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Sample records for carlo simulation model

  1. Quantum Monte Carlo Simulations of Correlated-Electron Models

    NASA Astrophysics Data System (ADS)

    Zhang, Shiwei

    1996-05-01

    We briefly review quantum Monte Carlo simulation methods for strongly correlated fermion systems and the well-known ``sign'' problem that plagues these methods. We then discuss recent efforts to overcome the problem in the context of simulations of lattice models of electron correlations. In particular, we describe a new algorithm^1, called the constrained path Monte Carlo (CPMC), for studying ground-state (T=0K) properties. It has the form of a random walk in a space of mean-field solutions (Slater determinants); the exponential decay of ``sign'' or signal-to-noise ratio is eliminated by constraining the paths of the random walk according to a known trial wave function. Applications of this algorithm to the Hubbard model have enabled accurate and systematic studies of correlation functions, including s- and d-wave pairings, and hence the long-standing problem of the model's relevance to superconductivity. The method is directly applicable to a variety of other models important to understand high-Tc superconductors and heavy-fermion compounds. In addition, it is expected to be useful to simulations of nuclei, atoms, molecules, and solids. We also comment on possible extensions of the algorithm to finite-temperature calculations. Work supported in part by the Department of Energy's High Performance Computing and Communication Program at Los Alamos National Laboratory, and at OSU by DOE-Basic Energy Sciences, Division of Materials Sciences. ^1 Shiwei Zhang, J. Carlson, and J. E. Gubernatis, Phys. Rev. Lett. 74, 3652 (1995).

  2. Modeling and Computer Simulation: Molecular Dynamics and Kinetic Monte Carlo

    SciTech Connect

    Wirth, B.D.; Caturla, M.J.; Diaz de la Rubia, T.

    2000-10-10

    Recent years have witnessed tremendous advances in the realistic multiscale simulation of complex physical phenomena, such as irradiation and aging effects of materials, made possible by the enormous progress achieved in computational physics for calculating reliable, yet tractable interatomic potentials and the vast improvements in computational power and parallel computing. As a result, computational materials science is emerging as an important complement to theory and experiment to provide fundamental materials science insight. This article describes the atomistic modeling techniques of molecular dynamics (MD) and kinetic Monte Carlo (KMC), and an example of their application to radiation damage production and accumulation in metals. It is important to note at the outset that the primary objective of atomistic computer simulation should be obtaining physical insight into atomic-level processes. Classical molecular dynamics is a powerful method for obtaining insight about the dynamics of physical processes that occur on relatively short time scales. Current computational capability allows treatment of atomic systems containing as many as 10{sup 9} atoms for times on the order of 100 ns (10{sup -7}s). The main limitation of classical MD simulation is the relatively short times accessible. Kinetic Monte Carlo provides the ability to reach macroscopic times by modeling diffusional processes and time-scales rather than individual atomic vibrations. Coupling MD and KMC has developed into a powerful, multiscale tool for the simulation of radiation damage in metals.

  3. Applications for a fast Monte Carlo model for Lidar simulations

    NASA Astrophysics Data System (ADS)

    Buras, R.; Mayer, B.

    2009-04-01

    Lidars have the means to probe a multitude of components of the atmosphere with fairly exact spacial precision. However, in order to correctly retrieve atmospheric observables it is necessary to take into account geometrical effects as well as the contribution of multiply scattered photons. Thus retrieval algorithms need thorough validation by an exact model. In particular, physical or geometrical effects not taken into account by, or approximated in the retrieval algorithm must be proven to be unimportant, or correctly approximated. To this end I present a fast yet exact Lidar simulator based on the Monte Carlo method. The simulator is part of the Monte Carlo solver MYSTIC contained in the libRadtran software package. The Lidar simulator can be applied to several types of Lidars, such as HSRL (e.g. EarthCare), trace gas detectors (e.g. A-Scope), and wide angle Lidars (e.g. WAIL) for space- and air-borne Lidars as well as ground Lidars.

  4. Modelling laser light propagation in thermoplastics using Monte Carlo simulations

    NASA Astrophysics Data System (ADS)

    Parkinson, Alexander

    Laser welding has great potential as a fast, non-contact joining method for thermoplastic parts. In the laser transmission welding of thermoplastics, light passes through a semi-transparent part to reach the weld interface. There, it is absorbed as heat, which causes melting and subsequent welding. The distribution and quantity of light reaching the interface are important for predicting the quality of a weld, but are experimentally difficult to estimate. A model for simulating the path of this laser light through these light-scattering plastic parts has been developed. The technique uses a Monte-Carlo approach to generate photon paths through the material, accounting for absorption, scattering and reflection between boundaries in the transparent polymer. It was assumed that any light escaping the bottom surface contributed to welding. The photon paths are then scaled according to the input beam profile in order to simulate non-Gaussian beam profiles. A method for determining the 3 independent optical parameters to accurately predict transmission and beam power distribution at the interface was established using experimental data for polycarbonate at 4 different glass fibre concentrations and polyamide-6 reinforced with 20% long glass fibres. Exit beam profiles and transmissions predicted by the simulation were found to be in generally good agreement (R2>0.90) with experimental measurements. The simulations allowed the prediction of transmission and power distributions at other thicknesses as well as information on reflection, energy absorption and power distributions at other thicknesses for these materials.

  5. Monte Carlo simulations of lattice models for single polymer systems

    SciTech Connect

    Hsu, Hsiao-Ping

    2014-10-28

    Single linear polymer chains in dilute solutions under good solvent conditions are studied by Monte Carlo simulations with the pruned-enriched Rosenbluth method up to the chain length N∼O(10{sup 4}). Based on the standard simple cubic lattice model (SCLM) with fixed bond length and the bond fluctuation model (BFM) with bond lengths in a range between 2 and √(10), we investigate the conformations of polymer chains described by self-avoiding walks on the simple cubic lattice, and by random walks and non-reversible random walks in the absence of excluded volume interactions. In addition to flexible chains, we also extend our study to semiflexible chains for different stiffness controlled by a bending potential. The persistence lengths of chains extracted from the orientational correlations are estimated for all cases. We show that chains based on the BFM are more flexible than those based on the SCLM for a fixed bending energy. The microscopic differences between these two lattice models are discussed and the theoretical predictions of scaling laws given in the literature are checked and verified. Our simulations clarify that a different mapping ratio between the coarse-grained models and the atomistically realistic description of polymers is required in a coarse-graining approach due to the different crossovers to the asymptotic behavior.

  6. Optimizing Muscle Parameters in Musculoskeletal Modeling Using Monte Carlo Simulations

    NASA Technical Reports Server (NTRS)

    Hanson, Andrea; Reed, Erik; Cavanagh, Peter

    2011-01-01

    Astronauts assigned to long-duration missions experience bone and muscle atrophy in the lower limbs. The use of musculoskeletal simulation software has become a useful tool for modeling joint and muscle forces during human activity in reduced gravity as access to direct experimentation is limited. Knowledge of muscle and joint loads can better inform the design of exercise protocols and exercise countermeasure equipment. In this study, the LifeModeler(TM) (San Clemente, CA) biomechanics simulation software was used to model a squat exercise. The initial model using default parameters yielded physiologically reasonable hip-joint forces. However, no activation was predicted in some large muscles such as rectus femoris, which have been shown to be active in 1-g performance of the activity. Parametric testing was conducted using Monte Carlo methods and combinatorial reduction to find a muscle parameter set that more closely matched physiologically observed activation patterns during the squat exercise. Peak hip joint force using the default parameters was 2.96 times body weight (BW) and increased to 3.21 BW in an optimized, feature-selected test case. The rectus femoris was predicted to peak at 60.1% activation following muscle recruitment optimization, compared to 19.2% activation with default parameters. These results indicate the critical role that muscle parameters play in joint force estimation and the need for exploration of the solution space to achieve physiologically realistic muscle activation.

  7. Monte Carlo simulations of lattice models for single polymer systems

    NASA Astrophysics Data System (ADS)

    Hsu, Hsiao-Ping

    2014-10-01

    Single linear polymer chains in dilute solutions under good solvent conditions are studied by Monte Carlo simulations with the pruned-enriched Rosenbluth method up to the chain length N ˜ O(10^4). Based on the standard simple cubic lattice model (SCLM) with fixed bond length and the bond fluctuation model (BFM) with bond lengths in a range between 2 and sqrt{10}, we investigate the conformations of polymer chains described by self-avoiding walks on the simple cubic lattice, and by random walks and non-reversible random walks in the absence of excluded volume interactions. In addition to flexible chains, we also extend our study to semiflexible chains for different stiffness controlled by a bending potential. The persistence lengths of chains extracted from the orientational correlations are estimated for all cases. We show that chains based on the BFM are more flexible than those based on the SCLM for a fixed bending energy. The microscopic differences between these two lattice models are discussed and the theoretical predictions of scaling laws given in the literature are checked and verified. Our simulations clarify that a different mapping ratio between the coarse-grained models and the atomistically realistic description of polymers is required in a coarse-graining approach due to the different crossovers to the asymptotic behavior.

  8. Monte Carlo simulations of lattice models for single polymer systems.

    PubMed

    Hsu, Hsiao-Ping

    2014-10-28

    Single linear polymer chains in dilute solutions under good solvent conditions are studied by Monte Carlo simulations with the pruned-enriched Rosenbluth method up to the chain length N~O(10(4)). Based on the standard simple cubic lattice model (SCLM) with fixed bond length and the bond fluctuation model (BFM) with bond lengths in a range between 2 and √10, we investigate the conformations of polymer chains described by self-avoiding walks on the simple cubic lattice, and by random walks and non-reversible random walks in the absence of excluded volume interactions. In addition to flexible chains, we also extend our study to semiflexible chains for different stiffness controlled by a bending potential. The persistence lengths of chains extracted from the orientational correlations are estimated for all cases. We show that chains based on the BFM are more flexible than those based on the SCLM for a fixed bending energy. The microscopic differences between these two lattice models are discussed and the theoretical predictions of scaling laws given in the literature are checked and verified. Our simulations clarify that a different mapping ratio between the coarse-grained models and the atomistically realistic description of polymers is required in a coarse-graining approach due to the different crossovers to the asymptotic behavior. PMID:25362337

  9. Improving light propagation Monte Carlo simulations with accurate 3D modeling of skin tissue

    SciTech Connect

    Paquit, Vincent C; Price, Jeffery R; Meriaudeau, Fabrice; Tobin Jr, Kenneth William

    2008-01-01

    In this paper, we present a 3D light propagation model to simulate multispectral reflectance images of large skin surface areas. In particular, we aim to simulate more accurately the effects of various physiological properties of the skin in the case of subcutaneous vein imaging compared to existing models. Our method combines a Monte Carlo light propagation model, a realistic three-dimensional model of the skin using parametric surfaces and a vision system for data acquisition. We describe our model in detail, present results from the Monte Carlo modeling and compare our results with those obtained with a well established Monte Carlo model and with real skin reflectance images.

  10. Modeling root-reinforcement with a Fiber-Bundle Model and Monte Carlo simulation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This paper uses sensitivity analysis and a Fiber-Bundle Model (FBM) to examine assumptions underpinning root-reinforcement models. First, different methods for apportioning load between intact roots were investigated. Second, a Monte Carlo approach was used to simulate plants with heartroot, platero...

  11. Monte Carlo simulation of classical spin models with chaotic billiards

    NASA Astrophysics Data System (ADS)

    Suzuki, Hideyuki

    2013-11-01

    It has recently been shown that the computing abilities of Boltzmann machines, or Ising spin-glass models, can be implemented by chaotic billiard dynamics without any use of random numbers. In this paper, we further numerically investigate the capabilities of the chaotic billiard dynamics as a deterministic alternative to random Monte Carlo methods by applying it to classical spin models in statistical physics. First, we verify that the billiard dynamics can yield samples that converge to the true distribution of the Ising model on a small lattice, and we show that it appears to have the same convergence rate as random Monte Carlo sampling. Second, we apply the billiard dynamics to finite-size scaling analysis of the critical behavior of the Ising model and show that the phase-transition point and the critical exponents are correctly obtained. Third, we extend the billiard dynamics to spins that take more than two states and show that it can be applied successfully to the Potts model. We also discuss the possibility of extensions to continuous-valued models such as the XY model.

  12. The simulation of radar and coherent backscattering with the Monte Carlo model MYSTIC

    NASA Astrophysics Data System (ADS)

    Pause, Christian; Buras, Robert; Emde, Claudia; Mayer, Bernhard

    2013-05-01

    A new method to simulate radar and coherent backscattering within the framework of the 3D Monte Carlo radiative transfer model MYSTIC has been developed. Simulating radar is solved with the help of the already existing lidar simulator. Therefore the larger part of this paper presents a solution to simulate coherent backscattering and shows a comparison to a real case.

  13. Modeling of hysteresis loops by Monte Carlo simulation

    NASA Astrophysics Data System (ADS)

    Nehme, Z.; Labaye, Y.; Sayed Hassan, R.; Yaacoub, N.; Greneche, J. M.

    2015-12-01

    Recent advances in MC simulations of magnetic properties are rather devoted to non-interacting systems or ultrafast phenomena, while the modeling of quasi-static hysteresis loops of an assembly of spins with strong internal exchange interactions remains limited to specific cases. In the case of any assembly of magnetic moments, we propose MC simulations on the basis of a three dimensional classical Heisenberg model applied to an isolated magnetic slab involving first nearest neighbors exchange interactions and uniaxial anisotropy. Three different algorithms were successively implemented in order to simulate hysteresis loops: the classical free algorithm, the cone algorithm and a mixed one consisting of adding some global rotations. We focus particularly our study on the impact of varying the anisotropic constant parameter on the coercive field for different temperatures and algorithms. A study of the angular acceptation move distribution allows the dynamics of our simulations to be characterized. The results reveal that the coercive field is linearly related to the anisotropy providing that the algorithm and the numeric conditions are carefully chosen. In a general tendency, it is found that the efficiency of the simulation can be greatly enhanced by using the mixed algorithm that mimic the physics of collective behavior. Consequently, this study lead as to better quantified coercive fields measurements resulting from physical phenomena of complex magnetic (nano)architectures with different anisotropy contributions.

  14. Monte Carlo simulations of a model two-dimensional, two-patch colloidal particles

    NASA Astrophysics Data System (ADS)

    RŻysko, W.; Sokołowski, S.; Staszewski, T.

    2015-08-01

    We carried out Monte Carlo simulations of the two-patch colloids in two-dimensions. Similar model investigated theoretically in three-dimensions exhibited a re-entrant phase transition. Our simulations indicate that no re-entrant transition exists and the phase diagram for the system is of a swan-neck type and corresponds solely to the fluid-solid transition.

  15. Sample Size Requirements in Single- and Multiphase Growth Mixture Models: A Monte Carlo Simulation Study

    ERIC Educational Resources Information Center

    Kim, Su-Young

    2012-01-01

    Just as growth mixture models are useful with single-phase longitudinal data, multiphase growth mixture models can be used with multiple-phase longitudinal data. One of the practically important issues in single- and multiphase growth mixture models is the sample size requirements for accurate estimation. In a Monte Carlo simulation study, the…

  16. Monte Carlo simulation of CP sup N minus 1 models

    SciTech Connect

    Campostrini, M.; Rossi, P.; Vicari, E. )

    1992-09-15

    Numerical simulations of two-dimensional CP{sup {ital N}{minus}1} models are performed at {ital N}=2, 10, and 21. The lattice action adopted depends explicitly on the gauge degrees of freedom and shows precocious scaling. Our tests of scaling are the stability of adimensional physical quantities (second moment of the correlation function versus inverse mass gap, magnetic susceptibility versus square correlation length) and rotation invariance. Topological properties of the models are explored by measuring the topological susceptibility and by extracting the Abelian string tension. Several different (local and nonlocal) lattice definitions of topological charge are discussed and compared. The qualitative physical picture derived from the continuum 1/{ital N} expansion is confirmed, and agreement with quantitative 1/{ital N} predictions is satisfactory. Variant (Symanzik-improved) actions are considered in the CP{sup 1}{approx}O(3) case and agreement with universality and previous simulations (when comparable) is found. The simulation algorithm is an efficient picture of over-heat-bath and microcanonical algorithms. The dynamical features and critical exponents of the algorithm are discussed in detail.

  17. Direct simulation Monte Carlo modeling of e-beam metal deposition

    SciTech Connect

    Venkattraman, A.; Alexeenko, A. A.

    2010-07-15

    Three-dimensional direct simulation Monte Carlo (DSMC) method is applied here to model the electron-beam physical vapor deposition of copper thin films. Various molecular models for copper-copper interactions have been considered and a suitable molecular model has been determined based on comparisons of dimensional mass fluxes obtained from simulations and previous experiments. The variable hard sphere model that is determined for atomic copper vapor can be used in DSMC simulations for design and analysis of vacuum deposition systems, allowing for accurate prediction of growth rates, uniformity, and microstructure.

  18. Monte Carlo simulation based toy model for fission process

    NASA Astrophysics Data System (ADS)

    Kurniadi, Rizal; Waris, Abdul; Viridi, Sparisoma

    2016-09-01

    Nuclear fission has been modeled notoriously using two approaches method, macroscopic and microscopic. This work will propose another approach, where the nucleus is treated as a toy model. The aim is to see the usefulness of particle distribution in fission yield calculation. Inasmuch nucleus is a toy, then the Fission Toy Model (FTM) does not represent real process in nature completely. The fission event in FTM is represented by one random number. The number is assumed as width of distribution probability of nucleon position in compound nuclei when fission process is started. By adopting the nucleon density approximation, the Gaussian distribution is chosen as particle distribution. This distribution function generates random number that randomizes distance between particles and a central point. The scission process is started by smashing compound nucleus central point into two parts that are left central and right central points. The yield is determined from portion of nuclei distribution which is proportional with portion of mass numbers. By using modified FTM, characteristic of particle distribution in each fission event could be formed before fission process. These characteristics could be used to make prediction about real nucleons interaction in fission process. The results of FTM calculation give information that the γ value seems as energy.

  19. 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.

  20. Monte Carlo simulation for statistical mechanics model of ion-channel cooperativity in cell membranes

    NASA Astrophysics Data System (ADS)

    Erdem, Riza; Aydiner, Ekrem

    2009-03-01

    Voltage-gated ion channels are key molecules for the generation and propagation of electrical signals in excitable cell membranes. The voltage-dependent switching of these channels between conducting and nonconducting states is a major factor in controlling the transmembrane voltage. In this study, a statistical mechanics model of these molecules has been discussed on the basis of a two-dimensional spin model. A new Hamiltonian and a new Monte Carlo simulation algorithm are introduced to simulate such a model. It was shown that the results well match the experimental data obtained from batrachotoxin-modified sodium channels in the squid giant axon using the cut-open axon technique.

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

    NASA Astrophysics Data System (ADS)

    Baes, M.; Camps, P.

    2015-09-01

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

  2. Recommended direct simulation Monte Carlo collision model parameters for modeling ionized air transport processes

    NASA Astrophysics Data System (ADS)

    Swaminathan-Gopalan, Krishnan; Stephani, Kelly A.

    2016-02-01

    A systematic approach for calibrating the direct simulation Monte Carlo (DSMC) collision model parameters to achieve consistency in the transport processes is presented. The DSMC collision cross section model parameters are calibrated for high temperature atmospheric conditions by matching the collision integrals from DSMC against ab initio based collision integrals that are currently employed in the Langley Aerothermodynamic Upwind Relaxation Algorithm (LAURA) and Data Parallel Line Relaxation (DPLR) high temperature computational fluid dynamics solvers. The DSMC parameter values are computed for the widely used Variable Hard Sphere (VHS) and the Variable Soft Sphere (VSS) models using the collision-specific pairing approach. The recommended best-fit VHS/VSS parameter values are provided over a temperature range of 1000-20 000 K for a thirteen-species ionized air mixture. Use of the VSS model is necessary to achieve consistency in transport processes of ionized gases. The agreement of the VSS model transport properties with the transport properties as determined by the ab initio collision integral fits was found to be within 6% in the entire temperature range, regardless of the composition of the mixture. The recommended model parameter values can be readily applied to any gas mixture involving binary collisional interactions between the chemical species presented for the specified temperature range.

  3. Full modelling of the MOSAIC animal PET system based on the GATE Monte Carlo simulation code

    NASA Astrophysics Data System (ADS)

    Merheb, C.; Petegnief, Y.; Talbot, J. N.

    2007-02-01

    Positron emission tomography (PET) systems dedicated to animal imaging are now widely used for biological studies. The scanner performance strongly depends on the design and the characteristics of the system. Many parameters must be optimized like the dimensions and type of crystals, geometry and field-of-view (FOV), sampling, electronics, lightguide, shielding, etc. Monte Carlo modelling is a powerful tool to study the effect of each of these parameters on the basis of realistic simulated data. Performance assessment in terms of spatial resolution, count rates, scatter fraction and sensitivity is an important prerequisite before the model can be used instead of real data for a reliable description of the system response function or for optimization of reconstruction algorithms. The aim of this study is to model the performance of the Philips Mosaic™ animal PET system using a comprehensive PET simulation code in order to understand and describe the origin of important factors that influence image quality. We use GATE, a Monte Carlo simulation toolkit for a realistic description of the ring PET model, the detectors, shielding, cap, electronic processing and dead times. We incorporate new features to adjust signal processing to the Anger logic underlying the Mosaic™ system. Special attention was paid to dead time and energy spectra descriptions. Sorting of simulated events in a list mode format similar to the system outputs was developed to compare experimental and simulated sensitivity and scatter fractions for different energy thresholds using various models of phantoms describing rat and mouse geometries. Count rates were compared for both cylindrical homogeneous phantoms. Simulated spatial resolution was fitted to experimental data for 18F point sources at different locations within the FOV with an analytical blurring function for electronic processing effects. Simulated and measured sensitivities differed by less than 3%, while scatter fractions agreed

  4. Restructuring of a model hydrophobic surface: Monte Carlo simulations using a simple coarse-grained model.

    PubMed

    Eun, Changsun; Das, Jhuma; Berkowitz, Max L

    2013-12-12

    A lattice model is proposed to explain the restructuring of an ionic surfactant absorbed on a charged surface. When immersed in water, an ionic mica plate initially covered by a monolayer of surfactants rearranges to a surface inhomogeneously covered by patches of surfactant bilayer and bare mica. The model considers four species that can cover lattice sites of a surface. These species include (i) a surfactant molecule with its headgroup down, (ii) surfactant molecule with the headgroup up, (iii) a surfactant dimer arranged in a tail-to-tail configuration, which is a part of a bilayer, and (iv) a mica lattice site covered by water. We consider that only nearest neighbors on the lattice interact and describe the interactions by an interaction matrix. Using this model, we perform Monte Carlo simulations and study how the structure of the inhomogeneous surface depends on the interaction between water covered lattice site and its neighboring surfactant species covered sites. We observe that when this interaction is absent, the system undergoes phase separation into a bilayer phase and mica surface covered with water. When this interaction is taken into account, patches of surfactant bilayer and water are present in our system. The interaction between mica surfaces covered by patches of ionic surfactants is studied in experiments to understand the nature of long-ranged "hydrophobic" forces. PMID:23962357

  5. Ultrafast vectorized multispin coding algorithm for the Monte Carlo simulation of the 3D Ising model

    NASA Astrophysics Data System (ADS)

    Wansleben, Stephan

    1987-02-01

    A new Monte Carlo algorithm for the 3D Ising model and its implementation on a CDC CYBER 205 is presented. This approach is applicable to lattices with sizes between 3·3·3 and 192·192·192 with periodic boundary conditions, and is adjustable to various kinetic models. It simulates a canonical ensemble at given temperature generating a new random number for each spin flip. For the Metropolis transition probability the speed is 27 ns per updates on a two-pipe CDC Cyber 205 with 2 million words physical memory, i.e. 1.35 times the cycle time per update or 38 million updates per second.

