented in the DSMC code. Simulation results for 27.8 and 27.4 km/s shock waves are obtained at 0.2 and 0.1 Torr, respectively, and compared to measured spectra in the VUV, UV, visible, and IR ranges. These results confirm the persistence of non-equilibrium for several centimeters behind the shock and the diffusion of atomic hydrogen upstream of the shock wave. Although the magnitude of the radiance did not match experiments and an ionization inductance period was not observed in the simulations, the discrepancies indicated where improvements are needed in the DSMC and NEQAIR models.

State resolved vibrational relaxation modeling for strongly nonequilibrium flows

NASA Astrophysics Data System (ADS)

Boyd, Iain D.; Josyula, Eswar

2011-05-01

Vibrational relaxation is an important physical process in hypersonic flows. Activation of the vibrational mode affects the fundamental thermodynamic properties and finite rate relaxation can reduce the degree of dissociation of a gas. Low fidelity models of vibrational activation employ a relaxation time to capture the process at a macroscopic level. High fidelity, state-resolved models have been developed for use in continuum gas dynamics simulations based on computational fluid dynamics (CFD). By comparison, such models are not as common for use with the direct simulation Monte Carlo (DSMC) method. In this study, a high fidelity, state-resolved vibrational relaxation model is developed for the DSMC technique. The model is based on the forced harmonic oscillator approach in which multi-quantum transitions may become dominant at high temperature. Results obtained for integrated rate coefficients from the DSMC model are consistent with the corresponding CFD model. Comparison of relaxation results obtained with the high-fidelity DSMC model shows significantly less excitation of upper vibrational levels in comparison to the standard, lower fidelity DSMC vibrational relaxation model. Application of the new DSMC model to a Mach 7 normal shock wave in carbon monoxide provides better agreement with experimental measurements than the standard DSMC relaxation model.

Particle behavior simulation in thermophoresis phenomena by direct simulation Monte Carlo method

NASA Astrophysics Data System (ADS)

Wada, Takao

2014-07-01

A particle motion considering thermophoretic force is simulated by using direct simulation Monte Carlo (DSMC) method. Thermophoresis phenomena, which occur for a particle size of 1 μm, are treated in this paper. The problem of thermophoresis simulation is computation time which is proportional to the collision frequency. Note that the time step interval becomes much small for the simulation considering the motion of large size particle. Thermophoretic forces calculated by DSMC method were reported, but the particle motion was not computed because of the small time step interval. In this paper, the molecule-particle collision model, which computes the collision between a particle and multi molecules in a collision event, is considered. The momentum transfer to the particle is computed with a collision weight factor, where the collision weight factor means the number of molecules colliding with a particle in a collision event. The large time step interval is adopted by considering the collision weight factor. Furthermore, the large time step interval is about million times longer than the conventional time step interval of the DSMC method when a particle size is 1 μm. Therefore, the computation time becomes about one-millionth. We simulate the graphite particle motion considering thermophoretic force by DSMC-Neutrals (Particle-PLUS neutral module) with above the collision weight factor, where DSMC-Neutrals is commercial software adopting DSMC method. The size and the shape of the particle are 1 μm and a sphere, respectively. The particle-particle collision is ignored. We compute the thermophoretic forces in Ar and H2 gases of a pressure range from 0.1 to 100 mTorr. The results agree well with Gallis' analytical results. Note that Gallis' analytical result for continuum limit is the same as Waldmann's result.

FDDO and DSMC analyses of rarefied gas flow through 2D nozzles

NASA Technical Reports Server (NTRS)

Chung, Chan-Hong; De Witt, Kenneth J.; Jeng, Duen-Ren; Penko, Paul F.

1992-01-01

Two different approaches, the finite-difference method coupled with the discrete-ordinate method (FDDO), and the direct-simulation Monte Carlo (DSMC) method, are used in the analysis of the flow of a rarefied gas expanding through a two-dimensional nozzle and into a surrounding low-density environment. In the FDDO analysis, by employing the discrete-ordinate method, the Boltzmann equation simplified by a model collision integral is transformed to a set of partial differential equations which are continuous in physical space but are point functions in molecular velocity space. The set of partial differential equations are solved by means of a finite-difference approximation. In the DSMC analysis, the variable hard sphere model is used as a molecular model and the no time counter method is employed as a collision sampling technique. The results of both the FDDO and the DSMC methods show good agreement. The FDDO method requires less computational effort than the DSMC method by factors of 10 to 40 in CPU time, depending on the degree of rarefaction.

DSMC Studies of the Richtmyer-Meshkov Instability

NASA Astrophysics Data System (ADS)

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

2014-11-01

A new exascale-capable Direct Simulation Monte Carlo (DSMC) code, SPARTA, developed to be highly efficient on massively parallel computers, has extended the applicability of DSMC to challenging, transient three-dimensional problems in the continuum regime. Because DSMC inherently accounts for compressibility, viscosity, and diffusivity, it has the potential to improve the understanding of the mechanisms responsible for hydrodynamic instabilities. Here, the Richtmyer-Meshkov instability at the interface between two gases was studied parametrically using SPARTA. Simulations performed on Sequoia, an IBM Blue Gene/Q supercomputer at Lawrence Livermore National Laboratory, are used to investigate various Atwood numbers (0.33-0.94) and Mach numbers (1.2-12.0) for two-dimensional and three-dimensional perturbations. Comparisons with theoretical predictions demonstrate that DSMC accurately predicts the early-time growth of the instability. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Implementation of a vibrationally linked chemical reaction model for DSMC

NASA Technical Reports Server (NTRS)

Carlson, A. B.; Bird, Graeme A.

1994-01-01

A new procedure closely linking dissociation and exchange reactions in air to the vibrational levels of the diatomic molecules has been implemented in both one- and two-dimensional versions of Direct Simulation Monte Carlo (DSMC) programs. The previous modeling of chemical reactions with DSMC was based on the continuum reaction rates for the various possible reactions. The new method is more closely related to the actual physics of dissociation and is more appropriate to the particle nature of DSMC. Two cases are presented: the relaxation to equilibrium of undissociated air initially at 10,000 K, and the axisymmetric calculation of shuttle forebody heating during reentry at 92.35 km and 7500 m/s. Although reaction rates are not used in determining the dissociations or exchange reactions, the new method produces rates which agree astonishingly well with the published rates derived from experiment. The results for gas properties and surface properties also agree well with the results produced by earlier DSMC models, equilibrium air calculations, and experiment.

Experimental validation of a direct simulation by Monte Carlo molecular gas flow model

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

Shufflebotham, P.K.; Bartel, T.J.; Berney, B.

1995-07-01

The Sandia direct simulation Monte Carlo (DSMC) molecular/transition gas flow simulation code has significant potential as a computer-aided design tool for the design of vacuum systems in low pressure plasma processing equipment. The purpose of this work was to verify the accuracy of this code through direct comparison to experiment. To test the DSMC model, a fully instrumented, axisymmetric vacuum test cell was constructed, and spatially resolved pressure measurements made in N{sub 2} at flows from 50 to 500 sccm. In a ``blind`` test, the DSMC code was used to model the experimental conditions directly, and the results compared tomore » the measurements. It was found that the model predicted all the experimental findings to a high degree of accuracy. Only one modeling issue was uncovered. The axisymmetric model showed localized low pressure spots along the axis next to surfaces. Although this artifact did not significantly alter the accuracy of the results, it did add noise to the axial data. {copyright} {ital 1995} {ital American} {ital Vacuum} {ital Society}« 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.

Nonequilibrium Hypersonic Aerothermodynamics Using the Direct Simulation Monte Carlo And Navier-Stokes Models

DTIC Science & Technology

2008-01-17

15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT UU 18 . NUMBER OF PAGES 261 19a. NAME OF RESPONSIBLE PERSON a...REPORT unclassified b. ABSTRACT unclassified c. THIS PAGE unclassified Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39- 18 This material...Sciences Meeting and Exhibit. Several DSMC [13, 58] and CFD [ 18 , 28, 43] solutions were submitted. Later, others compared CFD and DSMC solutions to these

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.

Some Developments of the Equilibrium Particle Simulation Method for the Direct Simulation of Compressible Flows

NASA Technical Reports Server (NTRS)

Macrossan, M. N.

1995-01-01

The direct simulation Monte Carlo (DSMC) method is the established technique for the simulation of rarefied gas flows. In some flows of engineering interest, such as occur for aero-braking spacecraft in the upper atmosphere, DSMC can become prohibitively expensive in CPU time because some regions of the flow, particularly on the windward side of blunt bodies, become collision dominated. As an alternative to using a hybrid DSMC and continuum gas solver (Euler or Navier-Stokes solver) this work is aimed at making the particle simulation method efficient in the high density regions of the flow. A high density, infinite collision rate limit of DSMC, the Equilibrium Particle Simulation method (EPSM) was proposed some 15 years ago. EPSM is developed here for the flow of a gas consisting of many different species of molecules and is shown to be computationally efficient (compared to DSMC) for high collision rate flows. It thus offers great potential as part of a hybrid DSMC/EPSM code which could handle flows in the transition regime between rarefied gas flows and fully continuum flows. As a first step towards this goal a pure EPSM code is described. The next step of combining DSMC and EPSM is not attempted here but should be straightforward. EPSM and DSMC are applied to Taylor-Couette flow with Kn = 0.02 and 0.0133 and S(omega) = 3). Toroidal vortices develop for both methods but some differences are found, as might be expected for the given flow conditions. EPSM appears to be less sensitive to the sequence of random numbers used in the simulation than is DSMC and may also be more dissipative. The question of the origin and the magnitude of the dissipation in EPSM is addressed. It is suggested that this analysis is also relevant to DSMC when the usual accuracy requirements on the cell size and decoupling time step are relaxed in the interests of computational efficiency.

Application of a Modular Particle-Continuum Method to Partially Rarefied, Hypersonic Flow

NASA Astrophysics Data System (ADS)

Deschenes, Timothy R.; Boyd, Iain D.

2011-05-01

The Modular Particle-Continuum (MPC) method is used to simulate partially-rarefied, hypersonic flow over a sting-mounted planetary probe configuration. This hybrid method uses computational fluid dynamics (CFD) to solve the Navier-Stokes equations in regions that are continuum, while using direct simulation Monte Carlo (DSMC) in portions of the flow that are rarefied. The MPC method uses state-based coupling to pass information between the two flow solvers and decouples both time-step and mesh densities required by each solver. It is parallelized for distributed memory systems using dynamic domain decomposition and internal energy modes can be consistently modeled to be out of equilibrium with the translational mode in both solvers. The MPC results are compared to both full DSMC and CFD predictions and available experimental measurements. By using DSMC in only regions where the flow is nonequilibrium, the MPC method is able to reproduce full DSMC results down to the level of velocity and rotational energy probability density functions while requiring a fraction of the computational time.

Pressure measurements in a low-density nozzle plume for code verification

NASA Technical Reports Server (NTRS)

Penko, Paul F.; Boyd, Iain D.; Meissner, Dana L.; Dewitt, Kenneth J.

1991-01-01

Measurements of Pitot pressure were made in the exit plane and plume of a low-density, nitrogen nozzle flow. Two numerical computer codes were used to analyze the flow, including one based on continuum theory using the explicit MacCormack method, and the other on kinetic theory using the method of direct-simulation Monte Carlo (DSMC). The continuum analysis was carried to the nozzle exit plane and the results were compared to the measurements. The DSMC analysis was extended into the plume of the nozzle flow and the results were compared with measurements at the exit plane and axial stations 12, 24 and 36 mm into the near-field plume. Two experimental apparatus were used that differed in design and gave slightly different profiles of pressure measurements. The DSMC method compared well with the measurements from each apparatus at all axial stations and provided a more accurate prediction of the flow than the continuum method, verifying the validity of DSMC for such calculations.

The direct simulation of acoustics on Earth, Mars, and Titan.

PubMed

Hanford, Amanda D; Long, Lyle N

2009-02-01

With the recent success of the Huygens lander on Titan, a moon of Saturn, there has been renewed interest in further exploring the acoustic environments of the other planets in the solar system. The direct simulation Monte Carlo (DSMC) method is used here for modeling sound propagation in the atmospheres of Earth, Mars, and Titan at a variety of altitudes above the surface. DSMC is a particle method that describes gas dynamics through direct physical modeling of particle motions and collisions. The validity of DSMC for the entire range of Knudsen numbers (Kn), where Kn is defined as the mean free path divided by the wavelength, allows for the exploration of sound propagation in planetary environments for all values of Kn. DSMC results at a variety of altitudes on Earth, Mars, and Titan including the details of nonlinearity, absorption, dispersion, and molecular relaxation in gas mixtures are given for a wide range of Kn showing agreement with various continuum theories at low Kn and deviation from continuum theory at high Kn. Despite large computation time and memory requirements, DSMC is the method best suited to study high altitude effects or where continuum theory is not valid.

Simulation of unsteady flows by the DSMC macroscopic chemistry method

NASA Astrophysics Data System (ADS)

Goldsworthy, Mark; Macrossan, Michael; Abdel-jawad, Madhat

2009-03-01

In the Direct Simulation Monte-Carlo (DSMC) method, a combination of statistical and deterministic procedures applied to a finite number of 'simulator' particles are used to model rarefied gas-kinetic processes. In the macroscopic chemistry method (MCM) for DSMC, chemical reactions are decoupled from the specific particle pairs selected for collisions. Information from all of the particles within a cell, not just those selected for collisions, is used to determine a reaction rate coefficient for that cell. Unlike collision-based methods, MCM can be used with any viscosity or non-reacting collision models and any non-reacting energy exchange models. It can be used to implement any reaction rate formulations, whether these be from experimental or theoretical studies. MCM has been previously validated for steady flow DSMC simulations. Here we show how MCM can be used to model chemical kinetics in DSMC simulations of unsteady flow. Results are compared with a collision-based chemistry procedure for two binary reactions in a 1-D unsteady shock-expansion tube simulation. Close agreement is demonstrated between the two methods for instantaneous, ensemble-averaged profiles of temperature, density and species mole fractions, as well as for the accumulated number of net reactions per cell.

Study of the Transition Flow Regime using Monte Carlo Methods

NASA Technical Reports Server (NTRS)

Hassan, H. A.

1999-01-01

This NASA Cooperative Agreement presents a study of the Transition Flow Regime Using Monte Carlo Methods. The topics included in this final report are: 1) New Direct Simulation Monte Carlo (DSMC) procedures; 2) The DS3W and DS2A Programs; 3) Papers presented; 4) Miscellaneous Applications and Program Modifications; 5) Solution of Transitional Wake Flows at Mach 10; and 6) Turbulence Modeling of Shock-Dominated Fows with a k-Enstrophy Formulation.

DSMC simulations of shock interactions about sharp double cones

NASA Astrophysics Data System (ADS)

Moss, James N.

2001-08-01

This paper presents the results of a numerical study of shock interactions resulting from Mach 10 flow about sharp double cones. Computations are made by using the direct simulation Monte Carlo (DSMC) method of Bird. The sensitivity and characteristics of the interactions are examined by varying flow conditions, model size, and configuration. The range of conditions investigated includes those for which experiments have been or will be performed in the ONERA R5Ch low-density wind tunnel and the Calspan-University of Buffalo Research Center (CUBRC) Large Energy National Shock (LENS) tunnel.

DSMC Simulations of Shock Interactions About Sharp Double Cones

NASA Technical Reports Server (NTRS)

Moss, James N.

2000-01-01

This paper presents the results of a numerical study of shock interactions resulting from Mach 10 flow about sharp double cones. Computations are made by using the direct simulation Monte Carlo (DSMC) method of Bird. The sensitivity and characteristics of the interactions are examined by varying flow conditions, model size, and configuration. The range of conditions investigated includes those for which experiments have been or will be performed in the ONERA R5Ch low-density wind tunnel and the Calspan-University of Buffalo Research Center (CUBRC) Large Energy National Shock (LENS) tunnel.

Fast and accurate calculation of dilute quantum gas using Uehling–Uhlenbeck model equation

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

Yano, Ryosuke, E-mail: ryosuke.yano@tokiorisk.co.jp

The Uehling–Uhlenbeck (U–U) model equation is studied for the fast and accurate calculation of a dilute quantum gas. In particular, the direct simulation Monte Carlo (DSMC) method is used to solve the U–U model equation. DSMC analysis based on the U–U model equation is expected to enable the thermalization to be accurately obtained using a small number of sample particles and the dilute quantum gas dynamics to be calculated in a practical time. Finally, the applicability of DSMC analysis based on the U–U model equation to the fast and accurate calculation of a dilute quantum gas is confirmed by calculatingmore » the viscosity coefficient of a Bose gas on the basis of the Green–Kubo expression and the shock layer of a dilute Bose gas around a cylinder.« less

Analysis of Plume Impingement Effects from Orion Crew Service Module Dual Reaction Control System Engine Firings

NASA Technical Reports Server (NTRS)

Prisbell, Andrew; Marichalar, J.; Lumpkin, F.; LeBeau, G.

2010-01-01

Plume impingement effects on the Orion Crew Service Module (CSM) were analyzed for various dual Reaction Control System (RCS) engine firings and various configurations of the solar arrays. The study was performed using a decoupled computational fluid dynamics (CFD) and Direct Simulation Monte Carlo (DSMC) approach. This approach included a single jet plume solution for the R1E RCS engine computed with the General Aerodynamic Simulation Program (GASP) CFD code. The CFD solution was used to create an inflow surface for the DSMC solution based on the Bird continuum breakdown parameter. The DSMC solution was then used to model the dual RCS plume impingement effects on the entire CSM geometry with deployed solar arrays. However, because the continuum breakdown parameter of 0.5 could not be achieved due to geometrical constraints and because high resolution in the plume shock interaction region is desired, a focused DSMC simulation modeling only the plumes and the shock interaction region was performed. This high resolution intermediate solution was then used as the inflow to the larger DSMC solution to obtain plume impingement heating, forces, and moments on the CSM and the solar arrays for a total of 21 cases that were analyzed. The results of these simulations were used to populate the Orion CSM Aerothermal Database.

Effects of continuum breakdown on hypersonic aerothermodynamics for reacting flow

NASA Astrophysics Data System (ADS)

Holman, Timothy D.; Boyd, Iain D.

2011-02-01

This study investigates the effects of continuum breakdown on the surface aerothermodynamic properties (pressure, stress, and heat transfer rate) of a sphere in a Mach 25 flow of reacting air in regimes varying from continuum to a rarefied gas. Results are generated using both continuum [computational fluid dynamics (CFD)] and particle [direct simulation Monte Carlo (DSMC)] approaches. The DSMC method utilizes a chemistry model that calculates the backward rates from an equilibrium constant. A preferential dissociation model is modified in the CFD method to better compare with the vibrationally favored dissociation model that is utilized in the DSMC method. Tests of these models are performed to confirm their validity and to compare the chemistry models in both numerical methods. This study examines the effect of reacting air flow on continuum breakdown and the surface properties of the sphere. As the global Knudsen number increases, the amount of continuum breakdown in the flow and on the surface increases. This increase in continuum breakdown significantly affects the surface properties, causing an increase in the differences between CFD and DSMC. Explanations are provided for the trends observed.

Investigation of the High-Energy Oxidation of FiberForm from DSMC Analysis of Molecular Beam Experiments

NASA Technical Reports Server (NTRS)

Borner, A.; Swaminathan-Gopalan, K.; Stephani, Kelly; Poovathingal, S.; Murray, V. J.; Minton, T. K.; Panerai, F.; Mansour, N. N.

2017-01-01

A collaborative effort between the University of Illinois at Urbana-Champaign (UIUC), NASA Ames Research Center (ARC) and Montana State University (MSU) succeeded at developing a new finite-rate carbon oxidation model from molecular beam scattering experiments on vitreous carbon (VC). We now aim to use the direct simulation Monte Carlo (DSMC) code SPARTA to apply the model to each fiber of the porous fibrous Thermal Protection Systems (TPS) material FiberForm (FF). The detailed micro-structure of FF was obtained from X-ray micro-tomography and then used in DSMC. Both experiments and simulations show that the CO/O products ratio increased at all temperatures from VC to FF. We postulate this is due to the larger number of collisions an O atom encounters inside the porous FF material compared to the flat surface of VC. For the simulations, we particularly focused on the lowest and highest temperatures studied experimentally, 1023 K and 1823 K, and found good agreement between the finite-rate DSMC simulations and experiments.

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.

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.

Simulations of Ground and Space-Based Oxygen Atom Experiments

NASA Technical Reports Server (NTRS)

Finchum, A. (Technical Monitor); Cline, J. A.; Minton, T. K.; Braunstein, M.

2003-01-01

A low-earth orbit (LEO) materials erosion scenario and the ground-based experiment designed to simulate it are compared using the direct-simulation Monte Carlo (DSMC) method. The DSMC model provides a detailed description of the interactions between the hyperthermal gas flow and a normally oriented flat plate for each case. We find that while the general characteristics of the LEO exposure are represented in the ground-based experiment, multi-collision effects can potentially alter the impact energy and directionality of the impinging molecules in the ground-based experiment. Multi-collision phenomena also affect downstream flux measurements.

Direct Simulation of Reentry Flows with Ionization

NASA Technical Reports Server (NTRS)

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

1989-01-01

The Direct Simulation Monte Carlo (DSMC) method is applied in this paper to the study of rarefied, hypersonic, reentry flows. The assumptions and simplifications involved with the treatment of ionization, free electrons and the electric field are investigated. A new method is presented for the calculation of the electric field and handling of charged particles with DSMC. In addition, a two-step model for electron impact ionization is implemented. The flow field representing a 10 km/sec shock at an altitude of 65 km is calculated. The effects of the new modeling techniques on the calculation results are presented and discussed.

DSMC Simulations of Hypersonic Flows and Comparison With Experiments

NASA Technical Reports Server (NTRS)

Moss, James N.; Bird, Graeme A.; Markelov, Gennady N.

2004-01-01

This paper presents computational results obtained with the direct simulation Monte Carlo (DSMC) method for several biconic test cases in which shock interactions and flow separation-reattachment are key features of the flow. Recent ground-based experiments have been performed for several biconic configurations, and surface heating rate and pressure measurements have been proposed for code validation studies. The present focus is to expand on the current validating activities for a relatively new DSMC code called DS2V that Bird (second author) has developed. Comparisons with experiments and other computations help clarify the agreement currently being achieved between computations and experiments and to identify the range of measurement variability of the proposed validation data when benchmarked with respect to the current computations. For the test cases with significant vibrational nonequilibrium, the effect of the vibrational energy surface accommodation on heating and other quantities is demonstrated.

Hypersonic simulations using open-source CFD and DSMC solvers

NASA Astrophysics Data System (ADS)

Casseau, V.; Scanlon, T. J.; John, B.; Emerson, D. R.; Brown, R. E.

2016-11-01

Hypersonic hybrid hydrodynamic-molecular gas flow solvers are required to satisfy the two essential requirements of any high-speed reacting code, these being physical accuracy and computational efficiency. The James Weir Fluids Laboratory at the University of Strathclyde is currently developing an open-source hybrid code which will eventually reconcile the direct simulation Monte-Carlo method, making use of the OpenFOAM application called dsmcFoam, and the newly coded open-source two-temperature computational fluid dynamics solver named hy2Foam. In conjunction with employing the CVDV chemistry-vibration model in hy2Foam, novel use is made of the QK rates in a CFD solver. In this paper, further testing is performed, in particular with the CFD solver, to ensure its efficacy before considering more advanced test cases. The hy2Foam and dsmcFoam codes have shown to compare reasonably well, thus providing a useful basis for other codes to compare against.

Comparisons of the Maxwell and CLL Gas/Surface Interaction Models Using DSMC

NASA Technical Reports Server (NTRS)

Hedahl, Marc O.

1995-01-01

Two contrasting models of gas-surface interactions are studied using the Direct Simulation Monte Carlo (DSMC) method. The DSMC calculations examine differences in predictions of aerodynamic forces and heat transfer between the Maxwell and Cercignani-Lampis-Lord (CLL) models for flat plate configurations at freestream conditions corresponding to a 140 km orbit around Venus. The size of the flat plate is that of one of the solar panels on the Magellan spacecraft, and the freestream conditions are one of those experienced during aerobraking maneuvers. Results are presented for both a single flat plate and a two-plate configuration as a function of angle of attack and gas-surface accommodation coefficients. The two plate system is not representative of the Magellan geometry, but is studied to explore possible experiments that might be used to differentiate between the two gas surface interaction models.

DREAM: An Efficient Methodology for DSMC Simulation of Unsteady Processes

NASA Astrophysics Data System (ADS)

Cave, H. M.; Jermy, M. C.; Tseng, K. C.; Wu, J. S.

2008-12-01

A technique called the DSMC Rapid Ensemble Averaging Method (DREAM) for reducing the statistical scatter in the output from unsteady DSMC simulations is introduced. During post-processing by DREAM, the DSMC algorithm is re-run multiple times over a short period before the temporal point of interest thus building up a combination of time- and ensemble-averaged sampling data. The particle data is regenerated several mean collision times before the output time using the particle data generated during the original DSMC run. This methodology conserves the original phase space data from the DSMC run and so is suitable for reducing the statistical scatter in highly non-equilibrium flows. In this paper, the DREAM-II method is investigated and verified in detail. Propagating shock waves at high Mach numbers (Mach 8 and 12) are simulated using a parallel DSMC code (PDSC) and then post-processed using DREAM. The ability of DREAM to obtain the correct particle velocity distribution in the shock structure is demonstrated and the reduction of statistical scatter in the output macroscopic properties is measured. DREAM is also used to reduce the statistical scatter in the results from the interaction of a Mach 4 shock with a square cavity and for the interaction of a Mach 12 shock on a wedge in a channel.

Evaluation of new collision-pair selection models in DSMC

NASA Astrophysics Data System (ADS)

Akhlaghi, Hassan; Roohi, Ehsan

2017-10-01

The current paper investigates new collision-pair selection procedures in a direct simulation Monte Carlo (DSMC) method. Collision partner selection based on the random procedure from nearest neighbor particles and deterministic selection of nearest neighbor particles have already been introduced as schemes that provide accurate results in a wide range of problems. In the current research, new collision-pair selections based on the time spacing and direction of the relative movement of particles are introduced and evaluated. Comparisons between the new and existing algorithms are made considering appropriate test cases including fluctuations in homogeneous gas, 2D equilibrium flow, and Fourier flow problem. Distribution functions for number of particles and collisions in cell, velocity components, and collisional parameters (collision separation, time spacing, relative velocity, and the angle between relative movements of particles) are investigated and compared with existing analytical relations for each model. The capability of each model in the prediction of the heat flux in the Fourier problem at different cell numbers, numbers of particles, and time steps is examined. For new and existing collision-pair selection schemes, the effect of an alternative formula for the number of collision-pair selections and avoiding repetitive collisions are investigated via the prediction of the Fourier heat flux. The simulation results demonstrate the advantages and weaknesses of each model in different test cases.

Particle/Continuum Hybrid Simulation in a Parallel Computing Environment

NASA Technical Reports Server (NTRS)

Baganoff, Donald

1996-01-01

The objective of this study was to modify an existing parallel particle code based on the direct simulation Monte Carlo (DSMC) method to include a Navier-Stokes (NS) calculation so that a hybrid solution could be developed. In carrying out this work, it was determined that the following five issues had to be addressed before extensive program development of a three dimensional capability was pursued: (1) find a set of one-sided kinetic fluxes that are fully compatible with the DSMC method, (2) develop a finite volume scheme to make use of these one-sided kinetic fluxes, (3) make use of the one-sided kinetic fluxes together with DSMC type boundary conditions at a material surface so that velocity slip and temperature slip arise naturally for near-continuum conditions, (4) find a suitable sampling scheme so that the values of the one-sided fluxes predicted by the NS solution at an interface between the two domains can be converted into the correct distribution of particles to be introduced into the DSMC domain, (5) carry out a suitable number of tests to confirm that the developed concepts are valid, individually and in concert for a hybrid scheme.

Molecular-Level Simulations of the Turbulent Taylor-Green Flow

NASA Astrophysics Data System (ADS)

Gallis, M. A.; Bitter, N. P.; Koehler, T. P.; Plimpton, S. J.; Torczynski, J. R.; Papadakis, G.

2017-11-01

The Direct Simulation Monte Carlo (DSMC) method, a statistical, molecular-level technique that provides accurate solutions to the Boltzmann equation, is applied to the turbulent Taylor-Green vortex flow. The goal of this work is to investigate whether DSMC can accurately simulate energy decay in a turbulent flow. If so, then simulating turbulent flows at the molecular level can provide new insights because the energy decay can be examined in detail from molecular to macroscopic length scales, thereby directly linking molecular relaxation processes to macroscopic transport processes. The DSMC simulations are performed on half a million cores of Sequoia, the 17 Pflop platform at Lawrence Livermore National Laboratory, and the kinetic-energy dissipation rate and the energy spectrum are computed directly from the molecular velocities. The DSMC simulations are found to reproduce the Kolmogorov -5/3 law and to agree with corresponding Navier-Stokes simulations obtained using a spectral method. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

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.

Oxygen transport properties estimation by DSMC-CT simulations

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

Bruno, Domenico; Frezzotti, Aldo; Ghiroldi, Gian Pietro

Coupling DSMC simulations with classical trajectories calculations is emerging as a powerful tool to improve predictive capabilities of computational rarefied gas dynamics. The considerable increase of computational effort outlined in the early application of the method (Koura,1997) can be compensated by running simulations on massively parallel computers. In particular, GPU acceleration has been found quite effective in reducing computing time (Ferrigni,2012; Norman et al.,2013) of DSMC-CT simulations. The aim of the present work is to study rarefied Oxygen flows by modeling binary collisions through an accurate potential energy surface, obtained by molecular beams scattering (Aquilanti, et al.,1999). The accuracy ofmore » the method is assessed by calculating molecular Oxygen shear viscosity and heat conductivity following three different DSMC-CT simulation methods. In the first one, transport properties are obtained from DSMC-CT simulations of spontaneous fluctuation of an equilibrium state (Bruno et al, Phys. Fluids, 23, 093104, 2011). In the second method, the collision trajectory calculation is incorporated in a Monte Carlo integration procedure to evaluate the Taxman’s expressions for the transport properties of polyatomic gases (Taxman,1959). In the third, non-equilibrium zero and one-dimensional rarefied gas dynamic simulations are adopted and the transport properties are computed from the non-equilibrium fluxes of momentum and energy. The three methods provide close values of the transport properties, their estimated statistical error not exceeding 3%. The experimental values are slightly underestimated, the percentage deviation being, again, few percent.« less

DSMC Simulations of Hypersonic Flows With Shock Interactions and Validation With Experiments

NASA Technical Reports Server (NTRS)

Moss, James N.; Bird, Graeme A.

2004-01-01

The capabilities of a relatively new direct simulation Monte Carlo (DSMC) code are examined for the problem of hypersonic laminar shock/shock and shock/boundary layer interactions, where boundary layer separation is an important feature of the flow. Flow about two model configurations is considered, where both configurations (a biconic and a hollow cylinder-flare) have recent published experimental measurements. The computations are made by using the DS2V code of Bird, a general two-dimensional/axisymmetric time accurate code that incorporates many of the advances in DSMC over the past decade. The current focus is on flows produced in ground-based facilities at Mach 12 and 16 test conditions with nitrogen as the test gas and the test models at zero incidence. Results presented highlight the sensitivity of the calculations to grid resolutions, sensitivity to physical modeling parameters, and comparison with experimental measurements. Information is provided concerning the flow structure and surface results for the extent of separation, heating, pressure, and skin friction.

DSMC Simulations of Hypersonic Flows With Shock Interactions and Validation With Experiments

NASA Technical Reports Server (NTRS)

Moss, James N.; Bird, Graeme A.

2004-01-01

The capabilities of a relatively new direct simulation Monte Carlo (DSMC) code are examined for the problem of hypersonic laminar shock/shock and shock/boundary layer interactions, where boundary layer separation is an important feature of the flow. Flow about two model configurations is considered, where both configurations (a biconic and a hollow cylinder-flare) have recent published experimental measurements. The computations are made by using the DS2V code of Bird, a general two-dimensional/axisymmetric time accurate code that incorporates many of the advances in DSMC over the past decade. The current focus is on flows produced in ground-based facilities at Mach 12 and 16 test conditions with nitrogen as the test gas and the test models at zero incidence. Results presented highlight the sensitivity of the calculations to grid resolution, sensitivity to physical modeling parameters, and comparison with experimental measurements. Information is provided concerning the flow structure and surface results for the extent of separation, heating, pressure, and skin friction.

A continuum analysis of chemical nonequilibrium under hypersonic low-density flight conditions

NASA Technical Reports Server (NTRS)

Gupta, R. N.

1986-01-01

Results of employing the continuum model of Navier-Stokes equations under the low-density flight conditions are presented. These results are obtained with chemical nonequilibrium and multicomponent surface slip boundary conditions. The conditions analyzed are those encountered by the nose region of the Space Shuttle Orbiter during reentry. A detailed comparison of the Navier-Stokes (NS) results is made with the viscous shock-layer (VSL) and direct simulation Monte Carlo (DSMC) predictions. With the inclusion of new surface-slip boundary conditions in NS calculations, the surface heat transfer and other flowfield quantities adjacent to the surface are predicted favorably with the DSMC calculations from 75 km to 115 km in altitude. This suggests a much wider practical range for the applicability of Navier-Stokes solutions than previously thought. This is appealing because the continuum (NS and VSL) methods are commonly used to solve the fluid flow problems and are less demanding in terms of computer resource requirements than the noncontinuum (DSMC) methods.

Error estimation for CFD aeroheating prediction under rarefied flow condition

NASA Astrophysics Data System (ADS)

Jiang, Yazhong; Gao, Zhenxun; Jiang, Chongwen; Lee, Chunhian

2014-12-01

Both direct simulation Monte Carlo (DSMC) and Computational Fluid Dynamics (CFD) methods have become widely used for aerodynamic prediction when reentry vehicles experience different flow regimes during flight. The implementation of slip boundary conditions in the traditional CFD method under Navier-Stokes-Fourier (NSF) framework can extend the validity of this approach further into transitional regime, with the benefit that much less computational cost is demanded compared to DSMC simulation. Correspondingly, an increasing error arises in aeroheating calculation as the flow becomes more rarefied. To estimate the relative error of heat flux when applying this method for a rarefied flow in transitional regime, theoretical derivation is conducted and a dimensionless parameter ɛ is proposed by approximately analyzing the ratio of the second order term to first order term in the heat flux expression in Burnett equation. DSMC simulation for hypersonic flow over a cylinder in transitional regime is performed to test the performance of parameter ɛ, compared with two other parameters, Knρ and MaṡKnρ.

Measurement and analysis of a small nozzle plume in vacuum

NASA Technical Reports Server (NTRS)

Penko, P. F.; Boyd, I. D.; Meissner, D. L.; Dewitt, K. J.

1993-01-01

Pitot pressures and flow angles are measured in the plume of a nozzle flowing nitrogen and exhausting to a vacuum. Total pressures are measured with Pitot tubes sized for specific regions of the plume and flow angles measured with a conical probe. The measurement area for total pressure extends 480 mm (16 exit diameters) downstream of the nozzle exit plane and radially to 60 mm (1.9 exit diameters) off the plume axis. The measurement area for flow angle extends to 160 mm (5 exit diameters) downstream and radially to 60 mm. The measurements are compared to results from a numerical simulation of the flow that is based on kinetic theory and uses the direct-simulation Monte Carlo (DSMC) method. Comparisons of computed results from the DSMC method with measurements of flow angle display good agreement in the far-field of the plume and improve with increasing distance from the exit plane. Pitot pressures computed from the DSMC method are in reasonably good agreement with experimental results over the entire measurement area.

Comparison of a 3-D CFD-DSMC Solution Methodology With a Wind Tunnel Experiment

NASA Technical Reports Server (NTRS)

Glass, Christopher E.; Horvath, Thomas J.

2002-01-01

A solution method for problems that contain both continuum and rarefied flow regions is presented. The methodology is applied to flow about the 3-D Mars Sample Return Orbiter (MSRO) that has a highly compressed forebody flow, a shear layer where the flow separates from a forebody lip, and a low density wake. Because blunt body flow fields contain such disparate regions, employing a single numerical technique to solve the entire 3-D flow field is often impractical, or the technique does not apply. Direct simulation Monte Carlo (DSMC) could be employed to solve the entire flow field; however, the technique requires inordinate computational resources for continuum and near-continuum regions, and is best suited for the wake region. Computational fluid dynamics (CFD) will solve the high-density forebody flow, but continuum assumptions do not apply in the rarefied wake region. The CFD-DSMC approach presented herein may be a suitable way to obtain a higher fidelity solution.

Development of the ARISTOTLE webware for cloud-based rarefied gas flow modeling

NASA Astrophysics Data System (ADS)

Deschenes, Timothy R.; Grot, Jonathan; Cline, Jason A.

2016-11-01

Rarefied gas dynamics are important for a wide variety of applications. An improvement in the ability of general users to predict these gas flows will enable optimization of current, and discovery of future processes. Despite this potential, most rarefied simulation software is designed by and for experts in the community. This has resulted in low adoption of the methods outside of the immediate RGD community. This paper outlines an ongoing effort to create a rarefied gas dynamics simulation tool that can be used by a general audience. The tool leverages a direct simulation Monte Carlo (DSMC) library that is available to the entire community and a web-based simulation process that will enable all users to take advantage of high performance computing capabilities. First, the DSMC library and simulation architecture are described. Then the DSMC library is used to predict a number of representative transient gas flows that are applicable to the rarefied gas dynamics community. The paper closes with a summary and future direction.

Investigation of the DSMC Approach for Ion/neutral Species in Modeling Low Pressure Plasma Reactor

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

Deng Hao; Li, Z.; Levin, D.

2011-05-20

Low pressure plasma reactors are important tools for ionized metal physical vapor deposition (IMPVD), a semiconductor plasma processing technology that is increasingly being applied to deposit Cu seed layers on semiconductor surfaces of trenches and vias with the high aspect ratio (e.g., >5:1). A large fraction of ionized atoms produced by the IMPVD process leads to an anisotropic deposition flux towards the substrate, a feature which is critical for attaining a void-free and uniform fill. Modeling such devices is challenging due to their high plasma density, reactive environment, but low gas pressure. A modular code developed by the Computational Opticalmore » and Discharge Physics Group, the Hybrid Plasma Equipment Model (HPEM), has been successfully applied to the numerical investigations of IMPVD by modeling a hollow cathode magnetron (HCM) device. However, as the development of semiconductor devices progresses towards the lower pressure regime (e.g., <5 mTorr), the breakdown of the continuum assumption limits the application of the fluid model in HPEM and suggests the incorporation of the kinetic method, such as the direct simulation Monte Carlo (DSMC), in the plasma simulation.The DSMC method, which solves the Boltzmann equation of transport, has been successfully applied in modeling micro-fluidic flows in MEMS devices with low Reynolds numbers, a feature shared with the HCM. Modeling of the basic physical and chemical processes for ion/neutral species in plasma have been developed and implemented in DSMC, which include ion particle motion due to the Lorentz force, electron impact reactions, charge exchange reactions, and charge recombination at the surface. The heating of neutrals due to collisions with ions and the heating of ions due to the electrostatic field will be shown to be captured by the DSMC simulations. In this work, DSMC calculations were coupled with the modules from HPEM so that the plasma can be self-consistently solved. Differences in the Ar results, the dominant species in the reactor, produced by the DSMC-HPEM coupled simulation will be shown in comparison with the original HPEM results. The effects of the DSMC calculations for ion/neutral species on HPEM plasma simulation will be further analyzed.« less

DSMC simulations of Mach 20 nitrogen flows about a 70 degree blunted cone and its wake

NASA Technical Reports Server (NTRS)

Moss, James N.; Dogra, Virendra K.; Wilmoth, Richard G.

1993-01-01

Numerical results obtained with the direct simulation Monte Carlo (DSMC) method are presented for Mach 20 nitrogen flow about a 70-deg blunted cone. The flow conditions simulated are those that can be obtained in existing low-density hypersonic wind tunnels. Three sets of flow conditions are simulated with freestream Knudsen numbers ranging from 0.03 to 0.001. The focus is to characterize the wake flow under rarefied conditions. This is accomplished by calculating the influence of rarefaction on wake structure along with the impact that an afterbody has on flow features. This data report presents extensive information concerning flowfield features and surface quantities.

Hypersonic Shock Interactions About a 25 deg/65 deg Sharp Double Cone

NASA Technical Reports Server (NTRS)

Moss, James N.; LeBeau, Gerald J.; Glass, Christopher E.

2002-01-01

This paper presents the results of a numerical study of shock interactions resulting from Mach 10 air flow about a sharp double cone. Computations are made with the direct simulation Monte Carlo (DSMC) method by using two different codes: the G2 code of Bird and the DAC (DSMC Analysis Code) code of LeBeau. The flow conditions are the pretest nominal free-stream conditions specified for the ONERA R5Ch low-density wind tunnel. The focus is on the sensitivity of the interactions to grid resolution while providing information concerning the flow structure and surface results for the extent of separation, heating, pressure, and skin friction.

The solution of a model problem of the atmospheric entry of a small meteoroid

NASA Astrophysics Data System (ADS)

Zalogin, G. N.; Kusov, A. L.

2016-03-01

Direct simulation Monte Carlo modeling (DSMC) is used to solve the problem of the entry into the Earth's atmosphere of a small meteoroid. The main aspects of the physical theory of meteors, such as mass loss (ablation) and effects of aerodynamic and thermal shielding, are considered based on the numerical solution of the model problem of the atmospheric entry of an iron meteoroid. The DSMC makes it possible to obtain insight into the structure of the disturbed area around the meteoroid (coma) and trace its evolution depending on entry velocity and height (Knudsen number) in a transitional flow regime where calculation methods used for free molecular and continuum regimes are inapplicable.

DSMC Simulations of Apollo Capsule Aerodynamics for Hypersonic Rarefied Conditions

NASA Technical Reports Server (NTRS)

Moss, James N.; Glass, Christopher E.; Greene, Francis A.

2006-01-01

Direct simulation Monte Carlo DSMC simulations are performed for the Apollo capsule in the hypersonic low density transitional flow regime. The focus is on ow conditions similar to that experienced by the Apollo Command Module during the high altitude portion of its reentry Results for aerodynamic forces and moments are presented that demonstrate their sensitivity to rarefaction that is for free molecular to continuum conditions. Also aerodynamic data are presented that shows their sensitivity to a range of reentry velocity encompasing conditions that include reentry from low Earth orbit lunar return and Mars return velocities to km/s. The rarefied results are anchored in the continuum regime with data from Navier Stokes simulations

Molecular-level simulations of turbulence and its decay

DOE PAGES

Gallis, M. A.; Bitter, N. P.; Koehler, T. P.; ...

2017-02-08

Here, we provide the first demonstration that molecular-level methods based on gas kinetic theory and molecular chaos can simulate turbulence and its decay. The direct simulation Monte Carlo (DSMC) method, a molecular-level technique for simulating gas flows that resolves phenomena from molecular to hydrodynamic (continuum) length scales, is applied to simulate the Taylor-Green vortex flow. The DSMC simulations reproduce the Kolmogorov –5/3 law and agree well with the turbulent kinetic energy and energy dissipation rate obtained from direct numerical simulation of the Navier-Stokes equations using a spectral method. This agreement provides strong evidence that molecular-level methods for gases can bemore » used to investigate turbulent flows quantitatively.« less

Particle kinetic simulation of high altitude hypervelocity flight

NASA Technical Reports Server (NTRS)

Boyd, Iain; Haas, Brian L.

1994-01-01

Rarefied flows about hypersonic vehicles entering the upper atmosphere or through nozzles expanding into a near vacuum may only be simulated accurately with a direct simulation Monte Carlo (DSMC) method. Under this grant, researchers enhanced the models employed in the DSMC method and performed simulations in support of existing NASA projects or missions. DSMC models were developed and validated for simulating rotational, vibrational, and chemical relaxation in high-temperature flows, including effects of quantized anharmonic oscillators and temperature-dependent relaxation rates. State-of-the-art advancements were made in simulating coupled vibration-dissociation recombination for post-shock flows. Models were also developed to compute vehicle surface temperatures directly in the code rather than requiring isothermal estimates. These codes were instrumental in simulating aerobraking of NASA's Magellan spacecraft during orbital maneuvers to assess heat transfer and aerodynamic properties of the delicate satellite. NASA also depended upon simulations of entry of the Galileo probe into the atmosphere of Jupiter to provide drag and flow field information essential for accurate interpretation of an onboard experiment. Finally, the codes have been used extensively to simulate expanding nozzle flows in low-power thrusters in support of propulsion activities at NASA-Lewis. Detailed comparisons between continuum calculations and DSMC results helped to quantify the limitations of continuum CFD codes in rarefied applications.

NAS Experiences of Porting CM Fortran Codes to HPF on IBM SP2 and SGI Power Challenge

NASA Technical Reports Server (NTRS)

Saini, Subhash

1995-01-01

Current Connection Machine (CM) Fortran codes developed for the CM-2 and the CM-5 represent an important class of parallel applications. Several users have employed CM Fortran codes in production mode on the CM-2 and the CM-5 for the last five to six years, constituting a heavy investment in terms of cost and time. With Thinking Machines Corporation's decision to withdraw from the hardware business and with the decommissioning of many CM-2 and CM-5 machines, the best way to protect the substantial investment in CM Fortran codes is to port the codes to High Performance Fortran (HPF) on highly parallel systems. HPF is very similar to CM Fortran and thus represents a natural transition. Conversion issues involved in porting CM Fortran codes on the CM-5 to HPF are presented. In particular, the differences between data distribution directives and the CM Fortran Utility Routines Library, as well as the equivalent functionality in the HPF Library are discussed. Several CM Fortran codes (Cannon algorithm for matrix-matrix multiplication, Linear solver Ax=b, 1-D convolution for 2-D datasets, Laplace's Equation solver, and Direct Simulation Monte Carlo (DSMC) codes have been ported to Subset HPF on the IBM SP2 and the SGI Power Challenge. Speedup ratios versus number of processors for the Linear solver and DSMC code are presented.

Shock-Wave/Boundary-Layer Interactions in Hypersonic Low Density Flows

NASA Technical Reports Server (NTRS)

Moss, James N.; Olejniczak, Joseph

2004-01-01

Results of numerical simulations of Mach 10 air flow over a hollow cylinder-flare and a double-cone are presented where viscous effects are significant. The flow phenomena include shock-shock and shock- boundary-layer interactions with accompanying flow separation, recirculation, and reattachment. The purpose of this study is to promote an understanding of the fundamental gas dynamics resulting from such complex interactions and to clarify the requirements for meaningful simulations of such flows when using the direct simulation Monte Carlo (DSMC) method. Particular emphasis is placed on the sensitivity of computed results to grid resolution. Comparisons of the DSMC results for the hollow cylinder-flare (30 deg.) configuration are made with the results of experimental measurements conducted in the ONERA RSCh wind tunnel for heating, pressure, and the extent of separation. Agreement between computations and measurements for various quantities is good except that for pressure. For the same flow conditions, the double- cone geometry (25 deg.- 65 deg.) produces much stronger interactions, and these interactions are investigated numerically using both DSMC and Navier-Stokes codes. For the double-cone computations, a two orders of magnitude variation in free-stream density (with Reynolds numbers from 247 to 24,7 19) is investigated using both computational methods. For this range of flow conditions, the computational results are in qualitative agreement for the extent of separation with the DSMC method always predicting a smaller separation region. Results from the Navier-Stokes calculations suggest that the flow for the highest density double-cone case may be unsteady; however, the DSMC solution does not show evidence of unsteadiness.

Effects of Chemistry on Blunt-Body Wake Structure

NASA Technical Reports Server (NTRS)

Dogra, Virendra K.; Moss, James N.; Wilmoth, Richard G.; Taylor, Jeff C.; Hassan, H. A.

1995-01-01

Results of a numerical study are presented for hypersonic low-density flow about a 70-deg blunt cone using direct simulation Monte Carlo (DSMC) and Navier-Stokes calculations. Particular emphasis is given to the effects of chemistry on the near-wake structure and on the surface quantities and the comparison of the DSMC results with the Navier-Stokes calculations. The flow conditions simulated are those experienced by a space vehicle at an altitude of 85 km and a velocity of 7 km/s during Earth entry. A steady vortex forms in the near wake for these freestream conditions for both chemically reactive and nonreactive air gas models. The size (axial length) of the vortex for the reactive air calculations is 25% larger than that of the nonreactive air calculations. The forebody surface quantities are less sensitive to the chemistry than the base surface quantities. The presence of the afterbody has no effect on the forebody flow structure or the surface quantities. The comparisons of DSMC and Navier-Stokes calculations show good agreement for the wake structure and the forebody surface quantities.

Restricted Collision List method for faster Direct Simulation Monte-Carlo (DSMC) collisions

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

Macrossan, Michael N., E-mail: m.macrossan@uq.edu.au

The ‘Restricted Collision List’ (RCL) method for speeding up the calculation of DSMC Variable Soft Sphere collisions, with Borgnakke–Larsen (BL) energy exchange, is presented. The method cuts down considerably on the number of random collision parameters which must be calculated (deflection and azimuthal angles, and the BL energy exchange factors). A relatively short list of these parameters is generated and the parameters required in any cell are selected from this list. The list is regenerated at intervals approximately equal to the smallest mean collision time in the flow, and the chance of any particle re-using the same collision parameters inmore » two successive collisions is negligible. The results using this method are indistinguishable from those obtained with standard DSMC. The CPU time saving depends on how much of a DSMC calculation is devoted to collisions and how much is devoted to other tasks, such as moving particles and calculating particle interactions with flow boundaries. For 1-dimensional calculations of flow in a tube, the new method saves 20% of the CPU time per collision for VSS scattering with no energy exchange. With RCL applied to rotational energy exchange, the CPU saving can be greater; for small values of the rotational collision number, for which most collisions involve some rotational energy exchange, the CPU may be reduced by 50% or more.« less

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

Development of a Detailed Surface Chemistry Framework in DSMC

NASA Technical Reports Server (NTRS)

Swaminathan-Gopalan, K.; Borner, A.; Stephani, K. A.

2017-01-01

Many of the current direct simulation Monte Carlo (DSMC) codes still employ only simple surface catalysis models. These include only basic mechanisms such as dissociation, recombination, and exchange reactions, without any provision for adsorption and finite rate kinetics. Incorporating finite rate chemistry at the surface is increasingly becoming a necessity for various applications such as high speed re-entry flows over thermal protection systems (TPS), micro-electro-mechanical systems (MEMS), surface catalysis, etc. In the recent years, relatively few works have examined finite-rate surface reaction modeling using the DSMC method.In this work, a generalized finite-rate surface chemistry framework incorporating a comprehensive list of reaction mechanisms is developed and implemented into the DSMC solver SPARTA. The various mechanisms include adsorption, desorption, Langmuir-Hinshelwood (LH), Eley-Rideal (ER), Collision Induced (CI), condensation, sublimation, etc. The approach is to stochastically model the various competing reactions occurring on a set of active sites. Both gas-surface (e.g., ER, CI) and pure-surface (e.g., LH, desorption) reaction mechanisms are incorporated. The reaction mechanisms could also be catalytic or surface altering based on the participation of the bulk-phase species (e.g., bulk carbon atoms). Marschall and MacLean developed a general formulation in which multiple phases and surface sites are used and we adopt a similar convention in the current work. Microscopic parameters of reaction probabilities (for gas-surface reactions) and frequencies (for pure-surface reactions) that are require for DSMC are computed from the surface properties and macroscopic parameters such as rate constants, sticking coefficients, etc. The energy and angular distributions of the products are decided based on the reaction type and input parameters. Thus, the user has the capability to model various surface reactions via user-specified reaction rate constants, surface properties and parameters.

DSMC Computations for Regions of Shock/Shock and Shock/Boundary Layer Interaction

NASA Technical Reports Server (NTRS)

Moss, James N.

2001-01-01

This paper presents the results of a numerical study of hypersonic interacting flows at flow conditions that include those for which experiments have been conducted in the Calspan-University of Buffalo Research Center (CUBRC) Large Energy National Shock (LENS) tunnel and the ONERA R5Ch low-density wind tunnel. The computations are made with the direct simulation Monte Carlo (DSMC) method of Bird. The focus is on Mach 9.3 to 11.4 flows about flared axisymmetric configurations, both hollow cylinder flares and double cones. The results presented highlight the sensitivity of the calculations to grid resolution, provide results concerning the conditions for incipient separation, and provide information concerning the flow structure and surface results for the extent of separation, heating, pressure, and skin friction.

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

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.

Hypersonic low-density solutions of the Navier-Stokes equations with chemical nonequilibrium and multicomponent surface slip

NASA Technical Reports Server (NTRS)

Gupta, R. N.; Simmonds, A. L.

1986-01-01

Solutions of the Navier-Stokes equations with chemical nonequilibrium and multicomponent surface slip are presented along the stagnation streamline under low-density hypersonic flight conditions. The conditions analyzed are those encountered by the nose region of the Space Shuttle Orbiter during reentry. A detailed comparison of the Navier-Stokes (NS) results is made with the viscous shock-layer (VSL) and Direct Simulation Monte Carlo (DSMC) predictions. With the inclusion of surface-slip boundary conditions in NS calculations, the surface heat transfer and other flow field quantities adjacent to the surface are predicted favorably with the DSMC calculations from 75 km to 115 km in altitude. Therefore, the practical range for the applicability of Navier-Stokes solutions is much wider than previously thought. This is appealing because the continuum (NS and VSL) methods are commonly used to solve the fluid flow problems and are less demanding in terms of computer resource requirements than the noncontinuum (DSMC) methods. The NS solutions agree well with the VSL results for altitudes less than 92 km. An assessment is made of the frozen flow approximation employed in the VSL calculations.

Plume flowfield analysis of the shuttle primary Reaction Control System (RCS) rocket engine

NASA Technical Reports Server (NTRS)

Hueser, J. E.; Brock, F. J.

1990-01-01

A solution was generated for the physical properties of the Shuttle RCS 4000 N (900 lb) rocket engine exhaust plume flowfield. The modeled exhaust gas consists of the five most abundant molecular species, H2, N2, H2O, CO, and CO2. The solution is for a bare RCS engine firing into a vacuum; the only additional hardware surface in the flowfield is a cylinder (=engine mount) which coincides with the nozzle lip outer corner at X = 0, extends to the flowfield outer boundary at X = -137 m and is coaxial with the negative symmetry axis. Continuum gas dynamic methods and the Direct Simulation Monte Carlo (DSMC) method were combined in an iterative procedure to produce a selfconsistent solution. Continuum methods were used in the RCS nozzle and in the plume as far as the P = 0.03 breakdown contour; the DSMC method was used downstream of this continuum flow boundary. The DSMC flowfield extends beyond 100 m from the nozzle exit and thus the solution includes the farfield flow properties, but substantial information is developed on lip flow dynamics and thus results are also presented for the flow properties in the vicinity of the nozzle lip.

DSMC study of oxygen shockwaves based on high-fidelity vibrational relaxation and dissociation models

NASA Astrophysics Data System (ADS)

Borges Sebastião, Israel; Kulakhmetov, Marat; Alexeenko, Alina

2017-01-01

This work evaluates high-fidelity vibrational-translational (VT) energy relaxation and dissociation models for pure O2 normal shockwave simulations with the direct simulation Monte Carlo (DSMC) method. The O2-O collisions are described using ab initio state-specific relaxation and dissociation models. The Macheret-Fridman (MF) dissociation model is adapted to the DSMC framework by modifying the standard implementation of the total collision energy (TCE) model. The O2-O2 dissociation is modeled with this TCE+MF approach, which is calibrated with O2-O ab initio data and experimental equilibrium dissociation rates. The O2-O2 vibrational relaxation is modeled via the Larsen-Borgnakke model, calibrated to experimental VT rates. All the present results are compared to experimental data and previous calculations available in the literature. It is found that, in general, the ab initio dissociation model is better than the TCE model at matching the shock experiments. Therefore, when available, efficient ab initio models are preferred over phenomenological models. We also show that the proposed TCE + MF formulation can be used to improve the standard TCE model results when ab initio data are not available or limited.

