Girsanov's transformation based variance reduced Monte Carlo simulation schemes for reliability estimation in nonlinear stochastic dynamics

NASA Astrophysics Data System (ADS)

Kanjilal, Oindrila; Manohar, C. S.

2017-07-01

The study considers the problem of simulation based time variant reliability analysis of nonlinear randomly excited dynamical systems. Attention is focused on importance sampling strategies based on the application of Girsanov's transformation method. Controls which minimize the distance function, as in the first order reliability method (FORM), are shown to minimize a bound on the sampling variance of the estimator for the probability of failure. Two schemes based on the application of calculus of variations for selecting control signals are proposed: the first obtains the control force as the solution of a two-point nonlinear boundary value problem, and, the second explores the application of the Volterra series in characterizing the controls. The relative merits of these schemes, vis-à-vis the method based on ideas from the FORM, are discussed. Illustrative examples, involving archetypal single degree of freedom (dof) nonlinear oscillators, and a multi-degree of freedom nonlinear dynamical system, are presented. The credentials of the proposed procedures are established by comparing the solutions with pertinent results from direct Monte Carlo simulations.

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.

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.

Nonequilibrium hypersonic flows simulations with asymptotic-preserving Monte Carlo methods

NASA Astrophysics Data System (ADS)

Ren, Wei; Liu, Hong; Jin, Shi

2014-12-01

In the rarefied gas dynamics, the DSMC method is one of the most popular numerical tools. It performs satisfactorily in simulating hypersonic flows surrounding re-entry vehicles and micro-/nano- flows. However, the computational cost is expensive, especially when Kn → 0. Even for flows in the near-continuum regime, pure DSMC simulations require a number of computational efforts for most cases. Albeit several DSMC/NS hybrid methods are proposed to deal with this, those methods still suffer from the boundary treatment, which may cause nonphysical solutions. Filbet and Jin [1] proposed a framework of new numerical methods of Boltzmann equation, called asymptotic preserving schemes, whose computational costs are affordable as Kn → 0. Recently, Ren et al. [2] realized the AP schemes with Monte Carlo methods (AP-DSMC), which have better performance than counterpart methods. In this paper, AP-DSMC is applied in simulating nonequilibrium hypersonic flows. Several numerical results are computed and analyzed to study the efficiency and capability of capturing complicated flow characteristics.

On recontamination and directional-bias problems in Monte Carlo simulation of PDF turbulence models

NASA Technical Reports Server (NTRS)

Hsu, Andrew T.

1991-01-01

Turbulent combustion can not be simulated adequately by conventional moment closure turbulence models. The difficulty lies in the fact that the reaction rate is in general an exponential function of the temperature, and the higher order correlations in the conventional moment closure models of the chemical source term can not be neglected, making the applications of such models impractical. The probability density function (pdf) method offers an attractive alternative: in a pdf model, the chemical source terms are closed and do not require additional models. A grid dependent Monte Carlo scheme was studied, since it is a logical alternative, wherein the number of computer operations increases only linearly with the increase of number of independent variables, as compared to the exponential increase in a conventional finite difference scheme. A new algorithm was devised that satisfies a restriction in the case of pure diffusion or uniform flow problems. Although for nonuniform flows absolute conservation seems impossible, the present scheme has reduced the error considerably.

ME(SSY)**2: Monte Carlo Code for Star Cluster Simulations

NASA Astrophysics Data System (ADS)

Freitag, Marc Dewi

2013-02-01

ME(SSY)**2 stands for “Monte-carlo Experiments with Spherically SYmmetric Stellar SYstems." This code simulates the long term evolution of spherical clusters of stars; it was devised specifically to treat dense galactic nuclei. It is based on the pioneering Monte Carlo scheme proposed by Hénon in the 70's and includes all relevant physical ingredients (2-body relaxation, stellar mass spectrum, collisions, tidal disruption, ldots). It is basically a Monte Carlo resolution of the Fokker-Planck equation. It can cope with any stellar mass spectrum or velocity distribution. Being a particle-based method, it also allows one to take stellar collisions into account in a very realistic way. This unique code, featuring most important physical processes, allows million particle simulations, spanning a Hubble time, in a few CPU days on standard personal computers and provides a wealth of data only rivalized by N-body simulations. The current version of the software requires the use of routines from the "Numerical Recipes in Fortran 77" (http://www.nrbook.com/a/bookfpdf.php).

On zero variance Monte Carlo path-stretching schemes

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

Lux, I.

1983-08-01

A zero variance path-stretching biasing scheme proposed for a special case by Dwivedi is derived in full generality. The procedure turns out to be the generalization of the exponential transform. It is shown that the biased game can be interpreted as an analog simulation procedure, thus saving some computational effort in comparison with the corresponding nonanalog game.

COMPARISON OF MONTE CARLO METHODS FOR NONLINEAR RADIATION TRANSPORT

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

W. R. MARTIN; F. B. BROWN

2001-03-01

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

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.

An atomistic simulation scheme for modeling crystal formation from solution.

PubMed

Kawska, Agnieszka; Brickmann, Jürgen; Kniep, Rüdiger; Hochrein, Oliver; Zahn, Dirk

2006-01-14

We present an atomistic simulation scheme for investigating crystal growth from solution. Molecular-dynamics simulation studies of such processes typically suffer from considerable limitations concerning both system size and simulation times. In our method this time-length scale problem is circumvented by an iterative scheme which combines a Monte Carlo-type approach for the identification of ion adsorption sites and, after each growth step, structural optimization of the ion cluster and the solvent by means of molecular-dynamics simulation runs. An important approximation of our method is based on assuming full structural relaxation of the aggregates between each of the growth steps. This concept only holds for compounds of low solubility. To illustrate our method we studied CaF2 aggregate growth from aqueous solution, which may be taken as prototypes for compounds of very low solubility. The limitations of our simulation scheme are illustrated by the example of NaCl aggregation from aqueous solution, which corresponds to a solute/solvent combination of very high salt solubility.

Discrete Fractional Component Monte Carlo Simulation Study of Dilute Nonionic Surfactants at the Air-Water Interface.

PubMed

Yoo, Brian; Marin-Rimoldi, Eliseo; Mullen, Ryan Gotchy; Jusufi, Arben; Maginn, Edward J

2017-09-26

We present a newly developed Monte Carlo scheme to predict bulk surfactant concentrations and surface tensions at the air-water interface for various surfactant interfacial coverages. Since the concentration regimes of these systems of interest are typically very dilute (≪10 -5 mol. frac.), Monte Carlo simulations with the use of insertion/deletion moves can provide the ability to overcome finite system size limitations that often prohibit the use of modern molecular simulation techniques. In performing these simulations, we use the discrete fractional component Monte Carlo (DFCMC) method in the Gibbs ensemble framework, which allows us to separate the bulk and air-water interface into two separate boxes and efficiently swap tetraethylene glycol surfactants C 10 E 4 between boxes. Combining this move with preferential translations, volume biased insertions, and Wang-Landau biasing vastly enhances sampling and helps overcome the classical "insertion problem", often encountered in non-lattice Monte Carlo simulations. We demonstrate that this methodology is both consistent with the original molecular thermodynamic theory (MTT) of Blankschtein and co-workers, as well as their recently modified theory (MD/MTT), which incorporates the results of surfactant infinite dilution transfer free energies and surface tension calculations obtained from molecular dynamics simulations.

Free energy and phase equilibria for the restricted primitive model of ionic fluids from Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Orkoulas, Gerassimos; Panagiotopoulos, Athanassios Z.

1994-07-01

In this work, we investigate the liquid-vapor phase transition of the restricted primitive model of ionic fluids. We show that at the low temperatures where the phase transition occurs, the system cannot be studied by conventional molecular simulation methods because convergence to equilibrium is slow. To accelerate convergence, we propose cluster Monte Carlo moves capable of moving more than one particle at a time. We then address the issue of charged particle transfers in grand canonical and Gibbs ensemble Monte Carlo simulations, for which we propose a biased particle insertion/destruction scheme capable of sampling short interparticle distances. We compute the chemical potential for the restricted primitive model as a function of temperature and density from grand canonical Monte Carlo simulations and the phase envelope from Gibbs Monte Carlo simulations. Our calculated phase coexistence curve is in agreement with recent results of Caillol obtained on the four-dimensional hypersphere and our own earlier Gibbs ensemble simulations with single-ion transfers, with the exception of the critical temperature, which is lower in the current calculations. Our best estimates for the critical parameters are T*c=0.053, ρ*c=0.025. We conclude with possible future applications of the biased techniques developed here for phase equilibrium calculations for ionic fluids.

Improved diffusion Monte Carlo propagators for bosonic systems using Itô calculus

NASA Astrophysics Data System (ADS)

Hâkansson, P.; Mella, M.; Bressanini, Dario; Morosi, Gabriele; Patrone, Marta

2006-11-01

The construction of importance sampled diffusion Monte Carlo (DMC) schemes accurate to second order in the time step is discussed. A central aspect in obtaining efficient second order schemes is the numerical solution of the stochastic differential equation (SDE) associated with the Fokker-Plank equation responsible for the importance sampling procedure. In this work, stochastic predictor-corrector schemes solving the SDE and consistent with Itô calculus are used in DMC simulations of helium clusters. These schemes are numerically compared with alternative algorithms obtained by splitting the Fokker-Plank operator, an approach that we analyze using the analytical tools provided by Itô calculus. The numerical results show that predictor-corrector methods are indeed accurate to second order in the time step and that they present a smaller time step bias and a better efficiency than second order split-operator derived schemes when computing ensemble averages for bosonic systems. The possible extension of the predictor-corrector methods to higher orders is also discussed.

Self-learning kinetic Monte Carlo simulations of Al diffusion in Mg

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

Nandipati, Giridhar; Govind, Niranjan; Andersen, Amity

2016-03-16

Atomistic on-lattice self-learning kinetic Monte Carlo (SLKMC) method was used to examine the vacancy-mediated diffusion of an Al atom in pure hcp Mg. Local atomic environment dependent activation barriers for vacancy-atom exchange processes were calculated on-the-fly using climbing image nudged-elastic band method (CI-NEB) and using a Mg-Al binary modified embedded-atom method (MEAM) interatomic potential. Diffusivities of vacancy and Al atom in pure Mg were obtained from SLKMC simulations and are compared with values available in the literature that are obtained from experiments and first-principle calculations. Al Diffusivities obtained from SLKMC simulations are lower, due to larger activation barriers and lowermore » diffusivity prefactors, than those available in the literature but have same order of magnitude. We present all vacancy-Mg and vacancy-Al atom exchange processes and their activation barriers that were identified in SLKMC simulations. We will describe a simple mapping scheme to map a hcp lattice on to a simple cubic lattice that would enable hcp lattices to be simulated in an on-lattice KMC framework. We also present the pattern recognition scheme used in SLKMC simulations.« less

Comparison between different adsorption-desorption kinetics schemes in two dimensional lattice gas

NASA Astrophysics Data System (ADS)

Huespe, V. J.; Belardinelli, R. E.; Pereyra, V. D.; Manzi, S. J.

2017-12-01

Monte Carlo simulation is used to study the adsorption-desorption kinetics in the framework of the kinetic lattice-gas model. Three schemes of the so-called hard dynamics and five schemes of the so called soft dynamics were used for this purpose. It is observed that for the hard dynamic schemes, the equilibrium and non-equilibrium observable, such as adsorption isotherms, sticking coefficients, and thermal desorption spectra, have a normal or physical sustainable behavior. While for the soft dynamics schemes, with the exception of the transition state theory, the equilibrium and non-equilibrium observables have several problems.

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

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

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

2010-07-20

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

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.

Accelerated Monte Carlo Methods for Coulomb Collisions

NASA Astrophysics Data System (ADS)

Rosin, Mark; Ricketson, Lee; Dimits, Andris; Caflisch, Russel; Cohen, Bruce

2014-03-01

We present a new highly efficient multi-level Monte Carlo (MLMC) simulation algorithm for Coulomb collisions in a plasma. The scheme, initially developed and used successfully for applications in financial mathematics, is applied here to kinetic plasmas for the first time. The method is based on a Langevin treatment of the Landau-Fokker-Planck equation and has a rich history derived from the works of Einstein and Chandrasekhar. The MLMC scheme successfully reduces the computational cost of achieving an RMS error ɛ in the numerical solution to collisional plasma problems from (ɛ-3) - for the standard state-of-the-art Langevin and binary collision algorithms - to a theoretically optimal (ɛ-2) scaling, when used in conjunction with an underlying Milstein discretization to the Langevin equation. In the test case presented here, the method accelerates simulations by factors of up to 100. We summarize the scheme, present some tricks for improving its efficiency yet further, and discuss the method's range of applicability. Work performed for US DOE by LLNL under contract DE-AC52- 07NA27344 and by UCLA under grant DE-FG02-05ER25710.

All-Particle Multiscale Computation of Hypersonic Rarefied Flow

NASA Astrophysics Data System (ADS)

Jun, E.; Burt, J. M.; Boyd, I. D.

2011-05-01

This study examines a new hybrid particle scheme used as an alternative means of multiscale flow simulation. The hybrid particle scheme employs the direct simulation Monte Carlo (DSMC) method in rarefied flow regions and the low diffusion (LD) particle method in continuum flow regions. The numerical procedures of the low diffusion particle method are implemented within an existing DSMC algorithm. The performance of the LD-DSMC approach is assessed by studying Mach 10 nitrogen flow over a sphere with a global Knudsen number of 0.002. The hybrid scheme results show good overall agreement with results from standard DSMC and CFD computation. Subcell procedures are utilized to improve computational efficiency and reduce sensitivity to DSMC cell size in the hybrid scheme. This makes it possible to perform the LD-DSMC simulation on a much coarser mesh that leads to a significant reduction in computation time.

Monte Carlo modeling and meteor showers

NASA Technical Reports Server (NTRS)

Kulikova, N. V.

1987-01-01

Prediction of short lived increases in the cosmic dust influx, the concentration in lower thermosphere of atoms and ions of meteor origin and the determination of the frequency of micrometeor impacts on spacecraft are all of scientific and practical interest and all require adequate models of meteor showers at an early stage of their existence. A Monte Carlo model of meteor matter ejection from a parent body at any point of space was worked out by other researchers. This scheme is described. According to the scheme, the formation of ten well known meteor streams was simulated and the possibility of genetic affinity of each of them with the most probable parent comet was analyzed. Some of the results are presented.

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.

Quantum Monte Carlo calculations of NiO

NASA Astrophysics Data System (ADS)

Maezono, Ryo; Towler, Mike D.; Needs, Richard. J.

2008-03-01

We describe variational and diffusion quantum Monte Carlo (VMC and DMC) calculations [1] of NiO using a 1024-electron simulation cell. We have used a smooth, norm-conserving, Dirac-Fock pseudopotential [2] in our work. Our trial wave functions were of Slater-Jastrow form, containing orbitals generated in Gaussian-basis UHF periodic calculations. Jastrow factor is optimized using variance minimization with optimized cutoff lengths using the same scheme as our previous work. [4] We apply the lattice regulated scheme [5] to evaluate non-local pseudopotentials in DMC and find the scheme improves the smoothness of the energy-volume curve. [1] CASINO ver.2.1 User Manual, University of Cambridge (2007). [2] J.R. Trail et.al., J. Chem. Phys. 122, 014112 (2005). [3] CRYSTAL98 User's Manual, University of Torino (1998). [4] Ryo Maezono et.al., Phys. Rev. Lett., 98, 025701 (2007). [5] Michele Casula, Phys. Rev. B 74, 161102R (2006).

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.

A GPU-based large-scale Monte Carlo simulation method for systems with long-range interactions

NASA Astrophysics Data System (ADS)

Liang, Yihao; Xing, Xiangjun; Li, Yaohang

2017-06-01

In this work we present an efficient implementation of Canonical Monte Carlo simulation for Coulomb many body systems on graphics processing units (GPU). Our method takes advantage of the GPU Single Instruction, Multiple Data (SIMD) architectures, and adopts the sequential updating scheme of Metropolis algorithm. It makes no approximation in the computation of energy, and reaches a remarkable 440-fold speedup, compared with the serial implementation on CPU. We further use this method to simulate primitive model electrolytes, and measure very precisely all ion-ion pair correlation functions at high concentrations. From these data, we extract the renormalized Debye length, renormalized valences of constituent ions, and renormalized dielectric constants. These results demonstrate unequivocally physics beyond the classical Poisson-Boltzmann theory.

Algorithms for adaptive stochastic control for a class of linear systems

NASA Technical Reports Server (NTRS)

Toda, M.; Patel, R. V.

1977-01-01

Control of linear, discrete time, stochastic systems with unknown control gain parameters is discussed. Two suboptimal adaptive control schemes are derived: one is based on underestimating future control and the other is based on overestimating future control. Both schemes require little on-line computation and incorporate in their control laws some information on estimation errors. The performance of these laws is studied by Monte Carlo simulations on a computer. Two single input, third order systems are considered, one stable and the other unstable, and the performance of the two adaptive control schemes is compared with that of the scheme based on enforced certainty equivalence and the scheme where the control gain parameters are known.

State estimation of stochastic non-linear hybrid dynamic system using an interacting multiple model algorithm.

PubMed

Elenchezhiyan, M; Prakash, J

2015-09-01

In this work, state estimation schemes for non-linear hybrid dynamic systems subjected to stochastic state disturbances and random errors in measurements using interacting multiple-model (IMM) algorithms are formulated. In order to compute both discrete modes and continuous state estimates of a hybrid dynamic system either an IMM extended Kalman filter (IMM-EKF) or an IMM based derivative-free Kalman filters is proposed in this study. The efficacy of the proposed IMM based state estimation schemes is demonstrated by conducting Monte-Carlo simulation studies on the two-tank hybrid system and switched non-isothermal continuous stirred tank reactor system. Extensive simulation studies reveal that the proposed IMM based state estimation schemes are able to generate fairly accurate continuous state estimates and discrete modes. In the presence and absence of sensor bias, the simulation studies reveal that the proposed IMM unscented Kalman filter (IMM-UKF) based simultaneous state and parameter estimation scheme outperforms multiple-model UKF (MM-UKF) based simultaneous state and parameter estimation scheme. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Girsanov's transformation based variance reduced Monte Carlo simulation schemes for reliability estimation in nonlinear stochastic dynamics

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

Kanjilal, Oindrila, E-mail: oindrila@civil.iisc.ernet.in; Manohar, C.S., E-mail: manohar@civil.iisc.ernet.in

The study considers the problem of simulation based time variant reliability analysis of nonlinear randomly excited dynamical systems. Attention is focused on importance sampling strategies based on the application of Girsanov's transformation method. Controls which minimize the distance function, as in the first order reliability method (FORM), are shown to minimize a bound on the sampling variance of the estimator for the probability of failure. Two schemes based on the application of calculus of variations for selecting control signals are proposed: the first obtains the control force as the solution of a two-point nonlinear boundary value problem, and, the secondmore » explores the application of the Volterra series in characterizing the controls. The relative merits of these schemes, vis-à-vis the method based on ideas from the FORM, are discussed. Illustrative examples, involving archetypal single degree of freedom (dof) nonlinear oscillators, and a multi-degree of freedom nonlinear dynamical system, are presented. The credentials of the proposed procedures are established by comparing the solutions with pertinent results from direct Monte Carlo simulations. - Highlights: • The distance minimizing control forces minimize a bound on the sampling variance. • Establishing Girsanov controls via solution of a two-point boundary value problem. • Girsanov controls via Volterra's series representation for the transfer functions.« less

The Monte Carlo photoionization and moving-mesh radiation hydrodynamics code CMACIONIZE

NASA Astrophysics Data System (ADS)

Vandenbroucke, B.; Wood, K.

2018-04-01

We present the public Monte Carlo photoionization and moving-mesh radiation hydrodynamics code CMACIONIZE, which can be used to simulate the self-consistent evolution of HII regions surrounding young O and B stars, or other sources of ionizing radiation. The code combines a Monte Carlo photoionization algorithm that uses a complex mix of hydrogen, helium and several coolants in order to self-consistently solve for the ionization and temperature balance at any given type, with a standard first order hydrodynamics scheme. The code can be run as a post-processing tool to get the line emission from an existing simulation snapshot, but can also be used to run full radiation hydrodynamical simulations. Both the radiation transfer and the hydrodynamics are implemented in a general way that is independent of the grid structure that is used to discretize the system, allowing it to be run both as a standard fixed grid code, but also as a moving-mesh code.

OWL: A scalable Monte Carlo simulation suite for finite-temperature study of materials

NASA Astrophysics Data System (ADS)

Li, Ying Wai; Yuk, Simuck F.; Cooper, Valentino R.; Eisenbach, Markus; Odbadrakh, Khorgolkhuu

The OWL suite is a simulation package for performing large-scale Monte Carlo simulations. Its object-oriented, modular design enables it to interface with various external packages for energy evaluations. It is therefore applicable to study the finite-temperature properties for a wide range of systems: from simple classical spin models to materials where the energy is evaluated by ab initio methods. This scheme not only allows for the study of thermodynamic properties based on first-principles statistical mechanics, it also provides a means for massive, multi-level parallelism to fully exploit the capacity of modern heterogeneous computer architectures. We will demonstrate how improved strong and weak scaling is achieved by employing novel, parallel and scalable Monte Carlo algorithms, as well as the applications of OWL to a few selected frontier materials research problems. This research was supported by the Office of Science of the Department of Energy under contract DE-AC05-00OR22725.

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.

Wavelet-based surrogate time series for multiscale simulation of heterogeneous catalysis

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

Savara, Aditya Ashi; Daw, C. Stuart; Xiong, Qingang

We propose a wavelet-based scheme that encodes the essential dynamics of discrete microscale surface reactions in a form that can be coupled with continuum macroscale flow simulations with high computational efficiency. This makes it possible to simulate the dynamic behavior of reactor-scale heterogeneous catalysis without requiring detailed concurrent simulations at both the surface and continuum scales using different models. Our scheme is based on the application of wavelet-based surrogate time series that encodes the essential temporal and/or spatial fine-scale dynamics at the catalyst surface. The encoded dynamics are then used to generate statistically equivalent, randomized surrogate time series, which canmore » be linked to the continuum scale simulation. As a result, we illustrate an application of this approach using two different kinetic Monte Carlo simulations with different characteristic behaviors typical for heterogeneous chemical reactions.« less

Wavelet-based surrogate time series for multiscale simulation of heterogeneous catalysis

DOE PAGES

Savara, Aditya Ashi; Daw, C. Stuart; Xiong, Qingang; ...

2016-01-28

We propose a wavelet-based scheme that encodes the essential dynamics of discrete microscale surface reactions in a form that can be coupled with continuum macroscale flow simulations with high computational efficiency. This makes it possible to simulate the dynamic behavior of reactor-scale heterogeneous catalysis without requiring detailed concurrent simulations at both the surface and continuum scales using different models. Our scheme is based on the application of wavelet-based surrogate time series that encodes the essential temporal and/or spatial fine-scale dynamics at the catalyst surface. The encoded dynamics are then used to generate statistically equivalent, randomized surrogate time series, which canmore » be linked to the continuum scale simulation. As a result, we illustrate an application of this approach using two different kinetic Monte Carlo simulations with different characteristic behaviors typical for heterogeneous chemical reactions.« less

A Distributed Data-Gathering Protocol Using AUV in Underwater Sensor Networks.

PubMed

Khan, Jawaad Ullah; Cho, Ho-Shin

2015-08-06

In this paper, we propose a distributed data-gathering scheme using an autonomous underwater vehicle (AUV) working as a mobile sink to gather data from a randomly distributed underwater sensor network where sensor nodes are clustered around several cluster headers. Unlike conventional data-gathering schemes where the AUV visits either every node or every cluster header, the proposed scheme allows the AUV to visit some selected nodes named path-nodes in a way that reduces the overall transmission power of the sensor nodes. Monte Carlo simulations are performed to investigate the performance of the proposed scheme compared with several preexisting techniques employing the AUV in terms of total amount of energy consumption, standard deviation of each node's energy consumption, latency to gather data at a sink, and controlling overhead. Simulation results show that the proposed scheme not only reduces the total energy consumption but also distributes the energy consumption more uniformly over the network, thereby increasing the lifetime of the network.

A Distributed Data-Gathering Protocol Using AUV in Underwater Sensor Networks

PubMed Central

Khan, Jawaad Ullah; Cho, Ho-Shin

2015-01-01

In this paper, we propose a distributed data-gathering scheme using an autonomous underwater vehicle (AUV) working as a mobile sink to gather data from a randomly distributed underwater sensor network where sensor nodes are clustered around several cluster headers. Unlike conventional data-gathering schemes where the AUV visits either every node or every cluster header, the proposed scheme allows the AUV to visit some selected nodes named path-nodes in a way that reduces the overall transmission power of the sensor nodes. Monte Carlo simulations are performed to investigate the performance of the proposed scheme compared with several preexisting techniques employing the AUV in terms of total amount of energy consumption, standard deviation of each node’s energy consumption, latency to gather data at a sink, and controlling overhead. Simulation results show that the proposed scheme not only reduces the total energy consumption but also distributes the energy consumption more uniformly over the network, thereby increasing the lifetime of the network. PMID:26287189

A Monte-Carlo Analysis of Organic Aerosol Volatility with Aerosol Microphysics

NASA Astrophysics Data System (ADS)

Gao, C. Y.; Tsigaridis, K.; Bauer, S. E.

2016-12-01

A newly developed box model scheme, MATRIX-VBS, includes the volatility-basis set (VBS) framework in an aerosol microphysical scheme MATRIX (Multiconfiguration Aerosol TRacker of mIXing state), which resolves aerosol mass and number concentrations and aerosol mixing state. The new scheme advanced the representation of organic aerosols in Earth system models by improving the traditional and simplistic treatment of organic aerosols as non-volatile and with a fixed size distribution. Further development includes adding the condensation of organics on coarse mode aerosols - dust and sea salt, thus making all organics in the system semi-volatile. To test and simplify the model, a Monte-Carlo analysis is performed to pin point which processes affect organics the most under which chemical and meteorological conditions. Since the model's parameterizations have the ability to capture a very wide range of conditions, from very clean to very polluted and for a wide range of meteorological conditions, all possible scenarios on Earth across the whole parameter space, including temperature, location, emissions and oxidant levels, are examined. The Monte-Carlo simulations provide quantitative information on the sensitivity of the newly developed model and help us understand how organics are affecting the size distribution, mixing state and volatility distribution at varying levels of meteorological conditions and pollution levels. In addition, these simulations give information on which parameters play a critical role in the aerosol distribution and evolution in the atmosphere and which do not, that will facilitate the simplification of the box model, an important step in its implementation in the global model.

Replica exchange and expanded ensemble simulations as Gibbs sampling: simple improvements for enhanced mixing.

PubMed

Chodera, John D; Shirts, Michael R

2011-11-21

The widespread popularity of replica exchange and expanded ensemble algorithms for simulating complex molecular systems in chemistry and biophysics has generated much interest in discovering new ways to enhance the phase space mixing of these protocols in order to improve sampling of uncorrelated configurations. Here, we demonstrate how both of these classes of algorithms can be considered as special cases of Gibbs sampling within a Markov chain Monte Carlo framework. Gibbs sampling is a well-studied scheme in the field of statistical inference in which different random variables are alternately updated from conditional distributions. While the update of the conformational degrees of freedom by Metropolis Monte Carlo or molecular dynamics unavoidably generates correlated samples, we show how judicious updating of the thermodynamic state indices--corresponding to thermodynamic parameters such as temperature or alchemical coupling variables--can substantially increase mixing while still sampling from the desired distributions. We show how state update methods in common use can lead to suboptimal mixing, and present some simple, inexpensive alternatives that can increase mixing of the overall Markov chain, reducing simulation times necessary to obtain estimates of the desired precision. These improved schemes are demonstrated for several common applications, including an alchemical expanded ensemble simulation, parallel tempering, and multidimensional replica exchange umbrella sampling.

Markov-chain model of classified atomistic transition states for discrete kinetic Monte Carlo simulations.

PubMed

Numazawa, Satoshi; Smith, Roger

2011-10-01

Classical harmonic transition state theory is considered and applied in discrete lattice cells with hierarchical transition levels. The scheme is then used to determine transitions that can be applied in a lattice-based kinetic Monte Carlo (KMC) atomistic simulation model. The model results in an effective reduction of KMC simulation steps by utilizing a classification scheme of transition levels for thermally activated atomistic diffusion processes. Thermally activated atomistic movements are considered as local transition events constrained in potential energy wells over certain local time periods. These processes are represented by Markov chains of multidimensional Boolean valued functions in three-dimensional lattice space. The events inhibited by the barriers under a certain level are regarded as thermal fluctuations of the canonical ensemble and accepted freely. Consequently, the fluctuating system evolution process is implemented as a Markov chain of equivalence class objects. It is shown that the process can be characterized by the acceptance of metastable local transitions. The method is applied to a problem of Au and Ag cluster growth on a rippled surface. The simulation predicts the existence of a morphology-dependent transition time limit from a local metastable to stable state for subsequent cluster growth by accretion. Excellent agreement with observed experimental results is obtained.

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

NASA Astrophysics Data System (ADS)

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

2014-06-01

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

CMacIonize: Monte Carlo photoionisation and moving-mesh radiation hydrodynamics

NASA Astrophysics Data System (ADS)

Vandenbroucke, Bert; Wood, Kenneth

2018-02-01

CMacIonize simulates the self-consistent evolution of HII regions surrounding young O and B stars, or other sources of ionizing radiation. The code combines a Monte Carlo photoionization algorithm that uses a complex mix of hydrogen, helium and several coolants in order to self-consistently solve for the ionization and temperature balance at any given time, with a standard first order hydrodynamics scheme. The code can be run as a post-processing tool to get the line emission from an existing simulation snapshot, but can also be used to run full radiation hydrodynamical simulations. Both the radiation transfer and the hydrodynamics are implemented in a general way that is independent of the grid structure that is used to discretize the system, allowing it to be run both as a standard fixed grid code and also as a moving-mesh code.

Numerical methods for the stochastic Landau-Lifshitz Navier-Stokes equations.

PubMed

Bell, John B; Garcia, Alejandro L; Williams, Sarah A

2007-07-01

The Landau-Lifshitz Navier-Stokes (LLNS) equations incorporate thermal fluctuations into macroscopic hydrodynamics by using stochastic fluxes. This paper examines explicit Eulerian discretizations of the full LLNS equations. Several computational fluid dynamics approaches are considered (including MacCormack's two-step Lax-Wendroff scheme and the piecewise parabolic method) and are found to give good results for the variance of momentum fluctuations. However, neither of these schemes accurately reproduces the fluctuations in energy or density. We introduce a conservative centered scheme with a third-order Runge-Kutta temporal integrator that does accurately produce fluctuations in density, energy, and momentum. A variety of numerical tests, including the random walk of a standing shock wave, are considered and results from the stochastic LLNS solver are compared with theory, when available, and with molecular simulations using a direct simulation Monte Carlo algorithm.

Multiple-time-stepping generalized hybrid Monte Carlo methods

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

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

2015-01-01

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

Comparison of the co-gasification of sewage sludge and food wastes and cost-benefit analysis of gasification- and incineration-based waste treatment schemes.

PubMed

You, Siming; Wang, Wei; Dai, Yanjun; Tong, Yen Wah; Wang, Chi-Hwa

2016-10-01

The compositions of food wastes and their co-gasification producer gas were compared with the existing data of sewage sludge. Results showed that food wastes are more favorable than sewage sludge for co-gasification based on residue generation and energy output. Two decentralized gasification-based schemes were proposed to dispose of the sewage sludge and food wastes in Singapore. Monte Carlo simulation-based cost-benefit analysis was conducted to compare the proposed schemes with the existing incineration-based scheme. It was found that the gasification-based schemes are financially superior to the incineration-based scheme based on the data of net present value (NPV), benefit-cost ratio (BCR), and internal rate of return (IRR). Sensitivity analysis was conducted to suggest effective measures to improve the economics of the schemes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Microsecond Simulations of DNA and Ion Transport in Nanopores with Novel Ion-Ion and Ion-Nucleotides Effective Potentials

PubMed Central

De Biase, Pablo M.; Markosyan, Suren; Noskov, Sergei

2014-01-01

We developed a novel scheme based on the Grand-Canonical Monte-Carlo/Brownian Dynamics (GCMC/BD) simulations and have extended it to studies of ion currents across three nanopores with the potential for ssDNA sequencing: solid-state nanopore Si3N4, α-hemolysin, and E111N/M113Y/K147N mutant. To describe nucleotide-specific ion dynamics compatible with ssDNA coarse-grained model, we used the Inverse Monte-Carlo protocol, which maps the relevant ion-nucleotide distribution functions from an all-atom MD simulations. Combined with the previously developed simulation platform for Brownian Dynamic (BD) simulations of ion transport, it allows for microsecond- and millisecond-long simulations of ssDNA dynamics in nanopore with a conductance computation accuracy that equals or exceeds that of all-atom MD simulations. In spite of the simplifications, the protocol produces results that agree with the results of previous studies on ion conductance across open channels and provide direct correlations with experimentally measured blockade currents and ion conductances that have been estimated from all-atom MD simulations. PMID:24738152

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

PubMed Central

Zaikin, Alexey; Míguez, Joaquín

2017-01-01

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

Fermi-level effects in semiconductor processing: A modeling scheme for atomistic kinetic Monte Carlo simulators

NASA Astrophysics Data System (ADS)

Martin-Bragado, I.; Castrillo, P.; Jaraiz, M.; Pinacho, R.; Rubio, J. E.; Barbolla, J.; Moroz, V.

2005-09-01

Atomistic process simulation is expected to play an important role for the development of next generations of integrated circuits. This work describes an approach for modeling electric charge effects in a three-dimensional atomistic kinetic Monte Carlo process simulator. The proposed model has been applied to the diffusion of electrically active boron and arsenic atoms in silicon. Several key aspects of the underlying physical mechanisms are discussed: (i) the use of the local Debye length to smooth out the atomistic point-charge distribution, (ii) algorithms to correctly update the charge state in a physically accurate and computationally efficient way, and (iii) an efficient implementation of the drift of charged particles in an electric field. High-concentration effects such as band-gap narrowing and degenerate statistics are also taken into account. The efficiency, accuracy, and relevance of the model are discussed.

An Object-Oriented Serial DSMC Simulation Package

NASA Astrophysics Data System (ADS)

Liu, Hongli; Cai, Chunpei

2011-05-01

A newly developed three-dimensional direct simulation Monte Carlo (DSMC) simulation package, named GRASP ("Generalized Rarefied gAs Simulation Package"), is reported in this paper. This package utilizes the concept of simulation engine, many C++ features and software design patterns. The package has an open architecture which can benefit further development and maintenance of the code. In order to reduce the engineering time for three-dimensional models, a hybrid grid scheme, combined with a flexible data structure compiled by C++ language, are implemented in this package. This scheme utilizes a local data structure based on the computational cell to achieve high performance on workstation processors. This data structure allows the DSMC algorithm to be very efficiently parallelized with domain decomposition and it provides much flexibility in terms of grid types. This package can utilize traditional structured, unstructured or hybrid grids within the framework of a single code to model arbitrarily complex geometries and to simulate rarefied gas flows. Benchmark test cases indicate that this package has satisfactory accuracy for complex rarefied gas flows.

On the modeling of the 2010 Gulf of Mexico Oil Spill

NASA Astrophysics Data System (ADS)

Mariano, A. J.; Kourafalou, V. H.; Srinivasan, A.; Kang, H.; Halliwell, G. R.; Ryan, E. H.; Roffer, M.

2011-09-01

Two oil particle trajectory forecasting systems were developed and applied to the 2010 Deepwater Horizon Oil Spill in the Gulf of Mexico. Both systems use ocean current fields from high-resolution numerical ocean circulation model simulations, Lagrangian stochastic models to represent unresolved sub-grid scale variability to advect oil particles, and Monte Carlo-based schemes for representing uncertain biochemical and physical processes. The first system assumes two-dimensional particle motion at the ocean surface, the oil is in one state, and the particle removal is modeled as a Monte Carlo process parameterized by a one number removal rate. Oil particles are seeded using both initial conditions based on observations and particles released at the location of the Maconda well. The initial conditions (ICs) of oil particle location for the two-dimensional surface oil trajectory forecasts are based on a fusing of all available information including satellite-based analyses. The resulting oil map is digitized into a shape file within which a polygon filling software generates longitude and latitude with variable particle density depending on the amount of oil present in the observations for the IC. The more complex system assumes three (light, medium, heavy) states for the oil, each state has a different removal rate in the Monte Carlo process, three-dimensional particle motion, and a particle size-dependent oil mixing model. Simulations from the two-dimensional forecast system produced results that qualitatively agreed with the uncertain "truth" fields. These simulations validated the use of our Monte Carlo scheme for representing oil removal by evaporation and other weathering processes. Eulerian velocity fields for predicting particle motion from data-assimilative models produced better particle trajectory distributions than a free running model with no data assimilation. Monte Carlo simulations of the three-dimensional oil particle trajectory, whose ensembles were generated by perturbing the size of the oil particles and the fraction in a given size range that are released at depth, the two largest unknowns in this problem. 36 realizations of the model were run with only subsurface oil releases. An average of these results yields that after three months, about 25% of the oil remains in the water column and that most of the oil is below 800 m.

From force-fields to photons: MD simulations of dye-labeled nucleic acids and Monte Carlo modeling of FRET

NASA Astrophysics Data System (ADS)

Goldner, Lori

2012-02-01

Fluorescence resonance energy transfer (FRET) is a powerful technique for understanding the structural fluctuations and transformations of RNA, DNA and proteins. Molecular dynamics (MD) simulations provide a window into the nature of these fluctuations on a different, faster, time scale. We use Monte Carlo methods to model and compare FRET data from dye-labeled RNA with what might be predicted from the MD simulation. With a few notable exceptions, the contribution of fluorophore and linker dynamics to these FRET measurements has not been investigated. We include the dynamics of the ground state dyes and linkers in our study of a 16mer double-stranded RNA. Water is included explicitly in the simulation. Cyanine dyes are attached at either the 3' or 5' ends with a 3 carbon linker, and differences in labeling schemes are discussed.[4pt] Work done in collaboration with Peker Milas, Benjamin D. Gamari, and Louis Parrot.

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.

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.

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.

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

Bertholon, François; Harant, Olivier; Bourlon, Bertrand

This article introduces a joined Bayesian estimation of gas samples issued from a gas chromatography column (GC) coupled with a NEMS sensor based on Giddings Eyring microscopic molecular stochastic model. The posterior distribution is sampled using a Monte Carlo Markov Chain and Gibbs sampling. Parameters are estimated using the posterior mean. This estimation scheme is finally applied on simulated and real datasets using this molecular stochastic forward model.

An efficient Bayesian data-worth analysis using a multilevel Monte Carlo method

NASA Astrophysics Data System (ADS)

Lu, Dan; Ricciuto, Daniel; Evans, Katherine

2018-03-01

Improving the understanding of subsurface systems and thus reducing prediction uncertainty requires collection of data. As the collection of subsurface data is costly, it is important that the data collection scheme is cost-effective. Design of a cost-effective data collection scheme, i.e., data-worth analysis, requires quantifying model parameter, prediction, and both current and potential data uncertainties. Assessment of these uncertainties in large-scale stochastic subsurface hydrological model simulations using standard Monte Carlo (MC) sampling or surrogate modeling is extremely computationally intensive, sometimes even infeasible. In this work, we propose an efficient Bayesian data-worth analysis using a multilevel Monte Carlo (MLMC) method. Compared to the standard MC that requires a significantly large number of high-fidelity model executions to achieve a prescribed accuracy in estimating expectations, the MLMC can substantially reduce computational costs using multifidelity approximations. Since the Bayesian data-worth analysis involves a great deal of expectation estimation, the cost saving of the MLMC in the assessment can be outstanding. While the proposed MLMC-based data-worth analysis is broadly applicable, we use it for a highly heterogeneous two-phase subsurface flow simulation to select an optimal candidate data set that gives the largest uncertainty reduction in predicting mass flow rates at four production wells. The choices made by the MLMC estimation are validated by the actual measurements of the potential data, and consistent with the standard MC estimation. But compared to the standard MC, the MLMC greatly reduces the computational costs.

A Monte-Carlo Analysis of Organic Volatility with Aerosol Microphysics

NASA Astrophysics Data System (ADS)

Gao, Chloe; Tsigaridis, Kostas; Bauer, Susanne E.

2017-04-01

A newly developed box model, MATRIX-VBS, includes the volatility-basis set (VBS) framework in an aerosol microphysical scheme MATRIX (Multiconfiguration Aerosol TRacker of mIXing state), which resolves aerosol mass and number concentrations and aerosol mixing state. The new scheme advanced the representation of organic aerosols in models by improving the traditional and simplistic treatment of organic aerosols as non-volatile and with a fixed size distribution. Further development includes adding the condensation of organics on coarse mode aerosols - dust and sea salt, thus making all organics in the system semi-volatile. To test and simplify the model, a Monte-Carlo analysis is performed to pin point which processes affect organics the most under varied chemical and meteorological conditions. Since the model's parameterizations have the ability to capture a very wide range of conditions, all possible scenarios on Earth across the whole parameter space, including temperature, humidity, location, emissions and oxidant levels, are examined. The Monte-Carlo simulations provide quantitative information on the sensitivity of the newly developed model and help us understand how organics are affecting the size distribution, mixing state and volatility distribution at varying levels of meteorological conditions and pollution levels. In addition, these simulations give information on which parameters play a critical role in the aerosol distribution and evolution in the atmosphere and which do not, that will facilitate the simplification of the box model, an important step in its implementation in the global model GISS ModelE as a module.

Flexible Charged Macromolecules on Mixed Fluid Lipid Membranes: Theory and Monte Carlo Simulations

PubMed Central

Tzlil, Shelly; Ben-Shaul, Avinoam

2005-01-01

Fluid membranes containing charged lipids enhance binding of oppositely charged proteins by mobilizing these lipids into the interaction zone, overcoming the concomitant entropic losses due to lipid segregation and lower conformational freedom upon macromolecule adsorption. We study this energetic-entropic interplay using Monte Carlo simulations and theory. Our model system consists of a flexible cationic polyelectrolyte, interacting, via Debye-Hückel and short-ranged repulsive potentials, with membranes containing neutral lipids, 1% tetravalent, and 10% (or 1%) monovalent anionic lipids. Adsorption onto a fluid membrane is invariably stronger than to an equally charged frozen or uniform membrane. Although monovalent lipids may suffice for binding rigid macromolecules, polyvalent counter-lipids (e.g., phosphatidylinositol 4,5 bisphosphate), whose entropy loss upon localization is negligible, are crucial for binding flexible macromolecules, which lose conformational entropy upon adsorption. Extending Rosenbluth's Monte Carlo scheme we directly simulate polymer adsorption on fluid membranes. Yet, we argue that similar information could be derived from a biased superposition of quenched membrane simulations. Using a simple cell model we account for surface concentration effects, and show that the average adsorption probabilities on annealed and quenched membranes coincide at vanishing surface concentrations. We discuss the relevance of our model to the electrostatic-switch mechanism of, e.g., the myristoylated alanine-rich C kinase substrate protein. PMID:16126828

Leading-Color Fully Differential Two-Loop Soft Corrections to QCD Dipole Showers

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

Dulat, Falko; Höche, Stefan; Prestel, Stefan

We compute the next-to-leading order corrections to soft-gluon radiation differentially in the one-emission phase space. We show that their contribution to the evolution of color dipoles can be obtained in a modified subtraction scheme, such that both one- and two-emission terms are amenable to Monte-Carlo integration. The two-loop cusp anomalous dimension is recovered naturally upon integration over the full phase space. We present two independent implementations of the new algorithm in the two event generators Pythia and Sherpa, and we compare the resulting fully differential simulation to the CMW scheme.

Fast analytical scatter estimation using graphics processing units.

PubMed

Ingleby, Harry; Lippuner, Jonas; Rickey, Daniel W; Li, Yue; Elbakri, Idris

2015-01-01

To develop a fast patient-specific analytical estimator of first-order Compton and Rayleigh scatter in cone-beam computed tomography, implemented using graphics processing units. The authors developed an analytical estimator for first-order Compton and Rayleigh scatter in a cone-beam computed tomography geometry. The estimator was coded using NVIDIA's CUDA environment for execution on an NVIDIA graphics processing unit. Performance of the analytical estimator was validated by comparison with high-count Monte Carlo simulations for two different numerical phantoms. Monoenergetic analytical simulations were compared with monoenergetic and polyenergetic Monte Carlo simulations. Analytical and Monte Carlo scatter estimates were compared both qualitatively, from visual inspection of images and profiles, and quantitatively, using a scaled root-mean-square difference metric. Reconstruction of simulated cone-beam projection data of an anthropomorphic breast phantom illustrated the potential of this method as a component of a scatter correction algorithm. The monoenergetic analytical and Monte Carlo scatter estimates showed very good agreement. The monoenergetic analytical estimates showed good agreement for Compton single scatter and reasonable agreement for Rayleigh single scatter when compared with polyenergetic Monte Carlo estimates. For a voxelized phantom with dimensions 128 × 128 × 128 voxels and a detector with 256 × 256 pixels, the analytical estimator required 669 seconds for a single projection, using a single NVIDIA 9800 GX2 video card. Accounting for first order scatter in cone-beam image reconstruction improves the contrast to noise ratio of the reconstructed images. The analytical scatter estimator, implemented using graphics processing units, provides rapid and accurate estimates of single scatter and with further acceleration and a method to account for multiple scatter may be useful for practical scatter correction schemes.

Monte Carlo simulation of reflection spectra of random multilayer media strongly scattering and absorbing light

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

Meglinskii, I V

2001-12-31

The reflection spectra of a multilayer random medium - the human skin - strongly scattering and absorbing light are numerically simulated. The propagation of light in the medium and the absorption spectra are simulated by the stochastic Monte Carlo method, which combines schemes for calculations of real photon trajectories and the statistical weight method. The model takes into account the inhomogeneous spatial distribution of blood vessels, water, and melanin, the degree of blood oxygenation, and the hematocrit index. The attenuation of the incident radiation caused by reflection and refraction at Fresnel boundaries of layers inside the medium is also considered.more » The simulated reflection spectra are compared with the experimental reflection spectra of the human skin. It is shown that a set of parameters that was used to describe the optical properties of skin layers and their possible variations, despite being far from complete, is nevertheless sufficient for the simulation of the reflection spectra of the human skin and their quantitative analysis. (laser applications and other topics in quantum electronics)« less

Self-optimized construction of transition rate matrices from accelerated atomistic simulations with Bayesian uncertainty quantification

NASA Astrophysics Data System (ADS)

Swinburne, Thomas D.; Perez, Danny

2018-05-01

A massively parallel method to build large transition rate matrices from temperature-accelerated molecular dynamics trajectories is presented. Bayesian Markov model analysis is used to estimate the expected residence time in the known state space, providing crucial uncertainty quantification for higher-scale simulation schemes such as kinetic Monte Carlo or cluster dynamics. The estimators are additionally used to optimize where exploration is performed and the degree of temperature acceleration on the fly, giving an autonomous, optimal procedure to explore the state space of complex systems. The method is tested against exactly solvable models and used to explore the dynamics of C15 interstitial defects in iron. Our uncertainty quantification scheme allows for accurate modeling of the evolution of these defects over timescales of several seconds.

Optimised Iteration in Coupled Monte Carlo - Thermal-Hydraulics Calculations

NASA Astrophysics Data System (ADS)

Hoogenboom, J. Eduard; Dufek, Jan

2014-06-01

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

Adaptive control of stochastic linear systems with unknown parameters. M.S. Thesis

NASA Technical Reports Server (NTRS)

Ku, R. T.

1972-01-01

The problem of optimal control of linear discrete-time stochastic dynamical system with unknown and, possibly, stochastically varying parameters is considered on the basis of noisy measurements. It is desired to minimize the expected value of a quadratic cost functional. Since the simultaneous estimation of the state and plant parameters is a nonlinear filtering problem, the extended Kalman filter algorithm is used. Several qualitative and asymptotic properties of the open loop feedback optimal control and the enforced separation scheme are discussed. Simulation results via Monte Carlo method show that, in terms of the performance measure, for stable systems the open loop feedback optimal control system is slightly better than the enforced separation scheme, while for unstable systems the latter scheme is far better.

Disturbance observer based model predictive control for accurate atmospheric entry of spacecraft

NASA Astrophysics Data System (ADS)

Wu, Chao; Yang, Jun; Li, Shihua; Li, Qi; Guo, Lei

2018-05-01

Facing the complex aerodynamic environment of Mars atmosphere, a composite atmospheric entry trajectory tracking strategy is investigated in this paper. External disturbances, initial states uncertainties and aerodynamic parameters uncertainties are the main problems. The composite strategy is designed to solve these problems and improve the accuracy of Mars atmospheric entry. This strategy includes a model predictive control for optimized trajectory tracking performance, as well as a disturbance observer based feedforward compensation for external disturbances and uncertainties attenuation. 500-run Monte Carlo simulations show that the proposed composite control scheme achieves more precise Mars atmospheric entry (3.8 km parachute deployment point distribution error) than the baseline control scheme (8.4 km) and integral control scheme (5.8 km).

Methods for High-Order Multi-Scale and Stochastic Problems Analysis, Algorithms, and Applications

DTIC Science & Technology

2016-10-17

finite volume schemes, discontinuous Galerkin finite element method, and related methods, for solving computational fluid dynamics (CFD) problems and...approximation for finite element methods. (3) The development of methods of simulation and analysis for the study of large scale stochastic systems of...laws, finite element method, Bernstein-Bezier finite elements , weakly interacting particle systems, accelerated Monte Carlo, stochastic networks 16

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.

Simulation of multivariate stationary stochastic processes using dimension-reduction representation methods

NASA Astrophysics Data System (ADS)

Liu, Zhangjun; Liu, Zenghui; Peng, Yongbo

2018-03-01

In view of the Fourier-Stieltjes integral formula of multivariate stationary stochastic processes, a unified formulation accommodating spectral representation method (SRM) and proper orthogonal decomposition (POD) is deduced. By introducing random functions as constraints correlating the orthogonal random variables involved in the unified formulation, the dimension-reduction spectral representation method (DR-SRM) and the dimension-reduction proper orthogonal decomposition (DR-POD) are addressed. The proposed schemes are capable of representing the multivariate stationary stochastic process with a few elementary random variables, bypassing the challenges of high-dimensional random variables inherent in the conventional Monte Carlo methods. In order to accelerate the numerical simulation, the technique of Fast Fourier Transform (FFT) is integrated with the proposed schemes. For illustrative purposes, the simulation of horizontal wind velocity field along the deck of a large-span bridge is proceeded using the proposed methods containing 2 and 3 elementary random variables. Numerical simulation reveals the usefulness of the dimension-reduction representation methods.

Fast Proton Titration Scheme for Multiscale Modeling of Protein Solutions.

PubMed

Teixeira, Andre Azevedo Reis; Lund, Mikael; da Silva, Fernando Luís Barroso

2010-10-12

Proton exchange between titratable amino acid residues and the surrounding solution gives rise to exciting electric processes in proteins. We present a proton titration scheme for studying acid-base equilibria in Metropolis Monte Carlo simulations where salt is treated at the Debye-Hückel level. The method, rooted in the Kirkwood model of impenetrable spheres, is applied on the three milk proteins α-lactalbumin, β-lactoglobulin, and lactoferrin, for which we investigate the net-charge, molecular dipole moment, and charge capacitance. Over a wide range of pH and salt conditions, excellent agreement is found with more elaborate simulations where salt is explicitly included. The implicit salt scheme is orders of magnitude faster than the explicit analog and allows for transparent interpretation of physical mechanisms. It is shown how the method can be expanded to multiscale modeling of aqueous salt solutions of many biomolecules with nonstatic charge distributions. Important examples are protein-protein aggregation, protein-polyelectrolyte complexation, and protein-membrane association.

Performance Analysis of Physical Layer Security of Opportunistic Scheduling in Multiuser Multirelay Cooperative Networks

PubMed Central

Shim, Kyusung; Do, Nhu Tri; An, Beongku

2017-01-01

In this paper, we study the physical layer security (PLS) of opportunistic scheduling for uplink scenarios of multiuser multirelay cooperative networks. To this end, we propose a low-complexity, yet comparable secrecy performance source relay selection scheme, called the proposed source relay selection (PSRS) scheme. Specifically, the PSRS scheme first selects the least vulnerable source and then selects the relay that maximizes the system secrecy capacity for the given selected source. Additionally, the maximal ratio combining (MRC) technique and the selection combining (SC) technique are considered at the eavesdropper, respectively. Investigating the system performance in terms of secrecy outage probability (SOP), closed-form expressions of the SOP are derived. The developed analysis is corroborated through Monte Carlo simulation. Numerical results show that the PSRS scheme significantly improves the secure ability of the system compared to that of the random source relay selection scheme, but does not outperform the optimal joint source relay selection (OJSRS) scheme. However, the PSRS scheme drastically reduces the required amount of channel state information (CSI) estimations compared to that required by the OJSRS scheme, specially in dense cooperative networks. PMID:28212286

Suppressing correlations in massively parallel simulations of lattice models

NASA Astrophysics Data System (ADS)

Kelling, Jeffrey; Ódor, Géza; Gemming, Sibylle

2017-11-01

For lattice Monte Carlo simulations parallelization is crucial to make studies of large systems and long simulation time feasible, while sequential simulations remain the gold-standard for correlation-free dynamics. Here, various domain decomposition schemes are compared, concluding with one which delivers virtually correlation-free simulations on GPUs. Extensive simulations of the octahedron model for 2 + 1 dimensional Kardar-Parisi-Zhang surface growth, which is very sensitive to correlation in the site-selection dynamics, were performed to show self-consistency of the parallel runs and agreement with the sequential algorithm. We present a GPU implementation providing a speedup of about 30 × over a parallel CPU implementation on a single socket and at least 180 × with respect to the sequential reference.

Performance and economic risk evaluation of dispersed solar thermal power systems by Monte Carlo simulation

NASA Technical Reports Server (NTRS)

Manvi, R.; Fujita, T.

1978-01-01

A preliminary comparative evaluation of dispersed solar thermal power plants utilizing advanced technologies available in 1985-2000 time frame is under way at JPL. The solar power plants of 50 KWe to 10 MWe size are equipped with two axis tracking parabolic dish concentrator systems operating at temperatures in excess of 1000 F. The energy conversion schemes under consideration include advanced steam, open and closed cycle gas turbines, stirling, and combined cycle. The energy storage systems include advanced batteries, liquid metal, and chemical. This paper outlines a simple methodology for a probabilistic assessment of such systems. Sources of uncertainty in the development of advanced systems are identified, and a computer Monte Carlo simulation is exercised to permit an analysis of the tradeoffs of the risk of failure versus the potential for large gains. Frequency distribution of energy cost for several alternatives are presented.

Standardization of 64Cu using an improved decay scheme

NASA Astrophysics Data System (ADS)

Amiot, M. N.; Bé, M. M.; Branger, T.; Cassette, P.; Lépy, M. C.; Ménesguen, Y.; Da Silva, I.

2012-08-01

A 64Cu solution was standardized by means of liquid scintillation counting. The activity of the solution was also determined with an ionization chamber whose response was simulated by using a Monte Carlo code. The photon emission intensities including K X-rays were determined to be I511=35.1 (3)%; I1346=0.472 (12)%, IKα=14.41 (15)%, IKβ=2.01 (3)%, respectively. 64Cu half-life was also determined as 12.718 (23) h. The new decay scheme used in the present work was established following the EURAMET 1085 exercise where a good agreement between activity measurement techniques was found.

Photodetachment and Doppler laser cooling of anionic molecules

NASA Astrophysics Data System (ADS)

Gerber, Sebastian; Fesel, Julian; Doser, Michael; Comparat, Daniel

2018-02-01

We propose to extend laser-cooling techniques, so far only achieved for neutral molecules, to molecular anions. A detailed computational study is performed for {{{C}}}2- molecules stored in Penning traps using GPU based Monte Carlo simulations. Two cooling schemes—Doppler laser cooling and photodetachment cooling—are investigated. The sympathetic cooling of antiprotons is studied for the Doppler cooling scheme, where it is shown that cooling of antiprotons to subKelvin temperatures could becomes feasible, with impacts on the field of antimatter physics. The presented cooling schemes also have applications for the generation of cold, negatively charged particle sources and for the sympathetic cooling of other molecular anions.

Single realization stochastic FDTD for weak scattering waves in biological random media.

PubMed

Tan, Tengmeng; Taflove, Allen; Backman, Vadim

2013-02-01

This paper introduces an iterative scheme to overcome the unresolved issues presented in S-FDTD (stochastic finite-difference time-domain) for obtaining ensemble average field values recently reported by Smith and Furse in an attempt to replace the brute force multiple-realization also known as Monte-Carlo approach with a single-realization scheme. Our formulation is particularly useful for studying light interactions with biological cells and tissues having sub-wavelength scale features. Numerical results demonstrate that such a small scale variation can be effectively modeled with a random medium problem which when simulated with the proposed S-FDTD indeed produces a very accurate result.