  6. Multiscale Modelling of UniMolecular FRET Probes Using Monte Carlo Simulations

    NASA Astrophysics Data System (ADS)

    Sanyal, Shourjya; MacKernan, Donal; Coker, David F.

    2015-09-01

    Föster Resonance Energy Transfer (FRET) based biosensors are widely used in experimental biology to understand spatiotemporal dynamics of protein pairs both in-vivo and in-vitro. In our study we have developed an idealised model consisting of two macroparticles, representing proteins attached to fluorescent chromophores, linked with an idealized flexible linker consisting of N point-like beads joined by harmonic springs. Monte Carlo simulations with these models are used to investigate the influence of flexible linkers on unimolecular FRET based bio-sensors. The results provide qualitative insight into the efficacy of designing flexible peptide linkers.

  7. Assessing Categorization Performance at the Individual Level: A Comparison of Monte Carlo Simulation and Probability Estimate Model Procedures

    PubMed Central

    Arterberry, Martha E.; Bornstein, Marc H.; Haynes, O. Maurice

    2012-01-01

    Two analytical procedures for identifying young children as categorizers, the Monte Carlo Simulation and the Probability Estimate Model, were compared. Using a sequential touching method, children age 12, 18, 24, and 30 months were given seven object sets representing different levels of categorical classification. From their touching performance, the probability that children were categorizing was then determined independently using Monte Carlo Simulation and the Probability Estimate Model. The two analytical procedures resulted in different percentages of children being classified as categorizers. Results using the Monte Carlo Simulation were more consistent with group-level analyses than results using the Probability Estimate Model. These findings recommend using the Monte Carlo Simulation for determining individual categorizer classification. PMID:21402410

  8. AO modelling for wide-field E-ELT instrumentation using Monte-Carlo simulation

    NASA Astrophysics Data System (ADS)

    Basden, Alastair; Morris, Simon; Morris, Tim; Myers, Richard

    2014-08-01

    Extensive simulations of AO performance for several E-ELT instruments (including EAGLE, MOSAIC, HIRES and MAORY) have been ongoing using the Monte-Carlo Durham AO Simulation Package. We present the latest simulation results, including studies into DM requirements, dependencies of performance on asterism, detailed point spread function generation, accurate telescope modelling, and studies of laser guide star effects. Details of simulations will be given, including the use of optical models of the E-ELT to generate wave- front sensor pupil illumination functions, laser guide star modelling, and investigations of different many-layer atmospheric profiles. We discuss issues related to ELT-scale simulation, how we have overcome these, and how we will be approaching forthcoming issues such as modelling of advanced wavefront control, multi-rate wavefront sensing, and advanced treatment of extended laser guide star spots. We also present progress made on integrating simulation with AO real-time control systems. The impact of simulation outcomes on instrument design studies will be discussed, and the ongoing work plan presented.

  9. Simulation of charge breeding of rubidium using Monte Carlo charge breeding code and generalized ECRIS model

    SciTech Connect

    Zhao, L.; Cluggish, B.; Kim, J. S.; Pardo, R.; Vondrasek, R.

    2010-02-15

    A Monte Carlo charge breeding code (MCBC) is being developed by FAR-TECH, Inc. to model the capture and charge breeding of 1+ ion beam in an electron cyclotron resonance ion source (ECRIS) device. The ECRIS plasma is simulated using the generalized ECRIS model which has two choices of boundary settings, free boundary condition and Bohm condition. The charge state distribution of the extracted beam ions is calculated by solving the steady state ion continuity equations where the profiles of the captured ions are used as source terms. MCBC simulations of the charge breeding of Rb+ showed good agreement with recent charge breeding experiments at Argonne National Laboratory (ANL). MCBC correctly predicted the peak of highly charged ion state outputs under free boundary condition and similar charge state distribution width but a lower peak charge state under the Bohm condition. The comparisons between the simulation results and ANL experimental measurements are presented and discussed.

  10. Experiments with encapsulation of Monte Carlo simulation results in machine learning models

    NASA Astrophysics Data System (ADS)

    Lal Shrestha, Durga; Kayastha, Nagendra; Solomatine, Dimitri

    2010-05-01

    Uncertainty analysis techniques based on Monte Carlo (MC) simulation have been applied in hydrological sciences successfully in the last decades. They allow for quantification of the model output uncertainty resulting from uncertain model parameters, input data or model structure. They are very flexible, conceptually simple and straightforward, but become impractical in real time applications for complex models when there is little time to perform the uncertainty analysis because of the large number of model runs required. A number of new methods were developed to improve the efficiency of Monte Carlo methods and still these methods require considerable number of model runs in both offline and operational mode to produce reliable and meaningful uncertainty estimation. This paper presents experiments with machine learning techniques used to encapsulate the results of MC runs. A version of MC simulation method, the generalised likelihood uncertain estimation (GLUE) method, is first used to assess the parameter uncertainty of the conceptual rainfall-runoff model HBV. Then the three machines learning methods, namely artificial neural networks, M5 model trees and locally weighted regression methods are trained to encapsulate the uncertainty estimated by the GLUE method using the historical input data. The trained machine learning models are then employed to predict the uncertainty of the model output for the new input data. This method has been applied to two contrasting catchments: the Brue catchment (United Kingdom) and the Bagamati catchment (Nepal). The experimental results demonstrate that the machine learning methods are reasonably accurate in approximating the uncertainty estimated by GLUE. The great advantage of the proposed method is its efficiency to reproduce the MC based simulation results; it can thus be an effective tool to assess the uncertainty of flood forecasting in real time.

  11. Monte Carlo simulation for statistical mechanics model of ion-channel cooperativity in cell membranes.

    PubMed

    Erdem, Riza; Aydiner, Ekrem

    2009-03-01

    Voltage-gated ion channels are key molecules for the generation and propagation of electrical signals in excitable cell membranes. The voltage-dependent switching of these channels between conducting and nonconducting states is a major factor in controlling the transmembrane voltage. In this study, a statistical mechanics model of these molecules has been discussed on the basis of a two-dimensional spin model. A new Hamiltonian and a new Monte Carlo simulation algorithm are introduced to simulate such a model. It was shown that the results well match the experimental data obtained from batrachotoxin-modified sodium channels in the squid giant axon using the cut-open axon technique. PMID:19391983

  12. Monte Carlo simulations of a supersymmetric matrix model of dynamical compactification in non perturbative string theory

    NASA Astrophysics Data System (ADS)

    Anagnostopoulos, K.; Azuma, T.; Nishimura, J.

    The IKKT or IIB matrix model has been postulated to be a non perturbative definition of superstring theory. It has the attractive feature that spacetime is dynamically generated, which makes possible the scenario of dynamical compactification of extra dimensions, which in the Euclidean model manifests by spontaneously breaking the SO(10) rotational invariance (SSB). In this work we study using Monte Carlo simulations the 6 dimensional version of the Euclidean IIB matrix model. Simulations are found to be plagued by a strong complex action problem and the factorization method is used for effective sampling and computing expectation values of the extent of spacetime in various dimensions. Our results are consistent with calculations using the Gaussian Expansion method which predict SSB to SO(3) symmetric vacua, a finite universal extent of the compactified dimensions and finite spacetime volume.

  13. Monte Carlo simulation of flux lattice melting in a model high- T sub c superconductor

    SciTech Connect

    Ryu, S.; Doniach, S.; Deutscher, G.; Kapitulnik, A. School of Physics and Astronomy, Tel Aviv University, Ramat-Aviv 69978 )

    1992-02-03

    We studied flux lattice melting in a model high-{ital T}{sub {ital c}} superconductor by Monte Carlo simulation in terms of vortex variables. We identify two melting curves in the {ital B}-{ital T} phase diagram and evaluate a density-dependent Lindemann criterion number for melting. We also observe that the transition temperature shifts downward toward the two-dimensional melting limit as the density of flux lines increases. Although the transition temperature does not change, a significant difference in shear modulus is observed when flux cutting or reconnection is allowed.

  14. Review of dynamical models for external dose calculations based on Monte Carlo simulations in urbanised areas.

    PubMed

    Eged, Katalin; Kis, Zoltán; Voigt, Gabriele

    2006-01-01

    After an accidental release of radionuclides to the inhabited environment the external gamma irradiation from deposited radioactivity contributes significantly to the radiation exposure of the population for extended periods. For evaluating this exposure pathway, three main model requirements are needed: (i) to calculate the air kerma value per photon emitted per unit source area, based on Monte Carlo (MC) simulations; (ii) to describe the distribution and dynamics of radionuclides on the diverse urban surfaces; and (iii) to combine all these elements in a relevant urban model to calculate the resulting doses according to the actual scenario. This paper provides an overview about the different approaches to calculate photon transport in urban areas and about several dose calculation codes published. Two types of Monte Carlo simulations are presented using the global and the local approaches of photon transport. Moreover, two different philosophies of the dose calculation, the "location factor method" and a combination of relative contamination of surfaces with air kerma values are described. The main features of six codes (ECOSYS, EDEM2M, EXPURT, PARATI, TEMAS, URGENT) are highlighted together with a short model-model features intercomparison. PMID:16095771

  15. Fission yield calculation using toy model based on Monte Carlo simulation

    SciTech Connect

    Jubaidah; Kurniadi, Rizal

    2015-09-30

    Toy model is a new approximation in predicting fission yield distribution. Toy model assumes nucleus as an elastic toy consist of marbles. The number of marbles represents the number of nucleons, A. This toy nucleus is able to imitate the real nucleus properties. In this research, the toy nucleons are only influenced by central force. A heavy toy nucleus induced by a toy nucleon will be split into two fragments. These two fission fragments are called fission yield. In this research, energy entanglement is neglected. Fission process in toy model is illustrated by two Gaussian curves intersecting each other. There are five Gaussian parameters used in this research. They are scission point of the two curves (R{sub c}), mean of left curve (μ{sub L}) and mean of right curve (μ{sub R}), deviation of left curve (σ{sub L}) and deviation of right curve (σ{sub R}). The fission yields distribution is analyses based on Monte Carlo simulation. The result shows that variation in σ or µ can significanly move the average frequency of asymmetry fission yields. This also varies the range of fission yields distribution probability. In addition, variation in iteration coefficient only change the frequency of fission yields. Monte Carlo simulation for fission yield calculation using toy model successfully indicates the same tendency with experiment results, where average of light fission yield is in the range of 90

  16. A geometrical model for the Monte Carlo simulation of the TrueBeam linac

    NASA Astrophysics Data System (ADS)

    Rodriguez, M.; Sempau, J.; Fogliata, A.; Cozzi, L.; Sauerwein, W.; Brualla, L.

    2015-06-01

    Monte Carlo simulation of linear accelerators (linacs) depends on the accurate geometrical description of the linac head. The geometry of the Varian TrueBeam linac is not available to researchers. Instead, the company distributes phase-space files of the flattening-filter-free (FFF) beams tallied at a plane located just upstream of the jaws. Yet, Monte Carlo simulations based on third-party tallied phase spaces are subject to limitations. In this work, an experimentally based geometry developed for the simulation of the FFF beams of the Varian TrueBeam linac is presented. The Monte Carlo geometrical model of the TrueBeam linac uses information provided by Varian that reveals large similarities between the TrueBeam machine and the Clinac 2100 downstream of the jaws. Thus, the upper part of the TrueBeam linac was modeled by introducing modifications to the Varian Clinac 2100 linac geometry. The most important of these modifications is the replacement of the standard flattening filters by ad hoc thin filters. These filters were modeled by comparing dose measurements and simulations. The experimental dose profiles for the 6 MV and 10 MV FFF beams were obtained from the Varian Golden Data Set and from in-house measurements performed with a diode detector for radiation fields ranging from 3  ×  3 to 40  ×  40 cm2 at depths of maximum dose of 5 and 10 cm. Indicators of agreement between the experimental data and the simulation results obtained with the proposed geometrical model were the dose differences, the root-mean-square error and the gamma index. The same comparisons were performed for dose profiles obtained from Monte Carlo simulations using the phase-space files distributed by Varian for the TrueBeam linac as the sources of particles. Results of comparisons show a good agreement of the dose for the ansatz geometry similar to that obtained for the simulations with the TrueBeam phase-space files for all fields and depths considered, except for the

  17. A geometrical model for the Monte Carlo simulation of the TrueBeam linac.

    PubMed

    Rodriguez, M; Sempau, J; Fogliata, A; Cozzi, L; Sauerwein, W; Brualla, L

    2015-06-01

    Monte Carlo simulation of linear accelerators (linacs) depends on the accurate geometrical description of the linac head. The geometry of the Varian TrueBeam linac is not available to researchers. Instead, the company distributes phase-space files of the flattening-filter-free (FFF) beams tallied at a plane located just upstream of the jaws. Yet, Monte Carlo simulations based on third-party tallied phase spaces are subject to limitations. In this work, an experimentally based geometry developed for the simulation of the FFF beams of the Varian TrueBeam linac is presented. The Monte Carlo geometrical model of the TrueBeam linac uses information provided by Varian that reveals large similarities between the TrueBeam machine and the Clinac 2100 downstream of the jaws. Thus, the upper part of the TrueBeam linac was modeled by introducing modifications to the Varian Clinac 2100 linac geometry. The most important of these modifications is the replacement of the standard flattening filters by ad hoc thin filters. These filters were modeled by comparing dose measurements and simulations. The experimental dose profiles for the 6 MV and 10 MV FFF beams were obtained from the Varian Golden Data Set and from in-house measurements performed with a diode detector for radiation fields ranging from 3  ×  3 to 40  ×  40 cm(2) at depths of maximum dose of 5 and 10 cm. Indicators of agreement between the experimental data and the simulation results obtained with the proposed geometrical model were the dose differences, the root-mean-square error and the gamma index. The same comparisons were performed for dose profiles obtained from Monte Carlo simulations using the phase-space files distributed by Varian for the TrueBeam linac as the sources of particles. Results of comparisons show a good agreement of the dose for the ansatz geometry similar to that obtained for the simulations with the TrueBeam phase-space files for all fields and depths considered, except for

  18. 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.

  19. Grand canonical Monte Carlo simulation of the adsorption isotherms of water molecules on model soot particles

    NASA Astrophysics Data System (ADS)

    Moulin, F.; Picaud, S.; Hoang, P. N. M.; Jedlovszky, P.

    2007-10-01

    The grand canonical Monte Carlo method is used to simulate the adsorption isotherms of water molecules on different types of model soot particles. The soot particles are modeled by graphite-type layers arranged in an onionlike structure that contains randomly distributed hydrophilic sites, such as OH and COOH groups. The calculated water adsorption isotherm at 298K exhibits different characteristic shapes depending both on the type and the location of the hydrophilic sites and also on the size of the pores inside the soot particle. The different shapes of the adsorption isotherms result from different ways of water aggregation in or/and around the soot particle. The present results show the very weak influence of the OH sites on the water adsorption process when compared to the COOH sites. The results of these simulations can help in interpreting the experimental isotherms of water adsorbed on aircraft soot.

  20. A Monte Carlo simulation based inverse propagation method for stochastic model updating

    NASA Astrophysics Data System (ADS)

    Bao, Nuo; Wang, Chunjie

    2015-08-01

    This paper presents an efficient stochastic model updating method based on statistical theory. Significant parameters have been selected implementing the F-test evaluation and design of experiments, and then the incomplete fourth-order polynomial response surface model (RSM) has been developed. Exploiting of the RSM combined with Monte Carlo simulation (MCS), reduces the calculation amount and the rapid random sampling becomes possible. The inverse uncertainty propagation is given by the equally weighted sum of mean and covariance matrix objective functions. The mean and covariance of parameters are estimated synchronously by minimizing the weighted objective function through hybrid of particle-swarm and Nelder-Mead simplex optimization method, thus the better correlation between simulation and test is achieved. Numerical examples of a three degree-of-freedom mass-spring system under different conditions and GARTEUR assembly structure validated the feasibility and effectiveness of the proposed method.

  1. Monte Carlo Simulations of inter- and intra-grain spin structure of Ising and Heisenberg models

    NASA Astrophysics Data System (ADS)

    Leblanc, Martin

    In order to keep supplying computer hard disk drives with more and more storage space, it is essential to have smaller bits. With smaller bits, superparamagnetism, the spontaneous flipping of the magnetic moments in a bit caused by thermal fluctuations, becomes increasingly important and impacts the stability of stored data. Recording media is composed of magnetic grains (usually made of CoCrPt alloys) roughly 10 nm in size from which bits are composed. Most modeling efforts that study magnetic recording media treat the grains as weakly interacting uniformly magnetized objects. In this work, the spin structure internal to a grain is examined along with the impact of varying the relative strengths of intrar-grain and inter-grain exchange interactions. The interplay between these two effects needs to be examined for a greater understanding of superparamagnetism as well as for the applications of the proposed Heat Assisted Magnetic Recording (HAMR) technology where thermal fluctuations facilitate head-field induced bit reversal in high anisotropy media. Simulations using the Monte Carlo method (with cluster-flipping algorithms) are performed on a 2D single-layer and multilayer Ising model with a strong intrar-grain exchange interaction J as well as a weak inter-grain exchange J'. A strong deviation from traditional behavior is found when J'/J is significant. M-H hysteresis loops are also calculated and the coercivity, H c is estimated. A large value represents a strong resilience to the superparamagnetic effect. It is found that taking into account the internal degrees of freedom has a significant effect on Hce. As the Ising model serves only as an approximation, preliminary simulations are also reported on a more realistic Heisenberg model with uniaxial anisotropy. Key Words: Ising model, Heisenberg model, Monte Carlo Simulation

  2. Probing the limitations of Sigmund's model of spatially resolved sputtering using Monte Carlo simulations

    NASA Astrophysics Data System (ADS)

    Hobler, Gerhard; Bradley, R. Mark; Urbassek, Herbert M.

    2016-05-01

    Sigmund's model of spatially resolved sputtering is the underpinning of many models of nanoscale pattern formation induced by ion bombardment. It is based on three assumptions: (i) the number of sputtered atoms is proportional to the nuclear energy deposition (NED) near the surface, (ii) the NED distribution is independent of the orientation and shape of the solid surface and is identical to the one in an infinite medium, and (iii) the NED distribution in an infinite medium can be approximated by a Gaussian. We test the validity of these assumptions using Monte Carlo simulations of He, Ar, and Xe impacts on Si at energies of 2, 20, and 200 keV with incidence angles from perpendicular to grazing. We find that for the more commonly-employed beam parameters (Ar and Xe ions at 2 and 20 keV and nongrazing incidence), the Sigmund model's predictions are within a factor of 2 of the Monte Carlo results for the total sputter yield and the first two moments of the spatially resolved sputter yield. This is partly due to a compensation of errors introduced by assumptions (i) and (ii). The Sigmund model, however, does not describe the skewness of the spatially resolved sputter yield, which is almost always significant. The approximation is much poorer for He ions and/or high energies (200 keV). All three of Sigmund's assumptions break down at grazing incidence angles. In all cases, we discuss the origin of the deviations from Sigmund's model.

  3. Iterative optimisation of Monte Carlo detector models using measurements and simulations

    NASA Astrophysics Data System (ADS)

    Marzocchi, O.; Leone, D.

    2015-04-01

    This work proposes a new technique to optimise the Monte Carlo models of radiation detectors, offering the advantage of a significantly lower user effort and therefore an improved work efficiency compared to the prior techniques. The method consists of four steps, two of which are iterative and suitable for automation using scripting languages. The four steps consist in the acquisition in the laboratory of measurement data to be used as reference; the modification of a previously available detector model; the simulation of a tentative model of the detector to obtain the coefficients of a set of linear equations; the solution of the system of equations and the update of the detector model. Steps three and four can be repeated for more accurate results. This method avoids the "try and fail" approach typical of the prior techniques.

  4. Monte-Carlo simulations of a coarse-grained model for α-oligothiophenes

    NASA Astrophysics Data System (ADS)

    Almutairi, Amani; Luettmer-Strathmann, Jutta

    The interfacial layer of an organic semiconductor in contact with a metal electrode has important effects on the performance of thin-film devices. However, the structure of this layer is not easy to model. Oligothiophenes are small, π-conjugated molecules with applications in organic electronics that also serve as small-molecule models for polythiophenes. α-hexithiophene (6T) is a six-ring molecule, whose adsorption on noble metal surfaces has been studied extensively (see, e.g., Ref.). In this work, we develop a coarse-grained model for α-oligothiophenes. We describe the molecules as linear chains of bonded, discotic particles with Gay-Berne potential interactions between non-bonded ellipsoids. We perform Monte Carlo simulations to study the structure of isolated and adsorbed molecules

  5. Momentum transfer Monte Carlo model for the simulation of laser speckle contrast imaging (Conference Presentation)

    NASA Astrophysics Data System (ADS)

    Regan, Caitlin; Hayakawa, Carole K.; Choi, Bernard

    2016-03-01

    Laser speckle imaging (LSI) enables measurement of relative blood flow in microvasculature and perfusion in tissues. To determine the impact of tissue optical properties and perfusion dynamics on speckle contrast, we developed a computational simulation of laser speckle contrast imaging. We used a discrete absorption-weighted Monte Carlo simulation to model the transport of light in tissue. We simulated optical excitation of a uniform flat light source and tracked the momentum transfer of photons as they propagated through a simulated tissue geometry. With knowledge of the probability distribution of momentum transfer occurring in various layers of the tissue, we calculated the expected laser speckle contrast arising with coherent excitation using both reflectance and transmission geometries. We simulated light transport in a single homogeneous tissue while independently varying either absorption (.001-100mm^-1), reduced scattering (.1-10mm^-1), or anisotropy (0.05-0.99) over a range of values relevant to blood and commonly imaged tissues. We observed that contrast decreased by 49% with an increase in optical scattering, and observed a 130% increase with absorption (exposure time = 1ms). We also explored how speckle contrast was affected by the depth (0-1mm) and flow speed (0-10mm/s) of a dynamic vascular inclusion. This model of speckle contrast is important to increase our understanding of how parameters such as perfusion dynamics, vessel depth, and tissue optical properties affect laser speckle imaging.

  6. Modeling the self-assembly of functionalized fullerenes on solid surfaces using Monte Carlo simulations

    NASA Astrophysics Data System (ADS)

    Bubnis, Gregory J.