Comparison between phenomenological and ab-initio reaction and relaxation models in DSMC

NASA Astrophysics Data System (ADS)

Sebastião, Israel B.; Kulakhmetov, Marat; Alexeenko, Alina

2016-11-01

New state-specific vibrational-translational energy exchange and dissociation models, based on ab-initio data, are implemented in direct simulation Monte Carlo (DSMC) method and compared to the established Larsen-Borgnakke (LB) and total collision energy (TCE) phenomenological models. For consistency, both the LB and TCE models are calibrated with QCT-calculated O2+O data. The model comparison test cases include 0-D thermochemical relaxation under adiabatic conditions and 1-D normal shockwave calculations. The results show that both the ME-QCT-VT and LB models can reproduce vibrational relaxation accurately but the TCE model is unable to reproduce nonequilibrium rates even when it is calibrated to accurate equilibrium rates. The new reaction model does capture QCT-calculated nonequilibrium rates. For all investigated cases, we discuss the prediction differences based on the new model features.

Modifications to Axially Symmetric Simulations Using New DSMC (2007) Algorithms

NASA Technical Reports Server (NTRS)

Liechty, Derek S.

2008-01-01

Several modifications aimed at improving physical accuracy are proposed for solving axially symmetric problems building on the DSMC (2007) algorithms introduced by Bird. Originally developed to solve nonequilibrium, rarefied flows, the DSMC method is now regularly used to solve complex problems over a wide range of Knudsen numbers. These new algorithms include features such as nearest neighbor collisions excluding the previous collision partners, separate collision and sampling cells, automatically adaptive variable time steps, a modified no-time counter procedure for collisions, and discontinuous and event-driven physical processes. Axially symmetric solutions require radial weighting for the simulated molecules since the molecules near the axis represent fewer real molecules than those farther away from the axis due to the difference in volume of the cells. In the present methodology, these radial weighting factors are continuous, linear functions that vary with the radial position of each simulated molecule. It is shown that how one defines the number of tentative collisions greatly influences the mean collision time near the axis. The method by which the grid is treated for axially symmetric problems also plays an important role near the axis, especially for scalar pressure. A new method to treat how the molecules are traced through the grid is proposed to alleviate the decrease in scalar pressure at the axis near the surface. Also, a modification to the duplication buffer is proposed to vary the duplicated molecular velocities while retaining the molecular kinetic energy and axially symmetric nature of the problem.

Comparison of DSMC and CFD Solutions of Fire II Including Radiative Heating

NASA Technical Reports Server (NTRS)

Liechty, Derek S.; Johnston, Christopher O.; Lewis, Mark J.

2011-01-01

The ability to compute rarefied, ionized hypersonic flows is becoming more important as missions such as Earth reentry, landing high mass payloads on Mars, and the exploration of the outer planets and their satellites are being considered. These flows may also contain significant radiative heating. To prepare for these missions, NASA is developing the capability to simulate rarefied, ionized flows and to then calculate the resulting radiative heating to the vehicle's surface. In this study, the DSMC codes DAC and DS2V are used to obtain charge-neutral ionization solutions. NASA s direct simulation Monte Carlo code DAC is currently being updated to include the ability to simulate charge-neutral ionized flows, take advantage of the recently introduced Quantum-Kinetic chemistry model, and to include electronic energy levels as an additional internal energy mode. The Fire II flight test is used in this study to assess these new capabilities. The 1634 second data point was chosen for comparisons to be made in order to include comparisons to computational fluid dynamics solutions. The Knudsen number at this point in time is such that the DSMC simulations are still tractable and the CFD computations are at the edge of what is considered valid. It is shown that there can be quite a bit of variability in the vibrational temperature inferred from DSMC solutions and that, from how radiative heating is computed, the electronic temperature is much better suited for radiative calculations. To include the radiative portion of heating, the flow-field solutions are post-processed by the non-equilibrium radiation code HARA. Acceptable agreement between CFD and DSMC flow field solutions is demonstrated and the progress of the updates to DAC, along with an appropriate radiative heating solution, are discussed. In addition, future plans to generate more high fidelity radiative heat transfer solutions are discussed.

New chemical-DSMC method in numerical simulation of axisymmetric rarefied reactive flow

NASA Astrophysics Data System (ADS)

Zakeri, Ramin; Kamali Moghadam, Ramin; Mani, Mahmoud

2017-04-01

The modified quantum kinetic (MQK) chemical reaction model introduced by Zakeri et al. is developed for applicable cases in axisymmetric reactive rarefied gas flows using the direct simulation Monte Carlo (DSMC) method. Although, the MQK chemical model uses some modifications in the quantum kinetic (QK) method, it also employs the general soft sphere collision model and Stockmayer potential function to properly select the collision pairs in the DSMC algorithm and capture both the attraction and repulsion intermolecular forces in rarefied gas flows. For assessment of the presented model in the simulation of more complex and applicable reacting flows, first, the air dissociation is studied in a single cell for equilibrium and non-equilibrium conditions. The MQK results agree well with the analytical and experimental data and they accurately predict the characteristics of the rarefied flowfield with chemical reaction. To investigate accuracy of the MQK chemical model in the simulation of the axisymmetric flow, air dissociation is also assessed in an axial hypersonic flow around two geometries, the sphere as a benchmark case and the blunt body (STS-2) as an applicable test case. The computed results including the transient, rotational and vibrational temperatures, species concentration in the stagnation line, and also the heat flux and pressure coefficient on the surface are compared with those of the other chemical methods like the QK and total collision energy (TCE) models and available analytical and experimental data. Generally, the MQK chemical model properly simulates the chemical reactions and predicts flowfield characteristics more accurate rather than the typical QK model. Although in some cases, results of the MQK approaches match with those of the TCE method, the main point is that the MQK does not need any experimental data or unrealistic assumption of specular boundary condition as used in the TCE method. Another advantage of the MQK model is the significant reduction of computational cost rather than the QK chemical model to reach the same accuracy because of applying more proper collision model and consequently, decrease of the particles collision number.

Review of blunt body wake flows at hypersonic low density conditions

NASA Technical Reports Server (NTRS)

Moss, J. N.; Price, J. M.

1996-01-01

Recent results of experimental and computational studies concerning hypersonic flows about blunted cones including their near wake are reviewed. Attention is focused on conditions where rarefaction effects are present, particularly in the wake. The experiments have been performed for a common model configuration (70 deg spherically-blunted cone) in five hypersonic facilities that encompass a significant range of rarefaction and nonequilibrium effects. Computational studies using direct simulation Monte Carlo (DSMC) and Navier-Stokes solvers have been applied to selected experiments performed in each of the facilities. In addition, computations have been made for typical flight conditions in both Earth and Mars atmospheres, hence more energetic flows than produced in the ground-based tests. Also, comparisons of DSMC calculations and forebody measurements made for the Japanese Orbital Reentry Experiment (OREX) vehicle (a 50 deg spherically-blunted cone) are presented to bridge the spectrum of ground to flight conditions.

Particle kinetic simulation of high altitude hypervelocity flight

NASA Technical Reports Server (NTRS)

Haas, Brian L.

1993-01-01

In this grant period, the focus has been on enhancement and application of the direct simulation Monte Carlo (DSMC) particle method for computing hypersonic flows of re-entry vehicles. Enhancement efforts dealt with modeling gas-gas interactions for thermal non-equilibrium relaxation processes and gas-surface interactions for prediction of vehicle surface temperatures. Both are important for application to problems of engineering interest. The code was employed in a parametric study to improve future applications, and in simulations of aeropass maneuvers in support of the Magellan mission. Detailed comparisons between continuum models for internal energy relaxation and DSMC models reveals that several discrepancies exist. These include definitions of relaxation parameters and the methodologies for implementing them in DSMC codes. These issues were clarified and all differences were rectified in a paper (Appendix A) submitted to Physics of Fluids A, featuring several key figures in the DSMC community as co-authors and B. Haas as first author. This material will be presented at the Fluid Dynamics meeting of the American Physical Society on November 21, 1993. The aerodynamics of space vehicles in highly rarefied flows are very sensitive to the vehicle surface temperatures. Rather than require prescribed temperature estimates for spacecraft as is typically done in DSMC methods, a new technique was developed which couples the dynamic surface heat transfer characteristics into the DSMC flow simulation code to compute surface temperatures directly. This model, when applied to thin planar bodies such as solar panels, was described in AIAA Paper No. 93-2765 (Appendix B) and was presented at the Thermophysics Conference in July 1993. The paper has been submitted to the Journal of Thermophysics and Heat Transfer. Application of the DSMC method to problems of practical interest requires a trade off between solution accuracy and computational expense and limitations. A parametric study was performed and reported in AIAA Paper No. 93-2806 (Appendix C) which assessed the accuracy penalties associated with simulations of varying grid resolution and flow domain size. The paper was also presented at the Thermophysics Conference and will be submitted to the journal shortly. Finally, the DSMC code was employed to assess the pitch, yaw, and roll aerodynamics of the Magellan spacecraft during entry into the Venus atmosphere at off-design attitudes. This work was in support of the Magellan aerobraking maneuver of May 25-Aug. 3, 1993. Furthermore, analysis of the roll characteristics of the configuration with canted solar panels was performed in support of the proposed 'Windmill' experiment. Results were reported in AIAA Paper No. 93-3676 (Appendix D) presented at the Atmospheric Flight Mechanics Conference in August 1993, and were submitted to Journal of Spacecraft and Rockets.

DSMC Simulations of Blunt Body Flows for Mars Entries: Mars Pathfinder and Mars Microprobe Capsules

NASA Technical Reports Server (NTRS)

Moss, James N.; Wilmoth, Richard G.; Price, Joseph M.

1997-01-01

The hypersonic transitional flow aerodynamics of the Mars Pathfinder and Mars Microprobe capsules are simulated with the direct simulation Monte Carlo method. Calculations of axial, normal, and static pitching coefficients were obtained over an angle of attack range comparable to actual flight requirements. Comparisons are made with modified Newtonian and free-molecular-flow calculations. Aerothermal results were also obtained for zero incidence entry conditions.

DSMC simulations of vapor transport toward development of the lithium vapor box divertor concept

NASA Astrophysics Data System (ADS)

Jagoe, Christopher; Schwartz, Jacob; Goldston, Robert

2016-10-01

The lithium vapor divertor box concept attempts to achieve volumetric dissipation of the high heat efflux from a fusion power system. The vapor extracts the heat of the incoming plasma by ionization and radiation, while remaining localized in the vapor box due to differential pumping based on rapid condensation. Preliminary calculations with lithium vapor at densities appropriate for an NSTX-U-scale machine give Knudsen numbers between 0.01 and 1, outside both the range of continuum fluid dynamics and of collisionless Monte Carlo. The direct-simulation Monte Carlo (DSMC) method, however, can simulate rarefied gas flows in this regime. Using the solver contained in the OpenFOAM package, pressure-driven flows of water vapor will be analyzed. The use of water vapor in the relevant range of Knudsen number allows for a flexible similarity experiment to verify the reliability of the code before moving to tests with lithium. The simulation geometry consists of chains of boxes on a temperature gradient, connected by slots with widths that are a representative fraction of the dimensions of the box. We expect choked flow, sonic shocks, and order-of-magnitude pressure and density drops from box to box, but this expectation will be tested in the simulation and then experiment. This work is supported by the Princeton Environmental Institute.

Effects of neutral distribution and external magnetic field on plasma momentum in electrodeless plasma thrusters

NASA Astrophysics Data System (ADS)

Takase, Kazuki; Takahashi, Kazunori; Takao, Yoshinori

2018-02-01

The effects of neutral distribution and an external magnetic field on plasma distribution and thruster performance are numerically investigated using a particle-in-cell simulation with Monte Carlo collisions (PIC-MCC) and the direct simulation Monte Carlo (DSMC) method. The modeled thruster consists of a quartz tube 1 cm in diameter and 3 cm in length, where a double-turn rf loop antenna is wound at the center of the tube and a solenoid is placed between the loop antenna and the downstream tube exit. A xenon propellant is introduced from both the upstream and downstream sides of the thruster, and the flow rates are varied while maintaining the total gas flow rate of 30 μg/s. The PIC-MCC calculations have been conducted using the neutral distribution obtained from the DSMC calculations, which were applied with different strengths of the magnetic field. The numerical results show that both the downstream gas injection and the external magnetic field with a maximum strength near the thruster exit lead to a shift of the plasma density peak from the upstream to the downstream side. Consequently, a larger total thrust is obtained when increasing the downstream gas injection and the magnetic field strength, which qualitatively agrees with a previous experiment using a helicon plasma source.

TiOx deposited by magnetron sputtering: a joint modelling and experimental study

NASA Astrophysics Data System (ADS)

Tonneau, R.; Moskovkin, P.; Pflug, A.; Lucas, S.

2018-05-01

This paper presents a 3D multiscale simulation approach to model magnetron reactive sputter deposition of TiOx⩽2 at various O2 inlets and its validation against experimental results. The simulation first involves the transport of sputtered material in a vacuum chamber by means of a three-dimensional direct simulation Monte Carlo (DSMC) technique. Second, the film growth at different positions on a 3D substrate is simulated using a kinetic Monte Carlo (kMC) method. When simulating the transport of species in the chamber, wall chemistry reactions are taken into account in order to get the proper content of the reactive species in the volume. Angular and energy distributions of particles are extracted from DSMC and used for film growth modelling by kMC. Along with the simulation, experimental deposition of TiOx coatings on silicon samples placed at different positions on a curved sample holder was performed. The experimental results are in agreement with the simulated ones. For a given coater, the plasma phase hysteresis behaviour, film composition and film morphology are predicted. The used methodology can be applied to any coater and any films. This paves the way to the elaboration of a virtual coater allowing a user to predict composition and morphology of films deposited in silico.

Comparisons of the Maxwell and CLL gas/surface interaction models using DSMC

NASA Technical Reports Server (NTRS)

Hedahl, Marc O.; Wilmoth, Richard G.

1995-01-01

The behavior of two different models of gas-surface interactions is studied using the Direct Simulation Monte Carlo (DSMC) method. The DSMC calculations examine differences in predictions of aerodynamic forces and heat transfer between the Maxwell and the Cercignani-Lampis-Lord (CLL) models for flat plate configurations at freestream conditions corresponding to a 140 km orbit around Venus. The size of the flat plate represents one of the solar panels on the Magellan spacecraft, and the freestream conditions correspond to those experienced during aerobraking maneuvers. Results are presented for both a single flat plate and a two-plate configuration as a function of angle of attack and gas-surface accommodation coefficients. The two-plate system is not representative of the Magellan geometry but is studied to explore possible experiments that might be used to differentiate between the two gas-surface interaction models. The Maxwell and CLL models produce qualitatively similar results for the aerodynamic forces and heat transfer on a single flat plate. However, the flow fields produced with the two models are qualitatively different for both the single-plate and two-plate calculations. These differences in the flowfield lead to predictions of the angle of attack for maximum heat transfer in a two plate configuration that are distinctly different for the two gas-surface interactions models.

Consistent post-reaction vibrational energy redistribution in DSMC simulations using TCE model

NASA Astrophysics Data System (ADS)

Borges Sebastião, Israel; Alexeenko, Alina

2016-10-01

The direct simulation Monte Carlo (DSMC) method has been widely applied to study shockwaves, hypersonic reentry flows, and other nonequilibrium flow phenomena. Although there is currently active research on high-fidelity models based on ab initio data, the total collision energy (TCE) and Larsen-Borgnakke (LB) models remain the most often used chemistry and relaxation models in DSMC simulations, respectively. The conventional implementation of the discrete LB model, however, may not satisfy detailed balance when recombination and exchange reactions play an important role in the flow energy balance. This issue can become even more critical in reacting mixtures involving polyatomic molecules, such as in combustion. In this work, this important shortcoming is addressed and an empirical approach to consistently specify the post-reaction vibrational states close to thermochemical equilibrium conditions is proposed within the TCE framework. Following Bird's quantum-kinetic (QK) methodology for populating post-reaction states, the new TCE-based approach involves two main steps. The state-specific TCE reaction probabilities for a forward reaction are first pre-computed from equilibrium 0-D simulations. These probabilities are then employed to populate the post-reaction vibrational states of the corresponding reverse reaction. The new approach is illustrated by application to exchange and recombination reactions relevant to H2-O2 combustion processes.

Combining DSMC Simulations and ROSINA/COPS Data of Comet 67P/Churyumov-Gerasimenko to Develop a Realistic Empirical Coma Model and to Determine Accurate Production Rates

NASA Astrophysics Data System (ADS)

Hansen, K. C.; Fougere, N.; Bieler, A. M.; Altwegg, K.; Combi, M. R.; Gombosi, T. I.; Huang, Z.; Rubin, M.; Tenishev, V.; Toth, G.; Tzou, C. Y.

2015-12-01

We have previously published results from the AMPS DSMC (Adaptive Mesh Particle Simulator Direct Simulation Monte Carlo) model and its characterization of the neutral coma of comet 67P/Churyumov-Gerasimenko through detailed comparison with data collected by the ROSINA/COPS (Rosetta Orbiter Spectrometer for Ion and Neutral Analysis/COmet Pressure Sensor) instrument aboard the Rosetta spacecraft [Bieler, 2015]. Results from these DSMC models have been used to create an empirical model of the near comet coma (<200 km) of comet 67P. The empirical model characterizes the neutral coma in a comet centered, sun fixed reference frame as a function of heliocentric distance, radial distance from the comet, local time and declination. The model is a significant improvement over more simple empirical models, such as the Haser model. While the DSMC results are a more accurate representation of the coma at any given time, the advantage of a mean state, empirical model is the ease and speed of use. One use of such an empirical model is in the calculation of a total cometary coma production rate from the ROSINA/COPS data. The COPS data are in situ measurements of gas density and velocity along the ROSETTA spacecraft track. Converting the measured neutral density into a production rate requires knowledge of the neutral gas distribution in the coma. Our empirical model provides this information and therefore allows us to correct for the spacecraft location to calculate a production rate as a function of heliocentric distance. We will present the full empirical model as well as the calculated neutral production rate for the period of August 2014 - August 2015 (perihelion).

Transient Macroscopic Chemistry in the DSMC Method

NASA Astrophysics Data System (ADS)

Goldsworthy, M. J.; Macrossan, M. N.; Abdel-Jawad, M.

2008-12-01

In the Direct Simulation Monte Carlo method, a combination of statistical and deterministic procedures applied to a finite number of `simulator' particles are used to model rarefied gas-kinetic processes. Traditionally, chemical reactions are modelled using information from specific colliding particle pairs. In the Macroscopic Chemistry Method (MCM), the reactions are decoupled from the specific particle pairs selected for collisions. Information from all of the particles within a cell is used to determine a reaction rate coefficient for that cell. MCM has previously been applied to steady flow DSMC simulations. Here we show how MCM can be used to model chemical kinetics in DSMC simulations of unsteady flow. Results are compared with a collision-based chemistry procedure for two binary reactions in a 1-D unsteady shock-expansion tube simulation and during the unsteady development of 2-D flow through a cavity. For the shock tube simulation, close agreement is demonstrated between the two methods for instantaneous, ensemble-averaged profiles of temperature and species mole fractions. For the cavity flow, a high degree of thermal non-equilibrium is present and non-equilibrium reaction rate correction factors are employed in MCM. Very close agreement is demonstrated for ensemble averaged mole fraction contours predicted by the particle and macroscopic methods at three different flow-times. A comparison of the accumulated number of net reactions per cell shows that both methods compute identical numbers of reaction events. For the 2-D flow, MCM required similar CPU and memory resources to the particle chemistry method. The Macroscopic Chemistry Method is applicable to any general DSMC code using any viscosity or non-reacting collision models and any non-reacting energy exchange models. MCM can be used to implement any reaction rate formulations, whether these be from experimental or theoretical studies.

Plume Impingement to the Lunar Surface: A Challenging Problem for DSMC

NASA Technical Reports Server (NTRS)

Lumpkin, Forrest; Marichalar, Jermiah; Piplica, Anthony

2007-01-01

The President's Vision for Space Exploration calls for the return of human exploration of the Moon. The plans are ambitious and call for the creation of a lunar outpost. Lunar Landers will therefore be required to land near predeployed hardware, and the dust storm created by the Lunar Lander's plume impingement to the lunar surface presents a hazard. Knowledge of the number density, size distribution, and velocity of the grains in the dust cloud entrained into the flow is needing to develop mitigation strategies. An initial step to acquire such knowledge is simulating the associated plume impingement flow field. The following paper presents results from a loosely coupled continuum flow solver/Direct Simulation Monte Carlo (DSMC) technique for simulating the plume impingement of the Apollo Lunar module on the lunar surface. These cases were chosen for initial study to allow for comparison with available Apollo video. The relatively high engine thrust and the desire to simulate interesting cases near touchdown result in flow that is nearly entirely continuum. The DSMC region of the flow field was simulated using NASA's DSMC Analysis Code (DAC) and must begin upstream of the impingement shock for the loosely coupled technique to succeed. It was therefore impossible to achieve mean free path resolution with a reasonable number of molecules (say 100 million) as is shown. In order to mitigate accuracy and performance issues when using such large cells, advanced techniques such as collision limiting and nearest neighbor collisions were employed. The final paper will assess the benefits and shortcomings of such techniques. In addition, the effects of plume orientation, plume altitude, and lunar topography, such as craters, on the flow field, the surface pressure distribution, and the surface shear stress distribution are presented.

Axisymmetric Plume Simulations with NASA's DSMC Analysis Code

NASA Technical Reports Server (NTRS)

Stewart, B. D.; Lumpkin, F. E., III

2012-01-01

A comparison of axisymmetric Direct Simulation Monte Carlo (DSMC) Analysis Code (DAC) results to analytic and Computational Fluid Dynamics (CFD) solutions in the near continuum regime and to 3D DAC solutions in the rarefied regime for expansion plumes into a vacuum is performed to investigate the validity of the newest DAC axisymmetric implementation. This new implementation, based on the standard DSMC axisymmetric approach where the representative molecules are allowed to move in all three dimensions but are rotated back to the plane of symmetry by the end of the move step, has been fully integrated into the 3D-based DAC code and therefore retains all of DAC s features, such as being able to compute flow over complex geometries and to model chemistry. Axisymmetric DAC results for a spherically symmetric isentropic expansion are in very good agreement with a source flow analytic solution in the continuum regime and show departure from equilibrium downstream of the estimated breakdown location. Axisymmetric density contours also compare favorably against CFD results for the R1E thruster while temperature contours depart from equilibrium very rapidly away from the estimated breakdown surface. Finally, axisymmetric and 3D DAC results are in very good agreement over the entire plume region and, as expected, this new axisymmetric implementation shows a significant reduction in computer resources required to achieve accurate simulations for this problem over the 3D simulations.

Modeling of molecular nitrogen collisions and dissociation processes for direct simulation Monte Carlo.

PubMed

Parsons, Neal; Levin, Deborah A; van Duin, Adri C T; Zhu, Tong

2014-12-21

The Direct Simulation Monte Carlo (DSMC) method typically used for simulating hypersonic Earth re-entry flows requires accurate total collision cross sections and reaction probabilities. However, total cross sections are often determined from extrapolations of relatively low-temperature viscosity data, so their reliability is unknown for the high temperatures observed in hypersonic flows. Existing DSMC reaction models accurately reproduce experimental equilibrium reaction rates, but the applicability of these rates to the strong thermal nonequilibrium observed in hypersonic shocks is unknown. For hypersonic flows, these modeling issues are particularly relevant for nitrogen, the dominant species of air. To rectify this deficiency, the Molecular Dynamics/Quasi-Classical Trajectories (MD/QCT) method is used to accurately compute collision and reaction cross sections for the N2(Σg+1)-N2(Σg+1) collision pair for conditions expected in hypersonic shocks using a new potential energy surface developed using a ReaxFF fit to recent advanced ab initio calculations. The MD/QCT-computed reaction probabilities were found to exhibit better physical behavior and predict less dissociation than the baseline total collision energy reaction model for strong nonequilibrium conditions expected in a shock. The MD/QCT reaction model compared well with computed equilibrium reaction rates and shock-tube data. In addition, the MD/QCT-computed total cross sections were found to agree well with established variable hard sphere total cross sections.

Simulation of thermal transpiration flow using a high-order moment method

NASA Astrophysics Data System (ADS)

Sheng, Qiang; Tang, Gui-Hua; Gu, Xiao-Jun; Emerson, David R.; Zhang, Yong-Hao

2014-04-01

Nonequilibrium thermal transpiration flow is numerically analyzed by an extended thermodynamic approach, a high-order moment method. The captured velocity profiles of temperature-driven flow in a parallel microchannel and in a micro-chamber are compared with available kinetic data or direct simulation Monte Carlo (DSMC) results. The advantages of the high-order moment method are shown as a combination of more accuracy than the Navier-Stokes-Fourier (NSF) equations and less computation cost than the DSMC method. In addition, the high-order moment method is also employed to simulate the thermal transpiration flow in complex geometries in two types of Knudsen pumps. One is based on micro-mechanized channels, where the effect of different wall temperature distributions on thermal transpiration flow is studied. The other relies on porous structures, where the variation of flow rate with a changing porosity or pore surface area ratio is investigated. These simulations can help to optimize the design of a real Knudsen pump.

DSMC Simulation of Separated Flows About Flared Bodies at Hypersonic Conditions

NASA Technical Reports Server (NTRS)

Moss, James N.

2000-01-01

This paper describes the results of a numerical study of interacting hypersonic flows at conditions that can be produced in ground-based test facilities. The computations are made with the direct simulation Monte Carlo (DSMC) method of Bird. The focus is on Mach 10 flows about flared axisymmetric configurations, both hollow cylinder flares and double cones. The flow conditions are those for which experiments have been or will be performed in the ONERA R5Ch low-density wind tunnel and the Calspan-University of Buffalo Research Center (CUBRC) Large Energy National Shock (LENS) tunnel. The range of flow conditions, model configurations, and model sizes provides a significant range of shock/shock and shock/boundary layer interactions at low Reynolds number conditions. Results presented will highlight the sensitivity of the calculations to grid resolution, contrast the differences in flow structure for hypersonic cold flows and those of more energetic but still low enthalpy flows, and compare the present results with experimental measurements for surface heating, pressure, and extent of separation.

Numerical simulation of rarefied gas flow through a slit

NASA Technical Reports Server (NTRS)

Keith, Theo G., Jr.; Jeng, Duen-Ren; De Witt, Kenneth J.; Chung, Chan-Hong

1990-01-01

Two different approaches, the finite-difference method coupled with the discrete-ordinate method (FDDO), and the direct-simulation Monte Carlo (DSMC) method, are used in the analysis of the flow of a rarefied gas from one reservoir to another through a two-dimensional slit. The cases considered are for hard vacuum downstream pressure, finite pressure ratios, and isobaric pressure with thermal diffusion, which are not well established in spite of the simplicity of the flow field. In the FDDO analysis, by employing the discrete-ordinate method, the Boltzmann equation simplified by a model collision integral is transformed to a set of partial differential equations which are continuous in physical space but are point functions in molecular velocity space. The set of partial differential equations are solved by means of a finite-difference approximation. In the DSMC analysis, three kinds of collision sampling techniques, the time counter (TC) method, the null collision (NC) method, and the no time counter (NTC) method, are used.

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.

Energy Deposition into a Collisional Gas from Optical Lattices Formed in an Optical Cavity (PREPRINT)

DTIC Science & Technology

2008-07-02

In order to cover a range of molecular species, argon , nitrogen, and methane were used as test gases. The polarizability to mass ratio of these gases...Japan, 21-25 July 2008. 14. ABSTRACT The Direct Simulation Monte Carlo (DSMC) method was used to investigate the interaction between argon ...reducing the maximum temperature. The optimal intervening time was found to be 0.7, 1.0 and 0.25 ns for argon , nitrogen, and methane at one atmosphere

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.

Modeling shock waves in an ideal gas: combining the Burnett approximation and Holian's conjecture.

PubMed

He, Yi-Guang; Tang, Xiu-Zhang; Pu, Yi-Kang

2008-07-01

We model a shock wave in an ideal gas by combining the Burnett approximation and Holian's conjecture. We use the temperature in the direction of shock propagation rather than the average temperature in the Burnett transport coefficients. The shock wave profiles and shock thickness are compared with other theories. The results are found to agree better with the nonequilibrium molecular dynamics (NEMD) and direct simulation Monte Carlo (DSMC) data than the Burnett equations and the modified Navier-Stokes theory.

Microscale Modeling of Porous Thermal Protection System Materials

NASA Astrophysics Data System (ADS)

Stern, Eric C.

Ablative thermal protection system (TPS) materials play a vital role in the design of entry vehicles. Most simulation tools for ablative TPS in use today take a macroscopic approach to modeling, which involves heavy empiricism. Recent work has suggested improving the fidelity of the simulations by taking a multi-scale approach to the physics of ablation. In this work, a new approach for modeling ablative TPS at the microscale is proposed, and its feasibility and utility is assessed. This approach uses the Direct Simulation Monte Carlo (DSMC) method to simulate the gas flow through the microstructure, as well as the gas-surface interaction. Application of the DSMC method to this problem allows the gas phase dynamics---which are often rarefied---to be modeled to a high degree of fidelity. Furthermore this method allows for sophisticated gas-surface interaction models to be implemented. In order to test this approach for realistic materials, a method for generating artificial microstructures which emulate those found in spacecraft TPS is developed. Additionally, a novel approach for allowing the surface to move under the influence of chemical reactions at the surface is developed. This approach is shown to be efficient and robust for performing coupled simulation of the oxidation of carbon fibers. The microscale modeling approach is first applied to simulating the steady flow of gas through the porous medium. Predictions of Darcy permeability for an idealized microstructure agree with empirical correlations from the literature, as well as with predictions from computational fluid dynamics (CFD) when the continuum assumption is valid. Expected departures are observed for conditions at which the continuum assumption no longer holds. Comparisons of simulations using a fabricated microstructure to experimental data for a real spacecraft TPS material show good agreement when similar microstructural parameters are used to build the geometry. The approach is then applied to investigating the ablation of porous materials through oxidation. A simple gas surface interaction model is described, and an approach for coupling the surface reconstruction algorithm to the DSMC method is outlined. Simulations of single carbon fibers at representative conditions suggest this approach to be feasible for simulating the ablation of porous TPS materials at scale. Additionally, the effect of various simulation parameters on in-depth morphology is investigated for random fibrous microstructures.

DSMC simulation of two-phase plume flow with UV radiation

NASA Astrophysics Data System (ADS)

Li, Jie; Liu, Ying; Wang, Ning; Jin, Ling

2014-12-01

Rarefied gas-particle two-phase plume in which the phase of particles is liquid or solid flows from a solid propellant rocket of hypersonic vehicle flying at high altitudes, the aluminum oxide particulates not only impact the rarefied gas flow properties, but also make a great difference to plume radiation signature, so the radiation prediction of the rarefied gas-particle two-phase plume flow is very important for space target detection of hypersonic vehicles. Accordingly, this project aims to study the rarefied gas-particle two-phase flow and ultraviolet radiation (UV) characteristics. Considering a two-way interphase coupling of momentum and energy, the direct simulation Monte Carlo (DSMC) method is developed for particle phase change and the particle flow, including particulate collision, coalescence as well as separation, and a Monte Carlo ray trace model is implemented for the particulate UV radiation. A program for the numerical simulation of the gas-particle two-phase flow and radiation in which the gas flow nonequilibrium is strong is implemented as well. Ultraviolet radiation characteristics of the particle phase is studied based on the calculation of the flow field coupled with the radiation calculation, the radiation model for different size particles is analyzed, focusing on the effects of particle emission, absorption, scattering as well as the searchlight emission of the nozzle. A new approach may be proposed to describe the rarefied gas-particle two-phase plume flow and radiation transfer characteristics in this project.

Study of Plume Impingement Effects in the Lunar Lander Environment

NASA Technical Reports Server (NTRS)

Marichalar, Jeremiah; Prisbell, A.; Lumpkin, F.; LeBeau, G.

2010-01-01

Plume impingement effects from the descent and ascent engine firings of the Lunar Lander were analyzed in support of the Lunar Architecture Team under the Constellation Program. The descent stage analysis was performed to obtain shear and pressure forces on the lunar surface as well as velocity and density profiles in the flow field in an effort to understand lunar soil erosion and ejected soil impact damage which was analyzed as part of a separate study. A CFD/DSMC decoupled methodology was used with the Bird continuum breakdown parameter to distinguish the continuum flow from the rarefied flow. The ascent stage analysis was performed to ascertain the forces and moments acting on the Lunar Lander Ascent Module due to the firing of the main engine on take-off. The Reacting and Multiphase Program (RAMP) method of characteristics (MOC) code was used to model the continuum region of the nozzle plume, and the Direct Simulation Monte Carlo (DSMC) Analysis Code (DAC) was used to model the impingement results in the rarefied region. The ascent module (AM) was analyzed for various pitch and yaw rotations and for various heights in relation to the descent module (DM). For the ascent stage analysis, the plume inflow boundary was located near the nozzle exit plane in a region where the flow number density was large enough to make the DSMC solution computationally expensive. Therefore, a scaling coefficient was used to make the DSMC solution more computationally manageable. An analysis of the effectiveness of this scaling technique was performed by investigating various scaling parameters for a single height and rotation of the AM. Because the inflow boundary was near the nozzle exit plane, another analysis was performed investigating three different inflow contours to determine the effects of the flow expansion around the nozzle lip on the final plume impingement results.

N-S/DSMC hybrid simulation of hypersonic flow over blunt body including wakes

NASA Astrophysics Data System (ADS)

Li, Zhonghua; Li, Zhihui; Li, Haiyan; Yang, Yanguang; Jiang, Xinyu

2014-12-01

A hybrid N-S/DSMC method is presented and applied to solve the three-dimensional hypersonic transitional flows by employing the MPC (modular Particle-Continuum) technique based on the N-S and the DSMC method. A sub-relax technique is adopted to deal with information transfer between the N-S and the DSMC. The hypersonic flows over a 70-deg spherically blunted cone under different Kn numbers are simulated using the CFD, DSMC and hybrid N-S/DSMC method. The present computations are found in good agreement with DSMC and experimental results. The present method provides an efficient way to predict the hypersonic aerodynamics in near-continuum transitional flow regime.

Numerical Modeling of Thermal Edge Flow

NASA Astrophysics Data System (ADS)

Ibrayeva, Aizhan

A gas flow can be induced between two interdigitated arrays of thin vanes, when one of the arrays is uniformly heated or cooled. Sharply curved isotherms near the vane edges leads to momentum imbalance among incident particles, which creates Knudsen force to the vane and thermal edge flow in a gas. The flow is observed in a rarefied gas, when the mean free path of the molecules are comparable with the characteristic length scale of the system. In order to understand a physical mechanism of the flow and Knudsen force, the configuration was numerically investigated under different gas rarefication degrees and temperature gradients in the system by direct simulation Monte Carlo (DSMC) method. From simulations, the highest force value is obtained when Knudsen number is around 0.5 and becomes negligible in free molecular and continuum regimes. DSMC results are analyzed from the theoretical point of view and compared to experimental data. Validation of the simulations is done by the RKDG method. An effect of various geometric parameters to the performance of the actuator was investigated and suggestions were made for improved design of the device.

Effect of plasma distribution on propulsion performance in electrodeless plasma thrusters

NASA Astrophysics Data System (ADS)

Takao, Yoshinori; Takase, Kazuki; Takahashi, Kazunori

2016-09-01

A helicon plasma thruster consisting of a helicon plasma source and a magnetic nozzle is one of the candidates for long-lifetime thrusters because no electrodes are employed to generate or accelerate plasma. A recent experiment, however, detected the non-negligible axial momentum lost to the lateral wall boundary, which degrades thruster performance, when the source was operated with highly ionized gases. To investigate this mechanism, we have conducted two-dimensional axisymmetric particle-in-cell (PIC) simulations with the neutral distribution obtained by Direct Simulation Monte Carlo (DSMC) method. The numerical results have indicated that the axially asymmetric profiles of the plasma density and potential are obtained when the strong decay of neutrals occurs at the source downstream. This asymmetric potential profile leads to the accelerated ion towards the lateral wall, leading to the non-negligible net axial force in the opposite direction of the thrust. Hence, to reduce this asymmetric profile by increasing the neutral density at downstream and/or by confining plasma with external magnetic field would result in improvement of the propulsion performance. These effects are also analyzed by PIC/DSMC simulations.

Evaluation of nonequilibrium boundary conditions for hypersonic rarefied gas flows

NASA Astrophysics Data System (ADS)

Le, N. T. P.; Greenshields, Ch. J.; Reese, J. M.

2012-01-01

A new Computational Fluid Dynamics (CFD) solver for high-speed viscous §ows in the OpenFOAM code is validated against published experimental data and Direct Simulation Monte Carlo (DSMC) results. The laminar §at plate and circular cylinder cases are studied for Mach numbers, Ma, ranging from 6 to 12.7, and with argon and nitrogen as working gases. Simulation results for the laminar §at plate cases show that the combination of accommodation coefficient values σu = 0.7 and σT = 1.0 in the Maxwell/Smoluchowski conditions, and the coefficient values A1 = 1.5 and A2 = 1.0 in the second-order velocity slip condition, give best agreement with experimental data of surface pressure. The values σu = 0.7 and σT = 1.0 also give good agreement with DSMC data of surface pressure at the stagnation point in the circular cylinder case at Kn = 0.25. The Langmuir surface adsorption condition is also tested for the laminar §at plate case, but initial results were not as good as the Maxwell/Smoluchowski boundary conditions.

Predicting Flows of Rarefied Gases

NASA Technical Reports Server (NTRS)

LeBeau, Gerald J.; Wilmoth, Richard G.

2005-01-01

DSMC Analysis Code (DAC) is a flexible, highly automated, easy-to-use computer program for predicting flows of rarefied gases -- especially flows of upper-atmospheric, propulsion, and vented gases impinging on spacecraft surfaces. DAC implements the direct simulation Monte Carlo (DSMC) method, which is widely recognized as standard for simulating flows at densities so low that the continuum-based equations of computational fluid dynamics are invalid. DAC enables users to model complex surface shapes and boundary conditions quickly and easily. The discretization of a flow field into computational grids is automated, thereby relieving the user of a traditionally time-consuming task while ensuring (1) appropriate refinement of grids throughout the computational domain, (2) determination of optimal settings for temporal discretization and other simulation parameters, and (3) satisfaction of the fundamental constraints of the method. In so doing, DAC ensures an accurate and efficient simulation. In addition, DAC can utilize parallel processing to reduce computation time. The domain decomposition needed for parallel processing is completely automated, and the software employs a dynamic load-balancing mechanism to ensure optimal parallel efficiency throughout the simulation.

Key issues of ultraviolet radiation of OH at high altitudes

NASA Astrophysics Data System (ADS)

Zhang, Yuhuai; Wan, Tian; Jiang, Jianzheng; Fan, Jing

2014-12-01

Ultraviolet (UV) emissions radiated by hydroxyl (OH) is one of the fundamental elements in the prediction of radiation signature of high-altitude and high-speed vehicle. In this work, the OH A2Σ+→ X2Π ultraviolet emission band behind the bow shock is computed under the experimental condition of the second bow-shock ultraviolet flight (BSUV-2). Four related key issues are discussed, namely, the source of hydrogen element in the high-altitude atmosphere, the formation mechanism of OH species, efficient computational algorithm of trace species in rarefied flows, and accurate calculation of OH emission spectra. Firstly, by analyzing the typical atmospheric model, the vertical distributions of the number densities of different species containing hydrogen element are given. According to the different dominating species containing hydrogen element, the atmosphere is divided into three zones, and the formation mechanism of OH species is analyzed in the different zones. The direct simulation Monte Carlo (DSMC) method and the Navier-Stokes equations are employed to compute the number densities of the different OH electronically and vibrationally excited states. Different to the previous work, the trace species separation (TSS) algorithm is applied twice in order to accurately calculate the densities of OH species and its excited states. Using a non-equilibrium radiation model, the OH ultraviolet emission spectra and intensity at different altitudes are computed, and good agreement is obtained with the flight measured data.

Predictive Modeling in Plasma Reactor and Process Design

NASA Technical Reports Server (NTRS)

Hash, D. B.; Bose, D.; Govindan, T. R.; Meyyappan, M.; Arnold, James O. (Technical Monitor)

1997-01-01

Research continues toward the improvement and increased understanding of high-density plasma tools. Such reactor systems are lauded for their independent control of ion flux and energy enabling high etch rates with low ion damage and for their improved ion velocity anisotropy resulting from thin collisionless sheaths and low neutral pressures. Still, with the transition to 300 mm processing, achieving etch uniformity and high etch rates concurrently may be a formidable task for such large diameter wafers for which computational modeling can play an important role in successful reactor and process design. The inductively coupled plasma (ICP) reactor is the focus of the present investigation. The present work attempts to understand the fundamental physical phenomena of such systems through computational modeling. Simulations will be presented using both computational fluid dynamics (CFD) techniques and the direct simulation Monte Carlo (DSMC) method for argon and chlorine discharges. ICP reactors generally operate at pressures on the order of 1 to 10 mTorr. At such low pressures, rarefaction can be significant to the degree that the constitutive relations used in typical CFD techniques become invalid and a particle simulation must be employed. This work will assess the extent to which CFD can be applied and evaluate the degree to which accuracy is lost in prediction of the phenomenon of interest; i.e., etch rate. If the CFD approach is found reasonably accurate and bench-marked with DSMC and experimental results, it has the potential to serve as a design tool due to the rapid time relative to DSMC. The continuum CFD simulation solves the governing equations for plasma flow using a finite difference technique with an implicit Gauss-Seidel Line Relaxation method for time marching toward a converged solution. The equation set consists of mass conservation for each species, separate energy equations for the electrons and heavy species, and momentum equations for the gas. The sheath is modeled by imposing the Bohm velocity to the ions near the walls. The DSMC method simulates each constituent of the gas as a separate species which would be analogous in CFD to employing separate species mass, momentum, and energy equations. All particles including electrons are moved and allowed to collide with one another with the stipulation that the electrons remain tied to the ions consistent with the concept of ambipolar diffusion. The velocities of the electrons are allowed to be modified during collisions and are not confined to a Maxwellian distribution. These benefits come at a price in terms of computational time and memory. The DSMC and CFD are made as consistent as possible by using similar chemistry and power deposition models. Although the comparison of CFD and DSMC is interesting, the main goal of this work is the increased understanding of high-density plasma flowfields that can then direct improvements in both techniques. This work is unique in the level of the physical models employed in both the DSMC and CFD for high-density plasma reactor applications. For example, the electrons are simulated in the present DSMC work which has not been done before for low temperature plasma processing problems. In the CFD approach, for the first time, the charged particle transport (discharge physics) has been self-consistently coupled to the gas flow and heat transfer.

Nonequilibrium diffusive gas dynamics: Poiseuille microflow

NASA Astrophysics Data System (ADS)

Abramov, Rafail V.; Otto, Jasmine T.

2018-05-01

We test the recently developed hierarchy of diffusive moment closures for gas dynamics together with the near-wall viscosity scaling on the Poiseuille flow of argon and nitrogen in a one micrometer wide channel, and compare it against the corresponding Direct Simulation Monte Carlo computations. We find that the diffusive regularized Grad equations with viscosity scaling provide the most accurate approximation to the benchmark DSMC results. At the same time, the conventional Navier-Stokes equations without the near-wall viscosity scaling are found to be the least accurate among the tested closures.

DSMC modeling of flows with recombination reactions

NASA Astrophysics Data System (ADS)

Gimelshein, Sergey; Wysong, Ingrid

2017-06-01

An empirical microscopic recombination model is developed for the direct simulation Monte Carlo method that complements the extended weak vibrational bias model of dissociation. The model maintains the correct equilibrium reaction constant in a wide range of temperatures by using the collision theory to enforce the number of recombination events. It also strictly follows the detailed balance requirement for equilibrium gas. The model and its implementation are verified with oxygen and nitrogen heat bath relaxation and compared with available experimental data on atomic oxygen recombination in argon and molecular nitrogen.

A Fokker-Planck based kinetic model for diatomic rarefied gas flows

NASA Astrophysics Data System (ADS)

Gorji, M. Hossein; Jenny, Patrick

2013-06-01

A Fokker-Planck based kinetic model is presented here, which also accounts for internal energy modes characteristic for diatomic gas molecules. The model is based on a Fokker-Planck approximation of the Boltzmann equation for monatomic molecules, whereas phenomenological principles were employed for the derivation. It is shown that the model honors the equipartition theorem in equilibrium and fulfills the Landau-Teller relaxation equations for internal degrees of freedom. The objective behind this approximate kinetic model is accuracy at reasonably low computational cost. This can be achieved due to the fact that the resulting stochastic differential equations are continuous in time; therefore, no collisions between the simulated particles have to be calculated. Besides, because of the devised energy conserving time integration scheme, it is not required to resolve the collisional scales, i.e., the mean collision time and the mean free path of molecules. This, of course, gives rise to much more efficient simulations with respect to other particle methods, especially the conventional direct simulation Monte Carlo (DSMC), for small and moderate Knudsen numbers. To examine the new approach, first the computational cost of the model was compared with respect to DSMC, where significant speed up could be obtained for small Knudsen numbers. Second, the structure of a high Mach shock (in nitrogen) was studied, and the good performance of the model for such out of equilibrium conditions could be demonstrated. At last, a hypersonic flow of nitrogen over a wedge was studied, where good agreement with respect to DSMC (with level to level transition model) for vibrational and translational temperatures is shown.

DSMC Simulations of High Mach Number Taylor-Couette Flow

NASA Astrophysics Data System (ADS)

Pradhan, Sahadev

2017-11-01

The main focus of this work is to characterise the Taylor-Couette flow of an ideal gas between two coaxial cylinders at Mach number Ma =(Uw /√{ kbTw / m }) in the range 0.01

Investigation of the ellipsoidal-statistical Bhatnagar-Gross-Krook kinetic model applied to gas-phase transport of heat and tangential momentum between parallel walls

NASA Astrophysics Data System (ADS)

Gallis, M. A.; Torczynski, J. R.

2011-03-01

The ellipsoidal-statistical Bhatnagar-Gross-Krook (ES-BGK) kinetic model is investigated for steady gas-phase transport of heat, tangential momentum, and mass between parallel walls (i.e., Fourier, Couette, and Fickian flows). This investigation extends the original study of Cercignani and Tironi, who first applied the ES-BGK model to heat transport (i.e., Fourier flow) shortly after this model was proposed by Holway. The ES-BGK model is implemented in a molecular-gas-dynamics code so that results from this model can be compared directly to results from the full Boltzmann collision term, as computed by the same code with the direct simulation Monte Carlo (DSMC) algorithm of Bird. A gas of monatomic molecules is considered. These molecules collide in a pairwise fashion according to either the Maxwell or the hard-sphere interaction and reflect from the walls according to the Cercignani-Lampis-Lord model with unity accommodation coefficients. Simulations are performed at pressures from near-free-molecular to near-continuum. Unlike the BGK model, the ES-BGK model produces heat-flux and shear-stress values that both agree closely with the DSMC values at all pressures. However, for both interactions, the ES-BGK model produces molecular-velocity-distribution functions that are qualitatively similar to those determined for the Maxwell interaction from Chapman-Enskog theory for small wall temperature differences and moment-hierarchy theory for large wall temperature differences. Moreover, the ES-BGK model does not produce accurate values of the mass self-diffusion coefficient for either interaction. Nevertheless, given its reasonable accuracy for heat and tangential-momentum transport, its sound theoretical foundation (it obeys the H-theorem), and its available extension to polyatomic molecules, the ES-BGK model may be a useful method for simulating certain classes of single-species noncontinuum gas flows, as Cercignani suggested.

Investigation on a coupled CFD/DSMC method for continuum-rarefied flows

NASA Astrophysics Data System (ADS)

Tang, Zhenyu; He, Bijiao; Cai, Guobiao

2012-11-01

The purpose of the present work is to investigate the coupled CFD/DSMC method using the existing CFD and DSMC codes developed by the authors. The interface between the continuum and particle regions is determined by the gradient-length local Knudsen number. A coupling scheme combining both state-based and flux-based coupling methods is proposed in the current study. Overlapping grids are established between the different grid systems of CFD and DSMC codes. A hypersonic flow over a 2D cylinder has been simulated using the present coupled method. Comparison has been made between the results obtained from both methods, which shows that the coupled CFD/DSMC method can achieve the same precision as the pure DSMC method and obtain higher computational efficiency.

Transport and Distribution of Hydroxyl Radicals and Oxygen Atoms from H2O Photodissociation in the Inner Coma of Comet 67P/Churyumov-Gerasimenko

NASA Astrophysics Data System (ADS)

Lai, Ian-Lin; Su, Cheng-Chin; Ip, Wing-Huen; Wei, Chen-En; Wu, Jong-Shinn; Lo, Ming-Chung; Liao, Ying; Thomas, Nicolas

2016-03-01

With a combination of the Direct Simulation Monte Carlo (DSMC) calculation and test particle computation, the ballistic transport process of the hydroxyl radicals and oxygen atoms produced by photodissociation of water molecules in the coma of comet 67P/Churyumov-Gerasimenko is modelled. We discuss the key elements and essential features of such simulations which results can be compared with the remote-sensing and in situ measurements of cometary gas coma from the Rosetta mission at different orbital phases of this comet.

Numerical Simulation of Transitional, Hypersonic Flows using a Hybrid Particle-Continuum Method

NASA Astrophysics Data System (ADS)

Verhoff, Ashley Marie

Analysis of hypersonic flows requires consideration of multiscale phenomena due to the range of flight regimes encountered, from rarefied conditions in the upper atmosphere to fully continuum flow at low altitudes. At transitional Knudsen numbers there are likely to be localized regions of strong thermodynamic nonequilibrium effects that invalidate the continuum assumptions of the Navier-Stokes equations. Accurate simulation of these regions, which include shock waves, boundary and shear layers, and low-density wakes, requires a kinetic theory-based approach where no prior assumptions are made regarding the molecular distribution function. Because of the nature of these types of flows, there is much to be gained in terms of both numerical efficiency and physical accuracy by developing hybrid particle-continuum simulation approaches. The focus of the present research effort is the continued development of the Modular Particle-Continuum (MPC) method, where the Navier-Stokes equations are solved numerically using computational fluid dynamics (CFD) techniques in regions of the flow field where continuum assumptions are valid, and the direct simulation Monte Carlo (DSMC) method is used where strong thermodynamic nonequilibrium effects are present. Numerical solutions of transitional, hypersonic flows are thus obtained with increased physical accuracy relative to CFD alone, and improved numerical efficiency is achieved in comparison to DSMC alone because this more computationally expensive method is restricted to those regions of the flow field where it is necessary to maintain physical accuracy. In this dissertation, a comprehensive assessment of the physical accuracy of the MPC method is performed, leading to the implementation of a non-vacuum supersonic outflow boundary condition in particle domains, and more consistent initialization of DSMC simulator particles along hybrid interfaces. The relative errors between MPC and full DSMC results are greatly reduced as a direct result of these improvements. Next, a new parameter for detecting rotational nonequilibrium effects is proposed and shown to offer advantages over other continuum breakdown parameters, achieving further accuracy gains. Lastly, the capabilities of the MPC method are extended to accommodate multiple chemical species in rotational nonequilibrium, each of which is allowed to equilibrate independently, enabling application of the MPC method to more realistic atmospheric flows.

Conservative bin-to-bin fractional collisions

NASA Astrophysics Data System (ADS)

Martin, Robert

2016-11-01

Particle methods such as direct simulation Monte Carlo (DSMC) and particle-in-cell (PIC) are commonly used to model rarefied kinetic flows for engineering applications because of their ability to efficiently capture non-equilibrium behavior. The primary drawback to these methods relates to the poor convergence properties due to the stochastic nature of the methods which typically rely heavily on high degrees of non-equilibrium and time averaging to compensate for poor signal to noise ratios. For standard implementations, each computational particle represents many physical particles which further exacerbate statistical noise problems for flow with large species density variation such as encountered in flow expansions and chemical reactions. The stochastic weighted particle method (SWPM) introduced by Rjasanow and Wagner overcome this difficulty by allowing the ratio of real to computational particles to vary on a per particle basis throughout the flow. The DSMC procedure must also be slightly modified to properly sample the Boltzmann collision integral accounting for the variable particle weights and to avoid the creation of additional particles with negative weight. In this work, the SWPM with necessary modification to incorporate the variable hard sphere (VHS) collision cross section model commonly used in engineering applications is first incorporated into an existing engineering code, the Thermophysics Universal Research Framework. The results and computational efficiency are compared to a few simple test cases using a standard validated implementation of the DSMC method along with the adapted SWPM/VHS collision using an octree based conservative phase space reconstruction. The SWPM method is then further extended to combine the collision and phase space reconstruction into a single step which avoids the need to create additional computational particles only to destroy them again during the particle merge. This is particularly helpful when oversampling the collision integral when compared to the standard DSMC method. However, it is found that the more frequent phase space reconstructions can cause added numerical thermalization with low particle per cell counts due to the coarseness of the octree used. However, the methods are expected to be of much greater utility in transient expansion flows and chemical reactions in the future.

Molecular simulation of small Knudsen number flows

NASA Astrophysics Data System (ADS)

Fei, Fei; Fan, Jing

2012-11-01

The direct simulation Monte Carlo (DSMC) method is a powerful particle-based method for modeling gas flows. It works well for relatively large Knudsen (Kn) numbers, typically larger than 0.01, but quickly becomes computationally intensive as Kn decreases due to its time step and cell size limitations. An alternative approach was proposed to relax or remove these limitations, based on replacing pairwise collisions with a stochastic model corresponding to the Fokker-Planck equation [J. Comput. Phys., 229, 1077 (2010); J. Fluid Mech., 680, 574 (2011)]. Similar to the DSMC method, the downside of that approach suffers from computationally statistical noise. To solve the problem, a diffusion-based information preservation (D-IP) method has been developed. The main idea is to track the motion of a simulated molecule from the diffusive standpoint, and obtain the flow velocity and temperature through sampling and averaging the IP quantities. To validate the idea and the corresponding model, several benchmark problems with Kn ˜ 10-3-10-4 have been investigated. It is shown that the IP calculations are not only accurate, but also efficient because they make possible using a time step and cell size over an order of magnitude larger than the mean collision time and mean free path, respectively.

Study of cluster behavior in the riser of CFB by the DSMC method

NASA Astrophysics Data System (ADS)

Liu, H. P.; Liu, D. Y.; Liu, H.

2010-03-01

The flow behaviors of clusters in the riser of a two-dimensional (2D) circulating fluidized bed was numerically studied based on the Euler-Lagrangian approach. Gas turbulence was modeled by means of Large Eddy Simulation (LES). Particle collision was modeled by means of the direct simulation Monte Carlo (DSMC) method. Clusters' hydrodynamic characteristics are obtained using a cluster identification method proposed by sharrma et al. (2000). The descending clusters near the wall region and the up- and down-flowing clusters in the core were studied separately due to their different flow behaviors. The effects of superficial gas velocity on the cluster behavior were analyzed. Simulated results showed that near wall clusters flow downward and the descent velocity is about -45 cm/s. The occurrence frequency of the up-flowing cluster is higher than that of down-flowing cluster in the core of riser. With the increase of superficial gas velocity, the solid concentration and occurrence frequency of clusters decrease, while the cluster axial velocity increase. Simulated results were in agreement with experimental data. The stochastic method used in present paper is feasible for predicting the cluster flow behavior in CFBs.

Rarefied flow past a flat plate at incidence

NASA Technical Reports Server (NTRS)

Dogra, Virendra K.; Moss, James N.; Price, Joseph M.