Single realization stochastic FDTD for weak scattering waves in biological random media

PubMed Central

Tan, Tengmeng; Taflove, Allen; Backman, Vadim

2015-01-01

This paper introduces an iterative scheme to overcome the unresolved issues presented in S-FDTD (stochastic finite-difference time-domain) for obtaining ensemble average field values recently reported by Smith and Furse in an attempt to replace the brute force multiple-realization also known as Monte-Carlo approach with a single-realization scheme. Our formulation is particularly useful for studying light interactions with biological cells and tissues having sub-wavelength scale features. Numerical results demonstrate that such a small scale variation can be effectively modeled with a random medium problem which when simulated with the proposed S-FDTD indeed produces a very accurate result. PMID:27158153

An update on the BQCD Hybrid Monte Carlo program

NASA Astrophysics Data System (ADS)

Haar, Taylor Ryan; Nakamura, Yoshifumi; Stüben, Hinnerk

2018-03-01

We present an update of BQCD, our Hybrid Monte Carlo program for simulating lattice QCD. BQCD is one of the main production codes of the QCDSF collaboration and is used by CSSM and in some Japanese finite temperature and finite density projects. Since the first publication of the code at Lattice 2010 the program has been extended in various ways. New features of the code include: dynamical QED, action modification in order to compute matrix elements by using Feynman-Hellman theory, more trace measurements (like Tr(D-n) for K, cSW and chemical potential reweighting), a more flexible integration scheme, polynomial filtering, term-splitting for RHMC, and a portable implementation of performance critical parts employing SIMD.

Constant-pH Hybrid Nonequilibrium Molecular Dynamics–Monte Carlo Simulation Method

PubMed Central

2016-01-01

A computational method is developed to carry out explicit solvent simulations of complex molecular systems under conditions of constant pH. In constant-pH simulations, preidentified ionizable sites are allowed to spontaneously protonate and deprotonate as a function of time in response to the environment and the imposed pH. The method, based on a hybrid scheme originally proposed by H. A. Stern (J. Chem. Phys.2007, 126, 164112), consists of carrying out short nonequilibrium molecular dynamics (neMD) switching trajectories to generate physically plausible configurations with changed protonation states that are subsequently accepted or rejected according to a Metropolis Monte Carlo (MC) criterion. To ensure microscopic detailed balance arising from such nonequilibrium switches, the atomic momenta are altered according to the symmetric two-ends momentum reversal prescription. To achieve higher efficiency, the original neMD–MC scheme is separated into two steps, reducing the need for generating a large number of unproductive and costly nonequilibrium trajectories. In the first step, the protonation state of a site is randomly attributed via a Metropolis MC process on the basis of an intrinsic pKa; an attempted nonequilibrium switch is generated only if this change in protonation state is accepted. This hybrid two-step inherent pKa neMD–MC simulation method is tested with single amino acids in solution (Asp, Glu, and His) and then applied to turkey ovomucoid third domain and hen egg-white lysozyme. Because of the simple linear increase in the computational cost relative to the number of titratable sites, the present method is naturally able to treat extremely large systems. PMID:26300709

Evaluation of the dose perturbation around gold and steel fiducial markers in a medical linac through Geant4 Monte Carlo simulation.

PubMed

Pontoriero, Antonio; Amato, Ernesto; Iatí, Giuseppe; De Renzis, Costantino; Pergolizzi, Stefano

2015-01-01

Purpose of this work was to study the dose perturbation within the target volume of a external MV radiation therapy when using metal fiducials. We developed a Monte Carlo simulation in Geant4 of a cylindrical fiducial made either of gold or of steel and simulated the photon irradiation beam originating from a medical Linac operating at 6, 10 or 15 MV. For each energy, two different irradiation schemes were simulated: a single 5 × 5-cm square field in the -x direction, and five 5 × 5-cm fields at 0°, 80°, 165°, 195° and 280°. In a single beam irradiation scheme, we observed a dose reduction behind fiducials varying from -20% for gold at 6 MV to -5% for steel at 15 MV, and a dose increment in front of the fiducial ranging from +33% for gold at 15 MV to +10% for steel at 6 MV. When five beams were employed, a dose increment ranging from +28% to +46% has been found around gold. Around a steel fiducial, an average increment of +17% was found, irrespective of the photon energy. When using a single beam, the decrement of dose behind both steel and gold markers increases with the photon energy. This effect vanishes when a multifield treatment is delivered; in this instance there is a dose increment around fiducials, according to both fiducial material and photon energy, with lower values for steel and 6 MV. This energy represents the best choice when fiducial markers are present inside the irradiated volume.

Outage Performance Analysis of Relay Selection Schemes in Wireless Energy Harvesting Cooperative Networks over Non-Identical Rayleigh Fading Channels †

PubMed Central

Do, Nhu Tri; Bao, Vo Nguyen Quoc; An, Beongku

2016-01-01

In this paper, we study relay selection in decode-and-forward wireless energy harvesting cooperative networks. In contrast to conventional cooperative networks, the relays harvest energy from the source’s radio-frequency radiation and then use that energy to forward the source information. Considering power splitting receiver architecture used at relays to harvest energy, we are concerned with the performance of two popular relay selection schemes, namely, partial relay selection (PRS) scheme and optimal relay selection (ORS) scheme. In particular, we analyze the system performance in terms of outage probability (OP) over independent and non-identical (i.n.i.d.) Rayleigh fading channels. We derive the closed-form approximations for the system outage probabilities of both schemes and validate the analysis by the Monte-Carlo simulation. The numerical results provide comprehensive performance comparison between the PRS and ORS schemes and reveal the effect of wireless energy harvesting on the outage performances of both schemes. Additionally, we also show the advantages and drawbacks of the wireless energy harvesting cooperative networks and compare to the conventional cooperative networks. PMID:26927119

Outage Performance Analysis of Relay Selection Schemes in Wireless Energy Harvesting Cooperative Networks over Non-Identical Rayleigh Fading Channels.

PubMed

Do, Nhu Tri; Bao, Vo Nguyen Quoc; An, Beongku

2016-02-26

In this paper, we study relay selection in decode-and-forward wireless energy harvesting cooperative networks. In contrast to conventional cooperative networks, the relays harvest energy from the source's radio-frequency radiation and then use that energy to forward the source information. Considering power splitting receiver architecture used at relays to harvest energy, we are concerned with the performance of two popular relay selection schemes, namely, partial relay selection (PRS) scheme and optimal relay selection (ORS) scheme. In particular, we analyze the system performance in terms of outage probability (OP) over independent and non-identical (i.n.i.d.) Rayleigh fading channels. We derive the closed-form approximations for the system outage probabilities of both schemes and validate the analysis by the Monte-Carlo simulation. The numerical results provide comprehensive performance comparison between the PRS and ORS schemes and reveal the effect of wireless energy harvesting on the outage performances of both schemes. Additionally, we also show the advantages and drawbacks of the wireless energy harvesting cooperative networks and compare to the conventional cooperative networks.

Condition Number as a Measure of Noise Performance of Diffusion Tensor Data Acquisition Schemes with MRI

NASA Astrophysics Data System (ADS)

Skare, Stefan; Hedehus, Maj; Moseley, Michael E.; Li, Tie-Qiang

2000-12-01

Diffusion tensor mapping with MRI can noninvasively track neural connectivity and has great potential for neural scientific research and clinical applications. For each diffusion tensor imaging (DTI) data acquisition scheme, the diffusion tensor is related to the measured apparent diffusion coefficients (ADC) by a transformation matrix. With theoretical analysis we demonstrate that the noise performance of a DTI scheme is dependent on the condition number of the transformation matrix. To test the theoretical framework, we compared the noise performances of different DTI schemes using Monte-Carlo computer simulations and experimental DTI measurements. Both the simulation and the experimental results confirmed that the noise performances of different DTI schemes are significantly correlated with the condition number of the associated transformation matrices. We therefore applied numerical algorithms to optimize a DTI scheme by minimizing the condition number, hence improving the robustness to experimental noise. In the determination of anisotropic diffusion tensors with different orientations, MRI data acquisitions using a single optimum b value based on the mean diffusivity can produce ADC maps with regional differences in noise level. This will give rise to rotational variances of eigenvalues and anisotropy when diffusion tensor mapping is performed using a DTI scheme with a limited number of diffusion-weighting gradient directions. To reduce this type of artifact, a DTI scheme with not only a small condition number but also a large number of evenly distributed diffusion-weighting gradients in 3D is preferable.

Enabling grand-canonical Monte Carlo: extending the flexibility of GROMACS through the GromPy python interface module.

PubMed

Pool, René; Heringa, Jaap; Hoefling, Martin; Schulz, Roland; Smith, Jeremy C; Feenstra, K Anton

2012-05-05

We report on a python interface to the GROMACS molecular simulation package, GromPy (available at https://github.com/GromPy). This application programming interface (API) uses the ctypes python module that allows function calls to shared libraries, for example, written in C. To the best of our knowledge, this is the first reported interface to the GROMACS library that uses direct library calls. GromPy can be used for extending the current GROMACS simulation and analysis modes. In this work, we demonstrate that the interface enables hybrid Monte-Carlo/molecular dynamics (MD) simulations in the grand-canonical ensemble, a simulation mode that is currently not implemented in GROMACS. For this application, the interplay between GromPy and GROMACS requires only minor modifications of the GROMACS source code, not affecting the operation, efficiency, and performance of the GROMACS applications. We validate the grand-canonical application against MD in the canonical ensemble by comparison of equations of state. The results of the grand-canonical simulations are in complete agreement with MD in the canonical ensemble. The python overhead of the grand-canonical scheme is only minimal. Copyright © 2012 Wiley Periodicals, Inc.

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

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

Turner, S.A.

1996-02-01

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

Impact of risk aversion and disease outbreak characteristics on the incentives of producers as a group to participate in animal disease insurance-A simulation.

PubMed

Niemi, Jarkko K; Heikkilä, Jaakko

2011-06-01

The participation of agricultural producers in financing losses caused by livestock epidemics has been debated in many countries. One of the issues raised is how reluctant producers are to participate voluntarily in the financing of disease losses before an outbreak occurs. This study contributes to the literature by examining whether disease losses should be financed through pre- or post-outbreak premiums or their combination. A Monte Carlo simulation was employed to illustrate the costs of financing two diseases of different profiles. The profiles differed in the probability in which the damage occurs and in the average damage per event. Three hypothetical financing schemes were compared based on their ability to reduce utility losses in the case of risk-neutral and risk-averse producer groups. The schemes were examined in a dynamic setting where premiums depended on the compensation history of the sector. If producers choose the preferred financing scheme based on utility losses, results suggest that the timing of the premiums, the transaction costs of the scheme, the degree of risk aversion of the producer, and the level and the volatility of premiums affect the choice of the financing scheme. Copyright © 2011 Elsevier B.V. All rights reserved.

PENGEOM-A general-purpose geometry package for Monte Carlo simulation of radiation transport in material systems defined by quadric surfaces

NASA Astrophysics Data System (ADS)

Almansa, Julio; Salvat-Pujol, Francesc; Díaz-Londoño, Gloria; Carnicer, Artur; Lallena, Antonio M.; Salvat, Francesc

2016-02-01

The Fortran subroutine package PENGEOM provides a complete set of tools to handle quadric geometries in Monte Carlo simulations of radiation transport. The material structure where radiation propagates is assumed to consist of homogeneous bodies limited by quadric surfaces. The PENGEOM subroutines (a subset of the PENELOPE code) track particles through the material structure, independently of the details of the physics models adopted to describe the interactions. Although these subroutines are designed for detailed simulations of photon and electron transport, where all individual interactions are simulated sequentially, they can also be used in mixed (class II) schemes for simulating the transport of high-energy charged particles, where the effect of soft interactions is described by the random-hinge method. The definition of the geometry and the details of the tracking algorithm are tailored to optimize simulation speed. The use of fuzzy quadric surfaces minimizes the impact of round-off errors. The provided software includes a Java graphical user interface for editing and debugging the geometry definition file and for visualizing the material structure. Images of the structure are generated by using the tracking subroutines and, hence, they describe the geometry actually passed to the simulation code.

A Zeeman slower for diatomic molecules

NASA Astrophysics Data System (ADS)

Petzold, M.; Kaebert, P.; Gersema, P.; Siercke, M.; Ospelkaus, S.

2018-04-01

We present a novel slowing scheme for beams of laser-coolable diatomic molecules reminiscent of Zeeman slowing of atomic beams. The scheme results in efficient compression of the one-dimensional velocity distribution to velocities trappable by magnetic or magneto-optical traps. We experimentally demonstrate our method in an atomic testbed and show an enhancement of flux below v = 35 m s‑1 by a factor of ≈20 compared to white light slowing. 3D Monte Carlo simulations performed to model the experiment show excellent agreement. We apply the same simulations to the prototype molecule 88Sr19F and expect 15% of the initial flux to be continuously compressed in a narrow velocity window at around 10 m s‑1. This is the first experimentally shown continuous and dissipative slowing technique in molecule-like level structures, promising to provide the missing link for the preparation of large ultracold molecular ensembles.

Size and habit evolution of PETN crystals - a lattice Monte Carlo study

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

Zepeda-Ruiz, L A; Maiti, A; Gee, R

2006-02-28

Starting from an accurate inter-atomic potential we develop a simple scheme of generating an ''on-lattice'' molecular potential of short range, which is then incorporated into a lattice Monte Carlo code for simulating size and shape evolution of nanocrystallites. As a specific example, we test such a procedure on the morphological evolution of a molecular crystal of interest to us, e.g., Pentaerythritol Tetranitrate, or PETN, and obtain realistic facetted structures in excellent agreement with experimental morphologies. We investigate several interesting effects including, the evolution of the initial shape of a ''seed'' to an equilibrium configuration, and the variation of growth morphologymore » as a function of the rate of particle addition relative to diffusion.« less

Fraction number of trapped atoms and velocity distribution function in sub-recoil laser cooling scheme

NASA Astrophysics Data System (ADS)

Alekseev, V. A.; Krylova, D. D.

1996-02-01

The analytical investigation of Bloch equations is used to describe the main features of the 1D velocity selective coherent population trapping cooling scheme. For the initial stage of cooling the fraction of cooled atoms is derived in the case of a Gaussian initial velocity distribution. At very long times of interaction the fraction of cooled atoms and the velocity distribution function are described by simple analytical formulae and do not depend on the initial distribution. These results are in good agreement with those of Bardou, Bouchaud, Emile, Aspect and Cohen-Tannoudji based on statistical analysis in terms of Levy flights and with Monte-Carlo simulations of the process.

SKIRT: Hybrid parallelization of radiative transfer simulations

NASA Astrophysics Data System (ADS)

Verstocken, S.; Van De Putte, D.; Camps, P.; Baes, M.

2017-07-01

We describe the design, implementation and performance of the new hybrid parallelization scheme in our Monte Carlo radiative transfer code SKIRT, which has been used extensively for modelling the continuum radiation of dusty astrophysical systems including late-type galaxies and dusty tori. The hybrid scheme combines distributed memory parallelization, using the standard Message Passing Interface (MPI) to communicate between processes, and shared memory parallelization, providing multiple execution threads within each process to avoid duplication of data structures. The synchronization between multiple threads is accomplished through atomic operations without high-level locking (also called lock-free programming). This improves the scaling behaviour of the code and substantially simplifies the implementation of the hybrid scheme. The result is an extremely flexible solution that adjusts to the number of available nodes, processors and memory, and consequently performs well on a wide variety of computing architectures.

Non-Cartesian MRI Reconstruction With Automatic Regularization Via Monte-Carlo SURE

PubMed Central

Weller, Daniel S.; Nielsen, Jon-Fredrik; Fessler, Jeffrey A.

2013-01-01

Magnetic resonance image (MRI) reconstruction from undersampled k-space data requires regularization to reduce noise and aliasing artifacts. Proper application of regularization however requires appropriate selection of associated regularization parameters. In this work, we develop a data-driven regularization parameter adjustment scheme that minimizes an estimate (based on the principle of Stein’s unbiased risk estimate—SURE) of a suitable weighted squared-error measure in k-space. To compute this SURE-type estimate, we propose a Monte-Carlo scheme that extends our previous approach to inverse problems (e.g., MRI reconstruction) involving complex-valued images. Our approach depends only on the output of a given reconstruction algorithm and does not require knowledge of its internal workings, so it is capable of tackling a wide variety of reconstruction algorithms and nonquadratic regularizers including total variation and those based on the ℓ1-norm. Experiments with simulated and real MR data indicate that the proposed approach is capable of providing near mean squared-error (MSE) optimal regularization parameters for single-coil undersampled non-Cartesian MRI reconstruction. PMID:23591478

Monte Carlo investigation on quantifying the retinal pigment epithelium melanin concentration by photoacoustic ophthalmoscopy.

PubMed

Shu, Xiao; Liu, Wenzhong; Zhang, Hao F

2015-10-01

The retinal pigment epithelium (RPE) melanin plays an important role in maintaining normal visual functions. A decrease in the RPE melanin concentration with aging is believed to be associated with several blinding diseases, including age-related macular degeneration. Quantifying the RPE melanin noninvasively is therefore important in evaluating the retinal health and aging conditions. Photoacoustic ophthalmoscopy (PAOM), as an optical absorption-based imaging technology, can potentially be applied to measure variations in the RPE melanin if the relationship between the detected photoacoustic (PA) signal amplitudes and the RPE melanin concentrations can be established. In this work, we tested the feasibility of using PA signals from retinal blood vessels as references to measure RPE melanin variation using Monte Carlo (MC) simulation. The influences from PAOM axial resolution, the depth and diameter of the retinal blood vessel, and the RPE thickness were examined. We proposed a calibration scheme by relating detected PA signals to the RPE melanin concentrations, and we found that the scheme is robust to these tested parameters. This study suggests that PAOM has the capability of quantitatively measuring the RPE melanin in vivo.

Monte Carlo investigation on quantifying the retinal pigment epithelium melanin concentration by photoacoustic ophthalmoscopy

NASA Astrophysics Data System (ADS)

Shu, Xiao; Liu, Wenzhong; Zhang, Hao F.

2015-10-01

The retinal pigment epithelium (RPE) melanin plays an important role in maintaining normal visual functions. A decrease in the RPE melanin concentration with aging is believed to be associated with several blinding diseases, including age-related macular degeneration. Quantifying the RPE melanin noninvasively is therefore important in evaluating the retinal health and aging conditions. Photoacoustic ophthalmoscopy (PAOM), as an optical absorption-based imaging technology, can potentially be applied to measure variations in the RPE melanin if the relationship between the detected photoacoustic (PA) signal amplitudes and the RPE melanin concentrations can be established. In this work, we tested the feasibility of using PA signals from retinal blood vessels as references to measure RPE melanin variation using Monte Carlo (MC) simulation. The influences from PAOM axial resolution, the depth and diameter of the retinal blood vessel, and the RPE thickness were examined. We proposed a calibration scheme by relating detected PA signals to the RPE melanin concentrations, and we found that the scheme is robust to these tested parameters. This study suggests that PAOM has the capability of quantitatively measuring the RPE melanin in vivo.

Coulomb interactions in charged fluids.

PubMed

Vernizzi, Graziano; Guerrero-García, Guillermo Iván; de la Cruz, Monica Olvera

2011-07-01

The use of Ewald summation schemes for calculating long-range Coulomb interactions, originally applied to ionic crystalline solids, is a very common practice in molecular simulations of charged fluids at present. Such a choice imposes an artificial periodicity which is generally absent in the liquid state. In this paper we propose a simple analytical O(N(2)) method which is based on Gauss's law for computing exactly the Coulomb interaction between charged particles in a simulation box, when it is averaged over all possible orientations of a surrounding infinite lattice. This method mitigates the periodicity typical of crystalline systems and it is suitable for numerical studies of ionic liquids, charged molecular fluids, and colloidal systems with Monte Carlo and molecular dynamics simulations.

Lattice Boltzmann accelerated direct simulation Monte Carlo for dilute gas flow simulations.

PubMed

Di Staso, G; Clercx, H J H; Succi, S; Toschi, F

2016-11-13

Hybrid particle-continuum computational frameworks permit the simulation of gas flows by locally adjusting the resolution to the degree of non-equilibrium displayed by the flow in different regions of space and time. In this work, we present a new scheme that couples the direct simulation Monte Carlo (DSMC) with the lattice Boltzmann (LB) method in the limit of isothermal flows. The former handles strong non-equilibrium effects, as they typically occur in the vicinity of solid boundaries, whereas the latter is in charge of the bulk flow, where non-equilibrium can be dealt with perturbatively, i.e. according to Navier-Stokes hydrodynamics. The proposed concurrent multiscale method is applied to the dilute gas Couette flow, showing major computational gains when compared with the full DSMC scenarios. In addition, it is shown that the coupling with LB in the bulk flow can speed up the DSMC treatment of the Knudsen layer with respect to the full DSMC case. In other words, LB acts as a DSMC accelerator.This article is part of the themed issue 'Multiscale modelling at the physics-chemistry-biology interface'. © 2016 The Author(s).

GPU accelerated Monte Carlo simulation of Brownian motors dynamics with CUDA

NASA Astrophysics Data System (ADS)

Spiechowicz, J.; Kostur, M.; Machura, L.

2015-06-01

This work presents an updated and extended guide on methods of a proper acceleration of the Monte Carlo integration of stochastic differential equations with the commonly available NVIDIA Graphics Processing Units using the CUDA programming environment. We outline the general aspects of the scientific computing on graphics cards and demonstrate them with two models of a well known phenomenon of the noise induced transport of Brownian motors in periodic structures. As a source of fluctuations in the considered systems we selected the three most commonly occurring noises: the Gaussian white noise, the white Poissonian noise and the dichotomous process also known as a random telegraph signal. The detailed discussion on various aspects of the applied numerical schemes is also presented. The measured speedup can be of the astonishing order of about 3000 when compared to a typical CPU. This number significantly expands the range of problems solvable by use of stochastic simulations, allowing even an interactive research in some cases.

Numerical stabilization of entanglement computation in auxiliary-field quantum Monte Carlo simulations of interacting many-fermion systems.

PubMed

Broecker, Peter; Trebst, Simon

2016-12-01

In the absence of a fermion sign problem, auxiliary-field (or determinantal) quantum Monte Carlo (DQMC) approaches have long been the numerical method of choice for unbiased, large-scale simulations of interacting many-fermion systems. More recently, the conceptual scope of this approach has been expanded by introducing ingenious schemes to compute entanglement entropies within its framework. On a practical level, these approaches, however, suffer from a variety of numerical instabilities that have largely impeded their applicability. Here we report on a number of algorithmic advances to overcome many of these numerical instabilities and significantly improve the calculation of entanglement measures in the zero-temperature projective DQMC approach, ultimately allowing us to reach similar system sizes as for the computation of conventional observables. We demonstrate the applicability of this improved DQMC approach by providing an entanglement perspective on the quantum phase transition from a magnetically ordered Mott insulator to a band insulator in the bilayer square lattice Hubbard model at half filling.

Can Condensing Organic Aerosols Lead to Less Cloud Particles?

NASA Astrophysics Data System (ADS)

Gao, C. Y.; Tsigaridis, K.; Bauer, S.

2017-12-01

We examined the impact of condensing organic aerosols on activated cloud number concentration in a new aerosol microphysics box model, MATRIX-VBS. The model includes the volatility-basis set (VBS) framework in an aerosol microphysical scheme MATRIX (Multiconfiguration Aerosol TRacker of mIXing state) that resolves aerosol mass and number concentrations and aerosol mixing state. Preliminary results show that by including the condensation of organic aerosols, the new model (MATRIX-VBS) has less activated particles compared to the original model (MATRIX), which treats organic aerosols as non-volatile. Parameters such as aerosol chemical composition, mass and number concentrations, and particle sizes which affect activated cloud number concentration are thoroughly evaluated via a suite of Monte-Carlo simulations. The Monte-Carlo simulations also provide information on which climate-relevant parameters play a critical role in the aerosol evolution in the atmosphere. This study also helps simplifying the newly developed box model which will soon be implemented in the global model GISS ModelE as a module.

COSMOABC: Likelihood-free inference via Population Monte Carlo Approximate Bayesian Computation

NASA Astrophysics Data System (ADS)

Ishida, E. E. O.; Vitenti, S. D. P.; Penna-Lima, M.; Cisewski, J.; de Souza, R. S.; Trindade, A. M. M.; Cameron, E.; Busti, V. C.; COIN Collaboration

2015-11-01

Approximate Bayesian Computation (ABC) enables parameter inference for complex physical systems in cases where the true likelihood function is unknown, unavailable, or computationally too expensive. It relies on the forward simulation of mock data and comparison between observed and synthetic catalogues. Here we present COSMOABC, a Python ABC sampler featuring a Population Monte Carlo variation of the original ABC algorithm, which uses an adaptive importance sampling scheme. The code is very flexible and can be easily coupled to an external simulator, while allowing to incorporate arbitrary distance and prior functions. As an example of practical application, we coupled COSMOABC with the NUMCOSMO library and demonstrate how it can be used to estimate posterior probability distributions over cosmological parameters based on measurements of galaxy clusters number counts without computing the likelihood function. COSMOABC is published under the GPLv3 license on PyPI and GitHub and documentation is available at http://goo.gl/SmB8EX.

Fe-vacancy ordering in superconducting K 1–xFe 2–ySe 2: First-principles calculations and Monte Carlo simulations

DOE PAGES

Fang, Yong; Tai, Yuan -Yen; Deng, Junkai; ...

2015-07-20

Fe vacancies in the 33 K superconductor K 1–xFe 2–ySe 2 show ordering schemes that may be correlated with its superconducting properties. First-principles calculations and kinetic Monte Carlo simulations lead to a very simple model for vacancy ordering. Repulsive dipolar interactions between Fe vacancies show three ground states: amore » $$\\sqrt{8}\\times \\sqrt{10}$$ rhombus-ordered structure for 12.5% vacancies, a $$\\sqrt{5}\\times \\sqrt{5}$$ squared lattice for 20% vacancies, and a $$\\sqrt{5}\\times \\sqrt{5}$$ rhombus-ordered structure for 25% vacancies. Other structural states are derived from these three ground states and may contain additional disordered spatial regions. As a result, the repulsive interaction between Fe vacancies arises from enhanced Fe–Se covalent bonds, which differs from the well-known attractive interaction of Fe vacancies in body-centered cubic Fe.« less

A collision scheme for hybrid fluid-particle simulation of plasmas

NASA Astrophysics Data System (ADS)

Nguyen, Christine; Lim, Chul-Hyun; Verboncoeur, John

2006-10-01

Desorption phenomena at the wall of a tokamak can lead to the introduction of impurities at the edge of a thermonuclear plasma. In particular, the use of carbon as a constituent of the tokamak wall, as planned for ITER, requires the study of carbon and hydrocarbon transport in the plasma, including understanding of collisional interaction with the plasma. These collisions can result in new hydrocarbons, hydrogen, secondary electrons and so on. Computational modeling is a primary tool for studying these phenomena. XOOPIC [1] and OOPD1 are widely used computer modeling tools for the simulation of plasmas. Both are particle type codes. Particle simulation gives more kinetic information than fluid simulation, but more computation time is required. In order to reduce this disadvantage, hybrid simulation has been developed, and applied to the modeling of collisions. Present particle simulation tools such as XOOPIC and OODP1 employ a Monte Carlo model for the collisions between particle species and a neutral background gas defined by its temperature and pressure. In fluid-particle hybrid plasma models, collisions include combinations of particle and fluid interactions categorized by projectile-target pairing: particle-particle, particle-fluid, and fluid-fluid. For verification of this hybrid collision scheme, we compare simulation results to analytic solutions for classical plasma models. [1] Verboncoeur et al. Comput. Phys. Comm. 87, 199 (1995).

Probabilistic treatment of the uncertainty from the finite size of weighted Monte Carlo data

NASA Astrophysics Data System (ADS)

Glüsenkamp, Thorsten

2018-06-01

Parameter estimation in HEP experiments often involves Monte Carlo simulation to model the experimental response function. A typical application are forward-folding likelihood analyses with re-weighting, or time-consuming minimization schemes with a new simulation set for each parameter value. Problematically, the finite size of such Monte Carlo samples carries intrinsic uncertainty that can lead to a substantial bias in parameter estimation if it is neglected and the sample size is small. We introduce a probabilistic treatment of this problem by replacing the usual likelihood functions with novel generalized probability distributions that incorporate the finite statistics via suitable marginalization. These new PDFs are analytic, and can be used to replace the Poisson, multinomial, and sample-based unbinned likelihoods, which covers many use cases in high-energy physics. In the limit of infinite statistics, they reduce to the respective standard probability distributions. In the general case of arbitrary Monte Carlo weights, the expressions involve the fourth Lauricella function FD, for which we find a new finite-sum representation in a certain parameter setting. The result also represents an exact form for Carlson's Dirichlet average Rn with n > 0, and thereby an efficient way to calculate the probability generating function of the Dirichlet-multinomial distribution, the extended divided difference of a monomial, or arbitrary moments of univariate B-splines. We demonstrate the bias reduction of our approach with a typical toy Monte Carlo problem, estimating the normalization of a peak in a falling energy spectrum, and compare the results with previously published methods from the literature.

Parallel Fokker–Planck-DSMC algorithm for rarefied gas flow simulation in complex domains at all Knudsen numbers

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

Küchlin, Stephan, E-mail: kuechlin@ifd.mavt.ethz.ch; Jenny, Patrick

2017-01-01

A major challenge for the conventional Direct Simulation Monte Carlo (DSMC) technique lies in the fact that its computational cost becomes prohibitive in the near continuum regime, where the Knudsen number (Kn)—characterizing the degree of rarefaction—becomes small. In contrast, the Fokker–Planck (FP) based particle Monte Carlo scheme allows for computationally efficient simulations of rarefied gas flows in the low and intermediate Kn regime. The Fokker–Planck collision operator—instead of performing binary collisions employed by the DSMC method—integrates continuous stochastic processes for the phase space evolution in time. This allows for time step and grid cell sizes larger than the respective collisionalmore » scales required by DSMC. Dynamically switching between the FP and the DSMC collision operators in each computational cell is the basis of the combined FP-DSMC method, which has been proven successful in simulating flows covering the whole Kn range. Until recently, this algorithm had only been applied to two-dimensional test cases. In this contribution, we present the first general purpose implementation of the combined FP-DSMC method. Utilizing both shared- and distributed-memory parallelization, this implementation provides the capability for simulations involving many particles and complex geometries by exploiting state of the art computer cluster technologies.« less

Rigorous-two-Steps scheme of TRIPOLI-4® Monte Carlo code validation for shutdown dose rate calculation

NASA Astrophysics Data System (ADS)

Jaboulay, Jean-Charles; Brun, Emeric; Hugot, François-Xavier; Huynh, Tan-Dat; Malouch, Fadhel; Mancusi, Davide; Tsilanizara, Aime

2017-09-01

After fission or fusion reactor shutdown the activated structure emits decay photons. For maintenance operations the radiation dose map must be established in the reactor building. Several calculation schemes have been developed to calculate the shutdown dose rate. These schemes are widely developed in fusion application and more precisely for the ITER tokamak. This paper presents the rigorous-two-steps scheme implemented at CEA. It is based on the TRIPOLI-4® Monte Carlo code and the inventory code MENDEL. The ITER shutdown dose rate benchmark has been carried out, results are in a good agreement with the other participant.

Advanced GF(3²) nonbinary LDPC coded modulation with non-uniform 9-QAM outperforming star 8-QAM.

PubMed

Liu, Tao; Lin, Changyu; Djordjevic, Ivan B

2016-06-27

In this paper, we first describe a 9-symbol non-uniform signaling scheme based on Huffman code, in which different symbols are transmitted with different probabilities. By using the Huffman procedure, prefix code is designed to approach the optimal performance. Then, we introduce an algorithm to determine the optimal signal constellation sets for our proposed non-uniform scheme with the criterion of maximizing constellation figure of merit (CFM). The proposed nonuniform polarization multiplexed signaling 9-QAM scheme has the same spectral efficiency as the conventional 8-QAM. Additionally, we propose a specially designed GF(3²) nonbinary quasi-cyclic LDPC code for the coded modulation system based on the 9-QAM non-uniform scheme. Further, we study the efficiency of our proposed non-uniform 9-QAM, combined with nonbinary LDPC coding, and demonstrate by Monte Carlo simulation that the proposed GF(2³) nonbinary LDPC coded 9-QAM scheme outperforms nonbinary LDPC coded uniform 8-QAM by at least 0.8dB.

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.

Accounting for the Decreasing Denitrification Potential of Aquifers in Travel-Time Based Reactive-Transport Models of Nitrate

NASA Astrophysics Data System (ADS)

Cirpka, O. A.; Loschko, M.; Wöhling, T.; Rudolph, D. L.

2017-12-01

Excess nitrate concentrations pose a threat to drinking-water production from groundwater in all regions of intensive agriculture worldwide. Natural organic matter, pyrite, and other reduced constituents of the aquifer matrix can be oxidized by aerobic and denitrifying bacteria, leading to self-cleaning of groundwater. Various studies have shown that the heterogeneity of both hydraulic and chemical aquifer properties influence the reactive behavior. Since the exact spatial distributions of these properties are not known, predictions on the temporal evolution of nitrate should be probabilistic. However, the computational effort of pde-based, spatially explicit multi-component reactive-transport simulations are so high that multiple model runs become impossible. Conversely, simplistic models that treat denitrification as first-order decay process miss important controls on denitrification. We have proposed a Lagrangian framework of nonlinear reactive transport, in which the electron-donor supply by the aquifer matrix is parameterized by a relative reactivity, that is the reaction rate relative to a standard reaction rate for identical solute concentrations (Loschko et al., 2016). We could show that reactive transport simplifies to solving a single ordinary dfferential equation in terms of the cumulative relative reactivity for a given combination of inflow concentrations. Simulating 3-D flow and reactive transport are computationally so inexpensive that Monte Carlo simulation become feasible. The original scheme did not consider a change of the relative reactivity over time, implying that the electron-donor pool in the matrix is infinite. We have modified the scheme to address the consumption of the reducing aquifer constituents upon the reactions. We also analyzed how a minimally complex model of aerobic respiration and denitrification could look like. With the revised scheme, we performed Monte Carlo simulations in 3-D domains, confirming that the uncertainty in predicting nitrate breakthrough depends on the scale of observation. Reference: M. Loschko, T. Wöhling, D.L. Rudolph, O.A. Cirpka: Cumulative relative reactivity: a concept for modeling aquifer-scale reactive transport. Water Resour. Res. 52(10): 8117-8137, 2016, doi: 10.1002/2016WR019080.

Modeling scintillator and WLS fiber signals for fast Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Sánchez, F. A.; Medina-Tanco, G.

2010-08-01

In this work we present a fast, robust and flexible procedure to simulate electronic signals of scintillator units: plastic scintillator material embedded with a wavelength shifter optical fiber coupled to a photo-multiplier tube which, in turn, is plugged to a front-end electronic board. The simple rationale behind the simulation chain allows to adapt the procedure to a broad range of detectors based on that kind of units. We show that, in order to produce realistic results, the simulation parameters can be properly calibrated against laboratory measurements and used thereafter as input of the simulations. Simulated signals of atmospheric background cosmic ray muons are presented and their main features analyzed and validated using actual measured data. Conversely, for any given practical application, the present simulation scheme can be used to find an adequate combination of photo-multiplier tube and optical fiber at the prototyping stage.

Following atomistic kinetics on experimental timescales with the kinetic Activation–Relaxation Technique

DOE PAGES

Mousseau, Normand; Béland, Laurent Karim; Brommer, Peter; ...

2014-12-24

The properties of materials, even at the atomic level, evolve on macroscopic time scales. Following this evolution through simulation has been a challenge for many years. For lattice-based activated diffusion, kinetic Monte Carlo has turned out to be an almost perfect solution. Various accelerated molecular dynamical schemes, for their part, have allowed the study on long time scale of relatively simple systems. There is still a desire and need, however, for methods able to handle complex materials such as alloys and disordered systems. In this paper, we review the kinetic Activation–Relaxation Technique (k-ART), one of a handful of off-lattice kineticmore » Monte Carlo methods, with on-the-fly cataloging, that have been proposed in the last few years.« less

Results of EAS characteristics calculations in the framework of the universal hadronic interaction model NEXUS

NASA Astrophysics Data System (ADS)

Kalmykov, N. N.; Ostapchenko, S. S.; Werner, K.

An extensive air shower (EAS) calculation scheme based on cascade equations and some EAS characteristics for energies 1014 -1017 eV are presented. The universal hadronic interaction model NEXUS is employed to provide the necessary data concerning hadron-air collisions. The influence of model assumptions on the longitudinal EAS development is discussed in the framework of the NEXUS and QGSJET models. Applied to EAS simulations, perspectives of combined Monte Carlo and numerical methods are considered.

Laser cooling of a trapped two-component Fermi gas

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

Idziaszek, Z.; Centrum Fizyki Teoretycznej, Polska Akademia Nauk, 02-668 Warsaw; Santos, L.

2003-04-01

We study the collective Raman cooling of a trapped two-component Fermi gas using quantum master equation in the festina lente regime, where the heating due to photon reabsorption can be neglected. The Monte Carlo simulations show that three-dimensional temperatures of the order of 0.008T{sub F} can be achieved. We analyze the heating related to background losses, and show that our laser-cooling scheme can maintain the temperature of the gas without significant additional losses.

Impurity self-energy in the strongly-correlated Bose systems

NASA Astrophysics Data System (ADS)

Panochko, Galyna; Pastukhov, Volodymyr; Vakarchuk, Ivan

2018-02-01

We proposed the nonperturbative scheme for the calculation of the impurity spectrum in the Bose system at zero temperature. The method is based on the path-integral formulation and describes an impurity as a zero-density ideal Fermi gas interacting with Bose system for which the action is written in terms of density fluctuations. On the example of the 3He atom immersed in the liquid helium-4 a good consistency with experimental data and results of Monte Carlo simulations is shown.

Optimal signal constellation design for ultra-high-speed optical transport in the presence of nonlinear phase noise.

PubMed

Liu, Tao; Djordjevic, Ivan B

2014-12-29

In this paper, we first describe an optimal signal constellation design algorithm suitable for the coherent optical channels dominated by the linear phase noise. Then, we modify this algorithm to be suitable for the nonlinear phase noise dominated channels. In optimization procedure, the proposed algorithm uses the cumulative log-likelihood function instead of the Euclidian distance. Further, an LDPC coded modulation scheme is proposed to be used in combination with signal constellations obtained by proposed algorithm. Monte Carlo simulations indicate that the LDPC-coded modulation schemes employing the new constellation sets, obtained by our new signal constellation design algorithm, outperform corresponding QAM constellations significantly in terms of transmission distance and have better nonlinearity tolerance.

Statistical inferences with jointly type-II censored samples from two Pareto distributions

NASA Astrophysics Data System (ADS)

Abu-Zinadah, Hanaa H.

2017-08-01

In the several fields of industries the product comes from more than one production line, which is required to work the comparative life tests. This problem requires sampling of the different production lines, then the joint censoring scheme is appeared. In this article we consider the life time Pareto distribution with jointly type-II censoring scheme. The maximum likelihood estimators (MLE) and the corresponding approximate confidence intervals as well as the bootstrap confidence intervals of the model parameters are obtained. Also Bayesian point and credible intervals of the model parameters are presented. The life time data set is analyzed for illustrative purposes. Monte Carlo results from simulation studies are presented to assess the performance of our proposed method.

Modeling cation/anion-water interactions in functional aluminosilicate structures.

PubMed

Richards, A J; Barnes, P; Collins, D R; Christodoulos, F; Clark, S M

1995-02-01

A need for the computer simulation of hydration/dehydration processes in functional aluminosilicate structures has been noted. Full and realistic simulations of these systems can be somewhat ambitious and require the aid of interactive computer graphics to identify key structural/chemical units, both in the devising of suitable water-ion simulation potentials and in the analysis of hydrogen-bonding schemes in the subsequent simulation studies. In this article, the former is demonstrated by the assembling of a range of essential water-ion potentials. These span the range of formal charges from +4e to -2e, and are evaluated in the context of three types of structure: a porous zeolite, calcium silicate cement, and layered clay. As an example of the latter, the computer graphics output from Monte Carlo computer simulation studies of hydration/dehydration in calcium-zeolite A is presented.

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

Borowik, Piotr, E-mail: pborow@poczta.onet.pl; Thobel, Jean-Luc, E-mail: jean-luc.thobel@iemn.univ-lille1.fr; Adamowicz, Leszek, E-mail: adamo@if.pw.edu.pl

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 propertiesmore » 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.« less

A multiscale method for modeling high-aspect-ratio micro/nano flows

NASA Astrophysics Data System (ADS)

Lockerby, Duncan; Borg, Matthew; Reese, Jason

2012-11-01

In this paper we present a new multiscale scheme for simulating micro/nano flows of high aspect ratio in the flow direction, e.g. within long ducts, tubes, or channels, of varying section. The scheme consists of applying a simple hydrodynamic description over the entire domain, and allocating micro sub-domains in very small ``slices'' of the channel. Every micro element is a molecular dynamics simulation (or other appropriate model, e.g., a direct simulation Monte Carlo method for micro-channel gas flows) over the local height of the channel/tube. The number of micro elements as well as their streamwise position is chosen to resolve the geometrical features of the macro channel. While there is no direct communication between individual micro elements, coupling occurs via an iterative imposition of mass and momentum-flux conservation on the macro scale. The greater the streamwise scale of the geometry, the more significant is the computational speed-up when compared to a full MD simulation. We test our new multiscale method on the case of a converging/diverging nanochannel conveying a simple Lennard-Jones liquid. We validate the results from our simulations by comparing them to a full MD simulation of the same test case. Supported by EPSRC Programme Grant, EP/I011927/1.

Distributed polar-coded OFDM based on Plotkin's construction for half duplex wireless communication

NASA Astrophysics Data System (ADS)

Umar, Rahim; Yang, Fengfan; Mughal, Shoaib; Xu, HongJun

2018-07-01

A Plotkin-based polar-coded orthogonal frequency division multiplexing (P-PC-OFDM) scheme is proposed and its bit error rate (BER) performance over additive white gaussian noise (AWGN), frequency selective Rayleigh, Rician and Nakagami-m fading channels has been evaluated. The considered Plotkin's construction possesses a parallel split in its structure, which motivated us to extend the proposed P-PC-OFDM scheme in a coded cooperative scenario. As the relay's effective collaboration has always been pivotal in the design of cooperative communication therefore, an efficient selection criterion for choosing the information bits has been inculcated at the relay node. To assess the BER performance of the proposed cooperative scheme, we have also upgraded conventional polar-coded cooperative scheme in the context of OFDM as an appropriate bench marker. The Monte Carlo simulated results revealed that the proposed Plotkin-based polar-coded cooperative OFDM scheme convincingly outperforms the conventional polar-coded cooperative OFDM scheme by 0.5 0.6 dBs over AWGN channel. This prominent gain in BER performance is made possible due to the bit-selection criteria and the joint successive cancellation decoding adopted at the relay and the destination nodes, respectively. Furthermore, the proposed coded cooperative schemes outperform their corresponding non-cooperative schemes by a gain of 1 dB under an identical condition.

Monte Carlo simulation methodology for the reliabilty of aircraft structures under damage tolerance considerations

NASA Astrophysics Data System (ADS)

Rambalakos, Andreas

Current federal aviation regulations in the United States and around the world mandate the need for aircraft structures to meet damage tolerance requirements through out the service life. These requirements imply that the damaged aircraft structure must maintain adequate residual strength in order to sustain its integrity that is accomplished by a continuous inspection program. The multifold objective of this research is to develop a methodology based on a direct Monte Carlo simulation process and to assess the reliability of aircraft structures. Initially, the structure is modeled as a parallel system with active redundancy comprised of elements with uncorrelated (statistically independent) strengths and subjected to an equal load distribution. Closed form expressions for the system capacity cumulative distribution function (CDF) are developed by expanding the current expression for the capacity CDF of a parallel system comprised by three elements to a parallel system comprised with up to six elements. These newly developed expressions will be used to check the accuracy of the implementation of a Monte Carlo simulation algorithm to determine the probability of failure of a parallel system comprised of an arbitrary number of statistically independent elements. The second objective of this work is to compute the probability of failure of a fuselage skin lap joint under static load conditions through a Monte Carlo simulation scheme by utilizing the residual strength of the fasteners subjected to various initial load distributions and then subjected to a new unequal load distribution resulting from subsequent fastener sequential failures. The final and main objective of this thesis is to present a methodology for computing the resulting gradual deterioration of the reliability of an aircraft structural component by employing a direct Monte Carlo simulation approach. The uncertainties associated with the time to crack initiation, the probability of crack detection, the exponent in the crack propagation rate (Paris equation) and the yield strength of the elements are considered in the analytical model. The structural component is assumed to consist of a prescribed number of elements. This Monte Carlo simulation methodology is used to determine the required non-periodic inspections so that the reliability of the structural component will not fall below a prescribed minimum level. A sensitivity analysis is conducted to determine the effect of three key parameters on the specification of the non-periodic inspection intervals: namely a parameter associated with the time to crack initiation, the applied nominal stress fluctuation and the minimum acceptable reliability level.

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.

Rotational Brownian Dynamics simulations of clathrin cage formation

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

Ilie, Ioana M.; Briels, Wim J.; MESA+ Institute for Nanotechnology, University of Twente, P.O. Box 217, 7500 AE Enschede

2014-08-14

The self-assembly of nearly rigid proteins into ordered aggregates is well suited for modeling by the patchy particle approach. Patchy particles are traditionally simulated using Monte Carlo methods, to study the phase diagram, while Brownian Dynamics simulations would reveal insights into the assembly dynamics. However, Brownian Dynamics of rotating anisotropic particles gives rise to a number of complications not encountered in translational Brownian Dynamics. We thoroughly test the Rotational Brownian Dynamics scheme proposed by Naess and Elsgaeter [Macromol. Theory Simul. 13, 419 (2004); Naess and Elsgaeter Macromol. Theory Simul. 14, 300 (2005)], confirming its validity. We then apply the algorithmmore » to simulate a patchy particle model of clathrin, a three-legged protein involved in vesicle production from lipid membranes during endocytosis. Using this algorithm we recover time scales for cage assembly comparable to those from experiments. We also briefly discuss the undulatory dynamics of the polyhedral cage.« less

Two schemes for quantitative photoacoustic tomography based on Monte Carlo simulation

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

Liu, Yubin; Yuan, Zhen, E-mail: zhenyuan@umac.mo

Purpose: The aim of this study was to develop novel methods for photoacoustically determining the optical absorption coefficient of biological tissues using Monte Carlo (MC) simulation. Methods: In this study, the authors propose two quantitative photoacoustic tomography (PAT) methods for mapping the optical absorption coefficient. The reconstruction methods combine conventional PAT with MC simulation in a novel way to determine the optical absorption coefficient of biological tissues or organs. Specifically, the authors’ two schemes were theoretically and experimentally examined using simulations, tissue-mimicking phantoms, ex vivo, and in vivo tests. In particular, the authors explored these methods using several objects withmore » different absorption contrasts embedded in turbid media and by using high-absorption media when the diffusion approximation was not effective at describing the photon transport. Results: The simulations and experimental tests showed that the reconstructions were quantitatively accurate in terms of the locations, sizes, and optical properties of the targets. The positions of the recovered targets were accessed by the property profiles, where the authors discovered that the off center error was less than 0.1 mm for the circular target. Meanwhile, the sizes and quantitative optical properties of the targets were quantified by estimating the full width half maximum of the optical absorption property. Interestingly, for the reconstructed sizes, the authors discovered that the errors ranged from 0 for relatively small-size targets to 26% for relatively large-size targets whereas for the recovered optical properties, the errors ranged from 0% to 12.5% for different cases. Conclusions: The authors found that their methods can quantitatively reconstruct absorbing objects of different sizes and optical contrasts even when the diffusion approximation is unable to accurately describe the photon propagation in biological tissues. In particular, their methods are able to resolve the intrinsic difficulties that occur when quantitative PAT is conducted by combining conventional PAT with the diffusion approximation or with radiation transport modeling.« less

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.

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.

Scalable Metropolis Monte Carlo for simulation of hard shapes

NASA Astrophysics Data System (ADS)

Anderson, Joshua A.; Eric Irrgang, M.; Glotzer, Sharon C.

2016-07-01

We design and implement a scalable hard particle Monte Carlo simulation toolkit (HPMC), and release it open source as part of HOOMD-blue. HPMC runs in parallel on many CPUs and many GPUs using domain decomposition. We employ BVH trees instead of cell lists on the CPU for fast performance, especially with large particle size disparity, and optimize inner loops with SIMD vector intrinsics on the CPU. Our GPU kernel proposes many trial moves in parallel on a checkerboard and uses a block-level queue to redistribute work among threads and avoid divergence. HPMC supports a wide variety of shape classes, including spheres/disks, unions of spheres, convex polygons, convex spheropolygons, concave polygons, ellipsoids/ellipses, convex polyhedra, convex spheropolyhedra, spheres cut by planes, and concave polyhedra. NVT and NPT ensembles can be run in 2D or 3D triclinic boxes. Additional integration schemes permit Frenkel-Ladd free energy computations and implicit depletant simulations. In a benchmark system of a fluid of 4096 pentagons, HPMC performs 10 million sweeps in 10 min on 96 CPU cores on XSEDE Comet. The same simulation would take 7.6 h in serial. HPMC also scales to large system sizes, and the same benchmark with 16.8 million particles runs in 1.4 h on 2048 GPUs on OLCF Titan.

Leveraging Gibbs Ensemble Molecular Dynamics and Hybrid Monte Carlo/Molecular Dynamics for Efficient Study of Phase Equilibria.

PubMed

Gartner, Thomas E; Epps, Thomas H; Jayaraman, Arthi

2016-11-08

We describe an extension of the Gibbs ensemble molecular dynamics (GEMD) method for studying phase equilibria. Our modifications to GEMD allow for direct control over particle transfer between phases and improve the method's numerical stability. Additionally, we found that the modified GEMD approach had advantages in computational efficiency in comparison to a hybrid Monte Carlo (MC)/MD Gibbs ensemble scheme in the context of the single component Lennard-Jones fluid. We note that this increase in computational efficiency does not compromise the close agreement of phase equilibrium results between the two methods. However, numerical instabilities in the GEMD scheme hamper GEMD's use near the critical point. We propose that the computationally efficient GEMD simulations can be used to map out the majority of the phase window, with hybrid MC/MD used as a follow up for conditions under which GEMD may be unstable (e.g., near-critical behavior). In this manner, we can capitalize on the contrasting strengths of these two methods to enable the efficient study of phase equilibria for systems that present challenges for a purely stochastic GEMC method, such as dense or low temperature systems, and/or those with complex molecular topologies.

Accelerated event-by-event Monte Carlo microdosimetric calculations of electrons and protons tracks on a multi-core CPU and a CUDA-enabled GPU.

PubMed

Kalantzis, Georgios; Tachibana, Hidenobu

2014-01-01

For microdosimetric calculations event-by-event Monte Carlo (MC) methods are considered the most accurate. The main shortcoming of those methods is the extensive requirement for computational time. In this work we present an event-by-event MC code of low projectile energy electron and proton tracks for accelerated microdosimetric MC simulations on a graphic processing unit (GPU). Additionally, a hybrid implementation scheme was realized by employing OpenMP and CUDA in such a way that both GPU and multi-core CPU were utilized simultaneously. The two implementation schemes have been tested and compared with the sequential single threaded MC code on the CPU. Performance comparison was established on the speed-up for a set of benchmarking cases of electron and proton tracks. A maximum speedup of 67.2 was achieved for the GPU-based MC code, while a further improvement of the speedup up to 20% was achieved for the hybrid approach. The results indicate the capability of our CPU-GPU implementation for accelerated MC microdosimetric calculations of both electron and proton tracks without loss of accuracy. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

The “Electrostatic-Switch” Mechanism: Monte Carlo Study of MARCKS-Membrane Interaction

PubMed Central

Tzlil, Shelly; Murray, Diana; Ben-Shaul, Avinoam

2008-01-01

The binding of the myristoylated alanine-rich C kinase substrate (MARCKS) to mixed, fluid, phospholipid membranes is modeled with a recently developed Monte Carlo simulation scheme. The central domain of MARCKS is both basic (ζ = +13) and hydrophobic (five Phe residues), and is flanked with two long chains, one ending with the myristoylated N-terminus. This natively unfolded protein is modeled as a flexible chain of “beads” representing the amino acid residues. The membranes contain neutral (ζ = 0), monovalent (ζ = −1), and tetravalent (ζ = −4) lipids, all of which are laterally mobile. MARCKS-membrane interaction is modeled by Debye-Hückel electrostatic potentials and semiempirical hydrophobic energies. In agreement with experiment, we find that membrane binding is mediated by electrostatic attraction of the basic domain to acidic lipids and membrane penetration of its hydrophobic moieties. The binding is opposed by configurational entropy losses and electrostatic membrane repulsion of the two long chains, and by lipid demixing upon adsorption. The simulations provide a physical model for how membrane-adsorbed MARCKS attracts several PIP2 lipids (ζ = −4) to its vicinity, and how phosphorylation of the central domain (ζ = +13 to ζ = +7) triggers an “electrostatic switch”, which weakens both the membrane interaction and PIP2 sequestration. This scheme captures the essence of “discreteness of charge” at membrane surfaces and can examine the formation of membrane-mediated multicomponent macromolecular complexes that function in many cellular processes. PMID:18502797

Relative frequencies of constrained events in stochastic processes: An analytical approach.

PubMed

Rusconi, S; Akhmatskaya, E; Sokolovski, D; Ballard, N; de la Cal, J C

2015-10-01

The stochastic simulation algorithm (SSA) and the corresponding Monte Carlo (MC) method are among the most common approaches for studying stochastic processes. They relies on knowledge of interevent probability density functions (PDFs) and on information about dependencies between all possible events. Analytical representations of a PDF are difficult to specify in advance, in many real life applications. Knowing the shapes of PDFs, and using experimental data, different optimization schemes can be applied in order to evaluate probability density functions and, therefore, the properties of the studied system. Such methods, however, are computationally demanding, and often not feasible. We show that, in the case where experimentally accessed properties are directly related to the frequencies of events involved, it may be possible to replace the heavy Monte Carlo core of optimization schemes with an analytical solution. Such a replacement not only provides a more accurate estimation of the properties of the process, but also reduces the simulation time by a factor of order of the sample size (at least ≈10(4)). The proposed analytical approach is valid for any choice of PDF. The accuracy, computational efficiency, and advantages of the method over MC procedures are demonstrated in the exactly solvable case and in the evaluation of branching fractions in controlled radical polymerization (CRP) of acrylic monomers. This polymerization can be modeled by a constrained stochastic process. Constrained systems are quite common, and this makes the method useful for various applications.

Hybrid finite-volume/transported PDF method for the simulation of turbulent reactive flows

NASA Astrophysics Data System (ADS)

Raman, Venkatramanan

A novel computational scheme is formulated for simulating turbulent reactive flows in complex geometries with detailed chemical kinetics. A Probability Density Function (PDF) based method that handles the scalar transport equation is coupled with an existing Finite Volume (FV) Reynolds-Averaged Navier-Stokes (RANS) flow solver. The PDF formulation leads to closed chemical source terms and facilitates the use of detailed chemical mechanisms without approximations. The particle-based PDF scheme is modified to handle complex geometries and grid structures. Grid-independent particle evolution schemes that scale linearly with the problem size are implemented in the Monte-Carlo PDF solver. A novel algorithm, in situ adaptive tabulation (ISAT) is employed to ensure tractability of complex chemistry involving a multitude of species. Several non-reacting test cases are performed to ascertain the efficiency and accuracy of the method. Simulation results from a turbulent jet-diffusion flame case are compared against experimental data. The effect of micromixing model, turbulence model and reaction scheme on flame predictions are discussed extensively. Finally, the method is used to analyze the Dow Chlorination Reactor. Detailed kinetics involving 37 species and 158 reactions as well as a reduced form with 16 species and 21 reactions are used. The effect of inlet configuration on reactor behavior and product distribution is analyzed. Plant-scale reactors exhibit quenching phenomena that cannot be reproduced by conventional simulation methods. The FV-PDF method predicts quenching accurately and provides insight into the dynamics of the reactor near extinction. The accuracy of the fractional time-stepping technique in discussed in the context of apparent multiple-steady states observed in a non-premixed feed configuration of the chlorination reactor.

Diffusion in confinement: kinetic simulations of self- and collective diffusion behavior of adsorbed gases

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

Abouelnasr, MKF; Smit, B

2012-01-01

The self- and collective-diffusion behaviors of adsorbed methane, helium, and isobutane in zeolite frameworks LTA, MFI, AFI, and SAS were examined at various concentrations using a range of molecular simulation techniques including Molecular Dynamics (MD), Monte Carlo (MC), Bennett-Chandler (BC), and kinetic Monte Carlo (kMC). This paper has three main results. (1) A novel model for the process of adsorbate movement between two large cages was created, allowing the formulation of a mixing rule for the re-crossing coefficient between two cages of unequal loading. The predictions from this mixing rule were found to agree quantitatively with explicit simulations. (2) Amore » new approach to the dynamically corrected Transition State Theory method to analytically calculate self-diffusion properties was developed, explicitly accounting for nanoscale fluctuations in concentration. This approach was demonstrated to quantitatively agree with previous methods, but is uniquely suited to be adapted to a kMC simulation that can simulate the collective-diffusion behavior. (3) While at low and moderate loadings the self- and collective-diffusion behaviors in LTA are observed to coincide, at higher concentrations they diverge. A change in the adsorbate packing scheme was shown to cause this divergence, a trait which is replicated in a kMC simulation that explicitly models this behavior. These phenomena were further investigated for isobutane in zeolite MFI, where MD results showed a separation in self- and collective-diffusion behavior that was reproduced with kMC simulations.« less

Diffusion in confinement: kinetic simulations of self- and collective diffusion behavior of adsorbed gases.