    Since their discovery 25 years ago, carbon fullerenes have been widely studied for their unique physicochemical properties and for applications including organic electronics and photovoltaics. For these applications it is highly desirable for crystalline fullerene thin films to spontaneously self-assemble on surfaces. Accordingly, many studies have functionalized fullerenes with the aim of tailoring their intermolecular interactions and controlling interactions with the solid substrate. The success of these rational design approaches hinges on the subtle interplay of intermolecular forces and molecule-substrate interactions. Molecular modeling is well-suited to studying these interactions by directly simulating self-assembly. In this work, we consider three different fullerene functionalization approaches and for each approach we carry out Monte Carlo simulations of the self-assembly process. In all cases, we use a "coarse-grained" molecular representation that preserves the dominant physical interactions between molecules and maximizes computational efficiency. The first approach we consider is the traditional gold-thiolate SAM (self-assembled monolayer) strategy which tethers molecules to a gold substrate via covalent sulfur-gold bonds. For this we study an asymmetric fullerene thiolate bridged by a phenyl group. Clusters of 40 molecules are simulated on the Au(111) substrate at different temperatures and surface coverage densities. Fullerenes and S atoms are found to compete for Au(111) surface sites, and this competition prevents self-assembly of highly ordered monolayers. Next, we investigate self-assembled monolayers formed by fullerenes with hydrogen-bonding carboxylic acid substituents. We consider five molecules with different dimensions and symmetries. Monte Carlo cooling simulations are used to find the most stable solid structures of clusters adsorbed to Au(111). The results show cases where fullerene-Au(111) attraction, fullerene close-packing, and

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

    NASA Astrophysics Data System (ADS)

    Hsu, Andrew T.

    1992-02-01

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

  8. Business Scenario Evaluation Method Using Monte Carlo Simulation on Qualitative and Quantitative Hybrid Model

    NASA Astrophysics Data System (ADS)

    Samejima, Masaki; Akiyoshi, Masanori; Mitsukuni, Koshichiro; Komoda, Norihisa

    We propose a business scenario evaluation method using qualitative and quantitative hybrid model. In order to evaluate business factors with qualitative causal relations, we introduce statistical values based on propagation and combination of effects of business factors by Monte Carlo simulation. In propagating an effect, we divide a range of each factor by landmarks and decide an effect to a destination node based on the divided ranges. In combining effects, we decide an effect of each arc using contribution degree and sum all effects. Through applied results to practical models, it is confirmed that there are no differences between results obtained by quantitative relations and results obtained by the proposed method at the risk rate of 5%.

  9. Monte Carlo simulation of depth dose distribution in several organic models for boron neutron capture therapy

    NASA Astrophysics Data System (ADS)

    Matsumoto, T.

    2007-09-01

    Monte Carlo simulations are performed to evaluate depth-dose distributions for possible treatment of cancers by boron neutron capture therapy (BNCT). The ICRU computational model of ADAM & EVA was used as a phantom to simulate tumors at a depth of 5 cm in central regions of the lungs, liver and pancreas. Tumors of the prostate and osteosarcoma were also centered at the depth of 4.5 and 2.5 cm in the phantom models. The epithermal neutron beam from a research reactor was the primary neutron source for the MCNP calculation of the depth-dose distributions in those cancer models. For brain tumor irradiations, the whole-body dose was also evaluated. The MCNP simulations suggested that a lethal dose of 50 Gy to the tumors can be achieved without reaching the tolerance dose of 25 Gy to normal tissue. The whole-body phantom calculations also showed that the BNCT could be applied for brain tumors without significant damage to whole-body organs.

  10. 3-D Direct Simulation Monte Carlo modeling of comet 67P/Churyumov-Gerasimenko

    NASA Astrophysics Data System (ADS)

    Liao, Y.; Su, C.; Finklenburg, S.; Rubin, M.; Ip, W.; Keller, H.; Knollenberg, J.; Kührt, E.; Lai, I.; Skorov, Y.; Thomas, N.; Wu, J.; Chen, Y.

    2014-07-01

    After deep-space hibernation, ESA's Rosetta spacecraft has been successfully woken up and obtained the first images of comet 67P /Churyumov-Gerasimenko (C-G) in March 2014. It is expected that Rosetta will rendezvous with comet 67P and start to observe the nucleus and coma of the comet in the middle of 2014. As the comet approaches the Sun, a significant increase in activity is expected. Our aim is to understand the physical processes in the coma with the help of modeling in order to interpret the resulting measurements and establish observational and data analysis strategies. DSMC (Direct Simulation Monte Carlo) [1] is a very powerful numerical method to study rarefied gas flows such as cometary comae and has been used by several authors over the past decade to study cometary outflow [2,3]. Comparisons between DSMC and fluid techniques have also been performed to establish the limits of these techniques [2,4]. The drawback with 3D DSMC is that it is computationally highly intensive and thus time consuming. However, the performance can be dramatically increased with parallel computing on Graphic Processor Units (GPUs) [5]. We have already studied a case with comet 9P/Tempel 1 where the Deep Impact observations were used to define the shape of the nucleus and the outflow was simulated with the DSMC approach [6,7]. For comet 67P, we intend to determine the gas flow field in the innermost coma and the surface outgassing properties from analyses of the flow field, to investigate dust acceleration by gas drag, and to compare with observations (including time variability). The boundary conditions are implemented with a nucleus shape model [8] and thermal models which are based on the surface heat-balance equation. Several different parameter sets have been investigated. The calculations have been performed using the PDSC^{++} (Parallel Direct Simulation Monte Carlo) code [9] developed by Wu and his coworkers [10-12]. Simulation tasks can be accomplished within 24

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

    SciTech Connect

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

    1995-07-01

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

  12. Simulating photon scattering effects in structurally detailed ventricular models using a Monte Carlo approach

    PubMed Central

    Bishop, Martin J.; Plank, Gernot

    2014-01-01

    Light scattering during optical imaging of electrical activation within the heart is known to significantly distort the optically-recorded action potential (AP) upstroke, as well as affecting the magnitude of the measured response of ventricular tissue to strong electric shocks. Modeling approaches based on the photon diffusion equation have recently been instrumental in quantifying and helping to understand the origin of the resulting distortion. However, they are unable to faithfully represent regions of non-scattering media, such as small cavities within the myocardium which are filled with perfusate during experiments. Stochastic Monte Carlo (MC) approaches allow simulation and tracking of individual photon “packets” as they propagate through tissue with differing scattering properties. Here, we present a novel application of the MC method of photon scattering simulation, applied for the first time to the simulation of cardiac optical mapping signals within unstructured, tetrahedral, finite element computational ventricular models. The method faithfully allows simulation of optical signals over highly-detailed, anatomically-complex MR-based models, including representations of fine-scale anatomy and intramural cavities. We show that optical action potential upstroke is prolonged close to large subepicardial vessels than further away from vessels, at times having a distinct “humped” morphology. Furthermore, we uncover a novel mechanism by which photon scattering effects around vessels cavities interact with “virtual-electrode” regions of strong de-/hyper-polarized tissue surrounding cavities during shocks, significantly reducing the apparent optically-measured epicardial polarization. We therefore demonstrate the importance of this novel optical mapping simulation approach along with highly anatomically-detailed models to fully investigate electrophysiological phenomena driven by fine-scale structural heterogeneity. PMID:25309442

  13. Modeling the tight focusing of beams in absorbing media with Monte Carlo simulations.

    PubMed

    Brandes, Arnd R; Elmaklizi, Ahmed; Akarçay, H Günhan; Kienle, Alwin

    2014-01-01

    A severe drawback to the scalar Monte Carlo (MC) method is the difficulty of introducing diffraction when simulating light propagation. This hinders, for instance, the accurate modeling of beams focused through microscope objectives, where the diffraction patterns in the focal plane are of great importance in various applications. Here, we propose to overcome this issue by means of a direct extinction method. In the MC simulations, the photon paths' initial positions are sampled from probability distributions which are calculated with a modified angular spectrum of the plane waves technique. We restricted our study to the two-dimensional case, and investigated the feasibility of our approach for absorbing yet nonscattering materials. We simulated the focusing of collimated beams with uniform profiles through microscope objectives. Our results were compared with those yielded by independent simulations using the finite-difference time-domain method. Very good agreement was achieved between the results of both methods, not only for the power distributions around the focal region including diffraction patterns, but also for the distribution of the energy flow (Poynting vector). PMID:25393966

  14. Parallel Tempering Monte Carlo Simulations of Spherical Fixed-Connectivity Model for Polymerized Membranes

    NASA Astrophysics Data System (ADS)

    Usui, Satoshi; Koibuchi, Hiroshi

    2016-02-01

    We study the first order phase transition of the fixed-connectivity triangulated surface model using the Parallel Tempering Monte Carlo (PTMC) technique on relatively large lattices. From the PTMC results, we find that the transition is considerably stronger than the reported ones predicted by the conventional Metropolis MC (MMC) technique and the flat histogram MC technique. We also confirm that the results of the PTMC on relatively smaller lattices are in good agreement with those known results. This implies that the PTMC is successfully used to simulate the first order phase transitions. The parallel computation in the PTMC is implemented by OpenMP, where the speed of the PTMC on multi-core CPUs is considerably faster than that on the single-core CPUs.

  15. 3D Direct Simulation Monte Carlo Modeling of the Spacecraft Environment of Rosetta

    NASA Astrophysics Data System (ADS)

    Bieler, A. M.; Tenishev, V.; Fougere, N.; Gombosi, T. I.; Hansen, K. C.; Combi, M. R.; Huang, Z.; Jia, X.; Toth, G.; Altwegg, K.; Wurz, P.; Jäckel, A.; Le Roy, L.; Gasc, S.; Calmonte, U.; Rubin, M.; Tzou, C. Y.; Hässig, M.; Fuselier, S.; De Keyser, J.; Berthelier, J. J.; Mall, U. A.; Rème, H.; Fiethe, B.; Balsiger, H.

    2014-12-01

    The European Space Agency's Rosetta mission is the first to escort a comet over an extended time as the comet makes its way through the inner solar system. The ROSINA instrument suite consisting of a double focusing mass spectrometer, a time of flight mass spectrometer and a pressure sensor, will provide temporally and spatially resolved data on the comet's volatile inventory. The effect of spacecraft outgassing is well known and has been measured with the ROSINA instruments onboard Rosetta throughout the cruise phase. The flux of released neutral gas originating from the spacecraft cannot be distinguished from the cometary signal by the mass spectrometers and varies significantly with solar illumination conditions. For accurate interpretation of the instrument data, a good understanding of spacecraft outgassing is necessary. In this talk we present results simulating the spacecraft environment with the Adaptive Mesh Particle Simulator (AMPS) code. AMPS is a direct simulation monte carlo code that includes multiple species in a 3D adaptive mesh to describe a full scale model of the spacecraft environment. We use the triangulated surface model of the spacecraft to implement realistic outgassing rates for different areas on the surface and take shadowing effects in consideration. The resulting particle fluxes are compared to the measurements of the ROSINA experiment and implications for ROSINA measurements and data analysis are discussed. Spacecraft outgassing has implications for future space missions to rarefied atmospheres as it imposes a limit on the detection of various species.

  16. Single-site Lennard-Jones models via polynomial chaos surrogates of Monte Carlo molecular simulation

    NASA Astrophysics Data System (ADS)

    Kadoura, Ahmad; Siripatana, Adil; Sun, Shuyu; Knio, Omar; Hoteit, Ibrahim

    2016-06-01

    In this work, two Polynomial Chaos (PC) surrogates were generated to reproduce Monte Carlo (MC) molecular simulation results of the canonical (single-phase) and the NVT-Gibbs (two-phase) ensembles for a system of normalized structureless Lennard-Jones (LJ) particles. The main advantage of such surrogates, once generated, is the capability of accurately computing the needed thermodynamic quantities in a few seconds, thus efficiently replacing the computationally expensive MC molecular simulations. Benefiting from the tremendous computational time reduction, the PC surrogates were used to conduct large-scale optimization in order to propose single-site LJ models for several simple molecules. Experimental data, a set of supercritical isotherms, and part of the two-phase envelope, of several pure components were used for tuning the LJ parameters (ɛ, σ). Based on the conducted optimization, excellent fit was obtained for different noble gases (Ar, Kr, and Xe) and other small molecules (CH4, N2, and CO). On the other hand, due to the simplicity of the LJ model used, dramatic deviations between simulation and experimental data were observed, especially in the two-phase region, for more complex molecules such as CO2 and C2 H6.

  17. A stochastic Markov chain approach for tennis: Monte Carlo simulation and modeling

    NASA Astrophysics Data System (ADS)

    Aslam, Kamran

    This dissertation describes the computational formulation of probability density functions (pdfs) that facilitate head-to-head match simulations in tennis along with ranking systems developed from their use. A background on the statistical method used to develop the pdfs , the Monte Carlo method, and the resulting rankings are included along with a discussion on ranking methods currently being used both in professional sports and in other applications. Using an analytical theory developed by Newton and Keller in [34] that defines a tennis player's probability of winning a game, set, match and single elimination tournament, a computational simulation has been developed in Matlab that allows further modeling not previously possible with the analytical theory alone. Such experimentation consists of the exploration of non-iid effects, considers the concept the varying importance of points in a match and allows an unlimited number of matches to be simulated between unlikely opponents. The results of these studies have provided pdfs that accurately model an individual tennis player's ability along with a realistic, fair and mathematically sound platform for ranking them.

  18. Direct simulation Monte Carlo modeling of relaxation processes in polyatomic gases

    NASA Astrophysics Data System (ADS)

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

    2016-02-01

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

  19. Single-site Lennard-Jones models via polynomial chaos surrogates of Monte Carlo molecular simulation.

    PubMed

    Kadoura, Ahmad; Siripatana, Adil; Sun, Shuyu; Knio, Omar; Hoteit, Ibrahim

    2016-06-01

    In this work, two Polynomial Chaos (PC) surrogates were generated to reproduce Monte Carlo (MC) molecular simulation results of the canonical (single-phase) and the NVT-Gibbs (two-phase) ensembles for a system of normalized structureless Lennard-Jones (LJ) particles. The main advantage of such surrogates, once generated, is the capability of accurately computing the needed thermodynamic quantities in a few seconds, thus efficiently replacing the computationally expensive MC molecular simulations. Benefiting from the tremendous computational time reduction, the PC surrogates were used to conduct large-scale optimization in order to propose single-site LJ models for several simple molecules. Experimental data, a set of supercritical isotherms, and part of the two-phase envelope, of several pure components were used for tuning the LJ parameters (ε, σ). Based on the conducted optimization, excellent fit was obtained for different noble gases (Ar, Kr, and Xe) and other small molecules (CH4, N2, and CO). On the other hand, due to the simplicity of the LJ model used, dramatic deviations between simulation and experimental data were observed, especially in the two-phase region, for more complex molecules such as CO2 and C2 H6. PMID:27276951

  20. a Test Particle Model for Monte Carlo Simulation of Plasma Transport Driven by Quasineutrality

    NASA Astrophysics Data System (ADS)

    Kuhl, Nelson M.

    1995-11-01

    This paper is concerned with the problem of transport in controlled nuclear fusion as it applies to confinement in a tokamak or stellarator. We perform numerical experiments to validate a mathematical model of P. R. Garabedian in which the electric potential is determined by quasineutrality because of singular perturbation of the Poisson equation. The simulations are made using a transport code written by O. Betancourt and M. Taylor, with changes to incorporate our case studies. We adopt a test particle model naturally suggested by the problem of tracking particles in plasma physics. The statistics due to collisions are modeled by a drift kinetic equation whose numerical solution is based on the Monte Carlo method of A. Boozer and G. Kuo -Petravic. The collision operator drives the distribution function in velocity space towards the normal distribution, or Maxwellian. It is shown that details of the collision operator other than its dependence on the collision frequency and temperature matter little for transport, and the role of conservation of momentum is investigated. Exponential decay makes it possible to find the confinement times of both ions and electrons by high performance computing. Three -dimensional perturbations in the electromagnetic field model the anomalous transport of electrons and simulate the turbulent behavior that is presumably triggered by the displacement current. We make a convergence study of the method, derive scaling laws that are in good agreement with predictions from experimental data, and present a comparison with the JET experiment.

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

    PubMed

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

    2014-12-21

    The Direct Simulation Monte Carlo (DSMC) method typically used for simulating hypersonic Earth re-entry flows requires accurate total collision cross sections and reaction probabilities. However, total cross sections are often determined from extrapolations of relatively low-temperature viscosity data, so their reliability is unknown for the high temperatures observed in hypersonic flows. Existing DSMC reaction models accurately reproduce experimental equilibrium reaction rates, but the applicability of these rates to the strong thermal nonequilibrium observed in hypersonic shocks is unknown. For hypersonic flows, these modeling issues are particularly relevant for nitrogen, the dominant species of air. To rectify this deficiency, the Molecular Dynamics/Quasi-Classical Trajectories (MD/QCT) method is used to accurately compute collision and reaction cross sections for the N2(Σg+1)-N2(Σg+1) collision pair for conditions expected in hypersonic shocks using a new potential energy surface developed using a ReaxFF fit to recent advanced ab initio calculations. The MD/QCT-computed reaction probabilities were found to exhibit better physical behavior and predict less dissociation than the baseline total collision energy reaction model for strong nonequilibrium conditions expected in a shock. The MD/QCT reaction model compared well with computed equilibrium reaction rates and shock-tube data. In addition, the MD/QCT-computed total cross sections were found to agree well with established variable hard sphere total cross sections. PMID:25527935

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

    SciTech Connect

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

    2014-12-21

    The Direct Simulation Monte Carlo (DSMC) method typically used for simulating hypersonic Earth re-entry flows requires accurate total collision cross sections and reaction probabilities. However, total cross sections are often determined from extrapolations of relatively low-temperature viscosity data, so their reliability is unknown for the high temperatures observed in hypersonic flows. Existing DSMC reaction models accurately reproduce experimental equilibrium reaction rates, but the applicability of these rates to the strong thermal nonequilibrium observed in hypersonic shocks is unknown. For hypersonic flows, these modeling issues are particularly relevant for nitrogen, the dominant species of air. To rectify this deficiency, the Molecular Dynamics/Quasi-Classical Trajectories (MD/QCT) method is used to accurately compute collision and reaction cross sections for the N{sub 2}({sup 1}Σ{sub g}{sup +})-N{sub 2}({sup 1}Σ{sub g}{sup +}) collision pair for conditions expected in hypersonic shocks using a new potential energy surface developed using a ReaxFF fit to recent advanced ab initio calculations. The MD/QCT-computed reaction probabilities were found to exhibit better physical behavior and predict less dissociation than the baseline total collision energy reaction model for strong nonequilibrium conditions expected in a shock. The MD/QCT reaction model compared well with computed equilibrium reaction rates and shock-tube data. In addition, the MD/QCT-computed total cross sections were found to agree well with established variable hard sphere total cross sections.

  3. Monte Carlo computer simulations of Venus equilibrium and global resurfacing models

    NASA Technical Reports Server (NTRS)

    Dawson, D. D.; Strom, R. G.; Schaber, G. G.

    1992-01-01

    Two models have been proposed for the resurfacing history of Venus: (1) equilibrium resurfacing and (2) global resurfacing. The equilibrium model consists of two cases: in case 1, areas less than or equal to 0.03 percent of the planet are spatially randomly resurfaced at intervals of less than or greater than 150,000 yr to produce the observed spatially random distribution of impact craters and average surface age of about 500 m.y.; and in case 2, areas greater than or equal to 10 percent of the planet are resurfaced at intervals of greater than or equal to 50 m.y. The global resurfacing model proposes that the entire planet was resurfaced about 500 m.y. ago, destroying the preexisting crater population and followed by significantly reduced volcanism and tectonism. The present crater population has accumulated since then with only 4 percent of the observed craters having been embayed by more recent lavas. To test the equilibrium resurfacing model we have run several Monte Carlo computer simulations for the two proposed cases. It is shown that the equilibrium resurfacing model is not a valid model for an explanation of the observed crater population characteristics or Venus' resurfacing history. The global resurfacing model is the most likely explanation for the characteristics of Venus' cratering record. The amount of resurfacing since that event, some 500 m.y. ago, can be estimated by a different type of Monte Carolo simulation. To date, our initial simulation has only considered the easiest case to implement. In this case, the volcanic events are randomly distributed across the entire planet and, therefore, contrary to observation, the flooded craters are also randomly distributed across the planet.

  4. A virtual source model for Monte Carlo simulation of helical tomotherapy.

    PubMed

    Yuan, Jiankui; Rong, Yi; Chen, Quan

    2015-01-01

    The purpose of this study was to present a Monte Carlo (MC) simulation method based on a virtual source, jaw, and MLC model to calculate dose in patient for helical tomotherapy without the need of calculating phase-space files (PSFs). Current studies on the tomotherapy MC simulation adopt a full MC model, which includes extensive modeling of radiation source, primary and secondary jaws, and multileaf collimator (MLC). In the full MC model, PSFs need to be created at different scoring planes to facilitate the patient dose calculations. In the present work, the virtual source model (VSM) we established was based on the gold standard beam data of a tomotherapy unit, which can be exported from the treatment planning station (TPS). The TPS-generated sinograms were extracted from the archived patient XML (eXtensible Markup Language) files. The fluence map for the MC sampling was created by incorporating the percentage leaf open time (LOT) with leaf filter, jaw penumbra, and leaf latency contained from sinogram files. The VSM was validated for various geometry setups and clinical situations involving heterogeneous media and delivery quality assurance (DQA) cases. An agreement of < 1% was obtained between the measured and simulated results for percent depth doses (PDDs) and open beam profiles for all three jaw settings in the VSM commissioning. The accuracy of the VSM leaf filter model was verified in comparing the measured and simulated results for a Picket Fence pattern. An agreement of < 2% was achieved between the presented VSM and a published full MC model for heterogeneous phantoms. For complex clinical head and neck (HN) cases, the VSM-based MC simulation of DQA plans agreed with the film measurement with 98% of planar dose pixels passing on the 2%/2 mm gamma criteria. For patient treatment plans, results showed comparable dose-volume histograms (DVHs) for planning target volumes (PTVs) and organs at risk (OARs). Deviations observed in this study were consistent

  5. Treatment of input uncertainty in hydrologic modeling: Doing hydrology backward with Markov chain Monte Carlo simulation

    NASA Astrophysics Data System (ADS)

    Vrugt, Jasper A.; Ter Braak, Cajo J. F.; Clark, Martyn P.; Hyman, James M.; Robinson, Bruce A.

    2008-12-01

    There is increasing consensus in the hydrologic literature that an appropriate framework for streamflow forecasting and simulation should include explicit recognition of forcing and parameter and model structural error. This paper presents a novel Markov chain Monte Carlo (MCMC) sampler, entitled differential evolution adaptive Metropolis (DREAM), that is especially designed to efficiently estimate the posterior probability density function of hydrologic model parameters in complex, high-dimensional sampling problems. This MCMC scheme adaptively updates the scale and orientation of the proposal distribution during sampling and maintains detailed balance and ergodicity. It is then demonstrated how DREAM can be used to analyze forcing data error during watershed model calibration using a five-parameter rainfall-runoff model with streamflow data from two different catchments. Explicit treatment of precipitation error during hydrologic model calibration not only results in prediction uncertainty bounds that are more appropriate but also significantly alters the posterior distribution of the watershed model parameters. This has significant implications for regionalization studies. The approach also provides important new ways to estimate areal average watershed precipitation, information that is of utmost importance for testing hydrologic theory, diagnosing structural errors in models, and appropriately benchmarking rainfall measurement devices.