1988-01-01

Results of a numerical study using the direct simulation Monte Carlo (DSMC) method are presented for the transitional flow about a flat plate at 40 deg incidence. The plate has zero thickness and a length of 1.0 m. The flow conditions simulated are those experienced by the Shuttle Orbiter during reentry at 7.5 km/s. The range of freestream conditions are such that the freestream Knudsen number values are between 0.02 and 8.4, i.e., conditions that encompass most of the transitional flow regime. The DSMC simulations show that transitional effects are evident when compared with free molecule results for all cases considered. The calculated results demonstrate clearly the necessity of having a means of identifying the effects of transitional flow when making aerodynamic flight measurements as are currently being made with the Space Shuttle Orbiter vehicles. Previous flight data analyses have relied exclusively on adjustments in the gas-surface interaction models without accounting for the transitional effect which can be comparable in magnitude. The present calculations show that the transitional effect at 175 km would increase the Space Shuttle Orbiter lift-drag ratio by 90 percent over the free molecule value.

Collisional spreading of Enceladus’ neutral cloud

NASA Astrophysics Data System (ADS)

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

2010-10-01

We describe a direct simulation Monte Carlo (DSMC) model of Enceladus' neutral cloud and compare its results to observations of OH and O orbiting Saturn. The OH and O are observed far from Enceladus (at 3.95 R S), as far out as 25 R S for O. Previous DSMC models attributed this breadth primarily to ion/neutral scattering (including charge exchange) and molecular dissociation. However, the newly reported O observations and a reinterpretation of the OH observations (Melin, H., Shemansky, D.E., Liu, X. [2009] Planet. Space Sci., 57, 1743-1753, PS&S) showed that the cloud is broader than previously thought. We conclude that the addition of neutral/neutral scattering (Farmer, A.J. [2009] Icarus, 202, 280-286), which was underestimated by previous models, brings the model results in line with the new observations. Neutral/neutral collisions primarily happen in the densest part of the cloud, near Enceladus' orbit, but contribute to the spreading by pumping up orbital eccentricity. Based on the cloud model presented here Enceladus maybe the ultimate source of oxygen for the upper atmospheres of Titan and Saturn. We also predict that large quantities of OH, O and H 2O bombard Saturn's icy satellites.

Extension of a Kinetic Approach to Chemical Reactions to Electronic Energy Levels and Reactions Involving Charged Species with Application to DSMC Simulations

NASA Technical Reports Server (NTRS)

Liechty, Derek S.

2014-01-01

The ability to compute rarefied, ionized hypersonic flows is becoming more important as missions such as Earth reentry, landing high mass payloads on Mars, and the exploration of the outer planets and their satellites are being considered. Recently introduced molecular-level chemistry models that predict equilibrium and nonequilibrium reaction rates using only kinetic theory and fundamental molecular properties are extended in the current work to include electronic energy level transitions and reactions involving charged particles. These extensions are shown to agree favorably with reported transition and reaction rates from the literature for near-equilibrium conditions. Also, the extensions are applied to the second flight of the Project FIRE flight experiment at 1634 seconds with a Knudsen number of 0.001 at an altitude of 76.4 km. In order to accomplish this, NASA's direct simulation Monte Carlo code DAC was rewritten to include the ability to simulate charge-neutral ionized flows, take advantage of the recently introduced chemistry model, and to include the extensions presented in this work. The 1634 second data point was chosen for comparisons to be made in order to include a CFD solution. The Knudsen number at this point in time is such that the DSMC simulations are still tractable and the CFD computations are at the edge of what is considered valid because, although near-transitional, the flow is still considered to be continuum. It is shown that the inclusion of electronic energy levels in the DSMC simulation is necessary for flows of this nature and is required for comparison to the CFD solution. The flow field solutions are also post-processed by the nonequilibrium radiation code HARA to compute the radiative portion.

Key issues of ultraviolet radiation of OH at high altitudes

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

Zhang, Yuhuai; Wan, Tian; Jiang, Jianzheng

2014-12-09

Ultraviolet (UV) emissions radiated by hydroxyl (OH) is one of the fundamental elements in the prediction of radiation signature of high-altitude and high-speed vehicle. In this work, the OH A{sup 2}Σ{sup +}→X{sup 2}Π ultraviolet emission band behind the bow shock is computed under the experimental condition of the second bow-shock ultraviolet flight (BSUV-2). Four related key issues are discussed, namely, the source of hydrogen element in the high-altitude atmosphere, the formation mechanism of OH species, efficient computational algorithm of trace species in rarefied flows, and accurate calculation of OH emission spectra. Firstly, by analyzing the typical atmospheric model, the verticalmore » distributions of the number densities of different species containing hydrogen element are given. According to the different dominating species containing hydrogen element, the atmosphere is divided into three zones, and the formation mechanism of OH species is analyzed in the different zones. The direct simulation Monte Carlo (DSMC) method and the Navier-Stokes equations are employed to compute the number densities of the different OH electronically and vibrationally excited states. Different to the previous work, the trace species separation (TSS) algorithm is applied twice in order to accurately calculate the densities of OH species and its excited states. Using a non-equilibrium radiation model, the OH ultraviolet emission spectra and intensity at different altitudes are computed, and good agreement is obtained with the flight measured data.« less

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.

Heavy particle transport in sputtering systems

NASA Astrophysics Data System (ADS)

Trieschmann, Jan

2015-09-01

This contribution aims to discuss the theoretical background of heavy particle transport in plasma sputtering systems such as direct current magnetron sputtering (dcMS), high power impulse magnetron sputtering (HiPIMS), or multi frequency capacitively coupled plasmas (MFCCP). Due to inherently low process pressures below one Pa only kinetic simulation models are suitable. In this work a model appropriate for the description of the transport of film forming particles sputtered of a target material has been devised within the frame of the OpenFOAM software (specifically dsmcFoam). The three dimensional model comprises of ejection of sputtered particles into the reactor chamber, their collisional transport through the volume, as well as deposition of the latter onto the surrounding surfaces (i.e. substrates, walls). An angular dependent Thompson energy distribution fitted to results from Monte-Carlo simulations is assumed initially. Binary collisions are treated via the M1 collision model, a modified variable hard sphere (VHS) model. The dynamics of sputtered and background gas species can be resolved self-consistently following the direct simulation Monte-Carlo (DSMC) approach or, whenever possible, simplified based on the test particle method (TPM) with the assumption of a constant, non-stationary background at a given temperature. At the example of an MFCCP research reactor the transport of sputtered aluminum is specifically discussed. For the peculiar configuration and under typical process conditions with argon as process gas the transport of aluminum sputtered of a circular target is shown to be governed by a one dimensional interaction of the imposed and backscattered particle fluxes. The results are analyzed and discussed on the basis of the obtained velocity distribution functions (VDF). This work is supported by the German Research Foundation (DFG) in the frame of the Collaborative Research Centre TRR 87.

The spatial distribution of water in the inner coma of Comet 9P/Tempel 1: Comparison between models and observations

NASA Astrophysics Data System (ADS)

Finklenburg, S.; Thomas, N.; Su, C. C.; Wu, J.-S.

2014-07-01

The near nucleus coma of Comet 9P/Tempel 1 has been simulated with the 3D Direct Simulation Monte Carlo (DSMC) code PDSC++ (Su, C.-C. [2013]. Parallel Direct Simulation Monte Carlo (DSMC) Methods for Modeling Rarefied Gas Dynamics. PhD Thesis, National Chiao Tung University, Taiwan) and the derived column densities have been compared to observations of the water vapour distribution found by using infrared imaging spectrometer on the Deep Impact spacecraft (Feaga, L.M., A’Hearn, M.F., Sunshine, J.M., Groussin, O., Farnham, T.L. [2007]. Icarus 191(2), 134-145. http://dx.doi.org/10.1016/j.icarus.2007.04.038). Modelled total production rates are also compared to various observations made at the time of the Deep Impact encounter. Three different models were tested. For all models, the shape model constructed from the Deep Impact observations by Thomas et al. (Thomas, P.C., Veverka, J., Belton, M.J.S., Hidy, A., A’Hearn, M.F., Farnham, T.L., et al. [2007]. Icarus, 187(1), 4-15. http://dx.doi.org/10.1016/j.icarus.2006.12.013) was used. Outgassing depending only on the cosine of the solar insolation angle on each shape model facet is shown to provide an unsatisfactory model. Models constructed on the basis of active areas suggested by Kossacki and Szutowicz (Kossacki, K., Szutowicz, S. [2008]. Icarus, 195(2), 705-724. http://dx.doi.org/10.1016/j.icarus.2007.12.014) are shown to be superior. The Kossacki and Szutowicz model, however, also shows deficits which we have sought to improve upon. For the best model we investigate the properties of the outflow.

DSMC Evaluation of the Navier-Stokes Shear Viscosity of a Granular Fluid

DTIC Science & Technology

2005-07-13

transport coefficients of the HCS have been measured from DSMC by using the associated Green – Kubo formulas [8]. In the case of a system heated by the action...DSMC evaluation of the Navier–Stokes shear viscosity of a granular fluid José María Montanero∗, Andrés Santos† and Vicente Garzó† ∗Departamento de...proposed to measure the Navier–Stokes shear viscosity in a granular fluid described by the Enskog equation. The method is implemented in DSMC

Modeling and simulation of radiation from hypersonic flows with Monte Carlo methods

NASA Astrophysics Data System (ADS)

Sohn, Ilyoup

During extreme-Mach number reentry into Earth's atmosphere, spacecraft experience hypersonic non-equilibrium flow conditions that dissociate molecules and ionize atoms. Such situations occur behind a shock wave leading to high temperatures, which have an adverse effect on the thermal protection system and radar communications. Since the electronic energy levels of gaseous species are strongly excited for high Mach number conditions, the radiative contribution to the total heat load can be significant. In addition, radiative heat source within the shock layer may affect the internal energy distribution of dissociated and weakly ionized gas species and the number density of ablative species released from the surface of vehicles. Due to the radiation total heat load to the heat shield surface of the vehicle may be altered beyond mission tolerances. Therefore, in the design process of spacecrafts the effect of radiation must be considered and radiation analyses coupled with flow solvers have to be implemented to improve the reliability during the vehicle design stage. To perform the first stage for radiation analyses coupled with gas-dynamics, efficient databasing schemes for emission and absorption coefficients were developed to model radiation from hypersonic, non-equilibrium flows. For bound-bound transitions, spectral information including the line-center wavelength and assembled parameters for efficient calculations of emission and absorption coefficients are stored for typical air plasma species. Since the flow is non-equilibrium, a rate equation approach including both collisional and radiatively induced transitions was used to calculate the electronic state populations, assuming quasi-steady-state (QSS). The Voigt line shape function was assumed for modeling the line broadening effect. The accuracy and efficiency of the databasing scheme was examined by comparing results of the databasing scheme with those of NEQAIR for the Stardust flowfield. An accuracy of approximately 1 % was achieved with an efficiency about three times faster than the NEQAIR code. To perform accurate and efficient analyses of chemically reacting flowfield - radiation interactions, the direct simulation Monte Carlo (DSMC) and the photon Monte Carlo (PMC) radiative transport methods are used to simulate flowfield - radiation coupling from transitional to peak heating freestream conditions. The non-catalytic and fully catalytic surface conditions were modeled and good agreement of the stagnation-point convective heating between DSMC and continuum fluid dynamics (CFD) calculation under the assumption of fully catalytic surface was achieved. Stagnation-point radiative heating, however, was found to be very different. To simulate three-dimensional radiative transport, the finite-volume based PMC (FV-PMC) method was employed. DSMC - FV-PMC simulations with the goal of understanding the effect of radiation on the flow structure for different degrees of hypersonic non-equilibrium are presented. It is found that except for the highest altitudes, the coupling of radiation influences the flowfield, leading to a decrease in both heavy particle translational and internal temperatures and a decrease in the convective heat flux to the vehicle body. The DSMC - FV-PMC coupled simulations are compared with the previous coupled simulations and correlations obtained using continuum flow modeling and one-dimensional radiative transport. The modeling of radiative transport is further complicated by radiative transitions occurring during the excitation process of the same radiating gas species. This interaction affects the distribution of electronic state populations and, in turn, the radiative transport. The radiative transition rate in the excitation/de-excitation processes and the radiative transport equation (RTE) must be coupled simultaneously to account for non-local effects. The QSS model is presented to predict the electronic state populations of radiating gas species taking into account non-local radiation. The definition of the escape factor which is dependent on the incoming radiative intensity from over all directions is presented. The effect of the escape factor on the distribution of electronic state populations of the atomic N and O radiating species is examined in a highly non-equilibrium flow condition using DSMC and PMC methods and the corresponding change of the radiative heat flux due to the non-local radiation is also investigated.

DSMC Simulations in Support of the Columbia Shuttle Orbiter Accident Investigation

NASA Technical Reports Server (NTRS)

Boyles, Katie; LeBeau, Gerald J.; Gallis, Michael A.

2004-01-01

Three-dimensional Direct Simulation Monte Carlo simulations of Columbia Shuttle Orbiter flight STS-107 are presented. The aim of this work is to determine the aerodynamic and heating behavior of the Orbiter during aerobraking maneuvers and to provide piecewise integration of key scenario events to assess the plausibility of the candidate failure scenarios. The flight of the Orbiter is examined at two altitudes: 350-kft and 300-kft. The flowfield around the Orbiter and the heat transfer to it are calculated for the undamaged configuration. The flow inside the wing for an assumed damage to the leading edge in the form of a 10- inch hole is studied.

Direct simulation with vibration-dissociation coupling

NASA Technical Reports Server (NTRS)

Hash, David B.; Hassan, H. A.

1992-01-01

The majority of implementations of the Direct Simulation Monte Carlo (DSMC) method of Bird do not account for vibration-dissociation coupling. Haas and Boyd have proposed the vibrationally-favored dissociation model to accomplish this task. This model requires measurements of induction distance to determine model constants. A more general expression has been derived that does not require any experimental input. The model is used to calculate one-dimensional shock waves in nitrogen and the flow past a lunar transfer vehicle (LTV). For the conditions considered in the simulation, the influence of vibration-dissociation coupling on heat transfer in the stagnation region of the LTV can be significant.

N2 Temperature of Vibration instrument for sounding rocket observation in the lower thermosphere

NASA Astrophysics Data System (ADS)

Kurihara, J.; Iwagami, N.; Oyama, K.-I.

2013-11-01

The N2 Temperature of Vibration (NTV) instrument was developed to study energetics and structure of the lower thermosphere, applying the Electron Beam Fluorescence (EBF) technique to measurements of vibrational temperature, rotational temperature and number density of atmospheric N2. The sounding rocket experiments using this instrument have been conducted four times, including one failure of the electron gun. Aerodynamic effects on the measurement caused by the supersonic motion of the rocket were analyzed quantitatively using three-dimensional simulation of Direct Simulation Monte Carlo (DSMC) method, and the absolute density profile was obtained through the correction of the spin modulation.

Hypersonic separated flows about "tick" configurations with sensitivity to model design

NASA Astrophysics Data System (ADS)

Moss, J. N.; O'Byrne, S.; Gai, S. L.

2014-12-01

This paper presents computational results obtained by applying the direct simulation Monte Carlo (DSMC) method for hypersonic nonequilibrium flow about "tick-shaped" model configurations. These test models produces a complex flow where the nonequilibrium and rarefied aspects of the flow are initially enhanced as the flow passes over an expansion surface, and then the flow encounters a compression surface that can induce flow separation. The resulting flow is such that meaningful numerical simulations must have the capability to account for a significant range of rarefaction effects; hence the application of the DSMC method in the current study as the flow spans several flow regimes, including transitional, slip, and continuum. The current focus is to examine the sensitivity of both the model surface response (heating, friction and pressure) and flowfield structure to assumptions regarding surface boundary conditions and more extensively the impact of model design as influenced by leading edge configuration as well as the geometrical features of the expansion and compression surfaces. Numerical results indicate a strong sensitivity to both the extent of the leading edge sharpness and the magnitude of the leading edge bevel angle. Also, the length of the expansion surface for a fixed compression surface has a significant impact on the extent of separated flow.

A diffusive information preservation method for small Knudsen number flows

NASA Astrophysics Data System (ADS)

Fei, Fei; Fan, Jing

2013-06-01

The direct simulation Monte Carlo (DSMC) method is a powerful particle-based method for modeling gas flows. It works well for relatively large Knudsen (Kn) numbers, typically larger than 0.01, but quickly becomes computationally intensive as Kn decreases due to its time step and cell size limitations. An alternative approach was proposed to relax or remove these limitations, based on replacing pairwise collisions with a stochastic model corresponding to the Fokker-Planck equation [J. Comput. Phys., 229, 1077 (2010); J. Fluid Mech., 680, 574 (2011)]. Similar to the DSMC method, the downside of that approach suffers from computationally statistical noise. To solve the problem, a diffusion-based information preservation (D-IP) method has been developed. The main idea is to track the motion of a simulated molecule from the diffusive standpoint, and obtain the flow velocity and temperature through sampling and averaging the IP quantities. To validate the idea and the corresponding model, several benchmark problems with Kn ˜ 10-3-10-4 have been investigated. It is shown that the IP calculations are not only accurate, but also efficient because they make possible using a time step and cell size over an order of magnitude larger than the mean collision time and mean free path, respectively.

Hypersonic Separated Flows About "Tick" Configurations With Sensitivity to Model Design

NASA Technical Reports Server (NTRS)

Moss, J. N.; O'Byrne, S.; Gai, S. L.

2014-01-01

This paper presents computational results obtained by applying the direct simulation Monte Carlo (DSMC) method for hypersonic nonequilibrium flow about "tick-shaped" model configurations. These test models produces a complex flow where the nonequilibrium and rarefied aspects of the flow are initially enhanced as the flow passes over an expansion surface, and then the flow encounters a compression surface that can induce flow separation. The resulting flow is such that meaningful numerical simulations must have the capability to account for a significant range of rarefaction effects; hence the application of the DSMC method in the current study as the flow spans several flow regimes, including transitional, slip, and continuum. The current focus is to examine the sensitivity of both the model surface response (heating, friction and pressure) and flowfield structure to assumptions regarding surface boundary conditions and more extensively the impact of model design as influenced by leading edge configuration as well as the geometrical features of the expansion and compression surfaces. Numerical results indicate a strong sensitivity to both the extent of the leading edge sharpness and the magnitude of the leading edge bevel angle. Also, the length of the expansion surface for a fixed compression surface has a significant impact on the extent of separated flow.

Numerical investigation of rarefaction effects in the vicinity of a sharp leading edge

NASA Astrophysics Data System (ADS)

Pan, Shaowu; Gao, Zhenxun; Lee, Chunhian

2014-12-01

This paper presents a study of rarefaction effect on hypersonic flow over a sharp leading edge. Both continuum approach and kinetic method: a widely spread commercial Computational Fluid Dynamics-Navior-Stokes-Fourier (CFD-NSF) software - Fluent together with a direct simulation Monte Carlo (DSMC) code developed by the authors are employed for simulation of transition regime with Knudsen number ranging from 0.005 to 0.2. It is found that Fluent can predict the wall fluxes in the case of hypersonic argon flow over the sharp leading edge for the lowest Kn case (Kn = 0.005) in current paper while for other cases it also has a good agreement with DSMC except at the location near the sharp leading edge. Among all of the wall fluxes, it is found that coefficient of pressure is the most sensitive to rarefaction while heat transfer is the least one. A parameter based on translational nonequilibrium and a cut-off value of 0.34 is proposed for continuum breakdown in this paper. The structure of entropy and velocity profile in boundary layer is analyzed. Also, it is found that the ratio of heat transfer coefficient to skin friction coefficient remains uniform along the surface for the four cases in this paper.

Lattice Boltzmann simulation of nonequilibrium effects in oscillatory gas flow.

PubMed

Tang, G H; Gu, X J; Barber, R W; Emerson, D R; Zhang, Y H

2008-08-01

Accurate evaluation of damping in laterally oscillating microstructures is challenging due to the complex flow behavior. In addition, device fabrication techniques and surface properties will have an important effect on the flow characteristics. Although kinetic approaches such as the direct simulation Monte Carlo (DSMC) method and directly solving the Boltzmann equation can address these challenges, they are beyond the reach of current computer technology for large scale simulation. As the continuum Navier-Stokes equations become invalid for nonequilibrium flows, we take advantage of the computationally efficient lattice Boltzmann method to investigate nonequilibrium oscillating flows. We have analyzed the effects of the Stokes number, Knudsen number, and tangential momentum accommodation coefficient for oscillating Couette flow and Stokes' second problem. Our results are in excellent agreement with DSMC data for Knudsen numbers up to Kn=O(1) and show good agreement for Knudsen numbers as large as 2.5. In addition to increasing the Stokes number, we demonstrate that increasing the Knudsen number or decreasing the accommodation coefficient can also expedite the breakdown of symmetry for oscillating Couette flow. This results in an earlier transition from quasisteady to unsteady flow. Our paper also highlights the deviation in velocity slip between Stokes' second problem and the confined Couette case.

A study of internal energy relaxation in shocks using molecular dynamics based models

NASA Astrophysics Data System (ADS)

Li, Zheng; Parsons, Neal; Levin, Deborah A.

2015-10-01

Recent potential energy surfaces (PESs) for the N2 + N and N2 + N2 systems are used in molecular dynamics (MD) to simulate rates of vibrational and rotational relaxations for conditions that occur in hypersonic flows. For both chemical systems, it is found that the rotational relaxation number increases with the translational temperature and decreases as the rotational temperature approaches the translational temperature. The vibrational relaxation number is observed to decrease with translational temperature and approaches the rotational relaxation number in the high temperature region. The rotational and vibrational relaxation numbers are generally larger in the N2 + N2 system. MD-quasi-classical trajectory (QCT) with the PESs is also used to calculate the V-T transition cross sections, the collision cross section, and the dissociation cross section for each collision pair. Direct simulation Monte Carlo (DSMC) results for hypersonic flow over a blunt body with the total collision cross section from MD/QCT simulations, Larsen-Borgnakke with new relaxation numbers, and the N2 dissociation rate from MD/QCT show a profile with a decreased translational temperature and a rotational temperature close to vibrational temperature. The results demonstrate that many of the physical models employed in DSMC should be revised as fundamental potential energy surfaces suitable for high temperature conditions become available.

DSMC simulations of shock tube experiments for the dissociation rate of nitrogen

NASA Astrophysics Data System (ADS)

Bird, G. A.

2012-11-01

The DSMC method has been used to simulate the flow associated with several experiments that led to predictions of the dissociation rate in nitrogen. One involved optical interferometry to determine the density behind strong shock wave and the other involved the measurement of the shock tube end-wall pressure after the reflection of a similar shock wave. DSMC calculations for the un-reflected shock wave were made with the older TCE model that converts rate coefficients to reaction cross-sections, with the newer Q-K model that predicts the rates and with a set of reaction cross-sections for nitrogen dissociation from QCT calculations. A comparison of the resulting density profiles with the measured profile provides a test of the validity of the DSMC chemistry models. The DSMC reaction rates were sampled directly in the DSMC calculation, both far downstream where the flow is in equilibrium and in the non-equilibrium region immediately behind the shock. This permits a critical evaluation of data reduction procedures that were employed to deduce the dissociation rate from the measured quantities.

Gas flow in the near-surface porous boundary layer of the 67P/Churyumov-Gerasimenko using micro-CT images

NASA Astrophysics Data System (ADS)

Christou, Chariton; Kokou Dadzie, S.; Thomas, Nicolas; Hartogh, Paul; Jorda, Laurent; Kührt, Ekkehard; Whitby, James; Wright, Ian; Zarnecki, John

2017-04-01

While ESA's Rosetta mission has formally been completed, the data analysis and interpretation continues. Here, we address the physics of the gas flow at the surface of the comet. Understanding the sublimation of ice at the surface of the nucleus provides the initial boundary condition for studying the inner coma. The gas flow at the surface of the comet 67P/Churyumov-Gerasimenko can be in the rarefaction regime and a non-Maxwellian velocity distribution may be present. In these cases, continuum methods like Navier-Stokes-Fourier (NSF) set of equations are rarely applicable. Discrete particle methods such as Direct Simulation Monte Carlo (DSMC) method are usually adopted. DSMC is currently the dominant numerical method to study rarefied gas flows. It has been widely used to study cometary outflow over past years .1,2. In the present study, we investigate numerically, gas transport near the surface of the nucleus using DSMC. We focus on the outgassing from the near surface boundary layer into the vacuum (˜20 cm above the nucleus surface). Simulations are performed using the open source code dsmcFoam on an unstructured grid. Until now, artificially generated random porous media formed by packed spheres have been used to represent the comet surface boundary layer structure .3. In the present work, we used instead Micro-computerized-tomography (micro-CT) scanned images to provide geologically realistic 3D representations of the boundary layer porous structure. The images are from earth basins. The resolution is relatively high - in the range of some μm. Simulations from different rock samples with high porosity (and comparable to those expected at 67P) are compared. Gas properties near the surface boundary layer are presented and characterized. We have identified effects of the various porous structure properties on the gas flow fields. Temperature, density and velocity profiles have also been analyzed. .1. J.-F. Crifo, G. Loukianov, A. Rodionov and V. Zakharov, Icarus 176 (1), 192-219 (2005). 2. Y. Liao, C. Su, R. Marschall, J. Wu, M. Rubin, I. Lai, W. Ip, H. Keller, J. Knollenberg and E. Kührt, Earth, Moon, and Planets 117 (1), 41-64 (2016). 3. Y. V. Skorov, R. Van Lieshout, J. Blum and H. U. Keller, Icarus 212 (2), 867-876 (2011).

A parametric study of Enceladus plumes based on DSMC calculations for retrieving the outgassing parameters as measured by Cassini instruments

NASA Astrophysics Data System (ADS)

Mahieux, Arnaud; Goldstein, David B.; Varghese, Philip; Trafton, Laurence M.

2017-10-01

The vapor and particulate plumes arising from the southern polar regions of Enceladus are a key signature of what lies below the surface. Multiple Cassini instruments (INMS, CDA, CAPS, MAG, UVIS, VIMS, ISS) measured the gas-particle plume over the warm Tiger Stripe region and there have been several close flybys. Numerous observations also exist of the near-vent regions in the visible and the IR. The most likely source for these extensive geysers is a subsurface liquid reservoir of somewhat saline water and other volatiles boiling off through crevasse-like conduits into the vacuum of space.In this work, we use a DSMC code to simulate the plume as it exits a vent, considering axisymmetric conditions, in a vertical domain extending up to 10 km. Above 10 km altitude, the flow is collisionless and well modeled in a separate free molecular code. We perform a DSMC parametric and sensitivity study of the following vent parameters: vent diameter, outgassed flow density, water gas/water ice mass flow ratio, gas and ice speed, and ice grain diameter. We build parametric expressions of the plume characteristics at the 10 km upper boundary (number density, temperature, velocity) that will be used in a Bayesian inversion algorithm in order to constrain source conditions from fits to plume observations by various instruments on board the Cassini spacecraft and assess the parametric sensitivity study.

Assessment of predictive capabilities for aerodynamic heating in hypersonic flow

NASA Astrophysics Data System (ADS)

Knight, Doyle; Chazot, Olivier; Austin, Joanna; Badr, Mohammad Ali; Candler, Graham; Celik, Bayram; Rosa, Donato de; Donelli, Raffaele; Komives, Jeffrey; Lani, Andrea; Levin, Deborah; Nompelis, Ioannis; Panesi, Marco; Pezzella, Giuseppe; Reimann, Bodo; Tumuklu, Ozgur; Yuceil, Kemal

2017-04-01

The capability for CFD prediction of hypersonic shock wave laminar boundary layer interaction was assessed for a double wedge model at Mach 7.1 in air and nitrogen at 2.1 MJ/kg and 8 MJ/kg. Simulations were performed by seven research organizations encompassing both Navier-Stokes and Direct Simulation Monte Carlo (DSMC) methods as part of the NATO STO AVT Task Group 205 activity. Comparison of the CFD simulations with experimental heat transfer and schlieren visualization suggest the need for accurate modeling of the tunnel startup process in short-duration hypersonic test facilities, and the importance of fully 3-D simulations of nominally 2-D (i.e., non-axisymmmetric) experimental geometries.

Extension of a Kinetic Approach to Chemical Reactions to Electronic Energy Levels and Reactions Involving Charged Species With Application to DSMC Simulations

NASA Technical Reports Server (NTRS)

Liechty, Derek S.

2013-01-01

The ability to compute rarefied, ionized hypersonic flows is becoming more important as missions such as Earth reentry, landing high mass payloads on Mars, and the exploration of the outer planets and their satellites are being considered. Recently introduced molecular-level chemistry models that predict equilibrium and nonequilibrium reaction rates using only kinetic theory and fundamental molecular properties are extended in the current work to include electronic energy level transitions and reactions involving charged particles. These extensions are shown to agree favorably with reported transition and reaction rates from the literature for nearequilibrium conditions. Also, the extensions are applied to the second flight of the Project FIRE flight experiment at 1634 seconds with a Knudsen number of 0.001 at an altitude of 76.4 km. In order to accomplish this, NASA's direct simulation Monte Carlo code DAC was rewritten to include the ability to simulate charge-neutral ionized flows, take advantage of the recently introduced chemistry model, and to include the extensions presented in this work. The 1634 second data point was chosen for comparisons to be made in order to include a CFD solution. The Knudsen number at this point in time is such that the DSMC simulations are still tractable and the CFD computations are at the edge of what is considered valid because, although near-transitional, the flow is still considered to be continuum. It is shown that the inclusion of electronic energy levels in the DSMC simulation is necessary for flows of this nature and is required for comparison to the CFD solution. The flow field solutions are also post-processed by the nonequilibrium radiation code HARA to compute the radiative portion of the heating and is then compared to the total heating measured in flight.

Pre- and Post-equinox ROSINA production rates calculated using a realistic empirical coma model derived from AMPS-DSMC simulations of comet 67P/Churyumov-Gerasimenko

NASA Astrophysics Data System (ADS)

Hansen, Kenneth; Altwegg, Kathrin; Berthelier, Jean-Jacques; Bieler, Andre; Calmonte, Ursina; Combi, Michael; De Keyser, Johan; Fiethe, Björn; Fougere, Nicolas; Fuselier, Stephen; Gombosi, Tamas; Hässig, Myrtha; Huang, Zhenguang; Le Roy, Lena; Rubin, Martin; Tenishev, Valeriy; Toth, Gabor; Tzou, Chia-Yu

2016-04-01

We have previously used results from the AMPS DSMC (Adaptive Mesh Particle Simulator Direct Simulation Monte Carlo) model to create an empirical model of the near comet coma (<400 km) of comet 67P for the pre-equinox orbit of comet 67P/Churyumov-Gerasimenko. In this work we extend the empirical model to the post-equinox, post-perihelion time period. In addition, we extend the coma model to significantly further from the comet (~100,000-1,000,000 km). The empirical model characterizes the neutral coma in a comet centered, sun fixed reference frame as a function of heliocentric distance, radial distance from the comet, local time and declination. Furthermore, we have generalized the model beyond application to 67P by replacing the heliocentric distance parameterizations and mapping them to production rates. Using this method, the model become significantly more general and can be applied to any comet. The model is a significant improvement over simpler empirical models, such as the Haser model. For 67P, the DSMC results are, of course, a more accurate representation of the coma at any given time, but the advantage of a mean state, empirical model is the ease and speed of use. One application of the empirical model is to de-trend the spacecraft motion from the ROSINA COPS and DFMS data (Rosetta Orbiter Spectrometer for Ion and Neutral Analysis, Comet Pressure Sensor, Double Focusing Mass Spectrometer). The ROSINA instrument measures the neutral coma density at a single point and the measured value is influenced by the location of the spacecraft relative to the comet and the comet-sun line. Using the empirical coma model we can correct for the position of the spacecraft and compute a total production rate based on the single point measurement. In this presentation we will present the coma production rate as a function of heliocentric distance both pre- and post-equinox and perihelion.

Unified gas-kinetic scheme with multigrid convergence for rarefied flow study

NASA Astrophysics Data System (ADS)

Zhu, Yajun; Zhong, Chengwen; Xu, Kun

2017-09-01

The unified gas kinetic scheme (UGKS) is based on direct modeling of gas dynamics on the mesh size and time step scales. With the modeling of particle transport and collision in a time-dependent flux function in a finite volume framework, the UGKS can connect the flow physics smoothly from the kinetic particle transport to the hydrodynamic wave propagation. In comparison with the direct simulation Monte Carlo (DSMC) method, the current equation-based UGKS can implement implicit techniques in the updates of macroscopic conservative variables and microscopic distribution functions. The implicit UGKS significantly increases the convergence speed for steady flow computations, especially in the highly rarefied and near continuum regimes. In order to further improve the computational efficiency, for the first time, a geometric multigrid technique is introduced into the implicit UGKS, where the prediction step for the equilibrium state and the evolution step for the distribution function are both treated with multigrid acceleration. More specifically, a full approximate nonlinear system is employed in the prediction step for fast evaluation of the equilibrium state, and a correction linear equation is solved in the evolution step for the update of the gas distribution function. As a result, convergent speed has been greatly improved in all flow regimes from rarefied to the continuum ones. The multigrid implicit UGKS (MIUGKS) is used in the non-equilibrium flow study, which includes microflow, such as lid-driven cavity flow and the flow passing through a finite-length flat plate, and high speed one, such as supersonic flow over a square cylinder. The MIUGKS shows 5-9 times efficiency increase over the previous implicit scheme. For the low speed microflow, the efficiency of MIUGKS is several orders of magnitude higher than the DSMC. Even for the hypersonic flow at Mach number 5 and Knudsen number 0.1, the MIUGKS is still more than 100 times faster than the DSMC method for obtaining a convergent steady state solution.

ASC Weekly News Notes

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

Womble, David E.

Unified collision operator demonstrated for both radiation transport and PIC-DSMC. A side-by-side comparison between the DSMC method and the radiation transport method was conducted for photon attenuation in the atmosphere over 2 kilometers in physical distance with a reduction of photon density of six orders of magnitude. Both DSMC and traditional radiation transport agreed with theory to two digits. This indicates that PIC-DSMC operators can be unified with the radiation transport collision operators into a single code base and that physics kernels can remain unique to the actual collision pairs. This simulation example provides an initial validation of the unifiedmore » collision theory approach that will later be implemented into EMPIRE.« less

A DSMC Study of Low Pressure Argon Discharge

NASA Astrophysics Data System (ADS)

Hash, David; Meyyappan, M.

1997-10-01

Work toward a self-consistent plasma simulation using the DSMC method for examination of the flowfields of low-pressure high density plasma reactors is presented. Presently, DSMC simulations for these applications involve either treating the electrons as a fluid or imposing experimentally determined values for the electron number density profile. In either approach, the electrons themselves are not physically simulated. Self-consistent plasma DSMC simulations have been conducted for aerospace applications but at a severe computational cost due in part to the scalar architectures on which the codes were employed. The present work attempts to conduct such simulations at a more reasonable cost using a plasma version of the object-oriented parallel Cornell DSMC code, MONACO, on an IBM SP-2. Due the availability of experimental data, the GEC reference cell is chosen to conduct preliminary investigations. An argon discharge is examined thus affording a simple chemistry set with eight gas-phase reactions and five species: Ar, Ar^+, Ar^*, Ar_2, and e where Ar^* is a metastable.

Heat transfer in nonequilibrium boundary layer flow over a partly catalytic wall

NASA Astrophysics Data System (ADS)

Wang, Zhi-Hui

2016-11-01

Surface catalysis has a huge influence on the aeroheating performance of hypersonic vehicles. For the reentry flow problem of a traditional blunt vehicle, it is reasonable to assume a frozen boundary layer surrounding the vehicles' nose, and the catalytic heating can be decoupled with the heat conduction. However, when considering a hypersonic cruise vehicle flying in the medium-density near space, the boundary layer flow around its sharp leading-edge is likely to be nonequilibrium rather than frozen due to rarefied gas effects. As a result, there will be a competition between the heat conduction and the catalytic heating. In this paper, the theoretical modeling and the direct simulation Monte Carlo (DSMC) method are employed to study the corresponding rarefied nonequilibrium flow and heat transfer phenomena near the leading edge of the near space hypersonic vehicles. It is found that even under identical rarefication degree, the nonequilibrium degree of the flow and the corresponding heat transfer performance of the sharp leading edges could be different from that of the big blunt noses. A generalized model is preliminarily proposed to describe and to evaluate the competitive effects between the homogeneous recombination of atoms inside the nonequilibrium boundary layer and the heterogeneous recombination of atoms on the catalytic wall surface. The introduced nonequilibrium criterion and the analytical formula are validated and calibrated by the DSMC results, and the physical mechanism is discussed.

Development of a two-dimensional binning model for N{sub 2}–N relaxation in hypersonic shock conditions

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

Zhu, Tong, E-mail: tongzhu2@illinois.edu; Levin, Deborah A., E-mail: deblevin@illinois.edu; Li, Zheng, E-mail: zul107@psu.edu

2016-08-14

A high fidelity internal energy relaxation model for N{sub 2}–N suitable for use in direct simulation Monte Carlo (DSMC) modeling of chemically reacting flows is proposed. A novel two-dimensional binning approach with variable bin energy resolutions in the rotational and vibrational modes is developed for treating the internal mode of N{sub 2}. Both bin-to-bin and state-specific relaxation cross sections are obtained using the molecular dynamics/quasi-classical trajectory (MD/QCT) method with two potential energy surfaces as well as the state-specific database of Jaffe et al. The MD/QCT simulations of inelastic energy exchange between N{sub 2} and N show that there is amore » strong forward-preferential scattering behavior at high collision velocities. The 99 bin model is used in homogeneous DSMC relaxation simulations and is found to be able to recover the state-specific master equation results of Panesi et al. when the Jaffe state-specific cross sections are used. Rotational relaxation energy profiles and relaxation times obtained using the ReaxFF and Jaffe potential energy surfaces (PESs) are in general agreement but there are larger differences between the vibrational relaxation times. These differences become smaller as the translational temperature increases because the difference in the PES energy barrier becomes less important.« less

A generalized form of the Bernoulli Trial collision scheme in DSMC: Derivation and evaluation

NASA Astrophysics Data System (ADS)

Roohi, Ehsan; Stefanov, Stefan; Shoja-Sani, Ahmad; Ejraei, Hossein

2018-02-01

The impetus of this research is to present a generalized Bernoulli Trial collision scheme in the context of the direct simulation Monte Carlo (DSMC) method. Previously, a subsequent of several collision schemes have been put forward, which were mathematically based on the Kac stochastic model. These include Bernoulli Trial (BT), Ballot Box (BB), Simplified Bernoulli Trial (SBT) and Intelligent Simplified Bernoulli Trial (ISBT) schemes. The number of considered pairs for a possible collision in the above-mentioned schemes varies between N (l) (N (l) - 1) / 2 in BT, 1 in BB, and (N (l) - 1) in SBT or ISBT, where N (l) is the instantaneous number of particles in the lth cell. Here, we derive a generalized form of the Bernoulli Trial collision scheme (GBT) where the number of selected pairs is any desired value smaller than (N (l) - 1), i.e., Nsel < (N (l) - 1), keeping the same the collision frequency and accuracy of the solution as the original SBT and BT models. We derive two distinct formulas for the GBT scheme, where both formula recover BB and SBT limits if Nsel is set as 1 and N (l) - 1, respectively, and provide accurate solutions for a wide set of test cases. The present generalization further improves the computational efficiency of the BT-based collision models compared to the standard no time counter (NTC) and nearest neighbor (NN) collision models.

Comparison study of exhaust plume impingement effects of small mono- and bipropellant thrusters using parallelized DSMC method

PubMed Central

2017-01-01

A space propulsion system is important for the normal mission operations of a spacecraft by adjusting its attitude and maneuver. Generally, a mono- and a bipropellant thruster have been mainly used for low thrust liquid rocket engines. But as the plume gas expelled from these small thrusters diffuses freely in a vacuum space along all directions, unwanted effects due to the plume collision onto the spacecraft surfaces can dramatically cause a deterioration of the function and performance of a spacecraft. Thus, aim of the present study is to investigate and compare the major differences of the plume gas impingement effects quantitatively between the small mono- and bipropellant thrusters using the computational fluid dynamics (CFD). For an efficiency of the numerical calculations, the whole calculation domain is divided into two different flow regimes depending on the flow characteristics, and then Navier-Stokes equations and parallelized Direct Simulation Monte Carlo (DSMC) method are adopted for each flow regime. From the present analysis, thermal and mass influences of the plume gas impingements on the spacecraft were analyzed for the mono- and the bipropellant thrusters. As a result, it is concluded that a careful understanding on the plume impingement effects depending on the chemical characteristics of different propellants are necessary for the efficient design of the spacecraft. PMID:28636625

Modelling of the outburst on July 29th , 2015 observed with OSIRIS in the southern hemisphere of comet 67P/Churyumov-Gerasimenko

NASA Astrophysics Data System (ADS)

Gicquel, Adeline; Vincent, Jean-Baptiste; Sierks, Holger; Rose, Martin; Agarwal, Jessica; Deller, Jakob; Guettler, Carsten; Hoefner, Sebastian; Hofmann, Marc; Hu, Xuanyu; Kovacs, Gabor; Oklay Vincent, Nilda; Shi, Xian; Tubiana, Cecilia; Barbieri, Cesare; Lamy, Phylippe; Rodrigo, Rafael; Koschny, Detlef; Rickman, Hans; OSIRIS Team

2016-10-01

Images of the nucleus and the coma (gas and dust) of comet 67P/Churyumov- Gerasimenko have been acquired by the OSIRIS (Optical, Spectroscopic, and Infrared Remote Imaging System) cameras system since March 2014 using both the wide angle camera (WAC) and the narrow angle camera (NAC). We are using the NAC camera to study the bright outburst observed on July 29th, 2015 in the southern hemisphere. The NAC camera's wavelength ranges between 250-1000 nm with a combination of 12 filters. The high spatial resolution is needed to localize the source point of the outburst on the surface of the nucleus. At the time of the observations, the heliocentric distance was 1.25AU and the distance between the spacecraft and the comet was 126 km. We aim to understand the physics leading to such outgassing: Is the jet associated to the outbursts controlled by the micro-topography? Or by ice suddenly exposed? We are using the Direct Simulation Monte Carlo (DSMC) method to study the gas flow close to the nucleus. The goal of the DSMC code is to reproduce the opening angle of the jet, and constrain the outgassing ratio between outburst source and local region. The results of this model will be compared to the images obtained with the NAC camera.

Navier-Stokes Dynamics by a Discrete Boltzmann Model

NASA Technical Reports Server (NTRS)

Rubinstein, Robet

2010-01-01

This work investigates the possibility of particle-based algorithms for the Navier-Stokes equations and higher order continuum approximations of the Boltzmann equation; such algorithms would generalize the well-known Pullin scheme for the Euler equations. One such method is proposed in the context of a discrete velocity model of the Boltzmann equation. Preliminary results on shock structure are consistent with the expectation that the shock should be much broader than the near discontinuity predicted by the Pullin scheme, yet narrower than the prediction of the Boltzmann equation. We discuss the extension of this essentially deterministic method to a stochastic particle method that, like DSMC, samples the distribution function rather than resolving it completely.

Transient heat transfer in viscous rarefied gas between concentric cylinders. Effect of curvature

NASA Astrophysics Data System (ADS)

Gospodinov, P.; Roussinov, V.; Dankov, D.

2015-10-01

The thermoacoustic waves arising in cylindrical or planar Couette rarefied gas flow between rotating cylinders is studied in the cases of suddenly cylinder (active) wall velocity direction turn on. An unlimited increase in the radius of the inner cylinder flow can be interpreted as Couette flow between the two flat plates. Based on the developed in previous publications Navier-Stockes-Fourier (NSF) model and Direct Simulation Monte Carlo (DSMC) method and their numerical solutions, are considered transient processes in the gas phase. Macroscopic flow characteristics (velocity, density, temperature) are received. The cylindrical flow cases for fixed velocity and temperature of the both walls are considered. The curvature effects over the wave's distribution and attenuation are studied numerically.

Rarefaction effects on Galileo probe aerodynamics

NASA Technical Reports Server (NTRS)

Moss, James N.; LeBeau, Gerald J.; Blanchard, Robert C.; Price, Joseph M.

1996-01-01

Solutions of aerodynamic characteristics are presented for the Galileo Probe entering Jupiter's hydrogen-helium atmosphere at a nominal relative velocity of 47.4 km/s. Focus is on predicting the aerodynamic drag coefficient during the transitional flow regime using the direct simulation Monte Carlo (DSMC) method. Accuracy of the probe's drag coefficient directly impacts the inferred atmospheric properties that are being extracted from the deceleration measurements made by onboard accelerometers as part of the Atmospheric Structure Experiment. The range of rarefaction considered in the present study extends from the free molecular limit to continuum conditions. Comparisons made with previous calculations and experimental measurements show the present results for drag to merge well with Navier-Stokes and experimental results for the least rarefied conditions considered.

Multifluid MHD Simulations of the Plasma Environment of Comet Churyumov-Gerasimenko at Different Heliocentric Distances

NASA Astrophysics Data System (ADS)

Huang, Z.; Jia, X.; Rubin, M.; Fougere, N.; Gombosi, T. I.; Tenishev, V.; Combi, M. R.; Bieler, A. M.; Toth, G.; Hansen, K. C.; Shou, Y.

2014-12-01

We study the plasma environment of the comet Churyumov-Gerasimenko, which is the target of the Rosetta mission, by performing large scale numerical simulations. Our model is based on BATS-R-US within the Space Weather Modeling Framework that solves the governing multifluid MHD equations, which describe the behavior of the cometary heavy ions, the solar wind protons, and electrons. The model includes various mass loading processes, including ionization, charge exchange, dissociative ion-electron recombination, as well as collisional interactions between different fluids. The neutral background used in our MHD simulations is provided by a kinetic Direct Simulation Monte Carlo (DSMC) model. We will simulate how the cometary plasma environment changes at different heliocentric distances.

DSMC analysis of species separation in rarefied nozzle flows

NASA Technical Reports Server (NTRS)

Chung, Chan-Hong; De Witt, Kenneth J.; Jeng, Duen-Ren; Penko, Paul F.

1992-01-01

The direct-simulation Monte Carlo method has been used to investigate the behavior of a small amount of a harmful species in the plume and the backflow region of nuclear thermal propulsion rockets. Species separation due to pressure diffusion and nonequilibrium effects due to rapid expansion into a surrounding low-density environment are the most important factors in this type of flow. It is shown that a relatively large amount of the lighter species is scattered into the backflow region and the heavier species becomes negligible in this region due to the extreme separation between species. It is also shown that the type of molecular interaction between the species can have a substantial effect on separation of the species.

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.

Dose calculation accuracy of the Monte Carlo algorithm for CyberKnife compared with other commercially available dose calculation algorithms.

PubMed

Sharma, Subhash; Ott, Joseph; Williams, Jamone; Dickow, Danny

2011-01-01

Monte Carlo dose calculation algorithms have the potential for greater accuracy than traditional model-based algorithms. This enhanced accuracy is particularly evident in regions of lateral scatter disequilibrium, which can develop during treatments incorporating small field sizes and low-density tissue. A heterogeneous slab phantom was used to evaluate the accuracy of several commercially available dose calculation algorithms, including Monte Carlo dose calculation for CyberKnife, Analytical Anisotropic Algorithm and Pencil Beam convolution for the Eclipse planning system, and convolution-superposition for the Xio planning system. The phantom accommodated slabs of varying density; comparisons between planned and measured dose distributions were accomplished with radiochromic film. The Monte Carlo algorithm provided the most accurate comparison between planned and measured dose distributions. In each phantom irradiation, the Monte Carlo predictions resulted in gamma analysis comparisons >97%, using acceptance criteria of 3% dose and 3-mm distance to agreement. In general, the gamma analysis comparisons for the other algorithms were <95%. The Monte Carlo dose calculation algorithm for CyberKnife provides more accurate dose distribution calculations in regions of lateral electron disequilibrium than commercially available model-based algorithms. This is primarily because of the ability of Monte Carlo algorithms to implicitly account for tissue heterogeneities, density scaling functions; and/or effective depth correction factors are not required. Copyright © 2011 American Association of Medical Dosimetrists. Published by Elsevier Inc. All rights reserved.

Physical time scale in kinetic Monte Carlo simulations of continuous-time Markov chains.

PubMed

Serebrinsky, Santiago A

2011-03-01

We rigorously establish a physical time scale for a general class of kinetic Monte Carlo algorithms for the simulation of continuous-time Markov chains. This class of algorithms encompasses rejection-free (or BKL) and rejection (or "standard") algorithms. For rejection algorithms, it was formerly considered that the availability of a physical time scale (instead of Monte Carlo steps) was empirical, at best. Use of Monte Carlo steps as a time unit now becomes completely unnecessary.

Investigation of the hysteresis phenomena in steady shock reflection using kinetic and continuum methods

NASA Astrophysics Data System (ADS)

Ivanov, M.; Zeitoun, D.; Vuillon, J.; Gimelshein, S.; Markelov, G.

1996-05-01

The problem of transition of planar shock waves over straight wedges in steady flows from regular to Mach reflection and back was numerically studied by the DSMC method for solving the Boltzmann equation and finite difference method with FCT algorithm for solving the Euler equations. It is shown that the transition from regular to Mach reflection takes place in accordance with detachment criterion while the opposite transition occurs at smaller angles. The hysteresis effect was observed at increasing and decreasing shock wave angle.

DSMC simulations of the Shuttle Plume Impingement Flight EXperiment(SPIFEX)

NASA Technical Reports Server (NTRS)

Stewart, Benedicte; Lumpkin, Forrest

2017-01-01

During orbital maneuvers and proximity operations, a spacecraft fires its thrusters inducing plume impingement loads, heating and contamination to itself and to any other nearby spacecraft. These thruster firings are generally modeled using a combination of Computational Fluid Dynamics (CFD) and DSMC simulations. The Shuttle Plume Impingement Flight EXperiment(SPIFEX) produced data that can be compared to a high fidelity simulation. Due to the size of the Shuttle thrusters this problem was too resource intensive to be solved with DSMC when the experiment flew in 1994.

DSMC simulations of leading edge flat-plate boundary layer flows at high Mach number

NASA Astrophysics Data System (ADS)

Pradhan, Sahadev, , Dr.

2017-04-01

The flow over a 2D leading-edge flat plate is studied at Mach number Ma =(Uinf / \\setmn √{kBTinf / m}) in the range

DSMC simulations of leading edge flat-plate boundary layer flows at high Mach number

NASA Astrophysics Data System (ADS)

Pradhan, Sahadev, , Dr.

2016-11-01

The flow over a 2D leading-edge flat plate is studied at Mach number Ma = (Uinf /√{kBTinf / m }) in the range

DSMC simulations of leading edge flat-plate boundary layer flows at high Mach number

NASA Astrophysics Data System (ADS)

Pradhan, Sahadev, , Dr.

2017-01-01

The flow over a 2D leading-edge flat plate is studied at Mach number Ma = (Uinf /√{kBTinf / m }) in the range

DSMC simulations of leading edge flat-plate boundary layer flows at high Mach number

NASA Astrophysics Data System (ADS)

Pradhan, Sahadev

2016-10-01

The flow over a 2D leading-edge flat plate is studied at Mach number Ma = (Uinf / {kBTinf /m}) in the range

DSMC simulations of leading edge flat-plate boundary layer flows at high Mach number

NASA Astrophysics Data System (ADS)

Pradhan, Sahadev, , Dr.

The flow over a 2D leading-edge flat plate is studied at Mach number Ma = (Uinf / ∖ sqrt{kBTinf / m})in the range

Channel electron multiplier operated on a sounding rocket without a cryogenic vacuum pump from 120 - 75 km altitude

NASA Astrophysics Data System (ADS)

Dickson, S.; Gausa, M. A.; Robertson, S. H.; Sternovsky, Z.

2012-12-01

We demonstrate that a channel electron multiplier (CEM) can be operated on a sounding rocket in the pulse-counting mode from 120 km to 75 km altitude without the cryogenic evacuation used in the past. Evacuation of the CEM is provided only by aerodynamic flow around the rocket. This demonstration is motivated by the need for additional flights of mass spectrometers to clarify the fate of metallic compounds and ions ablated from micrometeorites and their possible role in the nucleation of noctilucent clouds. The CEMs were flown as guest instruments on the two sounding rockets of the CHAMPS (CHarge And mass of Meteoritic smoke ParticleS) rocket campaign which were launched into the mesosphere in October 2011 from Andøya Rocket Range, Norway. Modeling of the aerodynamic flow around the payload with Direct Simulation Monte-Carlo (DSMC) code showed that the pressure is reduced below ambient in the void beneath an aft-facing surface. An enclosure containing the CEM was placed above an aft-facing deck and a valve was opened on the downleg to expose the CEM to the aerodynamically evacuated region below. The CEM operated successfully from apogee down to ~75 km. A Pirani gauge confirmed pressures reduced to as low as 20% of ambient with the extent of reduction dependent upon altitude and velocity. Additional DSMC simulations indicate that there are alternate payload designs with improved aerodynamic pumping for forward mounted instruments such as mass spectrometers.

Coma dust scattering concepts applied to the Rosetta mission

NASA Astrophysics Data System (ADS)

Fink, Uwe; Rinaldi, Giovanna

2015-09-01

This paper describes basic concepts, as well as providing a framework, for the interpretation of the light scattered by the dust in a cometary coma as observed by instruments on a spacecraft such as Rosetta. It is shown that the expected optical depths are small enough that single scattering can be applied. Each of the quantities that contribute to the scattered intensity is discussed in detail. Using optical constants of the likely coma dust constituents, olivine, pyroxene and carbon, the scattering properties of the dust are calculated. For the resulting observable scattering intensities several particle size distributions are considered, a simple power law, power laws with a small particle cut off and a log-normal distributions with various parameters. Within the context of a simple outflow model, the standard definition of Afρ for a circular observing aperture is expanded to an equivalent Afρ for an annulus and specific line-of-sight observation. The resulting equivalence between the observed intensity and Afρ is used to predict observable intensities for 67P/Churyumov-Gerasimenko at the spacecraft encounter near 3.3 AU and near perihelion at 1.3 AU. This is done by normalizing particle production rates of various size distributions to agree with observed ground based Afρ values. Various geometries for the column densities in a cometary coma are considered. The calculations for a simple outflow model are compared with more elaborate Direct Simulation Monte Carlo Calculation (DSMC) models to define the limits of applicability of the simpler analytical approach. Thus our analytical approach can be applied to the majority of the Rosetta coma observations, particularly beyond several nuclear radii where the dust is no longer in a collisional environment, without recourse to computer intensive DSMC calculations for specific cases. In addition to a spherically symmetric 1-dimensional approach we investigate column densities for the 2-dimensional DSMC model on the day and night side of the comet. Our calculations are also applied to estimates of the dust particle densities and flux which are useful for the in-situ experiments on Rosetta.

An empirical model of H2O, CO2 and CO coma distributions and production rates for comet 67P/Churyumov-Gerasimenko based on ROSINA/DFMS measurements and AMPS-DSMC simulations

NASA Astrophysics Data System (ADS)

Hansen, Kenneth C.; Altwegg, Kathrin; Bieler, Andre; Berthelier, Jean-Jacques; Calmonte, Ursina; Combi, Michael R.; De Keyser, Johan; Fiethe, Björn; Fougere, Nicolas; Fuselier, Stephen; Gombosi, T. I.; Hässig, Myrtha; Huang, Zhenguang; Le Roy, Léna; Rubin, Martin; Tenishev, Valeriy; Toth, Gabor; Tzou, Chia-Yu; ROSINA Team

2016-10-01

We have previously used results from the AMPS DSMC (Adaptive Mesh Particle Simulator Direct Simulation Monte Carlo) model to create an empirical model of the near comet water (H2O) coma of comet 67P/Churyumov-Gerasimenko. In this work we create additional empirical models for the coma distributions of CO2 and CO. The AMPS simulations are based on ROSINA DFMS (Rosetta Orbiter Spectrometer for Ion and Neutral Analysis, Double Focusing Mass Spectrometer) data taken over the entire timespan of the Rosetta mission. The empirical model is created using AMPS DSMC results which are extracted from simulations at a range of radial distances, rotation phases and heliocentric distances. The simulation results are then averaged over a comet rotation and fitted to an empirical model distribution. Model coefficients are then fitted to piecewise-linear functions of heliocentric distance. The final product is an empirical model of the coma distribution which is a function of heliocentric distance, radial distance, and sun-fixed longitude and latitude angles. The model clearly mimics the behavior of water shifting production from North to South across the inbound equinox while the CO2 production is always in the South.The empirical model can be used to de-trend the spacecraft motion from the ROSINA COPS and DFMS data. The ROSINA instrument measures the neutral coma density at a single point and the measured value is influenced by the location of the spacecraft relative to the comet and the comet-sun line. Using the empirical coma model we can correct for the position of the spacecraft and compute a total production rate based on single point measurements. In this presentation we will present the coma production rates as a function of heliocentric distance for the entire Rosetta mission.This work was supported by contracts JPL#1266313 and JPL#1266314 from the US Rosetta Project and NASA grant NNX14AG84G from the Planetary Atmospheres Program.