PubMed

Abouelnasr, Mahmoud K F; Smit, Berend

2012-09-07

The self- and collective-diffusion behaviors of adsorbed methane, helium, and isobutane in zeolite frameworks LTA, MFI, AFI, and SAS were examined at various concentrations using a range of molecular simulation techniques including Molecular Dynamics (MD), Monte Carlo (MC), Bennett-Chandler (BC), and kinetic Monte Carlo (kMC). This paper has three main results. (1) A novel model for the process of adsorbate movement between two large cages was created, allowing the formulation of a mixing rule for the re-crossing coefficient between two cages of unequal loading. The predictions from this mixing rule were found to agree quantitatively with explicit simulations. (2) A new approach to the dynamically corrected Transition State Theory method to analytically calculate self-diffusion properties was developed, explicitly accounting for nanoscale fluctuations in concentration. This approach was demonstrated to quantitatively agree with previous methods, but is uniquely suited to be adapted to a kMC simulation that can simulate the collective-diffusion behavior. (3) While at low and moderate loadings the self- and collective-diffusion behaviors in LTA are observed to coincide, at higher concentrations they diverge. A change in the adsorbate packing scheme was shown to cause this divergence, a trait which is replicated in a kMC simulation that explicitly models this behavior. These phenomena were further investigated for isobutane in zeolite MFI, where MD results showed a separation in self- and collective- diffusion behavior that was reproduced with kMC simulations.

A fast simulation method for radiation maps using interpolation in a virtual environment.

PubMed

Li, Meng-Kun; Liu, Yong-Kuo; Peng, Min-Jun; Xie, Chun-Li; Yang, Li-Qun

2018-05-10

In nuclear decommissioning, virtual simulation technology is a useful tool to achieve an effective work process by using virtual environments to represent the physical and logical scheme of a real decommissioning project. This technology is cost-saving and time-saving, with the capacity to develop various decommissioning scenarios and reduce the risk of retrofitting. The method utilises a radiation map in a virtual simulation as the basis for the assessment of exposure to a virtual human. In this paper, we propose a fast simulation method using a known radiation source. The method has a unique advantage over point kernel and Monte Carlo methods because it generates the radiation map using interpolation in a virtual environment. The simulation of the radiation map including the calculation and the visualisation were realised using UNITY and MATLAB. The feasibility of the proposed method was tested on a hypothetical case and the results obtained are discussed in this paper.

A polynomial chaos approach to the analysis of vehicle dynamics under uncertainty

NASA Astrophysics Data System (ADS)

Kewlani, Gaurav; Crawford, Justin; Iagnemma, Karl

2012-05-01

The ability of ground vehicles to quickly and accurately analyse their dynamic response to a given input is critical to their safety and efficient autonomous operation. In field conditions, significant uncertainty is associated with terrain and/or vehicle parameter estimates, and this uncertainty must be considered in the analysis of vehicle motion dynamics. Here, polynomial chaos approaches that explicitly consider parametric uncertainty during modelling of vehicle dynamics are presented. They are shown to be computationally more efficient than the standard Monte Carlo scheme, and experimental results compared with the simulation results performed on ANVEL (a vehicle simulator) indicate that the method can be utilised for efficient and accurate prediction of vehicle motion in realistic scenarios.

Structures and Intermittency in a Passive Scalar Model

NASA Astrophysics Data System (ADS)

Vergassola, M.; Mazzino, A.

1997-09-01

Perturbative expansions for intermittency scaling exponents in the Kraichnan passive scalar model [Phys. Rev. Lett. 72, 1016 (1994)] are investigated. A one-dimensional compressible model is considered for this purpose. High resolution Monte Carlo simulations using an Ito approach adapted to an advecting velocity field with a very short correlation time are performed and lead to clean scaling behavior for passive scalar structure functions. Perturbative predictions for the scaling exponents around the Gaussian limit of the model are derived as in the Kraichnan model. Their comparison with the simulations indicates that the scale-invariant perturbative scheme correctly captures the inertial range intermittency corrections associated with the intense localized structures observed in the dynamics.

cosmoabc: Likelihood-free inference for cosmology

NASA Astrophysics Data System (ADS)

Ishida, Emille E. O.; Vitenti, Sandro D. P.; Penna-Lima, Mariana; Trindade, Arlindo M.; Cisewski, Jessi; M.; de Souza, Rafael; Cameron, Ewan; Busti, Vinicius C.

2015-05-01

Approximate Bayesian Computation (ABC) enables parameter inference for complex physical systems in cases where the true likelihood function is unknown, unavailable, or computationally too expensive. It relies on the forward simulation of mock data and comparison between observed and synthetic catalogs. cosmoabc is a Python Approximate Bayesian Computation (ABC) sampler featuring a Population Monte Carlo variation of the original ABC algorithm, which uses an adaptive importance sampling scheme. The code can be coupled to an external simulator to allow incorporation of arbitrary distance and prior functions. When coupled with the numcosmo library, it has been used to estimate posterior probability distributions over cosmological parameters based on measurements of galaxy clusters number counts without computing the likelihood function.

Identification of terrain cover using the optimum polarimetric classifier

NASA Technical Reports Server (NTRS)

Kong, J. A.; Swartz, A. A.; Yueh, H. A.; Novak, L. M.; Shin, R. T.

1988-01-01

A systematic approach for the identification of terrain media such as vegetation canopy, forest, and snow-covered fields is developed using the optimum polarimetric classifier. The covariance matrices for various terrain cover are computed from theoretical models of random medium by evaluating the scattering matrix elements. The optimal classification scheme makes use of a quadratic distance measure and is applied to classify a vegetation canopy consisting of both trees and grass. Experimentally measured data are used to validate the classification scheme. Analytical and Monte Carlo simulated classification errors using the fully polarimetric feature vector are compared with classification based on single features which include the phase difference between the VV and HH polarization returns. It is shown that the full polarimetric results are optimal and provide better classification performance than single feature measurements.

An Unsplit Monte-Carlo solver for the resolution of the linear Boltzmann equation coupled to (stiff) Bateman equations

NASA Astrophysics Data System (ADS)

Bernede, Adrien; Poëtte, Gaël

2018-02-01

In this paper, we are interested in the resolution of the time-dependent problem of particle transport in a medium whose composition evolves with time due to interactions. As a constraint, we want to use of Monte-Carlo (MC) scheme for the transport phase. A common resolution strategy consists in a splitting between the MC/transport phase and the time discretization scheme/medium evolution phase. After going over and illustrating the main drawbacks of split solvers in a simplified configuration (monokinetic, scalar Bateman problem), we build a new Unsplit MC (UMC) solver improving the accuracy of the solutions, avoiding numerical instabilities, and less sensitive to time discretization. The new solver is essentially based on a Monte Carlo scheme with time dependent cross sections implying the on-the-fly resolution of a reduced model for each MC particle describing the time evolution of the matter along their flight path.

Accuracy of maximum likelihood and least-squares estimates in the lidar slope method with noisy data.

PubMed

Eberhard, Wynn L

2017-04-01

The maximum likelihood estimator (MLE) is derived for retrieving the extinction coefficient and zero-range intercept in the lidar slope method in the presence of random and independent Gaussian noise. Least-squares fitting, weighted by the inverse of the noise variance, is equivalent to the MLE. Monte Carlo simulations demonstrate that two traditional least-squares fitting schemes, which use different weights, are less accurate. Alternative fitting schemes that have some positive attributes are introduced and evaluated. The principal factors governing accuracy of all these schemes are elucidated. Applying these schemes to data with Poisson rather than Gaussian noise alters accuracy little, even when the signal-to-noise ratio is low. Methods to estimate optimum weighting factors in actual data are presented. Even when the weighting estimates are coarse, retrieval accuracy declines only modestly. Mathematical tools are described for predicting retrieval accuracy. Least-squares fitting with inverse variance weighting has optimum accuracy for retrieval of parameters from single-wavelength lidar measurements when noise, errors, and uncertainties are Gaussian distributed, or close to optimum when only approximately Gaussian.

Performance analysis of EM-based blind detection for ON-OFF keying modulation over atmospheric optical channels

NASA Astrophysics Data System (ADS)

Dabiri, Mohammad Taghi; Sadough, Seyed Mohammad Sajad

2018-04-01

In the free-space optical (FSO) links, atmospheric turbulence lead to scintillation in the received signal. Due to its ease of implementation, intensity modulation with direct detection (IM/DD) based on ON-OFF keying (OOK) is a popular signaling scheme in these systems. Over turbulence channel, to detect OOK symbols in a blind way, i.e., without sending pilot symbols, an expectation-maximization (EM)-based detection method was recently proposed in the literature related to free-space optical (FSO) communication. However, the performance of EM-based detection methods severely depends on the length of the observation interval (Ls). To choose the optimum values of Ls at target bit error rates (BER)s of FSO communications which are commonly lower than 10-9, Monte-Carlo simulations would be very cumbersome and require a very long processing time. To facilitate performance evaluation, in this letter we derive the analytic expressions for BER and outage probability. Numerical results validate the accuracy of our derived analytic expressions. Our results may serve to evaluate the optimum value for Ls without resorting to time-consuming Monte-Carlo simulations.

A united event grand canonical Monte Carlo study of partially doped polyaniline

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

Byshkin, M. S., E-mail: mbyshkin@unisa.it, E-mail: gmilano@unisa.it; Correa, A.; Buonocore, F.

2013-12-28

A Grand Canonical Monte Carlo scheme, based on united events combining protonation/deprotonation and insertion/deletion of HCl molecules is proposed for the generation of polyaniline structures at intermediate doping levels between 0% (PANI EB) and 100% (PANI ES). A procedure based on this scheme and subsequent structure relaxations using molecular dynamics is described and validated. Using the proposed scheme and the corresponding procedure, atomistic models of amorphous PANI-HCl structures were generated and studied at different doping levels. Density, structure factors, and solubility parameters were calculated. Their values agree well with available experimental data. The interactions of HCl with PANI have beenmore » studied and distribution of their energies has been analyzed. The procedure has also been extended to the generation of PANI models including adsorbed water and the effect of inclusion of water molecules on PANI properties has also been modeled and discussed. The protocol described here is general and the proposed United Event Grand Canonical Monte Carlo scheme can be easily extended to similar polymeric materials used in gas sensing and to other systems involving adsorption and chemical reactions steps.« less

Selected spectroscopic results on element 115 decay chains

DOE PAGES

Rudolph, D.; Forsberg, U.; Golubev, P.; ...

2014-08-24

We observed thirty correlated α-decay chains in an experiment studying the fusion-evaporation reaction 48Ca + 243Am at the GSI Helmholtzzentrum fur Schwerionenforschung. The decay characteristics of the majority of these 30 chains are consistent with previous observations and interpretations of such chains to originate from isotopes of element Z = 115. High-resolution α-photon coincidence spectroscopy in conjunction with comprehensive Monte-Carlo simulations allow to propose excitation schemes of atomic nuclei of the heaviest elements, thereby probing nuclear structure models near the 'Island of Stability' with unprecedented experimental precision.

Cubature on Wiener Space: Pathwise Convergence

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

Bayer, Christian, E-mail: christian.bayer@wias-berlin.de; Friz, Peter K., E-mail: friz@math.tu-berlin.de

2013-04-15

Cubature on Wiener space (Lyons and Victoir in Proc. R. Soc. Lond. A 460(2041):169-198, 2004) provides a powerful alternative to Monte Carlo simulation for the integration of certain functionals on Wiener space. More specifically, and in the language of mathematical finance, cubature allows for fast computation of European option prices in generic diffusion models.We give a random walk interpretation of cubature and similar (e.g. the Ninomiya-Victoir) weak approximation schemes. By using rough path analysis, we are able to establish weak convergence for general path-dependent option prices.

Introduction to the EC’s Marie Curie Initial Training Network Project: The European Training Network in Digital Medical Imaging for Radiotherapy (ENTERVISION)

PubMed Central

Dosanjh, Manjit; Cirilli, Manuela; Navin, Sparsh

2015-01-01

Between 2011 and 2015, the ENTERVISION Marie Curie Initial Training Network has been training 15 young researchers from a variety of backgrounds on topics ranging from in-beam Positron Emission Tomography or Single Particle Tomography techniques, to adaptive treatment planning, optical imaging, Monte Carlo simulations and biological phantom design. This article covers the main research activities, as well as the training scheme implemented by the participating institutes, which included academia, research, and industry. PMID:26697403

Discrete diffusion Lyman α radiative transfer

NASA Astrophysics Data System (ADS)

Smith, Aaron; Tsang, Benny T.-H.; Bromm, Volker; Milosavljević, Miloš

2018-06-01

Due to its accuracy and generality, Monte Carlo radiative transfer (MCRT) has emerged as the prevalent method for Lyα radiative transfer in arbitrary geometries. The standard MCRT encounters a significant efficiency barrier in the high optical depth, diffusion regime. Multiple acceleration schemes have been developed to improve the efficiency of MCRT but the noise from photon packet discretization remains a challenge. The discrete diffusion Monte Carlo (DDMC) scheme has been successfully applied in state-of-the-art radiation hydrodynamics (RHD) simulations. Still, the established framework is not optimal for resonant line transfer. Inspired by the DDMC paradigm, we present a novel extension to resonant DDMC (rDDMC) in which diffusion in space and frequency are treated on equal footing. We explore the robustness of our new method and demonstrate a level of performance that justifies incorporating the method into existing Lyα codes. We present computational speedups of ˜102-106 relative to contemporary MCRT implementations with schemes that skip scattering in the core of the line profile. This is because the rDDMC runtime scales with the spatial and frequency resolution rather than the number of scatterings—the latter is typically ∝τ0 for static media, or ∝(aτ0)2/3 with core-skipping. We anticipate new frontiers in which on-the-fly Lyα radiative transfer calculations are feasible in 3D RHD. More generally, rDDMC is transferable to any computationally demanding problem amenable to a Fokker-Planck approximation of frequency redistribution.

Monte Carlo simulation of energy-dispersive x-ray fluorescence and applications

NASA Astrophysics Data System (ADS)

Li, Fusheng

Four key components with regards to Monte Carlo Library Least Squares (MCLLS) have been developed by the author. These include: a comprehensive and accurate Monte Carlo simulation code - CEARXRF5 with Differential Operators (DO) and coincidence sampling, Detector Response Function (DRF), an integrated Monte Carlo - Library Least-Squares (MCLLS) Graphical User Interface (GUI) visualization System (MCLLSPro) and a new reproducible and flexible benchmark experiment setup. All these developments or upgrades enable the MCLLS approach to be a useful and powerful tool for a tremendous variety of elemental analysis applications. CEARXRF, a comprehensive and accurate Monte Carlo code for simulating the total and individual library spectral responses of all elements, has been recently upgraded to version 5 by the author. The new version has several key improvements: input file format fully compatible with MCNP5, a new efficient general geometry tracking code, versatile source definitions, various variance reduction techniques (e.g. weight window mesh and splitting, stratifying sampling, etc.), a new cross section data storage and accessing method which improves the simulation speed by a factor of four and new cross section data, upgraded differential operators (DO) calculation capability, and also an updated coincidence sampling scheme which including K-L and L-L coincidence X-Rays, while keeping all the capabilities of the previous version. The new Differential Operators method is powerful for measurement sensitivity study and system optimization. For our Monte Carlo EDXRF elemental analysis system, it becomes an important technique for quantifying the matrix effect in near real time when combined with the MCLLS approach. An integrated visualization GUI system has been developed by the author to perform elemental analysis using iterated Library Least-Squares method for various samples when an initial guess is provided. This software was built on the Borland C++ Builder platform and has a user-friendly interface to accomplish all qualitative and quantitative tasks easily. That is to say, the software enables users to run the forward Monte Carlo simulation (if necessary) or use previously calculated Monte Carlo library spectra to obtain the sample elemental composition estimation within a minute. The GUI software is easy to use with user-friendly features and has the capability to accomplish all related tasks in a visualization environment. It can be a powerful tool for EDXRF analysts. A reproducible experiment setup has been built and experiments have been performed to benchmark the system. Two types of Standard Reference Materials (SRM), stainless steel samples from National Institute of Standards and Technology (NIST) and aluminum alloy samples from Alcoa Inc., with certified elemental compositions, are tested with this reproducible prototype system using a 109Cd radioisotope source (20mCi) and a liquid nitrogen cooled Si(Li) detector. The results show excellent agreement between the calculated sample compositions and their reference values and the approach is very fast.

Adsorption of three-domain antifreeze proteins on ice: a study using LGMMAS theory and Monte Carlo simulations.

PubMed

Lopez Ortiz, Juan Ignacio; Torres, Paola; Quiroga, Evelina; Narambuena, Claudio F; Ramirez-Pastor, Antonio J

2017-11-29

In the present work, the adsorption of three-domain antifreeze proteins on ice is studied by combining a statistical thermodynamics based theory and Monte Carlo simulations. The three-domain protein is modeled by a trimer, and the ice surface is represented by a lattice of adsorption sites. The statistical theory, obtained from the exact partition function of non-interacting trimers adsorbed in one dimension and its extension to two dimensions, includes the configuration of the molecule in the adsorbed state, and allows the existence of multiple adsorption states for the protein. We called this theory "lattice-gas model of molecules with multiple adsorption states" (LGMMAS). The main thermodynamics functions (partial and total adsorption isotherms, Helmholtz free energy and configurational entropy) are obtained by solving a non-linear system of j equations, where j is the total number of possible adsorption states of the protein. The theoretical results are contrasted with Monte Carlo simulations, and a modified Langmuir model (MLM) where the arrangement of the adsorption sites in space is immaterial. The formalism introduced here provides exact results in one-dimensional lattices, and offers a very accurate description in two dimensions (2D). In addition, the scheme is capable of predicting the proportion between coverage degrees corresponding to different conformations in the same energetic state. In contrast, the MLM does not distinguish between different adsorption states, and shows severe discrepancies with the 2D simulation results. These findings indicate that the adsorbate structure and the lattice geometry play fundamental roles in determining the statistics of multistate adsorbed molecules, and consequently, must be included in the theory.

Adapting phase-switch Monte Carlo method for flexible organic molecules

NASA Astrophysics Data System (ADS)

Bridgwater, Sally; Quigley, David

2014-03-01

The role of cholesterol in lipid bilayers has been widely studied via molecular simulation, however, there has been relatively little work on crystalline cholesterol in biological environments. Recent work has linked the crystallisation of cholesterol in the body with heart attacks and strokes. Any attempt to model this process will require new models and advanced sampling methods to capture and quantify the subtle polymorphism of solid cholesterol, in which two crystalline phases are separated by a phase transition close to body temperature. To this end, we have adapted phase-switch Monte Carlo for use with flexible molecules, to calculate the free energy between crystal polymorphs to a high degree of accuracy. The method samples an order parameter , which divides a displacement space for the N molecules, into regions energetically favourable for each polymorph; which is traversed using biased Monte Carlo. Results for a simple model of butane will be presented, demonstrating that conformational flexibility can be correctly incorporated within a phase-switching scheme. Extension to a coarse grained model of cholesterol and the resulting free energies will be discussed.

Free energy computations by minimization of Kullback-Leibler divergence: An efficient adaptive biasing potential method for sparse representations

NASA Astrophysics Data System (ADS)

Bilionis, I.; Koutsourelakis, P. S.

2012-05-01

The present paper proposes an adaptive biasing potential technique for the computation of free energy landscapes. It is motivated by statistical learning arguments and unifies the tasks of biasing the molecular dynamics to escape free energy wells and estimating the free energy function, under the same objective of minimizing the Kullback-Leibler divergence between appropriately selected densities. It offers rigorous convergence diagnostics even though history dependent, non-Markovian dynamics are employed. It makes use of a greedy optimization scheme in order to obtain sparse representations of the free energy function which can be particularly useful in multidimensional cases. It employs embarrassingly parallelizable sampling schemes that are based on adaptive Sequential Monte Carlo and can be readily coupled with legacy molecular dynamics simulators. The sequential nature of the learning and sampling scheme enables the efficient calculation of free energy functions parametrized by the temperature. The characteristics and capabilities of the proposed method are demonstrated in three numerical examples.

Dual adaptive dynamic control of mobile robots using neural networks.

PubMed

Bugeja, Marvin K; Fabri, Simon G; Camilleri, Liberato

2009-02-01

This paper proposes two novel dual adaptive neural control schemes for the dynamic control of nonholonomic mobile robots. The two schemes are developed in discrete time, and the robot's nonlinear dynamic functions are assumed to be unknown. Gaussian radial basis function and sigmoidal multilayer perceptron neural networks are used for function approximation. In each scheme, the unknown network parameters are estimated stochastically in real time, and no preliminary offline neural network training is used. In contrast to other adaptive techniques hitherto proposed in the literature on mobile robots, the dual control laws presented in this paper do not rely on the heuristic certainty equivalence property but account for the uncertainty in the estimates. This results in a major improvement in tracking performance, despite the plant uncertainty and unmodeled dynamics. Monte Carlo simulation and statistical hypothesis testing are used to illustrate the effectiveness of the two proposed stochastic controllers as applied to the trajectory-tracking problem of a differentially driven wheeled mobile robot.

Uncertainty based modeling of rainfall-runoff: Combined differential evolution adaptive Metropolis (DREAM) and K-means clustering

NASA Astrophysics Data System (ADS)

Zahmatkesh, Zahra; Karamouz, Mohammad; Nazif, Sara

2015-09-01

Simulation of rainfall-runoff process in urban areas is of great importance considering the consequences and damages of extreme runoff events and floods. The first issue in flood hazard analysis is rainfall simulation. Large scale climate signals have been proved to be effective in rainfall simulation and prediction. In this study, an integrated scheme is developed for rainfall-runoff modeling considering different sources of uncertainty. This scheme includes three main steps of rainfall forecasting, rainfall-runoff simulation and future runoff prediction. In the first step, data driven models are developed and used to forecast rainfall using large scale climate signals as rainfall predictors. Due to high effect of different sources of uncertainty on the output of hydrologic models, in the second step uncertainty associated with input data, model parameters and model structure is incorporated in rainfall-runoff modeling and simulation. Three rainfall-runoff simulation models are developed for consideration of model conceptual (structural) uncertainty in real time runoff forecasting. To analyze the uncertainty of the model structure, streamflows generated by alternative rainfall-runoff models are combined, through developing a weighting method based on K-means clustering. Model parameters and input uncertainty are investigated using an adaptive Markov Chain Monte Carlo method. Finally, calibrated rainfall-runoff models are driven using the forecasted rainfall to predict future runoff for the watershed. The proposed scheme is employed in the case study of the Bronx River watershed, New York City. Results of uncertainty analysis of rainfall-runoff modeling reveal that simultaneous estimation of model parameters and input uncertainty significantly changes the probability distribution of the model parameters. It is also observed that by combining the outputs of the hydrological models using the proposed clustering scheme, the accuracy of runoff simulation in the watershed is remarkably improved up to 50% in comparison to the simulations by the individual models. Results indicate that the developed methodology not only provides reliable tools for rainfall and runoff modeling, but also adequate time for incorporating required mitigation measures in dealing with potentially extreme runoff events and flood hazard. Results of this study can be used in identification of the main factors affecting flood hazard analysis.

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

DOE PAGES

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

2017-03-05

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

Coarse graining of atactic polystyrene and its derivatives

NASA Astrophysics Data System (ADS)

Agrawal, Anupriya; Perahia, Dvora; Grest, Gary S.

2014-03-01

Capturing large length scales in polymers and soft matter while retaining atomistic properties is imperative to computational studies of dynamic systems. Here we present a new methodology developing coarse-grain model based on atomistic simulation of atactic polystyrene (PS). Similar to previous work by Fritz et al., each monomer is described by two coarse grained beads. In contrast to this earlier work where intramolecular potentials were based on Monte Carlo simulation of both isotactic and syndiotactic single PS molecule to capture stereochemistry, we obtained intramolecular interactions from a single molecular dynamics simulation of an all-atom atactic PS melts. The non-bonded interactions are obtained using the iterative Boltzmann inversion (IBI) scheme. This methodology has been extended to coarse graining of poly-(t-butyl-styrene) (PtBS). An additional coarse-grained bead is used to describe the t-butyl group. Similar to the process for PS, the intramolecular interactions are obtained from a single all atom atactic melt simulation. Starting from the non-bonded interactions for PS, we show that the IBI method for the non-bonded interactions of PtBS converges relatively fast. A generalized scheme for substituted PS is currently in development. We would like to acknowledge Prof. Kurt Kremer for helpful discussions during this work.

Simulation of selected genealogies.

PubMed

Slade, P F

2000-02-01

Algorithms for generating genealogies with selection conditional on the sample configuration of n genes in one-locus, two-allele haploid and diploid models are presented. Enhanced integro-recursions using the ancestral selection graph, introduced by S. M. Krone and C. Neuhauser (1997, Theor. Popul. Biol. 51, 210-237), which is the non-neutral analogue of the coalescent, enables accessible simulation of the embedded genealogy. A Monte Carlo simulation scheme based on that of R. C. Griffiths and S. Tavaré (1996, Math. Comput. Modelling 23, 141-158), is adopted to consider the estimation of ancestral times under selection. Simulations show that selection alters the expected depth of the conditional ancestral trees, depending on a mutation-selection balance. As a consequence, branch lengths are shown to be an ineffective criterion for detecting the presence of selection. Several examples are given which quantify the effects of selection on the conditional expected time to the most recent common ancestor. Copyright 2000 Academic Press.

An Efficient Monte Carlo Method for Modeling Radiative Transfer in Protoplanetary Disks

NASA Technical Reports Server (NTRS)

Kim, Stacy

2011-01-01

Monte Carlo methods have been shown to be effective and versatile in modeling radiative transfer processes to calculate model temperature profiles for protoplanetary disks. Temperatures profiles are important for connecting physical structure to observation and for understanding the conditions for planet formation and migration. However, certain areas of the disk such as the optically thick disk interior are under-sampled, or are of particular interest such as the snow line (where water vapor condenses into ice) and the area surrounding a protoplanet. To improve the sampling, photon packets can be preferentially scattered and reemitted toward the preferred locations at the cost of weighting packet energies to conserve the average energy flux. Here I report on the weighting schemes developed, how they can be applied to various models, and how they affect simulation mechanics and results. We find that improvements in sampling do not always imply similar improvements in temperature accuracies and calculation speeds.

Exact stochastic unraveling of an optical coherence dynamics by cumulant expansion

NASA Astrophysics Data System (ADS)

Olšina, Jan; Kramer, Tobias; Kreisbeck, Christoph; Mančal, Tomáš

2014-10-01

A numerically exact Monte Carlo scheme for calculation of open quantum system dynamics is proposed and implemented. The method consists of a Monte Carlo summation of a perturbation expansion in terms of trajectories in Liouville phase-space with respect to the coupling between the excited states of the molecule. The trajectories are weighted by a complex decoherence factor based on the second-order cumulant expansion of the environmental evolution. The method can be used with an arbitrary environment characterized by a general correlation function and arbitrary coupling strength. It is formally exact for harmonic environments, and it can be used with arbitrary temperature. Time evolution of an optically excited Frenkel exciton dimer representing a molecular exciton interacting with a charge transfer state is calculated by the proposed method. We calculate the evolution of the optical coherence elements of the density matrix and linear absorption spectrum, and compare them with the predictions of standard simulation methods.

A new approach to integrate GPU-based Monte Carlo simulation into inverse treatment plan optimization for proton therapy.

PubMed

Li, Yongbao; Tian, Zhen; Song, Ting; Wu, Zhaoxia; Liu, Yaqiang; Jiang, Steve; Jia, Xun

2017-01-07

Monte Carlo (MC)-based spot dose calculation is highly desired for inverse treatment planning in proton therapy because of its accuracy. Recent studies on biological optimization have also indicated the use of MC methods to compute relevant quantities of interest, e.g. linear energy transfer. Although GPU-based MC engines have been developed to address inverse optimization problems, their efficiency still needs to be improved. Also, the use of a large number of GPUs in MC calculation is not favorable for clinical applications. The previously proposed adaptive particle sampling (APS) method can improve the efficiency of MC-based inverse optimization by using the computationally expensive MC simulation more effectively. This method is more efficient than the conventional approach that performs spot dose calculation and optimization in two sequential steps. In this paper, we propose a computational library to perform MC-based spot dose calculation on GPU with the APS scheme. The implemented APS method performs a non-uniform sampling of the particles from pencil beam spots during the optimization process, favoring those from the high intensity spots. The library also conducts two computationally intensive matrix-vector operations frequently used when solving an optimization problem. This library design allows a streamlined integration of the MC-based spot dose calculation into an existing proton therapy inverse planning process. We tested the developed library in a typical inverse optimization system with four patient cases. The library achieved the targeted functions by supporting inverse planning in various proton therapy schemes, e.g. single field uniform dose, 3D intensity modulated proton therapy, and distal edge tracking. The efficiency was 41.6  ±  15.3% higher than the use of a GPU-based MC package in a conventional calculation scheme. The total computation time ranged between 2 and 50 min on a single GPU card depending on the problem size.

A new approach to integrate GPU-based Monte Carlo simulation into inverse treatment plan optimization for proton therapy

NASA Astrophysics Data System (ADS)

Li, Yongbao; Tian, Zhen; Song, Ting; Wu, Zhaoxia; Liu, Yaqiang; Jiang, Steve; Jia, Xun

2017-01-01

Monte Carlo (MC)-based spot dose calculation is highly desired for inverse treatment planning in proton therapy because of its accuracy. Recent studies on biological optimization have also indicated the use of MC methods to compute relevant quantities of interest, e.g. linear energy transfer. Although GPU-based MC engines have been developed to address inverse optimization problems, their efficiency still needs to be improved. Also, the use of a large number of GPUs in MC calculation is not favorable for clinical applications. The previously proposed adaptive particle sampling (APS) method can improve the efficiency of MC-based inverse optimization by using the computationally expensive MC simulation more effectively. This method is more efficient than the conventional approach that performs spot dose calculation and optimization in two sequential steps. In this paper, we propose a computational library to perform MC-based spot dose calculation on GPU with the APS scheme. The implemented APS method performs a non-uniform sampling of the particles from pencil beam spots during the optimization process, favoring those from the high intensity spots. The library also conducts two computationally intensive matrix-vector operations frequently used when solving an optimization problem. This library design allows a streamlined integration of the MC-based spot dose calculation into an existing proton therapy inverse planning process. We tested the developed library in a typical inverse optimization system with four patient cases. The library achieved the targeted functions by supporting inverse planning in various proton therapy schemes, e.g. single field uniform dose, 3D intensity modulated proton therapy, and distal edge tracking. The efficiency was 41.6  ±  15.3% higher than the use of a GPU-based MC package in a conventional calculation scheme. The total computation time ranged between 2 and 50 min on a single GPU card depending on the problem size.

A New Approach to Integrate GPU-based Monte Carlo Simulation into Inverse Treatment Plan Optimization for Proton Therapy

PubMed Central

Li, Yongbao; Tian, Zhen; Song, Ting; Wu, Zhaoxia; Liu, Yaqiang; Jiang, Steve; Jia, Xun

2016-01-01

Monte Carlo (MC)-based spot dose calculation is highly desired for inverse treatment planning in proton therapy because of its accuracy. Recent studies on biological optimization have also indicated the use of MC methods to compute relevant quantities of interest, e.g. linear energy transfer. Although GPU-based MC engines have been developed to address inverse optimization problems, their efficiency still needs to be improved. Also, the use of a large number of GPUs in MC calculation is not favorable for clinical applications. The previously proposed adaptive particle sampling (APS) method can improve the efficiency of MC-based inverse optimization by using the computationally expensive MC simulation more effectively. This method is more efficient than the conventional approach that performs spot dose calculation and optimization in two sequential steps. In this paper, we propose a computational library to perform MC-based spot dose calculation on GPU with the APS scheme. The implemented APS method performs a non-uniform sampling of the particles from pencil beam spots during the optimization process, favoring those from the high intensity spots. The library also conducts two computationally intensive matrix-vector operations frequently used when solving an optimization problem. This library design allows a streamlined integration of the MC-based spot dose calculation into an existing proton therapy inverse planning process. We tested the developed library in a typical inverse optimization system with four patient cases. The library achieved the targeted functions by supporting inverse planning in various proton therapy schemes, e.g. single field uniform dose, 3D intensity modulated proton therapy, and distal edge tracking. The efficiency was 41.6±15.3% higher than the use of a GPU-based MC package in a conventional calculation scheme. The total computation time ranged between 2 and 50 min on a single GPU card depending on the problem size. PMID:27991456

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.

Monte Carlo methods and their analysis for Coulomb collisions in multicomponent plasmas

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

Bobylev, A.V., E-mail: alexander.bobylev@kau.se; Potapenko, I.F., E-mail: firena@yandex.ru

2013-08-01

Highlights: •A general approach to Monte Carlo methods for multicomponent plasmas is proposed. •We show numerical tests for the two-component (electrons and ions) case. •An optimal choice of parameters for speeding up the computations is discussed. •A rigorous estimate of the error of approximation is proved. -- Abstract: A general approach to Monte Carlo methods for Coulomb collisions is proposed. Its key idea is an approximation of Landau–Fokker–Planck equations by Boltzmann equations of quasi-Maxwellian kind. It means that the total collision frequency for the corresponding Boltzmann equation does not depend on the velocities. This allows to make the simulation processmore » very simple since the collision pairs can be chosen arbitrarily, without restriction. It is shown that this approach includes the well-known methods of Takizuka and Abe (1977) [12] and Nanbu (1997) as particular cases, and generalizes the approach of Bobylev and Nanbu (2000). The numerical scheme of this paper is simpler than the schemes by Takizuka and Abe [12] and by Nanbu. We derive it for the general case of multicomponent plasmas and show some numerical tests for the two-component (electrons and ions) case. An optimal choice of parameters for speeding up the computations is also discussed. It is also proved that the order of approximation is not worse than O(√(ε)), where ε is a parameter of approximation being equivalent to the time step Δt in earlier methods. A similar estimate is obtained for the methods of Takizuka and Abe and Nanbu.« less

Simulation of gas adsorption on a surface and in slit pores with grand canonical and canonical kinetic Monte Carlo methods.

PubMed

Ustinov, E A; Do, D D

2012-08-21

We present for the first time in the literature a new scheme of kinetic Monte Carlo method applied on a grand canonical ensemble, which we call hereafter GC-kMC. It was shown recently that the kinetic Monte Carlo (kMC) scheme is a very effective tool for the analysis of equilibrium systems. It had been applied in a canonical ensemble to describe vapor-liquid equilibrium of argon over a wide range of temperatures, gas adsorption on a graphite open surface and in graphitic slit pores. However, in spite of the conformity of canonical and grand canonical ensembles, the latter is more relevant in the correct description of open systems; for example, the hysteresis loop observed in adsorption of gases in pores under sub-critical conditions can only be described with a grand canonical ensemble. Therefore, the present paper is aimed at an extension of the kMC to open systems. The developed GC-kMC was proved to be consistent with the results obtained with the canonical kMC (C-kMC) for argon adsorption on a graphite surface at 77 K and in graphitic slit pores at 87.3 K. We showed that in slit micropores the hexagonal packing in the layers adjacent to the pore walls is observed at high loadings even at temperatures above the triple point of the bulk phase. The potential and applicability of the GC-kMC are further shown with the correct description of the heat of adsorption and the pressure tensor of the adsorbed phase.

Topological Constraints and Their Conformational Entropic Penalties on RNA Folds.

PubMed

Mak, Chi H; Phan, Ethan N H

2018-05-08

Functional RNAs can fold into intricate structures using a number of different secondary and tertiary structural motifs. Many factors contribute to the overall free energy of the target fold. This study aims at quantifying the entropic costs coming from the loss of conformational freedom when the sugar-phosphate backbone is subjected to constraints imposed by secondary and tertiary contacts. Motivated by insights from topology theory, we design a diagrammatic scheme to represent different types of RNA structures so that constraints associated with a folded structure may be segregated into mutually independent subsets, enabling the total conformational entropy loss to be easily calculated as a sum of independent terms. We used high-throughput Monte Carlo simulations to simulate large ensembles of single-stranded RNA sequences in solution to validate the assumptions behind our diagrammatic scheme, examining the entropic costs for hairpin initiation and formation of many multiway junctions. Our diagrammatic scheme aids in the factorization of secondary/tertiary constraints into distinct topological classes and facilitates the discovery of interrelationships among multiple constraints on RNA folds. This perspective, which to our knowledge is novel, leads to useful insights into the inner workings of some functional RNA sequences, demonstrating how they might operate by transforming their structures among different topological classes. Copyright © 2018 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Self-shading associated with a skylight-blocked approach system for the measurement of water-leaving radiance and its correction.

PubMed

Shang, Zhehai; Lee, Zhongping; Dong, Qiang; Wei, Jianwei

2017-09-01

Self-shading associated with a skylight-blocked approach (SBA) system for the measurement of water-leaving radiance (L w ) and its correction [Appl. Opt.52, 1693 (2013)APOPAI0003-693510.1364/AO.52.001693] is characterized by Monte Carlo simulations, and it is found that this error is in a range of ∼1%-20% under most water properties and solar positions. A model for estimating this shading error is further developed, and eventually a scheme to correct this error based on the shaded measurements is proposed and evaluated. It is found that the shade-corrected value in the visible domain is within 3% of the true value, which thus indicates that we can obtain not only high precision but also high accuracy L w in the field with the SBA scheme.

Using Equation-Free Computation to Accelerate Network-Free Stochastic Simulation of Chemical Kinetics.

PubMed

Lin, Yen Ting; Chylek, Lily A; Lemons, Nathan W; Hlavacek, William S

2018-06-21

The chemical kinetics of many complex systems can be concisely represented by reaction rules, which can be used to generate reaction events via a kinetic Monte Carlo method that has been termed network-free simulation. Here, we demonstrate accelerated network-free simulation through a novel approach to equation-free computation. In this process, variables are introduced that approximately capture system state. Derivatives of these variables are estimated using short bursts of exact stochastic simulation and finite differencing. The variables are then projected forward in time via a numerical integration scheme, after which a new exact stochastic simulation is initialized and the whole process repeats. The projection step increases efficiency by bypassing the firing of numerous individual reaction events. As we show, the projected variables may be defined as populations of building blocks of chemical species. The maximal number of connected molecules included in these building blocks determines the degree of approximation. Equation-free acceleration of network-free simulation is found to be both accurate and efficient.

Hybrid atomistic simulation of fluid uptake in a deformable solid

NASA Astrophysics Data System (ADS)

Moghadam, Mahyar M.; Rickman, J. M.

2014-01-01

Fluid imbibition via diffusion in a deformable solid results in solid stresses that may, in turn, alter subsequent fluid uptake. To examine this interplay between diffusional and elastic fields, we employed a hybrid Monte Carlo-molecular dynamics scheme to model the coupling of a fluid reservoir to a deformable solid, and then simulated the resulting fluid permeation into the solid. By monitoring the instantaneous structure factor and solid dimensions, we were able to determine the compositional strain associated with imbibition, and the diffusion coefficient in the Fickian regime was obtained from the time dependence of the fluid uptake. Finally, for large, mobile fluid atoms, a non-Fickian regime was highlighted and possible mechanisms for this behavior were identified.

Deviation from equilibrium conditions in molecular dynamic simulations of homogeneous nucleation.

PubMed

Halonen, Roope; Zapadinsky, Evgeni; Vehkamäki, Hanna

2018-04-28

We present a comparison between Monte Carlo (MC) results for homogeneous vapour-liquid nucleation of Lennard-Jones clusters and previously published values from molecular dynamics (MD) simulations. Both the MC and MD methods sample real cluster configuration distributions. In the MD simulations, the extent of the temperature fluctuation is usually controlled with an artificial thermostat rather than with more realistic carrier gas. In this study, not only a primarily velocity scaling thermostat is considered, but also Nosé-Hoover, Berendsen, and stochastic Langevin thermostat methods are covered. The nucleation rates based on a kinetic scheme and the canonical MC calculation serve as a point of reference since they by definition describe an equilibrated system. The studied temperature range is from T = 0.3 to 0.65 ϵ/k. The kinetic scheme reproduces well the isothermal nucleation rates obtained by Wedekind et al. [J. Chem. Phys. 127, 064501 (2007)] using MD simulations with carrier gas. The nucleation rates obtained by artificially thermostatted MD simulations are consistently lower than the reference nucleation rates based on MC calculations. The discrepancy increases up to several orders of magnitude when the density of the nucleating vapour decreases. At low temperatures, the difference to the MC-based reference nucleation rates in some cases exceeds the maximal nonisothermal effect predicted by classical theory of Feder et al. [Adv. Phys. 15, 111 (1966)].

Deviation from equilibrium conditions in molecular dynamic simulations of homogeneous nucleation

NASA Astrophysics Data System (ADS)

Halonen, Roope; Zapadinsky, Evgeni; Vehkamäki, Hanna

2018-04-01

We present a comparison between Monte Carlo (MC) results for homogeneous vapour-liquid nucleation of Lennard-Jones clusters and previously published values from molecular dynamics (MD) simulations. Both the MC and MD methods sample real cluster configuration distributions. In the MD simulations, the extent of the temperature fluctuation is usually controlled with an artificial thermostat rather than with more realistic carrier gas. In this study, not only a primarily velocity scaling thermostat is considered, but also Nosé-Hoover, Berendsen, and stochastic Langevin thermostat methods are covered. The nucleation rates based on a kinetic scheme and the canonical MC calculation serve as a point of reference since they by definition describe an equilibrated system. The studied temperature range is from T = 0.3 to 0.65 ɛ/k. The kinetic scheme reproduces well the isothermal nucleation rates obtained by Wedekind et al. [J. Chem. Phys. 127, 064501 (2007)] using MD simulations with carrier gas. The nucleation rates obtained by artificially thermostatted MD simulations are consistently lower than the reference nucleation rates based on MC calculations. The discrepancy increases up to several orders of magnitude when the density of the nucleating vapour decreases. At low temperatures, the difference to the MC-based reference nucleation rates in some cases exceeds the maximal nonisothermal effect predicted by classical theory of Feder et al. [Adv. Phys. 15, 111 (1966)].

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.

A hybrid (Monte Carlo/deterministic) approach for multi-dimensional radiation transport

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

Bal, Guillaume, E-mail: gb2030@columbia.edu; Davis, Anthony B., E-mail: Anthony.B.Davis@jpl.nasa.gov; Kavli Institute for Theoretical Physics, Kohn Hall, University of California, Santa Barbara, CA 93106-4030

2011-08-20

Highlights: {yields} We introduce a variance reduction scheme for Monte Carlo (MC) transport. {yields} The primary application is atmospheric remote sensing. {yields} The technique first solves the adjoint problem using a deterministic solver. {yields} Next, the adjoint solution is used as an importance function for the MC solver. {yields} The adjoint problem is solved quickly since it ignores the volume. - Abstract: A novel hybrid Monte Carlo transport scheme is demonstrated in a scene with solar illumination, scattering and absorbing 2D atmosphere, a textured reflecting mountain, and a small detector located in the sky (mounted on a satellite or amore » airplane). It uses a deterministic approximation of an adjoint transport solution to reduce variance, computed quickly by ignoring atmospheric interactions. This allows significant variance and computational cost reductions when the atmospheric scattering and absorption coefficient are small. When combined with an atmospheric photon-redirection scheme, significant variance reduction (equivalently acceleration) is achieved in the presence of atmospheric interactions.« less

Multi-pair two-way massive MIMO AF relaying with ZFR/ZFT beamforming and imperfect CSI over ricean fading channels

NASA Astrophysics Data System (ADS)

Xu, Kui; Sun, Xiaoli; Zhang, Dongmei

2016-10-01

This paper investigates the spectral and energy efficiencies of a multi-pair two-way amplify-and-forward (AF) relay system over Ricean fading channels, where multiple user-pairs exchange information within pair through a relay with very large number of antennas, while each user equipped with a single antenna. Firstly, beamforming matrixe of zero-forcing reception/zero-forcing transmission (ZFR/ZFT) with imperfect channel state information (CSI) at the relay is given. Then, the unified asymptotic signal-to-interference-plus-noise ratio (SINR) expressions with imperfect CSI are obtained analytically. Finally, two power scaling schemes are proposed and the asymptotic spectral and energy efficiencies based on the proposed power scaling schemes are derived and verified by the Monte-Carlo simulations. Theoretical analyses and simulation results show that with imperfect CSI, if the number of relay antennas grows asymptotically large, we need cut down the transmit power of each user and relay to different proportion when the Ricean K-factor is non-zero and zero (Rayleigh fading) in order to maintain a desirable rate.

Hollow laser plasma self-confined microjet generation

NASA Astrophysics Data System (ADS)

Sizyuk, Valeryi; Hassanein, Ahmed; CenterMaterials under Extreme Environment Team

2017-10-01

Hollow laser beam produced plasma (LPP) devices are being used for the generation of the self-confined cumulative microjet. Most important place by this LPP device construction is achieving of an annular distribution of the laser beam intensity by spot. An integrated model is being developed to detailed simulation of the plasma generation and evolution inside the laser beam channel. The model describes in two temperature approximation hydrodynamic processes in plasma, laser absorption processes, heat conduction, and radiation energy transport. The total variation diminishing scheme in the Lax-Friedrich formulation for the description of plasma hydrodynamic is used. Laser absorption and radiation transport models on the base of Monte Carlo method are being developed. Heat conduction part on the implicit scheme with sparse matrixes using is realized. The developed models are being integrated into HEIGHTS-LPP computer simulation package. The integrated modeling of the hollow beam laser plasma generation showed the self-confinement and acceleration of the plasma microjet inside the laser channel. It was found dependence of the microjet parameters including radiation emission on the hole and beam radiuses ratio. This work is supported by the National Science Foundation, PIRE project.

Quantum Gibbs ensemble Monte Carlo

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

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

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

Monte Carlo reference data sets for imaging research: Executive summary of the report of AAPM Research Committee Task Group 195.

PubMed

Sechopoulos, Ioannis; Ali, Elsayed S M; Badal, Andreu; Badano, Aldo; Boone, John M; Kyprianou, Iacovos S; Mainegra-Hing, Ernesto; McMillan, Kyle L; McNitt-Gray, Michael F; Rogers, D W O; Samei, Ehsan; Turner, Adam C

2015-10-01

The use of Monte Carlo simulations in diagnostic medical imaging research is widespread due to its flexibility and ability to estimate quantities that are challenging to measure empirically. However, any new Monte Carlo simulation code needs to be validated before it can be used reliably. The type and degree of validation required depends on the goals of the research project, but, typically, such validation involves either comparison of simulation results to physical measurements or to previously published results obtained with established Monte Carlo codes. The former is complicated due to nuances of experimental conditions and uncertainty, while the latter is challenging due to typical graphical presentation and lack of simulation details in previous publications. In addition, entering the field of Monte Carlo simulations in general involves a steep learning curve. It is not a simple task to learn how to program and interpret a Monte Carlo simulation, even when using one of the publicly available code packages. This Task Group report provides a common reference for benchmarking Monte Carlo simulations across a range of Monte Carlo codes and simulation scenarios. In the report, all simulation conditions are provided for six different Monte Carlo simulation cases that involve common x-ray based imaging research areas. The results obtained for the six cases using four publicly available Monte Carlo software packages are included in tabular form. In addition to a full description of all simulation conditions and results, a discussion and comparison of results among the Monte Carlo packages and the lessons learned during the compilation of these results are included. This abridged version of the report includes only an introductory description of the six cases and a brief example of the results of one of the cases. This work provides an investigator the necessary information to benchmark his/her Monte Carlo simulation software against the reference cases included here before performing his/her own novel research. In addition, an investigator entering the field of Monte Carlo simulations can use these descriptions and results as a self-teaching tool to ensure that he/she is able to perform a specific simulation correctly. Finally, educators can assign these cases as learning projects as part of course objectives or training programs.

Reduction of bias and variance for evaluation of computer-aided diagnostic schemes.

PubMed

Li, Qiang; Doi, Kunio

2006-04-01

Computer-aided diagnostic (CAD) schemes have been developed to assist radiologists in detecting various lesions in medical images. In addition to the development, an equally important problem is the reliable evaluation of the performance levels of various CAD schemes. It is good to see that more and more investigators are employing more reliable evaluation methods such as leave-one-out and cross validation, instead of less reliable methods such as resubstitution, for assessing their CAD schemes. However, the common applications of leave-one-out and cross-validation evaluation methods do not necessarily imply that the estimated performance levels are accurate and precise. Pitfalls often occur in the use of leave-one-out and cross-validation evaluation methods, and they lead to unreliable estimation of performance levels. In this study, we first identified a number of typical pitfalls for the evaluation of CAD schemes, and conducted a Monte Carlo simulation experiment for each of the pitfalls to demonstrate quantitatively the extent of bias and/or variance caused by the pitfall. Our experimental results indicate that considerable bias and variance may exist in the estimated performance levels of CAD schemes if one employs various flawed leave-one-out and cross-validation evaluation methods. In addition, for promoting and utilizing a high standard for reliable evaluation of CAD schemes, we attempt to make recommendations, whenever possible, for overcoming these pitfalls. We believe that, with the recommended evaluation methods, we can considerably reduce the bias and variance in the estimated performance levels of CAD schemes.

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

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

Badal, A; Zbijewski, W; Bolch, W

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

Large-scale-system effectiveness analysis. Final report

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

Patton, A.D.; Ayoub, A.K.; Foster, J.W.

1979-11-01

Objective of the research project has been the investigation and development of methods for calculating system reliability indices which have absolute, and measurable, significance to consumers. Such indices are a necessary prerequisite to any scheme for system optimization which includes the economic consequences of consumer service interruptions. A further area of investigation has been joint consideration of generation and transmission in reliability studies. Methods for finding or estimating the probability distributions of some measures of reliability performance have been developed. The application of modern Monte Carlo simulation methods to compute reliability indices in generating systems has been studied.

Fault-tolerant linear optical quantum computing with small-amplitude coherent States.

PubMed

Lund, A P; Ralph, T C; Haselgrove, H L

2008-01-25

Quantum computing using two coherent states as a qubit basis is a proposed alternative architecture with lower overheads but has been questioned as a practical way of performing quantum computing due to the fragility of diagonal states with large coherent amplitudes. We show that using error correction only small amplitudes (alpha>1.2) are required for fault-tolerant quantum computing. We study fault tolerance under the effects of small amplitudes and loss using a Monte Carlo simulation. The first encoding level resources are orders of magnitude lower than the best single photon scheme.

Accuracy of remotely sensed data: Sampling and analysis procedures

NASA Technical Reports Server (NTRS)

Congalton, R. G.; Oderwald, R. G.; Mead, R. A.

1982-01-01

A review and update of the discrete multivariate analysis techniques used for accuracy assessment is given. A listing of the computer program written to implement these techniques is given. New work on evaluating accuracy assessment using Monte Carlo simulation with different sampling schemes is given. The results of matrices from the mapping effort of the San Juan National Forest is given. A method for estimating the sample size requirements for implementing the accuracy assessment procedures is given. A proposed method for determining the reliability of change detection between two maps of the same area produced at different times is given.

Levels in 223Th populated by α decay of 227U

NASA Astrophysics Data System (ADS)

Kalaninová, Z.; Antalic, S.; Heßberger, F. P.; Ackermann, D.; Andel, B.; Kindler, B.; Laatiaoui, M.; Lommel, B.; Maurer, J.

2015-07-01

Levels in 223Th populated by the α decay of 227U were investigated using α -γ decay spectroscopy. The 227U isotope was produced in the fusion-evaporation reaction 22Ne +208Pb at the velocity filter separator for heavy-ion reaction products at Gesellschaft für Schwerionenforschung in Darmstadt (Germany). Several new excited levels and γ transitions were identified in 223Th . An improved α -decay scheme of 227U was suggested. The experimental α -decay energy spectrum of 227U was compared with the Monte Carlo simulation performed using the toolkit geant4.

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.

Variational Bayesian identification and prediction of stochastic nonlinear dynamic causal models.

PubMed

Daunizeau, J; Friston, K J; Kiebel, S J

2009-11-01

In this paper, we describe a general variational Bayesian approach for approximate inference on nonlinear stochastic dynamic models. This scheme extends established approximate inference on hidden-states to cover: (i) nonlinear evolution and observation functions, (ii) unknown parameters and (precision) hyperparameters and (iii) model comparison and prediction under uncertainty. Model identification or inversion entails the estimation of the marginal likelihood or evidence of a model. This difficult integration problem can be finessed by optimising a free-energy bound on the evidence using results from variational calculus. This yields a deterministic update scheme that optimises an approximation to the posterior density on the unknown model variables. We derive such a variational Bayesian scheme in the context of nonlinear stochastic dynamic hierarchical models, for both model identification and time-series prediction. The computational complexity of the scheme is comparable to that of an extended Kalman filter, which is critical when inverting high dimensional models or long time-series. Using Monte-Carlo simulations, we assess the estimation efficiency of this variational Bayesian approach using three stochastic variants of chaotic dynamic systems. We also demonstrate the model comparison capabilities of the method, its self-consistency and its predictive power.

A unified parameterization of clouds and turbulence using CLUBB and subcolumns in the Community Atmosphere Model

DOE PAGES

Thayer-Calder, K.; Gettelman, A.; Craig, C.; ...

2015-06-30

Most global climate models parameterize separate cloud types using separate parameterizations. This approach has several disadvantages, including obscure interactions between parameterizations and inaccurate triggering of cumulus parameterizations. Alternatively, a unified cloud parameterization uses one equation set to represent all cloud types. Such cloud types include stratiform liquid and ice cloud, shallow convective cloud, and deep convective cloud. Vital to the success of a unified parameterization is a general interface between clouds and microphysics. One such interface involves drawing Monte Carlo samples of subgrid variability of temperature, water vapor, cloud liquid, and cloud ice, and feeding the sample points into amore » microphysics scheme.This study evaluates a unified cloud parameterization and a Monte Carlo microphysics interface that has been implemented in the Community Atmosphere Model (CAM) version 5.3. Results describing the mean climate and tropical variability from global simulations are presented. The new model shows a degradation in precipitation skill but improvements in short-wave cloud forcing, liquid water path, long-wave cloud forcing, precipitable water, and tropical wave simulation. Also presented are estimations of computational expense and investigation of sensitivity to number of subcolumns.« less

A unified parameterization of clouds and turbulence using CLUBB and subcolumns in the Community Atmosphere Model

DOE PAGES

Thayer-Calder, Katherine; Gettelman, A.; Craig, Cheryl; ...

2015-12-01

Most global climate models parameterize separate cloud types using separate parameterizations.This approach has several disadvantages, including obscure interactions between parameterizations and inaccurate triggering of cumulus parameterizations. Alternatively, a unified cloud parameterization uses one equation set to represent all cloud types. Such cloud types include stratiform liquid and ice cloud, shallow convective cloud, and deep convective cloud. Vital to the success of a unified parameterization is a general interface between clouds and microphysics. One such interface involves drawing Monte Carlo samples of subgrid variability of temperature, water vapor, cloud liquid, and cloud ice, and feeding the sample points into a microphysicsmore » scheme. This study evaluates a unified cloud parameterization and a Monte Carlo microphysics interface that has been implemented in the Community Atmosphere Model (CAM) version 5.3. Results describing the mean climate and tropical variability from global simulations are presented. In conclusion, the new model shows a degradation in precipitation skill but improvements in short-wave cloud forcing, liquid water path, long-wave cloud forcing, perceptible water, and tropical wave simulation. Also presented are estimations of computational expense and investigation of sensitivity to number of subcolumns.« less

Non-adiabatic molecular dynamics by accelerated semiclassical Monte Carlo

DOE PAGES

White, Alexander J.; Gorshkov, Vyacheslav N.; Tretiak, Sergei; ...

2015-07-07

Non-adiabatic dynamics, where systems non-radiatively transition between electronic states, plays a crucial role in many photo-physical processes, such as fluorescence, phosphorescence, and photoisomerization. Methods for the simulation of non-adiabatic dynamics are typically either numerically impractical, highly complex, or based on approximations which can result in failure for even simple systems. Recently, the Semiclassical Monte Carlo (SCMC) approach was developed in an attempt to combine the accuracy of rigorous semiclassical methods with the efficiency and simplicity of widely used surface hopping methods. However, while SCMC was found to be more efficient than other semiclassical methods, it is not yet as efficientmore » as is needed to be used for large molecular systems. Here, we have developed two new methods: the accelerated-SCMC and the accelerated-SCMC with re-Gaussianization, which reduce the cost of the SCMC algorithm up to two orders of magnitude for certain systems. In many cases shown here, the new procedures are nearly as efficient as the commonly used surface hopping schemes, with little to no loss of accuracy. This implies that these modified SCMC algorithms will be of practical numerical solutions for simulating non-adiabatic dynamics in realistic molecular systems.« less

Equivalence of internal and external mixture schemes of single scattering properties in vector radiative transfer

PubMed Central

Mukherjee, Lipi; Zhai, Peng-Wang; Hu, Yongxiang; Winker, David M.