  6. Cluster expansion modeling and Monte Carlo simulation of alnico 5–7 permanent magnets

    DOE PAGESBeta

    Nguyen, Manh Cuong; Zhao, Xin; Wang, Cai -Zhuang; Ho, Kai -Ming

    2015-03-05

    The concerns about the supply and resource of rare earth (RE) metals have generated a lot of interests in searching for high performance RE-free permanent magnets. Alnico alloys are traditional non-RE permanent magnets and have received much attention recently due their good performance at high temperature. In this paper, we develop an accurate and efficient cluster expansion energy model for alnico 5–7. Monte Carlo simulations using the cluster expansion method are performed to investigate the structure of alnico 5–7 at atomistic and nano scales. The alnico 5–7 master alloy is found to decompose into FeCo-rich and NiAl-rich phases at lowmore » temperature. The boundary between these two phases is quite sharp (~2 nm) for a wide range of temperature. The compositions of the main constituents in these two phases become higher when the temperature gets lower. Both FeCo-rich and NiAl-rich phases are in B2 ordering with Fe and Al on α-site and Ni and Co on β-site. The degree of order of the NiAl-rich phase is much higher than that of the FeCo-rich phase. In addition, a small magnetic moment is also observed in NiAl-rich phase but the moment reduces as the temperature is lowered, implying that the magnetic properties of alnico 5–7 could be improved by lowering annealing temperature to diminish the magnetism in NiAl-rich phase. Furthermore, the results from our Monte Carlo simulations are consistent with available experimental results.« less

  7. Cluster expansion modeling and Monte Carlo simulation of alnico 5–7 permanent magnets

    SciTech Connect

    Nguyen, Manh Cuong Zhao, Xin; Wang, Cai-Zhuang; Ho, Kai-Ming

    2015-03-07

    The concerns about the supply and resource of rare earth (RE) metals have generated a lot of interests in searching for high performance RE-free permanent magnets. Alnico alloys are traditional non-RE permanent magnets and have received much attention recently due their good performance at high temperature. In this paper, we develop an accurate and efficient cluster expansion energy model for alnico 5–7. Monte Carlo simulations using the cluster expansion method are performed to investigate the structure of alnico 5–7 at atomistic and nano scales. The alnico 5–7 master alloy is found to decompose into FeCo-rich and NiAl-rich phases at low temperature. The boundary between these two phases is quite sharp (∼2 nm) for a wide range of temperature. The compositions of the main constituents in these two phases become higher when the temperature gets lower. Both FeCo-rich and NiAl-rich phases are in B2 ordering with Fe and Al on α-site and Ni and Co on β-site. The degree of order of the NiAl-rich phase is much higher than that of the FeCo-rich phase. A small magnetic moment is also observed in NiAl-rich phase but the moment reduces as the temperature is lowered, implying that the magnetic properties of alnico 5–7 could be improved by lowering annealing temperature to diminish the magnetism in NiAl-rich phase. The results from our Monte Carlo simulations are consistent with available experimental results.

  8. Cluster expansion modeling and Monte Carlo simulation of alnico 5–7 permanent magnets

    SciTech Connect

    Nguyen, Manh Cuong; Zhao, Xin; Wang, Cai -Zhuang; Ho, Kai -Ming

    2015-03-05

    The concerns about the supply and resource of rare earth (RE) metals have generated a lot of interests in searching for high performance RE-free permanent magnets. Alnico alloys are traditional non-RE permanent magnets and have received much attention recently due their good performance at high temperature. In this paper, we develop an accurate and efficient cluster expansion energy model for alnico 5–7. Monte Carlo simulations using the cluster expansion method are performed to investigate the structure of alnico 5–7 at atomistic and nano scales. The alnico 5–7 master alloy is found to decompose into FeCo-rich and NiAl-rich phases at low temperature. The boundary between these two phases is quite sharp (~2 nm) for a wide range of temperature. The compositions of the main constituents in these two phases become higher when the temperature gets lower. Both FeCo-rich and NiAl-rich phases are in B2 ordering with Fe and Al on α-site and Ni and Co on β-site. The degree of order of the NiAl-rich phase is much higher than that of the FeCo-rich phase. In addition, a small magnetic moment is also observed in NiAl-rich phase but the moment reduces as the temperature is lowered, implying that the magnetic properties of alnico 5–7 could be improved by lowering annealing temperature to diminish the magnetism in NiAl-rich phase. Furthermore, the results from our Monte Carlo simulations are consistent with available experimental results.

  9. Cluster expansion modeling and Monte Carlo simulation of alnico 5-7 permanent magnets

    NASA Astrophysics Data System (ADS)

    Nguyen, Manh Cuong; Zhao, Xin; Wang, Cai-Zhuang; Ho, Kai-Ming

    2015-03-01

    The concerns about the supply and resource of rare earth (RE) metals have generated a lot of interests in searching for high performance RE-free permanent magnets. Alnico alloys are traditional non-RE permanent magnets and have received much attention recently due their good performance at high temperature. In this paper, we develop an accurate and efficient cluster expansion energy model for alnico 5-7. Monte Carlo simulations using the cluster expansion method are performed to investigate the structure of alnico 5-7 at atomistic and nano scales. The alnico 5-7 master alloy is found to decompose into FeCo-rich and NiAl-rich phases at low temperature. The boundary between these two phases is quite sharp (˜2 nm) for a wide range of temperature. The compositions of the main constituents in these two phases become higher when the temperature gets lower. Both FeCo-rich and NiAl-rich phases are in B2 ordering with Fe and Al on α-site and Ni and Co on β-site. The degree of order of the NiAl-rich phase is much higher than that of the FeCo-rich phase. A small magnetic moment is also observed in NiAl-rich phase but the moment reduces as the temperature is lowered, implying that the magnetic properties of alnico 5-7 could be improved by lowering annealing temperature to diminish the magnetism in NiAl-rich phase. The results from our Monte Carlo simulations are consistent with available experimental results.

  10. Development of a randomized 3D cell model for Monte Carlo microdosimetry simulations

    SciTech Connect

    Douglass, Michael; Bezak, Eva; Penfold, Scott

    2012-06-15

    Purpose: The objective of the current work was to develop an algorithm for growing a macroscopic tumor volume from individual randomized quasi-realistic cells. The major physical and chemical components of the cell need to be modeled. It is intended to import the tumor volume into GEANT4 (and potentially other Monte Carlo packages) to simulate ionization events within the cell regions. Methods: A MATLAB Copyright-Sign code was developed to produce a tumor coordinate system consisting of individual ellipsoidal cells randomized in their spatial coordinates, sizes, and rotations. An eigenvalue method using a mathematical equation to represent individual cells was used to detect overlapping cells. GEANT4 code was then developed to import the coordinate system into GEANT4 and populate it with individual cells of varying sizes and composed of the membrane, cytoplasm, reticulum, nucleus, and nucleolus. Each region is composed of chemically realistic materials. Results: The in-house developed MATLAB Copyright-Sign code was able to grow semi-realistic cell distributions ({approx}2 Multiplication-Sign 10{sup 8} cells in 1 cm{sup 3}) in under 36 h. The cell distribution can be used in any number of Monte Carlo particle tracking toolkits including GEANT4, which has been demonstrated in this work. Conclusions: Using the cell distribution and GEANT4, the authors were able to simulate ionization events in the individual cell components resulting from 80 keV gamma radiation (the code is applicable to other particles and a wide range of energies). This virtual microdosimetry tool will allow for a more complete picture of cell damage to be developed.

  11. Incorporating dynamic collimator motion in Monte Carlo simulations: an application in modelling a dynamic wedge.

    PubMed

    Verhaegen, F; Liu, H H

    2001-02-01

    In radiation therapy, new treatment modalities employing dynamic collimation and intensity modulation increase the complexity of dose calculation because a new dimension, time, has to be incorporated into the traditional three-dimensional problem. In this work, we investigated two classes of sampling technique to incorporate dynamic collimator motion in Monte Carlo simulation. The methods were initially evaluated for modelling enhanced dynamic wedges (EDWs) from Varian accelerators (Varian Medical Systems, Palo Alto, USA). In the position-probability-sampling or PPS method, a cumulative probability distribution function (CPDF) was computed for the collimator position, which could then be sampled during simulations. In the static-component-simulation or SCS method, a dynamic field is approximated by multiple static fields in a step-shoot fashion. The weights of the particles or the number of particles simulated for each component field are computed from the probability distribution function (PDF) of the collimator position. The CPDF and PDF were computed from the segmented treatment tables (STTs) for the EDWs. An output correction factor had to be applied in this calculation to account for the backscattered radiation affecting monitor chamber readings. Comparison of the phase-space data from the PPS method (with the step-shoot motion) with those from the SCS method showed excellent agreement. The accuracy of the PPS method was further verified from the agreement between the measured and calculated dose distributions. Compared to the SCS method, the PPS method is more automated and efficient from an operational point of view. The principle of the PPS method can be extended to simulate other dynamic motions, and in particular, intensity-modulated beams using multileaf collimators. PMID:11229715

  12. Modeling parameterized geometry in GPU-based Monte Carlo particle transport simulation for radiotherapy

    NASA Astrophysics Data System (ADS)

    Chi, Yujie; Tian, Zhen; Jia, Xun

    2016-08-01

    Monte Carlo (MC) particle transport simulation on a graphics-processing unit (GPU) platform has been extensively studied recently due to the efficiency advantage achieved via massive parallelization. Almost all of the existing GPU-based MC packages were developed for voxelized geometry. This limited application scope of these packages. The purpose of this paper is to develop a module to model parametric geometry and integrate it in GPU-based MC simulations. In our module, each continuous region was defined by its bounding surfaces that were parameterized by quadratic functions. Particle navigation functions in this geometry were developed. The module was incorporated to two previously developed GPU-based MC packages and was tested in two example problems: (1) low energy photon transport simulation in a brachytherapy case with a shielded cylinder applicator and (2) MeV coupled photon/electron transport simulation in a phantom containing several inserts of different shapes. In both cases, the calculated dose distributions agreed well with those calculated in the corresponding voxelized geometry. The averaged dose differences were 1.03% and 0.29%, respectively. We also used the developed package to perform simulations of a Varian VS 2000 brachytherapy source and generated a phase-space file. The computation time under the parameterized geometry depended on the memory location storing the geometry data. When the data was stored in GPU’s shared memory, the highest computational speed was achieved. Incorporation of parameterized geometry yielded a computation time that was ~3 times of that in the corresponding voxelized geometry. We also developed a strategy to use an auxiliary index array to reduce frequency of geometry calculations and hence improve efficiency. With this strategy, the computational time ranged in 1.75–2.03 times of the voxelized geometry for coupled photon/electron transport depending on the voxel dimension of the auxiliary index array, and in 0

  13. Modeling parameterized geometry in GPU-based Monte Carlo particle transport simulation for radiotherapy.

    PubMed

    Chi, Yujie; Tian, Zhen; Jia, Xun

    2016-08-01

    Monte Carlo (MC) particle transport simulation on a graphics-processing unit (GPU) platform has been extensively studied recently due to the efficiency advantage achieved via massive parallelization. Almost all of the existing GPU-based MC packages were developed for voxelized geometry. This limited application scope of these packages. The purpose of this paper is to develop a module to model parametric geometry and integrate it in GPU-based MC simulations. In our module, each continuous region was defined by its bounding surfaces that were parameterized by quadratic functions. Particle navigation functions in this geometry were developed. The module was incorporated to two previously developed GPU-based MC packages and was tested in two example problems: (1) low energy photon transport simulation in a brachytherapy case with a shielded cylinder applicator and (2) MeV coupled photon/electron transport simulation in a phantom containing several inserts of different shapes. In both cases, the calculated dose distributions agreed well with those calculated in the corresponding voxelized geometry. The averaged dose differences were 1.03% and 0.29%, respectively. We also used the developed package to perform simulations of a Varian VS 2000 brachytherapy source and generated a phase-space file. The computation time under the parameterized geometry depended on the memory location storing the geometry data. When the data was stored in GPU's shared memory, the highest computational speed was achieved. Incorporation of parameterized geometry yielded a computation time that was ~3 times of that in the corresponding voxelized geometry. We also developed a strategy to use an auxiliary index array to reduce frequency of geometry calculations and hence improve efficiency. With this strategy, the computational time ranged in 1.75-2.03 times of the voxelized geometry for coupled photon/electron transport depending on the voxel dimension of the auxiliary index array, and in 0

  14. Parallel kinetic Monte Carlo simulation framework incorporating accurate models of adsorbate lateral interactions

    SciTech Connect

    Nielsen, Jens; D’Avezac, Mayeul; Hetherington, James; Stamatakis, Michail

    2013-12-14

    Ab initio kinetic Monte Carlo (KMC) simulations have been successfully applied for over two decades to elucidate the underlying physico-chemical phenomena on the surfaces of heterogeneous catalysts. These simulations necessitate detailed knowledge of the kinetics of elementary reactions constituting the reaction mechanism, and the energetics of the species participating in the chemistry. The information about the energetics is encoded in the formation energies of gas and surface-bound species, and the lateral interactions between adsorbates on the catalytic surface, which can be modeled at different levels of detail. The majority of previous works accounted for only pairwise-additive first nearest-neighbor interactions. More recently, cluster-expansion Hamiltonians incorporating long-range interactions and many-body terms have been used for detailed estimations of catalytic rate [C. Wu, D. J. Schmidt, C. Wolverton, and W. F. Schneider, J. Catal. 286, 88 (2012)]. In view of the increasing interest in accurate predictions of catalytic performance, there is a need for general-purpose KMC approaches incorporating detailed cluster expansion models for the adlayer energetics. We have addressed this need by building on the previously introduced graph-theoretical KMC framework, and we have developed Zacros, a FORTRAN2003 KMC package for simulating catalytic chemistries. To tackle the high computational cost in the presence of long-range interactions we introduce parallelization with OpenMP. We further benchmark our framework by simulating a KMC analogue of the NO oxidation system established by Schneider and co-workers [J. Catal. 286, 88 (2012)]. We show that taking into account only first nearest-neighbor interactions may lead to large errors in the prediction of the catalytic rate, whereas for accurate estimates thereof, one needs to include long-range terms in the cluster expansion.

  15. Impact of model parameters on Monte Carlo simulations of backscattering Mueller matrix images of colon tissue

    PubMed Central

    Antonelli, Maria-Rosaria; Pierangelo, Angelo; Novikova, Tatiana; Validire, Pierre; Benali, Abdelali; Gayet, Brice; De Martino, Antonello

    2011-01-01

    Polarimetric imaging is emerging as a viable technique for tumor detection and staging. As a preliminary step towards a thorough understanding of the observed contrasts, we present a set of numerical Monte Carlo simulations of the polarimetric response of multilayer structures representing colon samples in the backscattering geometry. In a first instance, a typical colon sample was modeled as one or two scattering “slabs” with monodisperse non absorbing scatterers representing the most superficial tissue layers (the mucosa and submucosa), above a totally depolarizing Lambertian lumping the contributions of the deeper layers (muscularis and pericolic tissue). The model parameters were the number of layers, their thicknesses and morphology, the sizes and concentrations of the scatterers, the optical index contrast between the scatterers and the surrounding medium, and the Lambertian albedo. With quite similar results for single and double layer structures, this model does not reproduce the experimentally observed stability of the relative magnitudes of the depolarizing powers for incident linear and circular polarizations. This issue was solved by considering bimodal populations including large and small scatterers in a single layer above the Lambertian, a result which shows the importance of taking into account the various types of scatterers (nuclei, collagen fibers and organelles) in the same model. PMID:21750762

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

    NASA Astrophysics Data System (ADS)

    Sohn, Ilyoup

    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

  17. A stochastic model updating method for parameter variability quantification based on response surface models and Monte Carlo simulation

    NASA Astrophysics Data System (ADS)

    Fang, Sheng-En; Ren, Wei-Xin; Perera, Ricardo

    2012-11-01

    Stochastic model updating must be considered for quantifying uncertainties inherently existing in real-world engineering structures. By this means the statistical properties, instead of deterministic values, of structural parameters can be sought indicating the parameter variability. However, the implementation of stochastic model updating is much more complicated than that of deterministic methods particularly in the aspects of theoretical complexity and low computational efficiency. This study attempts to propose a simple and cost-efficient method by decomposing a stochastic updating process into a series of deterministic ones with the aid of response surface models and Monte Carlo simulation. The response surface models are used as surrogates for original FE models in the interest of programming simplification, fast response computation and easy inverse optimization. Monte Carlo simulation is adopted for generating samples from the assumed or measured probability distributions of responses. Each sample corresponds to an individual deterministic inverse process predicting the deterministic values of parameters. Then the parameter means and variances can be statistically estimated based on all the parameter predictions by running all the samples. Meanwhile, the analysis of variance approach is employed for the evaluation of parameter variability significance. The proposed method has been demonstrated firstly on a numerical beam and then a set of nominally identical steel plates tested in the laboratory. It is found that compared with the existing stochastic model updating methods, the proposed method presents similar accuracy while its primary merits consist in its simple implementation and cost efficiency in response computation and inverse optimization.

  18. Monte Carlo simulation of x-ray scatter based on patient model from digital breast tomosynthesis

    NASA Astrophysics Data System (ADS)

    Liu, Bob; Wu, Tao; Moore, Richard H.; Kopans, Daniel B.

    2006-03-01

    We are developing a breast specific scatter correction method for digital beast tomosynthesis (DBT). The 3D breast volume was initially reconstructed from 15 projection images acquired from a GE prototype tomosynthesis system without correction of scatter. The voxel values were mapped to the tissue compositions using various segmentation schemes. This voxelized digital breast model was entered into a Monte Carlo package simulating the prototype tomosynthesis system. One billion photons were generated from the x-ray source for each projection in the simulation and images of scattered photons were obtained. A primary only projection image was then produced by subtracting the scatter image from the corresponding original projection image which contains contributions from the both primary photons and scatter photons. The scatter free projection images were then used to reconstruct the 3D breast using the same algorithm. Compared with the uncorrected 3D image, the x-ray attenuation coefficients represented by the scatter-corrected 3D image are closer to those derived from the measurement data.

  19. [Rapid simulation of electrode surface treatment based on Monte-Carlo model].

    PubMed

    Hu, Zhengtian; Xu, Ying; Guo, Miao; Sun, Zhitong; Li, Yan

    2014-12-01

    Micro- and integrated biosensor provides a powerful means for cell electrophysiology research. The technology of electroplating platinum black on the electrode can uprate signal-to-noise ratio and sensitivity of the sensor. For quantifying analysis of the processing method of electroplating process, this paper proposes a grid search algorithm based on the Monte-Carlo model. The paper also puts forward the operational optimization strategy, which can rapidly implement the process of large-scale nanoparticles with different particle size of dispersion (20-200 nm) attac- hing to the electrode and shortening a simulation time from average 20 hours to 0.5 hour when the test number is 10 and electrode radius is 100 microm. When the nanoparticle was in a single layer or multiple layers, the treatment uniformity and attachment rate was analyzed by using the grid search algorithm with different sizes and shapes of electrode. Simulation results showed that under ideal conditions, when the electrode radius is less than 100 /m, with the electrode size increasing, it has an obvious effect for the effective attachment and the homogeneity of nanoparticle, which is advantageous to the quantitative evaluation of electrode array's repeatability. Under the condition of the same electrode area, the best attachment is on the circular electrode compared to the attachments on the square and rectangular ones. PMID:25868260

  20. Convolution-Based Forced Detection Monte Carlo Simulation Incorporating Septal Penetration Modeling

    PubMed Central

    Liu, Shaoying; King, Michael A.; Brill, Aaron B.; Stabin, Michael G.; Farncombe, Troy H.

    2010-01-01

    In SPECT imaging, photon transport effects such as scatter, attenuation and septal penetration can negatively affect the quality of the reconstructed image and the accuracy of quantitation estimation. As such, it is useful to model these effects as carefully as possible during the image reconstruction process. Many of these effects can be included in Monte Carlo (MC) based image reconstruction using convolution-based forced detection (CFD). With CFD Monte Carlo (CFD-MC), often only the geometric response of the collimator is modeled, thereby making the assumption that the collimator materials are thick enough to completely absorb photons. However, in order to retain high collimator sensitivity and high spatial resolution, it is required that the septa be as thin as possible, thus resulting in a significant amount of septal penetration for high energy radionuclides. A method for modeling the effects of both collimator septal penetration and geometric response using ray tracing (RT) techniques has been performed and included into a CFD-MC program. Two look-up tables are pre-calculated based on the specific collimator parameters and radionuclides, and subsequently incorporated into the SIMIND MC program. One table consists of the cumulative septal thickness between any point on the collimator and the center location of the collimator. The other table presents the resultant collimator response for a point source at different distances from the collimator and for various energies. A series of RT simulations have been compared to experimental data for different radionuclides and collimators. Results of the RT technique matches experimental data of collimator response very well, producing correlation coefficients higher than 0.995. Reasonable values of the parameters in the lookup table and computation speed are discussed in order to achieve high accuracy while using minimal storage space for the look-up tables. In order to achieve noise-free projection images from MC, it

  1. Risk analysis of gravity dam instability using credibility theory Monte Carlo simulation model.

    PubMed

    Xin, Cao; Chongshi, Gu

    2016-01-01

    Risk analysis of gravity dam stability involves complicated uncertainty in many design parameters and measured data. Stability failure risk ratio described jointly by probability and possibility has deficiency in characterization of influence of fuzzy factors and representation of the likelihood of risk occurrence in practical engineering. In this article, credibility theory is applied into stability failure risk analysis of gravity dam. Stability of gravity dam is viewed as a hybrid event considering both fuzziness and randomness of failure criterion, design parameters and measured data. Credibility distribution function is conducted as a novel way to represent uncertainty of influence factors of gravity dam stability. And combining with Monte Carlo simulation, corresponding calculation method and procedure are proposed. Based on a dam section, a detailed application of the modeling approach on risk calculation of both dam foundation and double sliding surfaces is provided. The results show that, the present method is feasible to be applied on analysis of stability failure risk for gravity dams. The risk assessment obtained can reflect influence of both sorts of uncertainty, and is suitable as an index value. PMID:27386264

  2. Surface tensions of linear and branched alkanes from Monte Carlo simulations using the anisotropic united atom model.

    PubMed

    Biscay, F; Ghoufi, A; Goujon, F; Lachet, V; Malfreyt, P

    2008-11-01

    The anisotropic united atoms (AUA4) model has been used for linear and branched alkanes to predict the surface tension as a function of temperature by Monte Carlo simulations. Simulations are carried out for n-alkanes ( n-C5, n-C6, n-C7, and n-C10) and for two branched C7 isomers (2,3-dimethylpentane and 2,4-dimethylpentane). Different operational expressions of the surface tension using both the thermodynamic and the mechanical definitions have been applied. The simulated surface tensions with the AUA4 model are found to be consistent within both definitions and in good agreement with experiments. PMID:18847235

  3. Pharmacokinetic modeling and Monte Carlo simulation of ondansetron following oral administration in dogs.

    PubMed

    Baek, I-H; Lee, B-Y; Kang, J; Kwon, K-I

    2015-04-01

    Ondansetron is a potent antiemetic drug that has been commonly used to treat acute and chemotherapy-induced nausea and vomiting (CINV) in dogs. The aim of this study was to perform a pharmacokinetic analysis of ondansetron in dogs following oral administration of a single dose. A single 8-mg oral dose of ondansetron (Zofran(®) ) was administered to beagles (n = 18), and the plasma concentrations of ondansetron were measured by liquid chromatography-tandem mass spectrometry. The data were analyzed by modeling approaches using ADAPT5, and model discrimination was determined by the likelihood-ratio test. The peak plasma concentration (Cmax ) was 11.5 ± 10.0 ng/mL at 1.1 ± 0.8 h. The area under the plasma concentration vs. time curve from time zero to the last measurable concentration was 15.9 ± 14.7 ng·h/mL, and the half-life calculated from the terminal phase was 1.3 ± 0.7 h. The interindividual variability of the pharmacokinetic parameters was high (coefficient of variation > 44.1%), and the one-compartment model described the pharmacokinetics of ondansetron well. The estimated plasma concentration range of the usual empirical dose from the Monte Carlo simulation was 0.1-13.2 ng/mL. These findings will facilitate determination of the optimal dose regimen for dogs with CINV. PMID:25131428

  4. Pharmacodynamic evaluation of biapenem in peritoneal fluid using population pharmacokinetic modelling and Monte Carlo simulation.