A hybrid method with deviational particles for spatial inhomogeneous plasma

NASA Astrophysics Data System (ADS)

Yan, Bokai

2016-03-01

In this work we propose a Hybrid method with Deviational Particles (HDP) for a plasma modeled by the inhomogeneous Vlasov-Poisson-Landau system. We split the distribution into a Maxwellian part evolved by a grid based fluid solver and a deviation part simulated by numerical particles. These particles, named deviational particles, could be both positive and negative. We combine the Monte Carlo method proposed in [31], a Particle in Cell method and a Macro-Micro decomposition method [3] to design an efficient hybrid method. Furthermore, coarse particles are employed to accelerate the simulation. A particle resampling technique on both deviational particles and coarse particles is also investigated and improved. This method is applicable in all regimes and significantly more efficient compared to a PIC-DSMC method near the fluid regime.

Rarefaction Effects in Hypersonic Aerodynamics

NASA Astrophysics Data System (ADS)

Riabov, Vladimir V.

2011-05-01

The Direct Simulation Monte-Carlo (DSMC) technique is used for numerical analysis of rarefied-gas hypersonic flows near a blunt plate, wedge, two side-by-side plates, disk, torus, and rotating cylinder. The role of various similarity parameters (Knudsen and Mach numbers, geometrical and temperature factors, specific heat ratios, and others) in aerodynamics of the probes is studied. Important kinetic effects that are specific for the transition flow regime have been found: non-monotonic lift and drag of plates, strong repulsive force between side-by-side plates and cylinders, dependence of drag on torus radii ratio, and the reverse Magnus effect on the lift of a rotating cylinder. The numerical results are in a good agreement with experimental data, which were obtained in a vacuum chamber at low and moderate Knudsen numbers from 0.01 to 10.

Numerical Simulation of Rarefied Plume Flow Exhausting from a Small Nozzle

NASA Astrophysics Data System (ADS)

Hyakutake, Toru; Yamamoto, Kyoji

2003-05-01

This paper describes the numerical studies of a rarefied plume flow expanding through a nozzle into a vacuum, especially focusing on investigating the nozzle performance, the angular distributions of molecular flux in the nozzle plume and the influence of the backflow contamination for the variation of nozzle geometries and gas/surface interaction models. The direct simulation Monte Carlo (DSMC) method is employed for determining inside the nozzle and in the nozzle plume. The simulation results indicate that the half-angle of the diverging section in the highest thrust coefficient is 25° - 30° and this value varies with the expansion ratio of the nozzle. The descent of the half-angle brings about the increase of the molecules that are scattered in the backflow region.

RNA folding kinetics using Monte Carlo and Gillespie algorithms.

PubMed

Clote, Peter; Bayegan, Amir H

2018-04-01

RNA secondary structure folding kinetics is known to be important for the biological function of certain processes, such as the hok/sok system in E. coli. Although linear algebra provides an exact computational solution of secondary structure folding kinetics with respect to the Turner energy model for tiny ([Formula: see text]20 nt) RNA sequences, the folding kinetics for larger sequences can only be approximated by binning structures into macrostates in a coarse-grained model, or by repeatedly simulating secondary structure folding with either the Monte Carlo algorithm or the Gillespie algorithm. Here we investigate the relation between the Monte Carlo algorithm and the Gillespie algorithm. We prove that asymptotically, the expected time for a K-step trajectory of the Monte Carlo algorithm is equal to [Formula: see text] times that of the Gillespie algorithm, where [Formula: see text] denotes the Boltzmann expected network degree. If the network is regular (i.e. every node has the same degree), then the mean first passage time (MFPT) computed by the Monte Carlo algorithm is equal to MFPT computed by the Gillespie algorithm multiplied by [Formula: see text]; however, this is not true for non-regular networks. In particular, RNA secondary structure folding kinetics, as computed by the Monte Carlo algorithm, is not equal to the folding kinetics, as computed by the Gillespie algorithm, although the mean first passage times are roughly correlated. Simulation software for RNA secondary structure folding according to the Monte Carlo and Gillespie algorithms is publicly available, as is our software to compute the expected degree of the network of secondary structures of a given RNA sequence-see http://bioinformatics.bc.edu/clote/RNAexpNumNbors .

Cell-veto Monte Carlo algorithm for long-range systems.

PubMed

Kapfer, Sebastian C; Krauth, Werner

2016-09-01

We present a rigorous efficient event-chain Monte Carlo algorithm for long-range interacting particle systems. Using a cell-veto scheme within the factorized Metropolis algorithm, we compute each single-particle move with a fixed number of operations. For slowly decaying potentials such as Coulomb interactions, screening line charges allow us to take into account periodic boundary conditions. We discuss the performance of the cell-veto Monte Carlo algorithm for general inverse-power-law potentials, and illustrate how it provides a new outlook on one of the prominent bottlenecks in large-scale atomistic Monte Carlo simulations.

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

Analysis of high-speed rotating flow inside gas centrifuge casing

NASA Astrophysics Data System (ADS)

Pradhan, Sahadev, , Dr.

2017-10-01

The generalized analytical model for the radial boundary layer inside the gas centrifuge casing in which the inner cylinder is rotating at a constant angular velocity Ω_i while the outer one is stationary, is formulated for studying the secondary gas flow field due to wall thermal forcing, inflow/outflow of light gas along the boundaries, as well as due to the combination of the above two external forcing. The analytical model includes the sixth order differential equation for the radial boundary layer at the cylindrical curved surface in terms of master potential (χ) , which is derived from the equations of motion in an axisymmetric (r - z) plane. The linearization approximation is used, where the equations of motion are truncated at linear order in the velocity and pressure disturbances to the base flow, which is a solid-body rotation. Additional approximations in the analytical model include constant temperature in the base state (isothermal compressible Couette flow), high aspect ratio (length is large compared to the annular gap), high Reynolds number, but there is no limitation on the Mach number. The discrete eigenvalues and eigenfunctions of the linear operators (sixth-order in the radial direction for the generalized analytical equation) are obtained. The solutions for the secondary flow is determined in terms of these eigenvalues and eigenfunctions. These solutions are compared with direct simulation Monte Carlo (DSMC) simulations and found excellent agreement (with a difference of less than 15%) between the predictions of the analytical model and the DSMC simulations, provided the boundary conditions in the analytical model are accurately specified.

Analysis of high-speed rotating flow inside gas centrifuge casing

NASA Astrophysics Data System (ADS)

Pradhan, Sahadev, , Dr.

2017-09-01

The generalized analytical model for the radial boundary layer inside the gas centrifuge casing in which the inner cylinder is rotating at a constant angular velocity Ωi while the outer one is stationary, is formulated for studying the secondary gas flow field due to wall thermal forcing, inflow/outflow of light gas along the boundaries, as well as due to the combination of the above two external forcing. The analytical model includes the sixth order differential equation for the radial boundary layer at the cylindrical curved surface in terms of master potential (χ) , which is derived from the equations of motion in an axisymmetric (r - z) plane. The linearization approximation is used, where the equations of motion are truncated at linear order in the velocity and pressure disturbances to the base flow, which is a solid-body rotation. Additional approximations in the analytical model include constant temperature in the base state (isothermal compressible Couette flow), high aspect ratio (length is large compared to the annular gap), high Reynolds number, but there is no limitation on the Mach number. The discrete eigenvalues and eigenfunctions of the linear operators (sixth-order in the radial direction for the generalized analytical equation) are obtained. The solutions for the secondary flow is determined in terms of these eigenvalues and eigenfunctions. These solutions are compared with direct simulation Monte Carlo (DSMC) simulations and found excellent agreement (with a difference of less than 15%) between the predictions of the analytical model and the DSMC simulations, provided the boundary conditions in the analytical model are accurately specified.

Analysis of high-speed rotating flow inside gas centrifuge casing

NASA Astrophysics Data System (ADS)

Pradhan, Sahadev

2017-11-01

The generalized analytical model for the radial boundary layer inside the gas centrifuge casing in which the inner cylinder is rotating at a constant angular velocity Ωi while the outer one is stationary, is formulated for studying the secondary gas flow field due to wall thermal forcing, inflow/outflow of light gas along the boundaries, as well as due to the combination of the above two external forcing. The analytical model includes the sixth order differential equation for the radial boundary layer at the cylindrical curved surface in terms of master potential (χ) , which is derived from the equations of motion in an axisymmetric (r - z) plane. The linearization approximation is used, where the equations of motion are truncated at linear order in the velocity and pressure disturbances to the base flow, which is a solid-body rotation. Additional approximations in the analytical model include constant temperature in the base state (isothermal compressible Couette flow), high aspect ratio (length is large compared to the annular gap), high Reynolds number, but there is no limitation on the Mach number. The discrete eigenvalues and eigenfunctions of the linear operators (sixth-order in the radial direction for the generalized analytical equation) are obtained. The solutions for the secondary flow is determined in terms of these eigenvalues and eigenfunctions. These solutions are compared with direct simulation Monte Carlo (DSMC) simulations and found excellent agreement (with a difference of less than 15%) between the predictions of the analytical model and the DSMC simulations, provided the boundary conditions in the analytical model are accurately specified.

Thin film deposition using rarefied gas jet

NASA Astrophysics Data System (ADS)

Pradhan, Sahadev, , Dr.

2017-01-01

The rarefied gas jet of aluminium is studied at Mach number Ma =(U_j /√{ kbTj / m }) in the range .01

Aerodynamic characterization of the jet of an arc wind tunnel

NASA Astrophysics Data System (ADS)

Zuppardi, Gennaro; Esposito, Antonio

2016-11-01

It is well known that, due to a very aggressive environment and to a rather high rarefaction level of the arc wind tunnel jet, the measurement of fluid-dynamic parameters is difficult. For this reason, the aerodynamic characterization of the jet relies also on computer codes, simulating the operation of the tunnel. The present authors already used successfully such a kind of computing procedure for the tests in the arc wind tunnel (SPES) in Naples (Italy). In the present work an improved procedure is proposed. Like the former procedure also the present procedure relies on two codes working in tandem: 1) one-dimensional code simulating the inviscid and thermally not-conducting flow field in the torch, in the mix-chamber and in the nozzle up to the position, along the nozzle axis, of the continuum breakdown, 2) Direct Simulation Monte Carlo (DSMC) code simulating the flow field in the remaining part of the nozzle. In the present procedure, the DSMC simulation includes the simulation both in the nozzle and in the test chamber. An interesting problem, considered in this paper by means of the present procedure, has been the simulation of the flow field around a Pitot tube and of the related measurement of the stagnation pressure. The measured stagnation pressure, under rarefied conditions, may be even four times the theoretical value. Therefore a substantial correction has to be applied to the measured pressure. In the present paper a correction factor for the stagnation pressure measured in SPES is proposed. The analysis relies on twelve tests made in SPES.

DSMC simulations of leading edge flat-plate boundary layer flows at high Mach number

NASA Astrophysics Data System (ADS)

Pradhan, Sahadev

2016-09-01

The flow over a 2D leading-edge flat plate is studied at Mach number Ma = (Uinf /√{kBTinf / m }) in the range

The Rational Hybrid Monte Carlo algorithm

NASA Astrophysics Data System (ADS)

Clark, Michael

2006-12-01

The past few years have seen considerable progress in algorithmic development for the generation of gauge fields including the effects of dynamical fermions. The Rational Hybrid Monte Carlo (RHMC) algorithm, where Hybrid Monte Carlo is performed using a rational approximation in place the usual inverse quark matrix kernel is one of these developments. This algorithm has been found to be extremely beneficial in many areas of lattice QCD (chiral fermions, finite temperature, Wilson fermions etc.). We review the algorithm and some of these benefits, and we compare against other recent algorithm developements. We conclude with an update of the Berlin wall plot comparing costs of all popular fermion formulations.

Analysis of Effectiveness of Phoenix Entry Reaction Control System

NASA Technical Reports Server (NTRS)

Dyakonov, Artem A.; Glass, Christopher E.; Desai, Prasun, N.; VanNorman, John W.

2008-01-01

Interaction between the external flowfield and the reaction control system (RCS) thruster plumes of the Phoenix capsule during entry has been investigated. The analysis covered rarefied, transitional, hypersonic and supersonic flight regimes. Performance of pitch, yaw and roll control authority channels was evaluated, with specific emphasis on the yaw channel due to its low nominal yaw control authority. Because Phoenix had already been constructed and its RCS could not be modified before flight, an assessment of RCS efficacy along the trajectory was needed to determine possible issues and to make necessary software changes. Effectiveness of the system at various regimes was evaluated using a hybrid DSMC-CFD technique, based on DSMC Analysis Code (DAC) code and General Aerodynamic Simulation Program (GASP), the LAURA (Langley Aerothermal Upwind Relaxation Algorithm) code, and the FUN3D (Fully Unstructured 3D) code. Results of the analysis at hypersonic and supersonic conditions suggest a significant aero-RCS interference which reduced the efficacy of the thrusters and could likely produce control reversal. Very little aero-RCS interference was predicted in rarefied and transitional regimes. A recommendation was made to the project to widen controller system deadbands to minimize (if not eliminate) the use of RCS thrusters through hypersonic and supersonic flight regimes, where their performance would be uncertain.

Speed tracking control of pneumatic motor servo systems using observation-based adaptive dynamic sliding-mode control

NASA Astrophysics Data System (ADS)

Chen, Syuan-Yi; Gong, Sheng-Sian

2017-09-01

This study aims to develop an adaptive high-precision control system for controlling the speed of a vane-type air motor (VAM) pneumatic servo system. In practice, the rotor speed of a VAM depends on the input mass air flow, which can be controlled by the effective orifice area (EOA) of an electronic throttle valve (ETV). As the control variable of a second-order pneumatic system is the integral of the EOA, an observation-based adaptive dynamic sliding-mode control (ADSMC) system is proposed to derive the differential of the control variable, namely, the EOA control signal. In the ADSMC system, a proportional-integral-derivative fuzzy neural network (PIDFNN) observer is used to achieve an ideal dynamic sliding-mode control (DSMC), and a supervisor compensator is designed to eliminate the approximation error. As a result, the ADSMC incorporates the robustness of a DSMC and the online learning ability of a PIDFNN. To ensure the convergence of the tracking error, a Lyapunov-based analytical method is employed to obtain the adaptive algorithms required to tune the control parameters of the online ADSMC system. Finally, our experimental results demonstrate the precision and robustness of the ADSMC system for highly nonlinear and time-varying VAM pneumatic servo systems.

Analytic continuation of quantum Monte Carlo data by stochastic analytical inference.

PubMed

Fuchs, Sebastian; Pruschke, Thomas; Jarrell, Mark

2010-05-01

We present an algorithm for the analytic continuation of imaginary-time quantum Monte Carlo data which is strictly based on principles of Bayesian statistical inference. Within this framework we are able to obtain an explicit expression for the calculation of a weighted average over possible energy spectra, which can be evaluated by standard Monte Carlo simulations, yielding as by-product also the distribution function as function of the regularization parameter. Our algorithm thus avoids the usual ad hoc assumptions introduced in similar algorithms to fix the regularization parameter. We apply the algorithm to imaginary-time quantum Monte Carlo data and compare the resulting energy spectra with those from a standard maximum-entropy calculation.

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

Modeling of the Inner Coma of Comet 67P/Churyumov-Gerasimenko Constrained by VIRTIS and ROSINA Observations

NASA Astrophysics Data System (ADS)

Fougere, N.; Combi, M. R.; Tenishev, V.; Bieler, A. M.; Migliorini, A.; Bockelée-Morvan, D.; Toth, G.; Huang, Z.; Gombosi, T. I.; Hansen, K. C.; Capaccioni, F.; Filacchione, G.; Piccioni, G.; Debout, V.; Erard, S.; Leyrat, C.; Fink, U.; Rubin, M.; Altwegg, K.; Tzou, C. Y.; Le Roy, L.; Calmonte, U.; Berthelier, J. J.; Rème, H.; Hässig, M.; Fuselier, S. A.; Fiethe, B.; De Keyser, J.

2015-12-01

As it orbits around comet 67P/Churyumov-Gerasimenko (CG), the Rosetta spacecraft acquires more information about its main target. The numerous observations made at various geometries and at different times enable a good spatial and temporal coverage of the evolution of CG's cometary coma. However, the question regarding the link between the coma measurements and the nucleus activity remains relatively open notably due to gas expansion and strong kinetic effects in the comet's rarefied atmosphere. In this work, we use coma observations made by the ROSINA-DFMS instrument to constrain the activity at the surface of the nucleus. The distribution of the H2O and CO2 outgassing is described with the use of spherical harmonics. The coordinates in the orthogonal system represented by the spherical harmonics are computed using a least squared method, minimizing the sum of the square residuals between an analytical coma model and the DFMS data. Then, the previously deduced activity distributions are used in a Direct Simulation Monte Carlo (DSMC) model to compute a full description of the H2O and CO2 coma of comet CG from the nucleus' surface up to several hundreds of kilometers. The DSMC outputs are used to create synthetic images, which can be directly compared with VIRTIS measurements. The good agreement between the VIRTIS observations and the DSMC model, itself constrained with ROSINA data, provides a compelling juxtaposition of the measurements from these two instruments. Acknowledgements Work at UofM was supported by contracts JPL#1266313, JPL#1266314 and NASA grant NNX09AB59G. Work at UoB was funded by the State of Bern, the Swiss National Science Foundation and by the ESA PRODEX Program. Work at Southwest Research institute was supported by subcontract #1496541 from the JPL. Work at BIRA-IASB was supported by the Belgian Science Policy Office via PRODEX/ROSINA PEA 90020. The authors would like to thank ASI, CNES, DLR, NASA for supporting this research. VIRTIS was built by a consortium formed by Italy, France and Germany, under the scientific responsibility of the IAPS of INAF, which guides also the scientific operations. The consortium includes also the LESIA of the Observatoire de Paris, and the Institut für Planetenforschung of DLR. The authors wish to thank the RSGS and the RMOC for their continuous support.

Subsurface Gas Flow and Ice Grain Acceleration within Enceladus and Europa Fissures: 2D DSMC Models

NASA Astrophysics Data System (ADS)

Tucker, O. J.; Combi, M. R.; Tenishev, V.

2014-12-01

The ejection of material from geysers is a ubiquitous occurrence on outer solar system bodies. Water vapor plumes have been observed emanating from the southern hemispheres of Enceladus and Europa (Hansen et al. 2011, Roth et al. 2014), and N2plumes carrying ice and ark particles on Triton (Soderblom et al. 2009). The gas and ice grain distributions in the Enceladus plume depend on the subsurface gas properties and the geometry of the fissures e.g., (Schmidt et al. 2008, Ingersoll et al. 2010). Of course the fissures can have complex geometries due to tidal stresses, melting, freezing etc., but directly sampled and inferred gas and grain properties for the plume (source rate, bulk velocity, terminal grain velocity) can be used to provide a basis to constrain characteristic dimensions of vent width and depth. We used a 2-dimensional Direct Simulation Monte Carlo (DSMC) technique to model venting from both axi-symmetric canyons with widths ~2 km and narrow jets with widths ~15-40 m. For all of our vent geometries, considered the water vapor source rates (1027­ - 1028 s-1) and bulk gas velocities (~330 - 670 m/s) obtained at the surface were consistent with inferred values obtained by fits of the data for the plume densities (1026 - 1028 s-1, 250 - 1000 m/s) respectively. However, when using the resulting DSMC gas distribution for the canyon geometries to integrate the trajectories of ice grains we found it insufficient to accelerate submicron ice grains to Enceladus' escape speed. On the other hand, the gas distributions in the jet like vents accelerated grains > 10 μm significantly above Enceladus' escape speed. It has been suggested that micron-sized grains are ejected from the vents with speeds comparable to the Enceladus escape speed. Here we report on these results including comparisons to results obtained from 1D models as well as discuss the implications of our plume model results. We also show preliminary results for similar considerations applied to Europa. References: Hansen, 2011. Geophys. Res. Lett. 38, L11202; Ingersoll, 2010. Icarus 206, 594 - 607; Schmidt, 2008. Nature 451, 685 - 688; Soderblom, 2009. Science 250, 412 - 415; Roth, 2013l. Science http://dx.doi.org/10.1126/science.1247051 2013

Program Manager: Journal of the Defense Systems Management College, Volume 23, Number 3, DSMC 120, May-June 1994

DTIC Science & Technology

1994-06-01

Defense Systems Management requirements for program executive College (DSMC). However. the sec- officers ( PEas ), program managers ond and third sets have...and presenting in- predictable outcomes in terms of cul- formation would change the entire tural change. t4 of culture. Once, carrier pigeons took days

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.

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.

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.

Studies on Beam Formation in an Atomic Beam Source

NASA Astrophysics Data System (ADS)

Nass, A.; Stancari, M.; Steffens, E.

2009-08-01

Atomic beam sources (ABS) are widely used workhorses producing polarized atomic beams for polarized gas targets and polarized ion sources. Although they have been used for decades the understanding of the beam formation processes is crude. Models were used more or less successfully to describe the measured intensity and beam parameters. ABS's are also foreseen for future experiments, such as PAX [1]. An increase of intensity at a high polarization would be beneficial. A direct simulation Monte-Carlo method (DSMC) [2] was used to describe the beam formation of a hydrogen or deuterium beam in an ABS. For the first time a simulation of a supersonic gas expansion on a molecular level for this application was performed. Beam profile and Time-of-Flight measurements confirmed the simulation results. Furthermore a new method of beam formation was tested, the Carrier Jet method [3], based on an expanded beam surrounded by an over-expanded carrier jet.

Two-stage crossed beam cooling with ⁶Li and ¹³³Cs atoms in microgravity.

PubMed

Luan, Tian; Yao, Hepeng; Wang, Lu; Li, Chen; Yang, Shifeng; Chen, Xuzong; Ma, Zhaoyuan

2015-05-04

Applying the direct simulation Monte Carlo (DSMC) method developed for ultracold Bose-Fermi mixture gases research, we study the sympathetic cooling process of 6Li and 133Cs atoms in a crossed optical dipole trap. The obstacles to producing 6Li Fermi degenerate gas via direct sympathetic cooling with 133Cs are also analyzed, by which we find that the side-effect of the gravity is one of the main obstacles. Based on the dynamic nature of 6Li and 133Cs atoms, we suggest a two-stage cooling process with two pairs of crossed beams in microgravity environment. According to our simulations, the temperature of 6Li atoms can be cooled to T = 29.5 pK and T/TF = 0.59 with several thousand atoms, which propose a novel way to get ultracold fermion atoms with quantum degeneracy near pico-Kelvin.

Characterization of Vacuum Facility Background Gas Through Simulation and Considerations for Electric Propulsion Ground Testing

NASA Technical Reports Server (NTRS)

Yim, John T.; Burt, Jonathan M.

2015-01-01

The background gas in a vacuum facility for electric propulsion ground testing is examined in detail through a series of cold flow simulations using a direct simulation Monte Carlo (DSMC) code. The focus here is on the background gas itself, its structure and characteristics, rather than assessing its interaction and impact on thruster operation. The background gas, which is often incorrectly characterized as uniform, is found to have a notable velocity within a test facility. The gas velocity has an impact on the proper measurement of pressure and the calculation of ingestion flux to a thruster. There are also considerations for best practices for tests that involve the introduction of supplemental gas flows to artificially increase the background pressure. All of these effects need to be accounted for to properly characterize the operation of electric propulsion thrusters across different ground test vacuum facilities.

Hypersonic Flows About a 25 degree Sharp Cone

NASA Technical Reports Server (NTRS)

Moss, James N.

2001-01-01

This paper presents the results of a numerical study that examines the surface heating discrepancies observed between computed and measured values along a sharp cone. With Mach numbers of an order of 10 and the freestream length Reynolds number of an order of 10 000, the present computations have been made with the direct simulation Monte Carlo (DSMC) method by using the G2 code of Bird. The flow conditions are those specified for two experiments conducted in the Veridian 48-inch Hypersonic Shock Tunnel. Axisymmetric simulations are made since the test model was assumed to be at zero incidence. Details of the current calculations are presented, along with comparisons between the experimental data, for surface heating and pressure distributions. Results of the comparisons show major differences in measured and calculated results for heating distributions, with differences in excess of 25 percent for the two cases examined.

Development and application of computational aerothermodynamics flowfield computer codes

NASA Technical Reports Server (NTRS)

Venkatapathy, Ethiraj

1993-01-01

Computations are presented for one-dimensional, strong shock waves that are typical of those that form in front of a reentering spacecraft. The fluid mechanics and thermochemistry are modeled using two different approaches. The first employs traditional continuum techniques in solving the Navier-Stokes equations. The second-approach employs a particle simulation technique (the direct simulation Monte Carlo method, DSMC). The thermochemical models employed in these two techniques are quite different. The present investigation presents an evaluation of thermochemical models for nitrogen under hypersonic flow conditions. Four separate cases are considered. The cases are governed, respectively, by the following: vibrational relaxation; weak dissociation; strong dissociation; and weak ionization. In near-continuum, hypersonic flow, the nonequilibrium thermochemical models employed in continuum and particle simulations produce nearly identical solutions. Further, the two approaches are evaluated successfully against available experimental data for weakly and strongly dissociating flows.

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.

Radiolytic Model for Chemical Composition of Europa's Atmosphere and Surface

NASA Technical Reports Server (NTRS)

Cooper, John F.

2004-01-01

The overall objective of the present effort is to produce models for major and selected minor components of Europa s neutral atmosphere in 1-D versus altitude and in 2-D versus altitude and longitude or latitude. A 3-D model versus all three coordinates (alt, long, lat) will be studied but development on this is at present limited by computing facilities available to the investigation team. In this first year we have focused on 1-D modeling with Co-I Valery Shematovich s Direct Simulation Monte Carlo (DSMC) code for water group species (H2O, O2, O, OH) and on 2-D with Co-I Mau Wong's version of a similar code for O2, O, CO, CO2, and Na. Surface source rates of H2O and O2 from sputtering and radiolysis are used in the 1-D model, while observations for CO2 at the Europa surface and Na detected in a neutral cloud ejected from Europa are used, along with the O2 sputtering rate, to constrain source rates in the 2-D version. With these separate approaches we are investigating a range of processes important to eventual implementation of a comprehensive 3-D atmospheric model which could be used to understand present observations and develop science requirements for future observations, e.g. from Earth and in Europa orbit. Within the second year we expect to merge the full water group calculations into the 2-D version of the DSMC code which can then be extended to 3-D, pending availability of computing resources. Another important goal in the second year would be the inclusion of sulk and its more volatile oxides (SO, SO2).

Aerodynamic characteristics of the upper stages of a launch vehicle in low-density regime

NASA Astrophysics Data System (ADS)

Oh, Bum Seok; Lee, Joon Ho

2016-11-01

Aerodynamic characteristics of the orbital block (remaining configuration after separation of nose fairing and 1st and 2nd stages of the launch vehicle) and the upper 2-3stage (configuration after separation of 1st stage) of the 3 stages launch vehicle (KSLV-II, Korea Space Launch Vehicle) at high altitude of low-density regime are analyzed by SMILE code which is based on DSMC (Direct Simulation Monte-Carlo) method. To validating of the SMILE code, coefficients of axial force and normal forces of Apollo capsule are also calculated and the results agree very well with the data predicted by others. For the additional validations and applications of the DSMC code, aerodynamic calculation results of simple shapes of plate and wedge in low-density regime are also introduced. Generally, aerodynamic characteristics in low-density regime differ from those of continuum regime. To understand those kinds of differences, aerodynamic coefficients of the upper stages (including upper 2-3 stage and the orbital block) of the launch vehicle in low-density regime are analyzed as a function of Mach numbers and altitudes. The predicted axial force coefficients of the upper stages of the launch vehicle are very high compared to those in continuum regime. In case of the orbital block which flies at very high altitude (higher than 250km), all aerodynamic coefficients are more dependent on velocity variations than altitude variations. In case of the upper 2-3 stage which flies at high altitude (80km-150km), while the axial force coefficients and the locations of center of pressure are less changed with the variations of Knudsen numbers (altitudes), the normal force coefficients and pitching moment coefficients are more affected by variations of Knudsen numbers (altitude).

Collision of Physics and Software in the Monte Carlo Application Toolkit (MCATK)

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

Sweezy, Jeremy Ed

2016-01-21

The topic is presented in a series of slides organized as follows: MCATK overview, development strategy, available algorithms, problem modeling (sources, geometry, data, tallies), parallelism, miscellaneous tools/features, example MCATK application, recent areas of research, and summary and future work. MCATK is a C++ component-based Monte Carlo neutron-gamma transport software library with continuous energy neutron and photon transport. Designed to build specialized applications and to provide new functionality in existing general-purpose Monte Carlo codes like MCNP, it reads ACE formatted nuclear data generated by NJOY. The motivation behind MCATK was to reduce costs. MCATK physics involves continuous energy neutron & gammamore » transport with multi-temperature treatment, static eigenvalue (k eff and α) algorithms, time-dependent algorithm, and fission chain algorithms. MCATK geometry includes mesh geometries and solid body geometries. MCATK provides verified, unit-test Monte Carlo components, flexibility in Monte Carlo application development, and numerous tools such as geometry and cross section plotters.« less

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

Tortuosity Computations of Porous Materials using the Direct Simulation Monte Carlo

NASA Technical Reports Server (NTRS)

Borner, A.; Ferguson, C.; Panerai, F.; Mansour, Nagi N.

2017-01-01

Low-density carbon fiber preforms, used as thermal protection systems (TPS) materials for planetary entry systems, have permeable, highly porous microstructures consisting of interlaced fibers. Internal gas transport in TPS is important in modeling the penetration of hot boundary-layer gases and the in-depth transport of pyrolysis and ablation products. The gas effective diffusion coefficient of a porous material must be known before the gas transport can be modeled in material response solvers; however, there are very little available data for rigid fibrous insulators used in heritage TPS.The tortuosity factor, which reflects the efficiency of the percolation paths, can be computed from the effective diffusion coefficient of a gas inside a porous material and is based on the micro-structure of the material. It is well known, that the tortuosity factor is a strong function of the Knudsen number. Due to the small characteristic scales of porous media used in TPS applications (typical pore size of the order of 50 micron), the transport of gases can occur in the rarefied and transitional regimes, at Knudsen numbers above 1. A proper way to model the gas dynamics at these conditions consists in solving the Boltzmann equation using particle-based methods that account for movement and collisions of atoms and molecules.In this work we adopt, for the first time, the Direct Simulation Monte Carlo (DSMC) method to compute the tortuosity factor of fibrous media in the rarefied regime. To enable realistic simulations of the actual transport of gases in the porous medium, digitized computational grids are obtained from X-ray micro-tomography imaging of real TPS materials. The SPARTA DSMC solver is used for simulations. Effective diffusion coefficients and tortuosity factors are obtained by computing the mean-square displacement of diffusing particles.We first apply the method to compute the tortuosity factors as a function of the Knudsen number for computationally designed materials such as random cylindrical fibers and packed bed of spheres with prescribed porosity. Results are compared to literature values obtained using random walk methods in the rarefied and transitional regime and a finite-volume method for the continuum regime. We then compute tortuosity factors for a real carbon fiber material with a transverse isotropic structure (FiberForm), quantifying differences between through-thickness and in-plain tortuosities at various Knudsen regimes.

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

DSMC Simulations of Disturbance Torque to ISS During Airlock Depressurization

NASA Technical Reports Server (NTRS)

Lumpkin, F. E., III; Stewart, B. S.

2015-01-01

The primary attitude control system on the International Space Station (ISS) is part of the United States On-orbit Segment (USOS) and uses Control Moment Gyroscopes (CMG). The secondary system is part of the Russian On orbit Segment (RSOS) and uses a combination of gyroscopes and thrusters. Historically, events with significant disturbances such as the airlock depressurizations associated with extra-vehicular activity (EVA) have been performed using the RSOS attitude control system. This avoids excessive propulsive "de-saturations" of the CMGs. However, transfer of attitude control is labor intensive and requires significant propellant. Predictions employing NASA's DSMC Analysis Code (DAC) of the disturbance torque to the ISS for depressurization of the Pirs airlock on the RSOS will be presented [1]. These predictions were performed to assess the feasibility of using USOS control during these events. The ISS Pirs airlock is vented using a device known as a "T-vent" as shown in the inset in figure 1. By orienting two equal streams of gas in opposite directions, this device is intended to have no propulsive effect. However, disturbance force and torque to the ISS do occur due to plume impingement. The disturbance torque resulting from the Pirs depressurization during EVAs is estimated by using a loosely coupled CFD/DSMC technique [2]. CFD is used to simulate the flow field in the nozzle and the near field plume. DSMC is used to simulate the remaining flow field using the CFD results to create an in flow boundary to the DSMC simulation. Due to the highly continuum nature of flow field near the T-vent, two loosely coupled DSMC domains are employed. An 88.2 cubic meter inner domain contains the Pirs airlock and the T-vent. Inner domain results are used to create an in flow boundary for an outer domain containing the remaining portions of the ISS. Several orientations of the ISS solar arrays and radiators have been investigated to find cases that result in minimal disturbance torque. Figure 1 shows surface pressure contours on the ISS and a plane of number density contours for a particular case.

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.

Event-chain Monte Carlo algorithms for three- and many-particle interactions

NASA Astrophysics Data System (ADS)

Harland, J.; Michel, M.; Kampmann, T. A.; Kierfeld, J.

2017-02-01

We generalize the rejection-free event-chain Monte Carlo algorithm from many-particle systems with pairwise interactions to systems with arbitrary three- or many-particle interactions. We introduce generalized lifting probabilities between particles and obtain a general set of equations for lifting probabilities, the solution of which guarantees maximal global balance. We validate the resulting three-particle event-chain Monte Carlo algorithms on three different systems by comparison with conventional local Monte Carlo simulations: i) a test system of three particles with a three-particle interaction that depends on the enclosed triangle area; ii) a hard-needle system in two dimensions, where needle interactions constitute three-particle interactions of the needle end points; iii) a semiflexible polymer chain with a bending energy, which constitutes a three-particle interaction of neighboring chain beads. The examples demonstrate that the generalization to many-particle interactions broadens the applicability of event-chain algorithms considerably.

International Cooperation. The Next Generation. Report of the DSMC 1990 - 1991 Military Research Fellows

DTIC Science & Technology

1991-09-01

Maintaining Goal Congruence International Cooperation-the Next Generation ENDNOTES 1. Wolfgang Flume and David Swa, "British Aerospace-Leading...Program Management Questionnaire Report. Michael G. Krause , DSMC internal document, May 1989- 10. Bonn Seminar on Armaments cooperation, proceedings, w...Appendix K 154 International Cooperation-the Next Generation Dudney, Robert S., "The Electronics Industry Flume, Wolfgang , "Electronics for the Ger- Is

Scalable Domain Decomposed Monte Carlo Particle Transport

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

O'Brien, Matthew Joseph

2013-12-05

In this dissertation, we present the parallel algorithms necessary to run domain decomposed Monte Carlo particle transport on large numbers of processors (millions of processors). Previous algorithms were not scalable, and the parallel overhead became more computationally costly than the numerical simulation.

Implementation of Monte Carlo Dose calculation for CyberKnife treatment planning

NASA Astrophysics Data System (ADS)

Ma, C.-M.; Li, J. S.; Deng, J.; Fan, J.

2008-02-01

Accurate dose calculation is essential to advanced stereotactic radiosurgery (SRS) and stereotactic radiotherapy (SRT) especially for treatment planning involving heterogeneous patient anatomy. This paper describes the implementation of a fast Monte Carlo dose calculation algorithm in SRS/SRT treatment planning for the CyberKnife® SRS/SRT system. A superposition Monte Carlo algorithm is developed for this application. Photon mean free paths and interaction types for different materials and energies as well as the tracks of secondary electrons are pre-simulated using the MCSIM system. Photon interaction forcing and splitting are applied to the source photons in the patient calculation and the pre-simulated electron tracks are repeated with proper corrections based on the tissue density and electron stopping powers. Electron energy is deposited along the tracks and accumulated in the simulation geometry. Scattered and bremsstrahlung photons are transported, after applying the Russian roulette technique, in the same way as the primary photons. Dose calculations are compared with full Monte Carlo simulations performed using EGS4/MCSIM and the CyberKnife treatment planning system (TPS) for lung, head & neck and liver treatments. Comparisons with full Monte Carlo simulations show excellent agreement (within 0.5%). More than 10% differences in the target dose are found between Monte Carlo simulations and the CyberKnife TPS for SRS/SRT lung treatment while negligible differences are shown in head and neck and liver for the cases investigated. The calculation time using our superposition Monte Carlo algorithm is reduced up to 62 times (46 times on average for 10 typical clinical cases) compared to full Monte Carlo simulations. SRS/SRT dose distributions calculated by simple dose algorithms may be significantly overestimated for small lung target volumes, which can be improved by accurate Monte Carlo dose calculations.

Hybrid dose calculation: a dose calculation algorithm for microbeam radiation therapy

NASA Astrophysics Data System (ADS)

Donzelli, Mattia; Bräuer-Krisch, Elke; Oelfke, Uwe; Wilkens, Jan J.; Bartzsch, Stefan

2018-02-01

Microbeam radiation therapy (MRT) is still a preclinical approach in radiation oncology that uses planar micrometre wide beamlets with extremely high peak doses, separated by a few hundred micrometre wide low dose regions. Abundant preclinical evidence demonstrates that MRT spares normal tissue more effectively than conventional radiation therapy, at equivalent tumour control. In order to launch first clinical trials, accurate and efficient dose calculation methods are an inevitable prerequisite. In this work a hybrid dose calculation approach is presented that is based on a combination of Monte Carlo and kernel based dose calculation. In various examples the performance of the algorithm is compared to purely Monte Carlo and purely kernel based dose calculations. The accuracy of the developed algorithm is comparable to conventional pure Monte Carlo calculations. In particular for inhomogeneous materials the hybrid dose calculation algorithm out-performs purely convolution based dose calculation approaches. It is demonstrated that the hybrid algorithm can efficiently calculate even complicated pencil beam and cross firing beam geometries. The required calculation times are substantially lower than for pure Monte Carlo calculations.

Open Source Software Openfoam as a New Aerodynamical Simulation Tool for Rocket-Borne Measurements

NASA Astrophysics Data System (ADS)

Staszak, T.; Brede, M.; Strelnikov, B.

2015-09-01

The only way to do in-situ measurements, which are very important experimental studies for atmospheric science, in the mesoshere/lower thermosphere (MLT) is to use sounding rockets. The drawback of using rockets is the shock wave appearing because of the very high speed of the rocket motion (typically about 1000 mIs). This shock wave disturbs the density, the temperature and the velocity fields in the vicinity of the rocket, compared to undisturbed values of the atmosphere. This effect, however, can be quantified and the measured data has to be corrected not just to make it more precise but simply usable. The commonly accepted and widely used tool for this calculations is the Direct Simulation Monte Carlo (DSMC) technique developed by GA. Bird which is available as stand-alone program limited to use a single processor. Apart from complications with simulations of flows around bodies related to different flow regimes in the altitude range of MLT, that rise due to exponential density change by several orders of magnitude, a particular hardware configuration introduces significant difficulty for aerodynamical calculations due to choice of the grid sizes mainly depending on the demands on adequate DSMCs and good resolution of geometries with scale differences of factor of iO~. This makes either the calculation time unreasonably long or even prevents the calculation algorithm from converging. In this paper we apply the free open source software OpenFOAM (licensed under GNU GPL) for a three-dimensional CFD-Simulation of a flow around a sounding rocket instrumentation. An advantage of this software package, among other things, is that it can run on high performance clusters, which are easily scalable. We present the first results and discuss the potential of the new tool in applications for sounding rockets.

Event-chain algorithm for the Heisenberg model: Evidence for z≃1 dynamic scaling.

PubMed

Nishikawa, Yoshihiko; Michel, Manon; Krauth, Werner; Hukushima, Koji

2015-12-01

We apply the event-chain Monte Carlo algorithm to the three-dimensional ferromagnetic Heisenberg model. The algorithm is rejection-free and also realizes an irreversible Markov chain that satisfies global balance. The autocorrelation functions of the magnetic susceptibility and the energy indicate a dynamical critical exponent z≈1 at the critical temperature, while that of the magnetization does not measure the performance of the algorithm. We show that the event-chain Monte Carlo algorithm substantially reduces the dynamical critical exponent from the conventional value of z≃2.

Data decomposition of Monte Carlo particle transport simulations via tally servers

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

Romano, Paul K.; Siegel, Andrew R.; Forget, Benoit

An algorithm for decomposing large tally data in Monte Carlo particle transport simulations is developed, analyzed, and implemented in a continuous-energy Monte Carlo code, OpenMC. The algorithm is based on a non-overlapping decomposition of compute nodes into tracking processors and tally servers. The former are used to simulate the movement of particles through the domain while the latter continuously receive and update tally data. A performance model for this approach is developed, suggesting that, for a range of parameters relevant to LWR analysis, the tally server algorithm should perform with minimal overhead on contemporary supercomputers. An implementation of the algorithmmore » in OpenMC is then tested on the Intrepid and Titan supercomputers, supporting the key predictions of the model over a wide range of parameters. We thus conclude that the tally server algorithm is a successful approach to circumventing classical on-node memory constraints en route to unprecedentedly detailed Monte Carlo reactor simulations.« less

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.

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.

Scalable Domain Decomposed Monte Carlo Particle Transport

NASA Astrophysics Data System (ADS)

O'Brien, Matthew Joseph

In this dissertation, we present the parallel algorithms necessary to run domain decomposed Monte Carlo particle transport on large numbers of processors (millions of processors). Previous algorithms were not scalable, and the parallel overhead became more computationally costly than the numerical simulation. The main algorithms we consider are: • Domain decomposition of constructive solid geometry: enables extremely large calculations in which the background geometry is too large to fit in the memory of a single computational node. • Load Balancing: keeps the workload per processor as even as possible so the calculation runs efficiently. • Global Particle Find: if particles are on the wrong processor, globally resolve their locations to the correct processor based on particle coordinate and background domain. • Visualizing constructive solid geometry, sourcing particles, deciding that particle streaming communication is completed and spatial redecomposition. These algorithms are some of the most important parallel algorithms required for domain decomposed Monte Carlo particle transport. We demonstrate that our previous algorithms were not scalable, prove that our new algorithms are scalable, and run some of the algorithms up to 2 million MPI processes on the Sequoia supercomputer.

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.

The Impact of Monte Carlo Dose Calculations on Intensity-Modulated Radiation Therapy

NASA Astrophysics Data System (ADS)

Siebers, J. V.; Keall, P. J.; Mohan, R.

The effect of dose calculation accuracy for IMRT was studied by comparing different dose calculation algorithms. A head and neck IMRT plan was optimized using a superposition dose calculation algorithm. Dose was re-computed for the optimized plan using both Monte Carlo and pencil beam dose calculation algorithms to generate patient and phantom dose distributions. Tumor control probabilities (TCP) and normal tissue complication probabilities (NTCP) were computed to estimate the plan outcome. For the treatment plan studied, Monte Carlo best reproduces phantom dose measurements, the TCP was slightly lower than the superposition and pencil beam results, and the NTCP values differed little.

A shock-layer theory based on thirteen-moment equations and DSMC calculations of rarefied hypersonic flows

NASA Technical Reports Server (NTRS)

Cheng, H. K.; Wong, Eric Y.; Dogra, V. K.

1991-01-01

Grad's thirteen-moment equations are applied to the flow behind a bow shock under the formalism of a thin shock layer. Comparison of this version of the theory with Direct Simulation Monte Carlo calculations of flows about a flat plate at finite attack angle has lent support to the approach as a useful extension of the continuum model for studying translational nonequilibrium in the shock layer. This paper reassesses the physical basis and limitations of the development with additional calculations and comparisons. The streamline correlation principle, which allows transformation of the 13-moment based system to one based on the Navier-Stokes equations, is extended to a three-dimensional formulation. The development yields a strip theory for planar lifting surfaces at finite incidences. Examples reveal that the lift-to-drag ratio is little influenced by planform geometry and varies with altitudes according to a 'bridging function' determined by correlated two-dimensional calculations.

Simulating Irregular Source Geometries for Ionian Plumes

NASA Astrophysics Data System (ADS)

McDoniel, W. J.; Goldstein, D. B.; Varghese, P. L.; Trafton, L. M.; Buchta, D. A.; Freund, J.; Kieffer, S. W.

2011-05-01

Volcanic plumes on Io respresent a complex rarefied flow into a near-vacuum in the presence of gravity. A 3D Direct Simulation Monte Carlo (DSMC) method is used to investigate the gas dynamics of such plumes, with a focus on the effects of source geometry on far-field deposition patterns. A rectangular slit and a semicircular half annulus are simulated to illustrate general principles, especially the effects of vent curvature on deposition ring structure. Then two possible models for the giant plume Pele are presented. One is a curved line source corresponding to an IR image of a particularly hot region in the volcano's caldera and the other is a large area source corresponding to the entire caldera. The former is seen to produce the features seen in observations of Pele's ring, but with an error in orientation. The latter corrects the error in orientation, but loses some structure. A hybrid simulation of 3D slit flow is also discussed.

Orion Aerodynamics for Hypersonic Free Molecular to Continuum Conditions

NASA Technical Reports Server (NTRS)

Moss, James N.; Greene, Francis A.; Boyles, Katie A.

2006-01-01

Numerical simulations are performed for the Orion Crew Module, previously known as the Crew Exploration Vehicle (CEV) Command Module, to characterize its aerodynamics during the high altitude portion of its reentry into the Earth's atmosphere, that is, from free molecular to continuum hypersonic conditions. The focus is on flow conditions similar to those that the Orion Crew Module would experience during a return from the International Space Station. The bulk of the calculations are performed with two direct simulation Monte Carlo (DSMC) codes, and these data are anchored with results from both free molecular and Navier-Stokes calculations. Results for aerodynamic forces and moments are presented that demonstrate their sensitivity to rarefaction, that is, for free molecular to continuum conditions (Knudsen numbers of 111 to 0.0003). Also included are aerodynamic data as a function of angle of attack for different levels of rarefaction and results that demonstrate the aerodynamic sensitivity of the Orion CM to a range of reentry velocities (7.6 to 15 km/s).

Blunt Body Aerodynamics for Hypersonic Low Density Flows

NASA Technical Reports Server (NTRS)

Moss, James N.; Glass, Christopher E.; Greene, Francis A.

2006-01-01

Numerical simulations are performed for the Apollo capsule from the hypersonic rarefied to the continuum regimes. The focus is on flow conditions similar to those experienced by the Apollo 6 Command Module during the high altitude portion of its reentry. The present focus is to highlight some of the current activities that serve as a precursor for computational tool assessments that will be used to support the development of aerodynamic data bases for future capsule flight environments, particularly those for the Crew Exploration Vehicle (CEV). Results for aerodynamic forces and moments are presented that demonstrate their sensitivity to rarefaction; that is, free molecular to continuum conditions. Also, aerodynamic data are presented that shows their sensitivity to a range of reentry velocities, encompassing conditions that include reentry from low Earth orbit, lunar return, and Mars return velocities (7.7 to 15 km/s). The rarefied results obtained with direct simulation Monte Carlo (DSMC) codes are anchored in the continuum regime with data from Navier-Stokes simulations.

Three-dimensional implementation of the Low Diffusion method for continuum flow simulations

NASA Astrophysics Data System (ADS)

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

2017-11-01

Concepts of a particle-based continuum method have existed for many years. The ultimate goal is to couple such a method with the Direct Simulation Monte Carlo (DSMC) in order to bridge the gap of numerical tools in the treatment of the transitional flow regime between near-equilibrium and rarefied gas flows. For this purpose, the Low Diffusion (LD) method, introduced first by Burt and Boyd, offers a promising solution. In this paper, the LD method is revisited and the implementation in a modern particle solver named PICLas is given. The modifications of the LD routines enable three-dimensional continuum flow simulations. The implementation is successfully verified through a series of test cases: simple stationary shock, oblique shock simulation and thermal Couette flow. Additionally, the capability of this method is demonstrated by the simulation of a hypersonic nitrogen flow around a 70°-blunted cone. Overall results are in very good agreement with experimental data. Finally, the scalability of PICLas using LD on a high performance cluster is presented.

Simulation of Interaction of Strong Shocks with Gas Bubbles using the Direct Simulation Monte Carlo Method

NASA Astrophysics Data System (ADS)

Puranik, Bhalchandra; Watvisave, Deepak; Bhandarkar, Upendra

2016-11-01

The interaction of a shock with a density interface is observed in several technological applications such as supersonic combustion, inertial confinement fusion, and shock-induced fragmentation of kidney and gall-stones. The central physical process in this interaction is the mechanism of the Richtmyer-Meshkov Instability (RMI). The specific situation where the density interface is initially an isolated spherical or cylindrical gas bubble presents a relatively simple geometry that exhibits all the essential RMI processes such as reflected and refracted shocks, secondary instabilities, turbulence and mixing of the species. If the incident shocks are strong, the calorically imperfect nature needs to be modelled. In the present work, we have carried out simulations of the shock-bubble interaction using the DSMC method for such situations. Specifically, an investigation of the shock-bubble interaction with diatomic gases involving rotational and vibrational excitations at high temperatures is performed, and the effects of such high temperature phenomena will be presented.

The study of sound wave propagation in rarefied gases using unified gas-kinetic scheme

NASA Astrophysics Data System (ADS)

Wang, Rui-Jie; Xu, Kun

2012-08-01

Sound wave propagation in rarefied monatomic gases is simulated using a newly developed unified gaskinetic scheme (UGKS). The numerical calculations are carried out for a wide range of wave oscillating frequencies. The corresponding rarefaction parameter is defined as the ratio of sound wave frequency to the intermolecular particle collision frequency. The simulation covers the flow regime from the continuum to free molecule one. The treatment of the oscillating wall boundary condition and the methods for evaluating the absorption coefficient and sound wave speed are presented in detail. The simulation results from the UGKS are compared to the Navier-Stokes solutions, the direct simulation Monte Carlo (DSMC) simulation, and experimental measurements. Good agreement with the experimental data has been obtained in the whole flow regimes for the corresponding Knudsen number from 0.08 to 32. The current study clearly demonstrates the capability of the UGKS method in capturing the sound wave propagation and its usefulness for the rarefied flow study.

Experimental and Numerical Study of Nozzle Plume Impingement on Spacecraft Surfaces

NASA Astrophysics Data System (ADS)

Ketsdever, A. D.; Lilly, T. C.; Gimelshein, S. F.; Alexeenko, A. A.

2005-05-01

An experimental and numerical effort was undertaken to assess the effects of a cold gas (To=300K) nozzle plume impinging on a simulated spacecraft surface. The nozzle flow impingement is investigated experimentally using a nano-Newton resolution force balance and numerically using the Direct Simulation Monte Carlo (DSMC) numerical technique. The Reynolds number range investigated in this study is from 0.5 to approximately 900 using helium and nitrogen propellants. The thrust produced by the nozzle was first assessed on a force balance to provide a baseline case. Subsequently, an aluminum plate was attached to the same force balance at various angles from 0° (parallel to the plume flow) to 10°. For low Reynolds number helium flow, a 16.5% decrease in thrust was measured for the plate at 0° relative to the free plume expansion case. For low Reynolds number nitrogen flow, the difference was found to be 12%. The thrust degradation was found to decrease at higher Reynolds numbers and larger plate angles.

Thermally induced gas flows in ratchet channels with diffuse and specular boundaries

PubMed Central

Shahabi, Vahid; Baier, Tobias; Roohi, Ehsan; Hardt, Steffen

2017-01-01

A net gas flow can be induced in the gap between periodically structured surfaces held at fixed but different temperatures when the reflection symmetry along the channel axis is broken. Such a situation arises when one surface features a ratchet structure and can be augmented by altering the boundary conditions on different parts of this surface, with some regions reflecting specularly and others diffusely. In order to investigate the physical mechanisms inducing the flow in this configuration at various Knudsen numbers and geometric configurations, direct simulation Monte Carlo (DSMC) simulations are employed using transient adaptive subcells for collision partner selection. At large Knudsen numbers the results compare favorably with analytical expressions, while for small Knudsen numbers a qualitative explanation for the flow in the strong temperature inhomogeneity at the tips of the ratchet is provided. A detailed investigation of the performance for various ratchet geometries suggests optimum working conditions for a Knudsen pump based on this mechanism. PMID:28128309

A paradigm for modeling and computation of gas dynamics

NASA Astrophysics Data System (ADS)

Xu, Kun; Liu, Chang

2017-02-01

In the continuum flow regime, the Navier-Stokes (NS) equations are usually used for the description of gas dynamics. On the other hand, the Boltzmann equation is applied for the rarefied flow. These two equations are based on distinguishable modeling scales for flow physics. Fortunately, due to the scale separation, i.e., the hydrodynamic and kinetic ones, both the Navier-Stokes equations and the Boltzmann equation are applicable in their respective domains. However, in real science and engineering applications, they may not have such a distinctive scale separation. For example, around a hypersonic flying vehicle, the flow physics at different regions may correspond to different regimes, where the local Knudsen number can be changed significantly in several orders of magnitude. With a variation of flow physics, theoretically a continuous governing equation from the kinetic Boltzmann modeling to the hydrodynamic Navier-Stokes dynamics should be used for its efficient description. However, due to the difficulties of a direct modeling of flow physics in the scale between the kinetic and hydrodynamic ones, there is basically no reliable theory or valid governing equations to cover the whole transition regime, except resolving flow physics always down to the mean free path scale, such as the direct Boltzmann solver and the Direct Simulation Monte Carlo (DSMC) method. In fact, it is an unresolved problem about the exact scale for the validity of the NS equations, especially in the small Reynolds number cases. The computational fluid dynamics (CFD) is usually based on the numerical solution of partial differential equations (PDEs), and it targets on the recovering of the exact solution of the PDEs as mesh size and time step converging to zero. This methodology can be hardly applied to solve the multiple scale problem efficiently because there is no such a complete PDE for flow physics through a continuous variation of scales. For the non-equilibrium flow study, the direct modeling methods, such as DSMC, particle in cell, and smooth particle hydrodynamics, play a dominant role to incorporate the flow physics into the algorithm construction directly. It is fully legitimate to combine the modeling and computation together without going through the process of constructing PDEs. In other words, the CFD research is not only to obtain the numerical solution of governing equations but to model flow dynamics as well. This methodology leads to the unified gas-kinetic scheme (UGKS) for flow simulation in all flow regimes. Based on UGKS, the boundary for the validation of the Navier-Stokes equations can be quantitatively evaluated. The combination of modeling and computation provides a paradigm for the description of multiscale transport process.

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

Monte Carlo evaluation of Acuros XB dose calculation Algorithm for intensity modulated radiation therapy of nasopharyngeal carcinoma

NASA Astrophysics Data System (ADS)

Yeh, Peter C. Y.; Lee, C. C.; Chao, T. C.; Tung, C. J.