2018-01-01

Polarized radiation fields in a turbid medium are influenced by single-scattering properties of scatterers. It is common that media contain two or more types of scatterers, which makes it essential to properly mix single-scattering properties of different types of scatterers in the vector radiative transfer theory. The vector radiative transfer solvers can be divided into two basic categories: the stochastic and deterministic methods. The stochastic method is basically the Monte Carlo method, which can handle scatterers with different scattering properties explicitly. This mixture scheme is called the external mixture scheme in this paper. The deterministic methods, however, can only deal with a single set of scattering properties in the smallest discretized spatial volume. The single-scattering properties of different types of scatterers have to be averaged before they are input to deterministic solvers. This second scheme is called the internal mixture scheme. The equivalence of these two different mixture schemes of scattering properties has not been demonstrated so far. In this paper, polarized radiation fields for several scattering media are solved using the Monte Carlo and successive order of scattering (SOS) methods and scattering media contain two types of scatterers: Rayleigh scatterers (molecules) and Mie scatterers (aerosols). The Monte Carlo and SOS methods employ external and internal mixture schemes of scatterers, respectively. It is found that the percentage differences between radiances solved by these two methods with different mixture schemes are of the order of 0.1%. The differences of Q/I, U/I, and V/I are of the order of 10−5 ~ 10−4, where I, Q, U, and V are the Stokes parameters. Therefore, the equivalence between these two mixture schemes is confirmed to the accuracy level of the radiative transfer numerical benchmarks. This result provides important guidelines for many radiative transfer applications that involve the mixture of different scattering and absorptive particles. PMID:29047543

Thermodynamics and simulation of hard-sphere fluid and solid: Kinetic Monte Carlo method versus standard Metropolis scheme

NASA Astrophysics Data System (ADS)

Ustinov, E. A.

2017-01-01

The paper aims at a comparison of techniques based on the kinetic Monte Carlo (kMC) and the conventional Metropolis Monte Carlo (MC) methods as applied to the hard-sphere (HS) fluid and solid. In the case of the kMC, an alternative representation of the chemical potential is explored [E. A. Ustinov and D. D. Do, J. Colloid Interface Sci. 366, 216 (2012)], which does not require any external procedure like the Widom test particle insertion method. A direct evaluation of the chemical potential of the fluid and solid without thermodynamic integration is achieved by molecular simulation in an elongated box with an external potential imposed on the system in order to reduce the particle density in the vicinity of the box ends. The existence of rarefied zones allows one to determine the chemical potential of the crystalline phase and substantially increases its accuracy for the disordered dense phase in the central zone of the simulation box. This method is applicable to both the Metropolis MC and the kMC, but in the latter case, the chemical potential is determined with higher accuracy at the same conditions and the number of MC steps. Thermodynamic functions of the disordered fluid and crystalline face-centered cubic (FCC) phase for the hard-sphere system have been evaluated with the kinetic MC and the standard MC coupled with the Widom procedure over a wide range of density. The melting transition parameters have been determined by the point of intersection of the pressure-chemical potential curves for the disordered HS fluid and FCC crystal using the Gibbs-Duhem equation as a constraint. A detailed thermodynamic analysis of the hard-sphere fluid has provided a rigorous verification of the approach, which can be extended to more complex systems.

Purity of Gaussian states: Measurement schemes and time evolution in noisy channels

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

Paris, Matteo G.A.; Illuminati, Fabrizio; Serafini, Alessio

2003-07-01

We present a systematic study of the purity for Gaussian states of single-mode continuous variable systems. We prove the connection of purity to observable quantities for these states, and show that the joint measurement of two conjugate quadratures is necessary and sufficient to determine the purity at any time. The statistical reliability and the range of applicability of the proposed measurement scheme are tested by means of Monte Carlo simulated experiments. We then consider the dynamics of purity in noisy channels. We derive an evolution equation for the purity of general Gaussian states both in thermal and in squeezed thermalmore » baths. We show that purity is maximized at any given time for an initial coherent state evolving in a thermal bath, or for an initial squeezed state evolving in a squeezed thermal bath whose asymptotic squeezing is orthogonal to that of the input state.« less

An off-lattice, self-learning kinetic Monte Carlo method using local environments.

PubMed

Konwar, Dhrubajit; Bhute, Vijesh J; Chatterjee, Abhijit

2011-11-07

We present a method called local environment kinetic Monte Carlo (LE-KMC) method for efficiently performing off-lattice, self-learning kinetic Monte Carlo (KMC) simulations of activated processes in material systems. Like other off-lattice KMC schemes, new atomic processes can be found on-the-fly in LE-KMC. However, a unique feature of LE-KMC is that as long as the assumption that all processes and rates depend only on the local environment is satisfied, LE-KMC provides a general algorithm for (i) unambiguously describing a process in terms of its local atomic environments, (ii) storing new processes and environments in a catalog for later use with standard KMC, and (iii) updating the system based on the local information once a process has been selected for a KMC move. Search, classification, storage and retrieval steps needed while employing local environments and processes in the LE-KMC method are discussed. The advantages and computational cost of LE-KMC are discussed. We assess the performance of the LE-KMC algorithm by considering test systems involving diffusion in a submonolayer Ag and Ag-Cu alloy films on Ag(001) surface.

Universal aspects of conformations and transverse fluctuations of a two-dimensional semi-flexible chain

NASA Astrophysics Data System (ADS)

Hsu, Hsiao-Ping; Huang, Aiqun; Bhattacharya, Aniket; Binder, Kurt

2015-03-01

In this talk we compare the results obtained from Monte Carlo (MC) and Brownian dynamics (BD) simulation for the universal properties of a semi-flexible chain. Specifically we compare MC results obtained using pruned-enriched Rosenbluth method (PERM) with those obtained from BD simulation. We find that the scaled plot of root-mean-square (RMS) end-to-end distance / 2 Llp and RMS transverse transverse fluctuations √{ } /lp as a function of L /lp (where L and lp are the contour length, and the persistence length respectively) are universal and independent of the definition of the persistence length used in MC and BD schemes. We further investigate to what extent these results agree for a semi-flexible polymer confined in a quasi one dimensional channel.

Laser acceleration of electrons to giga-electron-volt energies using highly charged ions.

PubMed

Hu, S X; Starace, Anthony F

2006-06-01

The recent proposal to use highly charged ions as sources of electrons for laser acceleration [S. X. Hu and A. F. Starace, Phys. Rev. Lett. 88, 245003 (2002)] is investigated here in detail by means of three-dimensional, relativistic Monte Carlo simulations for a variety of system parameters, such as laser pulse duration, ionic charge state, and laser focusing spot size. Realistic laser focusing effects--e.g., the existence of longitudinal laser field components-are taken into account. Results of spatial averaging over the laser focus are also presented. These numerical simulations show that the proposed scheme for laser acceleration of electrons from highly charged ions is feasible with current or near-future experimental conditions and that electrons with GeV energies can be obtained in such experiments.

TU-H-207A-08: Estimating Radiation Dose From Low-Dose Lung Cancer Screening CT Exams Using Tube Current Modulation

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

Hardy, A; Bostani, M; McMillan, K

Purpose: The purpose of this work is to estimate effective and lung doses from a low-dose lung cancer screening CT protocol using Tube Current Modulation (TCM) across patient models of different sizes. Methods: Monte Carlo simulation methods were used to estimate effective and lung doses from a low-dose lung cancer screening protocol for a 64-slice CT (Sensation 64, Siemens Healthcare) that used TCM. Scanning parameters were from the AAPM protocols. Ten GSF voxelized patient models were used and had all radiosensitive organs identified to facilitate estimating both organ and effective doses. Predicted TCM schemes for each patient model were generatedmore » using a validated method wherein tissue attenuation characteristics and scanner limitations were used to determine the TCM output as a function of table position and source angle. The water equivalent diameter (WED) was determined by estimating the attenuation at the center of the scan volume for each patient model. Monte Carlo simulations were performed using the unique TCM scheme for each patient model. Lung doses were tallied and effective doses were estimated using ICRP 103 tissue weighting factors. Effective and lung dose values were normalized by scanspecific 32 cm CTDIvol values based upon the average tube current across the entire simulated scan. Absolute and normalized doses were reported as a function of WED for each patient. Results: For all ten patients modeled, the effective dose using TCM protocols was below 1.5 mSv. Smaller sized patient models experienced lower absolute doses compared to larger sized patients. Normalized effective and lung doses showed some dependence on patient size (R2 = 0.77 and 0.78, respectively). Conclusion: Effective doses for a low-dose lung screening protocol using TCM were below 1.5 mSv for all patient models used in this study. Institutional research agreement, Siemens Healthcare; Past recipient, research grant support, Siemens Healthcare; Consultant, Toshiba America Medical Systems; Consultant, Samsung Electronics.« less

Lattice based Kinetic Monte Carlo Simulations of a complex chemical reaction network

NASA Astrophysics Data System (ADS)

Danielson, Thomas; Savara, Aditya; Hin, Celine

Lattice Kinetic Monte Carlo (KMC) simulations offer a powerful alternative to using ordinary differential equations for the simulation of complex chemical reaction networks. Lattice KMC provides the ability to account for local spatial configurations of species in the reaction network, resulting in a more detailed description of the reaction pathway. In KMC simulations with a large number of reactions, the range of transition probabilities can span many orders of magnitude, creating subsets of processes that occur more frequently or more rarely. Consequently, processes that have a high probability of occurring may be selected repeatedly without actually progressing the system (i.e. the forward and reverse process for the same reaction). In order to avoid the repeated occurrence of fast frivolous processes, it is necessary to throttle the transition probabilities in such a way that avoids altering the overall selectivity. Likewise, as the reaction progresses, new frequently occurring species and reactions may be introduced, making a dynamic throttling algorithm a necessity. We present a dynamic steady-state detection scheme with the goal of accurately throttling rate constants in order to optimize the KMC run time without compromising the selectivity of the reaction network. The algorithm has been applied to a large catalytic chemical reaction network, specifically that of methanol oxidative dehydrogenation, as well as additional pathways on CeO2(111) resulting in formaldehyde, CO, methanol, CO2, H2 and H2O as gas products.

Carbon footprint assessment of Western Australian Groundwater Recycling Scheme

NASA Astrophysics Data System (ADS)

Simms, Andrew; Hamilton, Stacey; Biswas, Wahidul K.

2017-04-01

This research has determined the carbon footprint or the carbon dioxide equivalent (CO2 eq) of potable water production from a groundwater recycling scheme, consisting of the Beenyup wastewater treatment plant, the Beenyup groundwater replenishment trial plant and the Wanneroo groundwater treatment plant in Western Australia, using a life cycle assessment approach. It was found that the scheme produces 1300 tonnes of CO2 eq per gigalitre (GL) of water produced, which is 933 tonnes of CO2 eq higher than the desalination plant at Binningup in Western Australia powered by 100% renewable energy generated electricity. A Monte Carlo Simulation uncertainty analysis calculated a Coefficient of Variation value of 5.4%, thus confirming the accuracy of the simulation. Electricity input accounts for 83% of the carbon dioxide equivalent produced during the production of potable water. The chosen mitigation strategy was to consider the use of renewable energy to generate electricity for carbon intensive groundwater replenishment trial plant. Depending on the local situation, a maximum of 93% and a minimum of 21% greenhouse gas saving from electricity use can be attained at groundwater replenishment trial plant by replacing grid electricity with renewable electricity. In addition, the consideration of vibrational separation (V-Sep) that helps reduce wastes generation and chemical use resulted in a 4.03 tonne of CO2 eq saving per GL of water produced by the plant.

Carbon footprint assessment of Western Australian Groundwater Recycling Scheme.

PubMed

Simms, Andrew; Hamilton, Stacey; Biswas, Wahidul K

2017-04-01

This research has determined the carbon footprint or the carbon dioxide equivalent (CO 2 eq) of potable water production from a groundwater recycling scheme, consisting of the Beenyup wastewater treatment plant, the Beenyup groundwater replenishment trial plant and the Wanneroo groundwater treatment plant in Western Australia, using a life cycle assessment approach. It was found that the scheme produces 1300 tonnes of CO 2 eq per gigalitre (GL) of water produced, which is 933 tonnes of CO 2 eq higher than the desalination plant at Binningup in Western Australia powered by 100% renewable energy generated electricity. A Monte Carlo Simulation uncertainty analysis calculated a Coefficient of Variation value of 5.4%, thus confirming the accuracy of the simulation. Electricity input accounts for 83% of the carbon dioxide equivalent produced during the production of potable water. The chosen mitigation strategy was to consider the use of renewable energy to generate electricity for carbon intensive groundwater replenishment trial plant. Depending on the local situation, a maximum of 93% and a minimum of 21% greenhouse gas saving from electricity use can be attained at groundwater replenishment trial plant by replacing grid electricity with renewable electricity. In addition, the consideration of vibrational separation (V-Sep) that helps reduce wastes generation and chemical use resulted in a 4.03 tonne of CO 2 eq saving per GL of water produced by the plant.

Parametric behaviors of CLUBB in simulations of low clouds in the Community Atmosphere Model (CAM)

DOE PAGES

Guo, Zhun; Wang, Minghuai; Qian, Yun; ...

2015-07-03

In this study, we investigate the sensitivity of simulated low clouds to 14 selected tunable parameters of Cloud Layers Unified By Binormals (CLUBB), a higher order closure (HOC) scheme, and 4 parameters of the Zhang-McFarlane (ZM) deep convection scheme in the Community Atmosphere Model version 5 (CAM5). A quasi-Monte Carlo (QMC) sampling approach is adopted to effectively explore the high-dimensional parameter space and a generalized linear model is applied to study the responses of simulated cloud fields to tunable parameters. Our results show that the variance in simulated low-cloud properties (cloud fraction and liquid water path) can be explained bymore » the selected tunable parameters in two different ways: macrophysics itself and its interaction with microphysics. First, the parameters related to dynamic and thermodynamic turbulent structure and double Gaussians closure are found to be the most influential parameters for simulating low clouds. The spatial distributions of the parameter contributions show clear cloud-regime dependence. Second, because of the coupling between cloud macrophysics and cloud microphysics, the coefficient of the dissipation term in the total water variance equation is influential. This parameter affects the variance of in-cloud cloud water, which further influences microphysical process rates, such as autoconversion, and eventually low-cloud fraction. Furthermore, this study improves understanding of HOC behavior associated with parameter uncertainties and provides valuable insights for the interaction of macrophysics and microphysics.« less

The study of PDF turbulence models in combustion

NASA Technical Reports Server (NTRS)

Hsu, Andrew T.

1991-01-01

In combustion computations, it is known that the predictions of chemical reaction rates are poor if conventional turbulence models are used. The probability density function (pdf) method seems to be the only alternative that uses local instantaneous values of the temperature, density, etc., in predicting chemical reaction rates, and thus is the only viable approach for more accurate turbulent combustion calculations. The fact that the pdf equation has a very large dimensionality renders finite difference schemes extremely demanding on computer memories and thus impractical. A logical alternative is the Monte Carlo scheme. Since CFD has a certain maturity as well as acceptance, it seems that the use of a combined CFD and Monte Carlo scheme is more beneficial. Therefore, a scheme is chosen that uses a conventional CFD flow solver in calculating the flow field properties such as velocity, pressure, etc., while the chemical reaction part is solved using a Monte Carlo scheme. The discharge of a heated turbulent plane jet into quiescent air was studied. Experimental data for this problem shows that when the temperature difference between the jet and the surrounding air is small, buoyancy effect can be neglected and the temperature can be treated as a passive scalar. The fact that jet flows have a self-similar solution lends convenience in the modeling study. Futhermore, the existence of experimental data for turbulent shear stress and temperature variance make the case ideal for the testing of pdf models wherein these values can be directly evaluated.

Numerical and experimental analyses of the radiant heat flux produced by quartz heating systems

NASA Technical Reports Server (NTRS)

Turner, Travis L.; Ash, Robert L.

1994-01-01

A method is developed for predicting the radiant heat flux distribution produced by tungsten filament, tubular fused-quartz envelope heating systems with reflectors. The method is an application of Monte Carlo simulation, which takes the form of a random walk or ray tracing scheme. The method is applied to four systems of increasing complexity, including a single lamp without a reflector, a single lamp with a Hat reflector, a single lamp with a parabolic reflector, and up to six lamps in a six-lamp contoured-reflector heating unit. The application of the Monte Carlo method to the simulation of the thermal radiation generated by these systems is discussed. The procedures for numerical implementation are also presented. Experiments were conducted to study these quartz heating systems and to acquire measurements of the corresponding empirical heat flux distributions for correlation with analysis. The experiments were conducted such that several complicating factors could be isolated and studied sequentially. Comparisons of the experimental results with analysis are presented and discussed. Good agreement between the experimental and simulated results was obtained in all cases. This study shows that this method can be used to analyze very complicated quartz heating systems and can account for factors such as spectral properties, specular reflection from curved surfaces, source enhancement due to reflectors and/or adjacent sources, and interaction with a participating medium in a straightforward manner.

Analysis of Naval Ammunition Stock Positioning

DTIC Science & Technology

2015-12-01

model takes once the Monte -Carlo simulation determines the assigned probabilities for site-to-site locations. Column two shows how the simulation...stockpiles and positioning them at coastal Navy facilities. A Monte -Carlo simulation model was developed to simulate expected cost and delivery...TERMS supply chain management, Monte -Carlo simulation, risk, delivery performance, stock positioning 15. NUMBER OF PAGES 85 16. PRICE CODE 17

DUAL STATE-PARAMETER UPDATING SCHEME ON A CONCEPTUAL HYDROLOGIC MODEL USING SEQUENTIAL MONTE CARLO FILTERS

NASA Astrophysics Data System (ADS)

Noh, Seong Jin; Tachikawa, Yasuto; Shiiba, Michiharu; Kim, Sunmin

Applications of data assimilation techniques have been widely used to improve upon the predictability of hydrologic modeling. Among various data assimilation techniques, sequential Monte Carlo (SMC) filters, known as "particle filters" provide the capability to handle non-linear and non-Gaussian state-space models. This paper proposes a dual state-parameter updating scheme (DUS) based on SMC methods to estimate both state and parameter variables of a hydrologic model. We introduce a kernel smoothing method for the robust estimation of uncertain model parameters in the DUS. The applicability of the dual updating scheme is illustrated using the implementation of the storage function model on a middle-sized Japanese catchment. We also compare performance results of DUS combined with various SMC methods, such as SIR, ASIR and RPF.

Initial development of goCMC: a GPU-oriented fast cross-platform Monte Carlo engine for carbon ion therapy

PubMed Central

Qin, Nan; Pinto, Marco; Tian, Zhen; Dedes, Georgios; Pompos, Arnold; Jiang, Steve B.; Parodi, Katia; Jia, Xun

2017-01-01

Monte Carlo (MC) simulation is considered as the most accurate method for calculation of absorbed dose and fundamental physics quantities related to biological effects in carbon ion therapy. To improve its computational efficiency, we have developed a GPU-oriented fast MC package named goCMC, for carbon therapy. goCMC simulates particle transport in voxelized geometry with kinetic energy up to 450 MeV/u. Class II condensed history simulation scheme with a continuous slowing down approximation was employed. Energy straggling and multiple scattering were modeled. δ-electrons were terminated with their energy locally deposited. Four types of nuclear interactions were implemented in goCMC, i.e., carbon-hydrogen, carbon-carbon, carbon-oxygen and carbon-calcium inelastic collisions. Total cross section data from Geant4 were used. Secondary particles produced in these interactions were sampled according to particle yield with energy and directional distribution data derived from Geant4 simulation results. Secondary charged particles were transported following the condensed history scheme, whereas secondary neutral particles were ignored. goCMC was developed under OpenCL framework and is executable on different platforms, e.g. GPU and multi-core CPU. We have validated goCMC with Geant4 in cases with different beam energy and phantoms including four homogeneous phantoms, one heterogeneous half-slab phantom, and one patient case. For each case 3 × 107 carbon ions were simulated, such that in the region with dose greater than 10% of maximum dose, the mean relative statistical uncertainty was less than 1%. Good agreements for dose distributions and range estimations between goCMC and Geant4 were observed. 3D gamma passing rates with 1%/1 mm criterion were over 90% within 10%) isodose line except in two extreme cases, and those with 2%/1 mm criterion were all over 96%. Efficiency and code portability were tested with different GPUs and CPUs. Depending on the beam energy and voxel size, the computation time to simulate 107 carbons was 9.9–125 sec, 2.5–50 sec and 60–612 sec on an AMD Radeon GPU card, an NVidia GeForce GTX 1080 GPU card and an Intel Xeon E5-2640 CPU, respectively. The combined accuracy, efficiency and portability make goCMC attractive for research and clinical applications in carbon ion therapy. PMID:28140352

Initial development of goCMC: a GPU-oriented fast cross-platform Monte Carlo engine for carbon ion therapy

NASA Astrophysics Data System (ADS)

Qin, Nan; Pinto, Marco; Tian, Zhen; Dedes, Georgios; Pompos, Arnold; Jiang, Steve B.; Parodi, Katia; Jia, Xun

2017-05-01

Monte Carlo (MC) simulation is considered as the most accurate method for calculation of absorbed dose and fundamental physics quantities related to biological effects in carbon ion therapy. To improve its computational efficiency, we have developed a GPU-oriented fast MC package named goCMC, for carbon therapy. goCMC simulates particle transport in voxelized geometry with kinetic energy up to 450 MeV u-1. Class II condensed history simulation scheme with a continuous slowing down approximation was employed. Energy straggling and multiple scattering were modeled. δ-electrons were terminated with their energy locally deposited. Four types of nuclear interactions were implemented in goCMC, i.e. carbon-hydrogen, carbon-carbon, carbon-oxygen and carbon-calcium inelastic collisions. Total cross section data from Geant4 were used. Secondary particles produced in these interactions were sampled according to particle yield with energy and directional distribution data derived from Geant4 simulation results. Secondary charged particles were transported following the condensed history scheme, whereas secondary neutral particles were ignored. goCMC was developed under OpenCL framework and is executable on different platforms, e.g. GPU and multi-core CPU. We have validated goCMC with Geant4 in cases with different beam energy and phantoms including four homogeneous phantoms, one heterogeneous half-slab phantom, and one patient case. For each case 3× {{10}7} carbon ions were simulated, such that in the region with dose greater than 10% of maximum dose, the mean relative statistical uncertainty was less than 1%. Good agreements for dose distributions and range estimations between goCMC and Geant4 were observed. 3D gamma passing rates with 1%/1 mm criterion were over 90% within 10% isodose line except in two extreme cases, and those with 2%/1 mm criterion were all over 96%. Efficiency and code portability were tested with different GPUs and CPUs. Depending on the beam energy and voxel size, the computation time to simulate {{10}7} carbons was 9.9-125 s, 2.5-50 s and 60-612 s on an AMD Radeon GPU card, an NVidia GeForce GTX 1080 GPU card and an Intel Xeon E5-2640 CPU, respectively. The combined accuracy, efficiency and portability make goCMC attractive for research and clinical applications in carbon ion therapy.

Initial development of goCMC: a GPU-oriented fast cross-platform Monte Carlo engine for carbon ion therapy.

PubMed

Qin, Nan; Pinto, Marco; Tian, Zhen; Dedes, Georgios; Pompos, Arnold; Jiang, Steve B; Parodi, Katia; Jia, Xun

2017-05-07

Monte Carlo (MC) simulation is considered as the most accurate method for calculation of absorbed dose and fundamental physics quantities related to biological effects in carbon ion therapy. To improve its computational efficiency, we have developed a GPU-oriented fast MC package named goCMC, for carbon therapy. goCMC simulates particle transport in voxelized geometry with kinetic energy up to 450 MeV u -1 . Class II condensed history simulation scheme with a continuous slowing down approximation was employed. Energy straggling and multiple scattering were modeled. δ-electrons were terminated with their energy locally deposited. Four types of nuclear interactions were implemented in goCMC, i.e. carbon-hydrogen, carbon-carbon, carbon-oxygen and carbon-calcium inelastic collisions. Total cross section data from Geant4 were used. Secondary particles produced in these interactions were sampled according to particle yield with energy and directional distribution data derived from Geant4 simulation results. Secondary charged particles were transported following the condensed history scheme, whereas secondary neutral particles were ignored. goCMC was developed under OpenCL framework and is executable on different platforms, e.g. GPU and multi-core CPU. We have validated goCMC with Geant4 in cases with different beam energy and phantoms including four homogeneous phantoms, one heterogeneous half-slab phantom, and one patient case. For each case [Formula: see text] carbon ions were simulated, such that in the region with dose greater than 10% of maximum dose, the mean relative statistical uncertainty was less than 1%. Good agreements for dose distributions and range estimations between goCMC and Geant4 were observed. 3D gamma passing rates with 1%/1 mm criterion were over 90% within 10% isodose line except in two extreme cases, and those with 2%/1 mm criterion were all over 96%. Efficiency and code portability were tested with different GPUs and CPUs. Depending on the beam energy and voxel size, the computation time to simulate [Formula: see text] carbons was 9.9-125 s, 2.5-50 s and 60-612 s on an AMD Radeon GPU card, an NVidia GeForce GTX 1080 GPU card and an Intel Xeon E5-2640 CPU, respectively. The combined accuracy, efficiency and portability make goCMC attractive for research and clinical applications in carbon ion therapy.

Molecular origin of differences in hole and electron mobility in amorphous Alq3--a multiscale simulation study.

PubMed

Fuchs, Andreas; Steinbrecher, Thomas; Mommer, Mario S; Nagata, Yuki; Elstner, Marcus; Lennartz, Christian

2012-03-28

In order to determine the molecular origin of the difference in electron and hole mobilities of amorphous thin films of Alq(3) (meridional Alq(3) (tris(8-hydroxyquinoline) aluminium)) we performed multiscale simulations covering quantum mechanics, molecular mechanics and lattice models. The study includes realistic disordered morphologies, polarized site energies to describe diagonal disorder, quantum chemically calculated transfer integrals for the off-diagonal disorder, inner sphere reorganization energies and an approximative scheme for outer sphere reorganization energies. Intermolecular transfer rates were calculated via Marcus-theory and mobilities were simulated via kinetic Monte Carlo simulations and by a Master Equation approach. The difference in electron and hole mobility originates from the different localization of charge density in the radical anion (more delocalized) compared to the radical cation (more confined). This results in higher diagonal disorder for holes and less favourable overlap properties for the hole transfer integrals leading to an overall higher electron mobility.

Efficient simulation of voxelized phantom in GATE with embedded SimSET multiple photon history generator.

PubMed

Lin, Hsin-Hon; Chuang, Keh-Shih; Lin, Yi-Hsing; Ni, Yu-Ching; Wu, Jay; Jan, Meei-Ling

2014-10-21

GEANT4 Application for Tomographic Emission (GATE) is a powerful Monte Carlo simulator that combines the advantages of the general-purpose GEANT4 simulation code and the specific software tool implementations dedicated to emission tomography. However, the detailed physical modelling of GEANT4 is highly computationally demanding, especially when tracking particles through voxelized phantoms. To circumvent the relatively slow simulation of voxelized phantoms in GATE, another efficient Monte Carlo code can be used to simulate photon interactions and transport inside a voxelized phantom. The simulation system for emission tomography (SimSET), a dedicated Monte Carlo code for PET/SPECT systems, is well-known for its efficiency in simulation of voxel-based objects. An efficient Monte Carlo workflow integrating GATE and SimSET for simulating pinhole SPECT has been proposed to improve voxelized phantom simulation. Although the workflow achieves a desirable increase in speed, it sacrifices the ability to simulate decaying radioactive sources such as non-pure positron emitters or multiple emission isotopes with complex decay schemes and lacks the modelling of time-dependent processes due to the inherent limitations of the SimSET photon history generator (PHG). Moreover, a large volume of disk storage is needed to store the huge temporal photon history file produced by SimSET that must be transported to GATE. In this work, we developed a multiple photon emission history generator (MPHG) based on SimSET/PHG to support a majority of the medically important positron emitters. We incorporated the new generator codes inside GATE to improve the simulation efficiency of voxelized phantoms in GATE, while eliminating the need for the temporal photon history file. The validation of this new code based on a MicroPET R4 system was conducted for (124)I and (18)F with mouse-like and rat-like phantoms. Comparison of GATE/MPHG with GATE/GEANT4 indicated there is a slight difference in energy spectra for energy below 50 keV due to the lack of x-ray simulation from (124)I decay in the new code. The spatial resolution, scatter fraction and count rate performance are in good agreement between the two codes. For the case studies of (18)F-NaF ((124)I-IAZG) using MOBY phantom with 1  ×  1 × 1 mm(3) voxel sizes, the results show that GATE/MPHG can achieve acceleration factors of approximately 3.1 × (4.5 ×), 6.5 × (10.7 ×) and 9.5 × (31.0 ×) compared with GATE using the regular navigation method, the compressed voxel method and the parameterized tracking technique, respectively. In conclusion, the implementation of MPHG in GATE allows for improved efficiency of voxelized phantom simulations and is suitable for studying clinical and preclinical imaging.

Parameterizing deep convection using the assumed probability density function method

DOE PAGES

Storer, R. L.; Griffin, B. M.; Höft, J.; ...

2014-06-11

Due to their coarse horizontal resolution, present-day climate models must parameterize deep convection. This paper presents single-column simulations of deep convection using a probability density function (PDF) parameterization. The PDF parameterization predicts the PDF of subgrid variability of turbulence, clouds, and hydrometeors. That variability is interfaced to a prognostic microphysics scheme using a Monte Carlo sampling method. The PDF parameterization is used to simulate tropical deep convection, the transition from shallow to deep convection over land, and mid-latitude deep convection. These parameterized single-column simulations are compared with 3-D reference simulations. The agreement is satisfactory except when the convective forcing ismore » weak. The same PDF parameterization is also used to simulate shallow cumulus and stratocumulus layers. The PDF method is sufficiently general to adequately simulate these five deep, shallow, and stratiform cloud cases with a single equation set. This raises hopes that it may be possible in the future, with further refinements at coarse time step and grid spacing, to parameterize all cloud types in a large-scale model in a unified way.« less

Further developments in cloud statistics for computer simulations

NASA Technical Reports Server (NTRS)

Chang, D. T.; Willand, J. H.

1972-01-01

This study is a part of NASA's continued program to provide global statistics of cloud parameters for computer simulation. The primary emphasis was on the development of the data bank of the global statistical distributions of cloud types and cloud layers and their applications in the simulation of the vertical distributions of in-cloud parameters such as liquid water content. These statistics were compiled from actual surface observations as recorded in Standard WBAN forms. Data for a total of 19 stations were obtained and reduced. These stations were selected to be representative of the 19 primary cloud climatological regions defined in previous studies of cloud statistics. Using the data compiled in this study, a limited study was conducted of the hemogeneity of cloud regions, the latitudinal dependence of cloud-type distributions, the dependence of these statistics on sample size, and other factors in the statistics which are of significance to the problem of simulation. The application of the statistics in cloud simulation was investigated. In particular, the inclusion of the new statistics in an expanded multi-step Monte Carlo simulation scheme is suggested and briefly outlined.

Parameterizing deep convection using the assumed probability density function method

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

Storer, R. L.; Griffin, B. M.; Höft, J.

2015-01-06

Due to their coarse horizontal resolution, present-day climate models must parameterize deep convection. This paper presents single-column simulations of deep convection using a probability density function (PDF) parameterization. The PDF parameterization predicts the PDF of subgrid variability of turbulence, clouds, and hydrometeors. That variability is interfaced to a prognostic microphysics scheme using a Monte Carlo sampling method.The PDF parameterization is used to simulate tropical deep convection, the transition from shallow to deep convection over land, and midlatitude deep convection. These parameterized single-column simulations are compared with 3-D reference simulations. The agreement is satisfactory except when the convective forcing is weak.more » The same PDF parameterization is also used to simulate shallow cumulus and stratocumulus layers. The PDF method is sufficiently general to adequately simulate these five deep, shallow, and stratiform cloud cases with a single equation set. This raises hopes that it may be possible in the future, with further refinements at coarse time step and grid spacing, to parameterize all cloud types in a large-scale model in a unified way.« less

Parameterizing deep convection using the assumed probability density function method

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

Storer, R. L.; Griffin, B. M.; Hoft, Jan

2015-01-06

Due to their coarse horizontal resolution, present-day climate models must parameterize deep convection. This paper presents single-column simulations of deep convection using a probability density function (PDF) parameterization. The PDF parameterization predicts the PDF of subgrid variability of turbulence, clouds, and hydrometeors. That variability is interfaced to a prognostic microphysics scheme using a Monte Carlo sampling method.The PDF parameterization is used to simulate tropical deep convection, the transition from shallow to deep convection over land, and mid-latitude deep convection.These parameterized single-column simulations are compared with 3-D reference simulations. The agreement is satisfactory except when the convective forcing is weak. Themore » same PDF parameterization is also used to simulate shallow cumulus and stratocumulus layers. The PDF method is sufficiently general to adequately simulate these five deep, shallow, and stratiform cloud cases with a single equation set. This raises hopes that it may be possible in the future, with further refinements at coarse time step and grid spacing, to parameterize all cloud types in a large-scale model in a unified way.« less

Sparsity-aware multiple relay selection in large multi-hop decode-and-forward relay networks

NASA Astrophysics Data System (ADS)

Gouissem, A.; Hamila, R.; Al-Dhahir, N.; Foufou, S.

2016-12-01

In this paper, we propose and investigate two novel techniques to perform multiple relay selection in large multi-hop decode-and-forward relay networks. The two proposed techniques exploit sparse signal recovery theory to select multiple relays using the orthogonal matching pursuit algorithm and outperform state-of-the-art techniques in terms of outage probability and computation complexity. To reduce the amount of collected channel state information (CSI), we propose a limited-feedback scheme where only a limited number of relays feedback their CSI. Furthermore, a detailed performance-complexity tradeoff investigation is conducted for the different studied techniques and verified by Monte Carlo simulations.

A New Closed Form Approximation for BER for Optical Wireless Systems in Weak Atmospheric Turbulence

NASA Astrophysics Data System (ADS)

Kaushik, Rahul; Khandelwal, Vineet; Jain, R. C.

2018-04-01

Weak atmospheric turbulence condition in an optical wireless communication (OWC) is captured by log-normal distribution. The analytical evaluation of average bit error rate (BER) of an OWC system under weak turbulence is intractable as it involves the statistical averaging of Gaussian Q-function over log-normal distribution. In this paper, a simple closed form approximation for BER of OWC system under weak turbulence is given. Computation of BER for various modulation schemes is carried out using proposed expression. The results obtained using proposed expression compare favorably with those obtained using Gauss-Hermite quadrature approximation and Monte Carlo Simulations.

An ellipsoid-chain model for conjugated polymer solutions

NASA Astrophysics Data System (ADS)

Lee, Cheng K.; Hua, Chi C.; Chen, Show A.

2012-02-01

We propose an ellipsoid-chain model which may be routinely parameterized to capture large-scale properties of semiflexible, amphiphilic conjugated polymers in various solvent media. The model naturally utilizes the defect locations as pivotal centers connecting adjacent ellipsoids (each currently representing ten monomer units), and a variant umbrella-sampling scheme is employed to construct the potentials of mean force (PMF) for specific solvent media using atomistic dynamics data and simplex optimization. The performances, both efficacy and efficiency, of the model are thoroughly evaluated by comparing the simulation results on long, single-chain (i.e., 300-mer) structures with those from two existing, finer-grained models for a standard conjugated polymer (i.e., poly(2-methoxy-5-(2'-ethylhexyloxy)-1,4-phenylenevinylene) or MEH-PPV) in two distinct solvents (i.e., chloroform or toluene) as well as a hybrid, binary-solvent medium (i.e., chloroform/toluene = 1:1 in number density). The coarse-grained Monte Carlo (CGMC) simulation of the ellipsoid-chain model is shown to be the most efficient—about 300 times faster than the coarse-grained molecular dynamics (CGMD) simulation of the finest CG model that employs explicit solvents—in capturing elementary single-chain structures for both single-solvent media, and is a few times faster than the coarse-grained Langevin dynamics (CGLD) simulation of another implicit-solvent polymer model with a slightly greater coarse-graining level than in the CGMD simulation. For the binary-solvent system considered, however, both of the two implicit-solvent schemes (i.e., CGMC and CGLD) fail to capture the effects of conspicuous concentration fluctuations near the polymer-solvent interface, arising from a pronounced coupling between the solvent molecules and different parts of the polymer. Essential physical implications are elaborated on the success as well as the failure of the two implicit-solvent CG schemes under varying solvent conditions. Within the ellipsoid-chain model, the impact of synthesized defects on local segmental ordering as well as bulk chain conformation is also scrutinized, and essential consequences in practical applications discussed. In future perspectives, we remark on strategy that takes advantage of the coordination among various CG models and simulation schemes to warrant computational efficiency and accuracy, with the anticipated capability of simulating larger-scale, many-chain aggregate systems.

Numerical integration of detector response functions via Monte Carlo simulations

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

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

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

Numerical integration of detector response functions via Monte Carlo simulations

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Numerical integration of detector response functions via Monte Carlo simulations

DOE PAGES

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

2017-06-13

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

Radiation pressure driving of a dusty atmosphere

NASA Astrophysics Data System (ADS)

Tsang, Benny T.-H.; Milosavljević, Miloš

2015-10-01

Radiation pressure can be dynamically important in star-forming environments such as ultra-luminous infrared and submillimetre galaxies. Whether and how radiation drives turbulence and bulk outflows in star formation sites is still unclear. The uncertainty in part reflects the limitations of direct numerical schemes that are currently used to simulate radiation transfer and radiation-gas coupling. An idealized setup in which radiation is introduced at the base of a dusty atmosphere in a gravitational field has recently become the standard test for radiation-hydrodynamics methods in the context of star formation. To a series of treatments featuring the flux-limited diffusion approximation as well as a short-characteristics tracing and M1 closure for the variable Eddington tensor approximation, we here add another treatment that is based on the implicit Monte Carlo radiation transfer scheme. Consistent with all previous treatments, the atmosphere undergoes Rayleigh-Taylor instability and readjusts to a near-Eddington-limited state. We detect late-time net acceleration in which the turbulent velocity dispersion matches that reported previously with the short-characteristics-based radiation transport closure, the most accurate of the three preceding treatments. Our technical result demonstrates the importance of accurate radiation transfer in simulations of radiative feedback.

A deterministic partial differential equation model for dose calculation in electron radiotherapy.

PubMed

Duclous, R; Dubroca, B; Frank, M

2010-07-07

High-energy ionizing radiation is a prominent modality for the treatment of many cancers. The approaches to electron dose calculation can be categorized into semi-empirical models (e.g. Fermi-Eyges, convolution-superposition) and probabilistic methods (e.g.Monte Carlo). A third approach to dose calculation has only recently attracted attention in the medical physics community. This approach is based on the deterministic kinetic equations of radiative transfer. We derive a macroscopic partial differential equation model for electron transport in tissue. This model involves an angular closure in the phase space. It is exact for the free streaming and the isotropic regime. We solve it numerically by a newly developed HLLC scheme based on Berthon et al (2007 J. Sci. Comput. 31 347-89) that exactly preserves the key properties of the analytical solution on the discrete level. We discuss several test cases taken from the medical physics literature. A test case with an academic Henyey-Greenstein scattering kernel is considered. We compare our model to a benchmark discrete ordinate solution. A simplified model of electron interactions with tissue is employed to compute the dose of an electron beam in a water phantom, and a case of irradiation of the vertebral column. Here our model is compared to the PENELOPE Monte Carlo code. In the academic example, the fluences computed with the new model and a benchmark result differ by less than 1%. The depths at half maximum differ by less than 0.6%. In the two comparisons with Monte Carlo, our model gives qualitatively reasonable dose distributions. Due to the crude interaction model, these so far do not have the accuracy needed in clinical practice. However, the new model has a computational cost that is less than one-tenth of the cost of a Monte Carlo simulation. In addition, simulations can be set up in a similar way as a Monte Carlo simulation. If more detailed effects such as coupled electron-photon transport, bremsstrahlung, Compton scattering and the production of delta electrons are added to our model, the computation time will only slightly increase. Its margin of error, on the other hand, will decrease and should be within a few per cent of the actual dose. Therefore, the new model has the potential to become useful for dose calculations in clinical practice.

A deterministic partial differential equation model for dose calculation in electron radiotherapy

NASA Astrophysics Data System (ADS)

Duclous, R.; Dubroca, B.; Frank, M.

2010-07-01

High-energy ionizing radiation is a prominent modality for the treatment of many cancers. The approaches to electron dose calculation can be categorized into semi-empirical models (e.g. Fermi-Eyges, convolution-superposition) and probabilistic methods (e.g. Monte Carlo). A third approach to dose calculation has only recently attracted attention in the medical physics community. This approach is based on the deterministic kinetic equations of radiative transfer. We derive a macroscopic partial differential equation model for electron transport in tissue. This model involves an angular closure in the phase space. It is exact for the free streaming and the isotropic regime. We solve it numerically by a newly developed HLLC scheme based on Berthon et al (2007 J. Sci. Comput. 31 347-89) that exactly preserves the key properties of the analytical solution on the discrete level. We discuss several test cases taken from the medical physics literature. A test case with an academic Henyey-Greenstein scattering kernel is considered. We compare our model to a benchmark discrete ordinate solution. A simplified model of electron interactions with tissue is employed to compute the dose of an electron beam in a water phantom, and a case of irradiation of the vertebral column. Here our model is compared to the PENELOPE Monte Carlo code. In the academic example, the fluences computed with the new model and a benchmark result differ by less than 1%. The depths at half maximum differ by less than 0.6%. In the two comparisons with Monte Carlo, our model gives qualitatively reasonable dose distributions. Due to the crude interaction model, these so far do not have the accuracy needed in clinical practice. However, the new model has a computational cost that is less than one-tenth of the cost of a Monte Carlo simulation. In addition, simulations can be set up in a similar way as a Monte Carlo simulation. If more detailed effects such as coupled electron-photon transport, bremsstrahlung, Compton scattering and the production of δ electrons are added to our model, the computation time will only slightly increase. Its margin of error, on the other hand, will decrease and should be within a few per cent of the actual dose. Therefore, the new model has the potential to become useful for dose calculations in clinical practice.

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

PubMed

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

2015-02-01

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

Monte Carlo Simulation for Perusal and Practice.

ERIC Educational Resources Information Center

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

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

Laser acceleration of electrons to giga-electron-volt energies using highly charged ions

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

Hu, S. X.; Starace, Anthony F.

2006-06-15

The recent proposal to use highly charged ions as sources of electrons for laser acceleration [S. X. Hu and A. F. Starace, Phys. Rev. Lett. 88, 245003 (2002)] is investigated here in detail by means of three-dimensional, relativistic Monte Carlo simulations for a variety of system parameters, such as laser pulse duration, ionic charge state, and laser focusing spot size. Realistic laser focusing effects--e.g., the existence of longitudinal laser field components--are taken into account. Results of spatial averaging over the laser focus are also presented. These numerical simulations show that the proposed scheme for laser acceleration of electrons from highlymore » charged ions is feasible with current or near-future experimental conditions and that electrons with GeV energies can be obtained in such experiments.« less

Variational Approach to Monte Carlo Renormalization Group

NASA Astrophysics Data System (ADS)

Wu, Yantao; Car, Roberto

2017-12-01

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

PDF approach for compressible turbulent reacting flows

NASA Technical Reports Server (NTRS)

Hsu, A. T.; Tsai, Y.-L. P.; Raju, M. S.

1993-01-01

The objective of the present work is to develop a probability density function (pdf) turbulence model for compressible reacting flows for use with a CFD flow solver. The probability density function of the species mass fraction and enthalpy are obtained by solving a pdf evolution equation using a Monte Carlo scheme. The pdf solution procedure is coupled with a compressible CFD flow solver which provides the velocity and pressure fields. A modeled pdf equation for compressible flows, capable of capturing shock waves and suitable to the present coupling scheme, is proposed and tested. Convergence of the combined finite-volume Monte Carlo solution procedure is discussed, and an averaging procedure is developed to provide smooth Monte-Carlo solutions to ensure convergence. Two supersonic diffusion flames are studied using the proposed pdf model and the results are compared with experimental data; marked improvements over CFD solutions without pdf are observed. Preliminary applications of pdf to 3D flows are also reported.

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

NASA Technical Reports Server (NTRS)

Deepak, A.; Fluellen, A.

1978-01-01

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

[Accuracy Check of Monte Carlo Simulation in Particle Therapy Using Gel Dosimeters].

PubMed

Furuta, Takuya

2017-01-01

Gel dosimeters are a three-dimensional imaging tool for dose distribution induced by radiations. They can be used for accuracy check of Monte Carlo simulation in particle therapy. An application was reviewed in this article. An inhomogeneous biological sample placing a gel dosimeter behind it was irradiated by carbon beam. The recorded dose distribution in the gel dosimeter reflected the inhomogeneity of the biological sample. Monte Carlo simulation was conducted by reconstructing the biological sample from its CT image. The accuracy of the particle transport by Monte Carlo simulation was checked by comparing the dose distribution in the gel dosimeter between simulation and experiment.

Coarse kMC-based replica exchange algorithms for the accelerated simulation of protein folding in explicit solvent.

PubMed

Peter, Emanuel K; Shea, Joan-Emma; Pivkin, Igor V

2016-05-14

In this paper, we present a coarse replica exchange molecular dynamics (REMD) approach, based on kinetic Monte Carlo (kMC). The new development significantly can reduce the amount of replicas and the computational cost needed to enhance sampling in protein simulations. We introduce 2 different methods which primarily differ in the exchange scheme between the parallel ensembles. We apply this approach on folding of 2 different β-stranded peptides: the C-terminal β-hairpin fragment of GB1 and TrpZip4. Additionally, we use the new simulation technique to study the folding of TrpCage, a small fast folding α-helical peptide. Subsequently, we apply the new methodology on conformation changes in signaling of the light-oxygen voltage (LOV) sensitive domain from Avena sativa (AsLOV2). Our results agree well with data reported in the literature. In simulations of dialanine, we compare the statistical sampling of the 2 techniques with conventional REMD and analyze their performance. The new techniques can reduce the computational cost of REMD significantly and can be used in enhanced sampling simulations of biomolecules.

Monte Carlo Analysis of Molecule Absorption Probabilities in Diffusion-Based Nanoscale Communication Systems with Multiple Receivers.

PubMed

Arifler, Dogu; Arifler, Dizem

2017-04-01

For biomedical applications of nanonetworks, employing molecular communication for information transport is advantageous over nano-electromagnetic communication: molecular communication is potentially biocompatible and inherently energy-efficient. Recently, several studies have modeled receivers in diffusion-based molecular communication systems as "perfectly monitoring" or "perfectly absorbing" spheres based on idealized descriptions of chemoreception. In this paper, we focus on perfectly absorbing receivers and present methods to improve the accuracy of simulation procedures that are used to analyze these receivers. We employ schemes available from the chemical physics and biophysics literature and outline a Monte Carlo simulation algorithm that accounts for the possibility of molecule absorption during discrete time steps, leading to a more accurate analysis of absorption probabilities. Unlike most existing studies that consider a single receiver, this paper analyzes absorption probabilities for multiple receivers deterministically or randomly deployed in a region. For random deployments, the ultimate absorption probabilities as a function of transmitter-receiver distance are shown to fit well to power laws; the exponents derived become more negative as the number of receivers increases up to a limit beyond which no additional receivers can be "packed" in the deployment region. This paper is expected to impact the design of molecular nanonetworks with multiple absorbing receivers.

Quantum Monte Carlo for large chemical systems: implementing efficient strategies for petascale platforms and beyond.

PubMed

Scemama, Anthony; Caffarel, Michel; Oseret, Emmanuel; Jalby, William

2013-04-30

Various strategies to implement efficiently quantum Monte Carlo (QMC) simulations for large chemical systems are presented. These include: (i) the introduction of an efficient algorithm to calculate the computationally expensive Slater matrices. This novel scheme is based on the use of the highly localized character of atomic Gaussian basis functions (not the molecular orbitals as usually done), (ii) the possibility of keeping the memory footprint minimal, (iii) the important enhancement of single-core performance when efficient optimization tools are used, and (iv) the definition of a universal, dynamic, fault-tolerant, and load-balanced framework adapted to all kinds of computational platforms (massively parallel machines, clusters, or distributed grids). These strategies have been implemented in the QMC=Chem code developed at Toulouse and illustrated with numerical applications on small peptides of increasing sizes (158, 434, 1056, and 1731 electrons). Using 10-80 k computing cores of the Curie machine (GENCI-TGCC-CEA, France), QMC=Chem has been shown to be capable of running at the petascale level, thus demonstrating that for this machine a large part of the peak performance can be achieved. Implementation of large-scale QMC simulations for future exascale platforms with a comparable level of efficiency is expected to be feasible. Copyright © 2013 Wiley Periodicals, Inc.

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.

Rapid Monte Carlo Simulation of Gravitational Wave Galaxies

NASA Astrophysics Data System (ADS)

Breivik, Katelyn; Larson, Shane L.

2015-01-01

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

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.

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

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

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

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

Validation of the Monte Carlo simulator GATE for indium-111 imaging.

PubMed

Assié, K; Gardin, I; Véra, P; Buvat, I

2005-07-07

Monte Carlo simulations are useful for optimizing and assessing single photon emission computed tomography (SPECT) protocols, especially when aiming at measuring quantitative parameters from SPECT images. Before Monte Carlo simulated data can be trusted, the simulation model must be validated. The purpose of this work was to validate the use of GATE, a new Monte Carlo simulation platform based on GEANT4, for modelling indium-111 SPECT data, the quantification of which is of foremost importance for dosimetric studies. To that end, acquisitions of (111)In line sources in air and in water and of a cylindrical phantom were performed, together with the corresponding simulations. The simulation model included Monte Carlo modelling of the camera collimator and of a back-compartment accounting for photomultiplier tubes and associated electronics. Energy spectra, spatial resolution, sensitivity values, images and count profiles obtained for experimental and simulated data were compared. An excellent agreement was found between experimental and simulated energy spectra. For source-to-collimator distances varying from 0 to 20 cm, simulated and experimental spatial resolution differed by less than 2% in air, while the simulated sensitivity values were within 4% of the experimental values. The simulation of the cylindrical phantom closely reproduced the experimental data. These results suggest that GATE enables accurate simulation of (111)In SPECT acquisitions.

A new configurational bias scheme for sampling supramolecular structures

NASA Astrophysics Data System (ADS)

De Gernier, Robin; Curk, Tine; Dubacheva, Galina V.; Richter, Ralf P.; Mognetti, Bortolo M.

2014-12-01

We present a new simulation scheme which allows an efficient sampling of reconfigurable supramolecular structures made of polymeric constructs functionalized by reactive binding sites. The algorithm is based on the configurational bias scheme of Siepmann and Frenkel and is powered by the possibility of changing the topology of the supramolecular network by a non-local Monte Carlo algorithm. Such a plan is accomplished by a multi-scale modelling that merges coarse-grained simulations, describing the typical polymer conformations, with experimental results accounting for free energy terms involved in the reactions of the active sites. We test the new algorithm for a system of DNA coated colloids for which we compute the hybridisation free energy cost associated to the binding of tethered single stranded DNAs terminated by short sequences of complementary nucleotides. In order to demonstrate the versatility of our method, we also consider polymers functionalized by receptors that bind a surface decorated by ligands. In particular, we compute the density of states of adsorbed polymers as a function of the number of ligand-receptor complexes formed. Such a quantity can be used to study the conformational properties of adsorbed polymers useful when engineering adsorption with tailored properties. We successfully compare the results with the predictions of a mean field theory. We believe that the proposed method will be a useful tool to investigate supramolecular structures resulting from direct interactions between functionalized polymers for which efficient numerical methodologies of investigation are still lacking.

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

PubMed

Beentjes, Casper H L; Baker, Ruth E

2018-05-25

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

Simulations of non-relativistic quantum chromodynamics at strong and weak coupling

NASA Astrophysics Data System (ADS)

Shakespeare, Norman Harold

In this thesis heavy quarks are investigated using lattice nonrelativistic quantum chromodynamics (NRQCD). Two major research works are presented. In the first major work, simulations are done for the three quarkonium systems cc¯, bc¯, and bb¯. The hyperfine splittings are computed at both leading and next-to-leading order in the relativistic expansion, using a large number of lattice spacings. A detailed comparison between mean-link and average plaquette tadpole renormalization schemes is undertaken with a number of features favouring the use of mean-links. These include much better scaling behavior of the hyperfine splittings and smaller relativistic corrections to the spin splittings. Signs of a breakdown in the NRQCD expansion are seen when the bare quark mass, in lattice units, falls below about one. In the second work, coefficients for the perturbative expansion of the static quark self energy are extracted from Monte Carlo simulations in the perturbative region of lattice quantum chromodynamics (QCD). A very large systematic study resulted in a major extension of existing methods. Twisted boundary conditions are used to eliminate the effects of zero modes and to suppress tunneling between the degenerate Z3 vacua. The Monte Carlo results are in excellent agreement with analytic perturbation theory, which is known through second order. New results for the third order coefficient are reported. Preliminary work is reported on quark propagators which will be used to measure second order mass renormalizations for NRQCD fermions.

Re-186 and Sm-153 dosimetry based on scintigraphic imaging data in skeletal metastasis palliative treatment and Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Andreou, M.; Lagopati, N.; Lyra, M.

2011-09-01

Optimum treatment planning of patients suffering from painful skeletal metastases requires accurate calculations concerning absorbed dose in metastatic lesions and critical organs, such as red marrow. Delivering high doses to tumor cells while limiting radiation dose to normal tissue, is the key for successful palliation treatment. The aim of this study is to compare the dosimetric calculations, obtained by Monte Carlo (MC) simulation and the MIRDOSE model, in therapeutic schemes of skeleton metastatic lesions, with Rhenium-186 (Sn) -HEDP and Samarium-153 -EDTMP. A bolus injection of 1295 MBq (35mCi) Re-186- HEDP was infused in 11 patients with multiple skeletal metastases. The administered dose for the 8 patients who received Sm-153 was 1 mCi /kg. Planar scintigraphic images for the two groups of patients were obtained, 24 h, 48 h and 72 h post injection, by an Elscint Apex SPX gamma camera. The images were processed, utilizing ROI quantitative methods, to determine residence times and radionuclide uptakes. Dosimetric calculations were performed using the patient specific scintigraphic data by the MIRDOSE3 code of MIRD. Also, MCNPX was employed, simulating the distribution of the radioisotope in the ROI and calculating the absorbed doses in the metastatic lesion, and in critical organs. Summarizing, there is a good agreement between the results, derived from the two pathways, the patient specific and the mathematical, with a deviation of less than 9% for planar scintigraphic data compared to MC, for both radiopharmaceuticals.

Celestial Object Imaging Model and Parameter Optimization for an Optical Navigation Sensor Based on the Well Capacity Adjusting Scheme.

PubMed

Wang, Hao; Jiang, Jie; Zhang, Guangjun

2017-04-21

The simultaneous extraction of optical navigation measurements from a target celestial body and star images is essential for autonomous optical navigation. Generally, a single optical navigation sensor cannot simultaneously image the target celestial body and stars well-exposed because their irradiance difference is generally large. Multi-sensor integration or complex image processing algorithms are commonly utilized to solve the said problem. This study analyzes and demonstrates the feasibility of simultaneously imaging the target celestial body and stars well-exposed within a single exposure through a single field of view (FOV) optical navigation sensor using the well capacity adjusting (WCA) scheme. First, the irradiance characteristics of the celestial body are analyzed. Then, the celestial body edge model and star spot imaging model are established when the WCA scheme is applied. Furthermore, the effect of exposure parameters on the accuracy of star centroiding and edge extraction is analyzed using the proposed model. Optimal exposure parameters are also derived by conducting Monte Carlo simulation to obtain the best performance of the navigation sensor. Finally, laboratorial and night sky experiments are performed to validate the correctness of the proposed model and optimal exposure parameters.

Optimizing Cubature for Efficient Integration of Subspace Deformations

PubMed Central

An, Steven S.; Kim, Theodore; James, Doug L.

2009-01-01

We propose an efficient scheme for evaluating nonlinear subspace forces (and Jacobians) associated with subspace deformations. The core problem we address is efficient integration of the subspace force density over the 3D spatial domain. Similar to Gaussian quadrature schemes that efficiently integrate functions that lie in particular polynomial subspaces, we propose cubature schemes (multi-dimensional quadrature) optimized for efficient integration of force densities associated with particular subspace deformations, particular materials, and particular geometric domains. We support generic subspace deformation kinematics, and nonlinear hyperelastic materials. For an r-dimensional deformation subspace with O(r) cubature points, our method is able to evaluate subspace forces at O(r2) cost. We also describe composite cubature rules for runtime error estimation. Results are provided for various subspace deformation models, several hyperelastic materials (St.Venant-Kirchhoff, Mooney-Rivlin, Arruda-Boyce), and multimodal (graphics, haptics, sound) applications. We show dramatically better efficiency than traditional Monte Carlo integration. CR Categories: I.6.8 [Simulation and Modeling]: Types of Simulation—Animation, I.3.5 [Computer Graphics]: Computational Geometry and Object Modeling—Physically based modeling G.1.4 [Mathematics of Computing]: Numerical Analysis—Quadrature and Numerical Differentiation PMID:19956777

Celestial Object Imaging Model and Parameter Optimization for an Optical Navigation Sensor Based on the Well Capacity Adjusting Scheme

PubMed Central

Wang, Hao; Jiang, Jie; Zhang, Guangjun

2017-01-01

The simultaneous extraction of optical navigation measurements from a target celestial body and star images is essential for autonomous optical navigation. Generally, a single optical navigation sensor cannot simultaneously image the target celestial body and stars well-exposed because their irradiance difference is generally large. Multi-sensor integration or complex image processing algorithms are commonly utilized to solve the said problem. This study analyzes and demonstrates the feasibility of simultaneously imaging the target celestial body and stars well-exposed within a single exposure through a single field of view (FOV) optical navigation sensor using the well capacity adjusting (WCA) scheme. First, the irradiance characteristics of the celestial body are analyzed. Then, the celestial body edge model and star spot imaging model are established when the WCA scheme is applied. Furthermore, the effect of exposure parameters on the accuracy of star centroiding and edge extraction is analyzed using the proposed model. Optimal exposure parameters are also derived by conducting Monte Carlo simulation to obtain the best performance of the navigation sensor. Finally, laboratorial and night sky experiments are performed to validate the correctness of the proposed model and optimal exposure parameters. PMID:28430132

A self-adaptive memeplexes robust search scheme for solving stochastic demands vehicle routing problem

NASA Astrophysics Data System (ADS)

Chen, Xianshun; Feng, Liang; Ong, Yew Soon

2012-07-01

In this article, we proposed a self-adaptive memeplex robust search (SAMRS) for finding robust and reliable solutions that are less sensitive to stochastic behaviours of customer demands and have low probability of route failures, respectively, in vehicle routing problem with stochastic demands (VRPSD). In particular, the contribution of this article is three-fold. First, the proposed SAMRS employs the robust solution search scheme (RS 3) as an approximation of the computationally intensive Monte Carlo simulation, thus reducing the computation cost of fitness evaluation in VRPSD, while directing the search towards robust and reliable solutions. Furthermore, a self-adaptive individual learning based on the conceptual modelling of memeplex is introduced in the SAMRS. Finally, SAMRS incorporates a gene-meme co-evolution model with genetic and memetic representation to effectively manage the search for solutions in VRPSD. Extensive experimental results are then presented for benchmark problems to demonstrate that the proposed SAMRS serves as an efficable means of generating high-quality robust and reliable solutions in VRPSD.