    PubMed

    Ikawa, Kazuro; Morikawa, Norifumi; Ikeda, Kayo; Ohge, Hiroki; Sueda, Taijiro

    2008-10-01

    This study evaluated the pharmacodynamics of biapenem in peritoneal fluid (PF). Biapenem (300 or 600mg) was administered via a 0.5-h infusion to 19 patients before abdominal surgery. Venous blood and PF samples were obtained after 0.5, 1, 2, 3, 4, 5 and 6h. Drug concentration data (108 plasma samples and 105 PF samples) were analysed using population pharmacokinetic modelling. A three-compartment model fits the data, with creatinine clearance (CL(Cr)) as the most significant covariate: CL (L/h)=0.036 x CL(Cr)+4.88, V1 (L)=6.95, Q2 (L/h)=2.05, V2 (L)=3.47, Q3 (L/h)=13.7 and V3 (L)=5.91, where CL is the clearance, Q2 and Q3 are the intercompartmental clearances, and V1, V2 and V3 are the volumes of distribution of the central, peripheral and peritoneal compartments, respectively. A Monte Carlo simulation using the pharmacokinetic model showed the probabilities of attaining the bactericidal exposure target (30% of the time above the minimum inhibitory concentration (T>MIC)) in PF were greater than or equal to those in plasma. In the cases of CL(Cr)=90 and 60mL/min, the site-specific pharmacodynamic-derived breakpoints (the highest MIC values at which the probabilities of target attainment in PF were >or=90%) were 2microg/mL for 300mg every 12h, 4microg/mL for biapenem 300mg every 8h (q8h) and 8microg/mL for 600mg q8h. Thus, these results should support the clinical use of biapenem as a treatment for intra-abdominal infections and facilitate the design of the dosing regimen. PMID:18602798

  5. A bone composition model for Monte Carlo x-ray transport simulations

    SciTech Connect

    Zhou Hu; Keall, Paul J.; Graves, Edward E.

    2009-03-15

    In the megavoltage energy range although the mass attenuation coefficients of different bones do not vary by more than 10%, it has been estimated that a simple tissue model containing a single-bone composition could cause errors of up to 10% in the calculated dose distribution. In the kilovoltage energy range, the variation in mass attenuation coefficients of the bones is several times greater, and the expected error from applying this type of model could be as high as several hundred percent. Based on the observation that the calcium and phosphorus compositions of bones are strongly correlated with the bone density, the authors propose an analytical formulation of bone composition for Monte Carlo computations. Elemental compositions and densities of homogeneous adult human bones from the literature were used as references, from which the calcium and phosphorus compositions were fitted as polynomial functions of bone density and assigned to model bones together with the averaged compositions of other elements. To test this model using the Monte Carlo package DOSXYZnrc, a series of discrete model bones was generated from this formula and the radiation-tissue interaction cross-section data were calculated. The total energy released per unit mass of primary photons (terma) and Monte Carlo calculations performed using this model and the single-bone model were compared, which demonstrated that at kilovoltage energies the discrepancy could be more than 100% in bony dose and 30% in soft tissue dose. Percentage terma computed with the model agrees with that calculated on the published compositions to within 2.2% for kV spectra and 1.5% for MV spectra studied. This new bone model for Monte Carlo dose calculation may be of particular importance for dosimetry of kilovoltage radiation beams as well as for dosimetry of pediatric or animal subjects whose bone composition may differ substantially from that of adult human bones.

  6. On a modified Monte-Carlo method and variable soft sphere model for rarefied binary gas mixture flow simulation

    NASA Astrophysics Data System (ADS)

    Nourazar, S. S.; Jahangiri, P.; Aboutalebi, A.; Ganjaei, A. A.; Nourazar, M.; Khadem, J.

    2011-06-01

    The effect of new terms in the improved algorithm, the modified direct simulation Monte-Carlo (MDSMC) method, is investigated by simulating a rarefied binary gas mixture flow inside a rotating cylinder. Dalton law for the partial pressures contributed by each species of the binary gas mixture is incorporated into our simulation using the MDSMC method and the direct simulation Monte-Carlo (DSMC) method. Moreover, the effect of the exponent of the cosine of deflection angle (α) in the inter-molecular collision models, the variable soft sphere (VSS) and the variable hard sphere (VHS), is investigated in our simulation. The improvement of the results of simulation is pronounced using the MDSMC method when compared with the results of the DSMC method. The results of simulation using the VSS model show some improvements on the result of simulation for the mixture temperature at radial distances close to the cylinder wall where the temperature reaches the maximum value when compared with the results using the VHS model.

  7. Spatial Correlations in Monte Carlo Criticality Simulations

    NASA Astrophysics Data System (ADS)

    Dumonteil, E.; Malvagi, F.; Zoia, A.; Mazzolo, A.; Artusio, D.; Dieudonné, C.; De Mulatier, C.

    2014-06-01

    Temporal correlations arising in Monte Carlo criticality codes have focused the attention of both developers and practitioners for a long time. Those correlations affects the evaluation of tallies of loosely coupled systems, where the system's typical size is very large compared to the diffusion/absorption length scale of the neutrons. These time correlations are closely related to spatial correlations, both variables being linked by the transport equation. Therefore this paper addresses the question of diagnosing spatial correlations in Monte Carlo criticality simulations. In that aim, we will propose a spatial correlation function well suited to Monte Carlo simulations, and show its use while simulating a fuel pin-cell. The results will be discussed, modeled and interpreted using the tools of branching processes of statistical mechanics. A mechanism called "neutron clustering", affecting simulations, will be discussed in this frame.

  8. Local-states method for the calculation of free energies in Monte Carlo simulations of lattice models

    NASA Astrophysics Data System (ADS)

    Schlijper, A. G.; van Bergen, A. R. D.; Smit, B.

    1990-01-01

    We present and demonstrate an accurate, reliable, and computationally cheap method for the calculation of free energies in Monte Carlo simulations of lattice models. Even in the critical region it yields good results with comparatively short simulation runs. The method combines upper and lower bounds on the thermodynamic limit entropy density to yield not only an accurate estimate of the free energy but a bound on the possible error as well. The method is demonstrated on the two- and three-dimensional Ising models and the three-dimensional, three-states Potts model.

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

    NASA Astrophysics Data System (ADS)

    Sohn, Ilyoup

    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

  10. Experimental results and numerical modeling of a high-performance large-scale cryopump. I. Test particle Monte Carlo simulation

    SciTech Connect

    Luo Xueli; Day, Christian; Haas, Horst; Varoutis, Stylianos

    2011-07-15

    For the torus of the nuclear fusion project ITER (originally the International Thermonuclear Experimental Reactor, but also Latin: the way), eight high-performance large-scale customized cryopumps must be designed and manufactured to accommodate the very high pumping speeds and throughputs of the fusion exhaust gas needed to maintain the plasma under stable vacuum conditions and comply with other criteria which cannot be met by standard commercial vacuum pumps. Under an earlier research and development program, a model pump of reduced scale based on active cryosorption on charcoal-coated panels at 4.5 K was manufactured and tested systematically. The present article focuses on the simulation of the true three-dimensional complex geometry of the model pump by the newly developed ProVac3D Monte Carlo code. It is shown for gas throughputs of up to 1000 sccm ({approx}1.69 Pa m{sup 3}/s at T = 0 deg. C) in the free molecular regime that the numerical simulation results are in good agreement with the pumping speeds measured. Meanwhile, the capture coefficient associated with the virtual region around the cryogenic panels and shields which holds for higher throughputs is calculated using this generic approach. This means that the test particle Monte Carlo simulations in free molecular flow can be used not only for the optimization of the pumping system but also for the supply of the input parameters necessary for the future direct simulation Monte Carlo in the full flow regime.

  11. Coupling of kinetic Monte Carlo simulations of surface reactions to transport in a fluid for heterogeneous catalytic reactor modeling

    NASA Astrophysics Data System (ADS)

    Schaefer, C.; Jansen, A. P. J.

    2013-02-01

    We have developed a method to couple kinetic Monte Carlo simulations of surface reactions at a molecular scale to transport equations at a macroscopic scale. This method is applicable to steady state reactors. We use a finite difference upwinding scheme and a gap-tooth scheme to efficiently use a limited amount of kinetic Monte Carlo simulations. In general the stochastic kinetic Monte Carlo results do not obey mass conservation so that unphysical accumulation of mass could occur in the reactor. We have developed a method to perform mass balance corrections that is based on a stoichiometry matrix and a least-squares problem that is reduced to a non-singular set of linear equations that is applicable to any surface catalyzed reaction. The implementation of these methods is validated by comparing numerical results of a reactor simulation with a unimolecular reaction to an analytical solution. Furthermore, the method is applied to two reaction mechanisms. The first is the ZGB model for CO oxidation in which inevitable poisoning of the catalyst limits the performance of the reactor. The second is a model for the oxidation of NO on a Pt(111) surface, which becomes active due to lateral interaction at high coverages of oxygen. This reaction model is based on ab initio density functional theory calculations from literature.

  12. Coupling of kinetic Monte Carlo simulations of surface reactions to transport in a fluid for heterogeneous catalytic reactor modeling.

    PubMed

    Schaefer, C; Jansen, A P J

    2013-02-01

    We have developed a method to couple kinetic Monte Carlo simulations of surface reactions at a molecular scale to transport equations at a macroscopic scale. This method is applicable to steady state reactors. We use a finite difference upwinding scheme and a gap-tooth scheme to efficiently use a limited amount of kinetic Monte Carlo simulations. In general the stochastic kinetic Monte Carlo results do not obey mass conservation so that unphysical accumulation of mass could occur in the reactor. We have developed a method to perform mass balance corrections that is based on a stoichiometry matrix and a least-squares problem that is reduced to a non-singular set of linear equations that is applicable to any surface catalyzed reaction. The implementation of these methods is validated by comparing numerical results of a reactor simulation with a unimolecular reaction to an analytical solution. Furthermore, the method is applied to two reaction mechanisms. The first is the ZGB model for CO oxidation in which inevitable poisoning of the catalyst limits the performance of the reactor. The second is a model for the oxidation of NO on a Pt(111) surface, which becomes active due to lateral interaction at high coverages of oxygen. This reaction model is based on ab initio density functional theory calculations from literature. PMID:23406093

  13. Coupling of kinetic Monte Carlo simulations of surface reactions to transport in a fluid for heterogeneous catalytic reactor modeling

    SciTech Connect

    Schaefer, C.; Jansen, A. P. J.

    2013-02-07

    We have developed a method to couple kinetic Monte Carlo simulations of surface reactions at a molecular scale to transport equations at a macroscopic scale. This method is applicable to steady state reactors. We use a finite difference upwinding scheme and a gap-tooth scheme to efficiently use a limited amount of kinetic Monte Carlo simulations. In general the stochastic kinetic Monte Carlo results do not obey mass conservation so that unphysical accumulation of mass could occur in the reactor. We have developed a method to perform mass balance corrections that is based on a stoichiometry matrix and a least-squares problem that is reduced to a non-singular set of linear equations that is applicable to any surface catalyzed reaction. The implementation of these methods is validated by comparing numerical results of a reactor simulation with a unimolecular reaction to an analytical solution. Furthermore, the method is applied to two reaction mechanisms. The first is the ZGB model for CO oxidation in which inevitable poisoning of the catalyst limits the performance of the reactor. The second is a model for the oxidation of NO on a Pt(111) surface, which becomes active due to lateral interaction at high coverages of oxygen. This reaction model is based on ab initio density functional theory calculations from literature.

  14. Bayesian Modeling of Time Trends in Component Reliability Data via Markov Chain Monte Carlo Simulation

    SciTech Connect

    D. L. Kelly

    2007-06-01

    Markov chain Monte Carlo (MCMC) techniques represent an extremely flexible and powerful approach to Bayesian modeling. This work illustrates the application of such techniques to time-dependent reliability of components with repair. The WinBUGS package is used to illustrate, via examples, how Bayesian techniques can be used for parametric statistical modeling of time-dependent component reliability. Additionally, the crucial, but often overlooked subject of model validation is discussed, and summary statistics for judging the model’s ability to replicate the observed data are developed, based on the posterior predictive distribution for the parameters of interest.

  15. Development and validation of a measurement-based source model for kilovoltage cone-beam CT Monte Carlo dosimetry simulations

    SciTech Connect

    McMillan, Kyle; McNitt-Gray, Michael; Ruan, Dan

    2013-11-15

    Purpose: The purpose of this study is to adapt an equivalent source model originally developed for conventional CT Monte Carlo dose quantification to the radiation oncology context and validate its application for evaluating concomitant dose incurred by a kilovoltage (kV) cone-beam CT (CBCT) system integrated into a linear accelerator.Methods: In order to properly characterize beams from the integrated kV CBCT system, the authors have adapted a previously developed equivalent source model consisting of an equivalent spectrum module that takes into account intrinsic filtration and an equivalent filter module characterizing the added bowtie filtration. An equivalent spectrum was generated for an 80, 100, and 125 kVp beam with beam energy characterized by half-value layer measurements. An equivalent filter description was generated from bowtie profile measurements for both the full- and half-bowtie. Equivalent source models for each combination of equivalent spectrum and filter were incorporated into the Monte Carlo software package MCNPX. Monte Carlo simulations were then validated against in-phantom measurements for both the radiographic and CBCT mode of operation of the kV CBCT system. Radiographic and CBCT imaging dose was measured for a variety of protocols at various locations within a body (32 cm in diameter) and head (16 cm in diameter) CTDI phantom. The in-phantom radiographic and CBCT dose was simulated at all measurement locations and converted to absolute dose using normalization factors calculated from air scan measurements and corresponding simulations. The simulated results were compared with the physical measurements and their discrepancies were assessed quantitatively.Results: Strong agreement was observed between in-phantom simulations and measurements. For the radiographic protocols, simulations uniformly underestimated measurements by 0.54%–5.14% (mean difference =−3.07%, SD = 1.60%). For the CBCT protocols, simulations uniformly underestimated

  16. Development and validation of a measurement-based source model for kilovoltage cone-beam CT Monte Carlo dosimetry simulations

    PubMed Central

    McMillan, Kyle; McNitt-Gray, Michael; Ruan, Dan

    2013-01-01

    Purpose: The purpose of this study is to adapt an equivalent source model originally developed for conventional CT Monte Carlo dose quantification to the radiation oncology context and validate its application for evaluating concomitant dose incurred by a kilovoltage (kV) cone-beam CT (CBCT) system integrated into a linear accelerator. Methods: In order to properly characterize beams from the integrated kV CBCT system, the authors have adapted a previously developed equivalent source model consisting of an equivalent spectrum module that takes into account intrinsic filtration and an equivalent filter module characterizing the added bowtie filtration. An equivalent spectrum was generated for an 80, 100, and 125 kVp beam with beam energy characterized by half-value layer measurements. An equivalent filter description was generated from bowtie profile measurements for both the full- and half-bowtie. Equivalent source models for each combination of equivalent spectrum and filter were incorporated into the Monte Carlo software package MCNPX. Monte Carlo simulations were then validated against in-phantom measurements for both the radiographic and CBCT mode of operation of the kV CBCT system. Radiographic and CBCT imaging dose was measured for a variety of protocols at various locations within a body (32 cm in diameter) and head (16 cm in diameter) CTDI phantom. The in-phantom radiographic and CBCT dose was simulated at all measurement locations and converted to absolute dose using normalization factors calculated from air scan measurements and corresponding simulations. The simulated results were compared with the physical measurements and their discrepancies were assessed quantitatively. Results: Strong agreement was observed between in-phantom simulations and measurements. For the radiographic protocols, simulations uniformly underestimated measurements by 0.54%–5.14% (mean difference = −3.07%, SD = 1.60%). For the CBCT protocols, simulations uniformly

  17. Co-combustion of peanut hull and coal blends: Artificial neural networks modeling, particle swarm optimization and Monte Carlo simulation.

    PubMed

    Buyukada, Musa

    2016-09-01

    Co-combustion of coal and peanut hull (PH) were investigated using artificial neural networks (ANN), particle swarm optimization, and Monte Carlo simulation as a function of blend ratio, heating rate, and temperature. The best prediction was reached by ANN61 multi-layer perception model with a R(2) of 0.99994. Blend ratio of 90 to 10 (PH to coal, wt%), temperature of 305°C, and heating rate of 49°Cmin(-1) were determined as the optimum input values and yield of 87.4% was obtained under PSO optimized conditions. The validation experiments resulted in yields of 87.5%±0.2 after three replications. Monte Carlo simulations were used for the probabilistic assessments of stochastic variability and uncertainty associated with explanatory variables of co-combustion process. PMID:27243606

  18. Combining the Monotonic Lagrangian Grid with a Direct Simulation Monte Carlo Model

    NASA Astrophysics Data System (ADS)

    Cybyk, Bohdan Z.; Oran, Elaine S.; Boris, Jay P.; Anderson, John D.

    1995-12-01

    Using the monotonic Lagrangian grid (MLG) as a data structure in the direct simulation Monte Carlo (DSMC) methodology produces an approach that automatically adjusts grid resolution to time-varying densities in the flow. The MLG algorithm is an algorithm for tracking and sorting moving particles, and it has a monotonic data structure for indexing and storing the physical attributes of the particles. The DSMC method is a direct particle simulation technique widely used in predicting rarefied flows of dilute gases. Monotonicity features of the MLG ensure that particles close in physical space are stored in adjacent array locations so that particle interactions may be restricted to a "template" of near neighbors. The MLG templates provide a time-varying grid network that automatically adapts to local number densities within the flowfield. Computational advantages and disadvantages of this new implementation are demonstrated by a series of test problems.

  19. Modulated pulse bathymetric lidar Monte Carlo simulation

    NASA Astrophysics Data System (ADS)

    Luo, Tao; Wang, Yabo; Wang, Rong; Du, Peng; Min, Xia

    2015-10-01

    A typical modulated pulse bathymetric lidar system is investigated by simulation using a modulated pulse lidar simulation system. In the simulation, the return signal is generated by Monte Carlo method with modulated pulse propagation model and processed by mathematical tools like cross-correlation and digital filter. Computer simulation results incorporating the modulation detection scheme reveal a significant suppression of the water backscattering signal and corresponding target contrast enhancement. More simulation experiments are performed with various modulation and reception variables to investigate the effect of them on the bathymetric system performance.

  20. Fast Lattice Monte Carlo Simulations of Polymers

    NASA Astrophysics Data System (ADS)

    Wang, Qiang; Zhang, Pengfei

    2014-03-01

    The recently proposed fast lattice Monte Carlo (FLMC) simulations (with multiple occupancy of lattice sites (MOLS) and Kronecker δ-function interactions) give much faster/better sampling of configuration space than both off-lattice molecular simulations (with pair-potential calculations) and conventional lattice Monte Carlo simulations (with self- and mutual-avoiding walk and nearest-neighbor interactions) of polymers.[1] Quantitative coarse-graining of polymeric systems can also be performed using lattice models with MOLS.[2] Here we use several model systems, including polymer melts, solutions, blends, as well as confined and/or grafted polymers, to demonstrate the great advantages of FLMC simulations in the study of equilibrium properties of polymers.

  1. The Monte Carlo Integration Computer as an Instructional Model for the Simulation of Equilibrium and Kinetic Chemical Processes: The Development and Evaluation of a Teaching Aid.

    ERIC Educational Resources Information Center

    Wood, Dean Arthur

    A special purpose digital computer which utilizes the Monte Carlo integration method of obtaining simulations of chemical processes was developed and constructed. The computer, designated as the Monte Carlo Integration Computer (MCIC), was designed as an instructional model for the illustration of kinetic and equilibrium processes, and was…

  2. Analysis of polytype stability in PVT grown silicon carbide single crystal using competitive lattice model Monte Carlo simulations

    NASA Astrophysics Data System (ADS)

    Guo, Hui-Jun; Huang, Wei; Liu, Xi; Gao, Pan; Zhuo, Shi-Yi; Xin, Jun; Yan, Cheng-Feng; Zheng, Yan-Qing; Yang, Jian-Hua; Shi, Er-Wei

    2014-09-01

    Polytype stability is very important for high quality SiC single crystal growth. However, the growth conditions for the 4H, 6H and 15R polytypes are similar, and the mechanism of polytype stability is not clear. The kinetics aspects, such as surface-step nucleation, are important. The kinetic Monte Carlo method is a common tool to study surface kinetics in crystal growth. However, the present lattice models for kinetic Monte Carlo simulations cannot solve the problem of the competitive growth of two or more lattice structures. In this study, a competitive lattice model was developed for kinetic Monte Carlo simulation of the competition growth of the 4H and 6H polytypes of SiC. The site positions are fixed at the perfect crystal lattice positions without any adjustment of the site positions. Surface steps on seeds and large ratios of diffusion/deposition have positive effects on the 4H polytype stability. The 3D polytype distribution in a physical vapor transport method grown SiC ingot showed that the facet preserved the 4H polytype even if the 6H polytype dominated the growth surface. The theoretical and experimental results of polytype growth in SiC suggest that retaining the step growth mode is an important factor to maintain a stable single 4H polytype during SiC growth.

  3. Modeling of an industrial environment: external dose calculations based on Monte Carlo simulations of photon transport.

    PubMed

    Kis, Zoltán; Eged, Katalin; Voigt, Gabriele; Meckbach, Reinhard; Müller, Heinz

    2004-02-01

    External gamma exposures from radionuclides deposited on surfaces usually result in the major contribution to the total dose to the public living in urban-industrial environments. The aim of the paper is to give an example for a calculation of the collective and averted collective dose due to the contamination and decontamination of deposition surfaces in a complex environment based on the results of Monte Carlo simulations. The shielding effects of the structures in complex and realistic industrial environments (where productive and/or commercial activity is carried out) were computed by the use of Monte Carlo method. Several types of deposition areas (walls, roofs, windows, streets, lawn) were considered. Moreover, this paper gives a summary about the time dependence of the source strengths relative to a reference surface and a short overview about the mechanical and chemical intervention techniques which can be applied in this area. An exposure scenario was designed based on a survey of average German and Hungarian supermarkets. In the first part of the paper the air kermas per photon per unit area due to each specific deposition area contaminated by 137Cs were determined at several arbitrary locations in the whole environment relative to a reference value of 8.39 x 10(-4) pGy per gamma m(-2). The calculations provide the possibility to assess the whole contribution of a specific deposition area to the collective dose, separately. According to the current results, the roof and the paved area contribute the most part (approximately 92%) to the total dose in the first year taking into account the relative contamination of the deposition areas. When integrating over 10 or 50 y, these two surfaces remain the most important contributors as well but the ratio will increasingly be shifted in favor of the roof. The decontamination of the roof and the paved area results in about 80-90% of the total averted collective dose in each calculated time period (1, 10, 50 y

  4. Analytical model of the binary multileaf collimator of tomotherapy for Monte Carlo simulations

    NASA Astrophysics Data System (ADS)

    Sterpin, E.; Salvat, F.; Olivera, G. H.; Vynckier, S.