2017-11-01

Intensity-modulated radiation therapy is an effective treatment modality for the nasopharyngeal carcinoma. One important aspect of this cancer treatment is the need to have an accurate dose algorithm dealing with the complex air/bone/tissue interface in the head-neck region to achieve the cure without radiation-induced toxicities. The Acuros XB algorithm explicitly solves the linear Boltzmann transport equation in voxelized volumes to account for the tissue heterogeneities such as lungs, bone, air, and soft tissues in the treatment field receiving radiotherapy. With the single beam setup in phantoms, this algorithm has already been demonstrated to achieve the comparable accuracy with Monte Carlo simulations. In the present study, five nasopharyngeal carcinoma patients treated with the intensity-modulated radiation therapy were examined for their dose distributions calculated using the Acuros XB in the planning target volume and the organ-at-risk. Corresponding results of Monte Carlo simulations were computed from the electronic portal image data and the BEAMnrc/DOSXYZnrc code. Analysis of dose distributions in terms of the clinical indices indicated that the Acuros XB was in comparable accuracy with Monte Carlo simulations and better than the anisotropic analytical algorithm for dose calculations in real patients.

Automatic mesh adaptivity for hybrid Monte Carlo/deterministic neutronics modeling of difficult shielding problems

DOE PAGES

Ibrahim, Ahmad M.; Wilson, Paul P.H.; Sawan, Mohamed E.; ...

2015-06-30

The CADIS and FW-CADIS hybrid Monte Carlo/deterministic techniques dramatically increase the efficiency of neutronics modeling, but their use in the accurate design analysis of very large and geometrically complex nuclear systems has been limited by the large number of processors and memory requirements for their preliminary deterministic calculations and final Monte Carlo calculation. Three mesh adaptivity algorithms were developed to reduce the memory requirements of CADIS and FW-CADIS without sacrificing their efficiency improvement. First, a macromaterial approach enhances the fidelity of the deterministic models without changing the mesh. Second, a deterministic mesh refinement algorithm generates meshes that capture as muchmore » geometric detail as possible without exceeding a specified maximum number of mesh elements. Finally, a weight window coarsening algorithm decouples the weight window mesh and energy bins from the mesh and energy group structure of the deterministic calculations in order to remove the memory constraint of the weight window map from the deterministic mesh resolution. The three algorithms were used to enhance an FW-CADIS calculation of the prompt dose rate throughout the ITER experimental facility. Using these algorithms resulted in a 23.3% increase in the number of mesh tally elements in which the dose rates were calculated in a 10-day Monte Carlo calculation and, additionally, increased the efficiency of the Monte Carlo simulation by a factor of at least 3.4. The three algorithms enabled this difficult calculation to be accurately solved using an FW-CADIS simulation on a regular computer cluster, eliminating the need for a world-class super computer.« less

Monte Carlo tests of the ELIPGRID-PC algorithm

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

Davidson, J.R.

1995-04-01

The standard tool for calculating the probability of detecting pockets of contamination called hot spots has been the ELIPGRID computer code of Singer and Wickman. The ELIPGRID-PC program has recently made this algorithm available for an IBM{reg_sign} PC. However, no known independent validation of the ELIPGRID algorithm exists. This document describes a Monte Carlo simulation-based validation of a modified version of the ELIPGRID-PC code. The modified ELIPGRID-PC code is shown to match Monte Carlo-calculated hot-spot detection probabilities to within {plus_minus}0.5% for 319 out of 320 test cases. The one exception, a very thin elliptical hot spot located within a rectangularmore » sampling grid, differed from the Monte Carlo-calculated probability by about 1%. These results provide confidence in the ability of the modified ELIPGRID-PC code to accurately predict hot-spot detection probabilities within an acceptable range of error.« less

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…

Teaching Markov Chain Monte Carlo: Revealing the Basic Ideas behind the Algorithm

ERIC Educational Resources Information Center

Stewart, Wayne; Stewart, Sepideh

2014-01-01

For many scientists, researchers and students Markov chain Monte Carlo (MCMC) simulation is an important and necessary tool to perform Bayesian analyses. The simulation is often presented as a mathematical algorithm and then translated into an appropriate computer program. However, this can result in overlooking the fundamental and deeper…

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.

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.

A High-Order Low-Order Algorithm with Exponentially Convergent Monte Carlo for Thermal Radiative Transfer

DOE PAGES

Bolding, Simon R.; Cleveland, Mathew Allen; Morel, Jim E.

2016-10-21

In this paper, we have implemented a new high-order low-order (HOLO) algorithm for solving thermal radiative transfer problems. The low-order (LO) system is based on the spatial and angular moments of the transport equation and a linear-discontinuous finite-element spatial representation, producing equations similar to the standard S 2 equations. The LO solver is fully implicit in time and efficiently resolves the nonlinear temperature dependence at each time step. The high-order (HO) solver utilizes exponentially convergent Monte Carlo (ECMC) to give a globally accurate solution for the angular intensity to a fixed-source pure-absorber transport problem. This global solution is used tomore » compute consistency terms, which require the HO and LO solutions to converge toward the same solution. The use of ECMC allows for the efficient reduction of statistical noise in the Monte Carlo solution, reducing inaccuracies introduced through the LO consistency terms. Finally, we compare results with an implicit Monte Carlo code for one-dimensional gray test problems and demonstrate the efficiency of ECMC over standard Monte Carlo in this HOLO algorithm.« less

Percentage depth dose evaluation in heterogeneous media using thermoluminescent dosimetry

PubMed Central

da Rosa, L.A.R.; Campos, L.T.; Alves, V.G.L.; Batista, D.V.S.; Facure, A.

2010-01-01

The purpose of this study is to investigate the influence of lung heterogeneity inside a soft tissue phantom on percentage depth dose (PDD). PDD curves were obtained experimentally using LiF:Mg,Ti (TLD‐100) thermoluminescent detectors and applying Eclipse treatment planning system algorithms Batho, modified Batho (M‐Batho or BMod), equivalent TAR (E‐TAR or EQTAR), and anisotropic analytical algorithm (AAA) for a 15 MV photon beam and field sizes of 1×1,2×2,5×5, and 10×10cm2. Monte Carlo simulations were performed using the DOSRZnrc user code of EGSnrc. The experimental results agree with Monte Carlo simulations for all irradiation field sizes. Comparisons with Monte Carlo calculations show that the AAA algorithm provides the best simulations of PDD curves for all field sizes investigated. However, even this algorithm cannot accurately predict PDD values in the lung for field sizes of 1×1 and 2×2cm2. An overdosage in the lung of about 40% and 20% is calculated by the AAA algorithm close to the interface soft tissue/lung for 1×1 and 2×2cm2 field sizes, respectively. It was demonstrated that differences of 100% between Monte Carlo results and the algorithms Batho, modified Batho, and equivalent TAR responses may exist inside the lung region for the 1×1cm2 field. PACS number: 87.55.kd

Plume-Free Stream Interaction Heating Effects During Orion Crew Module Reentry

NASA Technical Reports Server (NTRS)

Marichalar, J.; Lumpkin, F.; Boyles, K.

2012-01-01

During reentry of the Orion Crew Module (CM), vehicle attitude control will be performed by firing reaction control system (RCS) thrusters. Simulation of RCS plumes and their interaction with the oncoming flow has been difficult for the analysis community due to the large scarf angles of the RCS thrusters and the unsteady nature of the Orion capsule backshell environments. The model for the aerothermal database has thus relied on wind tunnel test data to capture the heating effects of thruster plume interactions with the freestream. These data are only valid for the continuum flow regime of the reentry trajectory. A Direct Simulation Monte Carlo (DSMC) analysis was performed to study the vehicle heating effects that result from the RCS thruster plume interaction with the oncoming freestream flow at high altitudes during Orion CM reentry. The study was performed with the DSMC Analysis Code (DAC). The inflow boundary conditions for the jets were obtained from Data Parallel Line Relaxation (DPLR) computational fluid dynamics (CFD) solutions. Simulations were performed for the roll, yaw, pitch-up and pitch-down jets at altitudes of 105 km, 125 km and 160 km as well as vacuum conditions. For comparison purposes (see Figure 1), the freestream conditions were based on previous DAC simulations performed without active RCS to populate the aerodynamic database for the Orion CM. Other inputs to the analysis included a constant Orbital reentry velocity of 7.5 km/s and angle of attack of 160 degrees. The results of the study showed that the interaction effects decrease quickly with increasing altitude. Also, jets with highly scarfed nozzles cause more severe heating compared to the nozzles with lower scarf angles. The difficulty of performing these simulations was based on the maximum number density and the ratio of number densities between the freestream and the plume for each simulation. The lowest altitude solutions required a substantial amount of computational resources (up to 1800 processors) to simulate approximately 2 billion molecules for the refined (adapted) solutions.

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

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.

Monte Carlo uncertainty analysis of dose estimates in radiochromic film dosimetry with single-channel and multichannel algorithms.

PubMed

Vera-Sánchez, Juan Antonio; Ruiz-Morales, Carmen; González-López, Antonio

2018-03-01

To provide a multi-stage model to calculate uncertainty in radiochromic film dosimetry with Monte-Carlo techniques. This new approach is applied to single-channel and multichannel algorithms. Two lots of Gafchromic EBT3 are exposed in two different Varian linacs. They are read with an EPSON V800 flatbed scanner. The Monte-Carlo techniques in uncertainty analysis provide a numerical representation of the probability density functions of the output magnitudes. From this numerical representation, traditional parameters of uncertainty analysis as the standard deviations and bias are calculated. Moreover, these numerical representations are used to investigate the shape of the probability density functions of the output magnitudes. Also, another calibration film is read in four EPSON scanners (two V800 and two 10000XL) and the uncertainty analysis is carried out with the four images. The dose estimates of single-channel and multichannel algorithms show a Gaussian behavior and low bias. The multichannel algorithms lead to less uncertainty in the final dose estimates when the EPSON V800 is employed as reading device. In the case of the EPSON 10000XL, the single-channel algorithms provide less uncertainty in the dose estimates for doses higher than four Gy. A multi-stage model has been presented. With the aid of this model and the use of the Monte-Carlo techniques, the uncertainty of dose estimates for single-channel and multichannel algorithms are estimated. The application of the model together with Monte-Carlo techniques leads to a complete characterization of the uncertainties in radiochromic film dosimetry. Copyright © 2018 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Experiences with Markov Chain Monte Carlo Convergence Assessment in Two Psychometric Examples

ERIC Educational Resources Information Center

Sinharay, Sandip

2004-01-01

There is an increasing use of Markov chain Monte Carlo (MCMC) algorithms for fitting statistical models in psychometrics, especially in situations where the traditional estimation techniques are very difficult to apply. One of the disadvantages of using an MCMC algorithm is that it is not straightforward to determine the convergence of the…

Metis: A Pure Metropolis Markov Chain Monte Carlo Bayesian Inference Library

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

Bates, Cameron Russell; Mckigney, Edward Allen

The use of Bayesian inference in data analysis has become the standard for large scienti c experiments [1, 2]. The Monte Carlo Codes Group(XCP-3) at Los Alamos has developed a simple set of algorithms currently implemented in C++ and Python to easily perform at-prior Markov Chain Monte Carlo Bayesian inference with pure Metropolis sampling. These implementations are designed to be user friendly and extensible for customization based on speci c application requirements. This document describes the algorithmic choices made and presents two use cases.

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

Forward and inverse uncertainty quantification using multilevel Monte Carlo algorithms for an elliptic non-local equation

DOE PAGES

Jasra, Ajay; Law, Kody J. H.; Zhou, Yan

2016-01-01

Our paper considers uncertainty quantification for an elliptic nonlocal equation. In particular, it is assumed that the parameters which define the kernel in the nonlocal operator are uncertain and a priori distributed according to a probability measure. It is shown that the induced probability measure on some quantities of interest arising from functionals of the solution to the equation with random inputs is well-defined,s as is the posterior distribution on parameters given observations. As the elliptic nonlocal equation cannot be solved approximate posteriors are constructed. The multilevel Monte Carlo (MLMC) and multilevel sequential Monte Carlo (MLSMC) sampling algorithms are usedmore » for a priori and a posteriori estimation, respectively, of quantities of interest. Furthermore, these algorithms reduce the amount of work to estimate posterior expectations, for a given level of error, relative to Monte Carlo and i.i.d. sampling from the posterior at a given level of approximation of the solution of the elliptic nonlocal equation.« less

Forward and inverse uncertainty quantification using multilevel Monte Carlo algorithms for an elliptic non-local equation

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

Jasra, Ajay; Law, Kody J. H.; Zhou, Yan

Our paper considers uncertainty quantification for an elliptic nonlocal equation. In particular, it is assumed that the parameters which define the kernel in the nonlocal operator are uncertain and a priori distributed according to a probability measure. It is shown that the induced probability measure on some quantities of interest arising from functionals of the solution to the equation with random inputs is well-defined,s as is the posterior distribution on parameters given observations. As the elliptic nonlocal equation cannot be solved approximate posteriors are constructed. The multilevel Monte Carlo (MLMC) and multilevel sequential Monte Carlo (MLSMC) sampling algorithms are usedmore » for a priori and a posteriori estimation, respectively, of quantities of interest. Furthermore, these algorithms reduce the amount of work to estimate posterior expectations, for a given level of error, relative to Monte Carlo and i.i.d. sampling from the posterior at a given level of approximation of the solution of the elliptic nonlocal equation.« less

Exact and Monte carlo resampling procedures for the Wilcoxon-Mann-Whitney and Kruskal-Wallis tests.

PubMed

Berry, K J; Mielke, P W

2000-12-01

Exact and Monte Carlo resampling FORTRAN programs are described for the Wilcoxon-Mann-Whitney rank sum test and the Kruskal-Wallis one-way analysis of variance for ranks test. The program algorithms compensate for tied values and do not depend on asymptotic approximations for probability values, unlike most algorithms contained in PC-based statistical software packages.

Pattern Recognition for a Flight Dynamics Monte Carlo Simulation

NASA Technical Reports Server (NTRS)

Restrepo, Carolina; Hurtado, John E.

2011-01-01

The design, analysis, and verification and validation of a spacecraft relies heavily on Monte Carlo simulations. Modern computational techniques are able to generate large amounts of Monte Carlo data but flight dynamics engineers lack the time and resources to analyze it all. The growing amounts of data combined with the diminished available time of engineers motivates the need to automate the analysis process. Pattern recognition algorithms are an innovative way of analyzing flight dynamics data efficiently. They can search large data sets for specific patterns and highlight critical variables so analysts can focus their analysis efforts. This work combines a few tractable pattern recognition algorithms with basic flight dynamics concepts to build a practical analysis tool for Monte Carlo simulations. Current results show that this tool can quickly and automatically identify individual design parameters, and most importantly, specific combinations of parameters that should be avoided in order to prevent specific system failures. The current version uses a kernel density estimation algorithm and a sequential feature selection algorithm combined with a k-nearest neighbor classifier to find and rank important design parameters. This provides an increased level of confidence in the analysis and saves a significant amount of time.

Second-Order Consensus in Multiagent Systems via Distributed Sliding Mode Control.

PubMed

Yu, Wenwu; Wang, He; Cheng, Fei; Yu, Xinghuo; Wen, Guanghui

2016-11-22

In this paper, the new decoupled distributed sliding-mode control (DSMC) is first proposed for second-order consensus in multiagent systems, which finally solves the fundamental unknown problem for sliding-mode control (SMC) design of coupled networked systems. A distributed full-order sliding-mode surface is designed based on the homogeneity with dilation for reaching second-order consensus in multiagent systems, under which the sliding-mode states are decoupled. Then, the SMC is applied to the decoupled sliding-mode states to reach their origin in finite time, which is the sliding-mode surface. The states of agents can first reach the designed sliding-mode surface in finite time and then move to the second-order consensus state along the surface in finite time as well. The DSMC designed in this paper can eliminate the influence of singularity problems and weaken the influence of chattering, which is still very difficult in the SMC systems. In addition, DSMC proposes a general decoupling framework for designing SMC in networked multiagent systems. Simulations are presented to verify the theoretical results in this paper.

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.

Implementation of unsteady sampling procedures for the parallel direct simulation Monte Carlo method

NASA Astrophysics Data System (ADS)

Cave, H. M.; Tseng, K.-C.; Wu, J.-S.; Jermy, M. C.; Huang, J.-C.; Krumdieck, S. P.

2008-06-01

An unsteady sampling routine for a general parallel direct simulation Monte Carlo method called PDSC is introduced, allowing the simulation of time-dependent flow problems in the near continuum range. A post-processing procedure called DSMC rapid ensemble averaging method (DREAM) is developed to improve the statistical scatter in the results while minimising both memory and simulation time. This method builds an ensemble average of repeated runs over small number of sampling intervals prior to the sampling point of interest by restarting the flow using either a Maxwellian distribution based on macroscopic properties for near equilibrium flows (DREAM-I) or output instantaneous particle data obtained by the original unsteady sampling of PDSC for strongly non-equilibrium flows (DREAM-II). The method is validated by simulating shock tube flow and the development of simple Couette flow. Unsteady PDSC is found to accurately predict the flow field in both cases with significantly reduced run-times over single processor code and DREAM greatly reduces the statistical scatter in the results while maintaining accurate particle velocity distributions. Simulations are then conducted of two applications involving the interaction of shocks over wedges. The results of these simulations are compared to experimental data and simulations from the literature where there these are available. In general, it was found that 10 ensembled runs of DREAM processing could reduce the statistical uncertainty in the raw PDSC data by 2.5-3.3 times, based on the limited number of cases in the present study.

GPU-powered Shotgun Stochastic Search for Dirichlet process mixtures of Gaussian Graphical Models

PubMed Central

Mukherjee, Chiranjit; Rodriguez, Abel

2016-01-01

Gaussian graphical models are popular for modeling high-dimensional multivariate data with sparse conditional dependencies. A mixture of Gaussian graphical models extends this model to the more realistic scenario where observations come from a heterogenous population composed of a small number of homogeneous sub-groups. In this paper we present a novel stochastic search algorithm for finding the posterior mode of high-dimensional Dirichlet process mixtures of decomposable Gaussian graphical models. Further, we investigate how to harness the massive thread-parallelization capabilities of graphical processing units to accelerate computation. The computational advantages of our algorithms are demonstrated with various simulated data examples in which we compare our stochastic search with a Markov chain Monte Carlo algorithm in moderate dimensional data examples. These experiments show that our stochastic search largely outperforms the Markov chain Monte Carlo algorithm in terms of computing-times and in terms of the quality of the posterior mode discovered. Finally, we analyze a gene expression dataset in which Markov chain Monte Carlo algorithms are too slow to be practically useful. PMID:28626348

GPU-powered Shotgun Stochastic Search for Dirichlet process mixtures of Gaussian Graphical Models.

PubMed

Mukherjee, Chiranjit; Rodriguez, Abel

2016-01-01

Gaussian graphical models are popular for modeling high-dimensional multivariate data with sparse conditional dependencies. A mixture of Gaussian graphical models extends this model to the more realistic scenario where observations come from a heterogenous population composed of a small number of homogeneous sub-groups. In this paper we present a novel stochastic search algorithm for finding the posterior mode of high-dimensional Dirichlet process mixtures of decomposable Gaussian graphical models. Further, we investigate how to harness the massive thread-parallelization capabilities of graphical processing units to accelerate computation. The computational advantages of our algorithms are demonstrated with various simulated data examples in which we compare our stochastic search with a Markov chain Monte Carlo algorithm in moderate dimensional data examples. These experiments show that our stochastic search largely outperforms the Markov chain Monte Carlo algorithm in terms of computing-times and in terms of the quality of the posterior mode discovered. Finally, we analyze a gene expression dataset in which Markov chain Monte Carlo algorithms are too slow to be practically useful.

Search strategy in a complex and dynamic environment (the Indian Ocean case)

NASA Astrophysics Data System (ADS)

Loire, Sophie; Arbabi, Hassan; Clary, Patrick; Ivic, Stefan; Crnjaric-Zic, Nelida; Macesic, Senka; Crnkovic, Bojan; Mezic, Igor; UCSB Team; Rijeka Team

2014-11-01

The disappearance of Malaysia Airlines Flight 370 (MH370) in the early morning hours of 8 March 2014 has exposed the disconcerting lack of efficient methods for identifying where to look and how to look for missing objects in a complex and dynamic environment. The search area for plane debris is a remote part of the Indian Ocean. Searches, of the lawnmower type, have been unsuccessful so far. Lagrangian kinematics of mesoscale features are visible in hypergraph maps of the Indian Ocean surface currents. Without a precise knowledge of the crash site, these maps give an estimate of the time evolution of any initial distribution of plane debris and permits the design of a search strategy. The Dynamic Spectral Multiscale Coverage search algorithm is modified to search a spatial distribution of targets that is evolving with time following the dynamic of ocean surface currents. Trajectories are generated for multiple search agents such that their spatial coverage converges to the target distribution. Central to this DSMC algorithm is a metric for the ergodicity.

Modelling of the inner gas and dust coma of comet 67P/Churyumov-Gerasimenko using ROSINA/COPS and OSIRIS data - First results

NASA Astrophysics Data System (ADS)

Marschall, R.; Su, C. C.; Liao, Y.; Thomas, N.; Wu, J. S.; Altwegg, K.; Sierks, H.; Ip, W.-H.; Keller, H. U.; Knollenberg, J.; Kührt, E.; Lai, I. L.; Rubin, M.; Skorov, Y.; Jorda, L.; Preusker, F.; Scholten, F.; Gicquel, A.; Gracia-Berná, A.; Naletto, G.

2015-10-01

The physics of the outflow above the surface of comets is somewhat complex. Ice sublimating into vacuum forms a non-equilibrium boundary layer, the "Knudsen layer" (Kn-layer), with a scale height of #20 mean free paths. If the production rate is low, the Kn-layer becomes infinitely thick and the velocity distribution function (VDF) remains strongly non-Maxwellian. Thus our preferred method for gas dynamics simulations of the coma is Direct Simulation Monte Carlo DSMC. Here we report on the first results of models of the outflow from the Rosetta target, comet67P/Churyumov-Gerasimenko (C-G). Our aims are to (1) determine the gas flow-field of H2O and CO2 in the innermost coma and compare the results to the in-situ measurements of the ROSINA/COPS instrument (2) produce artificial images of the dust brightnesses that can be compared to the OSIRIS cameras. The comparison with ROSINA/COPS and OSIRIS data help to constrain the initial conditions of the simulations and thus yield information on the surface processes.

Simulation Approach for Microscale Noncontinuum Gas-Phase Heat Transfer

NASA Astrophysics Data System (ADS)

Torczynski, J. R.; Gallis, M. A.

2008-11-01

In microscale thermal actuators, gas-phase heat transfer from the heated beams to the adjacent unheated substrate is often the main energy-loss mechanism. Since the beam-substrate gap is comparable to the molecular mean free path, noncontinuum gas effects are important. A simulation approach is presented in which gas-phase heat transfer is described by Fourier's law in the bulk gas and by a wall boundary condition that equates the normal heat flux to the product of the gas-solid temperature difference and a heat transfer coefficient. The dimensionless parameters in this heat transfer coefficient are determined by comparison to Direct Simulation Monte Carlo (DSMC) results for heat transfer from beams of rectangular cross section to the substrate at free-molecular to near-continuum gas pressures. This simulation approach produces reasonably accurate gas-phase heat-transfer results for wide ranges of beam geometries and gas pressures. 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.

Gas Near a Wall: Shortened Mean Free Path, Reduced Viscosity, and the Manifestation of the Knudsen Layer in the Navier-Stokes Solution of a Shear Flow

NASA Astrophysics Data System (ADS)

Abramov, Rafail V.

2018-06-01

For the gas near a solid planar wall, we propose a scaling formula for the mean free path of a molecule as a function of the distance from the wall, under the assumption of a uniform distribution of the incident directions of the molecular free flight. We subsequently impose the same scaling onto the viscosity of the gas near the wall and compute the Navier-Stokes solution of the velocity of a shear flow parallel to the wall. Under the simplifying assumption of constant temperature of the gas, the velocity profile becomes an explicit nonlinear function of the distance from the wall and exhibits a Knudsen boundary layer near the wall. To verify the validity of the obtained formula, we perform the Direct Simulation Monte Carlo computations for the shear flow of argon and nitrogen at normal density and temperature. We find excellent agreement between our velocity approximation and the computed DSMC velocity profiles both within the Knudsen boundary layer and away from it.

Extension of the quantum-kinetic model to lunar and Mars return physics

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

Liechty, D. S.; Lewis, M. J.

The ability to compute rarefied, ionized hypersonic flows is becoming more important as missions such as Earth reentry, landing high-mass payloads on Mars, and the exploration of the outer planets and their satellites are being considered. A recently introduced molecular-level chemistry model, the quantum-kinetic, or Q-K, model that predicts reaction rates for gases in thermal equilibrium and non-equilibrium using only kinetic theory and fundamental molecular properties, is extended in the current work to include electronic energy level transitions and reactions involving charged particles. Like the Q-K procedures for neutral species chemical reactions, these new models are phenomenological procedures that aimmore » to reproduce the reaction/transition rates but do not necessarily capture the exact physics. These engineering models are necessarily efficient due to the requirement to compute billions of simulated collisions in direct simulation Monte Carlo (DSMC) simulations. The new models are shown to generally agree within the spread of reported transition and reaction rates from the literature for near equilibrium conditions.« less

New approach in direct-simulation of gas mixtures

NASA Technical Reports Server (NTRS)

Chung, Chan-Hong; De Witt, Kenneth J.; Jeng, Duen-Ren

1991-01-01

Results are reported for an investigation of a new direct-simulation Monte Carlo method by which energy transfer and chemical reactions are calculated. The new method, which reduces to the variable cross-section hard sphere model as a special case, allows different viscosity-temperature exponents for each species in a gas mixture when combined with a modified Larsen-Borgnakke phenomenological model. This removes the most serious limitation of the usefulness of the model for engineering simulations. The necessary kinetic theory for the application of the new method to mixtures of monatomic or polyatomic gases is presented, including gas mixtures involving chemical reactions. Calculations are made for the relaxation of a diatomic gas mixture, a plane shock wave in a gas mixture, and a chemically reacting gas flow along the stagnation streamline in front of a hypersonic vehicle. Calculated results show that the introduction of different molecular interactions for each species in a gas mixture produces significant differences in comparison with a common molecular interaction for all species in the mixture. This effect should not be neglected for accurate DSMC simulations in an engineering context.

Porosity Gradient at the Surface of Comet 67P/Churyumov-Gerasimenko

NASA Astrophysics Data System (ADS)

Christou, C.; Dadzie, S. K.; Thomas, N.; Hartogh, P.; Jorda, L.; Kuhrt, E.; Wright, I.; Zarnecki, J.

2017-12-01

The Rosetta mission has provided invaluable and unexpected information about our knowledge and understanding of comets until now. The on-board instruments, ROSINA and VIRTIS showed the non-uniformly outgassing of H2O over the surface of the nucleus. After Philae landing in a small lobe and the attempt to intrude MUPUS into the surface led to estimate the minimum compressive strength of material > 4MPa. This high strength of material (at least locally) along with different porosity ranges that have been presented for the 67P/Churyumov-Gerasimenko (67P) challenge our understanding of the surface and outgassing processes. Here we used the micro computed tomography (micro-CT) technology to represent 3D Earth rock samples with different porosity to investigate outgassing in the near surface boundary layer. The Direct Simulation of Monte Carlo (DSMC) method is used to simulate the rarefied cometary atmosphere. We presented results with H2O outgassing at a maximum production rate near perihelion. We show that an existence of a possible porosity gradient at the surface of the comet may explain some of the structures observed on 67P.

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.

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.

Parallel Markov chain Monte Carlo - bridging the gap to high-performance Bayesian computation in animal breeding and genetics.

PubMed

Wu, Xiao-Lin; Sun, Chuanyu; Beissinger, Timothy M; Rosa, Guilherme Jm; Weigel, Kent A; Gatti, Natalia de Leon; Gianola, Daniel

2012-09-25

Most Bayesian models for the analysis of complex traits are not analytically tractable and inferences are based on computationally intensive techniques. This is true of Bayesian models for genome-enabled selection, which uses whole-genome molecular data to predict the genetic merit of candidate animals for breeding purposes. In this regard, parallel computing can overcome the bottlenecks that can arise from series computing. Hence, a major goal of the present study is to bridge the gap to high-performance Bayesian computation in the context of animal breeding and genetics. Parallel Monte Carlo Markov chain algorithms and strategies are described in the context of animal breeding and genetics. Parallel Monte Carlo algorithms are introduced as a starting point including their applications to computing single-parameter and certain multiple-parameter models. Then, two basic approaches for parallel Markov chain Monte Carlo are described: one aims at parallelization within a single chain; the other is based on running multiple chains, yet some variants are discussed as well. Features and strategies of the parallel Markov chain Monte Carlo are illustrated using real data, including a large beef cattle dataset with 50K SNP genotypes. Parallel Markov chain Monte Carlo algorithms are useful for computing complex Bayesian models, which does not only lead to a dramatic speedup in computing but can also be used to optimize model parameters in complex Bayesian models. Hence, we anticipate that use of parallel Markov chain Monte Carlo will have a profound impact on revolutionizing the computational tools for genomic selection programs.

Parallel Markov chain Monte Carlo - bridging the gap to high-performance Bayesian computation in animal breeding and genetics

PubMed Central

2012-01-01

Background Most Bayesian models for the analysis of complex traits are not analytically tractable and inferences are based on computationally intensive techniques. This is true of Bayesian models for genome-enabled selection, which uses whole-genome molecular data to predict the genetic merit of candidate animals for breeding purposes. In this regard, parallel computing can overcome the bottlenecks that can arise from series computing. Hence, a major goal of the present study is to bridge the gap to high-performance Bayesian computation in the context of animal breeding and genetics. Results Parallel Monte Carlo Markov chain algorithms and strategies are described in the context of animal breeding and genetics. Parallel Monte Carlo algorithms are introduced as a starting point including their applications to computing single-parameter and certain multiple-parameter models. Then, two basic approaches for parallel Markov chain Monte Carlo are described: one aims at parallelization within a single chain; the other is based on running multiple chains, yet some variants are discussed as well. Features and strategies of the parallel Markov chain Monte Carlo are illustrated using real data, including a large beef cattle dataset with 50K SNP genotypes. Conclusions Parallel Markov chain Monte Carlo algorithms are useful for computing complex Bayesian models, which does not only lead to a dramatic speedup in computing but can also be used to optimize model parameters in complex Bayesian models. Hence, we anticipate that use of parallel Markov chain Monte Carlo will have a profound impact on revolutionizing the computational tools for genomic selection programs. PMID:23009363

Loading relativistic Maxwell distributions in particle simulations

NASA Astrophysics Data System (ADS)

Zenitani, S.

2015-12-01

In order to study energetic plasma phenomena by using particle-in-cell (PIC) and Monte-Carlo simulations, we need to deal with relativistic velocity distributions in these simulations. However, numerical algorithms to deal with relativistic distributions are not well known. In this contribution, we overview basic algorithms to load relativistic Maxwell distributions in PIC and Monte-Carlo simulations. For stationary relativistic Maxwellian, the inverse transform method and the Sobol algorithm are reviewed. To boost particles to obtain relativistic shifted-Maxwellian, two rejection methods are newly proposed in a physically transparent manner. Their acceptance efficiencies are 􏰅50% for generic cases and 100% for symmetric distributions. They can be combined with arbitrary base algorithms.

An unbiased Hessian representation for Monte Carlo PDFs.

PubMed

Carrazza, Stefano; Forte, Stefano; Kassabov, Zahari; Latorre, José Ignacio; Rojo, Juan

We develop a methodology for the construction of a Hessian representation of Monte Carlo sets of parton distributions, based on the use of a subset of the Monte Carlo PDF replicas as an unbiased linear basis, and of a genetic algorithm for the determination of the optimal basis. We validate the methodology by first showing that it faithfully reproduces a native Monte Carlo PDF set (NNPDF3.0), and then, that if applied to Hessian PDF set (MMHT14) which was transformed into a Monte Carlo set, it gives back the starting PDFs with minimal information loss. We then show that, when applied to a large Monte Carlo PDF set obtained as combination of several underlying sets, the methodology leads to a Hessian representation in terms of a rather smaller set of parameters (MC-H PDFs), thereby providing an alternative implementation of the recently suggested Meta-PDF idea and a Hessian version of the recently suggested PDF compression algorithm (CMC-PDFs). The mc2hessian conversion code is made publicly available together with (through LHAPDF6) a Hessian representations of the NNPDF3.0 set, and the MC-H PDF set.

Sliding mode stabilisation of networked systems with consecutive data packet dropouts using only accessible information

NASA Astrophysics Data System (ADS)

Argha, Ahmadreza; Li, Li; W. Su, Steven

2017-04-01

This paper develops a novel stabilising sliding mode for systems involving uncertainties as well as measurement data packet dropouts. In contrast to the existing literature that designs the switching function by using unavailable system states, a novel linear sliding function is constructed by employing only the available communicated system states for the systems involving measurement packet losses. This also equips us with the possibility to build a novel switching component for discrete-time sliding mode control (DSMC) by using only available system states. Finally, using a numerical example, we evaluate the performance of the designed DSMC for networked systems.

SU-F-T-444: Quality Improvement Review of Radiation Therapy Treatment Planning in the Presence of Dental Implants

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

Parenica, H; Ford, J; Mavroidis, P

Purpose: To quantify and compare the effect of metallic dental implants (MDI) on dose distributions calculated using Collapsed Cone Convolution Superposition (CCCS) algorithm or a Monte Carlo algorithm (with and without correcting for the density of the MDI). Methods: Seven previously treated patients to the head and neck region were included in this study. The MDI and the streaking artifacts on the CT images were carefully contoured. For each patient a plan was optimized and calculated using the Pinnacle3 treatment planning system (TPS). For each patient two dose calculations were performed, a) with the densities of the MDI and CTmore » artifacts overridden (12 g/cc and 1 g/cc respectively) and b) without density overrides. The plans were then exported to the Monaco TPS and recalculated using Monte Carlo dose calculation algorithm. The changes in dose to PTVs and surrounding Regions of Interest (ROIs) were examined between all plans. Results: The Monte Carlo dose calculation indicated that PTVs received 6% lower dose than the CCCS algorithm predicted. In some cases, the Monte Carlo algorithm indicated that surrounding ROIs received higher dose (up to a factor of 2). Conclusion: Not properly accounting for dental implants can impact both the high dose regions (PTV) and the low dose regions (OAR). This study implies that if MDI and the artifacts are not appropriately contoured and given the correct density, there is potential significant impact on PTV coverage and OAR maximum doses.« less

Bayesian estimation of realized stochastic volatility model by Hybrid Monte Carlo algorithm

NASA Astrophysics Data System (ADS)

Takaishi, Tetsuya

2014-03-01

The hybrid Monte Carlo algorithm (HMCA) is applied for Bayesian parameter estimation of the realized stochastic volatility (RSV) model. Using the 2nd order minimum norm integrator (2MNI) for the molecular dynamics (MD) simulation in the HMCA, we find that the 2MNI is more efficient than the conventional leapfrog integrator. We also find that the autocorrelation time of the volatility variables sampled by the HMCA is very short. Thus it is concluded that the HMCA with the 2MNI is an efficient algorithm for parameter estimations of the RSV model.

Exploring cluster Monte Carlo updates with Boltzmann machines

NASA Astrophysics Data System (ADS)

Wang, Lei

2017-11-01

Boltzmann machines are physics informed generative models with broad applications in machine learning. They model the probability distribution of an input data set with latent variables and generate new samples accordingly. Applying the Boltzmann machines back to physics, they are ideal recommender systems to accelerate the Monte Carlo simulation of physical systems due to their flexibility and effectiveness. More intriguingly, we show that the generative sampling of the Boltzmann machines can even give different cluster Monte Carlo algorithms. The latent representation of the Boltzmann machines can be designed to mediate complex interactions and identify clusters of the physical system. We demonstrate these findings with concrete examples of the classical Ising model with and without four-spin plaquette interactions. In the future, automatic searches in the algorithm space parametrized by Boltzmann machines may discover more innovative Monte Carlo updates.

Testing trivializing maps in the Hybrid Monte Carlo algorithm

PubMed Central

Engel, Georg P.; Schaefer, Stefan

2011-01-01

We test a recent proposal to use approximate trivializing maps in a field theory to speed up Hybrid Monte Carlo simulations. Simulating the CPN−1 model, we find a small improvement with the leading order transformation, which is however compensated by the additional computational overhead. The scaling of the algorithm towards the continuum is not changed. In particular, the effect of the topological modes on the autocorrelation times is studied. PMID:21969733

Dynamic load balancing for petascale quantum Monte Carlo applications: The Alias method

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

Sudheer, C. D.; Krishnan, S.; Srinivasan, A.

Diffusion Monte Carlo is the most accurate widely used Quantum Monte Carlo method for the electronic structure of materials, but it requires frequent load balancing or population redistribution steps to maintain efficiency and avoid accumulation of systematic errors on parallel machines. The load balancing step can be a significant factor affecting performance, and will become more important as the number of processing elements increases. We propose a new dynamic load balancing algorithm, the Alias Method, and evaluate it theoretically and empirically. An important feature of the new algorithm is that the load can be perfectly balanced with each process receivingmore » at most one message. It is also optimal in the maximum size of messages received by any process. We also optimize its implementation to reduce network contention, a process facilitated by the low messaging requirement of the algorithm. Empirical results on the petaflop Cray XT Jaguar supercomputer at ORNL showing up to 30% improvement in performance on 120,000 cores. The load balancing algorithm may be straightforwardly implemented in existing codes. The algorithm may also be employed by any method with many near identical computational tasks that requires load balancing.« less

Stochastic evaluation of second-order many-body perturbation energies.

PubMed

Willow, Soohaeng Yoo; Kim, Kwang S; Hirata, So

2012-11-28

With the aid of the Laplace transform, the canonical expression of the second-order many-body perturbation correction to an electronic energy is converted into the sum of two 13-dimensional integrals, the 12-dimensional parts of which are evaluated by Monte Carlo integration. Weight functions are identified that are analytically normalizable, are finite and non-negative everywhere, and share the same singularities as the integrands. They thus generate appropriate distributions of four-electron walkers via the Metropolis algorithm, yielding correlation energies of small molecules within a few mE(h) of the correct values after 10(8) Monte Carlo steps. This algorithm does away with the integral transformation as the hotspot of the usual algorithms, has a far superior size dependence of cost, does not suffer from the sign problem of some quantum Monte Carlo methods, and potentially easily parallelizable and extensible to other more complex electron-correlation theories.

Hierarchical fractional-step approximations and parallel kinetic Monte Carlo algorithms

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

Arampatzis, Giorgos, E-mail: garab@math.uoc.gr; Katsoulakis, Markos A., E-mail: markos@math.umass.edu; Plechac, Petr, E-mail: plechac@math.udel.edu

2012-10-01

We present a mathematical framework for constructing and analyzing parallel algorithms for lattice kinetic Monte Carlo (KMC) simulations. The resulting algorithms have the capacity to simulate a wide range of spatio-temporal scales in spatially distributed, non-equilibrium physiochemical processes with complex chemistry and transport micro-mechanisms. Rather than focusing on constructing exactly the stochastic trajectories, our approach relies on approximating the evolution of observables, such as density, coverage, correlations and so on. More specifically, we develop a spatial domain decomposition of the Markov operator (generator) that describes the evolution of all observables according to the kinetic Monte Carlo algorithm. This domain decompositionmore » corresponds to a decomposition of the Markov generator into a hierarchy of operators and can be tailored to specific hierarchical parallel architectures such as multi-core processors or clusters of Graphical Processing Units (GPUs). Based on this operator decomposition, we formulate parallel Fractional step kinetic Monte Carlo algorithms by employing the Trotter Theorem and its randomized variants; these schemes, (a) are partially asynchronous on each fractional step time-window, and (b) are characterized by their communication schedule between processors. The proposed mathematical framework allows us to rigorously justify the numerical and statistical consistency of the proposed algorithms, showing the convergence of our approximating schemes to the original serial KMC. The approach also provides a systematic evaluation of different processor communicating schedules. We carry out a detailed benchmarking of the parallel KMC schemes using available exact solutions, for example, in Ising-type systems and we demonstrate the capabilities of the method to simulate complex spatially distributed reactions at very large scales on GPUs. Finally, we discuss work load balancing between processors and propose a re-balancing scheme based on probabilistic mass transport methods.« less

Annealed Importance Sampling Reversible Jump MCMC algorithms

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

Karagiannis, Georgios; Andrieu, Christophe

2013-03-20

It will soon be 20 years since reversible jump Markov chain Monte Carlo (RJ-MCMC) algorithms have been proposed. They have significantly extended the scope of Markov chain Monte Carlo simulation methods, offering the promise to be able to routinely tackle transdimensional sampling problems, as encountered in Bayesian model selection problems for example, in a principled and flexible fashion. Their practical efficient implementation, however, still remains a challenge. A particular difficulty encountered in practice is in the choice of the dimension matching variables (both their nature and their distribution) and the reversible transformations which allow one to define the one-to-one mappingsmore » underpinning the design of these algorithms. Indeed, even seemingly sensible choices can lead to algorithms with very poor performance. The focus of this paper is the development and performance evaluation of a method, annealed importance sampling RJ-MCMC (aisRJ), which addresses this problem by mitigating the sensitivity of RJ-MCMC algorithms to the aforementioned poor design. As we shall see the algorithm can be understood as being an “exact approximation” of an idealized MCMC algorithm that would sample from the model probabilities directly in a model selection set-up. Such an idealized algorithm may have good theoretical convergence properties, but typically cannot be implemented, and our algorithms can approximate the performance of such idealized algorithms to an arbitrary degree while not introducing any bias for any degree of approximation. Our approach combines the dimension matching ideas of RJ-MCMC with annealed importance sampling and its Markov chain Monte Carlo implementation. We illustrate the performance of the algorithm with numerical simulations which indicate that, although the approach may at first appear computationally involved, it is in fact competitive.« less

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

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.

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.

Investigation of Thermal Stress Convection in Nonisothermal Gases under Microgravity Conditions

NASA Technical Reports Server (NTRS)

Mackowski, Daniel W.

1999-01-01

The project has sought to ascertain the veracity of the Burnett relations, as applied to slow moving, highly nonisothermal gases, by comparison of convection and stress predictions with those generated by the DSMC method. The Burnett equations were found to provide reasonable descriptions of the pressure distribution and normal stress in stationary gases with a 1-D temperature gradient. Continuum/Burnett predictions of thermal stress convection in 2-D heated enclosures, however, are not quantitatively supported by DSMC results. For such situations, it appears that thermal creep flows, generated at the boundaries of the enclosure, will be significantly larger than the flows resulting from thermal stress in the gas.

Numerical Simulations Of High-Altitude Aerothermodynamics Of A Prospective Spacecraft Model

NASA Astrophysics Data System (ADS)

Vashchenkov, P. V.; Kaskovsky, A. V.; Krylov, A. N.; Ivanov, M. S.

2011-05-01

The paper describes the computations of aerothermodynamic characteristics of a promising spacecraft (Prospective Piloted Transport System) along its de- scent trajectory at altitudes from 120 to 60 km. The computations are performed by the DSMC method with the use of the SMILE software system and by the engineering technique (local bridging method) with the use of the RuSat software system. The influence of real gas effects (excitation of rotational and vibrational energy modes and chemical reactions) on aerothermodynamic characteristics of the vehicle is studied. A comparison of results obtained by the approximate engineering method and the DSMC method allow the accuracy of prediction of aerodynamic characteristics by the local bridging method to be estimated.

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.

High-efficiency wavefunction updates for large scale Quantum Monte Carlo

NASA Astrophysics Data System (ADS)

Kent, Paul; McDaniel, Tyler; Li, Ying Wai; D'Azevedo, Ed

Within ab intio Quantum Monte Carlo (QMC) simulations, the leading numerical cost for large systems is the computation of the values of the Slater determinants in the trial wavefunctions. The evaluation of each Monte Carlo move requires finding the determinant of a dense matrix, which is traditionally iteratively evaluated using a rank-1 Sherman-Morrison updating scheme to avoid repeated explicit calculation of the inverse. For calculations with thousands of electrons, this operation dominates the execution profile. We propose a novel rank- k delayed update scheme. This strategy enables probability evaluation for multiple successive Monte Carlo moves, with application of accepted moves to the matrices delayed until after a predetermined number of moves, k. Accepted events grouped in this manner are then applied to the matrices en bloc with enhanced arithmetic intensity and computational efficiency. This procedure does not change the underlying Monte Carlo sampling or the sampling efficiency. For large systems and algorithms such as diffusion Monte Carlo where the acceptance ratio is high, order of magnitude speedups can be obtained on both multi-core CPU and on GPUs, making this algorithm highly advantageous for current petascale and future exascale computations.

Quantifying the effect of air gap, depth, and range shifter thickness on TPS dosimetric accuracy in superficial PBS proton therapy.

PubMed

Shirey, Robert J; Wu, Hsinshun Terry

2018-01-01

This study quantifies the dosimetric accuracy of a commercial treatment planning system as functions of treatment depth, air gap, and range shifter thickness for superficial pencil beam scanning proton therapy treatments. The RayStation 6 pencil beam and Monte Carlo dose engines were each used to calculate the dose distributions for a single treatment plan with varying range shifter air gaps. Central axis dose values extracted from each of the calculated plans were compared to dose values measured with a calibrated PTW Markus chamber at various depths in RW3 solid water. Dose was measured at 12 depths, ranging from the surface to 5 cm, for each of the 18 different air gaps, which ranged from 0.5 to 28 cm. TPS dosimetric accuracy, defined as the ratio of calculated dose relative to the measured dose, was plotted as functions of depth and air gap for the pencil beam and Monte Carlo dose algorithms. The accuracy of the TPS pencil beam dose algorithm was found to be clinically unacceptable at depths shallower than 3 cm with air gaps wider than 10 cm, and increased range shifter thickness only added to the dosimetric inaccuracy of the pencil beam algorithm. Each configuration calculated with Monte Carlo was determined to be clinically acceptable. Further comparisons of the Monte Carlo dose algorithm to the measured spread-out Bragg Peaks of multiple fields used during machine commissioning verified the dosimetric accuracy of Monte Carlo in a variety of beam energies and field sizes. Discrepancies between measured and TPS calculated dose values can mainly be attributed to the ability (or lack thereof) of the TPS pencil beam dose algorithm to properly model secondary proton scatter generated in the range shifter. © 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Hybrid Microgrid Configuration Optimization with Evolutionary Algorithms

NASA Astrophysics Data System (ADS)

Lopez, Nicolas

This dissertation explores the Renewable Energy Integration Problem, and proposes a Genetic Algorithm embedded with a Monte Carlo simulation to solve large instances of the problem that are impractical to solve via full enumeration. The Renewable Energy Integration Problem is defined as finding the optimum set of components to supply the electric demand to a hybrid microgrid. The components considered are solar panels, wind turbines, diesel generators, electric batteries, connections to the power grid and converters, which can be inverters and/or rectifiers. The methodology developed is explained as well as the combinatorial formulation. In addition, 2 case studies of a single objective optimization version of the problem are presented, in order to minimize cost and to minimize global warming potential (GWP) followed by a multi-objective implementation of the offered methodology, by utilizing a non-sorting Genetic Algorithm embedded with a monte Carlo Simulation. The method is validated by solving a small instance of the problem with known solution via a full enumeration algorithm developed by NREL in their software HOMER. The dissertation concludes that the evolutionary algorithms embedded with Monte Carlo simulation namely modified Genetic Algorithms are an efficient form of solving the problem, by finding approximate solutions in the case of single objective optimization, and by approximating the true Pareto front in the case of multiple objective optimization of the Renewable Energy Integration Problem.

SU-F-T-148: Are the Approximations in Analytic Semi-Empirical Dose Calculation Algorithms for Intensity Modulated Proton Therapy for Complex Heterogeneities of Head and Neck Clinically Significant?

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

Yepes, P; UT MD Anderson Cancer Center, Houston, TX; Titt, U

2016-06-15

Purpose: Evaluate the differences in dose distributions between the proton analytic semi-empirical dose calculation algorithm used in the clinic and Monte Carlo calculations for a sample of 50 head-and-neck (H&N) patients and estimate the potential clinical significance of the differences. Methods: A cohort of 50 H&N patients, treated at the University of Texas Cancer Center with Intensity Modulated Proton Therapy (IMPT), were selected for evaluation of clinical significance of approximations in computed dose distributions. H&N site was selected because of the highly inhomogeneous nature of the anatomy. The Fast Dose Calculator (FDC), a fast track-repeating accelerated Monte Carlo algorithm formore » proton therapy, was utilized for the calculation of dose distributions delivered during treatment plans. Because of its short processing time, FDC allows for the processing of large cohorts of patients. FDC has been validated versus GEANT4, a full Monte Carlo system and measurements in water and for inhomogeneous phantoms. A gamma-index analysis, DVHs, EUDs, and TCP and NTCPs computed using published models were utilized to evaluate the differences between the Treatment Plan System (TPS) and FDC. Results: The Monte Carlo results systematically predict lower dose delivered in the target. The observed differences can be as large as 8 Gy, and should have a clinical impact. Gamma analysis also showed significant differences between both approaches, especially for the target volumes. Conclusion: Monte Carlo calculations with fast algorithms is practical and should be considered for the clinic, at least as a treatment plan verification tool.« less

The Metropolis Monte Carlo method with CUDA enabled Graphic Processing Units

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

Hall, Clifford; School of Physics, Astronomy, and Computational Sciences, George Mason University, 4400 University Dr., Fairfax, VA 22030; Ji, Weixiao

2014-02-01

We present a CPU–GPU system for runtime acceleration of large molecular simulations using GPU computation and memory swaps. The memory architecture of the GPU can be used both as container for simulation data stored on the graphics card and as floating-point code target, providing an effective means for the manipulation of atomistic or molecular data on the GPU. To fully take advantage of this mechanism, efficient GPU realizations of algorithms used to perform atomistic and molecular simulations are essential. Our system implements a versatile molecular engine, including inter-molecule interactions and orientational variables for performing the Metropolis Monte Carlo (MMC) algorithm,more » which is one type of Markov chain Monte Carlo. By combining memory objects with floating-point code fragments we have implemented an MMC parallel engine that entirely avoids the communication time of molecular data at runtime. Our runtime acceleration system is a forerunner of a new class of CPU–GPU algorithms exploiting memory concepts combined with threading for avoiding bus bandwidth and communication. The testbed molecular system used here is a condensed phase system of oligopyrrole chains. A benchmark shows a size scaling speedup of 60 for systems with 210,000 pyrrole monomers. Our implementation can easily be combined with MPI to connect in parallel several CPU–GPU duets. -- Highlights: •We parallelize the Metropolis Monte Carlo (MMC) algorithm on one CPU—GPU duet. •The Adaptive Tempering Monte Carlo employs MMC and profits from this CPU—GPU implementation. •Our benchmark shows a size scaling-up speedup of 62 for systems with 225,000 particles. •The testbed involves a polymeric system of oligopyrroles in the condensed phase. •The CPU—GPU parallelization includes dipole—dipole and Mie—Jones classic potentials.« less

A point kernel algorithm for microbeam radiation therapy

NASA Astrophysics Data System (ADS)

Debus, Charlotte; Oelfke, Uwe; Bartzsch, Stefan

2017-11-01

Microbeam radiation therapy (MRT) is a treatment approach in radiation therapy where the treatment field is spatially fractionated into arrays of a few tens of micrometre wide planar beams of unusually high peak doses separated by low dose regions of several hundred micrometre width. In preclinical studies, this treatment approach has proven to spare normal tissue more effectively than conventional radiation therapy, while being equally efficient in tumour control. So far dose calculations in MRT, a prerequisite for future clinical applications are based on Monte Carlo simulations. However, they are computationally expensive, since scoring volumes have to be small. In this article a kernel based dose calculation algorithm is presented that splits the calculation into photon and electron mediated energy transport, and performs the calculation of peak and valley doses in typical MRT treatment fields within a few minutes. Kernels are analytically calculated depending on the energy spectrum and material composition. In various homogeneous materials peak, valley doses and microbeam profiles are calculated and compared to Monte Carlo simulations. For a microbeam exposure of an anthropomorphic head phantom calculated dose values are compared to measurements and Monte Carlo calculations. Except for regions close to material interfaces calculated peak dose values match Monte Carlo results within 4% and valley dose values within 8% deviation. No significant differences are observed between profiles calculated by the kernel algorithm and Monte Carlo simulations. Measurements in the head phantom agree within 4% in the peak and within 10% in the valley region. The presented algorithm is attached to the treatment planning platform VIRTUOS. It was and is used for dose calculations in preclinical and pet-clinical trials at the biomedical beamline ID17 of the European synchrotron radiation facility in Grenoble, France.

Monte Carlo Simulations of Radiative and Neutrino Transport under Astrophysical Conditions

NASA Astrophysics Data System (ADS)

Krivosheyev, Yu. M.; Bisnovatyi-Kogan, G. S.

2018-05-01

Monte Carlo simulations are utilized to model radiative and neutrino transfer in astrophysics. An algorithm that can be used to study radiative transport in astrophysical plasma based on simulations of photon trajectories in a medium is described. Formation of the hard X-ray spectrum of the Galactic microquasar SS 433 is considered in detail as an example. Specific requirements for applying such simulations to neutrino transport in a densemedium and algorithmic differences compared to its application to photon transport are discussed.

Monte Carlo sampling of Wigner functions and surface hopping quantum dynamics

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

Kube, Susanna; Lasser, Caroline; Weber, Marcus

2009-04-01

The article addresses the achievable accuracy for a Monte Carlo sampling of Wigner functions in combination with a surface hopping algorithm for non-adiabatic quantum dynamics. The approximation of Wigner functions is realized by an adaption of the Metropolis algorithm for real-valued functions with disconnected support. The integration, which is necessary for computing values of the Wigner function, uses importance sampling with a Gaussian weight function. The numerical experiments agree with theoretical considerations and show an error of 2-3%.

An efficient Monte Carlo-based algorithm for scatter correction in keV cone-beam CT

NASA Astrophysics Data System (ADS)

Poludniowski, G.; Evans, P. M.; Hansen, V. N.; Webb, S.

2009-06-01

A new method is proposed for scatter-correction of cone-beam CT images. A coarse reconstruction is used in initial iteration steps. Modelling of the x-ray tube spectra and detector response are included in the algorithm. Photon diffusion inside the imaging subject is calculated using the Monte Carlo method. Photon scoring at the detector is calculated using forced detection to a fixed set of node points. The scatter profiles are then obtained by linear interpolation. The algorithm is referred to as the coarse reconstruction and fixed detection (CRFD) technique. Scatter predictions are quantitatively validated against a widely used general-purpose Monte Carlo code: BEAMnrc/EGSnrc (NRCC, Canada). Agreement is excellent. The CRFD algorithm was applied to projection data acquired with a Synergy XVI CBCT unit (Elekta Limited, Crawley, UK), using RANDO and Catphan phantoms (The Phantom Laboratory, Salem NY, USA). The algorithm was shown to be effective in removing scatter-induced artefacts from CBCT images, and took as little as 2 min on a desktop PC. Image uniformity was greatly improved as was CT-number accuracy in reconstructions. This latter improvement was less marked where the expected CT-number of a material was very different to the background material in which it was embedded.

Constant-pressure nested sampling with atomistic dynamics

NASA Astrophysics Data System (ADS)

Baldock, Robert J. N.; Bernstein, Noam; Salerno, K. Michael; Pártay, Lívia B.; Csányi, Gábor

2017-10-01

The nested sampling algorithm has been shown to be a general method for calculating the pressure-temperature-composition phase diagrams of materials. While the previous implementation used single-particle Monte Carlo moves, these are inefficient for condensed systems with general interactions where single-particle moves cannot be evaluated faster than the energy of the whole system. Here we enhance the method by using all-particle moves: either Galilean Monte Carlo or the total enthalpy Hamiltonian Monte Carlo algorithm, introduced in this paper. We show that these algorithms enable the determination of phase transition temperatures with equivalent accuracy to the previous method at 1 /N of the cost for an N -particle system with general interactions, or at equal cost when single-particle moves can be done in 1 /N of the cost of a full N -particle energy evaluation. We demonstrate this speed-up for the freezing and condensation transitions of the Lennard-Jones system and show the utility of the algorithms by calculating the order-disorder phase transition of a binary Lennard-Jones model alloy, the eutectic of copper-gold, the density anomaly of water, and the condensation and solidification of bead-spring polymers. The nested sampling method with all three algorithms is implemented in the pymatnest software.