Thermal Neutron Capture onto the Stable Tungsten Isotopes

NASA Astrophysics Data System (ADS)

Hurst, A. M.; Firestone, R. B.; Sleaford, B. W.; Summers, N. C.; Revay, Zs.; Szentmiklósi, L.; Belgya, T.; Basunia, M. S.; Capote, R.; Choi, H.; Dashdorj, D.; Escher, J.; Krticka, M.; Nichols, A.

2012-02-01

Thermal neutron-capture measurements of the stable tungsten isotopes have been carried out using the guided thermal-neutron beam at the Budapest Reactor. Prompt singles spectra were collected and analyzed using the HYPERMET γ-ray analysis software package for the compound tungsten systems 183W, 184W, and 187W, prepared from isotopically-enriched samples of 182W, 183W, and 186W, respectively. These new data provide both confirmation and new insights into the decay schemes and structure of the tungsten isotopes reported in the Evaluated Gamma-ray Activation File based upon previous elemental analysis. The experimental data have also been compared to Monte Carlo simulations of γ-ray emission following the thermal neutron-capture process using the statistical-decay code DICEBOX. Together, the experimental cross sections and modeledfeeding contribution from the quasi continuum, have been used to determine the total radiative thermal neutron-capture cross sections for the tungsten isotopes and provide improved decay-scheme information for the structural- and neutron-data libraries.

Synchronous parallel spatially resolved stochastic cluster dynamics

DOE PAGES

Dunn, Aaron; Dingreville, Rémi; Martínez, Enrique; ...

2016-04-23

In this work, a spatially resolved stochastic cluster dynamics (SRSCD) model for radiation damage accumulation in metals is implemented using a synchronous parallel kinetic Monte Carlo algorithm. The parallel algorithm is shown to significantly increase the size of representative volumes achievable in SRSCD simulations of radiation damage accumulation. Additionally, weak scaling performance of the method is tested in two cases: (1) an idealized case of Frenkel pair diffusion and annihilation, and (2) a characteristic example problem including defect cluster formation and growth in α-Fe. For the latter case, weak scaling is tested using both Frenkel pair and displacement cascade damage.more » To improve scaling of simulations with cascade damage, an explicit cascade implantation scheme is developed for cases in which fast-moving defects are created in displacement cascades. For the first time, simulation of radiation damage accumulation in nanopolycrystals can be achieved with a three dimensional rendition of the microstructure, allowing demonstration of the effect of grain size on defect accumulation in Frenkel pair-irradiated α-Fe.« less

Soybean Physiology Calibration in the Community Land Model

NASA Astrophysics Data System (ADS)

Drewniak, B. A.; Bilionis, I.; Constantinescu, E. M.

2014-12-01

With the large influence of agricultural land use on biophysical and biogeochemical cycles, integrating cultivation into Earth System Models (ESMs) is increasingly important. The Community Land Model (CLM) was augmented with a CLM-Crop extension that simulates the development of three crop types: maize, soybean, and spring wheat. The CLM-Crop model is a complex system that relies on a suite of parametric inputs that govern plant growth under a given atmospheric forcing and available resources. However, the strong nonlinearity of ESMs makes parameter fitting a difficult task. In this study, our goal is to calibrate ten of the CLM-Crop parameters for one crop type, soybean, in order to improve model projection of plant development and carbon fluxes. We used measurements of gross primary productivity, net ecosystem exchange, and plant biomass from AmeriFlux sites to choose parameter values that optimize crop productivity in the model. Calibration is performed in a Bayesian framework by developing a scalable and adaptive scheme based on sequential Monte Carlo (SMC). Our scheme can perform model calibration using very few evaluations and, by exploiting parallelism, at a fraction of the time required by plain vanilla Markov Chain Monte Carlo (MCMC). We present the results from a twin experiment (self-validation) and calibration results and validation using real observations from an AmeriFlux tower site in the Midwestern United States, for the soybean crop type. The improved model will help researchers understand how climate affects crop production and resulting carbon fluxes, and additionally, how cultivation impacts climate.

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

PubMed

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

2010-08-01

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

Statistical thermodynamics of long straight rigid rods on triangular lattices: nematic order and adsorption thermodynamic functions.

PubMed

Matoz-Fernandez, D A; Linares, D H; Ramirez-Pastor, A J

2012-09-04

The statistical thermodynamics of straight rigid rods of length k on triangular lattices was developed on a generalization in the spirit of the lattice-gas model and the classical Guggenheim-DiMarzio approximation. In this scheme, the Helmholtz free energy and its derivatives were written in terms of the order parameter, δ, which characterizes the nematic phase occurring in the system at intermediate densities. Then, using the principle of minimum free energy with δ as a parameter, the main adsorption properties were calculated. Comparisons with Monte Carlo simulations and experimental data were performed in order to evaluate the outcome and limitations of the theoretical model.

Spin-squeezing and Dicke-state preparation by heterodyne measurement

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

Vanderbruggen, T.; Bernon, S.; Bertoldi, A.

2011-01-15

We investigate the quantum nondemolition (QND) measurement of an atomic population based on a heterodyne detection and show that the induced back-action allows for the preparation of both spin-squeezed and Dicke states. We use a wave-vector formalism to describe the stochastic process of the measurement and the associated atomic evolution. Analytical formulas of the atomic distribution momenta are derived in the weak-coupling regime both for short- and long-time behavior, and they are in good agreement with those obtained by a Monte Carlo simulation. The experimental implementation of the proposed heterodyne detection scheme is discussed. The role played in the squeezingmore » process by the spontaneous emission is considered.« less

An evaluation of sampling and full enumeration strategies for Fisher Jenks classification in big data settings

USGS Publications Warehouse

Rey, Sergio J.; Stephens, Philip A.; Laura, Jason R.

2017-01-01

Large data contexts present a number of challenges to optimal choropleth map classifiers. Application of optimal classifiers to a sample of the attribute space is one proposed solution. The properties of alternative sampling-based classification methods are examined through a series of Monte Carlo simulations. The impacts of spatial autocorrelation, number of desired classes, and form of sampling are shown to have significant impacts on the accuracy of map classifications. Tradeoffs between improved speed of the sampling approaches and loss of accuracy are also considered. The results suggest the possibility of guiding the choice of classification scheme as a function of the properties of large data sets.

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

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

Massively parallel simulator of optical coherence tomography of inhomogeneous turbid media.

PubMed

Malektaji, Siavash; Lima, Ivan T; Escobar I, Mauricio R; Sherif, Sherif S

2017-10-01

An accurate and practical simulator for Optical Coherence Tomography (OCT) could be an important tool to study the underlying physical phenomena in OCT such as multiple light scattering. Recently, many researchers have investigated simulation of OCT of turbid media, e.g., tissue, using Monte Carlo methods. The main drawback of these earlier simulators is the long computational time required to produce accurate results. We developed a massively parallel simulator of OCT of inhomogeneous turbid media that obtains both Class I diffusive reflectivity, due to ballistic and quasi-ballistic scattered photons, and Class II diffusive reflectivity due to multiply scattered photons. This Monte Carlo-based simulator is implemented on graphic processing units (GPUs), using the Compute Unified Device Architecture (CUDA) platform and programming model, to exploit the parallel nature of propagation of photons in tissue. It models an arbitrary shaped sample medium as a tetrahedron-based mesh and uses an advanced importance sampling scheme. This new simulator speeds up simulations of OCT of inhomogeneous turbid media by about two orders of magnitude. To demonstrate this result, we have compared the computation times of our new parallel simulator and its serial counterpart using two samples of inhomogeneous turbid media. We have shown that our parallel implementation reduced simulation time of OCT of the first sample medium from 407 min to 92 min by using a single GPU card, to 12 min by using 8 GPU cards and to 7 min by using 16 GPU cards. For the second sample medium, the OCT simulation time was reduced from 209 h to 35.6 h by using a single GPU card, and to 4.65 h by using 8 GPU cards, and to only 2 h by using 16 GPU cards. Therefore our new parallel simulator is considerably more practical to use than its central processing unit (CPU)-based counterpart. Our new parallel OCT simulator could be a practical tool to study the different physical phenomena underlying OCT, or to design OCT systems with improved performance. Copyright © 2017 Elsevier B.V. All rights reserved.

A Novel Strategy for Numerical Simulation of High-speed Turbulent Reacting Flows

NASA Technical Reports Server (NTRS)

Sheikhi, M. R. H.; Drozda, T. G.; Givi, P.

2003-01-01

The objective of this research is to improve and implement the filtered mass density function (FDF) methodology for large eddy simulation (LES) of high-speed reacting turbulent flows. We have just completed Year 1 of this research. This is the Final Report on our activities during the period: January 1, 2003 to December 31, 2003. 2002. In the efforts during the past year, LES is conducted of the Sandia Flame D, which is a turbulent piloted nonpremixed methane jet flame. The subgrid scale (SGS) closure is based on the scalar filtered mass density function (SFMDF) methodology. The SFMDF is basically the mass weighted probability density function (PDF) of the SGS scalar quantities. For this flame (which exhibits little local extinction), a simple flamelet model is used to relate the instantaneous composition to the mixture fraction. The modelled SFMDF transport equation is solved by a hybrid finite-difference/Monte Carlo scheme.

Channel Training for Analog FDD Repeaters: Optimal Estimators and Cramér-Rao Bounds

NASA Astrophysics Data System (ADS)

Wesemann, Stefan; Marzetta, Thomas L.

2017-12-01

For frequency division duplex channels, a simple pilot loop-back procedure has been proposed that allows the estimation of the UL & DL channels at an antenna array without relying on any digital signal processing at the terminal side. For this scheme, we derive the maximum likelihood (ML) estimators for the UL & DL channel subspaces, formulate the corresponding Cram\\'er-Rao bounds and show the asymptotic efficiency of both (SVD-based) estimators by means of Monte Carlo simulations. In addition, we illustrate how to compute the underlying (rank-1) SVD with quadratic time complexity by employing the power iteration method. To enable power control for the data transmission, knowledge of the channel gains is needed. Assuming that the UL & DL channels have on average the same gain, we formulate the ML estimator for the channel norm, and illustrate its robustness against strong noise by means of simulations.

Calculation of Coincidence Summing Correction Factors for an HPGe detector using GEANT4.

PubMed

Giubrone, G; Ortiz, J; Gallardo, S; Martorell, S; Bas, M C

2016-07-01

The aim of this paper was to calculate the True Coincidence Summing Correction Factors (TSCFs) for an HPGe coaxial detector in order to correct the summing effect as a result of the presence of (88)Y and (60)Co in a multigamma source used to obtain a calibration efficiency curve. Results were obtained for three volumetric sources using the Monte Carlo toolkit, GEANT4. The first part of this paper deals with modeling the detector in order to obtain a simulated full energy peak efficiency curve. A quantitative comparison between the measured and simulated values was made across the entire energy range under study. The True Summing Correction Factors were calculated for (88)Y and (60)Co using the full peak efficiencies obtained with GEANT4. This methodology was subsequently applied to (134)Cs, and presented a complex decay scheme. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Guan, Fada

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

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

Monte Carlo Modeling of the Initial Radiation Emitted by a Nuclear Device in the National Capital Region

DTIC Science & Technology

2013-07-01

also simulated in the models. Data was derived from calculations using the three-dimensional Monte Carlo radiation transport code MCNP (Monte Carlo N...32  B.  MCNP PHYSICS OPTIONS ......................................................................................... 33  C.  HAZUS...input deck’) for the MCNP , Monte Carlo N-Particle, radiation transport code. MCNP is a general-purpose code designed to simulate neutron, photon

Correlational and thermodynamic properties of finite-temperature electron liquids in the hypernetted-chain approximation.

PubMed

Tanaka, Shigenori

2016-12-07

Correlational and thermodynamic properties of homogeneous electron liquids at finite temperatures are theoretically analyzed in terms of dielectric response formalism with the hypernetted-chain (HNC) approximation and its modified version. The static structure factor and the local-field correction to describe the strong Coulomb-coupling effects beyond the random-phase approximation are self-consistently calculated through solution to integral equations in the paramagnetic (spin unpolarized) and ferromagnetic (spin polarized) states. In the ground state with the normalized temperature θ=0, the present HNC scheme well reproduces the exchange-correlation energies obtained by quantum Monte Carlo (QMC) simulations over the whole fluid phase (the coupling constant r s ≤100), i.e., within 1% and 2% deviations from putative best QMC values in the paramagnetic and ferromagnetic states, respectively. As compared with earlier studies based on the Singwi-Tosi-Land-Sjölander and modified convolution approximations, some improvements on the correlation energies and the correlation functions including the compressibility sum rule are found in the intermediate to strong coupling regimes. When applied to the electron fluids at intermediate Fermi degeneracies (θ≈1), the static structure factors calculated in the HNC scheme show good agreements with the results obtained by the path integral Monte Carlo (PIMC) simulation, while a small negative region in the radial distribution function is observed near the origin, which may be associated with a slight overestimation for the exchange-correlation hole in the HNC approximation. The interaction energies are calculated for various combinations of density and temperature parameters ranging from strong to weak degeneracy and from weak to strong coupling, and the HNC values are then parametrized as functions of r s and θ. The HNC exchange-correlation free energies obtained through the coupling-constant integration show reasonable agreements with earlier results including the PIMC-based fitting over the whole fluid region at finite degeneracies in the paramagnetic state. In contrast, a systematic difference between the HNC and PIMC results is observed in the ferromagnetic state, which suggests a necessity of further studies on the exchange-correlation free energies from both aspects of analytical theory and simulation.

The implications of regional and national demographic projections for future GMS costs in Ireland through to 2026.

PubMed

Conway, Aisling; Kenneally, Martin; Woods, Noel; Thummel, Andreas; Ryan, Marie

2014-10-21

As the health services in Ireland have become more resource-constrained, pressure has increased to reduce public spending on community drug schemes such as General Medical Services (GMS) drug prescribing and to understand current and future trends in prescribing. The GMS scheme covers approximately 37% of the Irish population in 2011 and entitles them, inter alia, to free prescription drugs and appliances. This paper projects the effects of future changes in population, coverage, claims rates and average claims cost on GMS costs in Ireland. Data on GMS coverage, claims rates and average cost per claim are drawn from the Primary Care Reimbursement Service (PCRS) and combined with Central Statistics Office (CSO) (Regional and National Population Projections through to 2026). A Monte Carlo Model is used to simulate the effects of demographic change (by region, age, gender, coverage, claims rates and average claims cost) will have on GMS prescribing costs in 2016, 2021 and 2026 under different scenarios. The Population of Ireland is projected to grow by 32% between 2007 and 2026 and by 96% for the over 70s. The Eastern region is estimated to grow by 3% over the lifetime of the projections at the expense of most other regions. The Monte Carlo simulations project that females will be a bigger driver of GMS costs than males. Midlands region will be the most expensive of the eight old health board regions. Those aged 70 and over and children under 11 will be significant drivers of GMS costs with the impending demographic changes. Overall GMS medicines costs are projected to rise to €1.9bn by 2026. Ireland's population will experience rapid growth over the next decade. Population growth coupled with an aging population will result in an increase in coverage rates, thus the projected increase in overall prescribing costs. Our projections and simulations map the likely evolution of GMS cost, given existing policies and demographic trends. These costs can be contained by government policy initiatives.

Information criteria for quantifying loss of reversibility in parallelized KMC

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

Gourgoulias, Konstantinos, E-mail: gourgoul@math.umass.edu; Katsoulakis, Markos A., E-mail: markos@math.umass.edu; Rey-Bellet, Luc, E-mail: luc@math.umass.edu

Parallel Kinetic Monte Carlo (KMC) is a potent tool to simulate stochastic particle systems efficiently. However, despite literature on quantifying domain decomposition errors of the particle system for this class of algorithms in the short and in the long time regime, no study yet explores and quantifies the loss of time-reversibility in Parallel KMC. Inspired by concepts from non-equilibrium statistical mechanics, we propose the entropy production per unit time, or entropy production rate, given in terms of an observable and a corresponding estimator, as a metric that quantifies the loss of reversibility. Typically, this is a quantity that cannot bemore » computed explicitly for Parallel KMC, which is why we develop a posteriori estimators that have good scaling properties with respect to the size of the system. Through these estimators, we can connect the different parameters of the scheme, such as the communication time step of the parallelization, the choice of the domain decomposition, and the computational schedule, with its performance in controlling the loss of reversibility. From this point of view, the entropy production rate can be seen both as an information criterion to compare the reversibility of different parallel schemes and as a tool to diagnose reversibility issues with a particular scheme. As a demonstration, we use Sandia Lab's SPPARKS software to compare different parallelization schemes and different domain (lattice) decompositions.« less

Information criteria for quantifying loss of reversibility in parallelized KMC

NASA Astrophysics Data System (ADS)

Gourgoulias, Konstantinos; Katsoulakis, Markos A.; Rey-Bellet, Luc

2017-01-01

Parallel Kinetic Monte Carlo (KMC) is a potent tool to simulate stochastic particle systems efficiently. However, despite literature on quantifying domain decomposition errors of the particle system for this class of algorithms in the short and in the long time regime, no study yet explores and quantifies the loss of time-reversibility in Parallel KMC. Inspired by concepts from non-equilibrium statistical mechanics, we propose the entropy production per unit time, or entropy production rate, given in terms of an observable and a corresponding estimator, as a metric that quantifies the loss of reversibility. Typically, this is a quantity that cannot be computed explicitly for Parallel KMC, which is why we develop a posteriori estimators that have good scaling properties with respect to the size of the system. Through these estimators, we can connect the different parameters of the scheme, such as the communication time step of the parallelization, the choice of the domain decomposition, and the computational schedule, with its performance in controlling the loss of reversibility. From this point of view, the entropy production rate can be seen both as an information criterion to compare the reversibility of different parallel schemes and as a tool to diagnose reversibility issues with a particular scheme. As a demonstration, we use Sandia Lab's SPPARKS software to compare different parallelization schemes and different domain (lattice) decompositions.

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.

Study the sensitivity of dose calculation in prism treatment planning system using Monte Carlo simulation of 6 MeV electron beam

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

Hardiansyah, D.; Haryanto, F.; Male, S.

2014-09-30

Prism is a non-commercial Radiotherapy Treatment Planning System (RTPS) develop by Ira J. Kalet from Washington University. Inhomogeneity factor is included in Prism TPS dose calculation. The aim of this study is to investigate the sensitivity of dose calculation on Prism using Monte Carlo simulation. Phase space source from head linear accelerator (LINAC) for Monte Carlo simulation is implemented. To achieve this aim, Prism dose calculation is compared with EGSnrc Monte Carlo simulation. Percentage depth dose (PDD) and R50 from both calculations are observed. BEAMnrc is simulated electron transport in LINAC head and produced phase space file. This file ismore » used as DOSXYZnrc input to simulated electron transport in phantom. This study is started with commissioning process in water phantom. Commissioning process is adjusted Monte Carlo simulation with Prism RTPS. Commissioning result is used for study of inhomogeneity phantom. Physical parameters of inhomogeneity phantom that varied in this study are: density, location and thickness of tissue. Commissioning result is shown that optimum energy of Monte Carlo simulation for 6 MeV electron beam is 6.8 MeV. This commissioning is used R50 and PDD with Practical length (R{sub p}) as references. From inhomogeneity study, the average deviation for all case on interest region is below 5 %. Based on ICRU recommendations, Prism has good ability to calculate the radiation dose in inhomogeneity tissue.« less

DPM, a fast, accurate Monte Carlo code optimized for photon and electron radiotherapy treatment planning dose calculations

NASA Astrophysics Data System (ADS)

Sempau, Josep; Wilderman, Scott J.; Bielajew, Alex F.

2000-08-01

A new Monte Carlo (MC) algorithm, the `dose planning method' (DPM), and its associated computer program for simulating the transport of electrons and photons in radiotherapy class problems employing primary electron beams, is presented. DPM is intended to be a high-accuracy MC alternative to the current generation of treatment planning codes which rely on analytical algorithms based on an approximate solution of the photon/electron Boltzmann transport equation. For primary electron beams, DPM is capable of computing 3D dose distributions (in 1 mm3 voxels) which agree to within 1% in dose maximum with widely used and exhaustively benchmarked general-purpose public-domain MC codes in only a fraction of the CPU time. A representative problem, the simulation of 1 million 10 MeV electrons impinging upon a water phantom of 1283 voxels of 1 mm on a side, can be performed by DPM in roughly 3 min on a modern desktop workstation. DPM achieves this performance by employing transport mechanics and electron multiple scattering distribution functions which have been derived to permit long transport steps (of the order of 5 mm) which can cross heterogeneity boundaries. The underlying algorithm is a `mixed' class simulation scheme, with differential cross sections for hard inelastic collisions and bremsstrahlung events described in an approximate manner to simplify their sampling. The continuous energy loss approximation is employed for energy losses below some predefined thresholds, and photon transport (including Compton, photoelectric absorption and pair production) is simulated in an analogue manner. The δ-scattering method (Woodcock tracking) is adopted to minimize the computational costs of transporting photons across voxels.

Maier-Saupe model of polymer nematics: Comparing free energies calculated with Self Consistent Field theory and Monte Carlo simulations.

PubMed

Greco, Cristina; Jiang, Ying; Chen, Jeff Z Y; Kremer, Kurt; Daoulas, Kostas Ch

2016-11-14

Self Consistent Field (SCF) theory serves as an efficient tool for studying mesoscale structure and thermodynamics of polymeric liquid crystals (LC). We investigate how some of the intrinsic approximations of SCF affect the description of the thermodynamics of polymeric LC, using a coarse-grained model. Polymer nematics are represented as discrete worm-like chains (WLC) where non-bonded interactions are defined combining an isotropic repulsive and an anisotropic attractive Maier-Saupe (MS) potential. The range of the potentials, σ, controls the strength of correlations due to non-bonded interactions. Increasing σ (which can be seen as an increase of coarse-graining) while preserving the integrated strength of the potentials reduces correlations. The model is studied with particle-based Monte Carlo (MC) simulations and SCF theory which uses partial enumeration to describe discrete WLC. In MC simulations the Helmholtz free energy is calculated as a function of strength of MS interactions to obtain reference thermodynamic data. To calculate the free energy of the nematic branch with respect to the disordered melt, we employ a special thermodynamic integration (TI) scheme invoking an external field to bypass the first-order isotropic-nematic transition. Methodological aspects which have not been discussed in earlier implementations of the TI to LC are considered. Special attention is given to the rotational Goldstone mode. The free-energy landscape in MC and SCF is directly compared. For moderate σ the differences highlight the importance of local non-bonded orientation correlations between segments, which SCF neglects. Simple renormalization of parameters in SCF cannot compensate the missing correlations. Increasing σ reduces correlations and SCF reproduces well the free energy in MC simulations.

Corruption of accuracy and efficiency of Markov chain Monte Carlo simulation by inaccurate numerical implementation of conceptual hydrologic models

NASA Astrophysics Data System (ADS)

Schoups, G.; Vrugt, J. A.; Fenicia, F.; van de Giesen, N. C.

2010-10-01

Conceptual rainfall-runoff models have traditionally been applied without paying much attention to numerical errors induced by temporal integration of water balance dynamics. Reliance on first-order, explicit, fixed-step integration methods leads to computationally cheap simulation models that are easy to implement. Computational speed is especially desirable for estimating parameter and predictive uncertainty using Markov chain Monte Carlo (MCMC) methods. Confirming earlier work of Kavetski et al. (2003), we show here that the computational speed of first-order, explicit, fixed-step integration methods comes at a cost: for a case study with a spatially lumped conceptual rainfall-runoff model, it introduces artificial bimodality in the marginal posterior parameter distributions, which is not present in numerically accurate implementations of the same model. The resulting effects on MCMC simulation include (1) inconsistent estimates of posterior parameter and predictive distributions, (2) poor performance and slow convergence of the MCMC algorithm, and (3) unreliable convergence diagnosis using the Gelman-Rubin statistic. We studied several alternative numerical implementations to remedy these problems, including various adaptive-step finite difference schemes and an operator splitting method. Our results show that adaptive-step, second-order methods, based on either explicit finite differencing or operator splitting with analytical integration, provide the best alternative for accurate and efficient MCMC simulation. Fixed-step or adaptive-step implicit methods may also be used for increased accuracy, but they cannot match the efficiency of adaptive-step explicit finite differencing or operator splitting. Of the latter two, explicit finite differencing is more generally applicable and is preferred if the individual hydrologic flux laws cannot be integrated analytically, as the splitting method then loses its advantage.

Validation of an In-Water, Tower-Shading Correction Scheme

NASA Technical Reports Server (NTRS)

Hooker, Stanford B. (Editor); Firestone, Elaine R. (Editor); Doyle, John P.; Zibordi, Giuseppe; vanderLinde, Dirk

2003-01-01

Large offshore structures used for the deployment of optical instruments can significantly perturb the intensity of the light field surrounding the optical measurement point, where different portions of the visible spectrum are subject to different shadowing effects. These effects degrade the quality of the acquired optical data and can reduce the accuracy of several derived quantities, such as those obtained by applying bio-optical algorithms directly to the shadow-perturbed data. As a result, optical remote sensing calibration and validation studies can be impaired if shadowing artifacts are not fully accounted for. In this work, the general in-water shadowing problem is examined for a particular case study. Backward Monte Carlo (MC) radiative transfer computations- performed in a vertically stratified, horizontally inhomogeneous, and realistic ocean-atmosphere system are shown to accurately simulate the shadow-induced relative percent errors affecting the radiance and irradiance data profiles acquired close to an oceanographic tower. Multiparameter optical data processing has provided adequate representation of experimental uncertainties allowing consistent comparison with simulations. The more detailed simulations at the subsurface depth appear to be essentially equivalent to those obtained assuming a simplified ocean-atmosphere system, except in highly stratified waters. MC computations performed in the simplified system can be assumed, therefore, to accurately simulate the optical measurements conducted under more complex sampling conditions (i.e., within waters presenting moderate stratification at most). A previously reported correction scheme, based on the simplified MC simulations, and developed for subsurface shadow-removal processing of in-water optical data taken close to the investigated oceanographic tower, is then validated adequately under most experimental conditions. It appears feasible to generalize the present tower-specific approach to solve other optical sensor shadowing problems pertaining to differently shaped deployment platforms, and also including surrounding structures and instrument casings.

Uncertainty-based simulation-optimization using Gaussian process emulation: Application to coastal groundwater management

NASA Astrophysics Data System (ADS)

Rajabi, Mohammad Mahdi; Ketabchi, Hamed

2017-12-01

Combined simulation-optimization (S/O) schemes have long been recognized as a valuable tool in coastal groundwater management (CGM). However, previous applications have mostly relied on deterministic seawater intrusion (SWI) simulations. This is a questionable simplification, knowing that SWI models are inevitably prone to epistemic and aleatory uncertainty, and hence a management strategy obtained through S/O without consideration of uncertainty may result in significantly different real-world outcomes than expected. However, two key issues have hindered the use of uncertainty-based S/O schemes in CGM, which are addressed in this paper. The first issue is how to solve the computational challenges resulting from the need to perform massive numbers of simulations. The second issue is how the management problem is formulated in presence of uncertainty. We propose the use of Gaussian process (GP) emulation as a valuable tool in solving the computational challenges of uncertainty-based S/O in CGM. We apply GP emulation to the case study of Kish Island (located in the Persian Gulf) using an uncertainty-based S/O algorithm which relies on continuous ant colony optimization and Monte Carlo simulation. In doing so, we show that GP emulation can provide an acceptable level of accuracy, with no bias and low statistical dispersion, while tremendously reducing the computational time. Moreover, five new formulations for uncertainty-based S/O are presented based on concepts such as energy distances, prediction intervals and probabilities of SWI occurrence. We analyze the proposed formulations with respect to their resulting optimized solutions, the sensitivity of the solutions to the intended reliability levels, and the variations resulting from repeated optimization runs.

Multivariate stochastic simulation with subjective multivariate normal distributions

Treesearch

P. J. Ince; J. Buongiorno

1991-01-01

In many applications of Monte Carlo simulation in forestry or forest products, it may be known that some variables are correlated. However, for simplicity, in most simulations it has been assumed that random variables are independently distributed. This report describes an alternative Monte Carlo simulation technique for subjectively assesed multivariate normal...

SU-C-BRC-06: OpenCL-Based Cross-Platform Monte Carlo Simulation Package for Carbon Ion Therapy

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

Qin, N; Tian, Z; Pompos, A

2016-06-15

Purpose: Monte Carlo (MC) simulation is considered to be the most accurate method for calculation of absorbed dose and fundamental physical quantities related to biological effects in carbon ion therapy. Its long computation time impedes clinical and research applications. We have developed an MC package, goCMC, on parallel processing platforms, aiming at achieving accurate and efficient simulations for carbon therapy. Methods: goCMC was developed under OpenCL framework. It supported transport simulation in voxelized geometry with kinetic energy up to 450 MeV/u. Class II condensed history algorithm was employed for charged particle transport with stopping power computed via Bethe-Bloch equation. Secondarymore » electrons were not transported with their energy locally deposited. Energy straggling and multiple scattering were modeled. Production of secondary charged particles from nuclear interactions was implemented based on cross section and yield data from Geant4. They were transported via the condensed history scheme. goCMC supported scoring various quantities of interest e.g. physical dose, particle fluence, spectrum, linear energy transfer, and positron emitting nuclei. Results: goCMC has been benchmarked against Geant4 with different phantoms and beam energies. For 100 MeV/u, 250 MeV/u and 400 MeV/u beams impinging to a water phantom, range difference was 0.03 mm, 0.20 mm and 0.53 mm, and mean dose difference was 0.47%, 0.72% and 0.79%, respectively. goCMC can run on various computing devices. Depending on the beam energy and voxel size, it took 20∼100 seconds to simulate 10{sup 7} carbons on an AMD Radeon GPU card. The corresponding CPU time for Geant4 with the same setup was 60∼100 hours. Conclusion: We have developed an OpenCL-based cross-platform carbon MC simulation package, goCMC. Its accuracy, efficiency and portability make goCMC attractive for research and clinical applications in carbon therapy.« less

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

NASA Astrophysics Data System (ADS)

Chen, Jundong

2018-03-01

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

Gray: a ray tracing-based Monte Carlo simulator for PET

NASA Astrophysics Data System (ADS)

Freese, David L.; Olcott, Peter D.; Buss, Samuel R.; Levin, Craig S.

2018-05-01

Monte Carlo simulation software plays a critical role in PET system design. Performing complex, repeated Monte Carlo simulations can be computationally prohibitive, as even a single simulation can require a large amount of time and a computing cluster to complete. Here we introduce Gray, a Monte Carlo simulation software for PET systems. Gray exploits ray tracing methods used in the computer graphics community to greatly accelerate simulations of PET systems with complex geometries. We demonstrate the implementation of models for positron range, annihilation acolinearity, photoelectric absorption, Compton scatter, and Rayleigh scatter. For validation, we simulate the GATE PET benchmark, and compare energy, distribution of hits, coincidences, and run time. We show a speedup using Gray, compared to GATE for the same simulation, while demonstrating nearly identical results. We additionally simulate the Siemens Biograph mCT system with both the NEMA NU-2 scatter phantom and sensitivity phantom. We estimate the total sensitivity within % when accounting for differences in peak NECR. We also estimate the peak NECR to be kcps, or within % of published experimental data. The activity concentration of the peak is also estimated within 1.3%.

Enhanced configurational sampling with hybrid non-equilibrium molecular dynamics-Monte Carlo propagator

NASA Astrophysics Data System (ADS)

Suh, Donghyuk; Radak, Brian K.; Chipot, Christophe; Roux, Benoît

2018-01-01

Molecular dynamics (MD) trajectories based on classical equations of motion can be used to sample the configurational space of complex molecular systems. However, brute-force MD often converges slowly due to the ruggedness of the underlying potential energy surface. Several schemes have been proposed to address this problem by effectively smoothing the potential energy surface. However, in order to recover the proper Boltzmann equilibrium probability distribution, these approaches must then rely on statistical reweighting techniques or generate the simulations within a Hamiltonian tempering replica-exchange scheme. The present work puts forth a novel hybrid sampling propagator combining Metropolis-Hastings Monte Carlo (MC) with proposed moves generated by non-equilibrium MD (neMD). This hybrid neMD-MC propagator comprises three elementary elements: (i) an atomic system is dynamically propagated for some period of time using standard equilibrium MD on the correct potential energy surface; (ii) the system is then propagated for a brief period of time during what is referred to as a "boosting phase," via a time-dependent Hamiltonian that is evolved toward the perturbed potential energy surface and then back to the correct potential energy surface; (iii) the resulting configuration at the end of the neMD trajectory is then accepted or rejected according to a Metropolis criterion before returning to step 1. A symmetric two-end momentum reversal prescription is used at the end of the neMD trajectories to guarantee that the hybrid neMD-MC sampling propagator obeys microscopic detailed balance and rigorously yields the equilibrium Boltzmann distribution. The hybrid neMD-MC sampling propagator is designed and implemented to enhance the sampling by relying on the accelerated MD and solute tempering schemes. It is also combined with the adaptive biased force sampling algorithm to examine. Illustrative tests with specific biomolecular systems indicate that the method can yield a significant speedup.

Enhanced configurational sampling with hybrid non-equilibrium molecular dynamics-Monte Carlo propagator.

PubMed

Suh, Donghyuk; Radak, Brian K; Chipot, Christophe; Roux, Benoît

2018-01-07

Molecular dynamics (MD) trajectories based on classical equations of motion can be used to sample the configurational space of complex molecular systems. However, brute-force MD often converges slowly due to the ruggedness of the underlying potential energy surface. Several schemes have been proposed to address this problem by effectively smoothing the potential energy surface. However, in order to recover the proper Boltzmann equilibrium probability distribution, these approaches must then rely on statistical reweighting techniques or generate the simulations within a Hamiltonian tempering replica-exchange scheme. The present work puts forth a novel hybrid sampling propagator combining Metropolis-Hastings Monte Carlo (MC) with proposed moves generated by non-equilibrium MD (neMD). This hybrid neMD-MC propagator comprises three elementary elements: (i) an atomic system is dynamically propagated for some period of time using standard equilibrium MD on the correct potential energy surface; (ii) the system is then propagated for a brief period of time during what is referred to as a "boosting phase," via a time-dependent Hamiltonian that is evolved toward the perturbed potential energy surface and then back to the correct potential energy surface; (iii) the resulting configuration at the end of the neMD trajectory is then accepted or rejected according to a Metropolis criterion before returning to step 1. A symmetric two-end momentum reversal prescription is used at the end of the neMD trajectories to guarantee that the hybrid neMD-MC sampling propagator obeys microscopic detailed balance and rigorously yields the equilibrium Boltzmann distribution. The hybrid neMD-MC sampling propagator is designed and implemented to enhance the sampling by relying on the accelerated MD and solute tempering schemes. It is also combined with the adaptive biased force sampling algorithm to examine. Illustrative tests with specific biomolecular systems indicate that the method can yield a significant speedup.

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.

The use of Monte Carlo simulations for accurate dose determination with thermoluminescence dosemeters in radiation therapy beams.

PubMed

Mobit, P

2002-01-01

The energy responses of LiF-TLDs irradiated in megavoltage electron and photon beams have been determined experimentally by many investigators over the past 35 years but the results vary considerably. General cavity theory has been used to model some of the experimental findings but the predictions of these cavity theories differ from each other and from measurements by more than 13%. Recently, two groups or investigators using Monte Carlo simulations and careful experimental techniques showed that the energy response of 1 mm or 2 mm thick LiF-TLD irradiated by megavoltage photon and electron beams is not more than 5% less than unity for low-Z phantom materials like water or Perspex. However, when the depth of irradiation is significantly different from dmax and the TLD size is more than 5 mm, then the energy response is up to 12% less than unity for incident electron beams. Monte Carlo simulations of some of the experiments reported in the literature showed that some of the contradictory experimental results are reproducible with Monte Carlo simulations. Monte Carlo simulations show that the energy response of LiF-TLDs depends on the size of detector used in electron beams, the depth of irradiation and the incident electron energy. Other differences can be attributed to absolute dose determination and precision of the TL technique. Monte Carlo simulations have also been used to evaluate some of the published general cavity theories. The results show that some of the parameters used to evaluate Burlin's general cavity theory are wrong by factor of 3. Despite this, the estimation of the energy response for most clinical situations using Burlin's cavity equation agrees with Monte Carlo simulations within 1%.

Three-dimensional analysis of tokamaks and stellarators

PubMed Central

Garabedian, Paul R.

2008-01-01

The NSTAB equilibrium and stability code and the TRAN Monte Carlo transport code furnish a simple but effective numerical simulation of essential features of present tokamak and stellarator experiments. When the mesh size is comparable to the island width, an accurate radial difference scheme in conservation form captures magnetic islands successfully despite a nested surface hypothesis imposed by the mathematics. Three-dimensional asymmetries in bifurcated numerical solutions of the axially symmetric tokamak problem are relevant to the observation of unstable neoclassical tearing modes and edge localized modes in experiments. Islands in compact stellarators with quasiaxial symmetry are easier to control, so these configurations will become good candidates for magnetic fusion if difficulties with safety and stability are encountered in the International Thermonuclear Experimental Reactor (ITER) project. PMID:18768807

Optimal boarding method for airline passengers

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

Steffen, Jason H.; /Fermilab

2008-02-01

Using a Markov Chain Monte Carlo optimization algorithm and a computer simulation, I find the passenger ordering which minimizes the time required to board the passengers onto an airplane. The model that I employ assumes that the time that a passenger requires to load his or her luggage is the dominant contribution to the time needed to completely fill the aircraft. The optimal boarding strategy may reduce the time required to board and airplane by over a factor of four and possibly more depending upon the dimensions of the aircraft. I explore some features of the optimal boarding method andmore » discuss practical modifications to the optimal. Finally, I mention some of the benefits that could come from implementing an improved passenger boarding scheme.« less

Edgeworth expansions of stochastic trading time

NASA Astrophysics Data System (ADS)

Decamps, Marc; De Schepper, Ann

2010-08-01

Under most local and stochastic volatility models the underlying forward is assumed to be a positive function of a time-changed Brownian motion. It relates nicely the implied volatility smile to the so-called activity rate in the market. Following Young and DeWitt-Morette (1986) [8], we propose to apply the Duru-Kleinert process-cum-time transformation in path integral to formulate the transition density of the forward. The method leads to asymptotic expansions of the transition density around a Gaussian kernel corresponding to the average activity in the market conditional on the forward value. The approximation is numerically illustrated for pricing vanilla options under the CEV model and the popular normal SABR model. The asymptotics can also be used for Monte Carlo simulations or backward integration schemes.

Monte Carlo simulation of aorta autofluorescence

NASA Astrophysics Data System (ADS)

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

2016-08-01

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

Fluctuations, noise, and numerical methods in gyrokinetic particle-in-cell simulations

NASA Astrophysics Data System (ADS)

Jenkins, Thomas Grant

In this thesis, the role of the "marker weight" (or "particle weight") used in gyrokinetic particle-in-cell (PIC) simulations is explored. Following a review of the foundations and major developments of gyrokinetic theory, key concepts of the Monte Carlo methods which form the basis for PIC simulations are set forth. Consistent with these methods, a Klimontovich representation for the set of simulation markers is developed in the extended phase space {R, v||, v ⊥, W, P} (with the additional coordinates representing weight fields); clear distinctions are consequently established between the marker distribution function and various physical distribution functions (arising from diverse moments of the marker distribution). Equations describing transport in the simulation are shown to be easily derivable using the formalism. The necessity of a two-weight model for nonequilibrium simulations is demonstrated, and a simple method for calculating the second (background-related) weight is presented. Procedures for arbitrary marker loading schemes in gyrokinetic PIC simulations are outlined; various initialization methods for simulations are compared. Possible effects of inadequate velocity-space resolution in gyrokinetic continuum simulations are explored. The "partial-f" simulation method is developed and its limitations indicated. A quasilinear treatment of electrostatic drift waves is shown to correctly predict nonlinear saturation amplitudes, and the relevance of the gyrokinetic fluctuation-dissipation theorem in assessing the effects of discrete-marker-induced statistical noise on the resulting marginally stable states is demonstrated.

Physical Principle for Generation of Randomness

NASA Technical Reports Server (NTRS)

Zak, Michail

2009-01-01

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

Structural Reliability and Monte Carlo Simulation.

ERIC Educational Resources Information Center

Laumakis, P. J.; Harlow, G.

2002-01-01

Analyzes a simple boom structure and assesses its reliability using elementary engineering mechanics. Demonstrates the power and utility of Monte-Carlo simulation by showing that such a simulation can be implemented more readily with results that compare favorably to the theoretical calculations. (Author/MM)

The Monte Carlo Method. Popular Lectures in Mathematics.

ERIC Educational Resources Information Center

Sobol', I. M.

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

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.

Fixed forced detection for fast SPECT Monte-Carlo simulation

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Fixed forced detection for fast SPECT Monte-Carlo simulation.

PubMed

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

2018-03-02

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

Monte Carlo simulation: Its status and future

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

Murtha, J.A.

1997-04-01

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

Direct Simulation Monte Carlo Calculations in Support of the Columbia Shuttle Orbiter Accident Investigation

NASA Technical Reports Server (NTRS)

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

2003-01-01

The Direct Simulation Monte Carlo method was used to provide 3-D simulations of the early entry phase of the Shuttle Orbiter. Undamaged and damaged scenarios were modeled to provide calibration points for engineering "bridging function" type of analysis. Currently the simulation technology (software and hardware) are mature enough to allow realistic simulations of three dimensional vehicles.

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.

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

NASA Astrophysics Data System (ADS)

Yasuda, Shugo

2017-02-01

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

Electrostatic correlations in inhomogeneous charged fluids beyond loop expansion

NASA Astrophysics Data System (ADS)

Buyukdagli, Sahin; Achim, C. V.; Ala-Nissila, T.

2012-09-01

Electrostatic correlation effects in inhomogeneous symmetric electrolytes are investigated within a previously developed electrostatic self-consistent theory [R. R. Netz and H. Orland, Eur. Phys. J. E 11, 301 (2003)], 10.1140/epje/i2002-10159-0. To this aim, we introduce two computational approaches that allow to solve the self-consistent equations beyond the loop expansion. The first method is based on a perturbative Green's function technique, and the second one is an extension of a previously introduced semiclassical approximation for single dielectric interfaces to the case of slit nanopores. Both approaches can handle the case of dielectrically discontinuous boundaries where the one-loop theory is known to fail. By comparing the theoretical results obtained from these schemes with the results of the Monte Carlo simulations that we ran for ions at neutral single dielectric interfaces, we first show that the weak coupling Debye-Huckel theory remains quantitatively accurate up to the bulk ion density ρb ≃ 0.01 M, whereas the self-consistent theory exhibits a good quantitative accuracy up to ρb ≃ 0.2 M, thus improving the accuracy of the Debye-Huckel theory by one order of magnitude in ionic strength. Furthermore, we compare the predictions of the self-consistent theory with previous Monte Carlo simulation data for charged dielectric interfaces and show that the proposed approaches can also accurately handle the correlation effects induced by the surface charge in a parameter regime where the mean-field result significantly deviates from the Monte Carlo data. Then, we derive from the perturbative self-consistent scheme the one-loop theory of asymmetrically partitioned salt systems around a dielectrically homogeneous charged surface. It is shown that correlation effects originate in these systems from a competition between the salt screening loss at the interface driving the ions to the bulk region, and the interfacial counterion screening excess attracting them towards the surface. This competition can be quantified in terms of the characteristic surface charge σ _s^*=√{2ρ _b/(π ℓ _B)}, where ℓB = 7 Å is the Bjerrum length. In the case of weak surface charges σ _s≪ σ _s^* where counterions form a diffuse layer, the interfacial salt screening loss is the dominant effect. As a result, correlation effects decrease the mean-field density of both coions and counterions. With an increase of the surface charge towards σ _s^*, the surface-attractive counterion screening excess starts to dominate, and correlation effects amplify in this regime the mean-field density of both type of ions. However, in the regime σ _s>σ _s^*, the same counterion screening excess also results in a significant decrease of the electrostatic mean-field potential. This reduces in turn the mean-field counterion density far from the charged surface. We also show that for σ _s≫ σ _s^*, electrostatic correlations result in a charge inversion effect. However, the electrostatic coupling regime where this phenomenon takes place should be verified with Monte Carlo simulations since this parameter regime is located beyond the validity range of the one-loop theory.

Electrostatic correlations in inhomogeneous charged fluids beyond loop expansion.

PubMed

Buyukdagli, Sahin; Achim, C V; Ala-Nissila, T

2012-09-14

Electrostatic correlation effects in inhomogeneous symmetric electrolytes are investigated within a previously developed electrostatic self-consistent theory [R. R. Netz and H. Orland, Eur. Phys. J. E 11, 301 (2003)]. To this aim, we introduce two computational approaches that allow to solve the self-consistent equations beyond the loop expansion. The first method is based on a perturbative Green's function technique, and the second one is an extension of a previously introduced semiclassical approximation for single dielectric interfaces to the case of slit nanopores. Both approaches can handle the case of dielectrically discontinuous boundaries where the one-loop theory is known to fail. By comparing the theoretical results obtained from these schemes with the results of the Monte Carlo simulations that we ran for ions at neutral single dielectric interfaces, we first show that the weak coupling Debye-Huckel theory remains quantitatively accurate up to the bulk ion density ρ(b) ≃ 0.01 M, whereas the self-consistent theory exhibits a good quantitative accuracy up to ρ(b) ≃ 0.2 M, thus improving the accuracy of the Debye-Huckel theory by one order of magnitude in ionic strength. Furthermore, we compare the predictions of the self-consistent theory with previous Monte Carlo simulation data for charged dielectric interfaces and show that the proposed approaches can also accurately handle the correlation effects induced by the surface charge in a parameter regime where the mean-field result significantly deviates from the Monte Carlo data. Then, we derive from the perturbative self-consistent scheme the one-loop theory of asymmetrically partitioned salt systems around a dielectrically homogeneous charged surface. It is shown that correlation effects originate in these systems from a competition between the salt screening loss at the interface driving the ions to the bulk region, and the interfacial counterion screening excess attracting them towards the surface. This competition can be quantified in terms of the characteristic surface charge σ(s)*=√(2ρ(b)/(πl(B)), where l(B) = 7 Å is the Bjerrum length. In the case of weak surface charges σ(s)≪σ(s)* where counterions form a diffuse layer, the interfacial salt screening loss is the dominant effect. As a result, correlation effects decrease the mean-field density of both coions and counterions. With an increase of the surface charge towards σ(s)*, the surface-attractive counterion screening excess starts to dominate, and correlation effects amplify in this regime the mean-field density of both type of ions. However, in the regime σ(s)>σ(s)*, the same counterion screening excess also results in a significant decrease of the electrostatic mean-field potential. This reduces in turn the mean-field counterion density far from the charged surface. We also show that for σ(s)≫σ(s)*, electrostatic correlations result in a charge inversion effect. However, the electrostatic coupling regime where this phenomenon takes place should be verified with Monte Carlo simulations since this parameter regime is located beyond the validity range of the one-loop theory.

Probability density function approach for compressible turbulent reacting flows

NASA Technical Reports Server (NTRS)

Hsu, A. T.; Tsai, Y.-L. P.; Raju, M. S.

1994-01-01

The objective of the present work is to extend the probability density function (PDF) tubulence model to compressible reacting flows. The proability density function of the species mass fractions and enthalpy are obtained by solving a PDF evolution equation using a Monte Carlo scheme. The PDF solution procedure is coupled with a compression finite-volume flow solver which provides the velocity and pressure fields. A modeled PDF equation for compressible flows, capable of treating flows with shock waves and suitable to the present coupling scheme, is proposed and tested. Convergence of the combined finite-volume Monte Carlo solution procedure is discussed. Two super sonic diffusion flames are studied using the proposed PDF model and the results are compared with experimental data; marked improvements over solutions without PDF are observed.

Evaluation of a two-dimensional numerical model for air quality simulation in a street canyon

NASA Astrophysics Data System (ADS)

Okamoto, Shin `Ichi; Lin, Fu Chi; Yamada, Hiroaki; Shiozawa, Kiyoshige

For many urban areas, the most severe air pollution caused by automobile emissions appears along a road surrounded by tall buildings: the so=called street canyon. A practical two-dimensional numerical model has been developed to be applied to this kind of road structure. This model contains two submodels: a wind-field model and a diffusion model based on a Monte Carlo particle scheme. In order to evaluate the predictive performance of this model, an air quality simulation was carried out at three trunk roads in the Tokyo metropolitan area: Nishi-Shimbashi, Aoyama and Kanda-Nishikicho (using SF 6 as a tracer and NO x measurement). Since this model has two-dimensional properties and cannot be used for the parallel wind condition, the perpendicular wind condition was selected for the simulation. The correlation coefficients for the SF 6 and NO x data in Aoyama were 0.67 and 0.62, respectively. When predictive performance of this model is compared with other models, this model is comparable to the SRI model, and superior to the APPS three-dimensional numerical model.

Population annealing simulations of a binary hard-sphere mixture

NASA Astrophysics Data System (ADS)

Callaham, Jared; Machta, Jonathan

2017-06-01

Population annealing is a sequential Monte Carlo scheme well suited to simulating equilibrium states of systems with rough free energy landscapes. Here we use population annealing to study a binary mixture of hard spheres. Population annealing is a parallel version of simulated annealing with an extra resampling step that ensures that a population of replicas of the system represents the equilibrium ensemble at every packing fraction in an annealing schedule. The algorithm and its equilibration properties are described, and results are presented for a glass-forming fluid composed of a 50/50 mixture of hard spheres with diameter ratio of 1.4:1. For this system, we obtain precise results for the equation of state in the glassy regime up to packing fractions φ ≈0.60 and study deviations from the Boublik-Mansoori-Carnahan-Starling-Leland equation of state. For higher packing fractions, the algorithm falls out of equilibrium and a free volume fit predicts jamming at packing fraction φ ≈0.667 . We conclude that population annealing is an effective tool for studying equilibrium glassy fluids and the jamming transition.

Evaluation of three inverse problem models to quantify skin microcirculation using diffusion-weighted MRI

NASA Astrophysics Data System (ADS)

Cordier, G.; Choi, J.; Raguin, L. G.

2008-11-01

Skin microcirculation plays an important role in diseases such as chronic venous insufficiency and diabetes. Magnetic resonance imaging (MRI) can provide quantitative information with a better penetration depth than other noninvasive methods, such as laser Doppler flowmetry or optical coherence tomography. Moreover, successful MRI skin studies have recently been reported. In this article, we investigate three potential inverse models to quantify skin microcirculation using diffusion-weighted MRI (DWI), also known as q-space MRI. The model parameters are estimated based on nonlinear least-squares (NLS). For each of the three models, an optimal DWI sampling scheme is proposed based on D-optimality in order to minimize the size of the confidence region of the NLS estimates and thus the effect of the experimental noise inherent to DWI. The resulting covariance matrices of the NLS estimates are predicted by asymptotic normality and compared to the ones computed by Monte-Carlo simulations. Our numerical results demonstrate the effectiveness of the proposed models and corresponding DWI sampling schemes as compared to conventional approaches.

Combined Molecular Algorithms for the Generation, Equilibration and Topological Analysis of Entangled Polymers: Methodology and Performance

PubMed Central

Karayiannis, Nikos Ch.; Kröger, Martin

2009-01-01

We review the methodology, algorithmic implementation and performance characteristics of a hierarchical modeling scheme for the generation, equilibration and topological analysis of polymer systems at various levels of molecular description: from atomistic polyethylene samples to random packings of freely-jointed chains of tangent hard spheres of uniform size. Our analysis focuses on hitherto less discussed algorithmic details of the implementation of both, the Monte Carlo (MC) procedure for the system generation and equilibration, and a postprocessing step, where we identify the underlying topological structure of the simulated systems in the form of primitive paths. In order to demonstrate our arguments, we study how molecular length and packing density (volume fraction) affect the performance of the MC scheme built around chain-connectivity altering moves. In parallel, we quantify the effect of finite system size, of polydispersity, and of the definition of the number of entanglements (and related entanglement molecular weight) on the results about the primitive path network. Along these lines we approve main concepts which had been previously proposed in the literature. PMID:20087477

Risk measures for power failures in transmission systems

NASA Astrophysics Data System (ADS)

Cassidy, Alex; Feinstein, Zachary; Nehorai, Arye

2016-11-01

We present a novel framework for evaluating the risk of failures in power transmission systems. We use the concept of systemic risk measures from the financial mathematics literature with models of power system failures in order to quantify the risk of the entire power system for design and comparative purposes. The proposed risk measures provide the collection of capacity vectors for the components in the system that lead to acceptable outcomes. Keys to the formulation of our measures of risk are two elements: a model of system behavior that provides the (distribution of) outcomes based on component capacities and an acceptability criterion that determines whether a (random) outcome is acceptable from an aggregated point of view. We examine the effects of altering the line capacities on energy not served under a variety of networks, flow manipulation methods, load shedding schemes, and load profiles using Monte Carlo simulations. Our results provide a quantitative comparison of the performance of these schemes, measured by the required line capacity. These results provide more complete descriptions of the risks of power failures than the previous, one-dimensional metrics.

Continuous-feed optical sorting of aerosol particles

PubMed Central

Curry, J. J.; Levine, Zachary H.

2016-01-01

We consider the problem of sorting, by size, spherical particles of order 100 nm radius. The scheme we analyze consists of a heterogeneous stream of spherical particles flowing at an oblique angle across an optical Gaussian mode standing wave. Sorting is achieved by the combined spatial and size dependencies of the optical force. Particles of all sizes enter the flow at a point, but exit at different locations depending on size. Exiting particles may be detected optically or separated for further processing. The scheme has the advantages of accommodating a high throughput, producing a continuous stream of continuously dispersed particles, and exhibiting excellent size resolution. We performed detailed Monte Carlo simulations of particle trajectories through the optical field under the influence of convective air flow. We also developed a method for deriving effective velocities and diffusion constants from the Fokker-Planck equation that can generate equivalent results much more quickly. With an optical wavelength of 1064 nm, polystyrene particles with radii in the neighborhood of 275 nm, for which the optical force vanishes, may be sorted with a resolution below 1 nm. PMID:27410570

SU-E-T-481: Dosimetric Effects of Tissue Heterogeneity in Proton Therapy: Monte Carlo Simulation and Experimental Study Using Animal Tissue Phantoms.

PubMed

Liu, Y; Zheng, Y

2012-06-01

Accurate determination of proton dosimetric effect for tissue heterogeneity is critical in proton therapy. Proton beams have finite range and consequently tissue heterogeneity plays a more critical role in proton therapy. The purpose of this study is to investigate the tissue heterogeneity effect in proton dosimetry based on anatomical-based Monte Carlo simulation using animal tissues. Animal tissues including a pig head and beef bulk were used in this study. Both pig head and beef were scanned using a GE CT scanner with 1.25 mm slice thickness. A treatment plan was created, using the CMS XiO treatment planning system (TPS) with a single proton spread-out-Bragg-peak beam (SOBP). Radiochromic films were placed at the distal falloff region. Image guidance was used to align the phantom before proton beams were delivered according to the treatment plan. The same two CT sets were converted to Monte Carlo simulation model. The Monte Carlo simulated dose calculations with/without tissue omposition were compared to TPS calculations and measurements. Based on the preliminary comparison, at the center of SOBP plane, the Monte Carlo simulation dose without tissue composition agreed generally well with TPS calculation. In the distal falloff region, the dose difference was large, and about 2 mm isodose line shift was observed with the consideration of tissue composition. The detailed comparison of dose distributions between Monte Carlo simulation, TPS calculations and measurements is underway. Accurate proton dose calculations are challenging in proton treatment planning for heterogeneous tissues. Tissue heterogeneity and tissue composition may lead to isodose line shifts up to a few millimeters in the distal falloff region. By simulating detailed particle transport and energy deposition, Monte Carlo simulations provide a verification method in proton dose calculation where inhomogeneous tissues are present. © 2012 American Association of Physicists in Medicine.