    2008-02-01

    Helical Tomotherapy (HT) delivers intensity-modulated radiotherapy by the means of many configurations of the binary multi-leaf collimator (MLC). The aim of the present study was to devise a method, which we call the 'transfer function' (TF) method, to perform the transport of particles through the MLC much faster than the time consuming Monte Carlo (MC) simulation and with no significant loss of accuracy. The TF method consists of calculating, for each photon in the phase-space file, the attenuation factor for each leaf (up to three) that the photon passes, assuming straight propagation through closed leaves, and storing these factors in a modified phase-space file. To account for the transport through the MLC in a given configuration, the weight of a photon is simply multiplied by the attenuation factors of the leaves that are intersected by the photon ray and are closed. The TF method was combined with the PENELOPE MC code, and validated with measurements for the three static field sizes available (40×5, 40×2.5 and 40×1 cm2) and for some MLC patterns. The TF method allows a large reduction in computation time, without introducing appreciable deviations from the result of full MC simulations.

  5. Realistic PET Monte Carlo Simulation With Pixelated Block Detectors, Light Sharing, Random Coincidences and Dead-Time Modeling

    PubMed Central

    Guérin, Bastein; Fakhri, Georges El

    2008-01-01

    We have developed and validated a realistic simulation of random coincidences, pixelated block detectors, light sharing among crystal elements and dead-time in 2D and 3D positron emission tomography (PET) imaging based on the SimSET Monte Carlo simulation software. Our simulation was validated by comparison to a Monte Carlo transport code widely used for PET modeling, GATE, and to measurements made on a PET scanner. Methods We have modified the SimSET software to allow independent tracking of single photons in the object and septa while taking advantage of existing voxel based attenuation and activity distributions and validated importance sampling techniques implemented in SimSET. For each single photon interacting in the detector, the energy-weighted average of interaction points was computed, a blurring model applied to account for light sharing and the associated crystal identified. Detector dead-time was modeled in every block as a function of the local single rate using a variance reduction technique. Electronic dead-time was modeled for the whole scanner as a function of the prompt coincidences rate. Energy spectra predicted by our simulation were compared to GATE. NEMA NU-2 2001 performance tests were simulated with the new simulation as well as with SimSET and compared to measurements made on a Discovery ST (DST) camera. Results Errors in simulated spatial resolution (full width at half maximum, FWHM) were 5.5% (6.1%) in 2D (3D) with the new simulation, compared with 42.5% (38.2%) with SimSET. Simulated (measured) scatter fractions were 17.8% (21.3%) in 2D and 45.8% (45.2%) in 3D. Simulated and measured sensitivities agreed within 2.3 % in 2D and 3D for all planes and simulated and acquired count rate curves (including NEC) were within 12.7% in 2D in the [0: 80 kBq/cc] range and in 3D in the [0: 35 kBq/cc] range. The new simulation yielded significantly more realistic singles’ and coincidences’ spectra, spatial resolution, global sensitivity and lesion

  6. Simulation of the full-core pin-model by JMCT Monte Carlo neutron-photon transport code

    SciTech Connect

    Li, D.; Li, G.; Zhang, B.; Shu, L.; Shangguan, D.; Ma, Y.; Hu, Z.

    2013-07-01

    Since the large numbers of cells over a million, the tallies over a hundred million and the particle histories over ten billion, the simulation of the full-core pin-by-pin model has become a real challenge for the computers and the computational methods. On the other hand, the basic memory of the model has exceeded the limit of a single CPU, so the spatial domain and data decomposition must be considered. JMCT (J Monte Carlo Transport code) has successful fulfilled the simulation of the full-core pin-by-pin model by the domain decomposition and the nested parallel computation. The k{sub eff} and flux of each cell are obtained. (authors)

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

    SciTech Connect

    Shang, Yu; Lin, Yu; Yu, Guoqiang; Li, Ting; Chen, Lei; Toborek, Michal

    2014-05-12

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

  8. Evaluation of the interindividual human variation in bioactivation of methyleugenol using physiologically based kinetic modeling and Monte Carlo simulations

    SciTech Connect

    Al-Subeihi, Ala' A.A.; Alhusainy, Wasma; Kiwamoto, Reiko; Spenkelink, Bert; Bladeren, Peter J. van; Rietjens, Ivonne M.C.M.; Punt, Ans

    2015-03-01

    The present study aims at predicting the level of formation of the ultimate carcinogenic metabolite of methyleugenol, 1′-sulfooxymethyleugenol, in the human population by taking variability in key bioactivation and detoxification reactions into account using Monte Carlo simulations. Depending on the metabolic route, variation was simulated based on kinetic constants obtained from incubations with a range of individual human liver fractions or by combining kinetic constants obtained for specific isoenzymes with literature reported human variation in the activity of these enzymes. The results of the study indicate that formation of 1′-sulfooxymethyleugenol is predominantly affected by variation in i) P450 1A2-catalyzed bioactivation of methyleugenol to 1′-hydroxymethyleugenol, ii) P450 2B6-catalyzed epoxidation of methyleugenol, iii) the apparent kinetic constants for oxidation of 1′-hydroxymethyleugenol, and iv) the apparent kinetic constants for sulfation of 1′-hydroxymethyleugenol. Based on the Monte Carlo simulations a so-called chemical-specific adjustment factor (CSAF) for intraspecies variation could be derived by dividing different percentiles by the 50th percentile of the predicted population distribution for 1′-sulfooxymethyleugenol formation. The obtained CSAF value at the 90th percentile was 3.2, indicating that the default uncertainty factor of 3.16 for human variability in kinetics may adequately cover the variation within 90% of the population. Covering 99% of the population requires a larger uncertainty factor of 6.4. In conclusion, the results showed that adequate predictions on interindividual human variation can be made with Monte Carlo-based PBK modeling. For methyleugenol this variation was observed to be in line with the default variation generally assumed in risk assessment. - Highlights: • Interindividual human differences in methyleugenol bioactivation were simulated. • This was done using in vitro incubations, PBK modeling

  9. 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.

  10. Transmission calculation by empirical numerical model and Monte Carlo simulation in high energy proton radiography of thick objects

    NASA Astrophysics Data System (ADS)

    Zheng, Na; Xu, Hai-Bo

    2015-10-01

    An empirical numerical model that includes nuclear absorption, multiple Coulomb scattering and energy loss is presented for the calculation of transmission through thick objects in high energy proton radiography. In this numerical model the angular distributions are treated as Gaussians in the laboratory frame. A Monte Carlo program based on the Geant4 toolkit was developed and used for high energy proton radiography experiment simulations and verification of the empirical numerical model. The two models are used to calculate the transmission fraction of carbon and lead step-wedges in proton radiography at 24 GeV/c, and to calculate radial transmission of the French Test Object in proton radiography at 24 GeV/c with different angular cuts. It is shown that the results of the two models agree with each other, and an analysis of the slight differences is given. Supported by NSAF (11176001) and Science and Technology Developing Foundation of China Academy of Engineering Physics (2012A0202006)

  11. Modeling of the elongation and retraction of Escherichia coli P pili under strain by Monte Carlo simulations.

    PubMed

    Björnham, Oscar; Axner, Ove; Andersson, Magnus

    2008-04-01

    P pili are fimbrial adhesion organelles expressed by uropathogenic Escherichia coli in the upper urinary tract. They constitute a stiff helix-like polymer consisting of a number of subunits joined by head-to-tail bonds. The elongation and retraction properties of individual P pili exposed to strain have been modeled by Monte Carlo (MC) simulations. The simulation model is based upon a three-state energy landscape that deforms under an applied force. Bond opening and closure are modeled by Bells theory while the elongation of the linearized part of the pilus is described by a worm-like chain model. The simulations are compared with measurements made by force measuring optical tweezers. It was found that the simulations can reproduce pili elongation as well as retraction, under both equilibrium and dynamic conditions, including entropic effects. It is shown that the simulations allow for an assessment of various model parameters, e.g. the unfolding force, energy barrier heights, and various distances in the energy landscape, including their stochastic spread that analytical models are unable to do. The results demonstrate that MC simulations are useful to model elongation and retraction properties of P pili, and therefore presumably also other types of pili, exposed to strain and/or stress. MC simulations are particularly suited for description of helix-like pili since these have an intricate self-regulating mechanical elongation behavior that makes analytical descriptions non-trivial when dynamic processes are studied, or if additional interactions in the rod or the behavior of the adhesion tip needs to be modeled. PMID:17926029

  12. An improved dynamic Monte Carlo model coupled with Poisson equation to simulate the performance of organic photovoltaic devices

    NASA Astrophysics Data System (ADS)

    Meng, Lingyi; Wang, Dong; Li, Qikai; Yi, Yuanping; Brédas, Jean-Luc; Shuai, Zhigang

    2011-03-01

    We describe a new dynamic Monte Carlo model to simulate the operation of a polymer-blend solar cell; this model provides major improvements with respect to the one we developed earlier [J. Phys. Chem. B 114, 36 (2010)] by incorporating the Poisson equation and a charge thermoactivation mechanism. The advantage of the present approach is its capacity to deal with a nonuniform electrostatic potential that dynamically depends on the charge distribution. In this way, the unbalance in electron and hole mobilities and the space-charge induced potential distribution can be treated explicitly. Simulations reproduce well the experimental I-V curve in the dark and the open-circuit voltage under illumination of a polymer-blend solar cell. The dependence of the photovoltaic performance on the difference in electron and hole mobilities is discussed.

  13. On the use of Monte Carlo simulations to model transport of positrons in gases and liquids.

    PubMed

    Petrović, Zoran Lj; Marjanović, Srdjan; Dujko, Saša; Banković, Ana; Malović, Gordana; Buckman, Stephen; Garcia, Gustavo; White, Ron; Brunger, Michael

    2014-01-01

    In this paper we make a parallel between the swarm method in physics of ionized gases and modeling of positrons in radiation therapy and diagnostics. The basic idea is to take advantage of the experience gained in the past with electron swarms and to use it in establishing procedures of modeling positron diagnostics and therapy based on the well-established experimental binary collision data. In doing so we discuss the application of Monte Carlo technique for positrons in the same manner as used previously for electron swarms, we discuss the role of complete cross section sets (complete in terms of number, momentum and energy balance and tested against measured swarm parameters), we discuss the role of benchmarks and how to choose benchmarks for electrons that may perhaps be a subject to experimental verification. Finally we show some samples of positron trajectories together with secondary electrons that were established solely on the basis of accurate binary cross sections and also how those may be used in modeling of both gas filled traps and living organisms. PMID:23466009

  14. Monte Carlo simulation of electron drift velocity in low-temperature-grown gallium arsenide in a Schottky-barrier model

    NASA Astrophysics Data System (ADS)

    Arifin, P.; Goldys, E.; Tansley, T. L.

    1995-08-01

    We present a method of simulating the electron transport in low-temperature-grown GaAs by the Monte Carlo method. Low-temperature-grown GaAs contains microscopic inclusions of As and these inhomogeneities render impossible the standard Monte Carlo mobility simulations. Our method overcomes this difficulty and allows the quantitative prediction of electron transport on the basis of principal microscopic material parameters, including the impurity and the precipitate concentrations and the precipitate size. The adopted approach involves simulations of a single electron trajectory in real space, while the influence of As precipitates on the GaAs matrix is treated in the framework of a Schottky-barrier model. The validity of this approach is verified by evaluation of the drift velocity in homogeneous GaAs where excellent agreement with other workers' results is reached. The drift velocity as a function of electric field in low-temperature-grown GaAs is calculated for a range of As precipitate concentrations. Effect of compensation ratio on drift velocity characteristics is also investigated. It is found that the drift velocity is reduced and the electric field at which the onset of the negative differential mobility occurs increases as the precipitate concentration increases. Both these effects are related to the reduced electron mean free path in the presence of precipitates. Additionally, comparatively high low-field electron mobilities in this material are theoretically explained.

  15. 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…

  16. Evaluation of the interindividual human variation in bioactivation of methyleugenol using physiologically based kinetic modeling and Monte Carlo simulations.

    PubMed

    Al-Subeihi, Ala A A; Alhusainy, Wasma; Kiwamoto, Reiko; Spenkelink, Bert; van Bladeren, Peter J; Rietjens, Ivonne M C M; Punt, Ans

    2015-03-01

    The present study aims at predicting the level of formation of the ultimate carcinogenic metabolite of methyleugenol, 1'-sulfooxymethyleugenol, in the human population by taking variability in key bioactivation and detoxification reactions into account using Monte Carlo simulations. Depending on the metabolic route, variation was simulated based on kinetic constants obtained from incubations with a range of individual human liver fractions or by combining kinetic constants obtained for specific isoenzymes with literature reported human variation in the activity of these enzymes. The results of the study indicate that formation of 1'-sulfooxymethyleugenol is predominantly affected by variation in i) P450 1A2-catalyzed bioactivation of methyleugenol to 1'-hydroxymethyleugenol, ii) P450 2B6-catalyzed epoxidation of methyleugenol, iii) the apparent kinetic constants for oxidation of 1'-hydroxymethyleugenol, and iv) the apparent kinetic constants for sulfation of 1'-hydroxymethyleugenol. Based on the Monte Carlo simulations a so-called chemical-specific adjustment factor (CSAF) for intraspecies variation could be derived by dividing different percentiles by the 50th percentile of the predicted population distribution for 1'-sulfooxymethyleugenol formation. The obtained CSAF value at the 90th percentile was 3.2, indicating that the default uncertainty factor of 3.16 for human variability in kinetics may adequately cover the variation within 90% of the population. Covering 99% of the population requires a larger uncertainty factor of 6.4. In conclusion, the results showed that adequate predictions on interindividual human variation can be made with Monte Carlo-based PBK modeling. For methyleugenol this variation was observed to be in line with the default variation generally assumed in risk assessment. PMID:25549870

  17. A relativistic Monte Carlo binary collision model for use in plasma particle simulation codes

    SciTech Connect

    Procassini, R.J.; Birdsall, C.K.; Morse, E.C.; Cohen, B.I.

    1987-05-14

    Particle simulations of plasma physics phenomena employ far fewer particles than the systems which are being simulated, owing to the limited speed and memory capacity of even the most powerful supercomputers. If the simulation consists of point particles in a gridless domain, then the combination of the small number of particles in a Debye sphere and the possibility of zero-impact-parameters, large-angle scattering results in a significant enhancement of fluctuation phenomena such as collisions. Collisional processes in a simulation may be difficult because of disparate time scales. A comparison of the relevant physical time scales of the system that is being simulated usually yields a large range of values. For instance, the grid-cell transit time is usually several orders of magnitude smaller than the 90/sup 0/ scattering time. Much of the physical phenomena of interest in the simulation are due to these long-time-scale collisional processes, but short-time-scale processes (such as particle bounce times in a mirror or tokamak) must be adequately resolved if the plasma dielectric response and the plasma potential are to be accurately determined. The following paper outlines the physics and operation of the binary collision model within the electrostatic code and presents the results of computer simulations of velocity space transport which were run to test the accuracy of the model. Also discussed are the timing statistics for the collision package relative to the other major physics packages in the code, as well as recommendations on the frequency of use of the collision package within the simulation sequence.

  18. Simulation of germanium detector calibration using the Monte Carlo method: comparison between point and surface source models.

    PubMed

    Ródenas, J; Burgos, M C; Zarza, I; Gallardo, S

    2005-01-01

    Simulation of detector calibration using the Monte Carlo method is very convenient. The computational calibration procedure using the MCNP code was validated by comparing results of the simulation with laboratory measurements. The standard source used for this validation was a disc-shaped filter where fission and activation products were deposited. Some discrepancies between the MCNP results and laboratory measurements were attributed to the point source model adopted. In this paper, the standard source has been simulated using both point and surface source models. Results from both models are compared with each other as well as with experimental measurements. Two variables, namely, the collimator diameter and detector-source distance have been considered in the comparison analysis. The disc model is seen to be a better model as expected. However, the point source model is good for large collimator diameter and also when the distance from detector to source increases, although for smaller sizes of the collimator and lower distances a surface source model is necessary. PMID:16604596

  19. Monte Carlo simulated coronary angiograms of realistic anatomy and pathology models

    NASA Astrophysics Data System (ADS)

    Kyprianou, Iacovos S.; Badal, Andreu; Badano, Aldo; Banh, Diemphuc; Freed, Melanie; Myers, Kyle J.; Thompson, Laura

    2007-03-01

    We have constructed a fourth generation anthropomorphic phantom which, in addition to the realistic description of the human anatomy, includes a coronary artery disease model. A watertight version of the NURBS-based Cardiac-Torso (NCAT) phantom was generated by converting the individual NURBS surfaces of each organ into closed, manifold and non-self-intersecting tessellated surfaces. The resulting 330 surfaces of the phantom organs and tissues are now comprised of ~5×10 6 triangles whose size depends on the individual organ surface normals. A database of the elemental composition of each organ was generated, and material properties such as density and scattering cross-sections were defined using PENELOPE. A 300 μm resolution model of a heart with 55 coronary vessel segments was constructed by fitting smooth triangular meshes to a high resolution cardiac CT scan we have segmented, and was consequently registered inside the torso model. A coronary artery disease model that uses hemodynamic properties such as blood viscosity and resistivity was used to randomly place plaque within the artery tree. To generate x-ray images of the aforementioned phantom, our group has developed an efficient Monte Carlo radiation transport code based on the subroutine package PENELOPE, which employs an octree spatial data-structure that stores and traverses the phantom triangles. X-ray angiography images were generated under realistic imaging conditions (90 kVp, 10° Wanode spectra with 3 mm Al filtration, ~5×10 11 x-ray source photons, and 10% per volume iodine contrast in the coronaries). The images will be used in an optimization algorithm to select the optimal technique parameters for a variety of imaging tasks.

  20. Modeling the effects and uncertainties of contaminated sediment remediation scenarios in a Norwegian fjord by Markov chain Monte Carlo simulation.

    PubMed

    Saloranta, Tuomo M; Armitage, James M; Haario, Heikki; Naes, Kristoffer; Cousins, Ian T; Barton, David N

    2008-01-01

    Multimedia environmental fate models are useful tools to investigate the long-term impacts of remediation measures designed to alleviate potential ecological and human health concerns in contaminated areas. Estimating and communicating the uncertainties associated with the model simulations is a critical task for demonstrating the transparency and reliability of the results. The Extended Fourier Amplitude Sensitivity Test(Extended FAST) method for sensitivity analysis and Bayesian Markov chain Monte Carlo (MCMC) method for uncertainty analysis and model calibration have several advantages over methods typically applied for multimedia environmental fate models. Most importantly, the simulation results and their uncertainties can be anchored to the available observations and their uncertainties. We apply these techniques for simulating the historical fate of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) in the Grenland fjords, Norway, and for predicting the effects of different contaminated sediment remediation (capping) scenarios on the future levels of PCDD/Fs in cod and crab therein. The remediation scenario simulations show that a significant remediation effect can first be seen when significant portions of the contaminated sediment areas are cleaned up, and that increase in capping area leads to both earlier achievement of good fjord status and narrower uncertainty in the predicted timing for this. PMID:18350897

  1. A High-Resolution Spatially Explicit Monte-Carlo Simulation Approach to Commercial and Residential Electricity and Water Demand Modeling

    SciTech Connect

    Morton, April M; McManamay, Ryan A; Nagle, Nicholas N; Piburn, Jesse O; Stewart, Robert N; Surendran Nair, Sujithkumar

    2016-01-01

    Abstract As urban areas continue to grow and evolve in a world of increasing environmental awareness, the need for high resolution spatially explicit estimates for energy and water demand has become increasingly important. Though current modeling efforts mark significant progress in the effort to better understand the spatial distribution of energy and water consumption, many are provided at a course spatial resolution or rely on techniques which depend on detailed region-specific data sources that are not publicly available for many parts of the U.S. Furthermore, many existing methods do not account for errors in input data sources and may therefore not accurately reflect inherent uncertainties in model outputs. We propose an alternative and more flexible Monte-Carlo simulation approach to high-resolution residential and commercial electricity and water consumption modeling that relies primarily on publicly available data sources. The method s flexible data requirement and statistical framework ensure that the model is both applicable to a wide range of regions and reflective of uncertainties in model results. Key words: Energy Modeling, Water Modeling, Monte-Carlo Simulation, Uncertainty Quantification Acknowledgment This manuscript has been authored by employees of UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the U.S. Department of Energy. Accordingly, the United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes.

  2. Monte Carlo simulations of two-dimensional Hubbard models with string bond tensor-network states

    NASA Astrophysics Data System (ADS)

    Song, Jeong-Pil; Wee, Daehyun; Clay, R. T.

    2015-03-01

    We study charge- and spin-ordered states in the two-dimensional extended Hubbard model on a triangular lattice at 1/3 filling. While the nearest-neighbor Coulomb repulsion V induces charge-ordered states, the competition between on-site U and nearest-neighbor V interactions lead to quantum phase transitions to an antiferromagnetic spin-ordered phase with honeycomb charge order. In order to avoid the fermion sign problem and handle frustrations here we use quantum Monte Carlo methods with the string-bond tensor network ansatz for fermionic systems in two dimensions. We determine the phase boundaries of the several spin- and charge-ordered states and show a phase diagram in the on-site U and the nearest-neighbor V plane. The numerical accuracy of the method is compared with exact diagonalization results in terms of the size of matrices D. We also test the use of lattice symmetries to improve the string-bond ansatz. Work at Mississippi State University was supported by the US Department of Energy grant DE-FG02-06ER46315.

  3. Reliability of Monte Carlo simulations in modeling neutron yields from a shielded fission source

    NASA Astrophysics Data System (ADS)

    McArthur, Matthew S.; Rees, Lawrence B.; Czirr, J. Bart

    2016-08-01

    Using the combination of a neutron-sensitive 6Li glass scintillator detector with a neutron-insensitive 7Li glass scintillator detector, we are able to make an accurate measurement of the capture rate of fission neutrons on 6Li. We used this detector with a 252Cf neutron source to measure the effects of both non-borated polyethylene and 5% borated polyethylene shielding on detection rates over a range of shielding thicknesses. Both of these measurements were compared with MCNP calculations to determine how well the calculations reproduced the measurements. When the source is highly shielded, the number of interactions experienced by each neutron prior to arriving at the detector is large, so it is important to compare Monte Carlo modeling with actual experimental measurements. MCNP reproduces the data fairly well, but it does generally underestimate detector efficiency both with and without polyethylene shielding. For non-borated polyethylene it underestimates the measured value by an average of 8%. This increases to an average of 11% for borated polyethylene.

  4. Assessment of high-fidelity collision models in the direct simulation Monte Carlo method

    NASA Astrophysics Data System (ADS)

    Weaver, Andrew B.

    Advances in computer technology over the decades has allowed for more complex physics to be modeled in the DSMC method. Beginning with the first paper on DSMC in 1963, 30,000 collision events per hour were simulated using a simple hard sphere model. Today, more than 10 billion collision events can be simulated per hour for the same problem. Many new and more physically realistic collision models such as the Lennard-Jones potential and the forced harmonic oscillator model have been introduced into DSMC. However, the fact that computer resources are more readily available and higher-fidelity models have been developed does not necessitate their usage. It is important to understand how such high-fidelity models affect the output quantities of interest in engineering applications. The effect of elastic and inelastic collision models on compressible Couette flow, ground-state atomic oxygen transport properties, and normal shock waves have therefore been investigated. Recommendations for variable soft sphere and Lennard-Jones model parameters are made based on a critical review of recent ab-initio calculations and experimental measurements of transport properties.