A new moving strategy for the sequential Monte Carlo approach in optimizing the hydrological model parameters

NASA Astrophysics Data System (ADS)

Zhu, Gaofeng; Li, Xin; Ma, Jinzhu; Wang, Yunquan; Liu, Shaomin; Huang, Chunlin; Zhang, Kun; Hu, Xiaoli

2018-04-01

Sequential Monte Carlo (SMC) samplers have become increasing popular for estimating the posterior parameter distribution with the non-linear dependency structures and multiple modes often present in hydrological models. However, the explorative capabilities and efficiency of the sampler depends strongly on the efficiency in the move step of SMC sampler. In this paper we presented a new SMC sampler entitled the Particle Evolution Metropolis Sequential Monte Carlo (PEM-SMC) algorithm, which is well suited to handle unknown static parameters of hydrologic model. The PEM-SMC sampler is inspired by the works of Liang and Wong (2001) and operates by incorporating the strengths of the genetic algorithm, differential evolution algorithm and Metropolis-Hasting algorithm into the framework of SMC. We also prove that the sampler admits the target distribution to be a stationary distribution. Two case studies including a multi-dimensional bimodal normal distribution and a conceptual rainfall-runoff hydrologic model by only considering parameter uncertainty and simultaneously considering parameter and input uncertainty show that PEM-SMC sampler is generally superior to other popular SMC algorithms in handling the high dimensional problems. The study also indicated that it may be important to account for model structural uncertainty by using multiplier different hydrological models in the SMC framework in future study.

Hypothesis testing of scientific Monte Carlo calculations.

PubMed

Wallerberger, Markus; Gull, Emanuel

2017-11-01

The steadily increasing size of scientific Monte Carlo simulations and the desire for robust, correct, and reproducible results necessitates rigorous testing procedures for scientific simulations in order to detect numerical problems and programming bugs. However, the testing paradigms developed for deterministic algorithms have proven to be ill suited for stochastic algorithms. In this paper we demonstrate explicitly how the technique of statistical hypothesis testing, which is in wide use in other fields of science, can be used to devise automatic and reliable tests for Monte Carlo methods, and we show that these tests are able to detect some of the common problems encountered in stochastic scientific simulations. We argue that hypothesis testing should become part of the standard testing toolkit for scientific simulations.

Hypothesis testing of scientific Monte Carlo calculations

NASA Astrophysics Data System (ADS)

Wallerberger, Markus; Gull, Emanuel

2017-11-01

The steadily increasing size of scientific Monte Carlo simulations and the desire for robust, correct, and reproducible results necessitates rigorous testing procedures for scientific simulations in order to detect numerical problems and programming bugs. However, the testing paradigms developed for deterministic algorithms have proven to be ill suited for stochastic algorithms. In this paper we demonstrate explicitly how the technique of statistical hypothesis testing, which is in wide use in other fields of science, can be used to devise automatic and reliable tests for Monte Carlo methods, and we show that these tests are able to detect some of the common problems encountered in stochastic scientific simulations. We argue that hypothesis testing should become part of the standard testing toolkit for scientific simulations.

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.

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.

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.

Multigroup Monte Carlo on GPUs: Comparison of history- and event-based algorithms

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

Hamilton, Steven P.; Slattery, Stuart R.; Evans, Thomas M.

This article presents an investigation of the performance of different multigroup Monte Carlo transport algorithms on GPUs with a discussion of both history-based and event-based approaches. Several algorithmic improvements are introduced for both approaches. By modifying the history-based algorithm that is traditionally favored in CPU-based MC codes to occasionally filter out dead particles to reduce thread divergence, performance exceeds that of either the pure history-based or event-based approaches. The impacts of several algorithmic choices are discussed, including performance studies on Kepler and Pascal generation NVIDIA GPUs for fixed source and eigenvalue calculations. Single-device performance equivalent to 20–40 CPU cores onmore » the K40 GPU and 60–80 CPU cores on the P100 GPU is achieved. Last, in addition, nearly perfect multi-device parallel weak scaling is demonstrated on more than 16,000 nodes of the Titan supercomputer.« less

Multigroup Monte Carlo on GPUs: Comparison of history- and event-based algorithms

DOE PAGES

Hamilton, Steven P.; Slattery, Stuart R.; Evans, Thomas M.

2017-12-22

This article presents an investigation of the performance of different multigroup Monte Carlo transport algorithms on GPUs with a discussion of both history-based and event-based approaches. Several algorithmic improvements are introduced for both approaches. By modifying the history-based algorithm that is traditionally favored in CPU-based MC codes to occasionally filter out dead particles to reduce thread divergence, performance exceeds that of either the pure history-based or event-based approaches. The impacts of several algorithmic choices are discussed, including performance studies on Kepler and Pascal generation NVIDIA GPUs for fixed source and eigenvalue calculations. Single-device performance equivalent to 20–40 CPU cores onmore » the K40 GPU and 60–80 CPU cores on the P100 GPU is achieved. Last, in addition, nearly perfect multi-device parallel weak scaling is demonstrated on more than 16,000 nodes of the Titan supercomputer.« less

Comments on "Including the effects of temperature-dependent opacities in the implicit Monte Carlo algorithm" by N.A. Gentile [J. Comput. Phys. 230 (2011) 5100-5114

NASA Astrophysics Data System (ADS)

Ghosh, Karabi

2017-02-01

We briefly comment on a paper by N.A. Gentile [J. Comput. Phys. 230 (2011) 5100-5114] in which the Fleck factor has been modified to include the effects of temperature-dependent opacities in the implicit Monte Carlo algorithm developed by Fleck and Cummings [1,2]. Instead of the Fleck factor, f = 1 / (1 + βcΔtσP), the author derived the modified Fleck factor g = 1 / (1 + βcΔtσP - min [σP‧ (aTr4 - aT4)cΔt/ρCV, 0 ]) to be used in the Implicit Monte Carlo (IMC) algorithm in order to obtain more accurate solutions with much larger time steps. Here β = 4 aT3 / ρCV, σP is the Planck opacity and the derivative of Planck opacity w.r.t. the material temperature is σP‧ = dσP / dT.

Parallel Algorithms for Monte Carlo Particle Transport Simulation on Exascale Computing Architectures

NASA Astrophysics Data System (ADS)

Romano, Paul Kollath

Monte Carlo particle transport methods are being considered as a viable option for high-fidelity simulation of nuclear reactors. While Monte Carlo methods offer several potential advantages over deterministic methods, there are a number of algorithmic shortcomings that would prevent their immediate adoption for full-core analyses. In this thesis, algorithms are proposed both to ameliorate the degradation in parallel efficiency typically observed for large numbers of processors and to offer a means of decomposing large tally data that will be needed for reactor analysis. A nearest-neighbor fission bank algorithm was proposed and subsequently implemented in the OpenMC Monte Carlo code. A theoretical analysis of the communication pattern shows that the expected cost is O( N ) whereas traditional fission bank algorithms are O(N) at best. The algorithm was tested on two supercomputers, the Intrepid Blue Gene/P and the Titan Cray XK7, and demonstrated nearly linear parallel scaling up to 163,840 processor cores on a full-core benchmark problem. An algorithm for reducing network communication arising from tally reduction was analyzed and implemented in OpenMC. The proposed algorithm groups only particle histories on a single processor into batches for tally purposes---in doing so it prevents all network communication for tallies until the very end of the simulation. The algorithm was tested, again on a full-core benchmark, and shown to reduce network communication substantially. A model was developed to predict the impact of load imbalances on the performance of domain decomposed simulations. The analysis demonstrated that load imbalances in domain decomposed simulations arise from two distinct phenomena: non-uniform particle densities and non-uniform spatial leakage. The dominant performance penalty for domain decomposition was shown to come from these physical effects rather than insufficient network bandwidth or high latency. The model predictions were verified with measured data from simulations in OpenMC on a full-core benchmark problem. Finally, a novel algorithm for decomposing large tally data was proposed, analyzed, and implemented/tested in OpenMC. The algorithm relies on disjoint sets of compute processes and tally servers. The analysis showed that for a range of parameters relevant to LWR analysis, the tally server algorithm should perform with minimal overhead. Tests were performed on Intrepid and Titan and demonstrated that the algorithm did indeed perform well over a wide range of parameters. (Copies available exclusively from MIT Libraries, libraries.mit.edu/docs - docs mit.edu)

MDTS: automatic complex materials design using Monte Carlo tree search.

PubMed

M Dieb, Thaer; Ju, Shenghong; Yoshizoe, Kazuki; Hou, Zhufeng; Shiomi, Junichiro; Tsuda, Koji

2017-01-01

Complex materials design is often represented as a black-box combinatorial optimization problem. In this paper, we present a novel python library called MDTS (Materials Design using Tree Search). Our algorithm employs a Monte Carlo tree search approach, which has shown exceptional performance in computer Go game. Unlike evolutionary algorithms that require user intervention to set parameters appropriately, MDTS has no tuning parameters and works autonomously in various problems. In comparison to a Bayesian optimization package, our algorithm showed competitive search efficiency and superior scalability. We succeeded in designing large Silicon-Germanium (Si-Ge) alloy structures that Bayesian optimization could not deal with due to excessive computational cost. MDTS is available at https://github.com/tsudalab/MDTS.

MDTS: automatic complex materials design using Monte Carlo tree search

NASA Astrophysics Data System (ADS)

Dieb, Thaer M.; Ju, Shenghong; Yoshizoe, Kazuki; Hou, Zhufeng; Shiomi, Junichiro; Tsuda, Koji

2017-12-01

Complex materials design is often represented as a black-box combinatorial optimization problem. In this paper, we present a novel python library called MDTS (Materials Design using Tree Search). Our algorithm employs a Monte Carlo tree search approach, which has shown exceptional performance in computer Go game. Unlike evolutionary algorithms that require user intervention to set parameters appropriately, MDTS has no tuning parameters and works autonomously in various problems. In comparison to a Bayesian optimization package, our algorithm showed competitive search efficiency and superior scalability. We succeeded in designing large Silicon-Germanium (Si-Ge) alloy structures that Bayesian optimization could not deal with due to excessive computational cost. MDTS is available at https://github.com/tsudalab/MDTS.

Efficient kinetic Monte Carlo method for reaction-diffusion problems with spatially varying annihilation rates

NASA Astrophysics Data System (ADS)

Schwarz, Karsten; Rieger, Heiko

2013-03-01

We present an efficient Monte Carlo method to simulate reaction-diffusion processes with spatially varying particle annihilation or transformation rates as it occurs for instance in the context of motor-driven intracellular transport. Like Green's function reaction dynamics and first-passage time methods, our algorithm avoids small diffusive hops by propagating sufficiently distant particles in large hops to the boundaries of protective domains. Since for spatially varying annihilation or transformation rates the single particle diffusion propagator is not known analytically, we present an algorithm that generates efficiently either particle displacements or annihilations with the correct statistics, as we prove rigorously. The numerical efficiency of the algorithm is demonstrated with an illustrative example.

Note: A pure-sampling quantum Monte Carlo algorithm with independent Metropolis.

PubMed

Vrbik, Jan; Ospadov, Egor; Rothstein, Stuart M

2016-07-14

Recently, Ospadov and Rothstein published a pure-sampling quantum Monte Carlo algorithm (PSQMC) that features an auxiliary Path Z that connects the midpoints of the current and proposed Paths X and Y, respectively. When sufficiently long, Path Z provides statistical independence of Paths X and Y. Under those conditions, the Metropolis decision used in PSQMC is done without any approximation, i.e., not requiring microscopic reversibility and without having to introduce any G(x → x'; τ) factors into its decision function. This is a unique feature that contrasts with all competing reptation algorithms in the literature. An example illustrates that dependence of Paths X and Y has adverse consequences for pure sampling.

Note: A pure-sampling quantum Monte Carlo algorithm with independent Metropolis

NASA Astrophysics Data System (ADS)

Vrbik, Jan; Ospadov, Egor; Rothstein, Stuart M.

2016-07-01

Recently, Ospadov and Rothstein published a pure-sampling quantum Monte Carlo algorithm (PSQMC) that features an auxiliary Path Z that connects the midpoints of the current and proposed Paths X and Y, respectively. When sufficiently long, Path Z provides statistical independence of Paths X and Y. Under those conditions, the Metropolis decision used in PSQMC is done without any approximation, i.e., not requiring microscopic reversibility and without having to introduce any G(x → x'; τ) factors into its decision function. This is a unique feature that contrasts with all competing reptation algorithms in the literature. An example illustrates that dependence of Paths X and Y has adverse consequences for pure sampling.

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.

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

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.

A robust algorithm for automated target recognition using precomputed radar cross sections

NASA Astrophysics Data System (ADS)

Ehrman, Lisa M.; Lanterman, Aaron D.

2004-09-01

Passive radar is an emerging technology that offers a number of unique benefits, including covert operation. Many such systems are already capable of detecting and tracking aircraft. The goal of this work is to develop a robust algorithm for adding automated target recognition (ATR) capabilities to existing passive radar systems. In previous papers, we proposed conducting ATR by comparing the precomputed RCS of known targets to that of detected targets. To make the precomputed RCS as accurate as possible, a coordinated flight model is used to estimate aircraft orientation. Once the aircraft's position and orientation are known, it is possible to determine the incident and observed angles on the aircraft, relative to the transmitter and receiver. This makes it possible to extract the appropriate radar cross section (RCS) from our simulated database. This RCS is then scaled to account for propagation losses and the receiver's antenna gain. A Rician likelihood model compares these expected signals from different targets to the received target profile. We have previously employed Monte Carlo runs to gauge the probability of error in the ATR algorithm; however, generation of a statistically significant set of Monte Carlo runs is computationally intensive. As an alternative to Monte Carlo runs, we derive the relative entropy (also known as Kullback-Liebler distance) between two Rician distributions. Since the probability of Type II error in our hypothesis testing problem can be expressed as a function of the relative entropy via Stein's Lemma, this provides us with a computationally efficient method for determining an upper bound on our algorithm's performance. It also provides great insight into the types of classification errors we can expect from our algorithm. This paper compares the numerically approximated probability of Type II error with the results obtained from a set of Monte Carlo runs.

Extension of a hybrid particle-continuum method for a mixture of chemical species

NASA Astrophysics Data System (ADS)

Verhoff, Ashley M.; Boyd, Iain D.

2012-11-01

Due to the physical accuracy and numerical efficiency achieved by analyzing transitional, hypersonic flow fields with hybrid particle-continuum methods, this paper describes a Modular Particle-Continuum (MPC) method and its extension to include multiple chemical species. Considerations that are specific to a hybrid approach for simulating gas mixtures are addressed, including a discussion of the Chapman-Enskog velocity distribution function (VDF) for near-equilibrium flows, and consistent viscosity models for the individual CFD and DSMC modules of the MPC method. Representative results for a hypersonic blunt-body flow are then presented, where the flow field properties, surface properties, and computational performance are compared for simulations employing full CFD, full DSMC, and the MPC method.

Poly-Gaussian model of randomly rough surface in rarefied gas flow

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

Aksenova, Olga A.; Khalidov, Iskander A.

2014-12-09

Surface roughness is simulated by the model of non-Gaussian random process. Our results for the scattering of rarefied gas atoms from a rough surface using modified approach to the DSMC calculation of rarefied gas flow near a rough surface are developed and generalized applying the poly-Gaussian model representing probability density as the mixture of Gaussian densities. The transformation of the scattering function due to the roughness is characterized by the roughness operator. Simulating rough surface of the walls by the poly-Gaussian random field expressed as integrated Wiener process, we derive a representation of the roughness operator that can be appliedmore » in numerical DSMC methods as well as in analytical investigations.« less

Computational analysis of fluid dynamics in pharmaceutical freeze-drying.

PubMed

Alexeenko, Alina A; Ganguly, Arnab; Nail, Steven L

2009-09-01

Analysis of water vapor flows encountered in pharmaceutical freeze-drying systems, laboratory-scale and industrial, is presented based on the computational fluid dynamics (CFD) techniques. The flows under continuum gas conditions are analyzed using the solution of the Navier-Stokes equations whereas the rarefied flow solutions are obtained by the direct simulation Monte Carlo (DSMC) method for the Boltzmann equation. Examples of application of CFD techniques to laboratory-scale and industrial scale freeze-drying processes are discussed with an emphasis on the utility of CFD for improvement of design and experimental characterization of pharmaceutical freeze-drying hardware and processes. The current article presents a two-dimensional simulation of a laboratory scale dryer with an emphasis on the importance of drying conditions and hardware design on process control and a three-dimensional simulation of an industrial dryer containing a comparison of the obtained results with analytical viscous flow solutions. It was found that the presence of clean in place (CIP)/sterilize in place (SIP) piping in the duct lead to significant changes in the flow field characteristics. The simulation results for vapor flow rates in an industrial freeze-dryer have been compared to tunable diode laser absorption spectroscopy (TDLAS) and gravimetric measurements.

On the Validity of Continuum Computational Fluid Dynamics Approach Under Very Low-Pressure Plasma Spray Conditions

NASA Astrophysics Data System (ADS)

Ivchenko, Dmitrii; Zhang, Tao; Mariaux, Gilles; Vardelle, Armelle; Goutier, Simon; Itina, Tatiana E.

2018-01-01

Plasma spray physical vapor deposition aims to substantially evaporate powders in order to produce coatings with various microstructures. This is achieved by powder vapor condensation onto the substrate and/or by deposition of fine melted powder particles and nanoclusters. The deposition process typically operates at pressures ranging between 10 and 200 Pa. In addition to the experimental works, numerical simulations are performed to better understand the process and optimize the experimental conditions. However, the combination of high temperatures and low pressure with shock waves initiated by supersonic expansion of the hot gas in the low-pressure medium makes doubtful the applicability of the continuum approach for the simulation of such a process. This work investigates (1) effects of the pressure dependence of thermodynamic and transport properties on computational fluid dynamics (CFD) predictions and (2) the validity of the continuum approach for thermal plasma flow simulation under very low-pressure conditions. The study compares the flow fields predicted with a continuum approach using CFD software with those obtained by a kinetic-based approach using a direct simulation Monte Carlo method (DSMC). It also shows how the presence of high gradients can contribute to prediction errors for typical PS-PVD conditions.

Knudsen paradox in granular gases and the roles of thermal and athermal walls

NASA Astrophysics Data System (ADS)

Gupta, Ronak; Alam, Meheboob

2017-11-01

The well-known `Knudsen-paradox' (which refers to the decrease of the mass-flow rate of a gas with increasing Knudsen number Kn , reaching a minimum at Kn O(1) and increasing logarithmically with Kn as Kn -> ∞) is revisited using direct simulation Monte Carlo (DSMC) method. It is shown that the `Knudsen-paradox' survives in the acceleration-driven Poiseuille flow of a granular gas in contact with thermal-walls. This result is in contradiction with recent molecular dynamics simulations (Alam et al., J. Fluid Mech., vol. 782, 2015, pp. 99-126) that revealed the absence of the Knudsen-minimum in granular Poiseuille flow. The above conundrum is resolved by distinguishing between `thermal' and `athermal' walls, and it is shown that, for both molecular and granular gases, the momentum-transfer to athermal-walls is much lower than that to thermal-walls which is directly responsible for the ``anomalous'' flow-rate-variation with Kn . In the continuum limit of Kn -> 0 , the athermal walls are found to be closely related to `non-flux/adiabatic' walls. The underlying mechanistic arguments lead to Maxwell's slip-boundary condition and a possible characterization of athermal walls in terms of an effective specularity coefficient is discussed.

Effect of Knudsen thermal force on the performance of low-pressure micro gas sensor

NASA Astrophysics Data System (ADS)

Barzegar Gerdroodbary, M.; Ganji, D. D.; Taeibi-Rahni, M.; Vakilipour, Shidvash

2017-07-01

In this paper, Direct Simulation Monte Carlo (DSMC) simulations were applied to investigate the mechanism of the force generation inside a low-pressure gas sensor. The flow feature and force generation mechanism inside a rectangular enclosure with heat and cold arms as the non-isothermal walls are comprehensively explained. In addition, extensive parametric studies are done to study the effects of physical parameters on the performance and characteristics of this device in different operating conditions. In this research, the Knudsen number is varied from 0.1 to 4.5 (0.5 to 11torr) to reveal all the characteristics of the thermally driven force inside the MEMS sensor. In order to simulate a rarefied gas inside the micro gas detector, Boltzmann equations are applied to obtain high-precision results. The effects of ambient pressure and temperature difference of arms are comprehensively investigated. Our findings show that maximum force increases more than 7 times when the temperature difference of the cold and hot arms is increased from 10 to 100K. In addition, the results demonstrate that the thermal gradient at rarefied pressure induces complex structure, and the mechanism of force generation highly varies at different pressure conditions.

Rotational and vibrational nonequilibrium effects in rarefied, hypersonic flow

NASA Technical Reports Server (NTRS)

Boyd, Iain D.

1989-01-01

Results are reported for an investigation into the methods by which energy transfer is calculated in the Direct Simulation Monte Carlo method. Description is made of a recently developed energy exchange model that deals with the translational and rotational modes. A new model for simulating the transfer of energy between the translational and vibrational modes is also explained. This model allows the vibrational relaxation time to follow the temperature dependence predicted by the Landau-Teller theory at moderate temperatures. For temperatures in excess of about 8000K the vibrational model is extended to include an empirical result for the relaxation time. The effect of introducing these temperature dependent collision numbers into the DSMC technique is assessed by making calculations representative of the stagnation streamline of a hypersonic space vehicle. Both thermal and chemical nonequilibrium effects are included while the flow conditions have been chosen such that ionization and radiation may be neglected. The introduction of these new models is found to significantly affect the degree of thermal nonequilibrium observed in the flowfield. Larger, and more widely ranging, differences in the results obtained with the different energy exchange probabilities are found when a significant amount of internal energy is included in the calculation of chemical nonequilibrium.

Prediction of rarefied micro-nozzle flows using the SPARTA library

NASA Astrophysics Data System (ADS)

Deschenes, Timothy R.; Grot, Jonathan

2016-11-01

The accurate numerical prediction of gas flows within micro-nozzles can help evaluate the performance and enable the design of optimal configurations for micro-propulsion systems. Viscous effects within the large boundary layers can have a strong impact on the nozzle performance. Furthermore, the variation in collision length scales from continuum to rarefied preclude the use of continuum-based computational fluid dynamics. In this paper, we describe the application of a massively parallel direct simulation Monte Carlo (DSMC) library to predict the steady-state and transient flow through a micro-nozzle. The nozzle's geometric configuration is described in a highly flexible manner to allow for the modification of the geometry in a systematic fashion. The transient simulation highlights a strong shock structure that forms within the converging portion of the nozzle when the expanded gas interacts with the nozzle walls. This structure has a strong impact on the buildup of the gas in the nozzle and affects the boundary layer thickness beyond the throat in the diverging section of the nozzle. Future work will look to examine the transient thrust and integrate this simulation capability into a web-based rarefied gas dynamics prediction software, which is currently under development.

Rarefied-continuum gas dynamics transition for SUMS project

NASA Technical Reports Server (NTRS)

Cheng, Sin-I

1989-01-01

This program is to develop an analytic method for reducing SUMS data for the determination of the undisturbed atmosphere conditions ahead of the shuttle along its descending trajectory. It is divided into an internal flow problem, an external flow problem and their matching conditions. Since the existing method of Direct Simulation Monte Carlo (DSMC) failed completely for the internal flow problem, the emphasis is on the internal flow of a highly non-equilibrium, rarefied air through a short tube of a diameter much less than the gaseous mean free path. A two fluid model analysis of this internal flow problem has been developed and studied with typical results illustrated. A computer program for such an analysis and a technical paper published in Lecture Notes in Physics No. 323 (1989) are included as Appendices 3 and 4. A proposal for in situ determination of the surface accommodation coefficients sigma sub t and sigma e is included in Appendix 5 because of their importance in quantitative data reduction. A two fluid formulation for the external flow problem is included as Appendix 6 and a review article for AIAA on Hypersonic propulsion, much dependent on ambient atmospheric density, is also included as Appendix 7.

Radiation transport in kinetic simulations and the influence of photoemission on electron current in self-sustaining discharges

DOE PAGES

Fierro, Andrew S.; Moore, Christopher Hudson; Scheiner, Brett; ...

2017-01-12

A kinetic description for electronic excitation of helium for principal quantum number nmore » $$\\leqslant $$ 4 has been included into a particle-in-cell (PIC) simulation utilizing direct simulation Monte Carlo (DSMC) for electron-neutral interactions. The excited electronic levels radiate state-dependent photons with wavelengths from the extreme ultraviolet (EUV) to visible regimes. Photon wavelengths are chosen according to a Voigt distribution accounting for the natural, pressure, and Doppler broadened linewidths. This method allows for reconstruction of the emission spectrum for a non-thermalized electron energy distribution function (EEDF) and investigation of high energy photon effects on surfaces, specifically photoemission. A parallel plate discharge with a fixed field (i.e. space charge neglected) is used to investigate the effects of including photoemission for a Townsend discharge. When operating at a voltage near the self-sustaining discharge threshold, it is observed that the electron current into the anode is higher when including photoemission from the cathode than without even when accounting for self-absorption from ground state atoms. As a result, the photocurrent has been observed to account for as much as 20% of the total current from the cathode under steady-state conditions.« less

Bayesian Estimation of Multidimensional Item Response Models. A Comparison of Analytic and Simulation Algorithms

ERIC Educational Resources Information Center

Martin-Fernandez, Manuel; Revuelta, Javier

2017-01-01

This study compares the performance of two estimation algorithms of new usage, the Metropolis-Hastings Robins-Monro (MHRM) and the Hamiltonian MCMC (HMC), with two consolidated algorithms in the psychometric literature, the marginal likelihood via EM algorithm (MML-EM) and the Markov chain Monte Carlo (MCMC), in the estimation of multidimensional…

Fungible Correlation Matrices: A Method for Generating Nonsingular, Singular, and Improper Correlation Matrices for Monte Carlo Research.

PubMed

Waller, Niels G

2016-01-01

For a fixed set of standardized regression coefficients and a fixed coefficient of determination (R-squared), an infinite number of predictor correlation matrices will satisfy the implied quadratic form. I call such matrices fungible correlation matrices. In this article, I describe an algorithm for generating positive definite (PD), positive semidefinite (PSD), or indefinite (ID) fungible correlation matrices that have a random or fixed smallest eigenvalue. The underlying equations of this algorithm are reviewed from both algebraic and geometric perspectives. Two simulation studies illustrate that fungible correlation matrices can be profitably used in Monte Carlo research. The first study uses PD fungible correlation matrices to compare penalized regression algorithms. The second study uses ID fungible correlation matrices to compare matrix-smoothing algorithms. R code for generating fungible correlation matrices is presented in the supplemental materials.

Using Stan for Item Response Theory Models

ERIC Educational Resources Information Center

Ames, Allison J.; Au, Chi Hang

2018-01-01

Stan is a flexible probabilistic programming language providing full Bayesian inference through Hamiltonian Monte Carlo algorithms. The benefits of Hamiltonian Monte Carlo include improved efficiency and faster inference, when compared to other MCMC software implementations. Users can interface with Stan through a variety of computing…

Quantum Monte Carlo Simulation of Frustrated Kondo Lattice Models

NASA Astrophysics Data System (ADS)

Sato, Toshihiro; Assaad, Fakher F.; Grover, Tarun

2018-03-01

The absence of the negative sign problem in quantum Monte Carlo simulations of spin and fermion systems has different origins. World-line based algorithms for spins require positivity of matrix elements whereas auxiliary field approaches for fermions depend on symmetries such as particle-hole symmetry. For negative-sign-free spin and fermionic systems, we show that one can formulate a negative-sign-free auxiliary field quantum Monte Carlo algorithm that allows Kondo coupling of fermions with the spins. Using this general approach, we study a half-filled Kondo lattice model on the honeycomb lattice with geometric frustration. In addition to the conventional Kondo insulator and antiferromagnetically ordered phases, we find a partial Kondo screened state where spins are selectively screened so as to alleviate frustration, and the lattice rotation symmetry is broken nematically.

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).

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.

A highly optimized vectorized code for Monte Carlo simulations of SU(3) lattice gauge theories

NASA Technical Reports Server (NTRS)

Barkai, D.; Moriarty, K. J. M.; Rebbi, C.

1984-01-01

New methods are introduced for improving the performance of the vectorized Monte Carlo SU(3) lattice gauge theory algorithm using the CDC CYBER 205. Structure, algorithm and programming considerations are discussed. The performance achieved for a 16(4) lattice on a 2-pipe system may be phrased in terms of the link update time or overall MFLOPS rates. For 32-bit arithmetic, it is 36.3 microsecond/link for 8 hits per iteration (40.9 microsecond for 10 hits) or 101.5 MFLOPS.

Uniform rovibrational collisional N2 bin model for DSMC, with application to atmospheric entry flows

NASA Astrophysics Data System (ADS)

Torres, E.; Bondar, Ye. A.; Magin, T. E.

2016-11-01

A state-to-state model for internal energy exchange and molecular dissociation allows for high-fidelity DSMC simulations. Elementary reaction cross sections for the N2 (v, J)+ N system were previously extracted from a quantum-chemical database, originally compiled at NASA Ames Research Center. Due to the high computational cost of simulating the full range of inelastic collision processes (approx. 23 million reactions), a coarse-grain model, called the Uniform RoVibrational Collisional (URVC) bin model can be used instead. This allows to reduce the original 9390 rovibrational levels of N2 to 10 energy bins. In the present work, this reduced model is used to simulate a 2D flow configuration, which more closely reproduces the conditions of high-speed entry into Earth's atmosphere. For this purpose, the URVC bin model had to be adapted for integration into the "Rarefied Gas Dynamics Analysis System" (RGDAS), a separate high-performance DSMC code capable of handling complex geometries and parallel computations. RGDAS was developed at the Institute of Theoretical and Applied Mechanics in Novosibirsk, Russia for use by the European Space Agency (ESA) and shares many features with the well-known SMILE code developed by the same group. We show that the reduced mechanism developed previously can be implemented in RGDAS, and the results exhibit nonequilibrium effects consistent with those observed in previous 1D-simulations.

Delayed Slater determinant update algorithms for high efficiency quantum Monte Carlo

DOE PAGES

McDaniel, Tyler; D’Azevedo, Ed F.; Li, Ying Wai; ...

2017-11-07

Within ab initio Quantum Monte Carlo simulations, the leading numerical cost for large systems is the computation of the values of the Slater determinants in the trial wavefunction. Each Monte Carlo step requires finding the determinant of a dense matrix. This is most commonly iteratively evaluated using a rank-1 Sherman-Morrison updating scheme to avoid repeated explicit calculation of the inverse. The overall computational cost is therefore formally cubic in the number of electrons or matrix size. To improve the numerical efficiency of this procedure, we propose a novel multiple rank delayed update scheme. This strategy enables probability evaluation with applicationmore » of accepted moves to the matrices delayed until after a predetermined number of moves, K. The accepted events are then applied to the matrices en bloc with enhanced arithmetic intensity and computational efficiency via matrix-matrix operations instead of matrix-vector operations. Here this procedure does not change the underlying Monte Carlo sampling or its statistical efficiency. For calculations on large systems and algorithms such as diffusion Monte Carlo where the acceptance ratio is high, order of magnitude improvements in the update time can be obtained on both multi- core CPUs and GPUs.« less

Delayed Slater determinant update algorithms for high efficiency quantum Monte Carlo

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

McDaniel, Tyler; D’Azevedo, Ed F.; Li, Ying Wai

Within ab initio Quantum Monte Carlo simulations, the leading numerical cost for large systems is the computation of the values of the Slater determinants in the trial wavefunction. Each Monte Carlo step requires finding the determinant of a dense matrix. This is most commonly iteratively evaluated using a rank-1 Sherman-Morrison updating scheme to avoid repeated explicit calculation of the inverse. The overall computational cost is therefore formally cubic in the number of electrons or matrix size. To improve the numerical efficiency of this procedure, we propose a novel multiple rank delayed update scheme. This strategy enables probability evaluation with applicationmore » of accepted moves to the matrices delayed until after a predetermined number of moves, K. The accepted events are then applied to the matrices en bloc with enhanced arithmetic intensity and computational efficiency via matrix-matrix operations instead of matrix-vector operations. Here this procedure does not change the underlying Monte Carlo sampling or its statistical efficiency. For calculations on large systems and algorithms such as diffusion Monte Carlo where the acceptance ratio is high, order of magnitude improvements in the update time can be obtained on both multi- core CPUs and GPUs.« less

Delayed Slater determinant update algorithms for high efficiency quantum Monte Carlo.

PubMed

McDaniel, T; D'Azevedo, E F; Li, Y W; Wong, K; Kent, P R C

2017-11-07

Within ab initio Quantum Monte Carlo simulations, the leading numerical cost for large systems is the computation of the values of the Slater determinants in the trial wavefunction. Each Monte Carlo step requires finding the determinant of a dense matrix. This is most commonly iteratively evaluated using a rank-1 Sherman-Morrison updating scheme to avoid repeated explicit calculation of the inverse. The overall computational cost is, therefore, formally cubic in the number of electrons or matrix size. To improve the numerical efficiency of this procedure, we propose a novel multiple rank delayed update scheme. This strategy enables probability evaluation with an application of accepted moves to the matrices delayed until after a predetermined number of moves, K. The accepted events are then applied to the matrices en bloc with enhanced arithmetic intensity and computational efficiency via matrix-matrix operations instead of matrix-vector operations. This procedure does not change the underlying Monte Carlo sampling or its statistical efficiency. For calculations on large systems and algorithms such as diffusion Monte Carlo, where the acceptance ratio is high, order of magnitude improvements in the update time can be obtained on both multi-core central processing units and graphical processing units.

Delayed Slater determinant update algorithms for high efficiency quantum Monte Carlo

NASA Astrophysics Data System (ADS)

McDaniel, T.; D'Azevedo, E. F.; Li, Y. W.; Wong, K.; Kent, P. R. C.

2017-11-01

Within ab initio Quantum Monte Carlo simulations, the leading numerical cost for large systems is the computation of the values of the Slater determinants in the trial wavefunction. Each Monte Carlo step requires finding the determinant of a dense matrix. This is most commonly iteratively evaluated using a rank-1 Sherman-Morrison updating scheme to avoid repeated explicit calculation of the inverse. The overall computational cost is, therefore, formally cubic in the number of electrons or matrix size. To improve the numerical efficiency of this procedure, we propose a novel multiple rank delayed update scheme. This strategy enables probability evaluation with an application of accepted moves to the matrices delayed until after a predetermined number of moves, K. The accepted events are then applied to the matrices en bloc with enhanced arithmetic intensity and computational efficiency via matrix-matrix operations instead of matrix-vector operations. This procedure does not change the underlying Monte Carlo sampling or its statistical efficiency. For calculations on large systems and algorithms such as diffusion Monte Carlo, where the acceptance ratio is high, order of magnitude improvements in the update time can be obtained on both multi-core central processing units and graphical processing units.

Distance between configurations in Markov chain Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Fukuma, Masafumi; Matsumoto, Nobuyuki; Umeda, Naoya

2017-12-01

For a given Markov chain Monte Carlo algorithm we introduce a distance between two configurations that quantifies the difficulty of transition from one configuration to the other configuration. We argue that the distance takes a universal form for the class of algorithms which generate local moves in the configuration space. We explicitly calculate the distance for the Langevin algorithm, and show that it certainly has desired and expected properties as distance. We further show that the distance for a multimodal distribution gets dramatically reduced from a large value by the introduction of a tempering method. We also argue that, when the original distribution is highly multimodal with large number of degenerate vacua, an anti-de Sitter-like geometry naturally emerges in the extended configuration space.

The impact of low-Z and high-Z metal implants in IMRT: A Monte Carlo study of dose inaccuracies in commercial dose algorithms

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

Spadea, Maria Francesca, E-mail: mfspadea@unicz.it; Verburg, Joost Mathias; Seco, Joao

2014-01-15

Purpose: The aim of the study was to evaluate the dosimetric impact of low-Z and high-Z metallic implants on IMRT plans. Methods: Computed tomography (CT) scans of three patients were analyzed to study effects due to the presence of Titanium (low-Z), Platinum and Gold (high-Z) inserts. To eliminate artifacts in CT images, a sinogram-based metal artifact reduction algorithm was applied. IMRT dose calculations were performed on both the uncorrected and corrected images using a commercial planning system (convolution/superposition algorithm) and an in-house Monte Carlo platform. Dose differences between uncorrected and corrected datasets were computed and analyzed using gamma index (Pγ{submore » <1}) and setting 2 mm and 2% as distance to agreement and dose difference criteria, respectively. Beam specific depth dose profiles across the metal were also examined. Results: Dose discrepancies between corrected and uncorrected datasets were not significant for low-Z material. High-Z materials caused under-dosage of 20%–25% in the region surrounding the metal and over dosage of 10%–15% downstream of the hardware. Gamma index test yielded Pγ{sub <1}>99% for all low-Z cases; while for high-Z cases it returned 91% < Pγ{sub <1}< 99%. Analysis of the depth dose curve of a single beam for low-Z cases revealed that, although the dose attenuation is altered inside the metal, it does not differ downstream of the insert. However, for high-Z metal implants the dose is increased up to 10%–12% around the insert. In addition, Monte Carlo method was more sensitive to the presence of metal inserts than superposition/convolution algorithm. Conclusions: The reduction in terms of dose of metal artifacts in CT images is relevant for high-Z implants. In this case, dose distribution should be calculated using Monte Carlo algorithms, given their superior accuracy in dose modeling in and around the metal. In addition, the knowledge of the composition of metal inserts improves the accuracy of the Monte Carlo dose calculation significantly.« less

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

Jakeman, John D.; Narayan, Akil; Zhou, Tao

We propose an algorithm for recovering sparse orthogonal polynomial expansions via collocation. A standard sampling approach for recovering sparse polynomials uses Monte Carlo sampling, from the density of orthogonality, which results in poor function recovery when the polynomial degree is high. Our proposed approach aims to mitigate this limitation by sampling with respect to the weighted equilibrium measure of the parametric domain and subsequently solves a preconditionedmore » $$\\ell^1$$-minimization problem, where the weights of the diagonal preconditioning matrix are given by evaluations of the Christoffel function. Our algorithm can be applied to a wide class of orthogonal polynomial families on bounded and unbounded domains, including all classical families. We present theoretical analysis to motivate the algorithm and numerical results that show our method is superior to standard Monte Carlo methods in many situations of interest. In conclusion, numerical examples are also provided to demonstrate that our proposed algorithm leads to comparable or improved accuracy even when compared with Legendre- and Hermite-specific algorithms.« less

Hybrid-optimization strategy for the communication of large-scale Kinetic Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Wu, Baodong; Li, Shigang; Zhang, Yunquan; Nie, Ningming

2017-02-01

The parallel Kinetic Monte Carlo (KMC) algorithm based on domain decomposition has been widely used in large-scale physical simulations. However, the communication overhead of the parallel KMC algorithm is critical, and severely degrades the overall performance and scalability. In this paper, we present a hybrid optimization strategy to reduce the communication overhead for the parallel KMC simulations. We first propose a communication aggregation algorithm to reduce the total number of messages and eliminate the communication redundancy. Then, we utilize the shared memory to reduce the memory copy overhead of the intra-node communication. Finally, we optimize the communication scheduling using the neighborhood collective operations. We demonstrate the scalability and high performance of our hybrid optimization strategy by both theoretical and experimental analysis. Results show that the optimized KMC algorithm exhibits better performance and scalability than the well-known open-source library-SPPARKS. On 32-node Xeon E5-2680 cluster (total 640 cores), the optimized algorithm reduces the communication time by 24.8% compared with SPPARKS.

A Generalized Sampling and Preconditioning Scheme for Sparse Approximation of Polynomial Chaos Expansions

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

Jakeman, John D.; Narayan, Akil; Zhou, Tao

We propose an algorithm for recovering sparse orthogonal polynomial expansions via collocation. A standard sampling approach for recovering sparse polynomials uses Monte Carlo sampling, from the density of orthogonality, which results in poor function recovery when the polynomial degree is high. Our proposed approach aims to mitigate this limitation by sampling with respect to the weighted equilibrium measure of the parametric domain and subsequently solves a preconditionedmore » $$\\ell^1$$-minimization problem, where the weights of the diagonal preconditioning matrix are given by evaluations of the Christoffel function. Our algorithm can be applied to a wide class of orthogonal polynomial families on bounded and unbounded domains, including all classical families. We present theoretical analysis to motivate the algorithm and numerical results that show our method is superior to standard Monte Carlo methods in many situations of interest. In conclusion, numerical examples are also provided to demonstrate that our proposed algorithm leads to comparable or improved accuracy even when compared with Legendre- and Hermite-specific algorithms.« less

A Generalized Sampling and Preconditioning Scheme for Sparse Approximation of Polynomial Chaos Expansions

DOE PAGES

Jakeman, John D.; Narayan, Akil; Zhou, Tao

2017-06-22

We propose an algorithm for recovering sparse orthogonal polynomial expansions via collocation. A standard sampling approach for recovering sparse polynomials uses Monte Carlo sampling, from the density of orthogonality, which results in poor function recovery when the polynomial degree is high. Our proposed approach aims to mitigate this limitation by sampling with respect to the weighted equilibrium measure of the parametric domain and subsequently solves a preconditionedmore » $$\\ell^1$$-minimization problem, where the weights of the diagonal preconditioning matrix are given by evaluations of the Christoffel function. Our algorithm can be applied to a wide class of orthogonal polynomial families on bounded and unbounded domains, including all classical families. We present theoretical analysis to motivate the algorithm and numerical results that show our method is superior to standard Monte Carlo methods in many situations of interest. In conclusion, numerical examples are also provided to demonstrate that our proposed algorithm leads to comparable or improved accuracy even when compared with Legendre- and Hermite-specific algorithms.« less

An Ensemble-Based Smoother with Retrospectively Updated Weights for Highly Nonlinear Systems

NASA Technical Reports Server (NTRS)

Chin, T. M.; Turmon, M. J.; Jewell, J. B.; Ghil, M.

2006-01-01

Monte Carlo computational methods have been introduced into data assimilation for nonlinear systems in order to alleviate the computational burden of updating and propagating the full probability distribution. By propagating an ensemble of representative states, algorithms like the ensemble Kalman filter (EnKF) and the resampled particle filter (RPF) rely on the existing modeling infrastructure to approximate the distribution based on the evolution of this ensemble. This work presents an ensemble-based smoother that is applicable to the Monte Carlo filtering schemes like EnKF and RPF. At the minor cost of retrospectively updating a set of weights for ensemble members, this smoother has demonstrated superior capabilities in state tracking for two highly nonlinear problems: the double-well potential and trivariate Lorenz systems. The algorithm does not require retrospective adaptation of the ensemble members themselves, and it is thus suited to a streaming operational mode. The accuracy of the proposed backward-update scheme in estimating non-Gaussian distributions is evaluated by comparison to the more accurate estimates provided by a Markov chain Monte Carlo algorithm.

Particle Communication and Domain Neighbor Coupling: Scalable Domain Decomposed Algorithms for Monte Carlo Particle Transport

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

O'Brien, M. J.; Brantley, P. S.

2015-01-20

In order to run Monte Carlo particle transport calculations on new supercomputers with hundreds of thousands or millions of processors, care must be taken to implement scalable algorithms. This means that the algorithms must continue to perform well as the processor count increases. In this paper, we examine the scalability of:(1) globally resolving the particle locations on the correct processor, (2) deciding that particle streaming communication has finished, and (3) efficiently coupling neighbor domains together with different replication levels. We have run domain decomposed Monte Carlo particle transport on up to 2 21 = 2,097,152 MPI processes on the IBMmore » BG/Q Sequoia supercomputer and observed scalable results that agree with our theoretical predictions. These calculations were carefully constructed to have the same amount of work on every processor, i.e. the calculation is already load balanced. We also examine load imbalanced calculations where each domain’s replication level is proportional to its particle workload. In this case we show how to efficiently couple together adjacent domains to maintain within workgroup load balance and minimize memory usage.« less

Quantum-enhanced reinforcement learning for finite-episode games with discrete state spaces

NASA Astrophysics Data System (ADS)

Neukart, Florian; Von Dollen, David; Seidel, Christian; Compostella, Gabriele

2017-12-01

Quantum annealing algorithms belong to the class of metaheuristic tools, applicable for solving binary optimization problems. Hardware implementations of quantum annealing, such as the quantum annealing machines produced by D-Wave Systems, have been subject to multiple analyses in research, with the aim of characterizing the technology's usefulness for optimization and sampling tasks. Here, we present a way to partially embed both Monte Carlo policy iteration for finding an optimal policy on random observations, as well as how to embed n sub-optimal state-value functions for approximating an improved state-value function given a policy for finite horizon games with discrete state spaces on a D-Wave 2000Q quantum processing unit (QPU). We explain how both problems can be expressed as a quadratic unconstrained binary optimization (QUBO) problem, and show that quantum-enhanced Monte Carlo policy evaluation allows for finding equivalent or better state-value functions for a given policy with the same number episodes compared to a purely classical Monte Carlo algorithm. Additionally, we describe a quantum-classical policy learning algorithm. Our first and foremost aim is to explain how to represent and solve parts of these problems with the help of the QPU, and not to prove supremacy over every existing classical policy evaluation algorithm.

Development of reversible jump Markov Chain Monte Carlo algorithm in the Bayesian mixture modeling for microarray data in Indonesia

NASA Astrophysics Data System (ADS)

Astuti, Ani Budi; Iriawan, Nur; Irhamah, Kuswanto, Heri

2017-12-01

In the Bayesian mixture modeling requires stages the identification number of the most appropriate mixture components thus obtained mixture models fit the data through data driven concept. Reversible Jump Markov Chain Monte Carlo (RJMCMC) is a combination of the reversible jump (RJ) concept and the Markov Chain Monte Carlo (MCMC) concept used by some researchers to solve the problem of identifying the number of mixture components which are not known with certainty number. In its application, RJMCMC using the concept of the birth/death and the split-merge with six types of movement, that are w updating, θ updating, z updating, hyperparameter β updating, split-merge for components and birth/death from blank components. The development of the RJMCMC algorithm needs to be done according to the observed case. The purpose of this study is to know the performance of RJMCMC algorithm development in identifying the number of mixture components which are not known with certainty number in the Bayesian mixture modeling for microarray data in Indonesia. The results of this study represent that the concept RJMCMC algorithm development able to properly identify the number of mixture components in the Bayesian normal mixture model wherein the component mixture in the case of microarray data in Indonesia is not known for certain number.

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.

Simulated Stochastic Approximation Annealing for Global Optimization with a Square-Root Cooling Schedule

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

Liang, Faming; Cheng, Yichen; Lin, Guang

2014-06-13

Simulated annealing has been widely used in the solution of optimization problems. As known by many researchers, the global optima cannot be guaranteed to be located by simulated annealing unless a logarithmic cooling schedule is used. However, the logarithmic cooling schedule is so slow that no one can afford to have such a long CPU time. This paper proposes a new stochastic optimization algorithm, the so-called simulated stochastic approximation annealing algorithm, which is a combination of simulated annealing and the stochastic approximation Monte Carlo algorithm. Under the framework of stochastic approximation Markov chain Monte Carlo, it is shown that themore » new algorithm can work with a cooling schedule in which the temperature can decrease much faster than in the logarithmic cooling schedule, e.g., a square-root cooling schedule, while guaranteeing the global optima to be reached when the temperature tends to zero. The new algorithm has been tested on a few benchmark optimization problems, including feed-forward neural network training and protein-folding. The numerical results indicate that the new algorithm can significantly outperform simulated annealing and other competitors.« less

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.

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.

Simulation-Based Model Checking for Nondeterministic Systems and Rare Events

DTIC Science & Technology

2016-03-24

year, we have investigated AO* search and Monte Carlo Tree Search algorithms to complement and enhance CMU’s SMCMDP. 1 Final Report, March 14... tree , so we can use it to find the probability of reachability for a property in PRISM’s Probabilistic LTL. By finding the maximum probability of...savings, particularly when handling very large models. 2.3 Monte Carlo Tree Search The Monte Carlo sampling process in SMCMDP can take a long time to

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

Virtual Network Embedding via Monte Carlo Tree Search.

PubMed

Haeri, Soroush; Trajkovic, Ljiljana

2018-02-01

Network virtualization helps overcome shortcomings of the current Internet architecture. The virtualized network architecture enables coexistence of multiple virtual networks (VNs) on an existing physical infrastructure. VN embedding (VNE) problem, which deals with the embedding of VN components onto a physical network, is known to be -hard. In this paper, we propose two VNE algorithms: MaVEn-M and MaVEn-S. MaVEn-M employs the multicommodity flow algorithm for virtual link mapping while MaVEn-S uses the shortest-path algorithm. They formalize the virtual node mapping problem by using the Markov decision process (MDP) framework and devise action policies (node mappings) for the proposed MDP using the Monte Carlo tree search algorithm. Service providers may adjust the execution time of the MaVEn algorithms based on the traffic load of VN requests. The objective of the algorithms is to maximize the profit of infrastructure providers. We develop a discrete event VNE simulator to implement and evaluate performance of MaVEn-M, MaVEn-S, and several recently proposed VNE algorithms. We introduce profitability as a new performance metric that captures both acceptance and revenue to cost ratios. Simulation results show that the proposed algorithms find more profitable solutions than the existing algorithms. Given additional computation time, they further improve embedding solutions.

Self-learning Monte Carlo with deep neural networks

NASA Astrophysics Data System (ADS)

Shen, Huitao; Liu, Junwei; Fu, Liang

2018-05-01

The self-learning Monte Carlo (SLMC) method is a general algorithm to speedup MC simulations. Its efficiency has been demonstrated in various systems by introducing an effective model to propose global moves in the configuration space. In this paper, we show that deep neural networks can be naturally incorporated into SLMC, and without any prior knowledge can learn the original model accurately and efficiently. Demonstrated in quantum impurity models, we reduce the complexity for a local update from O (β2) in Hirsch-Fye algorithm to O (β lnβ ) , which is a significant speedup especially for systems at low temperatures.

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.

Vectorization of a Monte Carlo simulation scheme for nonequilibrium gas dynamics

NASA Technical Reports Server (NTRS)

Boyd, Iain D.

1991-01-01

Significant improvement has been obtained in the numerical performance of a Monte Carlo scheme for the analysis of nonequilibrium gas dynamics through an implementation of the algorithm which takes advantage of vector hardware, as presently demonstrated through application to three different problems. These are (1) a 1D standing-shock wave; (2) the flow of an expanding gas through an axisymmetric nozzle; and (3) the hypersonic flow of Ar gas over a 3D wedge. Problem (3) is illustrative of the greatly increased number of molecules which the simulation may involve, thanks to improved algorithm performance.

Multicanonical hybrid Monte Carlo algorithm: Boosting simulations of compact QED

NASA Astrophysics Data System (ADS)

Arnold, G.; Schilling, K.; Lippert, Th.

1999-03-01

We demonstrate that substantial progress can be achieved in the study of the phase structure of four-dimensional compact QED by a joint use of hybrid Monte Carlo and multicanonical algorithms through an efficient parallel implementation. This is borne out by the observation of considerable speedup of tunnelling between the metastable states, close to the phase transition, on the Wilson line. We estimate that the creation of adequate samples (with order 100 flip-flops) becomes a matter of half a year's run time at 2 Gflops sustained performance for lattices of size up to 244.

A novel Monte Carlo algorithm for simulating crystals with McStas

NASA Astrophysics Data System (ADS)

Alianelli, L.; Sánchez del Río, M.; Felici, R.; Andersen, K. H.; Farhi, E.

2004-07-01

We developed an original Monte Carlo algorithm for the simulation of Bragg diffraction by mosaic, bent and gradient crystals. It has practical applications, as it can be used for simulating imperfect crystals (monochromators, analyzers and perhaps samples) in neutron ray-tracing packages, like McStas. The code we describe here provides a detailed description of the particle interaction with the microscopic homogeneous regions composing the crystal, therefore it can be used also for the calculation of quantities having a conceptual interest, as multiple scattering, or for the interpretation of experiments aiming at characterizing crystals, like diffraction topographs.

Probabilistic analysis algorithm for UA slope software program.

DOT National Transportation Integrated Search

2013-12-01

A reliability-based computational algorithm for using a single row and equally spaced drilled shafts to : stabilize an unstable slope has been developed in this research. The Monte-Carlo simulation (MCS) : technique was used in the previously develop...

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.

Estimating rare events in biochemical systems using conditional sampling.

PubMed

Sundar, V S

2017-01-28

The paper focuses on development of variance reduction strategies to estimate rare events in biochemical systems. Obtaining this probability using brute force Monte Carlo simulations in conjunction with the stochastic simulation algorithm (Gillespie's method) is computationally prohibitive. To circumvent this, important sampling tools such as the weighted stochastic simulation algorithm and the doubly weighted stochastic simulation algorithm have been proposed. However, these strategies require an additional step of determining the important region to sample from, which is not straightforward for most of the problems. In this paper, we apply the subset simulation method, developed as a variance reduction tool in the context of structural engineering, to the problem of rare event estimation in biochemical systems. The main idea is that the rare event probability is expressed as a product of more frequent conditional probabilities. These conditional probabilities are estimated with high accuracy using Monte Carlo simulations, specifically the Markov chain Monte Carlo method with the modified Metropolis-Hastings algorithm. Generating sample realizations of the state vector using the stochastic simulation algorithm is viewed as mapping the discrete-state continuous-time random process to the standard normal random variable vector. This viewpoint opens up the possibility of applying more sophisticated and efficient sampling schemes developed elsewhere to problems in stochastic chemical kinetics. The results obtained using the subset simulation method are compared with existing variance reduction strategies for a few benchmark problems, and a satisfactory improvement in computational time is demonstrated.

Parallel Monte Carlo Search for Hough Transform

NASA Astrophysics Data System (ADS)

Lopes, Raul H. C.; Franqueira, Virginia N. L.; Reid, Ivan D.; Hobson, Peter R.

2017-10-01

We investigate the problem of line detection in digital image processing and in special how state of the art algorithms behave in the presence of noise and whether CPU efficiency can be improved by the combination of a Monte Carlo Tree Search, hierarchical space decomposition, and parallel computing. The starting point of the investigation is the method introduced in 1962 by Paul Hough for detecting lines in binary images. Extended in the 1970s to the detection of space forms, what came to be known as Hough Transform (HT) has been proposed, for example, in the context of track fitting in the LHC ATLAS and CMS projects. The Hough Transform transfers the problem of line detection, for example, into one of optimization of the peak in a vote counting process for cells which contain the possible points of candidate lines. The detection algorithm can be computationally expensive both in the demands made upon the processor and on memory. Additionally, it can have a reduced effectiveness in detection in the presence of noise. Our first contribution consists in an evaluation of the use of a variation of the Radon Transform as a form of improving theeffectiveness of line detection in the presence of noise. Then, parallel algorithms for variations of the Hough Transform and the Radon Transform for line detection are introduced. An algorithm for Parallel Monte Carlo Search applied to line detection is also introduced. Their algorithmic complexities are discussed. Finally, implementations on multi-GPU and multicore architectures are discussed.

The Linked Neighbour List (LNL) method for fast off-lattice Monte Carlo simulations of fluids

NASA Astrophysics Data System (ADS)

Mazzeo, M. D.; Ricci, M.; Zannoni, C.

2010-03-01

We present a new algorithm, called linked neighbour list (LNL), useful to substantially speed up off-lattice Monte Carlo simulations of fluids by avoiding the computation of the molecular energy before every attempted move. We introduce a few variants of the LNL method targeted to minimise memory footprint or augment memory coherence and cache utilisation. Additionally, we present a few algorithms which drastically accelerate neighbour finding. We test our methods on the simulation of a dense off-lattice Gay-Berne fluid subjected to periodic boundary conditions observing a speedup factor of about 2.5 with respect to a well-coded implementation based on a conventional link-cell. We provide several implementation details of the different key data structures and algorithms used in this work.