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

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

PubMed

Patti, Alessandro; Cuetos, Alejandro

2012-07-01

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

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.

Monte Carlo Techniques for Nuclear Systems - Theory Lectures

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

Brown, Forrest B.

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

Monte Carlo Simulation of Microscopic Stock Market Models

NASA Astrophysics Data System (ADS)

Stauffer, Dietrich

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

Radiotherapy Monte Carlo simulation using cloud computing technology.

PubMed

Poole, C M; Cornelius, I; Trapp, J V; Langton, C M

2012-12-01

Cloud computing allows for vast computational resources to be leveraged quickly and easily in bursts as and when required. Here we describe a technique that allows for Monte Carlo radiotherapy dose calculations to be performed using GEANT4 and executed in the cloud, with relative simulation cost and completion time evaluated as a function of machine count. As expected, simulation completion time decreases as 1/n for n parallel machines, and relative simulation cost is found to be optimal where n is a factor of the total simulation time in hours. Using the technique, we demonstrate the potential usefulness of cloud computing as a solution for rapid Monte Carlo simulation for radiotherapy dose calculation without the need for dedicated local computer hardware as a proof of principal.

Gray: a ray tracing-based Monte Carlo simulator for PET.

PubMed

Freese, David L; Olcott, Peter D; Buss, Samuel R; Levin, Craig S

2018-05-21

Monte Carlo simulation software plays a critical role in PET system design. Performing complex, repeated Monte Carlo simulations can be computationally prohibitive, as even a single simulation can require a large amount of time and a computing cluster to complete. Here we introduce Gray, a Monte Carlo simulation software for PET systems. Gray exploits ray tracing methods used in the computer graphics community to greatly accelerate simulations of PET systems with complex geometries. We demonstrate the implementation of models for positron range, annihilation acolinearity, photoelectric absorption, Compton scatter, and Rayleigh scatter. For validation, we simulate the GATE PET benchmark, and compare energy, distribution of hits, coincidences, and run time. We show a [Formula: see text] speedup using Gray, compared to GATE for the same simulation, while demonstrating nearly identical results. We additionally simulate the Siemens Biograph mCT system with both the NEMA NU-2 scatter phantom and sensitivity phantom. We estimate the total sensitivity within [Formula: see text]% when accounting for differences in peak NECR. We also estimate the peak NECR to be [Formula: see text] kcps, or within [Formula: see text]% of published experimental data. The activity concentration of the peak is also estimated within 1.3%.

Analytical Applications of Monte Carlo Techniques.

ERIC Educational Resources Information Center

Guell, Oscar A.; Holcombe, James A.

1990-01-01

Described are analytical applications of the theory of random processes, in particular solutions obtained by using statistical procedures known as Monte Carlo techniques. Supercomputer simulations, sampling, integration, ensemble, annealing, and explicit simulation are discussed. (CW)

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.

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

PubMed

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

2016-04-01

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

Bayesian energy landscape tilting: towards concordant models of molecular ensembles.

PubMed

Beauchamp, Kyle A; Pande, Vijay S; Das, Rhiju

2014-03-18

Predicting biological structure has remained challenging for systems such as disordered proteins that take on myriad conformations. Hybrid simulation/experiment strategies have been undermined by difficulties in evaluating errors from computational model inaccuracies and data uncertainties. Building on recent proposals from maximum entropy theory and nonequilibrium thermodynamics, we address these issues through a Bayesian energy landscape tilting (BELT) scheme for computing Bayesian hyperensembles over conformational ensembles. BELT uses Markov chain Monte Carlo to directly sample maximum-entropy conformational ensembles consistent with a set of input experimental observables. To test this framework, we apply BELT to model trialanine, starting from disagreeing simulations with the force fields ff96, ff99, ff99sbnmr-ildn, CHARMM27, and OPLS-AA. BELT incorporation of limited chemical shift and (3)J measurements gives convergent values of the peptide's α, β, and PPII conformational populations in all cases. As a test of predictive power, all five BELT hyperensembles recover set-aside measurements not used in the fitting and report accurate errors, even when starting from highly inaccurate simulations. BELT's principled framework thus enables practical predictions for complex biomolecular systems from discordant simulations and sparse data. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Efficient hybrid non-equilibrium molecular dynamics--Monte Carlo simulations with symmetric momentum reversal.

PubMed

Chen, Yunjie; Roux, Benoît

2014-09-21

Hybrid schemes combining the strength of molecular dynamics (MD) and Metropolis Monte Carlo (MC) offer a promising avenue to improve the sampling efficiency of computer simulations of complex systems. A number of recently proposed hybrid methods consider new configurations generated by driving the system via a non-equilibrium MD (neMD) trajectory, which are subsequently treated as putative candidates for Metropolis MC acceptance or rejection. To obey microscopic detailed balance, it is necessary to alter the momentum of the system at the beginning and/or the end of the neMD trajectory. This strict rule then guarantees that the random walk in configurational space generated by such hybrid neMD-MC algorithm will yield the proper equilibrium Boltzmann distribution. While a number of different constructs are possible, the most commonly used prescription has been to simply reverse the momenta of all the particles at the end of the neMD trajectory ("one-end momentum reversal"). Surprisingly, it is shown here that the choice of momentum reversal prescription can have a considerable effect on the rate of convergence of the hybrid neMD-MC algorithm, with the simple one-end momentum reversal encountering particularly acute problems. In these neMD-MC simulations, different regions of configurational space end up being essentially isolated from one another due to a very small transition rate between regions. In the worst-case scenario, it is almost as if the configurational space does not constitute a single communicating class that can be sampled efficiently by the algorithm, and extremely long neMD-MC simulations are needed to obtain proper equilibrium probability distributions. To address this issue, a novel momentum reversal prescription, symmetrized with respect to both the beginning and the end of the neMD trajectory ("symmetric two-ends momentum reversal"), is introduced. Illustrative simulations demonstrate that the hybrid neMD-MC algorithm robustly yields a correct equilibrium probability distribution with this prescription.

Efficient hybrid non-equilibrium molecular dynamics - Monte Carlo simulations with symmetric momentum reversal

NASA Astrophysics Data System (ADS)

Chen, Yunjie; Roux, Benoît

2014-09-01

Hybrid schemes combining the strength of molecular dynamics (MD) and Metropolis Monte Carlo (MC) offer a promising avenue to improve the sampling efficiency of computer simulations of complex systems. A number of recently proposed hybrid methods consider new configurations generated by driving the system via a non-equilibrium MD (neMD) trajectory, which are subsequently treated as putative candidates for Metropolis MC acceptance or rejection. To obey microscopic detailed balance, it is necessary to alter the momentum of the system at the beginning and/or the end of the neMD trajectory. This strict rule then guarantees that the random walk in configurational space generated by such hybrid neMD-MC algorithm will yield the proper equilibrium Boltzmann distribution. While a number of different constructs are possible, the most commonly used prescription has been to simply reverse the momenta of all the particles at the end of the neMD trajectory ("one-end momentum reversal"). Surprisingly, it is shown here that the choice of momentum reversal prescription can have a considerable effect on the rate of convergence of the hybrid neMD-MC algorithm, with the simple one-end momentum reversal encountering particularly acute problems. In these neMD-MC simulations, different regions of configurational space end up being essentially isolated from one another due to a very small transition rate between regions. In the worst-case scenario, it is almost as if the configurational space does not constitute a single communicating class that can be sampled efficiently by the algorithm, and extremely long neMD-MC simulations are needed to obtain proper equilibrium probability distributions. To address this issue, a novel momentum reversal prescription, symmetrized with respect to both the beginning and the end of the neMD trajectory ("symmetric two-ends momentum reversal"), is introduced. Illustrative simulations demonstrate that the hybrid neMD-MC algorithm robustly yields a correct equilibrium probability distribution with this prescription.

Building Process Improvement Business Cases Using Bayesian Belief Networks and Monte Carlo Simulation

DTIC Science & Technology

2009-07-01

simulation. The pilot described in this paper used this two-step approach within a Define, Measure, Analyze, Improve, and Control ( DMAIC ) framework to...networks, BBN, Monte Carlo simulation, DMAIC , Six Sigma, business case 15. NUMBER OF PAGES 35 16. PRICE CODE 17. SECURITY CLASSIFICATION OF

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

PubMed Central

Pratx, Guillem; Xing, Lei

2011-01-01

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

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

PubMed Central

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

2011-01-01

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

Numerical analysis of electromagnetic cascades in emulsion chambers

NASA Technical Reports Server (NTRS)

Plyasheshnikov, A. V.; Vorobyev, K. V.

1985-01-01

A new calculational scheme of the Monte Carlo method assigned for the investigation of the development of high and extremely high energy electromagnetic cascades (EMC) in the matter was elaborated. The scheme was applied to the analysis of angular and radial distributions of EMC electrons in the atmosphere. By means of this scheme the EMC development in dense medium is investigated and some preliminary data are presented on the behavior of EMC in emulsion chambers. The results of more detailed theoretical analysis of the EMC development in emulsion chambers are discussed.

Importance biasing scheme implemented in the PRIZMA code

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

Kandiev, I.Z.; Malyshkin, G.N.

1997-12-31

PRIZMA code is intended for Monte Carlo calculations of linear radiation transport problems. The code has wide capabilities to describe geometry, sources, material composition, and to obtain parameters specified by user. There is a capability to calculate path of particle cascade (including neutrons, photons, electrons, positrons and heavy charged particles) taking into account possible transmutations. Importance biasing scheme was implemented to solve the problems which require calculation of functionals related to small probabilities (for example, problems of protection against radiation, problems of detection, etc.). The scheme enables to adapt trajectory building algorithm to problem peculiarities.

A dental public health approach based on computational mathematics: Monte Carlo simulation of childhood dental decay.

PubMed

Tennant, Marc; Kruger, Estie

2013-02-01

This study developed a Monte Carlo simulation approach to examining the prevalence and incidence of dental decay using Australian children as a test environment. Monte Carlo simulation has been used for a half a century in particle physics (and elsewhere); put simply, it is the probability for various population-level outcomes seeded randomly to drive the production of individual level data. A total of five runs of the simulation model for all 275,000 12-year-olds in Australia were completed based on 2005-2006 data. Measured on average decayed/missing/filled teeth (DMFT) and DMFT of highest 10% of sample (Sic10) the runs did not differ from each other by more than 2% and the outcome was within 5% of the reported sampled population data. The simulations rested on the population probabilities that are known to be strongly linked to dental decay, namely, socio-economic status and Indigenous heritage. Testing the simulated population found DMFT of all cases where DMFT<>0 was 2.3 (n = 128,609) and DMFT for Indigenous cases only was 1.9 (n = 13,749). In the simulation population the Sic25 was 3.3 (n = 68,750). Monte Carlo simulations were created in particle physics as a computational mathematical approach to unknown individual-level effects by resting a simulation on known population-level probabilities. In this study a Monte Carlo simulation approach to childhood dental decay was built, tested and validated. © 2013 FDI World Dental Federation.

CloudMC: a cloud computing application for Monte Carlo simulation.

PubMed

Miras, H; Jiménez, R; Miras, C; Gomà, C

2013-04-21

This work presents CloudMC, a cloud computing application-developed in Windows Azure®, the platform of the Microsoft® cloud-for the parallelization of Monte Carlo simulations in a dynamic virtual cluster. CloudMC is a web application designed to be independent of the Monte Carlo code in which the simulations are based-the simulations just need to be of the form: input files → executable → output files. To study the performance of CloudMC in Windows Azure®, Monte Carlo simulations with penelope were performed on different instance (virtual machine) sizes, and for different number of instances. The instance size was found to have no effect on the simulation runtime. It was also found that the decrease in time with the number of instances followed Amdahl's law, with a slight deviation due to the increase in the fraction of non-parallelizable time with increasing number of instances. A simulation that would have required 30 h of CPU on a single instance was completed in 48.6 min when executed on 64 instances in parallel (speedup of 37 ×). Furthermore, the use of cloud computing for parallel computing offers some advantages over conventional clusters: high accessibility, scalability and pay per usage. Therefore, it is strongly believed that cloud computing will play an important role in making Monte Carlo dose calculation a reality in future clinical practice.

Teaching Ionic Solvation Structure with a Monte Carlo Liquid Simulation Program

ERIC Educational Resources Information Center

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

2004-01-01

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

Non-hard sphere thermodynamic perturbation theory.

PubMed

Zhou, Shiqi

2011-08-21

A non-hard sphere (HS) perturbation scheme, recently advanced by the present author, is elaborated for several technical matters, which are key mathematical details for implementation of the non-HS perturbation scheme in a coupling parameter expansion (CPE) thermodynamic perturbation framework. NVT-Monte Carlo simulation is carried out for a generalized Lennard-Jones (LJ) 2n-n potential to obtain routine thermodynamic quantities such as excess internal energy, pressure, excess chemical potential, excess Helmholtz free energy, and excess constant volume heat capacity. Then, these new simulation data, and available simulation data in literatures about a hard core attractive Yukawa fluid and a Sutherland fluid, are used to test the non-HS CPE 3rd-order thermodynamic perturbation theory (TPT) and give a comparison between the non-HS CPE 3rd-order TPT and other theoretical approaches. It is indicated that the non-HS CPE 3rd-order TPT is superior to other traditional TPT such as van der Waals/HS (vdW/HS), perturbation theory 2 (PT2)/HS, and vdW/Yukawa (vdW/Y) theory or analytical equation of state such as mean spherical approximation (MSA)-equation of state and is at least comparable to several currently the most accurate Ornstein-Zernike integral equation theories. It is discovered that three technical issues, i.e., opening up new bridge function approximation for the reference potential, choosing proper reference potential, and/or using proper thermodynamic route for calculation of f(ex-ref), chiefly decide the quality of the non-HS CPE TPT. Considering that the non-HS perturbation scheme applies for a wide variety of model fluids, and its implementation in the CPE thermodynamic perturbation framework is amenable to high-order truncation, the non-HS CPE 3rd-order or higher order TPT will be more promising once the above-mentioned three technological advances are established. © 2011 American Institute of Physics

T-Opt: A 3D Monte Carlo simulation for light delivery design in photodynamic therapy (Conference Presentation)

NASA Astrophysics Data System (ADS)

Honda, Norihiro; Hazama, Hisanao; Awazu, Kunio

2017-02-01

The interstitial photodynamic therapy (iPDT) with 5-aminolevulinic acid (5-ALA) is a safe and feasible treatment modality of malignant glioblastoma. In order to cover the tumour volume, the exact position of the light diffusers within the lesion is needed to decide precisely. The aim of this study is the development of evaluation method of treatment volume with 3D Monte Carlo simulation for iPDT using 5-ALA. Monte Carlo simulations of fluence rate were performed using the optical properties of the brain tissue infiltrated by tumor cells and normal tissue. 3-D Monte Carlo simulation was used to calculate the position of the light diffusers within the lesion and light transport. The fluence rate near the diffuser was maximum and decreased exponentially with distance. The simulation can calculate the amount of singlet oxygen generated by PDT. In order to increase the accuracy of simulation results, the parameter for simulation includes the quantum yield of singlet oxygen generation, the accumulated concentration of photosensitizer within tissue, fluence rate, molar extinction coefficient at the wavelength of excitation light. The simulation is useful for evaluation of treatment region of iPDT with 5-ALA.

Collision partner selection schemes in DSMC: From micro/nano flows to hypersonic flows

NASA Astrophysics Data System (ADS)

Roohi, Ehsan; Stefanov, Stefan

2016-10-01

The motivation of this review paper is to present a detailed summary of different collision models developed in the framework of the direct simulation Monte Carlo (DSMC) method. The emphasis is put on a newly developed collision model, i.e., the Simplified Bernoulli trial (SBT), which permits efficient low-memory simulation of rarefied gas flows. The paper starts with a brief review of the governing equations of the rarefied gas dynamics including Boltzmann and Kac master equations and reiterates that the linear Kac equation reduces to a non-linear Boltzmann equation under the assumption of molecular chaos. An introduction to the DSMC method is provided, and principles of collision algorithms in the DSMC are discussed. A distinction is made between those collision models that are based on classical kinetic theory (time counter, no time counter (NTC), and nearest neighbor (NN)) and the other class that could be derived mathematically from the Kac master equation (pseudo-Poisson process, ballot box, majorant frequency, null collision, Bernoulli trials scheme and its variants). To provide a deeper insight, the derivation of both collision models, either from the principles of the kinetic theory or the Kac master equation, is provided with sufficient details. Some discussions on the importance of subcells in the DSMC collision procedure are also provided and different types of subcells are presented. The paper then focuses on the simplified version of the Bernoulli trials algorithm (SBT) and presents a detailed summary of validation of the SBT family collision schemes (SBT on transient adaptive subcells: SBT-TAS, and intelligent SBT: ISBT) in a broad spectrum of rarefied gas-flow test cases, ranging from low speed, internal micro and nano flows to external hypersonic flow, emphasizing first the accuracy of these new collision models and second, demonstrating that the SBT family scheme, if compared to other conventional and recent collision models, requires smaller number of particles per cell to obtain sufficiently accurate solutions.

Assessment of active methods for removal of LEO debris

NASA Astrophysics Data System (ADS)

Hakima, Houman; Emami, M. Reza

2018-03-01

This paper investigates the applicability of five active methods for removal of large low Earth orbit debris. The removal methods, namely net, laser, electrodynamic tether, ion beam shepherd, and robotic arm, are selected based on a set of high-level space mission constraints. Mission level criteria are then utilized to assess the performance of each redirection method in light of the results obtained from a Monte Carlo simulation. The simulation provides an insight into the removal time, performance robustness, and propellant mass criteria for the targeted debris range. The remaining attributes are quantified based on the models provided in the literature, which take into account several important parameters pertaining to each removal method. The means of assigning attributes to each assessment criterion is discussed in detail. A systematic comparison is performed using two different assessment schemes: Analytical Hierarchy Process and utility-based approach. A third assessment technique, namely the potential-loss analysis, is utilized to highlight the effect of risks in each removal methods.

Wealth distribution, Pareto law, and stretched exponential decay of money: Computer simulations analysis of agent-based models

NASA Astrophysics Data System (ADS)

Aydiner, Ekrem; Cherstvy, Andrey G.; Metzler, Ralf

2018-01-01

We study by Monte Carlo simulations a kinetic exchange trading model for both fixed and distributed saving propensities of the agents and rationalize the person and wealth distributions. We show that the newly introduced wealth distribution - that may be more amenable in certain situations - features a different power-law exponent, particularly for distributed saving propensities of the agents. For open agent-based systems, we analyze the person and wealth distributions and find that the presence of trap agents alters their amplitude, leaving however the scaling exponents nearly unaffected. For an open system, we show that the total wealth - for different trap agent densities and saving propensities of the agents - decreases in time according to the classical Kohlrausch-Williams-Watts stretched exponential law. Interestingly, this decay does not depend on the trap agent density, but rather on saving propensities. The system relaxation for fixed and distributed saving schemes are found to be different.

Physical layer simulation study for the coexistence of WLAN standards

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

Howlader, M. K.; Keiger, C.; Ewing, P. D.

This paper presents the results of a study on the performance of wireless local area network (WLAN) devices in the presence of interference from other wireless devices. To understand the coexistence of these wireless protocols, simplified physical-layer-system models were developed for the Bluetooth, Wireless Fidelity (WiFi), and Zigbee devices, all of which operate within the 2.4-GHz frequency band. The performances of these protocols were evaluated using Monte-Carlo simulations under various interference and channel conditions. The channel models considered were basic additive white Gaussian noise (AWGN), Rayleigh fading, and site-specific fading. The study also incorporated the basic modulation schemes, multiple accessmore » techniques, and channel allocations of the three protocols. This research is helping the U.S. Nuclear Regulatory Commission (NRC) understand the coexistence issues associated with deploying wireless devices and could prove useful in the development of a technical basis for guidance to address safety-related issues with the implementation of wireless systems in nuclear facilities. (authors)« less

Conformational rigidity in a lattice model of proteins.

PubMed

Collet, Olivier

2003-06-01

It is shown in this paper that some simulations of protein folding in lattice models, which use an incorrect implementation of the Monte Carlo algorithm, do not converge towards thermal equilibrium. I developed a rigorous treatment for protein folding simulation on a lattice model relying on the introduction of a parameter standing for the rigidity of the conformations. Its properties are discussed and its role during the folding process is elucidated. The calculation of thermal properties of small chains living on a two-dimensional lattice is performed and a Bortz-Kalos-Lebowitz scheme is implemented in the presented method in order to study kinetics of chains at very low temperature. The coefficients of the Arrhenius law obtained with this algorithm are found to be in excellent agreement with the value of the main potential barrier of the system. Finally, a scenario of the mechanisms, including the rigidity parameters, that guide a protein towards its native structure, at medium temperature, is given.

Gaussian process regression for sensor networks under localization uncertainty

USGS Publications Warehouse

Jadaliha, M.; Xu, Yunfei; Choi, Jongeun; Johnson, N.S.; Li, Weiming

2013-01-01

In this paper, we formulate Gaussian process regression with observations under the localization uncertainty due to the resource-constrained sensor networks. In our formulation, effects of observations, measurement noise, localization uncertainty, and prior distributions are all correctly incorporated in the posterior predictive statistics. The analytically intractable posterior predictive statistics are proposed to be approximated by two techniques, viz., Monte Carlo sampling and Laplace's method. Such approximation techniques have been carefully tailored to our problems and their approximation error and complexity are analyzed. Simulation study demonstrates that the proposed approaches perform much better than approaches without considering the localization uncertainty properly. Finally, we have applied the proposed approaches on the experimentally collected real data from a dye concentration field over a section of a river and a temperature field of an outdoor swimming pool to provide proof of concept tests and evaluate the proposed schemes in real situations. In both simulation and experimental results, the proposed methods outperform the quick-and-dirty solutions often used in practice.

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Proton Upset Monte Carlo Simulation

NASA Technical Reports Server (NTRS)

O'Neill, Patrick M.; Kouba, Coy K.; Foster, Charles C.

2009-01-01

The Proton Upset Monte Carlo Simulation (PROPSET) program calculates the frequency of on-orbit upsets in computer chips (for given orbits such as Low Earth Orbit, Lunar Orbit, and the like) from proton bombardment based on the results of heavy ion testing alone. The software simulates the bombardment of modern microelectronic components (computer chips) with high-energy (.200 MeV) protons. The nuclear interaction of the proton with the silicon of the chip is modeled and nuclear fragments from this interaction are tracked using Monte Carlo techniques to produce statistically accurate predictions.

A Dasymetric-Based Monte Carlo Simulation Approach to the Probabilistic Analysis of Spatial Variables

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

Morton, April M; Piburn, Jesse O; McManamay, Ryan A

2017-01-01

Monte Carlo simulation is a popular numerical experimentation technique used in a range of scientific fields to obtain the statistics of unknown random output variables. Despite its widespread applicability, it can be difficult to infer required input probability distributions when they are related to population counts unknown at desired spatial resolutions. To overcome this challenge, we propose a framework that uses a dasymetric model to infer the probability distributions needed for a specific class of Monte Carlo simulations which depend on population counts.

Obtaining identical results with double precision global accuracy on different numbers of processors in parallel particle Monte Carlo simulations

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

Cleveland, Mathew A., E-mail: cleveland7@llnl.gov; Brunner, Thomas A.; Gentile, Nicholas A.

2013-10-15

We describe and compare different approaches for achieving numerical reproducibility in photon Monte Carlo simulations. Reproducibility is desirable for code verification, testing, and debugging. Parallelism creates a unique problem for achieving reproducibility in Monte Carlo simulations because it changes the order in which values are summed. This is a numerical problem because double precision arithmetic is not associative. Parallel Monte Carlo, both domain replicated and decomposed simulations, will run their particles in a different order during different runs of the same simulation because the non-reproducibility of communication between processors. In addition, runs of the same simulation using different domain decompositionsmore » will also result in particles being simulated in a different order. In [1], a way of eliminating non-associative accumulations using integer tallies was described. This approach successfully achieves reproducibility at the cost of lost accuracy by rounding double precision numbers to fewer significant digits. This integer approach, and other extended and reduced precision reproducibility techniques, are described and compared in this work. Increased precision alone is not enough to ensure reproducibility of photon Monte Carlo simulations. Non-arbitrary precision approaches require a varying degree of rounding to achieve reproducibility. For the problems investigated in this work double precision global accuracy was achievable by using 100 bits of precision or greater on all unordered sums which where subsequently rounded to double precision at the end of every time-step.« less

Concepts and Plans towards fast large scale Monte Carlo production for the ATLAS Experiment

NASA Astrophysics Data System (ADS)

Ritsch, E.; Atlas Collaboration

2014-06-01

The huge success of the physics program of the ATLAS experiment at the Large Hadron Collider (LHC) during Run 1 relies upon a great number of simulated Monte Carlo events. This Monte Carlo production takes the biggest part of the computing resources being in use by ATLAS as of now. In this document we describe the plans to overcome the computing resource limitations for large scale Monte Carlo production in the ATLAS Experiment for Run 2, and beyond. A number of fast detector simulation, digitization and reconstruction techniques are being discussed, based upon a new flexible detector simulation framework. To optimally benefit from these developments, a redesigned ATLAS MC production chain is presented at the end of this document.

Application of Distribution Transformer Thermal Life Models to Electrified Vehicle Charging Loads Using Monte-Carlo Method: Preprint

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

Kuss, M.; Markel, T.; Kramer, W.

Concentrated purchasing patterns of plug-in vehicles may result in localized distribution transformer overload scenarios. Prolonged periods of transformer overloading causes service life decrements, and in worst-case scenarios, results in tripped thermal relays and residential service outages. This analysis will review distribution transformer load models developed in the IEC 60076 standard, and apply the model to a neighborhood with plug-in hybrids. Residential distribution transformers are sized such that night-time cooling provides thermal recovery from heavy load conditions during the daytime utility peak. It is expected that PHEVs will primarily be charged at night in a residential setting. If not managed properly,more » some distribution transformers could become overloaded, leading to a reduction in transformer life expectancy, thus increasing costs to utilities and consumers. A Monte-Carlo scheme simulated each day of the year, evaluating 100 load scenarios as it swept through the following variables: number of vehicle per transformer, transformer size, and charging rate. A general method for determining expected transformer aging rate will be developed, based on the energy needs of plug-in vehicles loading a residential transformer.« less

The development of GPU-based parallel PRNG for Monte Carlo applications in CUDA Fortran

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

Kargaran, Hamed, E-mail: h-kargaran@sbu.ac.ir; Minuchehr, Abdolhamid; Zolfaghari, Ahmad

The implementation of Monte Carlo simulation on the CUDA Fortran requires a fast random number generation with good statistical properties on GPU. In this study, a GPU-based parallel pseudo random number generator (GPPRNG) have been proposed to use in high performance computing systems. According to the type of GPU memory usage, GPU scheme is divided into two work modes including GLOBAL-MODE and SHARED-MODE. To generate parallel random numbers based on the independent sequence method, the combination of middle-square method and chaotic map along with the Xorshift PRNG have been employed. Implementation of our developed PPRNG on a single GPU showedmore » a speedup of 150x and 470x (with respect to the speed of PRNG on a single CPU core) for GLOBAL-MODE and SHARED-MODE, respectively. To evaluate the accuracy of our developed GPPRNG, its performance was compared to that of some other commercially available PPRNGs such as MATLAB, FORTRAN and Miller-Park algorithm through employing the specific standard tests. The results of this comparison showed that the developed GPPRNG in this study can be used as a fast and accurate tool for computational science applications.« less

Integrating interannual climate variability forecasts into weather-indexed crop insurance. The case of Malawi, Kenya and Tanzania

NASA Astrophysics Data System (ADS)

Vicarelli, M.; Giannini, A.; Osgood, D.

2009-12-01

In this study we explore the potential for re-insurance schemes built on regional climatic forecasts. We focus on micro-insurance contracts indexed on precipitation in 9 villages in Kenya, Tanzania (Eastern Africa) and Malawi (Southern Africa), and analyze the precipitation patterns and payouts resulting from El Niño Southern Oscillation (ENSO). The inability to manage future climate risk represents a “poverty trap” for several African regions. Weather shocks can potentially destabilize not only household, but also entire countries. Governments in drought-prone countries, donors and relief agencies are becoming aware of the importance to develop an ex-ante risk management framework for weather risk. Joint efforts to develop innovative mechanisms to spread and pool risk such as microinsurance and microcredit are currently being designed in several developing countries. While ENSO is an important component in modulating the rainfall regime in tropical Africa, the micro-insurance experiments currently under development to address drought risk among smallholder farmers in this region do not take into account ENSO monitoring or forecasting yet. ENSO forecasts could be integrated in the contracts and reinsurance schemes could be designed at the continental scale taking advantage of the different impact of ENSO on different regions. ENSO is associated to a bipolar precipitation pattern in Southern and Eastern Africa. La Niña years (i.e. Cold ENSO Episodes) are characterized by dry climate in Eastern Africa and wet climate in Southern Africa. During El Niño (or Warm Episode) the precipitation dipole is inverted, and Eastern Africa experiences increased probability for above normal rainfall (Halpert and Ropelewski, 1992, Journal of Climate). Our study represents the first exercise in trying to include ENSO forecasts in micro weather index insurance contract design. We analyzed the contracts payouts with respect to climate variability. In particular (i) we simulated possible payouts using historical precipitation data and analyzed the differences between years with different ENSO states from 1961 to 2005; (ii) we applied Monte Carlo methods to simulate precipitation distributions in each location and calculated the mean and variance of payouts associated to different ENSO states. The results obtained from historical precipitation data indicate that more abundant rainfall reduces payouts and the risk of loan default during La Niña in southern Kenya and Malawi, during El Niño in Tanzania. The results of the Monte Carlo simulations confirm our findings. Our results suggest that re-insurance schemes could be successfully designed to exploit the anti-correlation patterns related to interannual climate variability for different regions in Africa. Moreover, the exploratory framework presented can potentially be refined applied to other regions (e.g. Central and Latin America).

Environmental performance evaluation of large-scale municipal solid waste incinerators using data envelopment analysis

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

Chen, H.-W.; Chang, N.-B., E-mail: nchang@mail.ucf.ed; Chen, J.-C.

2010-07-15

Limited to insufficient land resources, incinerators are considered in many countries such as Japan and Germany as the major technology for a waste management scheme capable of dealing with the increasing demand for municipal and industrial solid waste treatment in urban regions. The evaluation of these municipal incinerators in terms of secondary pollution potential, cost-effectiveness, and operational efficiency has become a new focus in the highly interdisciplinary area of production economics, systems analysis, and waste management. This paper aims to demonstrate the application of data envelopment analysis (DEA) - a production economics tool - to evaluate performance-based efficiencies of 19more » large-scale municipal incinerators in Taiwan with different operational conditions. A 4-year operational data set from 2002 to 2005 was collected in support of DEA modeling using Monte Carlo simulation to outline the possibility distributions of operational efficiency of these incinerators. Uncertainty analysis using the Monte Carlo simulation provides a balance between simplifications of our analysis and the soundness of capturing the essential random features that complicate solid waste management systems. To cope with future challenges, efforts in the DEA modeling, systems analysis, and prediction of the performance of large-scale municipal solid waste incinerators under normal operation and special conditions were directed toward generating a compromised assessment procedure. Our research findings will eventually lead to the identification of the optimal management strategies for promoting the quality of solid waste incineration, not only in Taiwan, but also elsewhere in the world.« less

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.

Tool for Rapid Analysis of Monte Carlo Simulations

NASA Technical Reports Server (NTRS)

Restrepo, Carolina; McCall, Kurt E.; Hurtado, John E.

2011-01-01

Designing a spacecraft, or any other complex engineering system, requires extensive simulation and analysis work. Oftentimes, the large amounts of simulation data generated are very di cult and time consuming to analyze, with the added risk of overlooking potentially critical problems in the design. The authors have developed a generic data analysis tool that can quickly sort through large data sets and point an analyst to the areas in the data set that cause specific types of failures. The Tool for Rapid Analysis of Monte Carlo simulations (TRAM) has been used in recent design and analysis work for the Orion vehicle, greatly decreasing the time it takes to evaluate performance requirements. A previous version of this tool was developed to automatically identify driving design variables in Monte Carlo data sets. This paper describes a new, parallel version, of TRAM implemented on a graphical processing unit, and presents analysis results for NASA's Orion Monte Carlo data to demonstrate its capabilities.

An Overview of Importance Splitting for Rare Event Simulation

ERIC Educational Resources Information Center

Morio, Jerome; Pastel, Rudy; Le Gland, Francois

2010-01-01

Monte Carlo simulations are a classical tool to analyse physical systems. When unlikely events are to be simulated, the importance sampling technique is often used instead of Monte Carlo. Importance sampling has some drawbacks when the problem dimensionality is high or when the optimal importance sampling density is complex to obtain. In this…

Accelerating Monte Carlo simulations of photon transport in a voxelized geometry using a massively parallel graphics processing unit.

PubMed

Badal, Andreu; Badano, Aldo

2009-11-01

It is a known fact that Monte Carlo simulations of radiation transport are computationally intensive and may require long computing times. The authors introduce a new paradigm for the acceleration of Monte Carlo simulations: The use of a graphics processing unit (GPU) as the main computing device instead of a central processing unit (CPU). A GPU-based Monte Carlo code that simulates photon transport in a voxelized geometry with the accurate physics models from PENELOPE has been developed using the CUDATM programming model (NVIDIA Corporation, Santa Clara, CA). An outline of the new code and a sample x-ray imaging simulation with an anthropomorphic phantom are presented. A remarkable 27-fold speed up factor was obtained using a GPU compared to a single core CPU. The reported results show that GPUs are currently a good alternative to CPUs for the simulation of radiation transport. Since the performance of GPUs is currently increasing at a faster pace than that of CPUs, the advantages of GPU-based software are likely to be more pronounced in the future.

Data collection strategies for time-resolved X-ray free-electron laser diffraction, and 2-color methods

PubMed Central

Li, Chufeng; Schmidt, Kevin; Spence, John C.

2015-01-01

We compare three schemes for time-resolved X-ray diffraction from protein nanocrystals using an X-ray free-electron laser. We find expressions for the errors in structure factor measurement using the Monte Carlo pump-probe method of data analysis with a liquid jet, the fixed sample pump-probe (goniometer) method (both diffract-and-destroy, and below the safe damage dose), and a proposed two-color method. Here, an optical pump pulse arrives between X-ray pulses of slightly different energies which hit the same nanocrystal, using a weak first X-ray pulse which does not damage the sample. (Radiation damage is outrun in the other cases.) This two-color method, in which separated Bragg spots are impressed on the same detector readout, eliminates stochastic fluctuations in crystal size, shape, and orientation and is found to require two orders of magnitude fewer diffraction patterns than the currently used Monte Carlo liquid jet method, for 1% accuracy. Expressions are given for errors in structure factor measurement for the four approaches, and detailed simulations provided for cathepsin B and IC3 crystals. While the error is independent of the number of shots for the dose-limited goniometer method, it falls off inversely as the square root of the number of shots for the two-color and Monte Carlo methods, with a much smaller pre-factor for the two-color mode, when the first shot is below the damage threshold. PMID:26798813

Performance of ICTP's RegCM4 in Simulating the Rainfall Characteristics over the CORDEX-SEA Domain

NASA Astrophysics Data System (ADS)

Neng Liew, Ju; Tangang, Fredolin; Tieh Ngai, Sheau; Chung, Jing Xiang; Narisma, Gemma; Cruz, Faye Abigail; Phan Tan, Van; Thanh, Ngo-Duc; Santisirisomboon, Jerasron; Milindalekha, Jaruthat; Singhruck, Patama; Gunawan, Dodo; Satyaningsih, Ratna; Aldrian, Edvin

2015-04-01

The performance of the RegCM4 in simulating rainfall variations over the Southeast Asia regions was examined. Different combinations of six deep convective parameterization schemes, namely i) Grell scheme with Arakawa-Schubert closure assumption, ii) Grell scheme with Fritch-Chappel closure assumption, iii) Emanuel MIT scheme, iv) mixed scheme with Emanuel MIT scheme over the Ocean and the Grell scheme over the land, v) mixed scheme with Grell scheme over the land and Emanuel MIT scheme over the ocean and (vi) Kuo scheme, and three ocean flux treatments were tested. In order to account for uncertainties among the observation products, four different gridded rainfall products were used for comparison. The simulated climate is generally drier over the equatorial regions and slightly wetter over the mainland Indo-China compare to the observation. However, simulation with MIT cumulus scheme used over the land area consistently produces large amplitude of positive rainfall biases, although it simulates more realistic annual rainfall variations. The simulations are found less sensitive to treatment of ocean fluxes. Although the simulations produced the rainfall climatology well, all of them simulated much stronger interannual variability compare to that of the observed. Nevertheless, the time evolution of the inter-annual variations was well reproduced particularly over the eastern part of maritime continent. Over the mainland Southeast Asia (SEA), unrealistic rainfall anomalies processes were simulated. The lacking of summer season air-sea interaction results in strong oceanic forcings over the regions, leading to positive rainfall anomalies during years with warm ocean temperature anomalies. This incurs much stronger atmospheric forcings on the land surface processes compare to that of the observed. A score ranking system was designed to rank the simulations according to their performance in reproducing different aspects of rainfall characteristics. The result suggests that the simulation with Emanuel MIT convective scheme and BATs land surface scheme produces better collective performance compare to the rest of the simulations.

Event-shape-engineering study of charge separation in heavy-ion collisions

NASA Astrophysics Data System (ADS)

Wen, Fufang; Bryon, Jacob; Wen, Liwen; Wang, Gang

2018-01-01

Recent measurements of charge-dependent azimuthal correlations in high-energy heavy-ion collisions have indicated charge-separation signals perpendicular to the reaction plane, and have been related to the chiral magnetic effect (CME). However, the correlation signal is contaminated with the background caused by the collective motion (flow) of the collision system, and an effective approach is needed to remove the flow background from the correlation. We present a method study with simplified Monte Carlo simulations and a multi-phase transport model, and develop a scheme to reveal the true CME signal via event-shape engineering with the flow vector of the particles of interest. Supported by a grant (DE-FG02-88ER40424) from U.S. Department of Energy, Office of Nuclear Physics

Relative importance of multiple scattering by air molecules and aerosols in forming the atmospheric path radiance in the visible and near-infrared parts of the spectrum.

PubMed

Antoine, D; Morel, A

1998-04-20

Single and multiple scattering by molecules or by atmospheric aerosols only (homogeneous scattering), and heterogeneous scattering by aerosols and molecules, are recorded in Monte Carlo simulations. It is shown that heterogeneous scattering (1) always contributes significantly to the path reflectance (rho(path)), (2) is realized at the expense of homogeneous scattering, (3) decreases when aerosols are absorbing, and (4) introduces deviations in the spectral dependencies of reflectances compared with the Rayleigh exponent and the aerosol angstrom exponent. The ratio of rho(path) to the Rayleigh reflectance for an aerosol-free atmosphere is linearly related to the aerosol optical thickness. This result provides a basis for a new scheme for atmospheric correction of remotely sensed ocean color observations.

Free energy landscape from path-sampling: application to the structural transition in LJ38

NASA Astrophysics Data System (ADS)

Adjanor, G.; Athènes, M.; Calvo, F.

2006-09-01

We introduce a path-sampling scheme that allows equilibrium state-ensemble averages to be computed by means of a biased distribution of non-equilibrium paths. This non-equilibrium method is applied to the case of the 38-atom Lennard-Jones atomic cluster, which has a double-funnel energy landscape. We calculate the free energy profile along the Q4 bond orientational order parameter. At high or moderate temperature the results obtained using the non-equilibrium approach are consistent with those obtained using conventional equilibrium methods, including parallel tempering and Wang-Landau Monte Carlo simulations. At lower temperatures, the non-equilibrium approach becomes more efficient in exploring the relevant inherent structures. In particular, the free energy agrees with the predictions of the harmonic superposition approximation.

New estimation architecture for multisensor data fusion

NASA Astrophysics Data System (ADS)

Covino, Joseph M.; Griffiths, Barry E.

1991-07-01

This paper describes a novel method of hierarchical asynchronous distributed filtering called the Net Information Approach (NIA). The NIA is a Kalman-filter-based estimation scheme for spatially distributed sensors which must retain their local optimality yet require a nearly optimal global estimate. The key idea of the NIA is that each local sensor-dedicated filter tells the global filter 'what I've learned since the last local-to-global transmission,' whereas in other estimation architectures the local-to-global transmission consists of 'what I think now.' An algorithm based on this idea has been demonstrated on a small-scale target-tracking problem with many encouraging results. Feasibility of this approach was demonstrated by comparing NIA performance to an optimal centralized Kalman filter (lower bound) via Monte Carlo simulations.

Markov chain Monte Carlo estimation of quantum states

NASA Astrophysics Data System (ADS)

Diguglielmo, James; Messenger, Chris; Fiurášek, Jaromír; Hage, Boris; Samblowski, Aiko; Schmidt, Tabea; Schnabel, Roman

2009-03-01

We apply a Bayesian data analysis scheme known as the Markov chain Monte Carlo to the tomographic reconstruction of quantum states. This method yields a vector, known as the Markov chain, which contains the full statistical information concerning all reconstruction parameters including their statistical correlations with no a priori assumptions as to the form of the distribution from which it has been obtained. From this vector we can derive, e.g., the marginal distributions and uncertainties of all model parameters, and also of other quantities such as the purity of the reconstructed state. We demonstrate the utility of this scheme by reconstructing the Wigner function of phase-diffused squeezed states. These states possess non-Gaussian statistics and therefore represent a nontrivial case of tomographic reconstruction. We compare our results to those obtained through pure maximum-likelihood and Fisher information approaches.

Mixing Single Scattering Properties in Vector Radiative Transfer for Deterministic and Stochastic Solutions

NASA Astrophysics Data System (ADS)

Mukherjee, L.; Zhai, P.; Hu, Y.; Winker, D. M.

2016-12-01

Among the primary factors, which determine the polarized radiation, field of a turbid medium are the single scattering properties of the medium. When multiple types of scatterers are present, the single scattering properties of the scatterers need to be properly mixed in order to find the solutions to the vector radiative transfer theory (VRT). The VRT solvers can be divided into two types: deterministic and stochastic. The deterministic solver can only accept one set of single scattering property in its smallest discretized spatial volume. When the medium contains more than one kind of scatterer, their single scattering properties are averaged, and then used as input for the deterministic solver. The stochastic solver, can work with different kinds of scatterers explicitly. In this work, two different mixing schemes are studied using the Successive Order of Scattering (SOS) method and Monte Carlo (MC) methods. One scheme is used for deterministic and the other is used for the stochastic Monte Carlo method. It is found that the solutions from the two VRT solvers using two different mixing schemes agree with each other extremely well. This confirms the equivalence to the two mixing schemes and also provides a benchmark for the VRT solution for the medium studied.

Simultaneous 99mtc/111in spect reconstruction using accelerated convolution-based forced detection monte carlo

NASA Astrophysics Data System (ADS)

Karamat, Muhammad I.; Farncombe, Troy H.

2015-10-01

Simultaneous multi-isotope Single Photon Emission Computed Tomography (SPECT) imaging has a number of applications in cardiac, brain, and cancer imaging. The major concern however, is the significant crosstalk contamination due to photon scatter between the different isotopes. The current study focuses on a method of crosstalk compensation between two isotopes in simultaneous dual isotope SPECT acquisition applied to cancer imaging using 99mTc and 111In. We have developed an iterative image reconstruction technique that simulates the photon down-scatter from one isotope into the acquisition window of a second isotope. Our approach uses an accelerated Monte Carlo (MC) technique for the forward projection step in an iterative reconstruction algorithm. The MC estimated scatter contamination of a radionuclide contained in a given projection view is then used to compensate for the photon contamination in the acquisition window of other nuclide. We use a modified ordered subset-expectation maximization (OS-EM) algorithm named simultaneous ordered subset-expectation maximization (Sim-OSEM), to perform this step. We have undertaken a number of simulation tests and phantom studies to verify this approach. The proposed reconstruction technique was also evaluated by reconstruction of experimentally acquired phantom data. Reconstruction using Sim-OSEM showed very promising results in terms of contrast recovery and uniformity of object background compared to alternative reconstruction methods implementing alternative scatter correction schemes (i.e., triple energy window or separately acquired projection data). In this study the evaluation is based on the quality of reconstructed images and activity estimated using Sim-OSEM. In order to quantitate the possible improvement in spatial resolution and signal to noise ratio (SNR) observed in this study, further simulation and experimental studies are required.

TH-A-18C-04: Ultrafast Cone-Beam CT Scatter Correction with GPU-Based Monte Carlo Simulation

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

Xu, Y; Southern Medical University, Guangzhou; Bai, T

2014-06-15

Purpose: Scatter artifacts severely degrade image quality of cone-beam CT (CBCT). We present an ultrafast scatter correction framework by using GPU-based Monte Carlo (MC) simulation and prior patient CT image, aiming at automatically finish the whole process including both scatter correction and reconstructions within 30 seconds. Methods: The method consists of six steps: 1) FDK reconstruction using raw projection data; 2) Rigid Registration of planning CT to the FDK results; 3) MC scatter calculation at sparse view angles using the planning CT; 4) Interpolation of the calculated scatter signals to other angles; 5) Removal of scatter from the raw projections;more » 6) FDK reconstruction using the scatter-corrected projections. In addition to using GPU to accelerate MC photon simulations, we also use a small number of photons and a down-sampled CT image in simulation to further reduce computation time. A novel denoising algorithm is used to eliminate MC scatter noise caused by low photon numbers. The method is validated on head-and-neck cases with simulated and clinical data. Results: We have studied impacts of photo histories, volume down sampling factors on the accuracy of scatter estimation. The Fourier analysis was conducted to show that scatter images calculated at 31 angles are sufficient to restore those at all angles with <0.1% error. For the simulated case with a resolution of 512×512×100, we simulated 10M photons per angle. The total computation time is 23.77 seconds on a Nvidia GTX Titan GPU. The scatter-induced shading/cupping artifacts are substantially reduced, and the average HU error of a region-of-interest is reduced from 75.9 to 19.0 HU. Similar results were found for a real patient case. Conclusion: A practical ultrafast MC-based CBCT scatter correction scheme is developed. The whole process of scatter correction and reconstruction is accomplished within 30 seconds. This study is supported in part by NIH (1R01CA154747-01), The Core Technology Research in Strategic Emerging Industry, Guangdong, China (2011A081402003)« less

Minimizing a Wireless Passive LC-Tank Sensor to Monitor Bladder Pressure: A Simulation Study.

PubMed

Melgaard, Jacob; Struijk, Johannes J; Rijkhoff, Nico J M

2017-01-01

In this simulation study, a wireless passive LC-tank sensor system was characterized. Given the application of continuous bladder monitoring, a specific system was proposed in terms of coil geometries and electronic circuitry. Coupling coefficients were spatially mapped by simulation, as a function of both coil distance, and longitudinal and transverse translation of the sensor relative to the antenna. Further, two interrogation schemes were outlined. One was an auto-balancing bridge for computing the sensor-system impedance. In this case, the theoretical noise limit of the analogue part of the system was found by simulations. As the full system is not necessary for obtaining a pressure reading from the sensor, a simplified circuit more suited for an implantable system was deduced. For this system, both the analogue and digital parts were simulated. First, the required ADC resolution for operating the system at a given coupling was found by simulations in the noise-free case. Then, for one selected typical operational point, noise was added gradually, and through Monte-Carlo type simulations, the system performance was obtained. Combining these results, it was found that it at least is possible to operate the proposed system for distances up to 12 mm, or equivalently for coupling coefficients above 0.005. In this case a 14 bit ADC is required, and a carrier SNR of 27 dB can be tolerated.

Latin hypercube sampling and geostatistical modeling of spatial uncertainty in a spatially explicit forest landscape model simulation

Treesearch

Chonggang Xu; Hong S. He; Yuanman Hu; Yu Chang; Xiuzhen Li; Rencang Bu

2005-01-01

Geostatistical stochastic simulation is always combined with Monte Carlo method to quantify the uncertainty in spatial model simulations. However, due to the relatively long running time of spatially explicit forest models as a result of their complexity, it is always infeasible to generate hundreds or thousands of Monte Carlo simulations. Thus, it is of great...

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.

Implementation of an open-scenario, long-term space debris simulation approach

NASA Astrophysics Data System (ADS)

Stupl, J.; Nelson, B.; Faber, N.; Perez, A.; Carlino, R.; Yang, F.; Henze, C.; Karacalioglu, A.; O'Toole, C.; Swenson, J.

This paper provides a status update on the implementation of a flexible, long-term space debris simulation approach. The motivation is to build a tool that can assess the long-term impact of various options for debris-remediation, including the LightForce space debris collision avoidance scheme. State-of-the-art simulation approaches that assess the long-term development of the debris environment use either completely statistical approaches, or they rely on large time steps in the order of several (5-15) days if they simulate the positions of single objects over time. They cannot be easily adapted to investigate the impact of specific collision avoidance schemes or de-orbit schemes, because the efficiency of a collision avoidance maneuver can depend on various input parameters, including ground station positions, space object parameters and orbital parameters of the conjunctions and take place in much smaller timeframes than 5-15 days. For example, LightForce only changes the orbit of a certain object (aiming to reduce the probability of collision), but it does not remove entire objects or groups of objects. In the same sense, it is also not straightforward to compare specific de-orbit methods in regard to potential collision risks during a de-orbit maneuver. To gain flexibility in assessing interactions with objects, we implement a simulation that includes every tracked space object in LEO, propagates all objects with high precision, and advances with variable-sized time-steps as small as one second. It allows the assessment of the (potential) impact of changes to any object. The final goal is to employ a Monte Carlo approach to assess the debris evolution during the simulation time-frame of 100 years and to compare a baseline scenario to debris remediation scenarios or other scenarios of interest. To populate the initial simulation, we use the entire space-track object catalog in LEO. We then use a high precision propagator to propagate all objects over the entire simulation duration. If collisions are detected, the appropriate number of debris objects are created and inserted into the simulation framework. Depending on the scenario, further objects, e.g. due to new launches, can be added. At the end of the simulation, the total number of objects above a cut-off size and the number of detected collisions provide benchmark parameters for the comparison between scenarios. The simulation approach is computationally intensive as it involves ten thousands of objects; hence we use a highly parallel approach employing up to a thousand cores on the NASA Pleiades supercomputer for a single run. This paper describes our simulation approach, the status of its implementation, the approach in developing scenarios and examples of first test runs.

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

Sudhyadhom, A; McGuinness, C; Descovich, M

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

Monte Carlo simulation of biomolecular systems with BIOMCSIM

NASA Astrophysics Data System (ADS)

Kamberaj, H.; Helms, V.

2001-12-01

A new Monte Carlo simulation program, BIOMCSIM, is presented that has been developed in particular to simulate the behaviour of biomolecular systems, leading to insights and understanding of their functions. The computational complexity in Monte Carlo simulations of high density systems, with large molecules like proteins immersed in a solvent medium, or when simulating the dynamics of water molecules in a protein cavity, is enormous. The program presented in this paper seeks to provide these desirable features putting special emphasis on simulations in grand canonical ensembles. It uses different biasing techniques to increase the convergence of simulations, and periodic load balancing in its parallel version, to maximally utilize the available computer power. In periodic systems, the long-ranged electrostatic interactions can be treated by Ewald summation. The program is modularly organized, and implemented using an ANSI C dialect, so as to enhance its modifiability. Its performance is demonstrated in benchmark applications for the proteins BPTI and Cytochrome c Oxidase.

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.

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

PubMed

Renner, Franziska

2016-09-01

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

Monte Carlo Simulation Using HyperCard and Lotus 1-2-3.

ERIC Educational Resources Information Center

Oulman, Charles S.; Lee, Motoko Y.

Monte Carlo simulation is a computer modeling procedure for mimicking observations on a random variable. A random number generator is used in generating the outcome for the events that are being modeled. The simulation can be used to obtain results that otherwise require extensive testing or complicated computations. This paper describes how Monte…

Monte Carlo Particle Lists: MCPL

NASA Astrophysics Data System (ADS)

Kittelmann, T.; Klinkby, E.; Knudsen, E. B.; Willendrup, P.; Cai, X. X.; Kanaki, K.

2017-09-01

A binary format with lists of particle state information, for interchanging particles between various Monte Carlo simulation applications, is presented. Portable C code for file manipulation is made available to the scientific community, along with converters and plugins for several popular simulation packages.

Baseball Monte Carlo Style.

ERIC Educational Resources Information Center

Houser, Larry L.

1981-01-01

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

Instrumental resolution of the chopper spectrometer 4SEASONS evaluated by Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Kajimoto, Ryoichi; Sato, Kentaro; Inamura, Yasuhiro; Fujita, Masaki

2018-05-01

We performed simulations of the resolution function of the 4SEASONS spectrometer at J-PARC by using the Monte Carlo simulation package McStas. The simulations showed reasonably good agreement with analytical calculations of energy and momentum resolutions by using a simplified description. We implemented new functionalities in Utsusemi, the standard data analysis tool used in 4SEASONS, to enable visualization of the simulated resolution function and predict its shape for specific experimental configurations.

OBJECT KINETIC MONTE CARLO SIMULATIONS OF MICROSTRUCTURE EVOLUTION

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

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

2013-09-30

The objective is to report the development of the flexible object kinetic Monte Carlo (OKMC) simulation code KSOME (kinetic simulation of microstructure evolution) which can be used to simulate microstructure evolution of complex systems under irradiation. In this report we briefly describe the capabilities of KSOME and present preliminary results for short term annealing of single cascades in tungsten at various primary-knock-on atom (PKA) energies and temperatures.

High-resolution Monte Carlo simulation of flow and conservative transport in heterogeneous porous media: 2. Transport results

USGS Publications Warehouse

Naff, R.L.; Haley, D.F.; Sudicky, E.A.

1998-01-01

In this, the second of two papers concerned with the use of numerical simulation to examine flow and transport parameters in heterogeneous porous media via Monte Carlo methods, results from the transport aspect of these simulations are reported on. Transport simulations contained herein assume a finite pulse input of conservative tracer, and the numerical technique endeavors to realistically simulate tracer spreading as the cloud moves through a heterogeneous medium. Medium heterogeneity is limited to the hydraulic conductivity field, and generation of this field assumes that the hydraulic-conductivity process is second-order stationary. Methods of estimating cloud moments, and the interpretation of these moments, are discussed. Techniques for estimation of large-time macrodispersivities from cloud second-moment data, and for the approximation of the standard errors associated with these macrodispersivities, are also presented. These moment and macrodispersivity estimation techniques were applied to tracer clouds resulting from transport scenarios generated by specific Monte Carlo simulations. Where feasible, moments and macrodispersivities resulting from the Monte Carlo simulations are compared with first- and second-order perturbation analyses. Some limited results concerning the possible ergodic nature of these simulations, and the presence of non-Gaussian behavior of the mean cloud, are reported on as well.

SU-F-T-50: Evaluation of Monte Carlo Simulations Performance for Pediatric Brachytherapy Dosimetry

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

Chatzipapas, C; Kagadis, G; Papadimitroulas, P

Purpose: Pediatric tumors are generally treated with multi-modal procedures. Brachytherapy can be used with pediatric tumors, especially given that in this patient population low toxicity on normal tissues is critical as is the suppression of the probability for late malignancies. Our goal is to validate the GATE toolkit on realistic brachytherapy applications, and evaluate brachytherapy plans on pediatrics for accurate dosimetry on sensitive and critical organs of interest. Methods: The GATE Monte Carlo (MC) toolkit was used. Two High Dose Rate (HDR) 192Ir brachytherapy sources were simulated (Nucletron mHDR-v1 and Varian VS2000), and fully validated using the AAPM and ESTROmore » protocols. A realistic brachytherapy plan was also simulated using the XCAT anthropomorphic computational model .The simulated data were compared to the clinical dose points. Finally, a 14 years old girl with vaginal rhabdomyosarcoma was modelled based on clinical procedures for the calculation of the absorbed dose per organ. Results: The MC simulations resulted in accurate dosimetry in terms of dose rate constant (Λ), radial dose gL(r) and anisotropy function F(r,θ) for both sources.The simulations were executed using ∼1010 number of primaries resulting in statistical uncertainties lower than 2%.The differences between the theoretical values and the simulated ones ranged from 0.01% up to 3.3%, with the largest discrepancy (6%) being observed in the dose rate constant calculation.The simulated DVH using an adult female XCAT model was also compared to a clinical one resulting in differences smaller than 5%. Finally, a realistic pediatric brachytherapy simulation was performed to evaluate the absorbed dose per organ and to calculate DVH with respect to heterogeneities of the human anatomy. Conclusion: GATE is a reliable tool for brachytherapy simulations both for source modeling and for dosimetry in anthropomorphic voxelized models. Our project aims to evaluate a variety of pediatric brachytherapy schemes using a population of pediatric phantoms for several pathological cases. This study is part of a project that has received funding from the European Union Horizon2020 research and innovation programme under the MarieSklodowska-Curiegrantagreement.No691203.The results published in this study reflect only the authors view and the Research Executive Agency (REA) and the European Commission is not responsible for any use that may be madeof the information it contains.« less

A correction scheme for a simplified analytical random walk model algorithm of proton dose calculation in distal Bragg peak regions

NASA Astrophysics Data System (ADS)

Yao, Weiguang; Merchant, Thomas E.; Farr, Jonathan B.