  5. Phase transition in ultrathin magnetic films with long-range interactions: Monte Carlo simulation of the anisotropic Heisenberg model

    NASA Astrophysics Data System (ADS)

    Rapini, M.; Dias, R. A.; Costa, B. V.

    2007-01-01

    Ultrathin magnetic films can be modeled as an anisotropic Heisenberg model with long-range dipolar interactions. It is believed that the phase diagram presents three phases: An ordered ferromagnetic phase (I), a phase characterized by a change from out-of-plane to in-plane in the magnetization (II), and a high-temperature paramagnetic phase (III). It is claimed that the border lines from phase I to III and II to III are of second order and from I to II is first order. In the present work we have performed a very careful Monte Carlo simulation of the model. Our results strongly support that the line separating phases II and III is of the BKT type.

  6. Kinetic Monte Carlo simulations of travelling pulses and spiral waves in the lattice Lotka-Volterra model

    NASA Astrophysics Data System (ADS)

    Makeev, Alexei G.; Kurkina, Elena S.; Kevrekidis, Ioannis G.

    2012-06-01

    Kinetic Monte Carlo simulations are used to study the stochastic two-species Lotka-Volterra model on a square lattice. For certain values of the model parameters, the system constitutes an excitable medium: travelling pulses and rotating spiral waves can be excited. Stable solitary pulses travel with constant (modulo stochastic fluctuations) shape and speed along a periodic lattice. The spiral waves observed persist sometimes for hundreds of rotations, but they are ultimately unstable and break-up (because of fluctuations and interactions between neighboring fronts) giving rise to complex dynamic behavior in which numerous small spiral waves rotate and interact with each other. It is interesting that travelling pulses and spiral waves can be exhibited by the model even for completely immobile species, due to the non-local reaction kinetics.

  7. Integrated Cost and Schedule using Monte Carlo Simulation of a CPM Model - 12419

    SciTech Connect

    Hulett, David T.; Nosbisch, Michael R.

    2012-07-01

    . - Good-quality risk data that are usually collected in risk interviews of the project team, management and others knowledgeable in the risk of the project. The risks from the risk register are used as the basis of the risk data in the risk driver method. The risk driver method is based in the fundamental principle that identifiable risks drive overall cost and schedule risk. - A Monte Carlo simulation software program that can simulate schedule risk, burn WM2012 rate risk and time-independent resource risk. The results include the standard histograms and cumulative distributions of possible cost and time results for the project. However, by simulating both cost and time simultaneously we can collect the cost-time pairs of results and hence show the scatter diagram ('football chart') that indicates the joint probability of finishing on time and on budget. Also, we can derive the probabilistic cash flow for comparison with the time-phased project budget. Finally the risks to schedule completion and to cost can be prioritized, say at the P-80 level of confidence, to help focus the risk mitigation efforts. If the cost and schedule estimates including contingency reserves are not acceptable to the project stakeholders the project team should conduct risk mitigation workshops and studies, deciding which risk mitigation actions to take, and re-run the Monte Carlo simulation to determine the possible improvement to the project's objectives. Finally, it is recommended that the contingency reserves of cost and of time, calculated at a level that represents an acceptable degree of certainty and uncertainty for the project stakeholders, be added as a resource-loaded activity to the project schedule for strategic planning purposes. The risk analysis described in this paper is correct only for the current plan, represented by the schedule. The project contingency reserve of time and cost that are the main results of this analysis apply if that plan is to be followed. Of course project

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

    NASA Technical Reports Server (NTRS)

    Hsu, Andrew T.

    1992-01-01

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

  9. Monte Carlo simulation of the enantioseparation process

    NASA Astrophysics Data System (ADS)

    Bustos, V. A.; Acosta, G.; Gomez, M. R.; Pereyra, V. D.

    2012-09-01

    By means of Monte Carlo simulation, a study of enantioseparation by capillary electrophoresis has been carried out. A simplified system consisting of two enantiomers S (R) and a selector chiral C, which reacts with the enantiomers to form complexes RC (SC), has been considered. The dependence of Δμ (enantioseparation) with the concentration of chiral selector and with temperature have been analyzed by simulation. The effect of the binding constant and the charge of the complexes are also analyzed. The results are qualitatively satisfactory, despite the simplicity of the model.

  10. Leasing policy and the rate of petroleum development: analysis with a Monte Carlo simulation model

    SciTech Connect

    Abbey, D; Bivins, R

    1982-03-01

    The study has two objectives: first, to consider whether alternative leasing systems are desirable to speed the rate of oil and gas exploration and development in frontier basins; second, to evaluate the Petroleum Activity and Decision Simulation model developed by the US Department of the Interior for economic and land use planning and for policy analysis. Analysis of the model involved structural variation of the geology, exploration, and discovery submodels and also involved a formal sensitivity analysis using the Latin Hypercube Sampling Method. We report the rate of exploration, discovery, and petroleum output under a variety of price, leasing policy, and tax regimes.

  11. Calculation of dose distribution in compressible breast tissues using finite element modeling, Monte Carlo simulation and thermoluminescence dosimeters.

    PubMed

    Mohammadyari, Parvin; Faghihi, Reza; Mosleh-Shirazi, Mohammad Amin; Lotfi, Mehrzad; Hematiyan, Mohammad Rahim; Koontz, Craig; Meigooni, Ali S

    2015-12-01

    Compression is a technique to immobilize the target or improve the dose distribution within the treatment volume during different irradiation techniques such as AccuBoost(®) brachytherapy. However, there is no systematic method for determination of dose distribution for uncompressed tissue after irradiation under compression. In this study, the mechanical behavior of breast tissue between compressed and uncompressed states was investigated. With that, a novel method was developed to determine the dose distribution in uncompressed tissue after irradiation of compressed breast tissue. Dosimetry was performed using two different methods, namely, Monte Carlo simulations using the MCNP5 code and measurements using thermoluminescent dosimeters (TLD). The displacement of the breast elements was simulated using a finite element model and calculated using ABAQUS software. From these results, the 3D dose distribution in uncompressed tissue was determined. The geometry of the model was constructed from magnetic resonance images of six different women volunteers. The mechanical properties were modeled by using the Mooney-Rivlin hyperelastic material model. Experimental dosimetry was performed by placing the TLD chips into the polyvinyl alcohol breast equivalent phantom. The results determined that the nodal displacements, due to the gravitational force and the 60 Newton compression forces (with 43% contraction in the loading direction and 37% expansion in the orthogonal direction) were determined. Finally, a comparison of the experimental data and the simulated data showed agreement within 11.5%  ±  5.9%. PMID:26572554

  12. Calculation of dose distribution in compressible breast tissues using finite element modeling, Monte Carlo simulation and thermoluminescence dosimeters

    NASA Astrophysics Data System (ADS)

    Mohammadyari, Parvin; Faghihi, Reza; Mosleh-Shirazi, Mohammad Amin; Lotfi, Mehrzad; Rahim Hematiyan, Mohammad; Koontz, Craig; Meigooni, Ali S.

    2015-12-01

    Compression is a technique to immobilize the target or improve the dose distribution within the treatment volume during different irradiation techniques such as AccuBoost® brachytherapy. However, there is no systematic method for determination of dose distribution for uncompressed tissue after irradiation under compression. In this study, the mechanical behavior of breast tissue between compressed and uncompressed states was investigated. With that, a novel method was developed to determine the dose distribution in uncompressed tissue after irradiation of compressed breast tissue. Dosimetry was performed using two different methods, namely, Monte Carlo simulations using the MCNP5 code and measurements using thermoluminescent dosimeters (TLD). The displacement of the breast elements was simulated using a finite element model and calculated using ABAQUS software. From these results, the 3D dose distribution in uncompressed tissue was determined. The geometry of the model was constructed from magnetic resonance images of six different women volunteers. The mechanical properties were modeled by using the Mooney-Rivlin hyperelastic material model. Experimental dosimetry was performed by placing the TLD chips into the polyvinyl alcohol breast equivalent phantom. The results determined that the nodal displacements, due to the gravitational force and the 60 Newton compression forces (with 43% contraction in the loading direction and 37% expansion in the orthogonal direction) were determined. Finally, a comparison of the experimental data and the simulated data showed agreement within 11.5%  ±  5.9%.

  13. Study of optical clearing in polarization measurements by Monte Carlo simulations with anisotropic tissue-mimicking models.

    PubMed

    Chen, Dongsheng; Zeng, Nan; Wang, Yunfei; He, Honghui; Tuchin, Valery V; Ma, Hui

    2016-08-01

    We conducted Monte Carlo simulations based on anisotropic sclera-mimicking models to examine the polarization features in Mueller matrix polar decomposition (MMPD) parameters during the refractive index matching process, which is one of the major mechanisms of optical clearing. In a preliminary attempt, by changing the parameters of the models, wavelengths, and detection geometries, we demonstrate how the depolarization coefficient and retardance vary during the refractive index matching process and explain the polarization features using the average value and standard deviation of scattering numbers of the detected photons. We also study the depth-resolved polarization features during the gradual progression of the refractive index matching process. The results above indicate that the refractive index matching process increases the depth of polarization measurements and may lead to higher contrast between tissues of different anisotropies in deeper layers. MMPD-derived polarization parameters can characterize the refractive index matching process qualitatively. PMID:27240298

  14. Lifetime PCB 153 bioaccumulation and pharmacokinetics in pilot whales: Bayesian population PBPK modeling and Markov chain Monte Carlo simulations.

    PubMed

    Weijs, Liesbeth; Roach, Anthony C; Yang, Raymond S H; McDougall, Robin; Lyons, Michael; Housand, Conrad; Tibax, Detlef; Manning, Therese; Chapman, John; Edge, Katelyn; Covaci, Adrian; Blust, Ronny

    2014-01-01

    Physiologically based pharmacokinetic (PBPK) models for wild animal populations such as marine mammals typically have a high degree of model uncertainty and variability due to the scarcity of information and the embryonic nature of this field. Parameters values used in marine mammals models are usually taken from other mammalian species (e.g. rats or mice) and might not be entirely suitable to properly explain the kinetics of pollutants in marine mammals. Therefore, several parameters for a PBPK model for the bioaccumulation and pharmacokinetics of PCB 153 in long-finned pilot whales were estimated in the present study using the Bayesian approach executed with Markov chain Monte Carlo (MCMC) simulations. This method uses 'prior' information of the parameters, either from the literature or from previous model runs. The advantage is that this method uses such 'prior' parameters to calculate probability distributions to determine 'posterior' values that best explain the field observations. Those field observations or datasets were PCB 153 concentrations in blubber of long-finned pilot whales from Sandy Cape and Stanley, Tasmania, Australia. The model predictions showed an overall decrease in PCB 153 levels in blubber over the lifetime of the pilot whales. All parameters from the Sandy Cape model were updated using the Stanley dataset, except for the concentration of PCB 153 in the milk. The model presented here is a promising and preliminary start to PBPK modeling in long-finned pilot whales that would provide a basis for non-invasive studies in these protected marine mammals. PMID:24080004

  15. A variable hard sphere-based phenomenological inelastic collision model for rarefied gas flow simulations by the direct simulation Monte Carlo method

    NASA Astrophysics Data System (ADS)

    Prasanth, P. S.; Kakkassery, Jose K.; Vijayakumar, R.

    2012-04-01

    A modified phenomenological model is constructed for the simulation of rarefied flows of polyatomic non-polar gas molecules by the direct simulation Monte Carlo (DSMC) method. This variable hard sphere-based model employs a constant rotational collision number, but all its collisions are inelastic in nature and at the same time the correct macroscopic relaxation rate is maintained. In equilibrium conditions, there is equi-partition of energy between the rotational and translational modes and it satisfies the principle of reciprocity or detailed balancing. The present model is applicable for moderate temperatures at which the molecules are in their vibrational ground state. For verification, the model is applied to the DSMC simulations of the translational and rotational energy distributions in nitrogen gas at equilibrium and the results are compared with their corresponding Maxwellian distributions. Next, the Couette flow, the temperature jump and the Rayleigh flow are simulated; the viscosity and thermal conductivity coefficients of nitrogen are numerically estimated and compared with experimentally measured values. The model is further applied to the simulation of the rotational relaxation of nitrogen through low- and high-Mach-number normal shock waves in a novel way. In all cases, the results are found to be in good agreement with theoretically expected and experimentally observed values. It is concluded that the inelastic collision of polyatomic molecules can be predicted well by employing the constructed variable hard sphere (VHS)-based collision model.

  16. Accelerated GPU based SPECT Monte Carlo simulations

    NASA Astrophysics Data System (ADS)

    Garcia, Marie-Paule; Bert, Julien; Benoit, Didier; Bardiès, Manuel; Visvikis, Dimitris

    2016-06-01

    Monte Carlo (MC) modelling is widely used in the field of single photon emission computed tomography (SPECT) as it is a reliable technique to simulate very high quality scans. This technique provides very accurate modelling of the radiation transport and particle interactions in a heterogeneous medium. Various MC codes exist for nuclear medicine imaging simulations. Recently, new strategies exploiting the computing capabilities of graphical processing units (GPU) have been proposed. This work aims at evaluating the accuracy of such GPU implementation strategies in comparison to standard MC codes in the context of SPECT imaging. GATE was considered the reference MC toolkit and used to evaluate the performance of newly developed GPU Geant4-based Monte Carlo simulation (GGEMS) modules for SPECT imaging. Radioisotopes with different photon energies were used with these various CPU and GPU Geant4-based MC codes in order to assess the best strategy for each configuration. Three different isotopes were considered: 99m Tc, 111In and 131I, using a low energy high resolution (LEHR) collimator, a medium energy general purpose (MEGP) collimator and a high energy general purpose (HEGP) collimator respectively. Point source, uniform source, cylindrical phantom and anthropomorphic phantom acquisitions were simulated using a model of the GE infinia II 3/8" gamma camera. Both simulation platforms yielded a similar system sensitivity and image statistical quality for the various combinations. The overall acceleration factor between GATE and GGEMS platform derived from the same cylindrical phantom acquisition was between 18 and 27 for the different radioisotopes. Besides, a full MC simulation using an anthropomorphic phantom showed the full potential of the GGEMS platform, with a resulting acceleration factor up to 71. The good agreement with reference codes and the acceleration factors obtained support the use of GPU implementation strategies for improving computational efficiency

  17. Accelerated GPU based SPECT Monte Carlo simulations.

    PubMed

    Garcia, Marie-Paule; Bert, Julien; Benoit, Didier; Bardiès, Manuel; Visvikis, Dimitris

    2016-06-01

    Monte Carlo (MC) modelling is widely used in the field of single photon emission computed tomography (SPECT) as it is a reliable technique to simulate very high quality scans. This technique provides very accurate modelling of the radiation transport and particle interactions in a heterogeneous medium. Various MC codes exist for nuclear medicine imaging simulations. Recently, new strategies exploiting the computing capabilities of graphical processing units (GPU) have been proposed. This work aims at evaluating the accuracy of such GPU implementation strategies in comparison to standard MC codes in the context of SPECT imaging. GATE was considered the reference MC toolkit and used to evaluate the performance of newly developed GPU Geant4-based Monte Carlo simulation (GGEMS) modules for SPECT imaging. Radioisotopes with different photon energies were used with these various CPU and GPU Geant4-based MC codes in order to assess the best strategy for each configuration. Three different isotopes were considered: (99m) Tc, (111)In and (131)I, using a low energy high resolution (LEHR) collimator, a medium energy general purpose (MEGP) collimator and a high energy general purpose (HEGP) collimator respectively. Point source, uniform source, cylindrical phantom and anthropomorphic phantom acquisitions were simulated using a model of the GE infinia II 3/8" gamma camera. Both simulation platforms yielded a similar system sensitivity and image statistical quality for the various combinations. The overall acceleration factor between GATE and GGEMS platform derived from the same cylindrical phantom acquisition was between 18 and 27 for the different radioisotopes. Besides, a full MC simulation using an anthropomorphic phantom showed the full potential of the GGEMS platform, with a resulting acceleration factor up to 71. The good agreement with reference codes and the acceleration factors obtained support the use of GPU implementation strategies for improving computational

  18. Coarse-grained modeling of the intrinsically disordered protein Histatin 5 in solution: Monte Carlo simulations in combination with SAXS.

    PubMed

    Cragnell, Carolina; Durand, Dominique; Cabane, Bernard; Skepö, Marie

    2016-06-01

    Monte Carlo simulations and coarse-grained modeling have been used to analyze Histatin 5, an unstructured short cationic salivary peptide known to have anticandidical properties. The calculated scattering functions have been compared with intensity curves and the distance distribution function P(r) obtained from small angle X-ray scattering (SAXS), at both high and low salt concentrations. The aim was to achieve a molecular understanding and a physico-chemical insight of the obtained SAXS results and to gain information of the conformational changes of Histatin 5 due to altering salt content, charge distribution, and net charge. From a modeling perspective, the accuracy of the electrostatic interactions are of special interest. The used coarse-grained model was based on the primitive model in which charged hard spheres differing in charge and in size represent the ionic particles, and the solvent only enters the model through its relative permittivity. The Hamiltonian of the model comprises three different contributions: (i) excluded volumes, (ii) electrostatic, and (iii) van der Waals interactions. Even though the model can be considered as gross omitting all atomistic details, a great correspondence is obtained with the experimental results. Proteins 2016; 84:777-791. © 2016 Wiley Periodicals, Inc. PMID:26914439

  19. Development of Monte Carlo Capability for Orion Parachute Simulations

    NASA Technical Reports Server (NTRS)

    Moore, James W.

    2011-01-01

    Parachute test programs employ Monte Carlo simulation techniques to plan testing and make critical decisions related to parachute loads, rate-of-descent, or other parameters. This paper describes the development and use of a MATLAB-based Monte Carlo tool for three parachute drop test simulations currently used by NASA. The Decelerator System Simulation (DSS) is a legacy 6 Degree-of-Freedom (DOF) simulation used to predict parachute loads and descent trajectories. The Decelerator System Simulation Application (DSSA) is a 6-DOF simulation that is well suited for modeling aircraft extraction and descent of pallet-like test vehicles. The Drop Test Vehicle Simulation (DTVSim) is a 2-DOF trajectory simulation that is convenient for quick turn-around analysis tasks. These three tools have significantly different software architectures and do not share common input files or output data structures. Separate Monte Carlo tools were initially developed for each simulation. A recently-developed simulation output structure enables the use of the more sophisticated DSSA Monte Carlo tool with any of the core-simulations. The task of configuring the inputs for the nominal simulation is left to the existing tools. Once the nominal simulation is configured, the Monte Carlo tool perturbs the input set according to dispersion rules created by the analyst. These rules define the statistical distribution and parameters to be applied to each simulation input. Individual dispersed parameters are combined to create a dispersed set of simulation inputs. The Monte Carlo tool repeatedly executes the core-simulation with the dispersed inputs and stores the results for analysis. The analyst may define conditions on one or more output parameters at which to collect data slices. The tool provides a versatile interface for reviewing output of large Monte Carlo data sets while preserving the capability for detailed examination of individual dispersed trajectories. The Monte Carlo tool described in

  20. Modelling personal exposure to particulate air pollution: an assessment of time-integrated activity modelling, Monte Carlo simulation & artificial neural network approaches.

    PubMed

    McCreddin, A; Alam, M S; McNabola, A

    2015-01-01

    An experimental assessment of personal exposure to PM10 in 59 office workers was carried out in Dublin, Ireland. 255 samples of 24-h personal exposure were collected in real time over a 28 month period. A series of modelling techniques were subsequently assessed for their ability to predict 24-h personal exposure to PM10. Artificial neural network modelling, Monte Carlo simulation and time-activity based models were developed and compared. The results of the investigation showed that using the Monte Carlo technique to randomly select concentrations from statistical distributions of exposure concentrations in typical microenvironments encountered by office workers produced the most accurate results, based on 3 statistical measures of model performance. The Monte Carlo simulation technique was also shown to have the greatest potential utility over the other techniques, in terms of predicting personal exposure without the need for further monitoring data. Over the 28 month period only a very weak correlation was found between background air quality and personal exposure measurements, highlighting the need for accurate models of personal exposure in epidemiological studies. PMID:25260856

  1. Dependence on the dielectric model and pH in a synthetic helical peptide studied by Monte Carlo simulated annealing.

    PubMed

    Okamoto, Y

    1994-04-01

    Monte Carlo simulated annealing is applied to the tertiary structure prediction of a 17-residue synthetic peptide, which is known by experiment to exhibit high helical content at low pH. Two dielectric models are considered: sigmoidal distance-dependent dielectric function and a constant dielectric function (epsilon = 2). Starting from completely random initial conformations, our simulations for both dielectric models at low pH gave many helical conformations. The obtained low-energy conformations are compared with the nuclear Overhauser effect spectroscopy cross-peak data for both main chain and side chains, and it is shown that the results for the sigmoidal dielectric function are in remarkable agreement with the experimental data. The results predict the existence of two disjoint helices around residues 5-9 and 11-16, while nmr experiments imply significant alpha-helix content between residues 5 and 14. Simulations with high pH, on the other hand, hardly gave a helical conformation, which is also in accord with the experiment. These findings indicate that when side chains are charged, electrostatic interactions due to these changes play a major role in the helix stability. Our results are compared with the previous 500 ps molecular dynamics simulations of the same peptide. It is argued that simulated annealing is superior to molecular dynamics in two respects: (1) direct folding of alpha-helix from completely random initial conformations is possible for the former, whereas only unfolding of an alpha-helix can be studied by the latter; (2) while both methods predict high helix content for low pH, the results for high pH agree with experiment (low helix content) only for the former method. PMID:8186363

  2. Kinetic Monte Carlo Simulation of the oscillatory catalytic CO oxidation using a modified Ziff-Gulari-Barshad model

    NASA Astrophysics Data System (ADS)

    Sinha, Indrajit; Mukherjee, Ashim K.

    2014-03-01

    The oxidation of CO on Pt-group metal surfaces has attracted widespread attention since a long time due to its interesting oscillatory kinetics and spatiotemporal behavior. The use of STM in conjunction with other experimental data has confirmed the validity of the surface reconstruction (SR) model under low pressure and the more recent surface oxide (SO) model which is possible under sub-atmospheric pressure conditions [1]. In the SR model the surface is periodically reconstructed below a certain low critical CO-coverage and this reconstruction is lifted above a second, higher critical CO-coverage. Alternatively the SO model proposes periodic switching between a low-reactivity metallic surface and a high-reactivity oxide surface. Here we present an overview of our recent kinetic Monte Carlo (KMC) simulation studies on the oscillatory kinetics of surface catalyzed CO oxidation. Different modifications of the lattice gas Ziff-Gulari-Barshad (ZGB) model have been utilized or proposed for this purpose. First we present the effect of desorption on the ZGB reactive to poisoned irreversible phase transition in the SR model. Next we discuss our recent research on KMC simulation of the SO model. The ZGB framework is utilized to propose a new model incorporating not only the standard Langmuir-Hinshelwood (LH) mechanism, but also introducing the Mars-van Krevelen (MvK) mechanism for the surface oxide phase [5]. Phase diagrams, which are plots between long time averages of various oscillating quantities against the normalized CO pressure, show two or three transitions depending on the CO coverage critical threshold (CT) value beyond which all adsorbed oxygen atoms are converted to surface oxide.