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.

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

Bolding, Simon R.; Cleveland, Mathew Allen; Morel, Jim E.

In this paper, we have implemented a new high-order low-order (HOLO) algorithm for solving thermal radiative transfer problems. The low-order (LO) system is based on the spatial and angular moments of the transport equation and a linear-discontinuous finite-element spatial representation, producing equations similar to the standard S 2 equations. The LO solver is fully implicit in time and efficiently resolves the nonlinear temperature dependence at each time step. The high-order (HO) solver utilizes exponentially convergent Monte Carlo (ECMC) to give a globally accurate solution for the angular intensity to a fixed-source pure-absorber transport problem. This global solution is used tomore » compute consistency terms, which require the HO and LO solutions to converge toward the same solution. The use of ECMC allows for the efficient reduction of statistical noise in the Monte Carlo solution, reducing inaccuracies introduced through the LO consistency terms. Finally, we compare results with an implicit Monte Carlo code for one-dimensional gray test problems and demonstrate the efficiency of ECMC over standard Monte Carlo in this HOLO algorithm.« less

An empirical approach to estimate near-infra-red photon propagation and optically induced drug release in brain tissues

NASA Astrophysics Data System (ADS)

Prabhu Verleker, Akshay; Fang, Qianqian; Choi, Mi-Ran; Clare, Susan; Stantz, Keith M.

2015-03-01

The purpose of this study is to develop an alternate empirical approach to estimate near-infra-red (NIR) photon propagation and quantify optically induced drug release in brain metastasis, without relying on computationally expensive Monte Carlo techniques (gold standard). Targeted drug delivery with optically induced drug release is a noninvasive means to treat cancers and metastasis. This study is part of a larger project to treat brain metastasis by delivering lapatinib-drug-nanocomplexes and activating NIR-induced drug release. The empirical model was developed using a weighted approach to estimate photon scattering in tissues and calibrated using a GPU based 3D Monte Carlo. The empirical model was developed and tested against Monte Carlo in optical brain phantoms for pencil beams (width 1mm) and broad beams (width 10mm). The empirical algorithm was tested against the Monte Carlo for different albedos along with diffusion equation and in simulated brain phantoms resembling white-matter (μs'=8.25mm-1, μa=0.005mm-1) and gray-matter (μs'=2.45mm-1, μa=0.035mm-1) at wavelength 800nm. The goodness of fit between the two models was determined using coefficient of determination (R-squared analysis). Preliminary results show the Empirical algorithm matches Monte Carlo simulated fluence over a wide range of albedo (0.7 to 0.99), while the diffusion equation fails for lower albedo. The photon fluence generated by empirical code matched the Monte Carlo in homogeneous phantoms (R2=0.99). While GPU based Monte Carlo achieved 300X acceleration compared to earlier CPU based models, the empirical code is 700X faster than the Monte Carlo for a typical super-Gaussian laser beam.

An Efficient MCMC Algorithm to Sample Binary Matrices with Fixed Marginals

ERIC Educational Resources Information Center

Verhelst, Norman D.

2008-01-01

Uniform sampling of binary matrices with fixed margins is known as a difficult problem. Two classes of algorithms to sample from a distribution not too different from the uniform are studied in the literature: importance sampling and Markov chain Monte Carlo (MCMC). Existing MCMC algorithms converge slowly, require a long burn-in period and yield…

SKIRT: The design of a suite of input models for Monte Carlo radiative transfer simulations

NASA Astrophysics Data System (ADS)

Baes, M.; Camps, P.

2015-09-01

The Monte Carlo method is the most popular technique to perform radiative transfer simulations in a general 3D geometry. The algorithms behind and acceleration techniques for Monte Carlo radiative transfer are discussed extensively in the literature, and many different Monte Carlo codes are publicly available. On the contrary, the design of a suite of components that can be used for the distribution of sources and sinks in radiative transfer codes has received very little attention. The availability of such models, with different degrees of complexity, has many benefits. For example, they can serve as toy models to test new physical ingredients, or as parameterised models for inverse radiative transfer fitting. For 3D Monte Carlo codes, this requires algorithms to efficiently generate random positions from 3D density distributions. We describe the design of a flexible suite of components for the Monte Carlo radiative transfer code SKIRT. The design is based on a combination of basic building blocks (which can be either analytical toy models or numerical models defined on grids or a set of particles) and the extensive use of decorators that combine and alter these building blocks to more complex structures. For a number of decorators, e.g. those that add spiral structure or clumpiness, we provide a detailed description of the algorithms that can be used to generate random positions. Advantages of this decorator-based design include code transparency, the avoidance of code duplication, and an increase in code maintainability. Moreover, since decorators can be chained without problems, very complex models can easily be constructed out of simple building blocks. Finally, based on a number of test simulations, we demonstrate that our design using customised random position generators is superior to a simpler design based on a generic black-box random position generator.

Wavelet Monte Carlo dynamics: A new algorithm for simulating the hydrodynamics of interacting Brownian particles

NASA Astrophysics Data System (ADS)

Dyer, Oliver T.; Ball, Robin C.

2017-03-01

We develop a new algorithm for the Brownian dynamics of soft matter systems that evolves time by spatially correlated Monte Carlo moves. The algorithm uses vector wavelets as its basic moves and produces hydrodynamics in the low Reynolds number regime propagated according to the Oseen tensor. When small moves are removed, the correlations closely approximate the Rotne-Prager tensor, itself widely used to correct for deficiencies in Oseen. We also include plane wave moves to provide the longest range correlations, which we detail for both infinite and periodic systems. The computational cost of the algorithm scales competitively with the number of particles simulated, N, scaling as N In N in homogeneous systems and as N in dilute systems. In comparisons to established lattice Boltzmann and Brownian dynamics algorithms, the wavelet method was found to be only a factor of order 1 times more expensive than the cheaper lattice Boltzmann algorithm in marginally semi-dilute simulations, while it is significantly faster than both algorithms at large N in dilute simulations. We also validate the algorithm by checking that it reproduces the correct dynamics and equilibrium properties of simple single polymer systems, as well as verifying the effect of periodicity on the mobility tensor.

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.

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.

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.

MUSiC - A general search for deviations from monte carlo predictions in CMS

NASA Astrophysics Data System (ADS)

Biallass, Philipp A.; CMS Collaboration

2009-06-01

A model independent analysis approach in CMS is presented, systematically scanning the data for deviations from the Monte Carlo expectation. Such an analysis can contribute to the understanding of the detector and the tuning of the event generators. Furthermore, due to the minimal theoretical bias this approach is sensitive to a variety of models of new physics, including those not yet thought of. Events are classified into event classes according to their particle content (muons, electrons, photons, jets and missing transverse energy). A broad scan of various distributions is performed, identifying significant deviations from the Monte Carlo simulation. The importance of systematic uncertainties is outlined, which are taken into account rigorously within the algorithm. Possible detector effects and generator issues, as well as models involving Supersymmetry and new heavy gauge bosons are used as an input to the search algorithm.

MUSiC - A Generic Search for Deviations from Monte Carlo Predictions in CMS

NASA Astrophysics Data System (ADS)

Hof, Carsten

2009-05-01

We present a model independent analysis approach, systematically scanning the data for deviations from the Standard Model Monte Carlo expectation. Such an analysis can contribute to the understanding of the CMS detector and the tuning of the event generators. Furthermore, due to the minimal theoretical bias this approach is sensitive to a variety of models of new physics, including those not yet thought of. Events are classified into event classes according to their particle content (muons, electrons, photons, jets and missing transverse energy). A broad scan of various distributions is performed, identifying significant deviations from the Monte Carlo simulation. We outline the importance of systematic uncertainties, which are taken into account rigorously within the algorithm. Possible detector effects and generator issues, as well as models involving supersymmetry and new heavy gauge bosons have been used as an input to the search algorithm.

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.

Instantons in Quantum Annealing: Thermally Assisted Tunneling Vs Quantum Monte Carlo Simulations

NASA Technical Reports Server (NTRS)

Jiang, Zhang; Smelyanskiy, Vadim N.; Boixo, Sergio; Isakov, Sergei V.; Neven, Hartmut; Mazzola, Guglielmo; Troyer, Matthias

2015-01-01

Recent numerical result (arXiv:1512.02206) from Google suggested that the D-Wave quantum annealer may have an asymptotic speed-up than simulated annealing, however, the asymptotic advantage disappears when it is compared to quantum Monte Carlo (a classical algorithm despite its name). We show analytically that the asymptotic scaling of quantum tunneling is exactly the same as the escape rate in quantum Monte Carlo for a class of problems. Thus, the Google result might be explained in our framework. We also found that the transition state in quantum Monte Carlo corresponds to the instanton solution in quantum tunneling problems, which is observed in numerical simulations.

Modeling of the VIRTIS-M Observations of the Coma of Comet 67P/Churyumov-Gerasimenko

NASA Astrophysics Data System (ADS)

Fougere, Nicolas; Combi, Michael R.; Tenishev, Valeriy; Bieler, Andre; Migliorini, Alessandra; Piccioni, Giuseppe; Capaccioni, Fabrizio; Filacchione, Gianrico; Toth, Gabor; Huang, Zhenguang; Gombosi, Tamas; Hansen, Kenneth; Bockelee-Morvan, Dominique; Debout, Vincent; Erard, Stephane; Leyrat, Cedric; Fink, Uwe; Rubin, Martin; Altwegg, Kathrin; Tzou, Chia-Yu; Le Roy, Lena; Calmonte, Ursina; Berthelier, Jean-Jacques; Reme, Henri; Hassig, Myrtha; Fuselier, Stephen; Fiethe, Bjorn; De Keyser, Johan

2015-11-01

The recent images of the inner coma of 67P/Churyumov-Gerasimenko (CG) made by the infrared channel of the VIRTIS-M instrument on board the Rosetta spacecraft show the gas distribution as it expands in the coma (Migliorini et al. 2015, DPS abstract).Since VIRTIS is a remote sensing instrument, a proper modeling of these observations requires the computation of the full coma of comet CG, which necessitates the use of a kinetic approach due to the rather low gas densities. Hence, we apply a Direct Simulation Monde Carlo (DSMC) method to solve the Boltzmann equation and describe CG’s coma from the nucleus surface up to a few hundreds of kilometers. The model uses the SHAP5 nucleus shape model from the OSIRIS team. The gas flux distribution takes into account solar illumination, including self-shadowing. The local activity at the surface of the nucleus is given by spherical harmonics expansion reproducing best the ROSINA-DFMS data. The densities from the DSMC model outputs are then integrated along the line-of-sight to create synthetic images that are directly comparable with the VIRTIS-M column density measurements.The good agreement between the observations and the model illustrates our continuously improving understanding of the physics of the coma of comet CG.AcknowledgementsWork at UofM was supported by contracts JPL#1266313, JPL#1266314 and NASA grant NNX09AB59G. Work at UoB was funded by the State of Bern, the Swiss National Science Foundation and by the European Space Agency PRODEX Program. Work at Southwest Research institute was supported by subcontract #1496541 from the JPL. Work at BIRA-IASB was supported by the Belgian Science Policy Office via PRODEX/ROSINA PEA 90020. The authors would like to thank ASI, CNES, DLR, NASA for supporting this research. VIRTIS was built by a consortium formed by Italy, France and Germany, under the scientific responsibility of the IAPS of INAF, which guides also the scientific operations. The consortium includes also the LESIA of the Observatoire de Paris, and the Institut für Planetenforschung of DLR. The authors wish to thank the RSGS and the RMOC for their continuous support.

Goal-oriented sensitivity analysis for lattice kinetic Monte Carlo simulations

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

Arampatzis, Georgios, E-mail: garab@math.uoc.gr; Department of Mathematics and Statistics, University of Massachusetts, Amherst, Massachusetts 01003; Katsoulakis, Markos A., E-mail: markos@math.umass.edu

2014-03-28

In this paper we propose a new class of coupling methods for the sensitivity analysis of high dimensional stochastic systems and in particular for lattice Kinetic Monte Carlo (KMC). Sensitivity analysis for stochastic systems is typically based on approximating continuous derivatives with respect to model parameters by the mean value of samples from a finite difference scheme. Instead of using independent samples the proposed algorithm reduces the variance of the estimator by developing a strongly correlated-“coupled”- stochastic process for both the perturbed and unperturbed stochastic processes, defined in a common state space. The novelty of our construction is that themore » new coupled process depends on the targeted observables, e.g., coverage, Hamiltonian, spatial correlations, surface roughness, etc., hence we refer to the proposed method as goal-oriented sensitivity analysis. In particular, the rates of the coupled Continuous Time Markov Chain are obtained as solutions to a goal-oriented optimization problem, depending on the observable of interest, by considering the minimization functional of the corresponding variance. We show that this functional can be used as a diagnostic tool for the design and evaluation of different classes of couplings. Furthermore, the resulting KMC sensitivity algorithm has an easy implementation that is based on the Bortz–Kalos–Lebowitz algorithm's philosophy, where events are divided in classes depending on level sets of the observable of interest. Finally, we demonstrate in several examples including adsorption, desorption, and diffusion Kinetic Monte Carlo that for the same confidence interval and observable, the proposed goal-oriented algorithm can be two orders of magnitude faster than existing coupling algorithms for spatial KMC such as the Common Random Number approach. We also provide a complete implementation of the proposed sensitivity analysis algorithms, including various spatial KMC examples, in a supplementary MATLAB source code.« less

Extraction of diffuse correlation spectroscopy flow index by integration of Nth-order linear model with Monte Carlo simulation

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

Shang, Yu; Lin, Yu; Yu, Guoqiang, E-mail: guoqiang.yu@uky.edu

2014-05-12

Conventional semi-infinite solution for extracting blood flow index (BFI) from diffuse correlation spectroscopy (DCS) measurements may cause errors in estimation of BFI (αD{sub B}) in tissues with small volume and large curvature. We proposed an algorithm integrating Nth-order linear model of autocorrelation function with the Monte Carlo simulation of photon migrations in tissue for the extraction of αD{sub B}. The volume and geometry of the measured tissue were incorporated in the Monte Carlo simulation, which overcome the semi-infinite restrictions. The algorithm was tested using computer simulations on four tissue models with varied volumes/geometries and applied on an in vivo strokemore » model of mouse. Computer simulations shows that the high-order (N ≥ 5) linear algorithm was more accurate in extracting αD{sub B} (errors < ±2%) from the noise-free DCS data than the semi-infinite solution (errors: −5.3% to −18.0%) for different tissue models. Although adding random noises to DCS data resulted in αD{sub B} variations, the mean values of errors in extracting αD{sub B} were similar to those reconstructed from the noise-free DCS data. In addition, the errors in extracting the relative changes of αD{sub B} using both linear algorithm and semi-infinite solution were fairly small (errors < ±2.0%) and did not rely on the tissue volume/geometry. The experimental results from the in vivo stroke mice agreed with those in simulations, demonstrating the robustness of the linear algorithm. DCS with the high-order linear algorithm shows the potential for the inter-subject comparison and longitudinal monitoring of absolute BFI in a variety of tissues/organs with different volumes/geometries.« less

An Improved Elastic and Nonelastic Neutron Transport Algorithm for Space Radiation

NASA Technical Reports Server (NTRS)

Clowdsley, Martha S.; Wilson, John W.; Heinbockel, John H.; Tripathi, R. K.; Singleterry, Robert C., Jr.; Shinn, Judy L.

2000-01-01

A neutron transport algorithm including both elastic and nonelastic particle interaction processes for use in space radiation protection for arbitrary shield material is developed. The algorithm is based upon a multiple energy grouping and analysis of the straight-ahead Boltzmann equation by using a mean value theorem for integrals. The algorithm is then coupled to the Langley HZETRN code through a bidirectional neutron evaporation source term. Evaluation of the neutron fluence generated by the solar particle event of February 23, 1956, for an aluminum water shield-target configuration is then compared with MCNPX and LAHET Monte Carlo calculations for the same shield-target configuration. With the Monte Carlo calculation as a benchmark, the algorithm developed in this paper showed a great improvement in results over the unmodified HZETRN solution. In addition, a high-energy bidirectional neutron source based on a formula by Ranft showed even further improvement of the fluence results over previous results near the front of the water target where diffusion out the front surface is important. Effects of improved interaction cross sections are modest compared with the addition of the high-energy bidirectional source terms.

Delving Into Dissipative Quantum Dynamics: From Approximate to Numerically Exact Approaches

NASA Astrophysics Data System (ADS)

Chen, Hsing-Ta

In this thesis, I explore dissipative quantum dynamics of several prototypical model systems via various approaches, ranging from approximate to numerically exact schemes. In particular, in the realm of the approximate I explore the accuracy of Pade-resummed master equations and the fewest switches surface hopping (FSSH) algorithm for the spin-boson model, and non-crossing approximations (NCA) for the Anderson-Holstein model. Next, I develop new and exact Monte Carlo approaches and test them on the spin-boson model. I propose well-defined criteria for assessing the accuracy of Pade-resummed quantum master equations, which correctly demarcate the regions of parameter space where the Pade approximation is reliable. I continue the investigation of spin-boson dynamics by benchmark comparisons of the semiclassical FSSH algorithm to exact dynamics over a wide range of parameters. Despite small deviations from golden-rule scaling in the Marcus regime, standard surface hopping algorithm is found to be accurate over a large portion of parameter space. The inclusion of decoherence corrections via the augmented FSSH algorithm improves the accuracy of dynamical behavior compared to exact simulations, but the effects are generally not dramatic for the cases I consider. Next, I introduce new methods for numerically exact real-time simulation based on real-time diagrammatic Quantum Monte Carlo (dQMC) and the inchworm algorithm. These methods optimally recycle Monte Carlo information from earlier times to greatly suppress the dynamical sign problem. In the context of the spin-boson model, I formulate the inchworm expansion in two distinct ways: the first with respect to an expansion in the system-bath coupling and the second as an expansion in the diabatic coupling. In addition, a cumulant version of the inchworm Monte Carlo method is motivated by the latter expansion, which allows for further suppression of the growth of the sign error. I provide a comprehensive comparison of the performance of the inchworm Monte Carlo algorithms to other exact methodologies as well as a discussion of the relative advantages and disadvantages of each. Finally, I investigate the dynamical interplay between the electron-electron interaction and the electron-phonon coupling within the Anderson-Holstein model via two complementary NCAs: the first is constructed around the weak-coupling limit and the second around the polaron limit. The influence of phonons on spectral and transport properties is explored in equilibrium, for non-equilibrium steady state and for transient dynamics after a quench. I find the two NCAs disagree in nontrivial ways, indicating that more reliable approaches to the problem are needed. The complementary frameworks used here pave the way for numerically exact methods based on inchworm dQMC algorithms capable of treating open systems simultaneously coupled to multiple fermionic and bosonic baths.

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.

Statistical hadronization and microcanonical ensemble

DOE PAGES

Becattini, F.; Ferroni, L.

2004-01-01

We present a Monte Carlo calculation of the microcanonical ensemble of the of the ideal hadron-resonance gas including all known states up to a mass of 1. 8 GeV, taking into account quantum statistics. The computing method is a development of a previous one based on a Metropolis Monte Carlo algorithm, with a the grand-canonical limit of the multi-species multiplicity distribution as proposal matrix. The microcanonical average multiplicities of the various hadron species are found to converge to the canonical ones for moderately low values of the total energy. This algorithm opens the way for event generators based for themore » statistical hadronization model.« less

Experimental evaluation of a GPU-based Monte Carlo dose calculation algorithm in the Monaco treatment planning system.

PubMed

Paudel, Moti R; Kim, Anthony; Sarfehnia, Arman; Ahmad, Sayed B; Beachey, David J; Sahgal, Arjun; Keller, Brian M

2016-11-08

A new GPU-based Monte Carlo dose calculation algorithm (GPUMCD), devel-oped by the vendor Elekta for the Monaco treatment planning system (TPS), is capable of modeling dose for both a standard linear accelerator and an Elekta MRI linear accelerator. We have experimentally evaluated this algorithm for a standard Elekta Agility linear accelerator. A beam model was developed in the Monaco TPS (research version 5.09.06) using the commissioned beam data for a 6 MV Agility linac. A heterogeneous phantom representing several scenarios - tumor-in-lung, lung, and bone-in-tissue - was designed and built. Dose calculations in Monaco were done using both the current clinical Monte Carlo algorithm, XVMC, and the new GPUMCD algorithm. Dose calculations in a Pinnacle TPS were also produced using the collapsed cone convolution (CCC) algorithm with heterogeneity correc-tion. Calculations were compared with the measured doses using an ionization chamber (A1SL) and Gafchromic EBT3 films for 2 × 2 cm2, 5 × 5 cm2, and 10 × 10 cm2 field sizes. The percentage depth doses (PDDs) calculated by XVMC and GPUMCD in a homogeneous solid water phantom were within 2%/2 mm of film measurements and within 1% of ion chamber measurements. For the tumor-in-lung phantom, the calculated doses were within 2.5%/2.5 mm of film measurements for GPUMCD. For the lung phantom, doses calculated by all of the algorithms were within 3%/3 mm of film measurements, except for the 2 × 2 cm2 field size where the CCC algorithm underestimated the depth dose by ~ 5% in a larger extent of the lung region. For the bone phantom, all of the algorithms were equivalent and calculated dose to within 2%/2 mm of film measurements, except at the interfaces. Both GPUMCD and XVMC showed interface effects, which were more pronounced for GPUMCD and were comparable to film measurements, whereas the CCC algorithm showed these effects poorly. © 2016 The Authors.

A clinical study of lung cancer dose calculation accuracy with Monte Carlo simulation.

PubMed

Zhao, Yanqun; Qi, Guohai; Yin, Gang; Wang, Xianliang; Wang, Pei; Li, Jian; Xiao, Mingyong; Li, Jie; Kang, Shengwei; Liao, Xiongfei

2014-12-16

The accuracy of dose calculation is crucial to the quality of treatment planning and, consequently, to the dose delivered to patients undergoing radiation therapy. Current general calculation algorithms such as Pencil Beam Convolution (PBC) and Collapsed Cone Convolution (CCC) have shortcomings in regard to severe inhomogeneities, particularly in those regions where charged particle equilibrium does not hold. The aim of this study was to evaluate the accuracy of the PBC and CCC algorithms in lung cancer radiotherapy using Monte Carlo (MC) technology. Four treatment plans were designed using Oncentra Masterplan TPS for each patient. Two intensity-modulated radiation therapy (IMRT) plans were developed using the PBC and CCC algorithms, and two three-dimensional conformal therapy (3DCRT) plans were developed using the PBC and CCC algorithms. The DICOM-RT files of the treatment plans were exported to the Monte Carlo system to recalculate. The dose distributions of GTV, PTV and ipsilateral lung calculated by the TPS and MC were compared. For 3DCRT and IMRT plans, the mean dose differences for GTV between the CCC and MC increased with decreasing of the GTV volume. For IMRT, the mean dose differences were found to be higher than that of 3DCRT. The CCC algorithm overestimated the GTV mean dose by approximately 3% for IMRT. For 3DCRT plans, when the volume of the GTV was greater than 100 cm(3), the mean doses calculated by CCC and MC almost have no difference. PBC shows large deviations from the MC algorithm. For the dose to the ipsilateral lung, the CCC algorithm overestimated the dose to the entire lung, and the PBC algorithm overestimated V20 but underestimated V5; the difference in V10 was not statistically significant. PBC substantially overestimates the dose to the tumour, but the CCC is similar to the MC simulation. It is recommended that the treatment plans for lung cancer be developed using an advanced dose calculation algorithm other than PBC. MC can accurately calculate the dose distribution in lung cancer and can provide a notably effective tool for benchmarking the performance of other dose calculation algorithms within patients.

Water Oxidation Catalysis for NiOOH by a Metropolis Monte Carlo Algorithm.

PubMed

Hareli, Chen; Caspary Toroker, Maytal

2018-05-08

Understanding catalytic mechanisms is important for discovering better catalysts, particularly for water splitting reactions that are of great interest to the renewable energy field. One of the best performing catalysts for water oxidation is nickel oxyhydroxide (NiOOH). However, only one mechanism has been adopted so far for modeling catalysis of the active plane: β-NiOOH(01̅5). In order to understand how a second reaction mechanism affects catalysis, we perform Density Functional Theory + U (DFT+U) calculations of a second mechanism for water oxidation reaction of NiOOH. Then, we use a Metropolis Monte Carlo algorithm to calculate how many catalytic cycles are completed when two reaction mechanisms are competing. We find that within the Metropolis algorithm, the second mechanism has a higher overpotential and is therefore not active even for large applied biases.

Improved cache performance in Monte Carlo transport calculations using energy banding

NASA Astrophysics Data System (ADS)

Siegel, A.; Smith, K.; Felker, K.; Romano, P.; Forget, B.; Beckman, P.

2014-04-01

We present an energy banding algorithm for Monte Carlo (MC) neutral particle transport simulations which depend on large cross section lookup tables. In MC codes, read-only cross section data tables are accessed frequently, exhibit poor locality, and are typically too much large to fit in fast memory. Thus, performance is often limited by long latencies to RAM, or by off-node communication latencies when the data footprint is very large and must be decomposed on a distributed memory machine. The proposed energy banding algorithm allows maximal temporal reuse of data in band sizes that can flexibly accommodate different architectural features. The energy banding algorithm is general and has a number of benefits compared to the traditional approach. In the present analysis we explore its potential to achieve improvements in time-to-solution on modern cache-based architectures.

Three-dimensional particle simulation of back-sputtered carbon in electric propulsion test facility

NASA Astrophysics Data System (ADS)

Zheng, Hongru; Cai, Guobiao; Liu, Lihui; Shang, Shengfei; He, Bijiao

2017-03-01

The back-sputtering deposition on thruster surface caused by ion bombardment on chamber wall material affects the performance of thrusters during the ground based electric propulsion endurance tests. In order to decrease the back-sputtering deposition, most of vacuum chambers applied in electric propulsion experiments are equipped with anti-sputtering targets. In this paper, a three-dimensional model of plume experimental system (PES) including double layer anti-sputtering target is established. Simulation cases are made to simulate the plasma environment and sputtering effects when an ion thruster is working. The particle in cell (PIC) method and direct simulation Monte Carlo (DSMC) method is used to calculate the velocity and position of particles. Yamamura's model is used to simulate the sputtering process. The distribution of sputtered anti-sputtering target material is presented. The results show that the double layer anti-sputtering target can significantly reduce the deposition on thruster surface. The back-sputtering deposition rates on thruster exit surface for different cases are compared. The chevrons on the secondary target are rearranged to improve its performance. The position of secondary target has relation with the ion beam divergence angle, and the radius of the vacuum chamber. The back-sputtering deposition rate is lower when the secondary target covers the entire ion beam.

Thermal lattice BGK models for fluid dynamics

NASA Astrophysics Data System (ADS)

Huang, Jian

1998-11-01

As an alternative in modeling fluid dynamics, the Lattice Boltzmann method has attracted considerable attention. In this thesis, we shall present a general form of thermal Lattice BGK. This form can handle large differences in density, temperature, and high Mach number. This generalized method can easily model gases with different adiabatic index values. The numerical transport coefficients of this model are estimated both theoretically and numerically. Their dependency on the sizes of integration steps in time and space, and on the flow velocity and temperature, are studied and compared with other established CFD methods. This study shows that the numerical viscosity of the Lattice Boltzmann method depends linearly on the space interval, and on the flow velocity as well for supersonic flow. This indicates this method's limitation in modeling high Reynolds number compressible thermal flow. On the other hand, the Lattice Boltzmann method shows promise in modeling micro-flows, i.e., gas flows in micron-sized devices. A two-dimensional code has been developed based on the conventional thermal lattice BGK model, with some modifications and extensions for micro- flows and wall-fluid interactions. Pressure-driven micro- channel flow has been simulated. Results are compared with experiments and simulations using other methods, such as a spectral element code using slip boundary condition with Navier-Stokes equations and a Direct Simulation Monte Carlo (DSMC) method.

DSMC computations of hypersonic flow separation and re-attachment in the transition to continuum regime

NASA Astrophysics Data System (ADS)

Prakash, Ram; Gai, Sudhir L.; O'Byrne, Sean; Brown, Melrose

2016-11-01

The flow over a `tick' shaped configuration is performed using two Direct Simulation Monte Carlo codes: the DS2V code of Bird and the code from Sandia National Laboratory, called SPARTA. The configuration creates a flow field, where the flow is expanded initially but then is affected by the adverse pressure gradient induced by a compression surface. The flow field is challenging in the sense that the full flow domain is comprised of localized areas spanning continuum and transitional regimes. The present work focuses on the capability of SPARTA to model such flow conditions and also towards a comparative evaluation with results from DS2V. An extensive grid adaptation study is performed using both the codes on a model with a sharp leading edge and the converged results are then compared. The computational predictions are evaluated in terms of surface parameters such as heat flux, shear stress, pressure and velocity slip. SPARTA consistently predicts higher values for these surface properties. The skin friction predictions of both the codes don't give any indication of separation but the velocity slip plots indicate an incipient separation behavior at the corner. The differences in the results are attributed towards the flow resolution at the leading edge that dictates the downstream flow characteristics.

Uncertainty quantification analysis of the dynamics of an electrostatically actuated microelectromechanical switch model

NASA Astrophysics Data System (ADS)

Snow, Michael G.; Bajaj, Anil K.

2015-08-01

This work presents an uncertainty quantification (UQ) analysis of a comprehensive model for an electrostatically actuated microelectromechanical system (MEMS) switch. The goal is to elucidate the effects of parameter variations on certain key performance characteristics of the switch. A sufficiently detailed model of the electrostatically actuated switch in the basic configuration of a clamped-clamped beam is developed. This multi-physics model accounts for various physical effects, including the electrostatic fringing field, finite length of electrodes, squeeze film damping, and contact between the beam and the dielectric layer. The performance characteristics of immediate interest are the static and dynamic pull-in voltages for the switch. Numerical approaches for evaluating these characteristics are developed and described. Using Latin Hypercube Sampling and other sampling methods, the model is evaluated to find these performance characteristics when variability in the model's geometric and physical parameters is specified. Response surfaces of these results are constructed via a Multivariate Adaptive Regression Splines (MARS) technique. Using a Direct Simulation Monte Carlo (DSMC) technique on these response surfaces gives smooth probability density functions (PDFs) of the outputs characteristics when input probability characteristics are specified. The relative variation in the two pull-in voltages due to each of the input parameters is used to determine the critical parameters.

A global reaction route mapping-based kinetic Monte Carlo algorithm

NASA Astrophysics Data System (ADS)

Mitchell, Izaac; Irle, Stephan; Page, Alister J.

2016-07-01

We propose a new on-the-fly kinetic Monte Carlo (KMC) method that is based on exhaustive potential energy surface searching carried out with the global reaction route mapping (GRRM) algorithm. Starting from any given equilibrium state, this GRRM-KMC algorithm performs a one-step GRRM search to identify all surrounding transition states. Intrinsic reaction coordinate pathways are then calculated to identify potential subsequent equilibrium states. Harmonic transition state theory is used to calculate rate constants for all potential pathways, before a standard KMC accept/reject selection is performed. The selected pathway is then used to propagate the system forward in time, which is calculated on the basis of 1st order kinetics. The GRRM-KMC algorithm is validated here in two challenging contexts: intramolecular proton transfer in malonaldehyde and surface carbon diffusion on an iron nanoparticle. We demonstrate that in both cases the GRRM-KMC method is capable of reproducing the 1st order kinetics observed during independent quantum chemical molecular dynamics simulations using the density-functional tight-binding potential.

Efficiency in nonequilibrium molecular dynamics Monte Carlo simulations

DOE PAGES

Radak, Brian K.; Roux, Benoît

2016-10-07

Hybrid algorithms combining nonequilibrium molecular dynamics and Monte Carlo (neMD/MC) offer a powerful avenue for improving the sampling efficiency of computer simulations of complex systems. These neMD/MC algorithms are also increasingly finding use in applications where conventional approaches are impractical, such as constant-pH simulations with explicit solvent. However, selecting an optimal nonequilibrium protocol for maximum efficiency often represents a non-trivial challenge. This work evaluates the efficiency of a broad class of neMD/MC algorithms and protocols within the theoretical framework of linear response theory. The approximations are validated against constant pH-MD simulations and shown to provide accurate predictions of neMD/MC performance.more » An assessment of a large set of protocols confirms (both theoretically and empirically) that a linear work protocol gives the best neMD/MC performance. Lastly, a well-defined criterion for optimizing the time parameters of the protocol is proposed and demonstrated with an adaptive algorithm that improves the performance on-the-fly with minimal cost.« less

A global reaction route mapping-based kinetic Monte Carlo algorithm.

PubMed

Mitchell, Izaac; Irle, Stephan; Page, Alister J

2016-07-14

We propose a new on-the-fly kinetic Monte Carlo (KMC) method that is based on exhaustive potential energy surface searching carried out with the global reaction route mapping (GRRM) algorithm. Starting from any given equilibrium state, this GRRM-KMC algorithm performs a one-step GRRM search to identify all surrounding transition states. Intrinsic reaction coordinate pathways are then calculated to identify potential subsequent equilibrium states. Harmonic transition state theory is used to calculate rate constants for all potential pathways, before a standard KMC accept/reject selection is performed. The selected pathway is then used to propagate the system forward in time, which is calculated on the basis of 1st order kinetics. The GRRM-KMC algorithm is validated here in two challenging contexts: intramolecular proton transfer in malonaldehyde and surface carbon diffusion on an iron nanoparticle. We demonstrate that in both cases the GRRM-KMC method is capable of reproducing the 1st order kinetics observed during independent quantum chemical molecular dynamics simulations using the density-functional tight-binding potential.

Application of genetic algorithms to focal mechanism determination

NASA Astrophysics Data System (ADS)

Kobayashi, Reiji; Nakanishi, Ichiro

1994-04-01

Genetic algorithms are a new class of methods for global optimization. They resemble Monte Carlo techniques, but search for solutions more efficiently than uniform Monte Carlo sampling. In the field of geophysics, genetic algorithms have recently been used to solve some non-linear inverse problems (e.g., earthquake location, waveform inversion, migration velocity estimation). We present an application of genetic algorithms to focal mechanism determination from first-motion polarities of P-waves and apply our method to two recent large events, the Kushiro-oki earthquake of January 15, 1993 and the SW Hokkaido (Japan Sea) earthquake of July 12, 1993. Initial solution and curvature information of the objective function that gradient methods need are not required in our approach. Moreover globally optimal solutions can be efficiently obtained. Calculation of polarities based on double-couple models is the most time-consuming part of the source mechanism determination. The amount of calculations required by the method designed in this study is much less than that of previous grid search methods.

SU-E-T-202: Impact of Monte Carlo Dose Calculation Algorithm On Prostate SBRT Treatments

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

Venencia, C; Garrigo, E; Cardenas, J

2014-06-01

Purpose: The purpose of this work was to quantify the dosimetric impact of using Monte Carlo algorithm on pre calculated SBRT prostate treatment with pencil beam dose calculation algorithm. Methods: A 6MV photon beam produced by a Novalis TX (BrainLAB-Varian) linear accelerator equipped with HDMLC was used. Treatment plans were done using 9 fields with Iplanv4.5 (BrainLAB) and dynamic IMRT modality. Institutional SBRT protocol uses a total dose to the prostate of 40Gy in 5 fractions, every other day. Dose calculation is done by pencil beam (2mm dose resolution), heterogeneity correction and dose volume constraint (UCLA) for PTV D95%=40Gy andmore » D98%>39.2Gy, Rectum V20Gy<50%, V32Gy<20%, V36Gy<10% and V40Gy<5%, Bladder V20Gy<40% and V40Gy<10%, femoral heads V16Gy<5%, penile bulb V25Gy<3cc, urethra and overlap region between PTV and PRV Rectum Dmax<42Gy. 10 SBRT treatments plans were selected and recalculated using Monte Carlo with 2mm spatial resolution and mean variance of 2%. DVH comparisons between plans were done. Results: The average difference between PTV doses constraints were within 2%. However 3 plans have differences higher than 3% which does not meet the D98% criteria (>39.2Gy) and should have been renormalized. Dose volume constraint differences for rectum, bladder, femoral heads and penile bulb were les than 2% and within tolerances. Urethra region and overlapping between PTV and PRV Rectum shows increment of dose in all plans. The average difference for urethra region was 2.1% with a maximum of 7.8% and for the overlapping region 2.5% with a maximum of 8.7%. Conclusion: Monte Carlo dose calculation on dynamic IMRT treatments could affects on plan normalization. Dose increment in critical region of urethra and PTV overlapping region with PTV could have clinical consequences which need to be studied. The use of Monte Carlo dose calculation algorithm is limited because inverse planning dose optimization use only pencil beam.« less

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.

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…

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.

Simulation and performance of an artificial retina for 40 MHz track reconstruction

DOE PAGES

Abba, A.; Bedeschi, F.; Citterio, M.; ...

2015-03-05

We present the results of a detailed simulation of the artificial retina pattern-recognition algorithm, designed to reconstruct events with hundreds of charged-particle tracks in pixel and silicon detectors at LHCb with LHC crossing frequency of 40 MHz. Performances of the artificial retina algorithm are assessed using the official Monte Carlo samples of the LHCb experiment. We found performances for the retina pattern-recognition algorithm comparable with the full LHCb reconstruction algorithm.

Testing algorithms for critical slowing down

NASA Astrophysics Data System (ADS)

Cossu, Guido; Boyle, Peter; Christ, Norman; Jung, Chulwoo; Jüttner, Andreas; Sanfilippo, Francesco

2018-03-01

We present the preliminary tests on two modifications of the Hybrid Monte Carlo (HMC) algorithm. Both algorithms are designed to travel much farther in the Hamiltonian phase space for each trajectory and reduce the autocorrelations among physical observables thus tackling the critical slowing down towards the continuum limit. We present a comparison of costs of the new algorithms with the standard HMC evolution for pure gauge fields, studying the autocorrelation times for various quantities including the topological charge.

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.

Improved algorithm for estimating optical properties of food and biological materials using spatially-resolved diffuse reflectance

USDA-ARS?s Scientific Manuscript database

In this research, the inverse algorithm for estimating optical properties of food and biological materials from spatially-resolved diffuse reflectance was optimized in terms of data smoothing, normalization and spatial region of reflectance profile for curve fitting. Monte Carlo simulation was used ...

RNA inverse folding using Monte Carlo tree search.

PubMed

Yang, Xiufeng; Yoshizoe, Kazuki; Taneda, Akito; Tsuda, Koji

2017-11-06

Artificially synthesized RNA molecules provide important ways for creating a variety of novel functional molecules. State-of-the-art RNA inverse folding algorithms can design simple and short RNA sequences of specific GC content, that fold into the target RNA structure. However, their performance is not satisfactory in complicated cases. We present a new inverse folding algorithm called MCTS-RNA, which uses Monte Carlo tree search (MCTS), a technique that has shown exceptional performance in Computer Go recently, to represent and discover the essential part of the sequence space. To obtain high accuracy, initial sequences generated by MCTS are further improved by a series of local updates. Our algorithm has an ability to control the GC content precisely and can deal with pseudoknot structures. Using common benchmark datasets for evaluation, MCTS-RNA showed a lot of promise as a standard method of RNA inverse folding. MCTS-RNA is available at https://github.com/tsudalab/MCTS-RNA .

Modified Monte Carlo method for study of electron transport in degenerate electron gas in the presence of electron-electron interactions, application to graphene

NASA Astrophysics Data System (ADS)

Borowik, Piotr; Thobel, Jean-Luc; Adamowicz, Leszek

2017-07-01

Standard computational methods used to take account of the Pauli Exclusion Principle into Monte Carlo (MC) simulations of electron transport in semiconductors may give unphysical results in low field regime, where obtained electron distribution function takes values exceeding unity. Modified algorithms were already proposed and allow to correctly account for electron scattering on phonons or impurities. Present paper extends this approach and proposes improved simulation scheme allowing including Pauli exclusion principle for electron-electron (e-e) scattering into MC simulations. Simulations with significantly reduced computational cost recreate correct values of the electron distribution function. Proposed algorithm is applied to study transport properties of degenerate electrons in graphene with e-e interactions. This required adapting the treatment of e-e scattering in the case of linear band dispersion relation. Hence, this part of the simulation algorithm is described in details.

ALGEBRA: ALgorithm for the heterogeneous dosimetry based on GEANT4 for BRAchytherapy.

PubMed

Afsharpour, H; Landry, G; D'Amours, M; Enger, S; Reniers, B; Poon, E; Carrier, J-F; Verhaegen, F; Beaulieu, L

2012-06-07

Task group 43 (TG43)-based dosimetry algorithms are efficient for brachytherapy dose calculation in water. However, human tissues have chemical compositions and densities different than water. Moreover, the mutual shielding effect of seeds on each other (interseed attenuation) is neglected in the TG43-based dosimetry platforms. The scientific community has expressed the need for an accurate dosimetry platform in brachytherapy. The purpose of this paper is to present ALGEBRA, a Monte Carlo platform for dosimetry in brachytherapy which is sufficiently fast and accurate for clinical and research purposes. ALGEBRA is based on the GEANT4 Monte Carlo code and is capable of handling the DICOM RT standard to recreate a virtual model of the treated site. Here, the performance of ALGEBRA is presented for the special case of LDR brachytherapy in permanent prostate and breast seed implants. However, the algorithm is also capable of handling other treatments such as HDR brachytherapy.

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.

A Comparison of Experimental EPMA Data and Monte Carlo Simulations

NASA Technical Reports Server (NTRS)

Carpenter, P. K.

2004-01-01

Monte Carlo (MC) modeling shows excellent prospects for simulating electron scattering and x-ray emission from complex geometries, and can be compared to experimental measurements using electron-probe microanalysis (EPMA) and phi(rho z) correction algorithms. Experimental EPMA measurements made on NIST SRM 481 (AgAu) and 482 (CuAu) alloys, at a range of accelerating potential and instrument take-off angles, represent a formal microanalysis data set that has been used to develop phi(rho z) correction algorithms. The accuracy of MC calculations obtained using the NIST, WinCasino, WinXray, and Penelope MC packages will be evaluated relative to these experimental data. There is additional information contained in the extended abstract.

Rényi information flow in the Ising model with single-spin dynamics.

PubMed

Deng, Zehui; Wu, Jinshan; Guo, Wenan

2014-12-01

The n-index Rényi mutual information and transfer entropies for the two-dimensional kinetic Ising model with arbitrary single-spin dynamics in the thermodynamic limit are derived as functions of ensemble averages of observables and spin-flip probabilities. Cluster Monte Carlo algorithms with different dynamics from the single-spin dynamics are thus applicable to estimate the transfer entropies. By means of Monte Carlo simulations with the Wolff algorithm, we calculate the information flows in the Ising model with the Metropolis dynamics and the Glauber dynamics, respectively. We find that not only the global Rényi transfer entropy, but also the pairwise Rényi transfer entropy, peaks in the disorder phase.

A hybrid multi-objective imperialist competitive algorithm and Monte Carlo method for robust safety design of a rail vehicle

NASA Astrophysics Data System (ADS)

Nejlaoui, Mohamed; Houidi, Ajmi; Affi, Zouhaier; Romdhane, Lotfi

2017-10-01

This paper deals with the robust safety design optimization of a rail vehicle system moving in short radius curved tracks. A combined multi-objective imperialist competitive algorithm and Monte Carlo method is developed and used for the robust multi-objective optimization of the rail vehicle system. This robust optimization of rail vehicle safety considers simultaneously the derailment angle and its standard deviation where the design parameters uncertainties are considered. The obtained results showed that the robust design reduces significantly the sensitivity of the rail vehicle safety to the design parameters uncertainties compared to the determinist one and to the literature results.

Tracking control of concentration profiles in a fed-batch bioreactor using a linear algebra methodology.

PubMed

Rómoli, Santiago; Serrano, Mario Emanuel; Ortiz, Oscar Alberto; Vega, Jorge Rubén; Eduardo Scaglia, Gustavo Juan

2015-07-01

Based on a linear algebra approach, this paper aims at developing a novel control law able to track reference profiles that were previously-determined in the literature. A main advantage of the proposed strategy is that the control actions are obtained by solving a system of linear equations. The optimal controller parameters are selected through Monte Carlo Randomized Algorithm in order to minimize a proposed cost index. The controller performance is evaluated through several tests, and compared with other controller reported in the literature. Finally, a Monte Carlo Randomized Algorithm is conducted to assess the performance of the proposed controller. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Improved Monte Carlo Scheme for Efficient Particle Transfer in Heterogeneous Systems in the Grand Canonical Ensemble: Application to Vapor-Liquid Nucleation.

PubMed

Loeffler, Troy D; Sepehri, Aliasghar; Chen, Bin

2015-09-08

Reformulation of existing Monte Carlo algorithms used in the study of grand canonical systems has yielded massive improvements in efficiency. Here we present an energy biasing scheme designed to address targeting issues encountered in particle swap moves using sophisticated algorithms such as the Aggregation-Volume-Bias and Unbonding-Bonding methods. Specifically, this energy biasing scheme allows a particle to be inserted to (or removed from) a region that is more acceptable. As a result, this new method showed a several-fold increase in insertion/removal efficiency in addition to an accelerated rate of convergence for the thermodynamic properties of the system.

Poster — Thur Eve — 14: Improving Tissue Segmentation for Monte Carlo Dose Calculation using DECT

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

Di Salvio, A.; Bedwani, S.; Carrier, J-F.

2014-08-15

Purpose: To improve Monte Carlo dose calculation accuracy through a new tissue segmentation technique with dual energy CT (DECT). Methods: Electron density (ED) and effective atomic number (EAN) can be extracted directly from DECT data with a stoichiometric calibration method. Images are acquired with Monte Carlo CT projections using the user code egs-cbct and reconstructed using an FDK backprojection algorithm. Calibration is performed using projections of a numerical RMI phantom. A weighted parameter algorithm then uses both EAN and ED to assign materials to voxels from DECT simulated images. This new method is compared to a standard tissue characterization frommore » single energy CT (SECT) data using a segmented calibrated Hounsfield unit (HU) to ED curve. Both methods are compared to the reference numerical head phantom. Monte Carlo simulations on uniform phantoms of different tissues using dosxyz-nrc show discrepancies in depth-dose distributions. Results: Both SECT and DECT segmentation methods show similar performance assigning soft tissues. Performance is however improved with DECT in regions with higher density, such as bones, where it assigns materials correctly 8% more often than segmentation with SECT, considering the same set of tissues and simulated clinical CT images, i.e. including noise and reconstruction artifacts. Furthermore, Monte Carlo results indicate that kV photon beam depth-dose distributions can double between two tissues of density higher than muscle. Conclusions: A direct acquisition of ED and the added information of EAN with DECT data improves tissue segmentation and increases the accuracy of Monte Carlo dose calculation in kV photon beams.« less

Performances of the New Real Time Tsunami Detection Algorithm applied to tide gauges data

NASA Astrophysics Data System (ADS)

Chierici, F.; Embriaco, D.; Morucci, S.

2017-12-01

Real-time tsunami detection algorithms play a key role in any Tsunami Early Warning System. We have developed a new algorithm for tsunami detection (TDA) based on the real-time tide removal and real-time band-pass filtering of seabed pressure time series acquired by Bottom Pressure Recorders. The TDA algorithm greatly increases the tsunami detection probability, shortens the detection delay and enhances detection reliability with respect to the most widely used tsunami detection algorithm, while containing the computational cost. The algorithm is designed to be used also in autonomous early warning systems with a set of input parameters and procedures which can be reconfigured in real time. We have also developed a methodology based on Monte Carlo simulations to test the tsunami detection algorithms. The algorithm performance is estimated by defining and evaluating statistical parameters, namely the detection probability, the detection delay, which are functions of the tsunami amplitude and wavelength, and the occurring rate of false alarms. In this work we present the performance of the TDA algorithm applied to tide gauge data. We have adapted the new tsunami detection algorithm and the Monte Carlo test methodology to tide gauges. Sea level data acquired by coastal tide gauges in different locations and environmental conditions have been used in order to consider real working scenarios in the test. We also present an application of the algorithm to the tsunami event generated by Tohoku earthquake on March 11th 2011, using data recorded by several tide gauges scattered all over the Pacific area.

Assessing the performance of a covert automatic target recognition algorithm

NASA Astrophysics Data System (ADS)

Ehrman, Lisa M.; Lanterman, Aaron D.

2005-05-01

Passive radar systems exploit illuminators of opportunity, such as TV and FM radio, to illuminate potential targets. Doing so allows them to operate covertly and inexpensively. Our research seeks to enhance passive radar systems by adding automatic target recognition (ATR) capabilities. In previous papers we proposed conducting ATR by comparing the radar cross section (RCS) of aircraft detected by a passive radar system to the precomputed RCS of aircraft in the target class. To effectively model the low-frequency setting, the comparison is made via a Rician likelihood model. Monte Carlo simulations indicate that the approach is viable. This paper builds on that work by developing a method for quickly assessing the potential performance of the ATR algorithm without using exhaustive Monte Carlo trials. This method exploits the relation between the probability of error in a binary hypothesis test under the Bayesian framework to the Chernoff information. Since the data are well-modeled as Rician, we begin by deriving a closed-form approximation for the Chernoff information between two Rician densities. This leads to an approximation for the probability of error in the classification algorithm that is a function of the number of available measurements. We conclude with an application that would be particularly cumbersome to accomplish via Monte Carlo trials, but that can be quickly addressed using the Chernoff information approach. This application evaluates the length of time that an aircraft must be tracked before the probability of error in the ATR algorithm drops below a desired threshold.

Subtle Monte Carlo Updates in Dense Molecular Systems.

PubMed

Bottaro, Sandro; Boomsma, Wouter; E Johansson, Kristoffer; Andreetta, Christian; Hamelryck, Thomas; Ferkinghoff-Borg, Jesper

2012-02-14

Although Markov chain Monte Carlo (MC) simulation is a potentially powerful approach for exploring conformational space, it has been unable to compete with molecular dynamics (MD) in the analysis of high density structural states, such as the native state of globular proteins. Here, we introduce a kinetic algorithm, CRISP, that greatly enhances the sampling efficiency in all-atom MC simulations of dense systems. The algorithm is based on an exact analytical solution to the classic chain-closure problem, making it possible to express the interdependencies among degrees of freedom in the molecule as correlations in a multivariate Gaussian distribution. We demonstrate that our method reproduces structural variation in proteins with greater efficiency than current state-of-the-art Monte Carlo methods and has real-time simulation performance on par with molecular dynamics simulations. The presented results suggest our method as a valuable tool in the study of molecules in atomic detail, offering a potential alternative to molecular dynamics for probing long time-scale conformational transitions.

Monte Carlo simulations in X-ray imaging

NASA Astrophysics Data System (ADS)

Giersch, Jürgen; Durst, Jürgen

2008-06-01

Monte Carlo simulations have become crucial tools in many fields of X-ray imaging. They help to understand the influence of physical effects such as absorption, scattering and fluorescence of photons in different detector materials on image quality parameters. They allow studying new imaging concepts like photon counting, energy weighting or material reconstruction. Additionally, they can be applied to the fields of nuclear medicine to define virtual setups studying new geometries or image reconstruction algorithms. Furthermore, an implementation of the propagation physics of electrons and photons allows studying the behavior of (novel) X-ray generation concepts. This versatility of Monte Carlo simulations is illustrated with some examples done by the Monte Carlo simulation ROSI. An overview of the structure of ROSI is given as an example of a modern, well-proven, object-oriented, parallel computing Monte Carlo simulation for X-ray imaging.

Loading relativistic Maxwell distributions in particle simulations

NASA Astrophysics Data System (ADS)

Zenitani, Seiji

2015-04-01

Numerical algorithms to load relativistic Maxwell distributions in particle-in-cell (PIC) and Monte-Carlo simulations are presented. For stationary relativistic Maxwellian, the inverse transform method and the Sobol algorithm are reviewed. To boost particles to obtain relativistic shifted-Maxwellian, two rejection methods are proposed in a physically transparent manner. Their acceptance efficiencies are ≈50 % for generic cases and 100% for symmetric distributions. They can be combined with arbitrary base algorithms.

Polynomial complexity despite the fermionic sign

NASA Astrophysics Data System (ADS)

Rossi, R.; Prokof'ev, N.; Svistunov, B.; Van Houcke, K.; Werner, F.

2017-04-01

It is commonly believed that in unbiased quantum Monte Carlo approaches to fermionic many-body problems, the infamous sign problem generically implies prohibitively large computational times for obtaining thermodynamic-limit quantities. We point out that for convergent Feynman diagrammatic series evaluated with a recently introduced Monte Carlo algorithm (see Rossi R., arXiv:1612.05184), the computational time increases only polynomially with the inverse error on thermodynamic-limit quantities.

Effective Online Bayesian Phylogenetics via Sequential Monte Carlo with Guided Proposals

PubMed Central

Fourment, Mathieu; Claywell, Brian C; Dinh, Vu; McCoy, Connor; Matsen IV, Frederick A; Darling, Aaron E

2018-01-01

Abstract Modern infectious disease outbreak surveillance produces continuous streams of sequence data which require phylogenetic analysis as data arrives. Current software packages for Bayesian phylogenetic inference are unable to quickly incorporate new sequences as they become available, making them less useful for dynamically unfolding evolutionary stories. This limitation can be addressed by applying a class of Bayesian statistical inference algorithms called sequential Monte Carlo (SMC) to conduct online inference, wherein new data can be continuously incorporated to update the estimate of the posterior probability distribution. In this article, we describe and evaluate several different online phylogenetic sequential Monte Carlo (OPSMC) algorithms. We show that proposing new phylogenies with a density similar to the Bayesian prior suffers from poor performance, and we develop “guided” proposals that better match the proposal density to the posterior. Furthermore, we show that the simplest guided proposals can exhibit pathological behavior in some situations, leading to poor results, and that the situation can be resolved by heating the proposal density. The results demonstrate that relative to the widely used MCMC-based algorithm implemented in MrBayes, the total time required to compute a series of phylogenetic posteriors as sequences arrive can be significantly reduced by the use of OPSMC, without incurring a significant loss in accuracy. PMID:29186587

An evaluation of solution algorithms and numerical approximation methods for modeling an ion exchange process

NASA Astrophysics Data System (ADS)

Bu, Sunyoung; Huang, Jingfang; Boyer, Treavor H.; Miller, Cass T.

2010-07-01

The focus of this work is on the modeling of an ion exchange process that occurs in drinking water treatment applications. The model formulation consists of a two-scale model in which a set of microscale diffusion equations representing ion exchange resin particles that vary in size and age are coupled through a boundary condition with a macroscopic ordinary differential equation (ODE), which represents the concentration of a species in a well-mixed reactor. We introduce a new age-averaged model (AAM) that averages all ion exchange particle ages for a given size particle to avoid the expensive Monte-Carlo simulation associated with previous modeling applications. We discuss two different numerical schemes to approximate both the original Monte-Carlo algorithm and the new AAM for this two-scale problem. The first scheme is based on the finite element formulation in space coupled with an existing backward difference formula-based ODE solver in time. The second scheme uses an integral equation based Krylov deferred correction (KDC) method and a fast elliptic solver (FES) for the resulting elliptic equations. Numerical results are presented to validate the new AAM algorithm, which is also shown to be more computationally efficient than the original Monte-Carlo algorithm. We also demonstrate that the higher order KDC scheme is more efficient than the traditional finite element solution approach and this advantage becomes increasingly important as the desired accuracy of the solution increases. We also discuss issues of smoothness, which affect the efficiency of the KDC-FES approach, and outline additional algorithmic changes that would further improve the efficiency of these developing methods for a wide range of applications.