2016-10-01

The lateral homogeneity assumption is used in most analytical algorithms for proton dose, such as the pencil-beam algorithms and our simplified analytical random walk model. To improve the dose calculation in the distal fall-off region in heterogeneous media, we analyzed primary proton fluence near heterogeneous media and propose to calculate the lateral fluence with voxel-specific Gaussian distributions. The lateral fluence from a beamlet is no longer expressed by a single Gaussian for all the lateral voxels, but by a specific Gaussian for each lateral voxel. The voxel-specific Gaussian for the beamlet of interest is calculated by re-initializing the fluence deviation on an effective surface where the proton energies of the beamlet of interest and the beamlet passing the voxel are the same. The dose improvement from the correction scheme was demonstrated by the dose distributions in two sets of heterogeneous phantoms consisting of cortical bone, lung, and water and by evaluating distributions in example patients with a head-and-neck tumor and metal spinal implants. The dose distributions from Monte Carlo simulations were used as the reference. The correction scheme effectively improved the dose calculation accuracy in the distal fall-off region and increased the gamma test pass rate. The extra computation for the correction was about 20% of that for the original algorithm but is dependent upon patient geometry.

Elastic all-optical multi-hop interconnection in data centers with adaptive spectrum allocation

NASA Astrophysics Data System (ADS)

Hong, Yuanyuan; Hong, Xuezhi; Chen, Jiajia; He, Sailing

2017-01-01

In this paper, a novel flex-grid all-optical interconnect scheme that supports transparent multi-hop connections in data centers is proposed. An inter-rack all-optical multi-hop connection is realized with an optical loop employed at flex-grid wavelength selective switches (WSSs) in an intermediate rack rather than by relaying through optical-electric-optical (O-E-O) conversions. Compared with the conventional O-E-O based approach, the proposed all-optical scheme is able to off-load the traffic at intermediate racks, leading to a reduction of the power consumption and cost. The transmission performance of the proposed flex-grid multi-hop all-optical interconnect scheme with various modulation formats, including both coherently detected and directly detected approaches, are investigated by Monte-Carlo simulations. To enhance the spectrum efficiency (SE), number-of-hop adaptive bandwidth allocation is introduced. Numerical results show that the SE can be improved by up to 33.3% at 40 Gbps, and by up to 25% at 100 Gbps. The impact of parameters, such as targeted bit error rate (BER) level and insertion loss of components, on the transmission performance of the proposed approach are also explored. The results show that the maximum SE improvement of the adaptive approach over the non-adaptive one is enhanced with the decrease of the targeted BER levels and the component insertion loss.

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

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

Ogawa, K.; Maeda, S.

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

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

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

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

2016-04-15

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

SU-E-T-222: Computational Optimization of Monte Carlo Simulation On 4D Treatment Planning Using the Cloud Computing Technology

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

Chow, J

Purpose: This study evaluated the efficiency of 4D lung radiation treatment planning using Monte Carlo simulation on the cloud. The EGSnrc Monte Carlo code was used in dose calculation on the 4D-CT image set. Methods: 4D lung radiation treatment plan was created by the DOSCTP linked to the cloud, based on the Amazon elastic compute cloud platform. Dose calculation was carried out by Monte Carlo simulation on the 4D-CT image set on the cloud, and results were sent to the FFD4D image deformation program for dose reconstruction. The dependence of computing time for treatment plan on the number of computemore » node was optimized with variations of the number of CT image set in the breathing cycle and dose reconstruction time of the FFD4D. Results: It is found that the dependence of computing time on the number of compute node was affected by the diminishing return of the number of node used in Monte Carlo simulation. Moreover, the performance of the 4D treatment planning could be optimized by using smaller than 10 compute nodes on the cloud. The effects of the number of image set and dose reconstruction time on the dependence of computing time on the number of node were not significant, as more than 15 compute nodes were used in Monte Carlo simulations. Conclusion: The issue of long computing time in 4D treatment plan, requiring Monte Carlo dose calculations in all CT image sets in the breathing cycle, can be solved using the cloud computing technology. It is concluded that the optimized number of compute node selected in simulation should be between 5 and 15, as the dependence of computing time on the number of node is significant.« less

SU-F-T-149: Development of the Monte Carlo Simulation Platform Using Geant4 for Designing Heavy Ion Therapy Beam Nozzle

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

Shin, Jae-ik; Yoo, SeungHoon; Cho, Sungho

Purpose: The significant issue of particle therapy such as proton and carbon ion was a accurate dose delivery from beam line to patient. For designing the complex delivery system, Monte Carlo simulation can be used for the simulation of various physical interaction in scatters and filters. In this report, we present the development of Monte Carlo simulation platform to help design the prototype of particle therapy nozzle and performed the Monte Carlo simulation using Geant4. Also we show the prototype design of particle therapy beam nozzle for Korea Heavy Ion Medical Accelerator (KHIMA) project in Korea Institute of Radiological andmore » Medical Science(KIRAMS) at Republic of Korea. Methods: We developed a simulation platform for particle therapy beam nozzle using Geant4. In this platform, the prototype nozzle design of Scanning system for carbon was simply designed. For comparison with theoretic beam optics, the beam profile on lateral distribution at isocenter is compared with Mont Carlo simulation result. From the result of this analysis, we can expected the beam spot property of KHIMA system and implement the spot size optimization for our spot scanning system. Results: For characteristics study of scanning system, various combination of the spot size from accerlator with ridge filter and beam monitor was tested as simple design for KHIMA dose delivery system. Conclusion: In this report, we presented the part of simulation platform and the characteristics study. This study is now on-going in order to develop the simulation platform including the beam nozzle and the dose verification tool with treatment planning system. This will be presented as soon as it is become available.« less

Monte Carlo Methodology Serves Up a Software Success

NASA Technical Reports Server (NTRS)

2003-01-01

Widely used for the modeling of gas flows through the computation of the motion and collisions of representative molecules, the Direct Simulation Monte Carlo method has become the gold standard for producing research and engineering predictions in the field of rarefied gas dynamics. Direct Simulation Monte Carlo was first introduced in the early 1960s by Dr. Graeme Bird, a professor at the University of Sydney, Australia. It has since proved to be a valuable tool to the aerospace and defense industries in providing design and operational support data, as well as flight data analysis. In 2002, NASA brought to the forefront a software product that maintains the same basic physics formulation of Dr. Bird's method, but provides effective modeling of complex, three-dimensional, real vehicle simulations and parallel processing capabilities to handle additional computational requirements, especially in areas where computational fluid dynamics (CFD) is not applicable. NASA's Direct Simulation Monte Carlo Analysis Code (DAC) software package is now considered the Agency s premier high-fidelity simulation tool for predicting vehicle aerodynamics and aerothermodynamic environments in rarified, or low-density, gas flows.

MO-FG-BRA-01: 4D Monte Carlo Simulations for Verification of Dose Delivered to a Moving Anatomy

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

Gholampourkashi, S; Cygler, J E.; The Ottawa Hospital Cancer Centre, Ottawa, ON

Purpose: To validate 4D Monte Carlo (MC) simulations of dose delivery by an Elekta Agility linear accelerator to a moving phantom. Methods: Monte Carlo simulations were performed using the 4DdefDOSXYZnrc/EGSnrc user code which samples a new geometry for each incident particle and calculates the dose in a continuously moving anatomy. A Quasar respiratory motion phantom with a lung insert containing a 3 cm diameter tumor was used for dose measurements on an Elekta Agility linac with the phantom in stationary and moving states. Dose to the center of tumor was measured using calibrated EBT3 film and the RADPOS 4D dosimetrymore » system. A VMAT plan covering the tumor was created on the static CT scan of the phantom using Monaco V.5.10.02. A validated BEAMnrc model of our Elekta Agility linac was used for Monte Carlo simulations on stationary and moving anatomies. To compare the planned and delivered doses, linac log files recorded during measurements were used for the simulations. For 4D simulations, deformation vectors that modeled the rigid translation of the lung insert were generated as input to the 4DdefDOSXYZnrc code as well as the phantom motion trace recorded with RADPOS during the measurements. Results: Monte Carlo simulations and film measurements were found to agree within 2mm/2% for 97.7% of points in the film in the static phantom and 95.5% in the moving phantom. Dose values based on film and RADPOS measurements are within 2% of each other and within 2σ of experimental uncertainties with respect to simulations. Conclusion: Our 4D Monte Carlo simulation using the defDOSXYZnrc code accurately calculates dose delivered to a moving anatomy. Future work will focus on more investigation of VMAT delivery on a moving phantom to improve the agreement between simulation and measurements, as well as establishing the accuracy of our method in a deforming anatomy. This work was supported by the Ontario Consortium of Adaptive Interventions in Radiation Oncology (OCAIRO), funded by the Ontario Research Fund Research Excellence program.« less

Effect of the multiple scattering of electrons in Monte Carlo simulation of LINACS.

PubMed

Vilches, Manuel; García-Pareja, Salvador; Guerrero, Rafael; Anguiano, Marta; Lallena, Antonio M

2008-01-01

Results obtained from Monte Carlo simulations of the transport of electrons in thin slabs of dense material media and air slabs with different widths are analyzed. Various general purpose Monte Carlo codes have been used: PENELOPE, GEANT3, GEANT4, EGSNRC, MCNPX. Non-negligible differences between the angular and radial distributions after the slabs have been found. The effects of these differences on the depth doses measured in water are also discussed.

Accelerating Monte Carlo simulations of photon transport in a voxelized geometry using a massively parallel graphics processing unit

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

Badal, Andreu; Badano, Aldo

Purpose: It is a known fact that Monte Carlo simulations of radiation transport are computationally intensive and may require long computing times. The authors introduce a new paradigm for the acceleration of Monte Carlo simulations: The use of a graphics processing unit (GPU) as the main computing device instead of a central processing unit (CPU). Methods: A GPU-based Monte Carlo code that simulates photon transport in a voxelized geometry with the accurate physics models from PENELOPE has been developed using the CUDA programming model (NVIDIA Corporation, Santa Clara, CA). Results: An outline of the new code and a sample x-raymore » imaging simulation with an anthropomorphic phantom are presented. A remarkable 27-fold speed up factor was obtained using a GPU compared to a single core CPU. Conclusions: The reported results show that GPUs are currently a good alternative to CPUs for the simulation of radiation transport. Since the performance of GPUs is currently increasing at a faster pace than that of CPUs, the advantages of GPU-based software are likely to be more pronounced in the future.« less

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

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

Matthew Ellis; Derek Gaston; Benoit Forget

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

Multi-Conformation Monte Carlo: A Method for Introducing Flexibility in Efficient Simulations of Many-Protein Systems.

PubMed

Prytkova, Vera; Heyden, Matthias; Khago, Domarin; Freites, J Alfredo; Butts, Carter T; Martin, Rachel W; Tobias, Douglas J

2016-08-25

We present a novel multi-conformation Monte Carlo simulation method that enables the modeling of protein-protein interactions and aggregation in crowded protein solutions. This approach is relevant to a molecular-scale description of realistic biological environments, including the cytoplasm and the extracellular matrix, which are characterized by high concentrations of biomolecular solutes (e.g., 300-400 mg/mL for proteins and nucleic acids in the cytoplasm of Escherichia coli). Simulation of such environments necessitates the inclusion of a large number of protein molecules. Therefore, computationally inexpensive methods, such as rigid-body Brownian dynamics (BD) or Monte Carlo simulations, can be particularly useful. However, as we demonstrate herein, the rigid-body representation typically employed in simulations of many-protein systems gives rise to certain artifacts in protein-protein interactions. Our approach allows us to incorporate molecular flexibility in Monte Carlo simulations at low computational cost, thereby eliminating ambiguities arising from structure selection in rigid-body simulations. We benchmark and validate the methodology using simulations of hen egg white lysozyme in solution, a well-studied system for which extensive experimental data, including osmotic second virial coefficients, small-angle scattering structure factors, and multiple structures determined by X-ray and neutron crystallography and solution NMR, as well as rigid-body BD simulation results, are available for comparison.

Towards Stochastic Optimization-Based Electric Vehicle Penetration in a Novel Archipelago Microgrid.

PubMed

Yang, Qingyu; An, Dou; Yu, Wei; Tan, Zhengan; Yang, Xinyu

2016-06-17

Due to the advantage of avoiding upstream disturbance and voltage fluctuation from a power transmission system, Islanded Micro-Grids (IMG) have attracted much attention. In this paper, we first propose a novel self-sufficient Cyber-Physical System (CPS) supported by Internet of Things (IoT) techniques, namely "archipelago micro-grid (MG)", which integrates the power grid and sensor networks to make the grid operation effective and is comprised of multiple MGs while disconnected with the utility grid. The Electric Vehicles (EVs) are used to replace a portion of Conventional Vehicles (CVs) to reduce CO 2 emission and operation cost. Nonetheless, the intermittent nature and uncertainty of Renewable Energy Sources (RESs) remain a challenging issue in managing energy resources in the system. To address these issues, we formalize the optimal EV penetration problem as a two-stage Stochastic Optimal Penetration (SOP) model, which aims to minimize the emission and operation cost in the system. Uncertainties coming from RESs (e.g., wind, solar, and load demand) are considered in the stochastic model and random parameters to represent those uncertainties are captured by the Monte Carlo-based method. To enable the reasonable deployment of EVs in each MGs, we develop two scheduling schemes, namely Unlimited Coordinated Scheme (UCS) and Limited Coordinated Scheme (LCS), respectively. An extensive simulation study based on a modified 9 bus system with three MGs has been carried out to show the effectiveness of our proposed schemes. The evaluation data indicates that our proposed strategy can reduce both the environmental pollution created by CO 2 emissions and operation costs in UCS and LCS.

Towards Stochastic Optimization-Based Electric Vehicle Penetration in a Novel Archipelago Microgrid

PubMed Central

Yang, Qingyu; An, Dou; Yu, Wei; Tan, Zhengan; Yang, Xinyu

2016-01-01

Due to the advantage of avoiding upstream disturbance and voltage fluctuation from a power transmission system, Islanded Micro-Grids (IMG) have attracted much attention. In this paper, we first propose a novel self-sufficient Cyber-Physical System (CPS) supported by Internet of Things (IoT) techniques, namely “archipelago micro-grid (MG)”, which integrates the power grid and sensor networks to make the grid operation effective and is comprised of multiple MGs while disconnected with the utility grid. The Electric Vehicles (EVs) are used to replace a portion of Conventional Vehicles (CVs) to reduce CO2 emission and operation cost. Nonetheless, the intermittent nature and uncertainty of Renewable Energy Sources (RESs) remain a challenging issue in managing energy resources in the system. To address these issues, we formalize the optimal EV penetration problem as a two-stage Stochastic Optimal Penetration (SOP) model, which aims to minimize the emission and operation cost in the system. Uncertainties coming from RESs (e.g., wind, solar, and load demand) are considered in the stochastic model and random parameters to represent those uncertainties are captured by the Monte Carlo-based method. To enable the reasonable deployment of EVs in each MGs, we develop two scheduling schemes, namely Unlimited Coordinated Scheme (UCS) and Limited Coordinated Scheme (LCS), respectively. An extensive simulation study based on a modified 9 bus system with three MGs has been carried out to show the effectiveness of our proposed schemes. The evaluation data indicates that our proposed strategy can reduce both the environmental pollution created by CO2 emissions and operation costs in UCS and LCS. PMID:27322281

Comparison of effects of copropagated and precomputed atmosphere profiles on Monte Carlo trajectory simulation

NASA Technical Reports Server (NTRS)

Queen, Eric M.; Omara, Thomas M.

1990-01-01

A realization of a stochastic atmosphere model for use in simulations is presented. The model provides pressure, density, temperature, and wind velocity as a function of latitude, longitude, and altitude, and is implemented in a three degree of freedom simulation package. This implementation is used in the Monte Carlo simulation of an aeroassisted orbital transfer maneuver and results are compared to those of a more traditional approach.

Acceleration of Monte Carlo simulation of photon migration in complex heterogeneous media using Intel many-integrated core architecture.

PubMed

Gorshkov, Anton V; Kirillin, Mikhail Yu

2015-08-01

Over two decades, the Monte Carlo technique has become a gold standard in simulation of light propagation in turbid media, including biotissues. Technological solutions provide further advances of this technique. The Intel Xeon Phi coprocessor is a new type of accelerator for highly parallel general purpose computing, which allows execution of a wide range of applications without substantial code modification. We present a technical approach of porting our previously developed Monte Carlo (MC) code for simulation of light transport in tissues to the Intel Xeon Phi coprocessor. We show that employing the accelerator allows reducing computational time of MC simulation and obtaining simulation speed-up comparable to GPU. We demonstrate the performance of the developed code for simulation of light transport in the human head and determination of the measurement volume in near-infrared spectroscopy brain sensing.

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

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.

Random number generators for large-scale parallel Monte Carlo simulations on FPGA

NASA Astrophysics Data System (ADS)

Lin, Y.; Wang, F.; Liu, B.

2018-05-01

Through parallelization, field programmable gate array (FPGA) can achieve unprecedented speeds in large-scale parallel Monte Carlo (LPMC) simulations. FPGA presents both new constraints and new opportunities for the implementations of random number generators (RNGs), which are key elements of any Monte Carlo (MC) simulation system. Using empirical and application based tests, this study evaluates all of the four RNGs used in previous FPGA based MC studies and newly proposed FPGA implementations for two well-known high-quality RNGs that are suitable for LPMC studies on FPGA. One of the newly proposed FPGA implementations: a parallel version of additive lagged Fibonacci generator (Parallel ALFG) is found to be the best among the evaluated RNGs in fulfilling the needs of LPMC simulations on FPGA.

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.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Study of photo-oxidative reactivity of sunscreening agents based on photo-oxidation of uric acid by kinetic Monte Carlo simulation.

PubMed

Moradmand Jalali, Hamed; Bashiri, Hadis; Rasa, Hossein

2015-05-01

In the present study, the mechanism of free radical production by light-reflective agents in sunscreens (TiO2, ZnO and ZrO2) was obtained by applying kinetic Monte Carlo simulation. The values of the rate constants for each step of the suggested mechanism have been obtained by simulation. The effect of the initial concentration of mineral oxides and uric acid on the rate of uric acid photo-oxidation by irradiation of some sun care agents has been studied. The kinetic Monte Carlo simulation results agree qualitatively with the existing experimental data for the production of free radicals by sun care agents. Copyright © 2015 Elsevier B.V. All rights reserved.

Recommender engine for continuous-time quantum Monte Carlo methods

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Efficient Monte Carlo Methods for Biomolecular Simulations.

NASA Astrophysics Data System (ADS)

Bouzida, Djamal

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

Experimental benchmarking of a Monte Carlo dose simulation code for pediatric CT

NASA Astrophysics Data System (ADS)

Li, Xiang; Samei, Ehsan; Yoshizumi, Terry; Colsher, James G.; Jones, Robert P.; Frush, Donald P.

2007-03-01

In recent years, there has been a desire to reduce CT radiation dose to children because of their susceptibility and prolonged risk for cancer induction. Concerns arise, however, as to the impact of dose reduction on image quality and thus potentially on diagnostic accuracy. To study the dose and image quality relationship, we are developing a simulation code to calculate organ dose in pediatric CT patients. To benchmark this code, a cylindrical phantom was built to represent a pediatric torso, which allows measurements of dose distributions from its center to its periphery. Dose distributions for axial CT scans were measured on a 64-slice multidetector CT (MDCT) scanner (GE Healthcare, Chalfont St. Giles, UK). The same measurements were simulated using a Monte Carlo code (PENELOPE, Universitat de Barcelona) with the applicable CT geometry including bowtie filter. The deviations between simulated and measured dose values were generally within 5%. To our knowledge, this work is one of the first attempts to compare measured radial dose distributions on a cylindrical phantom with Monte Carlo simulated results. It provides a simple and effective method for benchmarking organ dose simulation codes and demonstrates the potential of Monte Carlo simulation for investigating the relationship between dose and image quality for pediatric CT patients.

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

PubMed

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

2018-01-01

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

Neoclassical toroidal viscosity calculations in tokamaks using a δf Monte Carlo simulation and their verifications.

PubMed

Satake, S; Park, J-K; Sugama, H; Kanno, R

2011-07-29

Neoclassical toroidal viscosities (NTVs) in tokamaks are investigated using a δf Monte Carlo simulation, and are successfully verified with a combined analytic theory over a wide range of collisionality. A Monte Carlo simulation has been required in the study of NTV since the complexities in guiding-center orbits of particles and their collisions cannot be fully investigated by any means of analytic theories alone. Results yielded the details of the complex NTV dependency on particle precessions and collisions, which were predicted roughly in a combined analytic theory. Both numerical and analytic methods can be utilized and extended based on these successful verifications.

Improved radial dose function estimation using current version MCNP Monte-Carlo simulation: Model 6711 and ISC3500 125I brachytherapy sources.

PubMed

Duggan, Dennis M

2004-12-01

Improved cross-sections in a new version of the Monte-Carlo N-particle (MCNP) code may eliminate discrepancies between radial dose functions (as defined by American Association of Physicists in Medicine Task Group 43) derived from Monte-Carlo simulations of low-energy photon-emitting brachytherapy sources and those from measurements on the same sources with thermoluminescent dosimeters. This is demonstrated for two 125I brachytherapy seed models, the Implant Sciences Model ISC3500 (I-Plant) and the Amersham Health Model 6711, by simulating their radial dose functions with two versions of MCNP, 4c2 and 5.

Modelling the spread of American foulbrood in honeybees

PubMed Central

Datta, Samik; Bull, James C.; Budge, Giles E.; Keeling, Matt J.

2013-01-01

We investigate the spread of American foulbrood (AFB), a disease caused by the bacterium Paenibacillus larvae, that affects bees and can be extremely damaging to beehives. Our dataset comes from an inspection period carried out during an AFB epidemic of honeybee colonies on the island of Jersey during the summer of 2010. The data include the number of hives of honeybees, location and owner of honeybee apiaries across the island. We use a spatial SIR model with an underlying owner network to simulate the epidemic and characterize the epidemic using a Markov chain Monte Carlo (MCMC) scheme to determine model parameters and infection times (including undetected ‘occult’ infections). Likely methods of infection spread can be inferred from the analysis, with both distance- and owner-based transmissions being found to contribute to the spread of AFB. The results of the MCMC are corroborated by simulating the epidemic using a stochastic SIR model, resulting in aggregate levels of infection that are comparable to the data. We use this stochastic SIR model to simulate the impact of different control strategies on controlling the epidemic. It is found that earlier inspections result in smaller epidemics and a higher likelihood of AFB extinction. PMID:24026473

BFS Simulation and Experimental Analysis of the Effect of Ti Additions on the Structure of NiAl

NASA Technical Reports Server (NTRS)

Bozzolo, Guillermo; Noebe, Ronald D.; Ferrante,John; Garg, Anita; Honecy, Frank S.; Amador, Carlos

1999-01-01

The Bozzolo-Ferrante-Smith (BFS) method for alloy energetics is applied to the study of ternary additions to NiAl. A description of the method and its application to alloy design is given. Two different approaches are used in the analysis of the effect of Ti additions to NiAl. First, a thorough analytical study is performed, where the energy of formation, lattice parameter and bulk modulus are calculated for a large number of possible atomic distributions of Ni, Al and Ti. Substitutional site preference schemes and formation of precipitates are thus predicted and analyzed. The second approach used consists of the determination of temperature effects on the final results, as obtained by performing a number of large scale numerical simulations using the Monte Carlo-Metropolis procedure and BFS for the calculation of the energy at every step in the simulation. The results indicate a sharp preference of Ti for Al sites in Ni-rich NiAl alloys and the formation of ternary Heusler precipitates beyond the predicted solubility limit of 5 at. % Ti. Experimental analysis of three Ni-Al-Ti alloys confirms the theoretical predictions.

Broadening of cloud droplet spectra through turbulent entrainment and eddy hopping

NASA Astrophysics Data System (ADS)

Abade, Gustavo; Grabowski, Wojciech; Pawlowska, Hanna

2017-11-01

This work discusses the effect of cloud turbulence and turbulent entrainment on the evolution of the cloud droplet-size spectrum. We simulate an ensemble of idealized turbulent cloud parcels that are subject to entrainment events, modeled as a random Poisson process. Entrainment events, subsequent turbulent mixing inside the parcel, supersaturation fluctuations, and the resulting stochastic droplet growth by condensation are simulated using a Monte Carlo scheme. Quantities characterizing the turbulence intensity, entrainment rate and the mean fraction of environmental air entrained in an event are specified as external parameters. Cloud microphysics is described by applying Lagrangian particles, the so-called superdroplets. They are either unactivated cloud condensation nuclei (CCN) or cloud droplets that form from activated CCN. The model accounts for the transport of environmental CCN into the cloud by the entraining eddies at the cloud edge. Turbulent mixing of the entrained dry air with cloudy air is described using a linear model. We show that turbulence plays an important role in aiding entrained CCN to activate, providing a source of small cloud droplets and thus broadening the droplet size distribution. Further simulation results will be reported at the meeting.

Atomistic Simulations and Experimental Analysis of the Effect of Ti Additions on the Structure of NiAl

NASA Technical Reports Server (NTRS)

Bozzolo, Guillermo; Noebe, Ronald D.; Ferrante, John; Garg, Anita; Amador, Carlos

1997-01-01

The Bozzolo-Ferrante-Smith (BFS) semiempirical method for alloy energetics is applied to the study of ternary additions to NiAl alloys. A detailed description of the method and its application to alloy design is given. Two different approaches are used in the analysis of the effect of Ti additions to NiAl. First, a thorough analytical study is performed, where the energy of formation, lattice parameter and bulk modulus are calculated for hundreds of possible atomic distributions of Ni, Al and Ti. Substitutional site preference schemes and formation of precipitates are thus predicted and analyzed. The second approach used consists of the determination of temperature effects on the final results, as obtained by performing a number of large scale numerical simulations using the Monte Carlo - Metropolis procedure and BFS for the calculation of the energy at every step in the simulation. The results indicate a sharp preference of Ti for Al sites in Ni-rich NiAl alloys and the formation of ternary Heusler precipitates beyond the predicted solubility limit of 5 at. % Ti. Experimental analysis of three NiAl+Ti alloys confirms the theoretical predictions.

Large eddy simulations of a bluff-body stabilized hydrogen-methane jet flame

NASA Astrophysics Data System (ADS)

Drozda, Tomasz; Pope, Stephen

2005-11-01

Large eddy simulation (LES) is conducted of the turbulent bluff-body stabilized hydrogen-methane flame as considered in the experiments of the Combustion Research Facility at the Sandia National Laboratories and of the Thermal Research Group at the University of Sydney [1]. Both, reacting and non-reacting flows are considered. The subgrid scale (SGS) closure in LES is based on the scalar filtered mass density function (SFMDF) methodology [2]. A flamelet model is used to relate the chemical composition to the mixture fraction. The modeled SFMDF transport equation is solved by a hybrid finite-difference (FD) / Monte Carlo (MC) scheme. The FD component of the hybrid solver is validated by comparisons of the experimentally available flow statistics with those predicted by LES. The results via this method capture important features of the flames as observed experimentally.[1] A. R. Masri, R. W. Dibble, and R. S. Barlow. The structure of turbulent nonpremixed flames revealed by Raman-Rayleigh-LIF measurements. Prog. Energy Combust. Sci., 22:307--362, 1996. [2] F. A. Jaberi, P. J. Colucci, S. James, P. Givi, and S. B. Pope. Filtered mass density function for large eddy simulation of turbulent reacting flows. J. Fluid Mech., 401:85--121, 1999.

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

PubMed Central

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

2013-01-01

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

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

NASA Technical Reports Server (NTRS)

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

2016-01-01

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

A new Monte Carlo-based treatment plan optimization approach for intensity modulated radiation therapy.

PubMed

Li, Yongbao; Tian, Zhen; Shi, Feng; Song, Ting; Wu, Zhaoxia; Liu, Yaqiang; Jiang, Steve; Jia, Xun

2015-04-07

Intensity-modulated radiation treatment (IMRT) plan optimization needs beamlet dose distributions. Pencil-beam or superposition/convolution type algorithms are typically used because of their high computational speed. However, inaccurate beamlet dose distributions may mislead the optimization process and hinder the resulting plan quality. To solve this problem, the Monte Carlo (MC) simulation method has been used to compute all beamlet doses prior to the optimization step. The conventional approach samples the same number of particles from each beamlet. Yet this is not the optimal use of MC in this problem. In fact, there are beamlets that have very small intensities after solving the plan optimization problem. For those beamlets, it may be possible to use fewer particles in dose calculations to increase efficiency. Based on this idea, we have developed a new MC-based IMRT plan optimization framework that iteratively performs MC dose calculation and plan optimization. At each dose calculation step, the particle numbers for beamlets were adjusted based on the beamlet intensities obtained through solving the plan optimization problem in the last iteration step. We modified a GPU-based MC dose engine to allow simultaneous computations of a large number of beamlet doses. To test the accuracy of our modified dose engine, we compared the dose from a broad beam and the summed beamlet doses in this beam in an inhomogeneous phantom. Agreement within 1% for the maximum difference and 0.55% for the average difference was observed. We then validated the proposed MC-based optimization schemes in one lung IMRT case. It was found that the conventional scheme required 10(6) particles from each beamlet to achieve an optimization result that was 3% difference in fluence map and 1% difference in dose from the ground truth. In contrast, the proposed scheme achieved the same level of accuracy with on average 1.2 × 10(5) particles per beamlet. Correspondingly, the computation time including both MC dose calculations and plan optimizations was reduced by a factor of 4.4, from 494 to 113 s, using only one GPU card.

A Pseudorange Measurement Scheme Based on Snapshot for Base Station Positioning Receivers.

PubMed

Mo, Jun; Deng, Zhongliang; Jia, Buyun; Bian, Xinmei

2017-12-01

Digital multimedia broadcasting signal is promised to be a wireless positioning signal. This paper mainly studies a multimedia broadcasting technology, named China mobile multimedia broadcasting (CMMB), in the context of positioning. Theoretical and practical analysis on the CMMB signal suggests that the existing CMMB signal does not have the meter positioning capability. So, the CMMB system has been modified to achieve meter positioning capability by multiplexing the CMMB signal and pseudo codes in the same frequency band. The time difference of arrival (TDOA) estimation method is used in base station positioning receivers. Due to the influence of a complex fading channel and the limited bandwidth of receivers, the regular tracking method based on pseudo code ranging is difficult to provide continuous and accurate TDOA estimations. A pseudorange measurement scheme based on snapshot is proposed to solve the problem. This algorithm extracts the TDOA estimation from the stored signal fragments, and utilizes the Taylor expansion of the autocorrelation function to improve the TDOA estimation accuracy. Monte Carlo simulations and real data tests show that the proposed algorithm can significantly reduce the TDOA estimation error for base station positioning receivers, and then the modified CMMB system achieves meter positioning accuracy.

Pseudorange Measurement Method Based on AIS Signals.

PubMed

Zhang, Jingbo; Zhang, Shufang; Wang, Jinpeng

2017-05-22

In order to use the existing automatic identification system (AIS) to provide additional navigation and positioning services, a complete pseudorange measurements solution is presented in this paper. Through the mathematical analysis of the AIS signal, the bit-0-phases in the digital sequences were determined as the timestamps. Monte Carlo simulation was carried out to compare the accuracy of the zero-crossing and differential peak, which are two timestamp detection methods in the additive white Gaussian noise (AWGN) channel. Considering the low-speed and low-dynamic motion characteristics of ships, an optimal estimation method based on the minimum mean square error is proposed to improve detection accuracy. Furthermore, the α difference filter algorithm was used to achieve the fusion of the optimal estimation results of the two detection methods. The results show that the algorithm can greatly improve the accuracy of pseudorange estimation under low signal-to-noise ratio (SNR) conditions. In order to verify the effectiveness of the scheme, prototypes containing the measurement scheme were developed and field tests in Xinghai Bay of Dalian (China) were performed. The test results show that the pseudorange measurement accuracy was better than 28 m (σ) without any modification of the existing AIS system.

Pseudorange Measurement Method Based on AIS Signals

PubMed Central

Zhang, Jingbo; Zhang, Shufang; Wang, Jinpeng

2017-01-01

In order to use the existing automatic identification system (AIS) to provide additional navigation and positioning services, a complete pseudorange measurements solution is presented in this paper. Through the mathematical analysis of the AIS signal, the bit-0-phases in the digital sequences were determined as the timestamps. Monte Carlo simulation was carried out to compare the accuracy of the zero-crossing and differential peak, which are two timestamp detection methods in the additive white Gaussian noise (AWGN) channel. Considering the low-speed and low-dynamic motion characteristics of ships, an optimal estimation method based on the minimum mean square error is proposed to improve detection accuracy. Furthermore, the α difference filter algorithm was used to achieve the fusion of the optimal estimation results of the two detection methods. The results show that the algorithm can greatly improve the accuracy of pseudorange estimation under low signal-to-noise ratio (SNR) conditions. In order to verify the effectiveness of the scheme, prototypes containing the measurement scheme were developed and field tests in Xinghai Bay of Dalian (China) were performed. The test results show that the pseudorange measurement accuracy was better than 28 m (σ) without any modification of the existing AIS system. PMID:28531153

Censored quantile regression with recursive partitioning-based weights

PubMed Central

Wey, Andrew; Wang, Lan; Rudser, Kyle

2014-01-01

Censored quantile regression provides a useful alternative to the Cox proportional hazards model for analyzing survival data. It directly models the conditional quantile of the survival time and hence is easy to interpret. Moreover, it relaxes the proportionality constraint on the hazard function associated with the popular Cox model and is natural for modeling heterogeneity of the data. Recently, Wang and Wang (2009. Locally weighted censored quantile regression. Journal of the American Statistical Association 103, 1117–1128) proposed a locally weighted censored quantile regression approach that allows for covariate-dependent censoring and is less restrictive than other censored quantile regression methods. However, their kernel smoothing-based weighting scheme requires all covariates to be continuous and encounters practical difficulty with even a moderate number of covariates. We propose a new weighting approach that uses recursive partitioning, e.g. survival trees, that offers greater flexibility in handling covariate-dependent censoring in moderately high dimensions and can incorporate both continuous and discrete covariates. We prove that this new weighting scheme leads to consistent estimation of the quantile regression coefficients and demonstrate its effectiveness via Monte Carlo simulations. We also illustrate the new method using a widely recognized data set from a clinical trial on primary biliary cirrhosis. PMID:23975800

An Energy-Dispersive X-Ray Fluorescence Spectrometry and Monte Carlo simulation study of Iron-Age Nuragic small bronzes ("Navicelle") from Sardinia, Italy

NASA Astrophysics Data System (ADS)

Schiavon, Nick; de Palmas, Anna; Bulla, Claudio; Piga, Giampaolo; Brunetti, Antonio

2016-09-01

A spectrometric protocol combining Energy Dispersive X-Ray Fluorescence Spectrometry with Monte Carlo simulations of experimental spectra using the XRMC code package has been applied for the first time to characterize the elemental composition of a series of famous Iron Age small scale archaeological bronze replicas of ships (known as the ;Navicelle;) from the Nuragic civilization in Sardinia, Italy. The proposed protocol is a useful, nondestructive and fast analytical tool for Cultural Heritage sample. In Monte Carlo simulations, each sample was modeled as a multilayered object composed by two or three layers depending on the sample: when all present, the three layers are the original bronze substrate, the surface corrosion patina and an outermost protective layer (Paraloid) applied during past restorations. Monte Carlo simulations were able to account for the presence of the patina/corrosion layer as well as the presence of the Paraloid protective layer. It also accounted for the roughness effect commonly found at the surface of corroded metal archaeological artifacts. In this respect, the Monte Carlo simulation approach adopted here was, to the best of our knowledge, unique and enabled to determine the bronze alloy composition together with the thickness of the surface layers without the need for previously removing the surface patinas, a process potentially threatening preservation of precious archaeological/artistic artifacts for future generations.

A Monte Carlo simulation study of associated liquid crystals

NASA Astrophysics Data System (ADS)

Berardi, R.; Fehervari, M.; Zannoni, C.

We have performed a Monte Carlo simulation study of a system of ellipsoidal particles with donor-acceptor sites modelling complementary hydrogen-bonding groups in real molecules. We have considered elongated Gay-Berne particles with terminal interaction sites allowing particles to associate and form dimers. The changes in the phase transitions and in the molecular organization and the interplay between orientational ordering and dimer formation are discussed. Particle flip and dimer moves have been used to increase the convergency rate of the Monte Carlo (MC) Markov chain.

Sensitivity analysis as an aid in modelling and control of (poorly-defined) ecological systems. [closed ecological systems

NASA Technical Reports Server (NTRS)

Hornberger, G. M.; Rastetter, E. B.

1982-01-01

A literature review of the use of sensitivity analyses in modelling nonlinear, ill-defined systems, such as ecological interactions is presented. Discussions of previous work, and a proposed scheme for generalized sensitivity analysis applicable to ill-defined systems are included. This scheme considers classes of mathematical models, problem-defining behavior, analysis procedures (especially the use of Monte-Carlo methods), sensitivity ranking of parameters, and extension to control system design.

Accurate Monte Carlo simulations for nozzle design, commissioning and quality assurance for a proton radiation therapy facility.

PubMed

Paganetti, H; Jiang, H; Lee, S Y; Kooy, H M

2004-07-01

Monte Carlo dosimetry calculations are essential methods in radiation therapy. To take full advantage of this tool, the beam delivery system has to be simulated in detail and the initial beam parameters have to be known accurately. The modeling of the beam delivery system itself opens various areas where Monte Carlo calculations prove extremely helpful, such as for design and commissioning of a therapy facility as well as for quality assurance verification. The gantry treatment nozzles at the Northeast Proton Therapy Center (NPTC) at Massachusetts General Hospital (MGH) were modeled in detail using the GEANT4.5.2 Monte Carlo code. For this purpose, various novel solutions for simulating irregular shaped objects in the beam path, like contoured scatterers, patient apertures or patient compensators, were found. The four-dimensional, in time and space, simulation of moving parts, such as the modulator wheel, was implemented. Further, the appropriate physics models and cross sections for proton therapy applications were defined. We present comparisons between measured data and simulations. These show that by modeling the treatment nozzle with millimeter accuracy, it is possible to reproduce measured dose distributions with an accuracy in range and modulation width, in the case of a spread-out Bragg peak (SOBP), of better than 1 mm. The excellent agreement demonstrates that the simulations can even be used to generate beam data for commissioning treatment planning systems. The Monte Carlo nozzle model was used to study mechanical optimization in terms of scattered radiation and secondary radiation in the design of the nozzles. We present simulations on the neutron background. Further, the Monte Carlo calculations supported commissioning efforts in understanding the sensitivity of beam characteristics and how these influence the dose delivered. We present the sensitivity of dose distributions in water with respect to various beam parameters and geometrical misalignments. This allows the definition of tolerances for quality assurance and the design of quality assurance procedures.

Cosmic ray air shower characteristics in the framework of the parton-based Gribov-Regge model NEXUS

NASA Astrophysics Data System (ADS)

Bossard, G.; Drescher, H. J.; Kalmykov, N. N.; Ostapchenko, S.; Pavlov, A. I.; Pierog, T.; Vishnevskaya, E. A.; Werner, K.

2001-03-01

The purpose of this paper is twofold: first we want to introduce a new type of hadronic interaction model (NEXUS), which has a much more solid theoretical basis than, for example, presently used models such as QGSJET and VENUS, and ensures therefore a much more reliable extrapolation towards high energies. Secondly, we want to promote an extensive air shower (EAS) calculation scheme, based on cascade equations rather than explicit Monte Carlo simulations, which is very accurate in calculations of main EAS characteristics and extremely fast concerning computing time. We employ the NEXUS model to provide the necessary data on particle production in hadron-air collisions and present the average EAS characteristics for energies 1014-1017 eV. The experimental data of the CASA-BLANCA group are analyzed in the framework of the new model.

Discrete velocity computations with stochastic variance reduction of the Boltzmann equation for gas mixtures

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

Clarke, Peter; Varghese, Philip; Goldstein, David

We extend a variance reduced discrete velocity method developed at UT Austin [1, 2] to gas mixtures with large mass ratios and flows with trace species. The mixture is stored as a collection of independent velocity distribution functions, each with a unique grid in velocity space. Different collision types (A-A, A-B, B-B, etc.) are treated independently, and the variance reduction scheme is formulated with different equilibrium functions for each separate collision type. The individual treatment of species enables increased focus on species important to the physics of the flow, even if the important species are present in trace amounts. Themore » method is verified through comparisons to Direct Simulation Monte Carlo computations and the computational workload per time step is investigated for the variance reduced method.« less

[Cost-effectiveness analysis of an alternative for the provision of primary health care for beneficiaries of Seguro Popular in Mexico].

PubMed

Figueroa-Lara, Alejandro; González-Block, Miguel A

2016-01-01

To estimate the cost-effectiveness ratio of public and private health care providers funded by Seguro Popular. A pilot contracting primary care health care scheme in the state of Hidalgo, Mexico, was evaluated through a population survey to assess quality of care and detection decreased of vision. Costs were assessed from the payer perspective using institutional sources.The alternatives analyzed were a private provider with capitated and performance-based payment modalities, and a public provider funded through budget subsidies. Sensitivity analysis was performed using Monte Carlo simulations. The private provider is dominant in the quality and cost-effective detection of decreased vision. Strategic purchasing of private providers of primary care has shown promising results as an alternative to improving quality of health services and reducing costs.

Jet energy resolution in proton-proton collisions at $$\\sqrt{\\mathrm{s}}=7\\mbox{ TeV}$$ recorded in 2010 with the ATLAS detector

DOE PAGES

Aad, G.; Abajyan, T.; Abbott, B.; ...

2013-03-02

The measurement of the jet energy resolution is presented using data recorded with the ATLAS detector in proton-proton collisions at √ s = 7 TeV. The sample corresponds to an integrated luminosity of 35 pb -1. Jets are reconstructed from energy deposits measured by the calorimeters and calibrated using different jet calibration schemes. The jet energy resolution is measured with two different in situ methods which are found to be in agreement within uncertainties. The total uncertainties on these measurements range from 20 % to 10 % for jets within |y| < 2.8 and with transverse momenta increasing from 30more » GeV to 500 GeV. Overall, the Monte Carlo simulation of the jet energy resolution agrees with the data within 10 %.« less

Jet energy resolution in proton-proton collisions at [Formula: see text] recorded in 2010 with the ATLAS detector.

PubMed

Aad, G; Abajyan, T; Abbott, B; Abdallah, J; Abdel Khalek, S; Abdelalim, A A; Abdinov, O; Aben, R; Abi, B; Abolins, M; AbouZeid, O S; Abramowicz, H; Abreu, H; Acerbi, E; Acharya, B S; Adamczyk, L; Adams, D L; Addy, T N; Adelman, J; Adomeit, S; Adragna, P; Adye, T; Aefsky, S; Aguilar-Saavedra, J A; Agustoni, M; Aharrouche, M; Ahlen, S P; Ahles, F; Ahmad, A; Ahsan, M; Aielli, G; Akdogan, T; Åkesson, T P A; Akimoto, G; Akimov, A V; Alam, M S; Alam, M A; Albert, J; Albrand, S; Aleksa, M; Aleksandrov, I N; Alessandria, F; Alexa, C; Alexander, G; Alexandre, G; Alexopoulos, T; Alhroob, M; Aliev, M; Alimonti, G; Alison, J; Allbrooke, B M M; Allport, P P; Allwood-Spiers, S E; Almond, J; Aloisio, A; Alon, R; Alonso, A; Alonso, F; Alvarez Gonzalez, B; Alviggi, M G; Amako, K; Amelung, C; Ammosov, V V; Amorim, A; Amram, N; Anastopoulos, C; Ancu, L S; Andari, N; Andeen, T; Anders, C F; Anders, G; Anderson, K J; Andreazza, A; Andrei, V; Anduaga, X S; Anger, P; Angerami, A; Anghinolfi, F; Anisenkov, A; 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Cwetanski, P; Czirr, H; Czodrowski, P; Czyczula, Z; D'Auria, S; D'Onofrio, M; D'Orazio, A; Da Cunha Sargedas De Sousa, M J; Da Via, C; Dabrowski, W; Dafinca, A; Dai, T; Dallapiccola, C; Dam, M; Dameri, M; Damiani, D S; Danielsson, H O; Dao, V; Darbo, G; Darlea, G L; Dassoulas, J A; Davey, W; Davidek, T; Davidson, N; Davidson, R; Davies, E; Davies, M; Davignon, O; Davison, A R; Davygora, Y; Dawe, E; Dawson, I; Daya-Ishmukhametova, R K; De, K; de Asmundis, R; De Castro, S; De Cecco, S; de Graat, J; De Groot, N; de Jong, P; De La Taille, C; De la Torre, H; De Lorenzi, F; de Mora, L; De Nooij, L; De Pedis, D; De Salvo, A; De Sanctis, U; De Santo, A; De Vivie De Regie, J B; De Zorzi, G; Dearnaley, W J; Debbe, R; Debenedetti, C; Dechenaux, B; Dedovich, D V; Degenhardt, J; Del Papa, C; Del Peso, J; Del Prete, T; Delemontex, T; Deliyergiyev, M; Dell'Acqua, A; Dell'Asta, L; Della Pietra, M; Della Volpe, D; Delmastro, M; Delsart, P A; Deluca, C; Demers, S; Demichev, M; Demirkoz, B; Deng, J; Denisov, S P; 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Serfon, C; Serin, L; Serkin, L; Seuster, R; Severini, H; Sfyrla, A; Shabalina, E; Shamim, M; Shan, L Y; Shank, J T; Shao, Q T; Shapiro, M; Shatalov, P B; Shaw, K; Sherman, D; Sherwood, P; Shibata, A; Shimizu, S; Shimojima, M; Shin, T; Shiyakova, M; Shmeleva, A; Shochet, M J; Short, D; Shrestha, S; Shulga, E; Shupe, M A; Sicho, P; Sidoti, A; Siegert, F; Sijacki, Dj; Silbert, O; Silva, J; Silver, Y; Silverstein, D; Silverstein, S B; Simak, V; Simard, O; Simic, Lj; Simion, S; Simioni, E; Simmons, B; Simoniello, R; Simonyan, M; Sinervo, P; Sinev, N B; Sipica, V; Siragusa, G; Sircar, A; Sisakyan, A N; Sivoklokov, S Yu; Sjölin, J; Sjursen, T B; Skinnari, L A; Skottowe, H P; Skovpen, K; Skubic, P; Slater, M; Slavicek, T; Sliwa, K; Smakhtin, V; Smart, B H; Smirnov, S Yu; Smirnov, Y; Smirnova, L N; Smirnova, O; Smith, B C; Smith, D; Smith, K M; Smizanska, M; Smolek, K; Snesarev, A A; Snow, S W; Snow, J; Snyder, S; Sobie, R; Sodomka, J; Soffer, A; Solans, C A; Solar, M; Solc, J; Soldatov, E Yu; Soldevila, U; Solfaroli Camillocci, E; Solodkov, A A; Solovyanov, O V; Solovyev, V; Soni, N; Sopko, V; Sopko, B; Sosebee, M; Soualah, R; Soukharev, A; Spagnolo, S; Spanò, F; Spighi, R; Spigo, G; Spiwoks, R; Spousta, M; Spreitzer, T; Spurlock, B; St Denis, R D; Stahlman, J; Stamen, R; Stanecka, E; Stanek, R W; Stanescu, C; Stanescu-Bellu, M; Stapnes, S; Starchenko, E A; Stark, J; Staroba, P; Starovoitov, P; Staszewski, R; Staude, A; Stavina, P; Steele, G; Steinbach, P; Steinberg, P; Stekl, I; Stelzer, B; Stelzer, H J; Stelzer-Chilton, O; Stenzel, H; Stern, S; Stewart, G A; Stillings, J A; Stockton, M C; Stoerig, K; Stoicea, G; Stonjek, S; Strachota, P; Stradling, A R; Straessner, A; Strandberg, J; Strandberg, S; Strandlie, A; Strang, M; Strauss, E; Strauss, M; Strizenec, P; Ströhmer, R; Strom, D M; Strong, J A; Stroynowski, R; Strube, J; Stugu, B; Stumer, I; Stupak, J; Sturm, P; Styles, N A; Soh, D A; Su, D; Subramania, Hs; Succurro, A; Sugaya, Y; Suhr, C; Suk, M; Sulin, V V; Sultansoy, S; Sumida, T; Sun, X; Sundermann, J E; Suruliz, K; Susinno, G; Sutton, M R; Suzuki, Y; Suzuki, Y; Svatos, M; Swedish, S; Sykora, I; Sykora, T; Sánchez, J; Ta, D; Tackmann, K; Taffard, A; Tafirout, R; Taiblum, N; Takahashi, Y; Takai, H; Takashima, R; Takeda, H; Takeshita, T; Takubo, Y; Talby, M; Talyshev, A; Tamsett, M C; Tanaka, J; Tanaka, R; Tanaka, S; Tanaka, S; Tanasijczuk, A J; Tani, K; Tannoury, N; Tapprogge, S; Tardif, D; Tarem, S; Tarrade, F; Tartarelli, G F; Tas, P; Tasevsky, M; Tassi, E; Tatarkhanov, M; Tayalati, Y; Taylor, C; Taylor, F E; Taylor, G N; Taylor, W; Teinturier, M; Teixeira Dias Castanheira, M; Teixeira-Dias, P; Temming, K K; Ten Kate, H; Teng, P K; Terada, S; Terashi, K; Terron, J; Testa, M; Teuscher, R J; Therhaag, J; Theveneaux-Pelzer, T; Thoma, S; Thomas, J P; Thompson, E N; Thompson, P D; Thompson, P D; Thompson, A S; Thomsen, L A; Thomson, E; Thomson, M; Thong, W M; Thun, R P; Tian, F; Tibbetts, M J; Tic, T; Tikhomirov, V O; Tikhonov, Y A; Timoshenko, S; Tipton, P; Tisserant, S; Todorov, T; Todorova-Nova, S; Toggerson, B; Tojo, J; Tokár, S; Tokushuku, K; Tollefson, K; Tomoto, M; Tompkins, L; Toms, K; Tonoyan, A; Topfel, C; Topilin, N D; Torchiani, I; Torrence, E; Torres, H; Torró Pastor, E; Toth, J; Touchard, F; Tovey, D R; Trefzger, T; Tremblet, L; Tricoli, A; Trigger, I M; Trincaz-Duvoid, S; Tripiana, M F; Triplett, N; Trischuk, W; Trocmé, B; Troncon, C; Trottier-McDonald, M; Trzebinski, M; Trzupek, A; Tsarouchas, C; Tseng, J C-L; Tsiakiris, M; Tsiareshka, P V; Tsionou, D; Tsipolitis, G; Tsiskaridze, S; Tsiskaridze, V; Tskhadadze, E G; Tsukerman, I I; Tsulaia, V; Tsung, J-W; Tsuno, S; Tsybychev, D; Tua, A; Tudorache, A; Tudorache, V; Tuggle, J M; Turala, M; Turecek, D; Turk Cakir, I; Turlay, E; Turra, R; Tuts, P M; Tykhonov, A; Tylmad, M; Tyndel, M; Tzanakos, G; Uchida, K; Ueda, I; Ueno, R; Ugland, M; Uhlenbrock, M; Uhrmacher, M; Ukegawa, F; Unal, G; Undrus, A; Unel, G; Unno, Y; Urbaniec, D; Usai, G; Uslenghi, M; Vacavant, L; Vacek, V; Vachon, B; Vahsen, S; Valenta, J; Valentinetti, S; Valero, A; Valkar, S; Valladolid Gallego, E; Vallecorsa, S; Valls Ferrer, J A; Van Der Deijl, P C; van der Geer, R; van der Graaf, H; Van Der Leeuw, R; van der Poel, E; van der Ster, D; van Eldik, N; van Gemmeren, P; van Vulpen, I; Vanadia, M; Vandelli, W; Vaniachine, A; Vankov, P; Vannucci, F; Vari, R; Varol, T; Varouchas, D; Vartapetian, A; Varvell, K E; Vassilakopoulos, V I; Vazeille, F; Vazquez Schroeder, T; Vegni, G; Veillet, J J; Veloso, F; Veness, R; Veneziano, S; Ventura, A; Ventura, D; Venturi, M; Venturi, N; Vercesi, V; Verducci, M; Verkerke, W; Vermeulen, J C; Vest, A; Vetterli, M C; Vichou, I; Vickey, T; Vickey Boeriu, O E; Viehhauser, G H A; Viel, S; Villa, M; Villaplana Perez, M; Vilucchi, E; Vincter, M G; Vinek, E; Vinogradov, V B; Virchaux, M; Virzi, J; Vitells, O; Viti, M; Vivarelli, I; Vives Vaque, F; Vlachos, S; Vladoiu, D; Vlasak, M; Vogel, A; Vokac, P; Volpi, G; Volpi, M; Volpini, G; von der Schmitt, H; von Radziewski, H; von Toerne, E; 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Zenz, S; Zerwas, D; Zevi Della Porta, G; Zhan, Z; Zhang, D; Zhang, H; Zhang, J; Zhang, X; Zhang, Z; Zhao, L; Zhao, T; Zhao, Z; Zhemchugov, A; Zhong, J; Zhou, B; Zhou, N; Zhou, Y; Zhu, C G; Zhu, H; Zhu, J; Zhu, Y; Zhuang, X; Zhuravlov, V; Zieminska, D; Zimin, N I; Zimmermann, R; Zimmermann, S; Zimmermann, S; Ziolkowski, M; Zitoun, R; Živković, L; Zmouchko, V V; Zobernig, G; Zoccoli, A; Zur Nedden, M; Zutshi, V; Zwalinski, L

The measurement of the jet energy resolution is presented using data recorded with the ATLAS detector in proton-proton collisions at [Formula: see text]. The sample corresponds to an integrated luminosity of 35 pb -1 . Jets are reconstructed from energy deposits measured by the calorimeters and calibrated using different jet calibration schemes. The jet energy resolution is measured with two different in situ methods which are found to be in agreement within uncertainties. The total uncertainties on these measurements range from 20 % to 10 % for jets within | y |<2.8 and with transverse momenta increasing from 30 GeV to 500 GeV. Overall, the Monte Carlo simulation of the jet energy resolution agrees with the data within 10 %.

Impact of different parameterization schemes on simulation of mesoscale convective system over south-east India

NASA Astrophysics Data System (ADS)

Madhulatha, A.; Rajeevan, M.

2018-02-01

Main objective of the present paper is to examine the role of various parameterization schemes in simulating the evolution of mesoscale convective system (MCS) occurred over south-east India. Using the Weather Research and Forecasting (WRF) model, numerical experiments are conducted by considering various planetary boundary layer, microphysics, and cumulus parameterization schemes. Performances of different schemes are evaluated by examining boundary layer, reflectivity, and precipitation features of MCS using ground-based and satellite observations. Among various physical parameterization schemes, Mellor-Yamada-Janjic (MYJ) boundary layer scheme is able to produce deep boundary layer height by simulating warm temperatures necessary for storm initiation; Thompson (THM) microphysics scheme is capable to simulate the reflectivity by reasonable distribution of different hydrometeors during various stages of system; Betts-Miller-Janjic (BMJ) cumulus scheme is able to capture the precipitation by proper representation of convective instability associated with MCS. Present analysis suggests that MYJ, a local turbulent kinetic energy boundary layer scheme, which accounts strong vertical mixing; THM, a six-class hybrid moment microphysics scheme, which considers number concentration along with mixing ratio of rain hydrometeors; and BMJ, a closure cumulus scheme, which adjusts thermodynamic profiles based on climatological profiles might have contributed for better performance of respective model simulations. Numerical simulation carried out using the above combination of schemes is able to capture storm initiation, propagation, surface variations, thermodynamic structure, and precipitation features reasonably well. This study clearly demonstrates that the simulation of MCS characteristics is highly sensitive to the choice of parameterization schemes.

Raman Monte Carlo simulation for light propagation for tissue with embedded objects

NASA Astrophysics Data System (ADS)

Periyasamy, Vijitha; Jaafar, Humaira Bte; Pramanik, Manojit

2018-02-01

Monte Carlo (MC) stimulation is one of the prominent simulation technique and is rapidly becoming the model of choice to study light-tissue interaction. Monte Carlo simulation for light transport in multi-layered tissue (MCML) is adapted and modelled with different geometry by integrating embedded objects of various shapes (i.e., sphere, cylinder, cuboid and ellipsoid) into the multi-layered structure. These geometries would be useful in providing a realistic tissue structure such as modelling for lymph nodes, tumors, blood vessels, head and other simulation medium. MC simulations were performed on various geometric medium. Simulation of MCML with embedded object (MCML-EO) was improvised for propagation of the photon in the defined medium with Raman scattering. The location of Raman photon generation is recorded. Simulations were experimented on a modelled breast tissue with tumor (spherical and ellipsoidal) and blood vessels (cylindrical). Results were presented in both A-line and B-line scans for embedded objects to determine spatial location where Raman photons were generated. Studies were done for different Raman probabilities.

Applying Monte-Carlo simulations to optimize an inelastic neutron scattering system for soil carbon analysis

USDA-ARS?s Scientific Manuscript database

Computer Monte-Carlo (MC) simulations (Geant4) of neutron propagation and acquisition of gamma response from soil samples was applied to evaluate INS system performance characteristic [sensitivity, minimal detectable level (MDL)] for soil carbon measurement. The INS system model with best performanc...