SU-F-SPS-11: The Dosimetric Comparison of Truebeam 2.0 and Cyberknife M6 Treatment Plans for Brain SRS Treatment

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

Mabhouti, H; Sanli, E; Cebe, M

Purpose: Brain stereotactic radiosurgery involves the use of precisely directed, single session radiation to create a desired radiobiologic response within the brain target with acceptable minimal effects on surrounding structures or tissues. In this study, the dosimetric comparison of Truebeam 2.0 and Cyberknife M6 treatment plans were made. Methods: For Truebeam 2.0 machine, treatment planning were done using 2 full arc VMAT technique with 6 FFF beam on the CT scan of Randophantom simulating the treatment of sterotactic treatments for one brain metastasis. The dose distribution were calculated using Eclipse treatment planning system with Acuros XB algorithm. The treatment planningmore » of the same target were also done for Cyberknife M6 machine with Multiplan treatment planning system using Monte Carlo algorithm. Using the same film batch, the net OD to dose calibration curve was obtained using both machine by delivering 0- 800 cGy. Films were scanned 48 hours after irradiation using an Epson 1000XL flatbed scanner. Dose distribution were measured using EBT3 film dosimeter. The measured and calculated doses were compared. Results: The dose distribution in the target and 2 cm beyond the target edge were calculated on TPSs and measured using EBT3 film. For cyberknife plans, the gamma analysis passing rates between measured and calculated dose distributions were 99.2% and 96.7% for target and peripheral region of target respectively. For Truebeam plans, the gamma analysis passing rates were 99.1% and 95.5% for target and peripheral region of target respectively. Conclusion: Although, target dose distribution calculated accurately by Acuros XB and Monte Carlo algorithms, Monte carlo calculation algorithm predicts dose distribution around the peripheral region of target more accurately than Acuros algorithm.« less

The kinetic activation-relaxation technique: an off-lattice, self-learning kinetic Monte Carlo algorithm with on-the-fly event search

NASA Astrophysics Data System (ADS)

Mousseau, Nomand

2012-02-01

While kinetic Monte Carlo algorithm has been proposed almost 40 years ago, its application in materials science has been mostly limited to lattice-based motion due to the difficulties associated with identifying new events and building usable catalogs when atoms moved into off-lattice position. Here, I present the kinetic activation-relaxation technique (kinetic ART) is an off-lattice, self-learning kinetic Monte Carlo algorithm with on-the-fly event search [1]. It combines ART nouveau [2], a very efficient unbiased open-ended activated method for finding transition states, with a topological classification [3] that allows a discrete cataloguing of local environments in complex systems, including disordered materials. In kinetic ART, local topologies are first identified for all atoms in a system. ART nouveau event searches are then launched for new topologies, building an extensive catalog of barriers and events. Next, all low energy events are fully reconstructed and relaxed, allowing to take complete account of elastic effects in the system's kinetics. Using standard kinetic Monte Carlo, the clock is brought forward and an event is then selected and applied before a new search for topologies is launched. In addition to presenting the various elements of the algorithm, I will discuss three recent applications to ion-bombarded silicon, defect diffusion in Fe and structural relaxation in amorphous silicon.[4pt] This work was done in collaboration with Laurent Karim B'eland, Peter Brommer, Fedwa El-Mellouhi, Jean-Francois Joly and Laurent Lewis.[4pt] [1] F. El-Mellouhi, N. Mousseau and L.J. Lewis, Phys. Rev. B. 78, 153202 (2008); L.K. B'eland et al., Phys. Rev. E 84, 046704 (2011).[2] G.T. Barkema and N. Mousseau, Phys. Rev. Lett. 77, 4358 (1996); E. Machado-Charry et al., J. Chem Phys. 135, 034102, (2011).[3] B.D. McKay, Congressus Numerantium 30, 45 (1981).

Effective optimization using sample persistence: A case study on quantum annealers and various Monte Carlo optimization methods

NASA Astrophysics Data System (ADS)

Karimi, Hamed; Rosenberg, Gili; Katzgraber, Helmut G.

2017-10-01

We present and apply a general-purpose, multistart algorithm for improving the performance of low-energy samplers used for solving optimization problems. The algorithm iteratively fixes the value of a large portion of the variables to values that have a high probability of being optimal. The resulting problems are smaller and less connected, and samplers tend to give better low-energy samples for these problems. The algorithm is trivially parallelizable since each start in the multistart algorithm is independent, and could be applied to any heuristic solver that can be run multiple times to give a sample. We present results for several classes of hard problems solved using simulated annealing, path-integral quantum Monte Carlo, parallel tempering with isoenergetic cluster moves, and a quantum annealer, and show that the success metrics and the scaling are improved substantially. When combined with this algorithm, the quantum annealer's scaling was substantially improved for native Chimera graph problems. In addition, with this algorithm the scaling of the time to solution of the quantum annealer is comparable to the Hamze-de Freitas-Selby algorithm on the weak-strong cluster problems introduced by Boixo et al. Parallel tempering with isoenergetic cluster moves was able to consistently solve three-dimensional spin glass problems with 8000 variables when combined with our method, whereas without our method it could not solve any.

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.

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.

Limited Memory Block Krylov Subspace Optimization for Computing Dominant Singular Value Decompositions

DTIC Science & Technology

2012-03-22

with performance profiles, Math. Program., 91 (2002), pp. 201–213. [6] P. DRINEAS, R. KANNAN, AND M. W. MAHONEY , Fast Monte Carlo algorithms for matrices...computing invariant subspaces of non-Hermitian matri- ces, Numer. Math., 25 ( 1975 /76), pp. 123–136. [25] , Matrix algorithms Vol. II: Eigensystems

Using Computer-Based "Experiments" in the Analysis of Chemical Reaction Equilibria

ERIC Educational Resources Information Center

Li, Zhao; Corti, David S.

2018-01-01

The application of the Reaction Monte Carlo (RxMC) algorithm to standard textbook problems in chemical reaction equilibria is discussed. The RxMC method is a molecular simulation algorithm for studying the equilibrium properties of reactive systems, and therefore provides the opportunity to develop computer-based "experiments" for the…

“Skin-Core-Skin” Structure of Polymer Crystallization Investigated by Multiscale Simulation

PubMed Central

Ruan, Chunlei

2018-01-01

“Skin-core-skin” structure is a typical crystal morphology in injection products. Previous numerical works have rarely focused on crystal evolution; rather, they have mostly been based on the prediction of temperature distribution or crystallization kinetics. The aim of this work was to achieve the “skin-core-skin” structure and investigate the role of external flow and temperature fields on crystal morphology. Therefore, the multiscale algorithm was extended to the simulation of polymer crystallization in a pipe flow. The multiscale algorithm contains two parts: a collocated finite volume method at the macroscopic level and a morphological Monte Carlo method at the microscopic level. The SIMPLE (semi-implicit method for pressure linked equations) algorithm was used to calculate the polymeric model at the macroscopic level, while the Monte Carlo method with stochastic birth-growth process of spherulites and shish-kebabs was used at the microscopic level. Results show that our algorithm is valid to predict “skin-core-skin” structure, and the initial melt temperature and the maximum velocity of melt at the inlet mainly affects the morphology of shish-kebabs. PMID:29659516

A derivation and scalable implementation of the synchronous parallel kinetic Monte Carlo method for simulating long-time dynamics

NASA Astrophysics Data System (ADS)

Byun, Hye Suk; El-Naggar, Mohamed Y.; Kalia, Rajiv K.; Nakano, Aiichiro; Vashishta, Priya

2017-10-01

Kinetic Monte Carlo (KMC) simulations are used to study long-time dynamics of a wide variety of systems. Unfortunately, the conventional KMC algorithm is not scalable to larger systems, since its time scale is inversely proportional to the simulated system size. A promising approach to resolving this issue is the synchronous parallel KMC (SPKMC) algorithm, which makes the time scale size-independent. This paper introduces a formal derivation of the SPKMC algorithm based on local transition-state and time-dependent Hartree approximations, as well as its scalable parallel implementation based on a dual linked-list cell method. The resulting algorithm has achieved a weak-scaling parallel efficiency of 0.935 on 1024 Intel Xeon processors for simulating biological electron transfer dynamics in a 4.2 billion-heme system, as well as decent strong-scaling parallel efficiency. The parallel code has been used to simulate a lattice of cytochrome complexes on a bacterial-membrane nanowire, and it is broadly applicable to other problems such as computational synthesis of new materials.

A global reaction route mapping-based kinetic Monte Carlo algorithm

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

Mitchell, Izaac; Page, Alister J., E-mail: sirle@chem.nagoya-u.ac.jp, E-mail: alister.page@newcastle.edu.au; Irle, Stephan, E-mail: sirle@chem.nagoya-u.ac.jp, E-mail: alister.page@newcastle.edu.au

2016-07-14

We propose a new on-the-fly kinetic Monte Carlo (KMC) method that is based on exhaustive potential energy surface searching carried out with the global reaction route mapping (GRRM) algorithm. Starting from any given equilibrium state, this GRRM-KMC algorithm performs a one-step GRRM search to identify all surrounding transition states. Intrinsic reaction coordinate pathways are then calculated to identify potential subsequent equilibrium states. Harmonic transition state theory is used to calculate rate constants for all potential pathways, before a standard KMC accept/reject selection is performed. The selected pathway is then used to propagate the system forward in time, which is calculatedmore » on the basis of 1st order kinetics. The GRRM-KMC algorithm is validated here in two challenging contexts: intramolecular proton transfer in malonaldehyde and surface carbon diffusion on an iron nanoparticle. We demonstrate that in both cases the GRRM-KMC method is capable of reproducing the 1st order kinetics observed during independent quantum chemical molecular dynamics simulations using the density-functional tight-binding potential.« less

Numerical heating in Particle-In-Cell simulations with Monte Carlo binary collisions

NASA Astrophysics Data System (ADS)

Alves, E. Paulo; Mori, Warren; Fiuza, Frederico

2017-10-01

The binary Monte Carlo collision (BMCC) algorithm is a robust and popular method to include Coulomb collision effects in Particle-in-Cell (PIC) simulations of plasmas. While a number of works have focused on extending the validity of the model to different physical regimes of temperature and density, little attention has been given to the fundamental coupling between PIC and BMCC algorithms. Here, we show that the coupling between PIC and BMCC algorithms can give rise to (nonphysical) numerical heating of the system, that can be far greater than that observed when these algorithms operate independently. This deleterious numerical heating effect can significantly impact the evolution of the simulated system particularly for long simulation times. In this work, we describe the source of this numerical heating, and derive scaling laws for the numerical heating rates based on the numerical parameters of PIC-BMCC simulations. We compare our theoretical scalings with PIC-BMCC numerical experiments, and discuss strategies to minimize this parasitic effect. This work is supported by DOE FES under FWP 100237 and 100182.

A Bootstrap Metropolis-Hastings Algorithm for Bayesian Analysis of Big Data.

PubMed

Liang, Faming; Kim, Jinsu; Song, Qifan

2016-01-01

Markov chain Monte Carlo (MCMC) methods have proven to be a very powerful tool for analyzing data of complex structures. However, their computer-intensive nature, which typically require a large number of iterations and a complete scan of the full dataset for each iteration, precludes their use for big data analysis. In this paper, we propose the so-called bootstrap Metropolis-Hastings (BMH) algorithm, which provides a general framework for how to tame powerful MCMC methods to be used for big data analysis; that is to replace the full data log-likelihood by a Monte Carlo average of the log-likelihoods that are calculated in parallel from multiple bootstrap samples. The BMH algorithm possesses an embarrassingly parallel structure and avoids repeated scans of the full dataset in iterations, and is thus feasible for big data problems. Compared to the popular divide-and-combine method, BMH can be generally more efficient as it can asymptotically integrate the whole data information into a single simulation run. The BMH algorithm is very flexible. Like the Metropolis-Hastings algorithm, it can serve as a basic building block for developing advanced MCMC algorithms that are feasible for big data problems. This is illustrated in the paper by the tempering BMH algorithm, which can be viewed as a combination of parallel tempering and the BMH algorithm. BMH can also be used for model selection and optimization by combining with reversible jump MCMC and simulated annealing, respectively.

A Bootstrap Metropolis–Hastings Algorithm for Bayesian Analysis of Big Data

PubMed Central

Kim, Jinsu; Song, Qifan

2016-01-01

Markov chain Monte Carlo (MCMC) methods have proven to be a very powerful tool for analyzing data of complex structures. However, their computer-intensive nature, which typically require a large number of iterations and a complete scan of the full dataset for each iteration, precludes their use for big data analysis. In this paper, we propose the so-called bootstrap Metropolis-Hastings (BMH) algorithm, which provides a general framework for how to tame powerful MCMC methods to be used for big data analysis; that is to replace the full data log-likelihood by a Monte Carlo average of the log-likelihoods that are calculated in parallel from multiple bootstrap samples. The BMH algorithm possesses an embarrassingly parallel structure and avoids repeated scans of the full dataset in iterations, and is thus feasible for big data problems. Compared to the popular divide-and-combine method, BMH can be generally more efficient as it can asymptotically integrate the whole data information into a single simulation run. The BMH algorithm is very flexible. Like the Metropolis-Hastings algorithm, it can serve as a basic building block for developing advanced MCMC algorithms that are feasible for big data problems. This is illustrated in the paper by the tempering BMH algorithm, which can be viewed as a combination of parallel tempering and the BMH algorithm. BMH can also be used for model selection and optimization by combining with reversible jump MCMC and simulated annealing, respectively. PMID:29033469

TH-E-BRE-07: Development of Dose Calculation Error Predictors for a Widely Implemented Clinical Algorithm

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

Egan, A; Laub, W

2014-06-15

Purpose: Several shortcomings of the current implementation of the analytic anisotropic algorithm (AAA) may lead to dose calculation errors in highly modulated treatments delivered to highly heterogeneous geometries. Here we introduce a set of dosimetric error predictors that can be applied to a clinical treatment plan and patient geometry in order to identify high risk plans. Once a problematic plan is identified, the treatment can be recalculated with more accurate algorithm in order to better assess its viability. Methods: Here we focus on three distinct sources dosimetric error in the AAA algorithm. First, due to a combination of discrepancies inmore » smallfield beam modeling as well as volume averaging effects, dose calculated through small MLC apertures can be underestimated, while that behind small MLC blocks can overestimated. Second, due the rectilinear scaling of the Monte Carlo generated pencil beam kernel, energy is not properly transported through heterogeneities near, but not impeding, the central axis of the beamlet. And third, AAA overestimates dose in regions very low density (< 0.2 g/cm{sup 3}). We have developed an algorithm to detect the location and magnitude of each scenario within the patient geometry, namely the field-size index (FSI), the heterogeneous scatter index (HSI), and the lowdensity index (LDI) respectively. Results: Error indices successfully identify deviations between AAA and Monte Carlo dose distributions in simple phantom geometries. Algorithms are currently implemented in the MATLAB computing environment and are able to run on a typical RapidArc head and neck geometry in less than an hour. Conclusion: Because these error indices successfully identify each type of error in contrived cases, with sufficient benchmarking, this method can be developed into a clinical tool that may be able to help estimate AAA dose calculation errors and when it might be advisable to use Monte Carlo calculations.« less

Identification of moisture content in tobacco plant leaves using outlier sample eliminating algorithms and hyperspectral data.

PubMed

Sun, Jun; Zhou, Xin; Wu, Xiaohong; Zhang, Xiaodong; Li, Qinglin

2016-02-26

Fast identification of moisture content in tobacco plant leaves plays a key role in the tobacco cultivation industry and benefits the management of tobacco plant in the farm. In order to identify moisture content of tobacco plant leaves in a fast and nondestructive way, a method involving Mahalanobis distance coupled with Monte Carlo cross validation(MD-MCCV) was proposed to eliminate outlier sample in this study. The hyperspectral data of 200 tobacco plant leaf samples of 20 moisture gradients were obtained using FieldSpc(®) 3 spectrometer. Savitzky-Golay smoothing(SG), roughness penalty smoothing(RPS), kernel smoothing(KS) and median smoothing(MS) were used to preprocess the raw spectra. In addition, Mahalanobis distance(MD), Monte Carlo cross validation(MCCV) and Mahalanobis distance coupled to Monte Carlo cross validation(MD-MCCV) were applied to select the outlier sample of the raw spectrum and four smoothing preprocessing spectra. Successive projections algorithm (SPA) was used to extract the most influential wavelengths. Multiple Linear Regression (MLR) was applied to build the prediction models based on preprocessed spectra feature in characteristic wavelengths. The results showed that the preferably four prediction model were MD-MCCV-SG (Rp(2) = 0.8401 and RMSEP = 0.1355), MD-MCCV-RPS (Rp(2) = 0.8030 and RMSEP = 0.1274), MD-MCCV-KS (Rp(2) = 0.8117 and RMSEP = 0.1433), MD-MCCV-MS (Rp(2) = 0.9132 and RMSEP = 0.1162). MD-MCCV algorithm performed best among MD algorithm, MCCV algorithm and the method without sample pretreatment algorithm in the eliminating outlier sample from 20 different moisture gradients of tobacco plant leaves and MD-MCCV can be used to eliminate outlier sample in the spectral preprocessing. Copyright © 2016 Elsevier Inc. All rights reserved.

Monte Carlo algorithms for Brownian phylogenetic models.

PubMed

Horvilleur, Benjamin; Lartillot, Nicolas

2014-11-01

Brownian models have been introduced in phylogenetics for describing variation in substitution rates through time, with applications to molecular dating or to the comparative analysis of variation in substitution patterns among lineages. Thus far, however, the Monte Carlo implementations of these models have relied on crude approximations, in which the Brownian process is sampled only at the internal nodes of the phylogeny or at the midpoints along each branch, and the unknown trajectory between these sampled points is summarized by simple branchwise average substitution rates. A more accurate Monte Carlo approach is introduced, explicitly sampling a fine-grained discretization of the trajectory of the (potentially multivariate) Brownian process along the phylogeny. Generic Monte Carlo resampling algorithms are proposed for updating the Brownian paths along and across branches. Specific computational strategies are developed for efficient integration of the finite-time substitution probabilities across branches induced by the Brownian trajectory. The mixing properties and the computational complexity of the resulting Markov chain Monte Carlo sampler scale reasonably with the discretization level, allowing practical applications with up to a few hundred discretization points along the entire depth of the tree. The method can be generalized to other Markovian stochastic processes, making it possible to implement a wide range of time-dependent substitution models with well-controlled computational precision. The program is freely available at www.phylobayes.org. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

International Conference on Artificial Immune Systems (1st) ICARIS 2002, held on 9, 10, and 11 September 2002

DTIC Science & Technology

2002-03-07

Michalewicz, Eds., Evolutionary Computation 1: Basic Algorithms and Operators, Institute of Physics, Bristol (UK), 2000. [3] David A. Van Veldhuizen ...2000. [4] Carlos A. Coello Coello, David A. Van Veldhuizen , and Gary B. Lamont, Evolutionary Algorithms for Solving Multi-Objective Problems, Kluwer...Academic Publishers, 233 Spring St., New York, NY 10013, 2002. [5] David A. Van Veldhuizen , Multiobjective Evolution- ary Algorithms: Classifications

Improving multivariate Horner schemes with Monte Carlo tree search

NASA Astrophysics Data System (ADS)

Kuipers, J.; Plaat, A.; Vermaseren, J. A. M.; van den Herik, H. J.

2013-11-01

Optimizing the cost of evaluating a polynomial is a classic problem in computer science. For polynomials in one variable, Horner's method provides a scheme for producing a computationally efficient form. For multivariate polynomials it is possible to generalize Horner's method, but this leaves freedom in the order of the variables. Traditionally, greedy schemes like most-occurring variable first are used. This simple textbook algorithm has given remarkably efficient results. Finding better algorithms has proved difficult. In trying to improve upon the greedy scheme we have implemented Monte Carlo tree search, a recent search method from the field of artificial intelligence. This results in better Horner schemes and reduces the cost of evaluating polynomials, sometimes by factors up to two.

Self-learning Monte Carlo method and cumulative update in fermion systems

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

Liu, Junwei; Shen, Huitao; Qi, Yang

2017-06-07

In this study, we develop the self-learning Monte Carlo (SLMC) method, a general-purpose numerical method recently introduced to simulate many-body systems, for studying interacting fermion systems. Our method uses a highly efficient update algorithm, which we design and dub “cumulative update”, to generate new candidate configurations in the Markov chain based on a self-learned bosonic effective model. From a general analysis and a numerical study of the double exchange model as an example, we find that the SLMC with cumulative update drastically reduces the computational cost of the simulation, while remaining statistically exact. Remarkably, its computational complexity is far lessmore » than the conventional algorithm with local updates.« less

Collective translational and rotational Monte Carlo cluster move for general pairwise interaction

NASA Astrophysics Data System (ADS)

Růžička, Štěpán; Allen, Michael P.

2014-09-01

Virtual move Monte Carlo is a cluster algorithm which was originally developed for strongly attractive colloidal, molecular, or atomistic systems in order to both approximate the collective dynamics and avoid sampling of unphysical kinetic traps. In this paper, we present the algorithm in the form, which selects the moving cluster through a wider class of virtual states and which is applicable to general pairwise interactions, including hard-core repulsion. The newly proposed way of selecting the cluster increases the acceptance probability by up to several orders of magnitude, especially for rotational moves. The results have their applications in simulations of systems interacting via anisotropic potentials both to enhance the sampling of the phase space and to approximate the dynamics.

Improvement of Simulation Method in Validation of Software of the Coordinate Measuring Systems

NASA Astrophysics Data System (ADS)

Nieciąg, Halina

2015-10-01

Software is used in order to accomplish various tasks at each stage of the functioning of modern measuring systems. Before metrological confirmation of measuring equipment, the system has to be validated. This paper discusses the method for conducting validation studies of a fragment of software to calculate the values of measurands. Due to the number and nature of the variables affecting the coordinate measurement results and the complex character and multi-dimensionality of measurands, the study used the Monte Carlo method of numerical simulation. The article presents an attempt of possible improvement of results obtained by classic Monte Carlo tools. The algorithm LHS (Latin Hypercube Sampling) was implemented as alternative to the simple sampling schema of classic algorithm.

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

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.

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.

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.

Axisymmetric Implementation for 3D-Based DSMC Codes

NASA Technical Reports Server (NTRS)

Stewart, Benedicte; Lumpkin, F. E.; LeBeau, G. J.

2011-01-01

The primary objective in developing NASA s DSMC Analysis Code (DAC) was to provide a high fidelity modeling tool for 3D rarefied flows such as vacuum plume impingement and hypersonic re-entry flows [1]. The initial implementation has been expanded over time to offer other capabilities including a novel axisymmetric implementation. Because of the inherently 3D nature of DAC, this axisymmetric implementation uses a 3D Cartesian domain and 3D surfaces. Molecules are moved in all three dimensions but their movements are limited by physical walls to a small wedge centered on the plane of symmetry (Figure 1). Unfortunately, far from the axis of symmetry, the cell size in the direction perpendicular to the plane of symmetry (the Z-direction) may become large compared to the flow mean free path. This frequently results in inaccuracies in these regions of the domain. A new axisymmetric implementation is presented which aims to solve this issue by using Bird s approach for the molecular movement while preserving the 3D nature of the DAC software [2]. First, the computational domain is similar to that previously used such that a wedge must still be used to define the inflow surface and solid walls within the domain. As before molecules are created inside the inflow wedge triangles but they are now rotated back to the symmetry plane. During the move step, molecules are moved in 3D but instead of interacting with the wedge walls, the molecules are rotated back to the plane of symmetry at the end of the move step. This new implementation was tested for multiple flows over axisymmetric shapes, including a sphere, a cone, a double cone and a hollow cylinder. Comparisons to previous DSMC solutions and experiments, when available, are made.

Using the Metropolis Algorithm to Calculate Thermodynamic Quantities: An Undergraduate Computational Experiment

ERIC Educational Resources Information Center

Beddard, Godfrey S.

2011-01-01

Thermodynamic quantities such as the average energy, heat capacity, and entropy are calculated using a Monte Carlo method based on the Metropolis algorithm. This method is illustrated with reference to the harmonic oscillator but is particularly useful when the partition function cannot be evaluated; an example using a one-dimensional spin system…

Comparison of normal tissue dose calculation methods for epidemiological studies of radiotherapy patients.

PubMed

Mille, Matthew M; Jung, Jae Won; Lee, Choonik; Kuzmin, Gleb A; Lee, Choonsik

2018-06-01

Radiation dosimetry is an essential input for epidemiological studies of radiotherapy patients aimed at quantifying the dose-response relationship of late-term morbidity and mortality. Individualised organ dose must be estimated for all tissues of interest located in-field, near-field, or out-of-field. Whereas conventional measurement approaches are limited to points in water or anthropomorphic phantoms, computational approaches using patient images or human phantoms offer greater flexibility and can provide more detailed three-dimensional dose information. In the current study, we systematically compared four different dose calculation algorithms so that dosimetrists and epidemiologists can better understand the advantages and limitations of the various approaches at their disposal. The four dose calculations algorithms considered were as follows: the (1) Analytical Anisotropic Algorithm (AAA) and (2) Acuros XB algorithm (Acuros XB), as implemented in the Eclipse treatment planning system (TPS); (3) a Monte Carlo radiation transport code, EGSnrc; and (4) an accelerated Monte Carlo code, the x-ray Voxel Monte Carlo (XVMC). The four algorithms were compared in terms of their accuracy and appropriateness in the context of dose reconstruction for epidemiological investigations. Accuracy in peripheral dose was evaluated first by benchmarking the calculated dose profiles against measurements in a homogeneous water phantom. Additional simulations in a heterogeneous cylinder phantom evaluated the performance of the algorithms in the presence of tissue heterogeneity. In general, we found that the algorithms contained within the commercial TPS (AAA and Acuros XB) were fast and accurate in-field or near-field, but not acceptable out-of-field. Therefore, the TPS is best suited for epidemiological studies involving large cohorts and where the organs of interest are located in-field or partially in-field. The EGSnrc and XVMC codes showed excellent agreement with measurements both in-field and out-of-field. The EGSnrc code was the most accurate dosimetry approach, but was too slow to be used for large-scale epidemiological cohorts. The XVMC code showed similar accuracy to EGSnrc, but was significantly faster, and thus epidemiological applications seem feasible, especially when the organs of interest reside far away from the field edge.

Predicting patchy particle crystals: variable box shape simulations and evolutionary algorithms.

PubMed

Bianchi, Emanuela; Doppelbauer, Günther; Filion, Laura; Dijkstra, Marjolein; Kahl, Gerhard

2012-06-07

We consider several patchy particle models that have been proposed in literature and we investigate their candidate crystal structures in a systematic way. We compare two different algorithms for predicting crystal structures: (i) an approach based on Monte Carlo simulations in the isobaric-isothermal ensemble and (ii) an optimization technique based on ideas of evolutionary algorithms. We show that the two methods are equally successful and provide consistent results on crystalline phases of patchy particle systems.

Small-Noise Analysis and Symmetrization of Implicit Monte Carlo Samplers

DOE PAGES

Goodman, Jonathan; Lin, Kevin K.; Morzfeld, Matthias

2015-07-06

Implicit samplers are algorithms for producing independent, weighted samples from multivariate probability distributions. These are often applied in Bayesian data assimilation algorithms. We use Laplace asymptotic expansions to analyze two implicit samplers in the small noise regime. Our analysis suggests a symmetrization of the algorithms that leads to improved implicit sampling schemes at a relatively small additional cost. Here, computational experiments confirm the theory and show that symmetrization is effective for small noise sampling problems.

The interaction of Io's plumes and sublimation atmosphere

NASA Astrophysics Data System (ADS)

McDoniel, William J.; Goldstein, David B.; Varghese, Philip L.; Trafton, Laurence M.

2017-09-01

Io's volcanic plumes are the ultimate source of its SO2 atmosphere, but past eruptions have covered the moon in surface frost which sublimates in sunlight. Today, Io's atmosphere is a result of some combination of volcanism and sublimation, but it is unknown exactly how these processes work together to create the observed atmosphere. We use the direct simulation Monte Carlo (DSMC) method to model the interaction of giant plumes with a sublimation atmosphere. Axisymmetric plume/atmosphere simulations demonstrate that the total mass of SO2 above Io's surface is only poorly approximated as the sum of independent volcanic and sublimated components. A simple analytic model is developed to show how variation in the mass of erupting gas above Io's surface can counteract variation in the mass of its hydrostatic atmosphere as surface temperature changes over a Jupiter year. Three-dimensional, unsteady simulations of giant plumes over an Io day are also presented, showing how plume material becomes suspended in the sublimation atmosphere. We find that a plume which produces some total mass above Io's surface at night will cause a net increase in the noon-time atmosphere of only a fraction of the night-time value. However, as much as seven times the night-side mass of the plume will become suspended in the sublimation atmosphere, altering its composition and displacing sublimated material.

Calculated X-ray Intensities Using Monte Carlo Algorithms: A Comparison to Experimental EPMA Data

NASA Technical Reports Server (NTRS)

Carpenter, P. K.

2005-01-01

Monte Carlo (MC) modeling has been used extensively to simulate electron scattering and x-ray emission from complex geometries. Here are presented comparisons between MC results and experimental electron-probe microanalysis (EPMA) measurements as well as phi(rhoz) correction algorithms. Experimental EPMA measurements made on NIST SRM 481 (AgAu) and 482 (CuAu) alloys, at a range of accelerating potential and instrument take-off angles, represent a formal microanalysis data set that has been widely used to develop phi(rhoz) correction algorithms. X-ray intensity data produced by MC simulations represents an independent test of both experimental and phi(rhoz) correction algorithms. The alpha-factor method has previously been used to evaluate systematic errors in the analysis of semiconductor and silicate minerals, and is used here to compare the accuracy of experimental and MC-calculated x-ray data. X-ray intensities calculated by MC are used to generate a-factors using the certificated compositions in the CuAu binary relative to pure Cu and Au standards. MC simulations are obtained using the NIST, WinCasino, and WinXray algorithms; derived x-ray intensities have a built-in atomic number correction, and are further corrected for absorption and characteristic fluorescence using the PAP phi(rhoz) correction algorithm. The Penelope code additionally simulates both characteristic and continuum x-ray fluorescence and thus requires no further correction for use in calculating alpha-factors.

High-Throughput Characterization of Porous Materials Using Graphics Processing Units

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

Kim, Jihan; Martin, Richard L.; Rübel, Oliver

We have developed a high-throughput graphics processing units (GPU) code that can characterize a large database of crystalline porous materials. In our algorithm, the GPU is utilized to accelerate energy grid calculations where the grid values represent interactions (i.e., Lennard-Jones + Coulomb potentials) between gas molecules (i.e., CHmore » $$_{4}$$ and CO$$_{2}$$) and material's framework atoms. Using a parallel flood fill CPU algorithm, inaccessible regions inside the framework structures are identified and blocked based on their energy profiles. Finally, we compute the Henry coefficients and heats of adsorption through statistical Widom insertion Monte Carlo moves in the domain restricted to the accessible space. The code offers significant speedup over a single core CPU code and allows us to characterize a set of porous materials at least an order of magnitude larger than ones considered in earlier studies. For structures selected from such a prescreening algorithm, full adsorption isotherms can be calculated by conducting multiple grand canonical Monte Carlo simulations concurrently within the GPU.« less

Searching for efficient Markov chain Monte Carlo proposal kernels

PubMed Central

Yang, Ziheng; Rodríguez, Carlos E.

2013-01-01

Markov chain Monte Carlo (MCMC) or the Metropolis–Hastings algorithm is a simulation algorithm that has made modern Bayesian statistical inference possible. Nevertheless, the efficiency of different Metropolis–Hastings proposal kernels has rarely been studied except for the Gaussian proposal. Here we propose a unique class of Bactrian kernels, which avoid proposing values that are very close to the current value, and compare their efficiency with a number of proposals for simulating different target distributions, with efficiency measured by the asymptotic variance of a parameter estimate. The uniform kernel is found to be more efficient than the Gaussian kernel, whereas the Bactrian kernel is even better. When optimal scales are used for both, the Bactrian kernel is at least 50% more efficient than the Gaussian. Implementation in a Bayesian program for molecular clock dating confirms the general applicability of our results to generic MCMC algorithms. Our results refute a previous claim that all proposals had nearly identical performance and will prompt further research into efficient MCMC proposals. PMID:24218600

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

Serin, E.; Codel, G.; Mabhouti, H.

Purpose: In small field geometries, the electronic equilibrium can be lost, making it challenging for the dose-calculation algorithm to accurately predict the dose, especially in the presence of tissue heterogeneities. In this study, dosimetric accuracy of Monte Carlo (MC) advanced dose calculation and sequential algorithms of Multiplan treatment planning system were investigated for small radiation fields incident on homogeneous and heterogeneous geometries. Methods: Small open fields of fixed cones of Cyberknife M6 unit 100 to 500 mm2 were used for this study. The fields were incident on in house phantom containing lung, air, and bone inhomogeneities and also homogeneous phantom.more » Using the same film batch, the net OD to dose calibration curve was obtained using CK with the 60 mm fixed cone by delivering 0- 800 cGy. Films were scanned 48 hours after irradiation using an Epson 1000XL flatbed scanner. The dosimetric accuracy of MC and sequential algorithms in the presence of the inhomogeneities was compared against EBT3 film dosimetry Results: Open field tests in a homogeneous phantom showed good agreement between two algorithms and film measurement For MC algorithm, the minimum gamma analysis passing rates between measured and calculated dose distributions were 99.7% and 98.3% for homogeneous and inhomogeneous fields in the case of lung and bone respectively. For sequential algorithm, the minimum gamma analysis passing rates were 98.9% and 92.5% for for homogeneous and inhomogeneous fields respectively for used all cone sizes. In the case of the air heterogeneity, the differences were larger for both calculation algorithms. Overall, when compared to measurement, the MC had better agreement than sequential algorithm. Conclusion: The Monte Carlo calculation algorithm in the Multiplan treatment planning system is an improvement over the existing sequential algorithm. Dose discrepancies were observed for in the presence of air inhomogeneities.« less

Excited states from quantum Monte Carlo in the basis of Slater determinants

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

Humeniuk, Alexander; Mitrić, Roland, E-mail: roland.mitric@uni-wuerzburg.de

2014-11-21

Building on the full configuration interaction quantum Monte Carlo (FCIQMC) algorithm introduced recently by Booth et al. [J. Chem. Phys. 131, 054106 (2009)] to compute the ground state of correlated many-electron systems, an extension to the computation of excited states (exFCIQMC) is presented. The Hilbert space is divided into a large part consisting of pure Slater determinants and a much smaller orthogonal part (the size of which is controlled by a cut-off threshold), from which the lowest eigenstates can be removed efficiently. In this way, the quantum Monte Carlo algorithm is restricted to the orthogonal complement of the lower excitedmore » states and projects out the next highest excited state. Starting from the ground state, higher excited states can be found one after the other. The Schrödinger equation in imaginary time is solved by the same population dynamics as in the ground state algorithm with modified probabilities and matrix elements, for which working formulae are provided. As a proof of principle, the method is applied to lithium hydride in the 3-21G basis set and to the helium dimer in the aug-cc-pVDZ basis set. It is shown to give the correct electronic structure for all bond lengths. Much more testing will be required before the applicability of this method to electron correlation problems of interesting size can be assessed.« less

A fast Monte Carlo EM algorithm for estimation in latent class model analysis with an application to assess diagnostic accuracy for cervical neoplasia in women with AGC

PubMed Central

Kang, Le; Carter, Randy; Darcy, Kathleen; Kauderer, James; Liao, Shu-Yuan

2013-01-01

In this article we use a latent class model (LCM) with prevalence modeled as a function of covariates to assess diagnostic test accuracy in situations where the true disease status is not observed, but observations on three or more conditionally independent diagnostic tests are available. A fast Monte Carlo EM (MCEM) algorithm with binary (disease) diagnostic data is implemented to estimate parameters of interest; namely, sensitivity, specificity, and prevalence of the disease as a function of covariates. To obtain standard errors for confidence interval construction of estimated parameters, the missing information principle is applied to adjust information matrix estimates. We compare the adjusted information matrix based standard error estimates with the bootstrap standard error estimates both obtained using the fast MCEM algorithm through an extensive Monte Carlo study. Simulation demonstrates that the adjusted information matrix approach estimates the standard error similarly with the bootstrap methods under certain scenarios. The bootstrap percentile intervals have satisfactory coverage probabilities. We then apply the LCM analysis to a real data set of 122 subjects from a Gynecologic Oncology Group (GOG) study of significant cervical lesion (S-CL) diagnosis in women with atypical glandular cells of undetermined significance (AGC) to compare the diagnostic accuracy of a histology-based evaluation, a CA-IX biomarker-based test and a human papillomavirus (HPV) DNA test. PMID:24163493

Multiscale Monte Carlo equilibration: Two-color QCD with two fermion flavors

DOE PAGES

Detmold, William; Endres, Michael G.

2016-12-02

In this study, we demonstrate the applicability of a recently proposed multiscale thermalization algorithm to two-color quantum chromodynamics (QCD) with two mass-degenerate fermion flavors. The algorithm involves refining an ensemble of gauge configurations that had been generated using a renormalization group (RG) matched coarse action, thereby producing a fine ensemble that is close to the thermalized distribution of a target fine action; the refined ensemble is subsequently rethermalized using conventional algorithms. Although the generalization of this algorithm from pure Yang-Mills theory to QCD with dynamical fermions is straightforward, we find that in the latter case, the method is susceptible tomore » numerical instabilities during the initial stages of rethermalization when using the hybrid Monte Carlo algorithm. We find that these instabilities arise from large fermion forces in the evolution, which are attributed to an accumulation of spurious near-zero modes of the Dirac operator. We propose a simple strategy for curing this problem, and demonstrate that rapid thermalization--as probed by a variety of gluonic and fermionic operators--is possible with the use of this solution. Also, we study the sensitivity of rethermalization rates to the RG matching of the coarse and fine actions, and identify effective matching conditions based on a variety of measured scales.« less

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.

Hamiltonian Monte Carlo acceleration using surrogate functions with random bases.

PubMed

Zhang, Cheng; Shahbaba, Babak; Zhao, Hongkai

2017-11-01

For big data analysis, high computational cost for Bayesian methods often limits their applications in practice. In recent years, there have been many attempts to improve computational efficiency of Bayesian inference. Here we propose an efficient and scalable computational technique for a state-of-the-art Markov chain Monte Carlo methods, namely, Hamiltonian Monte Carlo. The key idea is to explore and exploit the structure and regularity in parameter space for the underlying probabilistic model to construct an effective approximation of its geometric properties. To this end, we build a surrogate function to approximate the target distribution using properly chosen random bases and an efficient optimization process. The resulting method provides a flexible, scalable, and efficient sampling algorithm, which converges to the correct target distribution. We show that by choosing the basis functions and optimization process differently, our method can be related to other approaches for the construction of surrogate functions such as generalized additive models or Gaussian process models. Experiments based on simulated and real data show that our approach leads to substantially more efficient sampling algorithms compared to existing state-of-the-art methods.

Estimating source parameters from deformation data, with an application to the March 1997 earthquake swarm off the Izu Peninsula, Japan

NASA Astrophysics Data System (ADS)

Cervelli, P.; Murray, M. H.; Segall, P.; Aoki, Y.; Kato, T.

2001-06-01

We have applied two Monte Carlo optimization techniques, simulated annealing and random cost, to the inversion of deformation data for fault and magma chamber geometry. These techniques involve an element of randomness that permits them to escape local minima and ultimately converge to the global minimum of misfit space. We have tested the Monte Carlo algorithms on two synthetic data sets. We have also compared them to one another in terms of their efficiency and reliability. We have applied the bootstrap method to estimate confidence intervals for the source parameters, including the correlations inherent in the data. Additionally, we present methods that use the information from the bootstrapping procedure to visualize the correlations between the different model parameters. We have applied these techniques to GPS, tilt, and leveling data from the March 1997 earthquake swarm off of the Izu Peninsula, Japan. Using the two Monte Carlo algorithms, we have inferred two sources, a dike and a fault, that fit the deformation data and the patterns of seismicity and that are consistent with the regional stress field.

Program Manager - A Bimonthly Magazine of DSMC, Volume 27, Number 2.

DTIC Science & Technology

1998-04-01

catalog. http /www.gsa.gov -------------- - Online shopping for commercial items to http ’Iwww.ndia.org I--- support government interests. Events...funds. Allows users access to GAO "Whats New in Contracting?" educational reports, FAQs. products catalog. http://www.gsa.gov Online shopping for

Parallelization and implementation of approximate root isolation for nonlinear system by Monte Carlo

NASA Astrophysics Data System (ADS)

Khosravi, Ebrahim

1998-12-01

This dissertation solves a fundamental problem of isolating the real roots of nonlinear systems of equations by Monte-Carlo that were published by Bush Jones. This algorithm requires only function values and can be applied readily to complicated systems of transcendental functions. The implementation of this sequential algorithm provides scientists with the means to utilize function analysis in mathematics or other fields of science. The algorithm, however, is so computationally intensive that the system is limited to a very small set of variables, and this will make it unfeasible for large systems of equations. Also a computational technique was needed for investigating a metrology of preventing the algorithm structure from converging to the same root along different paths of computation. The research provides techniques for improving the efficiency and correctness of the algorithm. The sequential algorithm for this technique was corrected and a parallel algorithm is presented. This parallel method has been formally analyzed and is compared with other known methods of root isolation. The effectiveness, efficiency, enhanced overall performance of the parallel processing of the program in comparison to sequential processing is discussed. The message passing model was used for this parallel processing, and it is presented and implemented on Intel/860 MIMD architecture. The parallel processing proposed in this research has been implemented in an ongoing high energy physics experiment: this algorithm has been used to track neutrinoes in a super K detector. This experiment is located in Japan, and data can be processed on-line or off-line locally or remotely.

Accurate condensed history Monte Carlo simulation of electron transport. II. Application to ion chamber response simulations.

PubMed

Kawrakow, I

2000-03-01

In this report the condensed history Monte Carlo simulation of electron transport and its application to the calculation of ion chamber response is discussed. It is shown that the strong step-size dependencies and lack of convergence to the correct answer previously observed are the combined effect of the following artifacts caused by the EGS4/PRESTA implementation of the condensed history technique: dose underprediction due to PRESTA'S pathlength correction and lateral correlation algorithm; dose overprediction due to the boundary crossing algorithm; dose overprediction due to the breakdown of the fictitious cross section method for sampling distances between discrete interaction and the inaccurate evaluation of energy-dependent quantities. These artifacts are now understood quantitatively and analytical expressions for their effect are given.

Parameters estimation for reactive transport: A way to test the validity of a reactive model

NASA Astrophysics Data System (ADS)

Aggarwal, Mohit; Cheikh Anta Ndiaye, Mame; Carrayrou, Jérôme

The chemical parameters used in reactive transport models are not known accurately due to the complexity and the heterogeneous conditions of a real domain. We will present an efficient algorithm in order to estimate the chemical parameters using Monte-Carlo method. Monte-Carlo methods are very robust for the optimisation of the highly non-linear mathematical model describing reactive transport. Reactive transport of tributyltin (TBT) through natural quartz sand at seven different pHs is taken as the test case. Our algorithm will be used to estimate the chemical parameters of the sorption of TBT onto the natural quartz sand. By testing and comparing three models of surface complexation, we show that the proposed adsorption model cannot explain the experimental data.

Analysis of estimation algorithms for CDTI and CAS applications

NASA Technical Reports Server (NTRS)

Goka, T.

1985-01-01

Estimation algorithms for Cockpit Display of Traffic Information (CDTI) and Collision Avoidance System (CAS) applications were analyzed and/or developed. The algorithms are based on actual or projected operational and performance characteristics of an Enhanced TCAS II traffic sensor developed by Bendix and the Federal Aviation Administration. Three algorithm areas are examined and discussed. These are horizontal x and y, range and altitude estimation algorithms. Raw estimation errors are quantified using Monte Carlo simulations developed for each application; the raw errors are then used to infer impacts on the CDTI and CAS applications. Applications of smoothing algorithms to CDTI problems are also discussed briefly. Technical conclusions are summarized based on the analysis of simulation results.

Recommendations for dose calculations of lung cancer treatment plans treated with stereotactic ablative body radiotherapy (SABR)

NASA Astrophysics Data System (ADS)

Devpura, S.; Siddiqui, M. S.; Chen, D.; Liu, D.; Li, H.; Kumar, S.; Gordon, J.; Ajlouni, M.; Movsas, B.; Chetty, I. J.

2014-03-01

The purpose of this study was to systematically evaluate dose distributions computed with 5 different dose algorithms for patients with lung cancers treated using stereotactic ablative body radiotherapy (SABR). Treatment plans for 133 lung cancer patients, initially computed with a 1D-pencil beam (equivalent-path-length, EPL-1D) algorithm, were recalculated with 4 other algorithms commissioned for treatment planning, including 3-D pencil-beam (EPL-3D), anisotropic analytical algorithm (AAA), collapsed cone convolution superposition (CCC), and Monte Carlo (MC). The plan prescription dose was 48 Gy in 4 fractions normalized to the 95% isodose line. Tumors were classified according to location: peripheral tumors surrounded by lung (lung-island, N=39), peripheral tumors attached to the rib-cage or chest wall (lung-wall, N=44), and centrally-located tumors (lung-central, N=50). Relative to the EPL-1D algorithm, PTV D95 and mean dose values computed with the other 4 algorithms were lowest for "lung-island" tumors with smallest field sizes (3-5 cm). On the other hand, the smallest differences were noted for lung-central tumors treated with largest field widths (7-10 cm). Amongst all locations, dose distribution differences were most strongly correlated with tumor size for lung-island tumors. For most cases, convolution/superposition and MC algorithms were in good agreement. Mean lung dose (MLD) values computed with the EPL-1D algorithm were highly correlated with that of the other algorithms (correlation coefficient =0.99). The MLD values were found to be ~10% lower for small lung-island tumors with the model-based (conv/superposition and MC) vs. the correction-based (pencil-beam) algorithms with the model-based algorithms predicting greater low dose spread within the lungs. This study suggests that pencil beam algorithms should be avoided for lung SABR planning. For the most challenging cases, small tumors surrounded entirely by lung tissue (lung-island type), a Monte-Carlo-based algorithm may be warranted.

A Monte Carlo comparison of the recovery of winds near upwind and downwind from the SASS-1 model function by means of the sum of squares algorithm and a maximum likelihood estimator

NASA Technical Reports Server (NTRS)

Pierson, W. J., Jr.

1984-01-01

Backscatter measurements at upwind and crosswind are simulated for five incidence angles by means of the SASS-1 model function. The effects of communication noise and attitude errors are simulated by Monte Carlo methods, and the winds are recovered by both the Sum of Square (SOS) algorithm and a Maximum Likelihood Estimater (MLE). The SOS algorithm is shown to fail for light enough winds at all incidence angles and to fail to show areas of calm because backscatter estimates that were negative or that produced incorrect values of K sub p greater than one were discarded. The MLE performs well for all input backscatter estimates and returns calm when both are negative. The use of the SOS algorithm is shown to have introduced errors in the SASS-1 model function that, in part, cancel out the errors that result from using it, but that also cause disagreement with other data sources such as the AAFE circle flight data at light winds. Implications for future scatterometer systems are given.

Asteroid mass estimation using Markov-chain Monte Carlo

NASA Astrophysics Data System (ADS)

Siltala, Lauri; Granvik, Mikael

2017-11-01

Estimates for asteroid masses are based on their gravitational perturbations on the orbits of other objects such as Mars, spacecraft, or other asteroids and/or their satellites. In the case of asteroid-asteroid perturbations, this leads to an inverse problem in at least 13 dimensions where the aim is to derive the mass of the perturbing asteroid(s) and six orbital elements for both the perturbing asteroid(s) and the test asteroid(s) based on astrometric observations. We have developed and implemented three different mass estimation algorithms utilizing asteroid-asteroid perturbations: the very rough 'marching' approximation, in which the asteroids' orbital elements are not fitted, thereby reducing the problem to a one-dimensional estimation of the mass, an implementation of the Nelder-Mead simplex method, and most significantly, a Markov-chain Monte Carlo (MCMC) approach. We describe each of these algorithms with particular focus on the MCMC algorithm, and present example results using both synthetic and real data. Our results agree with the published mass estimates, but suggest that the published uncertainties may be misleading as a consequence of using linearized mass-estimation methods. Finally, we discuss remaining challenges with the algorithms as well as future plans.

Use of advanced particle methods in modeling space propulsion and its supersonic expansions

NASA Astrophysics Data System (ADS)

Borner, Arnaud

This research discusses the use of advanced kinetic particle methods such as Molecular Dynamics (MD) and direct simulation Monte Carlo (DSMC) to model space propulsion systems such as electrospray thrusters and their supersonic expansions. MD simulations are performed to model an electrospray thruster for the ionic liquid (IL) EMIM--BF4 using coarse-grained (CG) potentials. The model is initially featuring a constant electric field applied in the longitudinal direction. Two coarse-grained potentials are compared, and the effective-force CG (EFCG) potential is found to predict the formation of the Taylor cone, the cone-jet, and other extrusion modes for similar electric fields and mass flow rates observed in experiments of a IL fed capillary-tip-extractor system better than the simple CG potential. Later, one-dimensional and fully transient three-dimensional electric fields, the latter solving Poisson's equation to take into account the electric field due to space charge at each timestep, are computed by coupling the MD model to a Poisson solver. It is found that the inhomogeneous electric field as well as that of the IL space-charge improve agreement between modeling and experiment. The boundary conditions (BCs) are found to have a substantial impact on the potential and electric field, and the tip BC is introduced and compared to the two previous BCs, named plate and needle, showing good improvement by reducing unrealistically high radial electric fields generated in the vicinity of the capillary tip. The influence of the different boundary condition models on charged species currents as a function of the mass flow rate is studied, and it is found that a constant electric field model gives similar agreement to the more rigorous and computationally expensive tip boundary condition at lower flow rates. However, at higher mass flow rates the MD simulations with the constant electric field produces extruded particles with higher Coulomb energy per ion, consistent with droplet formation. Supersonic expansions to vacuum produce clusters of sufficiently small size that properties such as heat capacities and latent heat of evaporation cannot be described by bulk vapor thermodynamic values. Therefore, MD simulations are performed to compute the evaporation rate of small water clusters as a function of temperature and size and the rates are found to agree with Unimolecular Dissociation Theory (UDT) and Classical Nucleation Theory (CNT). The heat capacities and latent heat of vaporization obtained from Monte-Carlo Canonical-Ensemble (MCCE) simulations are used in DSMC simulations of two experiments that measured Rayleigh scattering and terminal dimer mole fraction of supersonic water-jet expansions. Water-cluster temperature and size are found to be influenced by the use of kinetic rather than thermodynamic heat-capacity and latent-heat values as well as the nucleation model. Additionally, MD simulations of water condensation in a one-dimensional free expansion are performed to simulate the conditions in the core of a plume. We find that the internal structure of the clusters formed depends on the stagnation temperature conditions. Clusters of sizes 21 and 324 are studied in detail, and their radial distribution functions (RDF) are computed and compared to reported RDFs for solid amorphous ice clusters. Dielectric properties of liquid water and water clusters are investigated, and the static dielectric constant, dipole moment autocorrelation function and relative permittivity are computed by means of MD simulations.

Multi-particle phase space integration with arbitrary set of singularities in CompHEP

NASA Astrophysics Data System (ADS)

Kovalenko, D. N.; Pukhov, A. E.

1997-02-01

We describe an algorithm of multi-particle phase space integration for collision and decay processes realized in CompHEP package version 3.2. In the framework of this algorithm it is possible to regularize an arbitrary set of singularities caused by virtual particle propagators. The algorithm is based on the method of the recursive representation of kinematics and on the multichannel Monte Carlo approach. CompHEP package is available by WWW: http://theory.npi.msu.su/pukhov/comphep.html

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.

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-344: Validation and Clinical Experience of Eclipse Electron Monte Carlo Algorithm (EMC)

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

Pokharel, S; Rana, S

2014-06-01

Purpose: The purpose of this study is to validate Eclipse Electron Monte Carlo (Algorithm for routine clinical uses. Methods: The PTW inhomogeneity phantom (T40037) with different combination of heterogeneous slabs has been CT-scanned with Philips Brilliance 16 slice scanner. The phantom contains blocks of Rando Alderson materials mimicking lung, Polystyrene (Tissue), PTFE (Bone) and PMAA. The phantom has 30×30×2.5 cm base plate with 2cm recesses to insert inhomogeneity. The detector systems used in this study are diode, tlds and Gafchromic EBT2 films. The diode and tlds were included in CT scans. The CT sets are transferred to Eclipse treatment planningmore » system. Several plans have been created with Eclipse Monte Carlo (EMC) algorithm 11.0.21. Measurements have been carried out in Varian TrueBeam machine for energy from 6–22mev. Results: The measured and calculated doses agreed very well for tissue like media. The agreement was reasonably okay for the presence of lung inhomogeneity. The point dose agreement was within 3.5% and Gamma passing rate at 3%/3mm was greater than 93% except for 6Mev(85%). The disagreement can reach as high as 10% in the presence of bone inhomogeneity. This is due to eclipse reporting dose to the medium as opposed to the dose to the water as in conventional calculation engines. Conclusion: Care must be taken when using Varian Eclipse EMC algorithm for dose calculation for routine clinical uses. The algorithm dose not report dose to water in which most of the clinical experiences are based on rather it just reports dose to medium directly. In the presence of inhomogeneity such as bone, the dose discrepancy can be as high as 10% or even more depending on the location of normalization point or volume. As Radiation oncology as an empirical science, care must be taken before using EMC reported monitor units for clinical uses.« less

Characterisation of mega-voltage electron pencil beam dose distributions: viability of a measurement-based approach.

PubMed

Barnes, M P; Ebert, M A

2008-03-01

The concept of electron pencil-beam dose distributions is central to pencil-beam algorithms used in electron beam radiotherapy treatment planning. The Hogstrom algorithm, which is a common algorithm for electron treatment planning, models large electron field dose distributions by the superposition of a series of pencil beam dose distributions. This means that the accurate characterisation of an electron pencil beam is essential for the accuracy of the dose algorithm. The aim of this study was to evaluate a measurement based approach for obtaining electron pencil-beam dose distributions. The primary incentive for the study was the accurate calculation of dose distributions for narrow fields as traditional electron algorithms are generally inaccurate for such geometries. Kodak X-Omat radiographic film was used in a solid water phantom to measure the dose distribution of circular 12 MeV beams from a Varian 21EX linear accelerator. Measurements were made for beams of diameter, 1.5, 2, 4, 8, 16 and 32 mm. A blocked-field technique was used to subtract photon contamination in the beam. The "error function" derived from Fermi-Eyges Multiple Coulomb Scattering (MCS) theory for corresponding square fields was used to fit resulting dose distributions so that extrapolation down to a pencil beam distribution could be made. The Monte Carlo codes, BEAM and EGSnrc were used to simulate the experimental arrangement. The 8 mm beam dose distribution was also measured with TLD-100 microcubes. Agreement between film, TLD and Monte Carlo simulation results were found to be consistent with the spatial resolution used. The study has shown that it is possible to extrapolate narrow electron beam dose distributions down to a pencil beam dose distribution using the error function. However, due to experimental uncertainties and measurement difficulties, Monte Carlo is recommended as the method of choice for characterising electron pencil-beam dose distributions.

Monte Carlo charged-particle tracking and energy deposition on a Lagrangian mesh.

PubMed

Yuan, J; Moses, G A; McKenty, P W

2005-10-01

A Monte Carlo algorithm for alpha particle tracking and energy deposition on a cylindrical computational mesh in a Lagrangian hydrodynamics code used for inertial confinement fusion (ICF) simulations is presented. The straight line approximation is used to follow propagation of "Monte Carlo particles" which represent collections of alpha particles generated from thermonuclear deuterium-tritium (DT) reactions. Energy deposition in the plasma is modeled by the continuous slowing down approximation. The scheme addresses various aspects arising in the coupling of Monte Carlo tracking with Lagrangian hydrodynamics; such as non-orthogonal severely distorted mesh cells, particle relocation on the moving mesh and particle relocation after rezoning. A comparison with the flux-limited multi-group diffusion transport method is presented for a polar direct drive target design for the National Ignition Facility. Simulations show the Monte Carlo transport method predicts about earlier ignition than predicted by the diffusion method, and generates higher hot spot temperature. Nearly linear speed-up is achieved for multi-processor parallel simulations.

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