Play It Again: Teaching Statistics with Monte Carlo Simulation

ERIC Educational Resources Information Center

Sigal, Matthew J.; Chalmers, R. Philip

2016-01-01

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

Monte Carlo simulation of MOSFET dosimeter for electron backscatter using the GEANT4 code.

PubMed

Chow, James C L; Leung, Michael K K

2008-06-01

The aim of this study is to investigate the influence of the body of the metal-oxide-semiconductor field effect transistor (MOSFET) dosimeter in measuring the electron backscatter from lead. The electron backscatter factor (EBF), which is defined as the ratio of dose at the tissue-lead interface to the dose at the same point without the presence of backscatter, was calculated by the Monte Carlo simulation using the GEANT4 code. Electron beams with energies of 4, 6, 9, and 12 MeV were used in the simulation. It was found that in the presence of the MOSFET body, the EBFs were underestimated by about 2%-0.9% for electron beam energies of 4-12 MeV, respectively. The trend of the decrease of EBF with an increase of electron energy can be explained by the small MOSFET dosimeter, mainly made of epoxy and silicon, not only attenuated the electron fluence of the electron beam from upstream, but also the electron backscatter generated by the lead underneath the dosimeter. However, this variation of the EBF underestimation is within the same order of the statistical uncertainties as the Monte Carlo simulations, which ranged from 1.3% to 0.8% for the electron energies of 4-12 MeV, due to the small dosimetric volume. Such small EBF deviation is therefore insignificant when the uncertainty of the Monte Carlo simulation is taken into account. Corresponding measurements were carried out and uncertainties compared to Monte Carlo results were within +/- 2%. Spectra of energy deposited by the backscattered electrons in dosimetric volumes with and without the lead and MOSFET were determined by Monte Carlo simulations. It was found that in both cases, when the MOSFET body is either present or absent in the simulation, deviations of electron energy spectra with and without the lead decrease with an increase of the electron beam energy. Moreover, the softer spectrum of the backscattered electron when lead is present can result in a reduction of the MOSFET response due to stronger recombination in the SiO2 gate. It is concluded that the MOSFET dosimeter performed well for measuring the electron backscatter from lead using electron beams. The uncertainty of EBF determined by comparing the results of Monte Carlo simulations and measurements is well within the accuracy of the MOSFET dosimeter (< +/- 4.2%) provided by the manufacturer.

Environmental performance evaluation of large-scale municipal solid waste incinerators using data envelopment analysis.

PubMed

Chen, Ho-Wen; Chang, Ni-Bin; Chen, Jeng-Chung; Tsai, Shu-Ju

2010-07-01

Limited to insufficient land resources, incinerators are considered in many countries such as Japan and Germany as the major technology for a waste management scheme capable of dealing with the increasing demand for municipal and industrial solid waste treatment in urban regions. The evaluation of these municipal incinerators in terms of secondary pollution potential, cost-effectiveness, and operational efficiency has become a new focus in the highly interdisciplinary area of production economics, systems analysis, and waste management. This paper aims to demonstrate the application of data envelopment analysis (DEA)--a production economics tool--to evaluate performance-based efficiencies of 19 large-scale municipal incinerators in Taiwan with different operational conditions. A 4-year operational data set from 2002 to 2005 was collected in support of DEA modeling using Monte Carlo simulation to outline the possibility distributions of operational efficiency of these incinerators. Uncertainty analysis using the Monte Carlo simulation provides a balance between simplifications of our analysis and the soundness of capturing the essential random features that complicate solid waste management systems. To cope with future challenges, efforts in the DEA modeling, systems analysis, and prediction of the performance of large-scale municipal solid waste incinerators under normal operation and special conditions were directed toward generating a compromised assessment procedure. Our research findings will eventually lead to the identification of the optimal management strategies for promoting the quality of solid waste incineration, not only in Taiwan, but also elsewhere in the world. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Comparison of Geant4-DNA simulation of S-values with other Monte Carlo codes

NASA Astrophysics Data System (ADS)

André, T.; Morini, F.; Karamitros, M.; Delorme, R.; Le Loirec, C.; Campos, L.; Champion, C.; Groetz, J.-E.; Fromm, M.; Bordage, M.-C.; Perrot, Y.; Barberet, Ph.; Bernal, M. A.; Brown, J. M. C.; Deleuze, M. S.; Francis, Z.; Ivanchenko, V.; Mascialino, B.; Zacharatou, C.; Bardiès, M.; Incerti, S.

2014-01-01

Monte Carlo simulations of S-values have been carried out with the Geant4-DNA extension of the Geant4 toolkit. The S-values have been simulated for monoenergetic electrons with energies ranging from 0.1 keV up to 20 keV, in liquid water spheres (for four radii, chosen between 10 nm and 1 μm), and for electrons emitted by five isotopes of iodine (131, 132, 133, 134 and 135), in liquid water spheres of varying radius (from 15 μm up to 250 μm). The results have been compared to those obtained from other Monte Carlo codes and from other published data. The use of the Kolmogorov-Smirnov test has allowed confirming the statistical compatibility of all simulation results.

Monte Carlo method for photon heating using temperature-dependent optical properties.

PubMed

Slade, Adam Broadbent; Aguilar, Guillermo

2015-02-01

The Monte Carlo method for photon transport is often used to predict the volumetric heating that an optical source will induce inside a tissue or material. This method relies on constant (with respect to temperature) optical properties, specifically the coefficients of scattering and absorption. In reality, optical coefficients are typically temperature-dependent, leading to error in simulation results. The purpose of this study is to develop a method that can incorporate variable properties and accurately simulate systems where the temperature will greatly vary, such as in the case of laser-thawing of frozen tissues. A numerical simulation was developed that utilizes the Monte Carlo method for photon transport to simulate the thermal response of a system that allows temperature-dependent optical and thermal properties. This was done by combining traditional Monte Carlo photon transport with a heat transfer simulation to provide a feedback loop that selects local properties based on current temperatures, for each moment in time. Additionally, photon steps are segmented to accurately obtain path lengths within a homogenous (but not isothermal) material. Validation of the simulation was done using comparisons to established Monte Carlo simulations using constant properties, and a comparison to the Beer-Lambert law for temperature-variable properties. The simulation is able to accurately predict the thermal response of a system whose properties can vary with temperature. The difference in results between variable-property and constant property methods for the representative system of laser-heated silicon can become larger than 100K. This simulation will return more accurate results of optical irradiation absorption in a material which undergoes a large change in temperature. This increased accuracy in simulated results leads to better thermal predictions in living tissues and can provide enhanced planning and improved experimental and procedural outcomes. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

A comparison of Monte-Carlo simulations using RESTRAX and McSTAS with experiment on IN14

NASA Astrophysics Data System (ADS)

Wildes, A. R.; S̆aroun, J.; Farhi, E.; Anderson, I.; Høghøj, P.; Brochier, A.

2000-03-01

Monte-Carlo simulations of a focusing supermirror guide after the monochromator on the IN14 cold neutron three-axis spectrometer, I.L.L. were carried out using the instrument simulation programs RESTRAX and McSTAS. The simulations were compared to experiment to check their accuracy. Comparisons of the flux ratios over both a 100 and a 1600 mm 2 area at the sample position compare well, and there is a very close agreement between simulation and experiment for the energy spread of the incident beam.

Applying Monte Carlo Simulation to Launch Vehicle Design and Requirements Analysis

NASA Technical Reports Server (NTRS)

Hanson, J. M.; Beard, B. B.

2010-01-01

This Technical Publication (TP) is meant to address a number of topics related to the application of Monte Carlo simulation to launch vehicle design and requirements analysis. Although the focus is on a launch vehicle application, the methods may be applied to other complex systems as well. The TP is organized so that all the important topics are covered in the main text, and detailed derivations are in the appendices. The TP first introduces Monte Carlo simulation and the major topics to be discussed, including discussion of the input distributions for Monte Carlo runs, testing the simulation, how many runs are necessary for verification of requirements, what to do if results are desired for events that happen only rarely, and postprocessing, including analyzing any failed runs, examples of useful output products, and statistical information for generating desired results from the output data. Topics in the appendices include some tables for requirements verification, derivation of the number of runs required and generation of output probabilistic data with consumer risk included, derivation of launch vehicle models to include possible variations of assembled vehicles, minimization of a consumable to achieve a two-dimensional statistical result, recontact probability during staging, ensuring duplicated Monte Carlo random variations, and importance sampling.

Investigation of nonlinear motion simulator washout schemes

NASA Technical Reports Server (NTRS)

Riedel, S. A.; Hofmann, L. G.

1978-01-01

An overview is presented of some of the promising washout schemes which have been devised. The four schemes presented fall into two basic configurations; crossfeed and crossproduct. Various nonlinear modifications further differentiate the four schemes. One nonlinear scheme is discussed in detail. This washout scheme takes advantage of subliminal motions to speed up simulator cab centering. It exploits so-called perceptual indifference thresholds to center the simulator cab at a faster rate whenever the input to the simulator is below the perceptual indifference level. The effect is to reduce the angular and translational simulation motion by comparison with that for the linear washout case. Finally, the conclusions and implications for further research in the area of nonlinear washout filters are presented.

The effect of carrier gas flow rate and source cell temperature on low pressure organic vapor phase deposition simulation by direct simulation Monte Carlo method

PubMed Central

Wada, Takao; Ueda, Noriaki

2013-01-01

The process of low pressure organic vapor phase deposition (LP-OVPD) controls the growth of amorphous organic thin films, where the source gases (Alq3 molecule, etc.) are introduced into a hot wall reactor via an injection barrel using an inert carrier gas (N2 molecule). It is possible to control well the following substrate properties such as dopant concentration, deposition rate, and thickness uniformity of the thin film. In this paper, we present LP-OVPD simulation results using direct simulation Monte Carlo-Neutrals (Particle-PLUS neutral module) which is commercial software adopting direct simulation Monte Carlo method. By estimating properly the evaporation rate with experimental vaporization enthalpies, the calculated deposition rates on the substrate agree well with the experimental results that depend on carrier gas flow rate and source cell temperature. PMID:23674843

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.

A review: Functional near infrared spectroscopy evaluation in muscle tissues using Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Halim, A. A. A.; Laili, M. H.; Salikin, M. S.; Rusop, M.

2018-05-01

Monte Carlo Simulation has advanced their quantification based on number of the photon counting to solve the propagation of light inside the tissues including the absorption, scattering coefficient and act as preliminary study for functional near infrared application. The goal of this paper is to identify the optical properties using Monte Carlo simulation for non-invasive functional near infrared spectroscopy (fNIRS) evaluation of penetration depth in human muscle. This paper will describe the NIRS principle and the basis for its proposed used in Monte Carlo simulation which focused on several important parameters include ATP, ADP and relate with blow flow and oxygen content at certain exercise intensity. This will cover the advantages and limitation of such application upon this simulation. This result may help us to prove that our human muscle is transparent to this near infrared region and could deliver a lot of information regarding to the oxygenation level in human muscle. Thus, this might be useful for non-invasive technique for detecting oxygen status in muscle from living people either athletes or working people and allowing a lots of investigation muscle physiology in future.

Simulation of bipolar charge transport in nanocomposite polymer films

NASA Astrophysics Data System (ADS)

Lean, Meng H.; Chu, Wei-Ping L.

2015-03-01

This paper describes 3D particle-in-cell simulation of bipolar charge injection and transport through nanocomposite film comprised of ferroelectric ceramic nanofillers in an amorphous polymer matrix. The classical electrical double layer (EDL) model for a monopolar core is extended (eEDL) to represent the nanofiller by replacing it with a dipolar core. Charge injection at the electrodes assumes metal-polymer Schottky emission at low to moderate fields and Fowler-Nordheim tunneling at high fields. Injected particles migrate via field-dependent Poole-Frenkel mobility and recombine with Monte Carlo selection. The simulation algorithm uses a boundary integral equation method for solution of the Poisson equation coupled with a second-order predictor-corrector scheme for robust time integration of the equations of motion. The stability criterion of the explicit algorithm conforms to the Courant-Friedrichs-Levy limit assuring robust and rapid convergence. The model is capable of simulating a wide dynamic range spanning leakage current to pre-breakdown. Simulation results for BaTiO3 nanofiller in amorphous polymer matrix indicate that charge transport behavior depend on nanoparticle polarization with anti-parallel orientation showing the highest leakage conduction and therefore lowest level of charge trapping in the interaction zone. Charge recombination is also highest, at the cost of reduced leakage conduction charge. The eEDL model predicts the meandering pathways of charge particle trajectories.

Result of Monte-Carlo simulation of electron-photon cascades in lead and layers of lead-scintillator

NASA Technical Reports Server (NTRS)

Wasilewski, A.; Krys, E.

1985-01-01

Results of Monte-Carlo simulation of electromagnetic cascade development in lead and lead-scintillator sandwiches are analyzed. It is demonstrated that the structure function for core approximation is not applicable in the case in which the primary energy is higher than 100 GeV. The simulation data has shown that introducing an inhomogeneous chamber structure results in subsequent reduction of secondary particles.

Interactive three-dimensional visualization and creation of geometries for Monte Carlo calculations

NASA Astrophysics Data System (ADS)

Theis, C.; Buchegger, K. H.; Brugger, M.; Forkel-Wirth, D.; Roesler, S.; Vincke, H.

2006-06-01

The implementation of three-dimensional geometries for the simulation of radiation transport problems is a very time-consuming task. Each particle transport code supplies its own scripting language and syntax for creating the geometries. All of them are based on the Constructive Solid Geometry scheme requiring textual description. This makes the creation a tedious and error-prone task, which is especially hard to master for novice users. The Monte Carlo code FLUKA comes with built-in support for creating two-dimensional cross-sections through the geometry and FLUKACAD, a custom-built converter to the commercial Computer Aided Design package AutoCAD, exists for 3D visualization. For other codes, like MCNPX, a couple of different tools are available, but they are often specifically tailored to the particle transport code and its approach used for implementing geometries. Complex constructive solid modeling usually requires very fast and expensive special purpose hardware, which is not widely available. In this paper SimpleGeo is presented, which is an implementation of a generic versatile interactive geometry modeler using off-the-shelf hardware. It is running on Windows, with a Linux version currently under preparation. This paper describes its functionality, which allows for rapid interactive visualization as well as generation of three-dimensional geometries, and also discusses critical issues regarding common CAD systems.

An accurate, compact and computationally efficient representation of orbitals for quantum Monte Carlo calculations

NASA Astrophysics Data System (ADS)

Luo, Ye; Esler, Kenneth; Kent, Paul; Shulenburger, Luke

Quantum Monte Carlo (QMC) calculations of giant molecules, surface and defect properties of solids have been feasible recently due to drastically expanding computational resources. However, with the most computationally efficient basis set, B-splines, these calculations are severely restricted by the memory capacity of compute nodes. The B-spline coefficients are shared on a node but not distributed among nodes, to ensure fast evaluation. A hybrid representation which incorporates atomic orbitals near the ions and B-spline ones in the interstitial regions offers a more accurate and less memory demanding description of the orbitals because they are naturally more atomic like near ions and much smoother in between, thus allowing coarser B-spline grids. We will demonstrate the advantage of hybrid representation over pure B-spline and Gaussian basis sets and also show significant speed-up like computing the non-local pseudopotentials with our new scheme. Moreover, we discuss a new algorithm for atomic orbital initialization which used to require an extra workflow step taking a few days. With this work, the highly efficient hybrid representation paves the way to simulate large size even in-homogeneous systems using QMC. This work was supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Computational Materials Sciences Program.

Assessment of radiation exposure in dental cone-beam computerized tomography with the use of metal-oxide semiconductor field-effect transistor (MOSFET) dosimeters and Monte Carlo simulations.

PubMed

Koivisto, J; Kiljunen, T; Tapiovaara, M; Wolff, J; Kortesniemi, M

2012-09-01

The aims of this study were to assess the organ and effective dose (International Commission on Radiological Protection (ICRP) 103) resulting from dental cone-beam computerized tomography (CBCT) imaging using a novel metal-oxide semiconductor field-effect transistor (MOSFET) dosimeter device, and to assess the reliability of the MOSFET measurements by comparing the results with Monte Carlo PCXMC simulations. Organ dose measurements were performed using 20 MOSFET dosimeters that were embedded in the 8 most radiosensitive organs in the maxillofacial and neck area. The dose-area product (DAP) values attained from CBCT scans were used for PCXMC simulations. The acquired MOSFET doses were then compared with the Monte Carlo simulations. The effective dose measurements using MOSFET dosimeters yielded, using 0.5-cm steps, a value of 153 μSv and the PCXMC simulations resulted in a value of 136 μSv. The MOSFET dosimeters placed in a head phantom gave results similar to Monte Carlo simulations. Minor vertical changes in the positioning of the phantom had a substantial affect on the overall effective dose. Therefore, the MOSFET dosimeters constitute a feasible method for dose assessment of CBCT units in the maxillofacial region. Copyright © 2012 Elsevier Inc. All rights reserved.

Multi-fidelity methods for uncertainty quantification in transport problems

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Contact radiotherapy using a 50 kV X-ray system: Evaluation of relative dose distribution with the Monte Carlo code PENELOPE and comparison with measurements

NASA Astrophysics Data System (ADS)

Croce, Olivier; Hachem, Sabet; Franchisseur, Eric; Marcié, Serge; Gérard, Jean-Pierre; Bordy, Jean-Marc

2012-06-01

This paper presents a dosimetric study concerning the system named "Papillon 50" used in the department of radiotherapy of the Centre Antoine-Lacassagne, Nice, France. The machine provides a 50 kVp X-ray beam, currently used to treat rectal cancers. The system can be mounted with various applicators of different diameters or shapes. These applicators can be fixed over the main rod tube of the unit in order to deliver the prescribed absorbed dose into the tumor with an optimal distribution. We have analyzed depth dose curves and dose profiles for the naked tube and for a set of three applicators. Dose measurements were made with an ionization chamber (PTW type 23342) and Gafchromic films (EBT2). We have also compared the measurements with simulations performed using the Monte Carlo code PENELOPE. Simulations were performed with a detailed geometrical description of the experimental setup and with enough statistics. Results of simulations are made in accordance with experimental measurements and provide an accurate evaluation of the dose delivered. The depths of the 50% isodose in water for the various applicators are 4.0, 6.0, 6.6 and 7.1 mm. The Monte Carlo PENELOPE simulations are in accordance with the measurements for a 50 kV X-ray system. Simulations are able to confirm the measurements provided by Gafchromic films or ionization chambers. Results also demonstrate that Monte Carlo simulations could be helpful to validate the future applicators designed for other localizations such as breast or skin cancers. Furthermore, Monte Carlo simulations could be a reliable alternative for a rapid evaluation of the dose delivered by such a system that uses multiple designs of applicators.

A Fast Monte Carlo Simulation for the International Linear Collider Detector

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

Furse, D.; /Georgia Tech

2005-12-15

The following paper contains details concerning the motivation for, implementation and performance of a Java-based fast Monte Carlo simulation for a detector designed to be used in the International Linear Collider. This simulation, presently included in the SLAC ILC group's org.lcsim package, reads in standard model or SUSY events in STDHEP file format, stochastically simulates the blurring in physics measurements caused by intrinsic detector error, and writes out an LCIO format file containing a set of final particles statistically similar to those that would have found by a full Monte Carlo simulation. In addition to the reconstructed particles themselves, descriptionsmore » of the calorimeter hit clusters and tracks that these particles would have produced are also included in the LCIO output. These output files can then be put through various analysis codes in order to characterize the effectiveness of a hypothetical detector at extracting relevant physical information about an event. Such a tool is extremely useful in preliminary detector research and development, as full simulations are extremely cumbersome and taxing on processor resources; a fast, efficient Monte Carlo can facilitate and even make possible detector physics studies that would be very impractical with the full simulation by sacrificing what is in many cases inappropriate attention to detail for valuable gains in time required for results.« less

Probabilistic approach of resource assessment in Kerinci geothermal field using numerical simulation coupling with monte carlo simulation

NASA Astrophysics Data System (ADS)

Hidayat, Iki; Sutopo; Pratama, Heru Berian

2017-12-01

The Kerinci geothermal field is one phase liquid reservoir system in the Kerinci District, western part of Jambi Province. In this field, there are geothermal prospects that identified by the heat source up flow inside a National Park area. Kerinci field was planned to develop 1×55 MWe by Pertamina Geothermal Energy. To define reservoir characterization, the numerical simulation of Kerinci field is developed by using TOUGH2 software with information from conceptual model. The pressure and temperature profile well data of KRC-B1 are validated with simulation data to reach natural state condition. The result of the validation is suitable matching. Based on natural state simulation, the resource assessment of Kerinci geothermal field is estimated by using Monte Carlo simulation with the result P10-P50-P90 are 49.4 MW, 64.3 MW and 82.4 MW respectively. This paper is the first study of resource assessment that has been estimated successfully in Kerinci Geothermal Field using numerical simulation coupling with Monte carlo simulation.

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

Energetic fluctuations in amorphous semiconducting polymers: Impact on charge-carrier mobility

NASA Astrophysics Data System (ADS)

Gali, Sai Manoj; D'Avino, Gabriele; Aurel, Philippe; Han, Guangchao; Yi, Yuanping; Papadopoulos, Theodoros A.; Coropceanu, Veaceslav; Brédas, Jean-Luc; Hadziioannou, Georges; Zannoni, Claudio; Muccioli, Luca

2017-10-01

We present a computational approach to model hole transport in an amorphous semiconducting fluorene-triphenylamine copolymer (TFB), which is based on the combination of molecular dynamics to predict the morphology of the oligomeric system and Kinetic Monte Carlo (KMC), parameterized with quantum chemistry calculations, to simulate hole transport. Carrying out a systematic comparison with available experimental results, we discuss the role that different transport parameters play in the KMC simulation and in particular the dynamic nature of positional and energetic disorder on the temperature and electric field dependence of charge mobility. It emerges that a semi-quantitative agreement with experiments is found only when the dynamic nature of the disorder is taken into account. This study establishes a clear link between microscopic quantities and macroscopic hole mobility for TFB and provides substantial evidence of the importance of incorporating fluctuations, at the molecular level, to obtain results that are in good agreement with temperature and electric field-dependent experimental mobilities. Our work makes a step forward towards the application of nanoscale theoretical schemes as a tool for predictive material screening.

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

NASA Astrophysics Data System (ADS)

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

2014-04-01

We introduce a theoretical framework for the calculation of uncertainties affecting observables produced by Monte Carlo particle transport, which derive from uncertainties in physical parameters input into simulation. The theoretical developments are complemented by a heuristic application, which illustrates the method of calculation in a streamlined simulation environment.

Quantum Monte Carlo Methods for First Principles Simulation of Liquid Water

ERIC Educational Resources Information Center

Gergely, John Robert

2009-01-01

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

Estimating Uncertainty in N2O Emissions from US Cropland Soils

USDA-ARS?s Scientific Manuscript database

A Monte Carlo analysis was combined with an empirically-based approach to quantify uncertainties in soil N2O emissions from US croplands estimated with the DAYCENT simulation model. Only a subset of croplands was simulated in the Monte Carlo analysis which was used to infer uncertainties across the ...

Testing the Intervention Effect in Single-Case Experiments: A Monte Carlo Simulation Study

ERIC Educational Resources Information Center

Heyvaert, Mieke; Moeyaert, Mariola; Verkempynck, Paul; Van den Noortgate, Wim; Vervloet, Marlies; Ugille, Maaike; Onghena, Patrick

2017-01-01

This article reports on a Monte Carlo simulation study, evaluating two approaches for testing the intervention effect in replicated randomized AB designs: two-level hierarchical linear modeling (HLM) and using the additive method to combine randomization test "p" values (RTcombiP). Four factors were manipulated: mean intervention effect,…

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…

Levofloxacin Penetration into Epithelial Lining Fluid as Determined by Population Pharmacokinetic Modeling and Monte Carlo Simulation

PubMed Central

Drusano, G. L.; Preston, S. L.; Gotfried, M. H.; Danziger, L. H.; Rodvold, K. A.

2002-01-01

Levofloxacin was administered orally to steady state to volunteers randomly in doses of 500 and 750 mg. Plasma and epithelial lining fluid (ELF) samples were obtained at 4, 12, and 24 h after the final dose. All data were comodeled in a population pharmacokinetic analysis employing BigNPEM. Penetration was evaluated from the population mean parameter vector values and from the results of a 1,000-subject Monte Carlo simulation. Evaluation from the population mean values demonstrated a penetration ratio (ELF/plasma) of 1.16. The Monte Carlo simulation provided a measure of dispersion, demonstrating a mean ratio of 3.18, with a median of 1.43 and a 95% confidence interval of 0.14 to 19.1. Population analysis with Monte Carlo simulation provides the best and least-biased estimate of penetration. It also demonstrates clearly that we can expect differences in penetration between patients. This analysis did not deal with inflammation, as it was performed in volunteers. The influence of lung pathology on penetration needs to be examined. PMID:11796385

Geant4 hadronic physics for space radiation environment.

PubMed

Ivantchenko, Anton V; Ivanchenko, Vladimir N; Molina, Jose-Manuel Quesada; Incerti, Sebastien L

2012-01-01

To test and to develop Geant4 (Geometry And Tracking version 4) Monte Carlo hadronic models with focus on applications in a space radiation environment. The Monte Carlo simulations have been performed using the Geant4 toolkit. Binary (BIC), its extension for incident light ions (BIC-ion) and Bertini (BERT) cascades were used as main Monte Carlo generators. For comparisons purposes, some other models were tested too. The hadronic testing suite has been used as a primary tool for model development and validation against experimental data. The Geant4 pre-compound (PRECO) and de-excitation (DEE) models were revised and improved. Proton, neutron, pion, and ion nuclear interactions were simulated with the recent version of Geant4 9.4 and were compared with experimental data from thin and thick target experiments. The Geant4 toolkit offers a large set of models allowing effective simulation of interactions of particles with matter. We have tested different Monte Carlo generators with our hadronic testing suite and accordingly we can propose an optimal configuration of Geant4 models for the simulation of the space radiation environment.

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

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

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

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

The development of novel simulation methodologies and intermolecular potential models for real fluids

NASA Astrophysics Data System (ADS)

Errington, Jeffrey Richard

This work focuses on the development of intermolecular potential models for real fluids. United-atom models have been developed for both non-polar and polar fluids. The models have been optimized to the vapor-liquid coexistence properties. Histogram reweighting techniques were used to calculate phase behavior. The Hamiltonian scaling grand canonical Monte Carlo method was developed to enable the determination of thermodynamic properties of several related Hamiltonians from a single simulation. With this method, the phase behavior of variations of the Buckingham exponential-6 potential was determined. Reservoir grand canonical Monte Carlo simulations were developed to simulate molecules with complex architectures and/or stiff intramolecular constraints. The scheme is based on the creation of a reservoir of ideal chains from which structures are selected for insertion during a simulation. New intermolecular potential models have been developed for water, the n-alkane homologous series, benzene, cyclohexane, carbon dioxide, ammonia and methanol. The models utilize the Buckingham exponential-6 potential to model non-polar interactions and point charges to describe polar interactions. With the exception of water, the new models reproduce experimental saturated densities, vapor pressures and critical parameters to within a few percent. In the case of water, we found a set of parameters that describes the phase behavior better than other available point charge models while giving a reasonable description of the liquid structure. The mixture behavior of water-hydrocarbon mixtures has also been examined. The Henry's law constants of methane, ethane, benzene and cyclohexane in water were determined using Widom insertion and expanded ensemble techniques. In addition the high-pressure phase behavior of water-methane and water-ethane systems was studied using the Gibbs ensemble method. The results from this study indicate that it is possible to obtain a good description of the phase behavior of pure components using united-atom models. The mixture behavior of non-polar systems, including highly asymmetric components, was in good agreement with experiment. The calculations for the highly non-ideal water-hydrocarbon mixtures reproduced experimental behavior with varying degrees of success. The results indicate that multibody effects, such as polarizability, must be taken into account when modeling mixtures of polar and non-polar components.

Window for Optimal Frequency Operation and Reliability of 3DEG and 2DEG Channels for Oxide Microwave MESFETs and HFETs

DTIC Science & Technology

2016-04-01

noise, and energy relaxation for doped zinc-oxide and structured ZnO transistor materials with a 2-D electron gas (2DEG) channel subjected to a strong...function on the time delay. Closed symbols represent the Monte Carlo data with hot-phonon effect at different electron gas density: 1•1017 cm-3...Monte Carlo simulation is performed for electron gas density of 1•1018 cm-3. Figure 18. Monte Carlo simulation of density-dependent hot-electron energy

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

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

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

2014-09-15

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

SU-E-T-586: Field Size Dependence of Output Factor for Uniform Scanning Proton Beams: A Comparison of TPS Calculation, Measurement and Monte Carlo Simulation

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

Zheng, Y; Singh, H; Islam, M

2014-06-01

Purpose: Output dependence on field size for uniform scanning beams, and the accuracy of treatment planning system (TPS) calculation are not well studied. The purpose of this work is to investigate the dependence of output on field size for uniform scanning beams and compare it among TPS calculation, measurements and Monte Carlo simulations. Methods: Field size dependence was studied using various field sizes between 2.5 cm diameter to 10 cm diameter. The field size factor was studied for a number of proton range and modulation combinations based on output at the center of spread out Bragg peak normalized to amore » 10 cm diameter field. Three methods were used and compared in this study: 1) TPS calculation, 2) ionization chamber measurement, and 3) Monte Carlos simulation. The XiO TPS (Electa, St. Louis) was used to calculate the output factor using a pencil beam algorithm; a pinpoint ionization chamber was used for measurements; and the Fluka code was used for Monte Carlo simulations. Results: The field size factor varied with proton beam parameters, such as range, modulation, and calibration depth, and could decrease over 10% from a 10 cm to 3 cm diameter field for a large range proton beam. The XiO TPS predicted the field size factor relatively well at large field size, but could differ from measurements by 5% or more for small field and large range beams. Monte Carlo simulations predicted the field size factor within 1.5% of measurements. Conclusion: Output factor can vary largely with field size, and needs to be accounted for accurate proton beam delivery. This is especially important for small field beams such as in stereotactic proton therapy, where the field size dependence is large and TPS calculation is inaccurate. Measurements or Monte Carlo simulations are recommended for output determination for such cases.« less

A measurement-based generalized source model for Monte Carlo dose simulations of CT scans

PubMed Central

Ming, Xin; Feng, Yuanming; Liu, Ransheng; Yang, Chengwen; Zhou, Li; Zhai, Hezheng; Deng, Jun

2018-01-01

The goal of this study is to develop a generalized source model (GSM) for accurate Monte Carlo dose simulations of CT scans based solely on the measurement data without a priori knowledge of scanner specifications. The proposed generalized source model consists of an extended circular source located at x-ray target level with its energy spectrum, source distribution and fluence distribution derived from a set of measurement data conveniently available in the clinic. Specifically, the central axis percent depth dose (PDD) curves measured in water and the cone output factors measured in air were used to derive the energy spectrum and the source distribution respectively with a Levenberg-Marquardt algorithm. The in-air film measurement of fan-beam dose profiles at fixed gantry was back-projected to generate the fluence distribution of the source model. A benchmarked Monte Carlo user code was used to simulate the dose distributions in water with the developed source model as beam input. The feasibility and accuracy of the proposed source model was tested on a GE LightSpeed and a Philips Brilliance Big Bore multi-detector CT (MDCT) scanners available in our clinic. In general, the Monte Carlo simulations of the PDDs in water and dose profiles along lateral and longitudinal directions agreed with the measurements within 4%/1mm for both CT scanners. The absolute dose comparison using two CTDI phantoms (16 cm and 32 cm in diameters) indicated a better than 5% agreement between the Monte Carlo-simulated and the ion chamber-measured doses at a variety of locations for the two scanners. Overall, this study demonstrated that a generalized source model can be constructed based only on a set of measurement data and used for accurate Monte Carlo dose simulations of patients’ CT scans, which would facilitate patient-specific CT organ dose estimation and cancer risk management in the diagnostic and therapeutic radiology. PMID:28079526

SU-F-T-657: In-Room Neutron Dose From High Energy Photon Beams

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

Christ, D; Ding, G

Purpose: To estimate neutron dose inside the treatment room from photodisintegration events in high energy photon beams using Monte Carlo simulations and experimental measurements. Methods: The Monte Carlo code MCNP6 was used for the simulations. An Eberline ESP-1 Smart Portable Neutron Detector was used to measure neutron dose. A water phantom was centered at isocenter on the treatment couch, and the detector was placed near the phantom. A Varian 2100EX linear accelerator delivered an 18MV open field photon beam to the phantom at 400MU/min, and a camera captured the detector readings. The experimental setup was modeled in the Monte Carlomore » simulation. The source was modeled for two extreme cases: a) hemispherical photon source emitting from the target and b) cone source with an angle of the primary collimator cone. The model includes the target, primary collimator, flattening filter, secondary collimators, water phantom, detector and concrete walls. Energy deposition tallies were measured for neutrons in the detector and for photons at the center of the phantom. Results: For an 18MV beam with an open 10cm by 10cm field and the gantry at 180°, the Monte Carlo simulations predict the neutron dose in the detector to be 0.11% of the photon dose in the water phantom for case a) and 0.01% for case b). The measured neutron dose is 0.04% of the photon dose. Considering the range of neutron dose predicted by Monte Carlo simulations, the calculated results are in good agreement with measurements. Conclusion: We calculated in-room neutron dose by using Monte Carlo techniques, and the predicted neutron dose is confirmed by experimental measurements. If we remodel the source as an electron beam hitting the target for a more accurate representation of the bremsstrahlung fluence, it is feasible that the Monte Carlo simulations can be used to help in shielding designs.« less

A measurement-based generalized source model for Monte Carlo dose simulations of CT scans

NASA Astrophysics Data System (ADS)

Ming, Xin; Feng, Yuanming; Liu, Ransheng; Yang, Chengwen; Zhou, Li; Zhai, Hezheng; Deng, Jun

2017-03-01

The goal of this study is to develop a generalized source model for accurate Monte Carlo dose simulations of CT scans based solely on the measurement data without a priori knowledge of scanner specifications. The proposed generalized source model consists of an extended circular source located at x-ray target level with its energy spectrum, source distribution and fluence distribution derived from a set of measurement data conveniently available in the clinic. Specifically, the central axis percent depth dose (PDD) curves measured in water and the cone output factors measured in air were used to derive the energy spectrum and the source distribution respectively with a Levenberg-Marquardt algorithm. The in-air film measurement of fan-beam dose profiles at fixed gantry was back-projected to generate the fluence distribution of the source model. A benchmarked Monte Carlo user code was used to simulate the dose distributions in water with the developed source model as beam input. The feasibility and accuracy of the proposed source model was tested on a GE LightSpeed and a Philips Brilliance Big Bore multi-detector CT (MDCT) scanners available in our clinic. In general, the Monte Carlo simulations of the PDDs in water and dose profiles along lateral and longitudinal directions agreed with the measurements within 4%/1 mm for both CT scanners. The absolute dose comparison using two CTDI phantoms (16 cm and 32 cm in diameters) indicated a better than 5% agreement between the Monte Carlo-simulated and the ion chamber-measured doses at a variety of locations for the two scanners. Overall, this study demonstrated that a generalized source model can be constructed based only on a set of measurement data and used for accurate Monte Carlo dose simulations of patients’ CT scans, which would facilitate patient-specific CT organ dose estimation and cancer risk management in the diagnostic and therapeutic radiology.

Elucidating the thermal, chemical, and mechanical mechanisms of ultraviolet ablation in poly(methyl methacrylate) via molecular dynamics simulations.

PubMed

Conforti, Patrick F; Prasad, Manish; Garrison, Barbara J

2008-08-01

[Figure: see text]. Laser ablation harnesses photon energy to remove material from a surface. Although applications such as laser-assisted in situ keratomileusis (LASIK) surgery, lithography, and nanoscale device fabrication take advantage of this process, a better understanding the underlying mechanism of ablation in polymeric materials remains much sought after. Molecular simulation is a particularly attractive technique to study the basic aspects of ablation because it allows control over specific process parameters and enables observation of microscopic mechanistic details. This Account describes a hybrid molecular dynamics-Monte Carlo technique to simulate laser ablation in poly(methyl methacrylate) (PMMA). It also discusses the impact of thermal and chemical excitation on the ensuing ejection processes. We used molecular dynamics simulation to study the molecular interactions in a coarse-grained PMMA substrate following photon absorption. To ascertain the role of chemistry in initiating ablation, we embedded a Monte Carlo protocol within the simulation framework. These calculations permit chemical reactions to occur probabilistically during the molecular dynamics calculation using predetermined reaction pathways and Arrhenius rates. With this hybrid scheme, we can examine thermal and chemical pathways of decomposition separately. In the simulations, we observed distinct mechanisms of ablation for each type of photoexcitation pathway. Ablation via thermal processes is governed by a critical number of bond breaks following the deposition of energy. For the case in which an absorbed photon directly causes a bond scission, ablation occurs following the rapid chemical decomposition of material. A detailed analysis of the processes shows that a critical energy for ablation can describe this complex series of events. The simulations show a decrease in the critical energy with a greater amount of photochemistry. Additionally, the simulations demonstrate the effects of the energy deposition rate on the ejection mechanism. When the energy is deposited rapidly, not allowing for mechanical relaxation of the sample, the formation of a pressure wave and subsequent tensile wave dominates the ejection process. This study provides insight into the influence of thermal, chemical, and mechanical processes in PMMA and facilitates greater understanding of the complex nature of polymer ablation. These simulations complement experiments that have used chemical design to harness the photochemical properties of materials to enhance laser ablation. We successfully fit the results of the simulations to established analytical models of both photothermal and photochemical ablation and demonstrate their relevance. Although the simulations are for PMMA, the mechanistic concepts are applicable to a large range of systems and provide a conceptual foundation for interpretation of experimental data.

LLNL Mercury Project Trinity Open Science Final Report

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

Brantley, Patrick; Dawson, Shawn; McKinley, Scott

2016-04-20

The Mercury Monte Carlo particle transport code developed at Lawrence Livermore National Laboratory (LLNL) is used to simulate the transport of radiation through urban environments. These challenging calculations include complicated geometries and require significant computational resources to complete. As a result, a question arises as to the level of convergence of the calculations with Monte Carlo simulation particle count. In the Trinity Open Science calculations, one main focus was to investigate convergence of the relevant simulation quantities with Monte Carlo particle count to assess the current simulation methodology. Both for this application space but also of more general applicability, wemore » also investigated the impact of code algorithms on parallel scaling on the Trinity machine as well as the utilization of the Trinity DataWarp burst buffer technology in Mercury via the LLNL Scalable Checkpoint/Restart (SCR) library.« less

Determining the Statistical Power of the Kolmogorov-Smirnov and Anderson-Darling Goodness-of-Fit Tests via Monte Carlo Simulation

DTIC Science & Technology

2016-12-01

KS and AD Statistical Power via Monte Carlo Simulation Statistical power is the probability of correctly rejecting the null hypothesis when the...Select a caveat DISTRIBUTION STATEMENT A. Approved for public release: distribution unlimited. Determining the Statistical Power...real-world data to test the accuracy of the simulation. Statistical comparison of these metrics can be necessary when making such a determination

Computer simulation of stochastic processes through model-sampling (Monte Carlo) techniques.

PubMed

Sheppard, C W.

1969-03-01

A simple Monte Carlo simulation program is outlined which can be used for the investigation of random-walk problems, for example in diffusion, or the movement of tracers in the blood circulation. The results given by the simulation are compared with those predicted by well-established theory, and it is shown how the model can be expanded to deal with drift, and with reflexion from or adsorption at a boundary.

Simulation of heavy precipitation episode over eastern Peninsular Malaysia using MM5: sensitivity to cumulus parameterization schemes

NASA Astrophysics Data System (ADS)

Salimun, Ester; Tangang, Fredolin; Juneng, Liew

2010-06-01

A comparative study has been conducted to investigate the skill of four convection parameterization schemes, namely the Anthes-Kuo (AK), the Betts-Miller (BM), the Kain-Fritsch (KF), and the Grell (GR) schemes in the numerical simulation of an extreme precipitation episode over eastern Peninsular Malaysia using the Pennsylvania State University—National Center for Atmospheric Research Center (PSU-NCAR) Fifth Generation Mesoscale Model (MM5). The event is a commonly occurring westward propagating tropical depression weather system during a boreal winter resulting from an interaction between a cold surge and the quasi-stationary Borneo vortex. The model setup and other physical parameterizations are identical in all experiments and hence any difference in the simulation performance could be associated with the cumulus parameterization scheme used. From the predicted rainfall and structure of the storm, it is clear that the BM scheme has an edge over the other schemes. The rainfall intensity and spatial distribution were reasonably well simulated compared to observations. The BM scheme was also better in resolving the horizontal and vertical structures of the storm. Most of the rainfall simulated by the BM simulation was of the convective type. The failure of other schemes (AK, GR and KF) in simulating the event may be attributed to the trigger function, closure assumption, and precipitation scheme. On the other hand, the appropriateness of the BM scheme for this episode may not be generalized for other episodes or convective environments.

Applying super-droplets as a compact representation of warm-rain microphysics for aerosol-cloud-aerosol interactions

NASA Astrophysics Data System (ADS)

Arabas, S.; Jaruga, A.; Pawlowska, H.; Grabowski, W. W.

2012-12-01

Clouds may influence aerosol characteristics of their environment. The relevant processes include wet deposition (rainout or washout) and cloud condensation nuclei (CCN) recycling through evaporation of cloud droplets and drizzle drops. Recycled CCN physicochemical properties may be altered if the evaporated droplets go through collisional growth or irreversible chemical reactions (e.g. SO2 oxidation). The key challenge of representing these processes in a numerical cloud model stems from the need to track properties of activated CCN throughout the cloud lifecycle. Lack of such "memory" characterises the so-called bulk, multi-moment as well as bin representations of cloud microphysics. In this study we apply the particle-based scheme of Shima et al. 2009. Each modelled particle (aka super-droplet) is a numerical proxy for a multiplicity of real-world CCN, cloud, drizzle or rain particles of the same size, nucleus type,and position. Tracking cloud nucleus properties is an inherent feature of the particle-based frameworks, making them suitable for studying aerosol-cloud-aerosol interactions. The super-droplet scheme is furthermore characterized by linear scalability in the number of computational particles, and no numerical diffusion in the condensational and in the Monte-Carlo type collisional growth schemes. The presentation will focus on processing of aerosol by a drizzling stratocumulus deck. The simulations are carried out using a 2D kinematic framework and a VOCALS experiment inspired set-up (see http://www.rap.ucar.edu/~gthompsn/workshop2012/case1/).

Diagnosing Undersampling Biases in Monte Carlo Eigenvalue and Flux Tally Estimates

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

Perfetti, Christopher M.; Rearden, Bradley T.; Marshall, William J.

2017-02-08

Here, this study focuses on understanding the phenomena in Monte Carlo simulations known as undersampling, in which Monte Carlo tally estimates may not encounter a sufficient number of particles during each generation to obtain unbiased tally estimates. Steady-state Monte Carlo simulations were performed using the KENO Monte Carlo tools within the SCALE code system for models of several burnup credit applications with varying degrees of spatial and isotopic complexities, and the incidence and impact of undersampling on eigenvalue and flux estimates were examined. Using an inadequate number of particle histories in each generation was found to produce a maximum bias of ~100 pcm in eigenvalue estimates and biases that exceeded 10% in fuel pin flux tally estimates. Having quantified the potential magnitude of undersampling biases in eigenvalue and flux tally estimates in these systems, this study then investigated whether Markov Chain Monte Carlo convergence metrics could be integrated into Monte Carlo simulations to predict the onset and magnitude of undersampling biases. Five potential metrics for identifying undersampling biases were implemented in the SCALE code system and evaluated for their ability to predict undersampling biases by comparing the test metric scores with the observed undersampling biases. Finally, of the five convergence metrics that were investigated, three (the Heidelberger-Welch relative half-width, the Gelman-Rubin more » $$\\hat{R}_c$$ diagnostic, and tally entropy) showed the potential to accurately predict the behavior of undersampling biases in the responses examined.« less

Use of Fluka to Create Dose Calculations

NASA Technical Reports Server (NTRS)

Lee, Kerry T.; Barzilla, Janet; Townsend, Lawrence; Brittingham, John

2012-01-01

Monte Carlo codes provide an effective means of modeling three dimensional radiation transport; however, their use is both time- and resource-intensive. The creation of a lookup table or parameterization from Monte Carlo simulation allows users to perform calculations with Monte Carlo results without replicating lengthy calculations. FLUKA Monte Carlo transport code was used to develop lookup tables and parameterizations for data resulting from the penetration of layers of aluminum, polyethylene, and water with areal densities ranging from 0 to 100 g/cm^2. Heavy charged ion radiation including ions from Z=1 to Z=26 and from 0.1 to 10 GeV/nucleon were simulated. Dose, dose equivalent, and fluence as a function of particle identity, energy, and scattering angle were examined at various depths. Calculations were compared against well-known results and against the results of other deterministic and Monte Carlo codes. Results will be presented.

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.

Influence of data collection schemes on the Life Cycle Assessment of a municipal wastewater treatment plant.

PubMed

Yoshida, Hiroko; Clavreul, Julie; Scheutz, Charlotte; Christensen, Thomas H

2014-06-01

A Life Cycle Assessment (LCA) of a municipal wastewater treatment plant (WWTP) was conducted to illustrate the effect of an emission inventory data collection scheme on the outcomes of an environmental impact assessment. Due to their burden in respect to data collection, LCAs often rely heavily on existing emission and operational data, which are gathered under either compulsory monitoring or reporting requirements under law. In this study, an LCA was conducted using three input data sources: Information compiled under compulsory disclosure requirements (the European Pollutant Release and Transfer Registry), compliance with national discharge limits, and a state-of-the-art emission data collection scheme conducted at the same WWTP. Parameter uncertainty for each collection scheme was assessed through Monte Carlo simulation. The comparison of the results confirmed that LCA results depend heavily on input data coverage. Due to the threshold on reporting value, the E-PRTR did not capture the impact for particulate matter emission, terrestrial acidification, or terrestrial eutrophication. While the current practice can capture more than 90% of non-carcinogenic human toxicity and marine eutrophication, an LCA based on the data collection scheme underestimates impact potential due to limitations of substance coverage. Besides differences between data collection schemes, the results showed that 3-13,500% of the impacts came from background systems, such as from the provisioning of fuel, electricity, and chemicals, which do not need to be disclosed currently under E-PRTR. The incidental release of pollutants was also assessed by employing a scenario-based approach, the results of which demonstrated that these non-routine emissions could increase overall WWTP greenhouse gas emissions by between 113 and 210%. Overall, current data collection schemes have the potential to provide standardized data collection and form the basis for a sound environmental impact assessment, but several improvements are recommended, including the additional collection of energy and chemical usage data, the elimination of a reporting threshold, the expansion of substance coverage, and the inclusion of non-point fugitive gas emissions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Optical roughness BRDF model for reverse Monte Carlo simulation of real material thermal radiation transfer.

PubMed

Su, Peiran; Eri, Qitai; Wang, Qiang

2014-04-10

Optical roughness was introduced into the bidirectional reflectance distribution function (BRDF) model to simulate the reflectance characteristics of thermal radiation. The optical roughness BRDF model stemmed from the influence of surface roughness and wavelength on the ray reflectance calculation. This model was adopted to simulate real metal emissivity. The reverse Monte Carlo method was used to display the distribution of reflectance rays. The numerical simulations showed that the optical roughness BRDF model can calculate the wavelength effect on emissivity and simulate the real metal emissivity variance with incidence angles.

Development of inorganic resists for electron beam lithography: Novel materials and simulations

NASA Astrophysics Data System (ADS)

Jeyakumar, Augustin

Electron beam lithography is gaining widespread utilization as the semiconductor industry progresses towards both advanced optical and non-optical lithographic technologies for high resolution patterning. The current resist technologies are based on organic systems that are imaged most commonly through chain scission, networking, or a chemically amplified polarity change in the material. Alternative resists based on inorganic systems were developed and characterized in this research for high resolution electron beam lithography and their interactions with incident electrons were investigated using Monte Carlo simulations. A novel inorganic resist imaging scheme was developed using metal-organic precursors which decompose to form metal oxides upon electron beam irradiation that can serve as inorganic hard masks for hybrid bilayer inorganic-organic imaging systems and also as directly patternable high resolution metal oxide structures. The electron beam imaging properties of these metal-organic materials were correlated to the precursor structure by studying effects such as interactions between high atomic number species and the incident electrons. Optimal single and multicomponent precursors were designed for utilization as viable inorganic resist materials for sub-50nm patterning in electron beam lithography. The electron beam imaging characteristics of the most widely used inorganic resist material, hydrogen silsesquioxane (HSQ), was also enhanced using a dual processing imaging approach with thermal curing as well as a sensitizer catalyzed imaging approach. The interaction between incident electrons and the high atomic number species contained in these inorganic resists was also studied using Monte Carlo simulations. The resolution attainable using inorganic systems as compared to organic systems can be greater for accelerating voltages greater than 50 keV due to minimized lateral scattering in the high density inorganic systems. The effects of loading nanoparticles in an electron beam resist was also investigated using a newly developed hybrid Monte Carlo approach that accounts for multiple components in a solid film. The resolution of the nanocomposite resist process was found to degrade with increasing nanoparticle loading. Finally, the electron beam patterning of self-assembled monolayers, which were found to primarily utilize backscattered electrons from the high atomic number substrate materials to form images, was also investigated and characterized. It was found that backscattered electrons limit the resolution attainable at low incident electron energies.

Poisson regression models outperform the geometrical model in estimating the peak-to-trough ratio of seasonal variation: a simulation study.

PubMed

Christensen, A L; Lundbye-Christensen, S; Dethlefsen, C

2011-12-01

Several statistical methods of assessing seasonal variation are available. Brookhart and Rothman [3] proposed a second-order moment-based estimator based on the geometrical model derived by Edwards [1], and reported that this estimator is superior in estimating the peak-to-trough ratio of seasonal variation compared with Edwards' estimator with respect to bias and mean squared error. Alternatively, seasonal variation may be modelled using a Poisson regression model, which provides flexibility in modelling the pattern of seasonal variation and adjustments for covariates. Based on a Monte Carlo simulation study three estimators, one based on the geometrical model, and two based on log-linear Poisson regression models, were evaluated in regards to bias and standard deviation (SD). We evaluated the estimators on data simulated according to schemes varying in seasonal variation and presence of a secular trend. All methods and analyses in this paper are available in the R package Peak2Trough[13]. Applying a Poisson regression model resulted in lower absolute bias and SD for data simulated according to the corresponding model assumptions. Poisson regression models had lower bias and SD for data simulated to deviate from the corresponding model assumptions than the geometrical model. This simulation study encourages the use of Poisson regression models in estimating the peak-to-trough ratio of seasonal variation as opposed to the geometrical model. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

A Monte Carlo Simulation of Brownian Motion in the Freshman Laboratory

ERIC Educational Resources Information Center

Anger, C. D.; Prescott, J. R.

1970-01-01

Describes a dry- lab" experiment for the college freshman laboratory, in which the essential features of Browian motion are given principles, using the Monte Carlo technique. Calculations principles, using the Monte Carlo technique. Calculations are carried out by a computation sheme based on computer language. Bibliography. (LC)

Grand canonical ensemble Monte Carlo simulation of the dCpG/proflavine crystal hydrate.

PubMed

Resat, H; Mezei, M

1996-09-01

The grand canonical ensemble Monte Carlo molecular simulation method is used to investigate hydration patterns in the crystal hydrate structure of the dCpG/proflavine intercalated complex. The objective of this study is to show by example that the recently advocated grand canonical ensemble simulation is a computationally efficient method for determining the positions of the hydrating water molecules in protein and nucleic acid structures. A detailed molecular simulation convergence analysis and an analogous comparison of the theoretical results with experiments clearly show that the grand ensemble simulations can be far more advantageous than the comparable canonical ensemble simulations.

TU-H-207A-02: Relative Importance of the Various Factors Influencing the Accuracy of Monte Carlo Simulated CT Dose Index

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

Marous, L; Muryn, J; Liptak, C

2016-06-15

Purpose: Monte Carlo simulation is a frequently used technique for assessing patient dose in CT. The accuracy of a Monte Carlo program is often validated using the standard CT dose index (CTDI) phantoms by comparing simulated and measured CTDI{sub 100}. To achieve good agreement, many input parameters in the simulation (e.g., energy spectrum and effective beam width) need to be determined. However, not all the parameters have equal importance. Our aim was to assess the relative importance of the various factors that influence the accuracy of simulated CTDI{sub 100}. Methods: A Monte Carlo program previously validated for a clinical CTmore » system was used to simulate CTDI{sub 100}. For the standard CTDI phantoms (32 and 16 cm in diameter), CTDI{sub 100} values from central and four peripheral locations at 70 and 120 kVp were first simulated using a set of reference input parameter values (treated as the truth). To emulate the situation in which the input parameter values used by the researcher may deviate from the truth, additional simulations were performed in which intentional errors were introduced into the input parameters, the effects of which on simulated CTDI{sub 100} were analyzed. Results: At 38.4-mm collimation, errors in effective beam width up to 5.0 mm showed negligible effects on simulated CTDI{sub 100} (<1.0%). Likewise, errors in acrylic density of up to 0.01 g/cm{sup 3} resulted in small CTDI{sub 100} errors (<2.5%). In contrast, errors in spectral HVL produced more significant effects: slight deviations (±0.2 mm Al) produced errors up to 4.4%, whereas more extreme deviations (±1.4 mm Al) produced errors as high as 25.9%. Lastly, ignoring the CT table introduced errors up to 13.9%. Conclusion: Monte Carlo simulated CTDI{sub 100} is insensitive to errors in effective beam width and acrylic density. However, they are sensitive to errors in spectral HVL. To obtain accurate results, the CT table should not be ignored. This work was supported by a Faculty Research and Development Award from Cleveland State University.« less

Sensitivity experiments of a regional climate model to the different convective schemes over Central Africa

NASA Astrophysics Data System (ADS)

Armand J, K. M.

2017-12-01

In this study, version 4 of the regional climate model (RegCM4) is used to perform 6 years simulation including one year for spin-up (from January 2001 to December 2006) over Central Africa using four convective schemes: The Emmanuel scheme (MIT), the Grell scheme with Arakawa-Schulbert closure assumption (GAS), the Grell scheme with Fritsch-Chappell closure assumption (GFC) and the Anthes-Kuo scheme (Kuo). We have investigated the ability of the model to simulate precipitation, surface temperature, wind and aerosols optical depth. Emphasis in the model results were made in December-January-February (DJF) and July-August-September (JAS) periods. Two subregions have been identified for more specific analysis namely: zone 1 which corresponds to the sahel region mainly classified as desert and steppe and zone 2 which is a region spanning the tropical rain forest and is characterised by a bimodal rain regime. We found that regardless of periods or simulated parameters, MIT scheme generally has a tendency to overestimate. The GAS scheme is more suitable in simulating the aforementioned parameters, as well as the diurnal cycle of precipitations everywhere over the study domain irrespective of the season. In JAS, model results are similar in the representation of regional wind circulation. Apart from the MIT scheme, all the convective schemes give the same trends in aerosols optical depth simulations. Additional experiment reveals that the use of BATS instead of Zeng scheme to calculate ocean flux appears to improve the quality of the model simulations.

APS undulator and wiggler sources: Monte-Carlo simulation

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

Xu, S.L.; Lai, B.; Viccaro, P.J.

1992-02-01

Standard insertion devices will be provided to each sector by the Advanced Photon Source. It is important to define the radiation characteristics of these general purpose devices. In this document,results of Monte-Carlo simulation are presented. These results, based on the SHADOW program, include the APS Undulator A (UA), Wiggler A (WA), and Wiggler B (WB).

Markov Chain Monte Carlo Estimation of Item Parameters for the Generalized Graded Unfolding Model

ERIC Educational Resources Information Center

de la Torre, Jimmy; Stark, Stephen; Chernyshenko, Oleksandr S.

2006-01-01

The authors present a Markov Chain Monte Carlo (MCMC) parameter estimation procedure for the generalized graded unfolding model (GGUM) and compare it to the marginal maximum likelihood (MML) approach implemented in the GGUM2000 computer program, using simulated and real personality data. In the simulation study, test length, number of response…

A systematic framework for Monte Carlo simulation of remote sensing errors map in carbon assessments

Treesearch

S. Healey; P. Patterson; S. Urbanski

2014-01-01

Remotely sensed observations can provide unique perspective on how management and natural disturbance affect carbon stocks in forests. However, integration of these observations into formal decision support will rely upon improved uncertainty accounting. Monte Carlo (MC) simulations offer a practical, empirical method of accounting for potential remote sensing errors...

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

NASA Astrophysics Data System (ADS)

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

1995-05-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Monte Carlo source simulation technique for solution of interference reactions in INAA experiments: a preliminary report

NASA Astrophysics Data System (ADS)

Allaf, M. Athari; Shahriari, M.; Sohrabpour, M.

2004-04-01

A new method using Monte Carlo source simulation of interference reactions in neutron activation analysis experiments has been developed. The neutron spectrum at the sample location has been simulated using the Monte Carlo code MCNP and the contributions of different elements to produce a specified gamma line have been determined. The produced response matrix has been used to measure peak areas and the sample masses of the elements of interest. A number of benchmark experiments have been performed and the calculated results verified against known values. The good agreement obtained between the calculated and known values suggests that this technique may be useful for the elimination of interference reactions in neutron activation analysis.