  3. SU-E-J-145: Validation of An Analytical Model for in Vivo Range Verification Using GATE Monte Carlo Simulation in Proton Therapy

    SciTech Connect

    Lee, C; Lin, H; Chao, T; Hsiao, I; Chuang, K

    2015-06-15

    Purpose: Predicted PET images on the basis of analytical filtering approach for proton range verification has been successful developed and validated using FLUKA Monte Carlo (MC) codes and phantom measurements. The purpose of the study is to validate the effectiveness of analytical filtering model for proton range verification on GATE/GEANT4 Monte Carlo simulation codes. Methods: In this study, we performed two experiments for validation of predicted β+-isotope by the analytical model with GATE/GEANT4 simulations. The first experiments to evaluate the accuracy of predicting β+-yields as a function of irradiated proton energies. In second experiment, we simulate homogeneous phantoms of different materials irradiated by a mono-energetic pencil-like proton beam. The results of filtered β+-yields distributions by the analytical model is compared with those of MC simulated β+-yields in proximal and distal fall-off ranges. Results: The results investigate the distribution between filtered β+-yields and MC simulated β+-yields distribution in different conditions. First, we found that the analytical filtering can be applied over the whole range of the therapeutic energies. Second, the range difference between filtered β+-yields and MC simulated β+-yields at the distal fall-off region are within 1.5mm for all materials used. The findings validated the usefulness of analytical filtering model on range verification of proton therapy on GATE Monte Carlo simulations. In addition, there is a larger discrepancy between filtered prediction and MC simulated β+-yields using GATE code, especially in proximal region. This discrepancy might Result from the absence of wellestablished theoretical models for predicting the nuclear interactions. Conclusion: Despite the fact that large discrepancies of the distributions between MC-simulated and predicted β+-yields were observed, the study prove the effectiveness of analytical filtering model for proton range verification using

  4. New Monte Carlo model of cylindrical diffusing fibers illustrates axially heterogeneous fluorescence detection: simulation and experimental validation

    PubMed Central

    Baran, Timothy M.; Foster, Thomas H.

    2011-01-01

    We present a new Monte Carlo model of cylindrical diffusing fibers that is implemented with a graphics processing unit. Unlike previously published models that approximate the diffuser as a linear array of point sources, this model is based on the construction of these fibers. This allows for accurate determination of fluence distributions and modeling of fluorescence generation and collection. We demonstrate that our model generates fluence profiles similar to a linear array of point sources, but reveals axially heterogeneous fluorescence detection. With axially homogeneous excitation fluence, approximately 90% of detected fluorescence is collected by the proximal third of the diffuser for μs'/μa = 8 in the tissue and 70 to 88% is collected in this region for μs'/μa = 80. Increased fluorescence detection by the distal end of the diffuser relative to the center section is also demonstrated. Validation of these results was performed by creating phantoms consisting of layered fluorescent regions. Diffusers were inserted into these layered phantoms and fluorescence spectra were collected. Fits to these spectra show quantitative agreement between simulated fluorescence collection sensitivities and experimental results. These results will be applicable to the use of diffusers as detectors for dosimetry in interstitial photodynamic therapy. PMID:21895311

  5. 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.

  6. Phase-coexistence simulations of fluid mixtures by the Markov Chain Monte Carlo method using single-particle models

    SciTech Connect

    Li, Jun; Calo, Victor M.

    2013-09-15

    We present a single-particle Lennard–Jones (L-J) model for CO{sub 2} and N{sub 2}. Simplified L-J models for other small polyatomic molecules can be obtained following the methodology described herein. The phase-coexistence diagrams of single-component systems computed using the proposed single-particle models for CO{sub 2} and N{sub 2} agree well with experimental data over a wide range of temperatures. These diagrams are computed using the Markov Chain Monte Carlo method based on the Gibbs-NVT ensemble. This good agreement validates the proposed simplified models. That is, with properly selected parameters, the single-particle models have similar accuracy in predicting gas-phase properties as more complex, state-of-the-art molecular models. To further test these single-particle models, three binary mixtures of CH{sub 4}, CO{sub 2} and N{sub 2} are studied using a Gibbs-NPT ensemble. These results are compared against experimental data over a wide range of pressures. The single-particle model has similar accuracy in the gas phase as traditional models although its deviation in the liquid phase is greater. Since the single-particle model reduces the particle number and avoids the time-consuming Ewald summation used to evaluate Coulomb interactions, the proposed model improves the computational efficiency significantly, particularly in the case of high liquid density where the acceptance rate of the particle-swap trial move increases. We compare, at constant temperature and pressure, the Gibbs-NPT and Gibbs-NVT ensembles to analyze their performance differences and results consistency. As theoretically predicted, the agreement between the simulations implies that Gibbs-NVT can be used to validate Gibbs-NPT predictions when experimental data is not available.

  7. A dynamic hydrological Monte Carlo simulation model to inform decision-making at Lake Toolibin, Western Australia.

    PubMed

    Jones, Stuart; Lacey, Peter; Walshe, Terry

    2009-04-01

    Lake Toolibin, an ephemeral lake in the agricultural zone of Western Australia, is under threat from secondary salinity due to land clearance throughout the catchment. The lake is extensively covered with native vegetation and is a Ramsar listed wetland, being one of the few remaining significant migratory bird habitats in the region. Currently, inflow with salinity greater than 1000 mg/L TDS is diverted from the lake in an effort to protect sensitive lakebed vegetation. However, this conservative threshold compromises the frequency and extent of lake inundation, which is essential for bird breeding. It is speculated that relaxing the threshold to 5000 mg/L may pose negligible additional risk to the condition of lakebed vegetation. To characterise the magnitude of improvement in the provision of bird breeding habitat that might be generated by relaxing the threshold, a dynamic water and salt balance model of the lake was developed and implemented using Monte Carlo simulation. Results from best estimate model inputs indicate that relaxation of the threshold increases the likelihood of satisfying habitat requirements by a factor of 9.7. A second-order Monte Carlo analysis incorporating incertitude generated plausible bounds of [2.6, 37.5] around the best estimate for the relative likelihood of satisfying habitat requirements. Parameter-specific sensitivity analyses suggest the availability of habitat is most sensitive to pan evaporation, lower than expected inflow volume, and higher than expected inflow salt concentration. The characterisation of uncertainty associated with environmental variation and incertitude allows managers to make informed risk-weighted decisions. PMID:19114292

  8. Warranty optimisation based on the prediction of costs to the manufacturer using neural network model and Monte Carlo simulation

    NASA Astrophysics Data System (ADS)

    Stamenkovic, Dragan D.; Popovic, Vladimir M.

    2015-02-01

    Warranty is a powerful marketing tool, but it always involves additional costs to the manufacturer. In order to reduce these costs and make use of warranty's marketing potential, the manufacturer needs to master the techniques for warranty cost prediction according to the reliability characteristics of the product. In this paper a combination free replacement and pro rata warranty policy is analysed as warranty model for one type of light bulbs. Since operating conditions have a great impact on product reliability, they need to be considered in such analysis. A neural network model is used to predict light bulb reliability characteristics based on the data from the tests of light bulbs in various operating conditions. Compared with a linear regression model used in the literature for similar tasks, the neural network model proved to be a more accurate method for such prediction. Reliability parameters obtained in this way are later used in Monte Carlo simulation for the prediction of times to failure needed for warranty cost calculation. The results of the analysis make possible for the manufacturer to choose the optimal warranty policy based on expected product operating conditions. In such a way, the manufacturer can lower the costs and increase the profit.

  9. A Kinetic Monte Carlo model for material aging: Simulations of second phase formation at Au/Bi{sub 2}Te{sub 3} junction in oxygen environments

    SciTech Connect

    Zhou, X. W.; Yang, N. Y. C.

    2014-03-14

    Electronic properties of semiconductor devices are sensitive to defects such as second phase precipitates, grain sizes, and voids. These defects can evolve over time especially under oxidation environments and it is therefore important to understand the resulting aging behavior in order for the reliable applications of devices. In this paper, we propose a kinetic Monte Carlo framework capable of simultaneous simulation of the evolution of second phases, precipitates, grain sizes, and voids in complicated systems involving many species including oxygen. This kinetic Monte Carlo model calculates the energy barriers of various events based directly on the experimental data. As a first step of our model implementation, we incorporate the second phase formation module in the parallel kinetic Monte Carlo codes SPPARKS. Selected aging simulations are performed to examine the formation of second phase precipitates at the eletroplated Au/Bi{sub 2}Te{sub 3} interface under oxygen and oxygen-free environments, and the results are compared with the corresponding experiments.

  10. A Monte Carlo pencil beam scanning model for proton treatment plan simulation using GATE/GEANT4

    NASA Astrophysics Data System (ADS)

    Grevillot, L.; Bertrand, D.; Dessy, F.; Freud, N.; Sarrut, D.

    2011-08-01

    This work proposes a generic method for modeling scanned ion beam delivery systems, without simulation of the treatment nozzle and based exclusively on beam data library (BDL) measurements required for treatment planning systems (TPS). To this aim, new tools dedicated to treatment plan simulation were implemented in the Gate Monte Carlo platform. The method was applied to a dedicated nozzle from IBA for proton pencil beam scanning delivery. Optical and energy parameters of the system were modeled using a set of proton depth-dose profiles and spot sizes measured at 27 therapeutic energies. For further validation of the beam model, specific 2D and 3D plans were produced and then measured with appropriate dosimetric tools. Dose contributions from secondary particles produced by nuclear interactions were also investigated using field size factor experiments. Pristine Bragg peaks were reproduced with 0.7 mm range and 0.2 mm spot size accuracy. A 32 cm range spread-out Bragg peak with 10 cm modulation was reproduced with 0.8 mm range accuracy and a maximum point-to-point dose difference of less than 2%. A 2D test pattern consisting of a combination of homogeneous and high-gradient dose regions passed a 2%/2 mm gamma index comparison for 97% of the points. In conclusion, the generic modeling method proposed for scanned ion beam delivery systems was applicable to an IBA proton therapy system. The key advantage of the method is that it only requires BDL measurements of the system. The validation tests performed so far demonstrated that the beam model achieves clinical performance, paving the way for further studies toward TPS benchmarking. The method involves new sources that are available in the new Gate release V6.1 and could be further applied to other particle therapy systems delivering protons or other types of ions like carbon.

  11. Effect of model parameters on Monte-Carlo simulated light scattering indicatrice of RBC suspension layer at physiological hematocrit

    NASA Astrophysics Data System (ADS)

    Priezzhev, Alexander V.; Kirillin, Mikhail Y.; Lopatin, Vladimir V.

    2002-05-01

    Using angle-resolved Monte-Carlo simulation we obtained indicatrices of light scattering from a whole blood layer (suspension of erythrocytes at physiological hematocrit) for different wavelengths (514 and 633 nm) of incident light. We considered the problems of conformity of parameters describing the model medium and real investigated medium under experiment conditions (shape and size of particles, refractive indexes of particles and suspension, hematocrit). The anisotropy factor was numerically determined for various shapes of model erythrocytes: equivolumed spheres, chaotically oriented spheroids with axial ratio (epsilon) =0.25, and bi-concave disks. For calculations we used different approaches: the exact Mie theory for spheres; hybrid approximation, based on anomalous diffraction approach, for spheroids; and geometrical optics approximation for bi-concave disks and spheroids. The best fir for experimental results obtained at (lambda) =514 nm provided the calculations for the layer of erythrocytes, modeled by chaotically oriented spheroids, which phase functions were calculated by geometrical optics approximation (taking into account Franhofer diffraction). So we conclude that the average shape of erythrocyte in suspension is closer to the spheroid with axes ratio 0.25.

  12. Assessment of the accuracy of an MCNPX-based Monte Carlo simulation model for predicting three-dimensional absorbed dose distributions

    PubMed Central

    Titt, U; Sahoo, N; Ding, X; Zheng, Y; Newhauser, W D; Zhu, X R; Polf, J C; Gillin, M T; Mohan, R

    2014-01-01

    In recent years, the Monte Carlo method has been used in a large number of research studies in radiation therapy. For applications such as treatment planning, it is essential to validate the dosimetric accuracy of the Monte Carlo simulations in heterogeneous media. The AAPM Report no 105 addresses issues concerning clinical implementation of Monte Carlo based treatment planning for photon and electron beams, however for proton-therapy planning, such guidance is not yet available. Here we present the results of our validation of the Monte Carlo model of the double scattering system used at our Proton Therapy Center in Houston. In this study, we compared Monte Carlo simulated depth doses and lateral profiles to measured data for a magnitude of beam parameters. We varied simulated proton energies and widths of the spread-out Bragg peaks, and compared them to measurements obtained during the commissioning phase of the Proton Therapy Center in Houston. Of 191 simulated data sets, 189 agreed with measured data sets to within 3% of the maximum dose difference and within 3 mm of the maximum range or penumbra size difference. The two simulated data sets that did not agree with the measured data sets were in the distal falloff of the measured dose distribution, where large dose gradients potentially produce large differences on the basis of minute changes in the beam steering. Hence, the Monte Carlo models of medium- and large-size double scattering proton-therapy nozzles were valid for proton beams in the 100 MeV–250 MeV interval. PMID:18670050

  13. Modelling of dissolved oxygen in the Danube River using artificial neural networks and Monte Carlo Simulation uncertainty analysis

    NASA Astrophysics Data System (ADS)

    Antanasijević, Davor; Pocajt, Viktor; Perić-Grujić, Aleksandra; Ristić, Mirjana

    2014-11-01

    This paper describes the training, validation, testing and uncertainty analysis of general regression neural network (GRNN) models for the forecasting of dissolved oxygen (DO) in the Danube River. The main objectives of this work were to determine the optimum data normalization and input selection techniques, the determination of the relative importance of uncertainty in different input variables, as well as the uncertainty analysis of model results using the Monte Carlo Simulation (MCS) technique. Min-max, median, z-score, sigmoid and tanh were validated as normalization techniques, whilst the variance inflation factor, correlation analysis and genetic algorithm were tested as input selection techniques. As inputs, the GRNN models used 19 water quality variables, measured in the river water each month at 17 different sites over a period of 9 years. The best results were obtained using min-max normalized data and the input selection based on the correlation between DO and dependent variables, which provided the most accurate GRNN model, and in combination the smallest number of inputs: Temperature, pH, HCO3-, SO42-, NO3-N, Hardness, Na, Cl-, Conductivity and Alkalinity. The results show that the correlation coefficient between measured and predicted DO values is 0.85. The inputs with the greatest effect on the GRNN model (arranged in descending order) were T, pH, HCO3-, SO42- and NO3-N. Of all inputs, variability of temperature had the greatest influence on the variability of DO content in river body, with the DO decreasing at a rate similar to the theoretical DO decreasing rate relating to temperature. The uncertainty analysis of the model results demonstrate that the GRNN can effectively forecast the DO content, since the distribution of model results are very similar to the corresponding distribution of real data.

  14. Core Formation And Gravothermal Collapse Of Self-interacting Dark Matter Halos: Monte Carlo N-body simulation versus Conducting Fluid Model

    NASA Astrophysics Data System (ADS)

    Koda, Jun; Shapiro, P. R.

    2007-12-01

    Self-interacting dark matter (SIDM) has been proposed to solve the cuspy core problem of dark matter halos in standard CDM. There are two ways to investigate the effect of the 2-body, non-gravitational, elastic collisions of SIDM, Monte-Carlo N-body simulation and a conducting fluid model. The former is a gravitational N-body simulation with a Monte Carlo algorithm for the SIDM scattering that changes the direction of N-body particles randomly according to a given scattering cross section. The latter is a system of fluid conservation equations with a thermal conduction that describes the collisional effect, which was originally invented to describe the gravothermal collapse of globular clusters. Our previous work found a significant disagreement as regards the strength of collisionality required to solve cuspy core problem. However the two methods have not been properly tested against each other. Here, we make direct comparisons between Monte Carlo N-body simulations and analytic and numerical solutions of the conducting fluid (gaseous) model, for various isolated self-interacting dark matter halos. The N-body simulations reproduce the analytical self-similar solution of gravothermal collapse in the fluid model when one free parameter, the coefficient of heat conduction C, is chosen to be 0.75. The gravothermal collapse results of the simulations agrees well with our 1D numerical hydro solutions of the fluid model within 20% for other initial conditions, including Plummer model, Hernquist profile and NFW profile. In conclusion the conducting fluid model is in reasonably good agreement with the Monte Carlo simulations for isolated halos. We will pursue the origin of the reported disagreement between two methods in a cosmological environment by comparing new N-body simulations with fully cosmological initial conditions.

  15. Path integral Monte Carlo simulations of H2 adsorbed to lithium-doped benzene: A model for hydrogen storage materials.

    PubMed

    Lindoy, Lachlan P; Kolmann, Stephen J; D'Arcy, Jordan H; Crittenden, Deborah L; Jordan, Meredith J T

    2015-11-21

    Finite temperature quantum and anharmonic effects are studied in H2-Li(+)-benzene, a model hydrogen storage material, using path integral Monte Carlo (PIMC) simulations on an interpolated potential energy surface refined over the eight intermolecular degrees of freedom based upon M05-2X/6-311+G(2df,p) density functional theory calculations. Rigid-body PIMC simulations are performed at temperatures ranging from 77 K to 150 K, producing both quantum and classical probability density histograms describing the adsorbed H2. Quantum effects broaden the histograms with respect to their classical analogues and increase the expectation values of the radial and angular polar coordinates describing the location of the center-of-mass of the H2 molecule. The rigid-body PIMC simulations also provide estimates of the change in internal energy, ΔUads, and enthalpy, ΔHads, for H2 adsorption onto Li(+)-benzene, as a function of temperature. These estimates indicate that quantum effects are important even at room temperature and classical results should be interpreted with caution. Our results also show that anharmonicity is more important in the calculation of U and H than coupling-coupling between the intermolecular degrees of freedom becomes less important as temperature increases whereas anharmonicity becomes more important. The most anharmonic motions in H2-Li(+)-benzene are the "helicopter" and "ferris wheel" H2 rotations. Treating these motions as one-dimensional free and hindered rotors, respectively, provides simple corrections to standard harmonic oscillator, rigid rotor thermochemical expressions for internal energy and enthalpy that encapsulate the majority of the anharmonicity. At 150 K, our best rigid-body PIMC estimates for ΔUads and ΔHads are -13.3 ± 0.1 and -14.5 ± 0.1 kJ mol(-1), respectively. PMID:26590532

  16. The solvation of ions in acetonitrile and acetone. II. Monte Carlo simulations using polarizable solvent models

    NASA Astrophysics Data System (ADS)

    Fischer, R.; Richardi, J.; Fries, P. H.; Krienke, H.

    2002-11-01

    Structural properties and energies of solvation are simulated for alkali and halide ions. The solvation structure is discussed in terms of various site-site distribution functions, of solvation numbers, and of orientational correlation functions of the solvent molecules around the ions. The solvent polarizability has notable effects which cannot be intuitively predicted. In particular, it is necessary to reproduce the experimental solvation numbers of small ions. The changes of solvation properties are investigated along the alkali and halide series. By comparing the solvation of ions in acetone to that in acetonitrile, it is shown that the spatial correlations among the solvent molecules around an ion result in a strong screening of the ion-solvent direct intermolecular potential and are essential to understand the changes in the solvation structures and energies between different solvents. The solvation properties derived from the simulations are compared to earlier predictions of the hypernetted chain (HNC) approximation of the molecular Ornstein-Zernike (MOZ) theory [J. Richardi, P. H. Fries, and H. Krienke, J. Chem. Phys. 108, 4079 (1998)]. The MOZ(HNC) formalism gives an overall qualitatively correct picture of the solvation and its various unexpected findings are corroborated. For the larger ions, its predictions become quantitative. The MOZ approach allows to calculate solvent-solvent and ion-solvent potentials of mean force, which shed light on the 3D labile molecular and ionic architectures in the solution. These potentials of mean force convey a unique information which is necessary to fully interpret the angle-averaged structural functions computed from the simulations. Finally, simulations of solutions at finite concentrations show that the solvent-solvent and ion-solvent spatial correlations at infinite dilution are marginally altered by the introduction of fair amounts of ions.

  17. Monte Carlo simulation of a film growth with reactive hydrophobic, polar, and aqueous components by a covalent bond fluctuating model

    NASA Astrophysics Data System (ADS)

    Yang, Shihai; Pandey, Ras B.

    2007-04-01

    Using a bond fluctuating model (BFM), Monte Carlo simulations are performed to study the film growth in a mixture of reactive hydrophobic (H) and hydrophilic (P) groups in a simultaneous reactive and evaporating aqueous (A) solution on a simple three dimensional lattice. In addition to the excluded volume, short range phenomenological interactions among each constituents and kinetic functionalities are used to capture their major characteristics. The simulation involves thermodynamic equilibration via stochastic movement of each constituent by Metropolis algorithm as well as cross-linking reaction among constituents with evaporating aqueous component. The film thickness (h) and its interface width (W) are examined with a reactive aqueous solvent for a range of temperatures (T). Results are compared with a previous study [Yang et al. Macromol. Theory Simul. 15, 263 (2006)] with an effective bond fluctuation model (EBFM). Simulation data show a much slower power-law growth for h and W with BFM than that with EBFM. With BFM, growth of the film thickness can be described by h ∝tγ, with a typical value γ1≈0.97 in initial time regime followed by γ2≈0.77 at T =5, for example. Growth of the interface width can also be described by a power law, W ∝tβ, with β1≈0.40 initially and β2≈0.25 in later stage. Corresponding values of the exponents with EBFM are much higher, i.e., γ1≈1.84, γ2≈1.34 and β1≈1.05, β2≈0.60 at T =5. Correct restrictions on the bond length with the excluded volume used with BFM are found to have a greater effect on steady-state film thickness (hs) and the interface width (Ws) at low temperatures than that at high temperatures. The relaxation patterns of the interface width with BFM seem to change noticeably from those with EBFM. A better relaxed film with a smoother surface is thus achieved by the improved cross-linking covalent bond fluctuation model which is more realistic in capturing appropriate details of systems such as

  18. Monte Carlo simulation of an expanding gas

    NASA Technical Reports Server (NTRS)

    Boyd, Iain D.

    1989-01-01

    By application of simple computer graphics techniques, the statistical performance of two Monte Carlo methods used in the simulation of rarefied gas flows are assessed. Specifically, two direct simulation Monte Carlo (DSMC) methods developed by Bird and Nanbu are considered. The graphics techniques are found to be of great benefit in the reduction and interpretation of the large volume of data generated, thus enabling important conclusions to be drawn about the simulation results. Hence, it is discovered that the method of Nanbu suffers from increased statistical fluctuations, thereby prohibiting its use in the solution of practical problems.

  19. 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)

  20. Sensitivity Analysis of the Sheet Metal Stamping Processes Based on Inverse Finite Element Modeling and Monte Carlo Simulation

    SciTech Connect

    Yu Maolin; Du, R.

    2005-08-05

    Sheet metal stamping is one of the most commonly used manufacturing processes, and hence, much research has been carried for economic gain. Searching through the literatures, however, it is found that there are still a lots of problems unsolved. For example, it is well known that for a same press, same workpiece material, and same set of die, the product quality may vary owing to a number of factors, such as the inhomogeneous of the workpice material, the loading error, the lubrication, and etc. Presently, few seem able to predict the quality variation, not to mention what contribute to the quality variation. As a result, trial-and-error is still needed in the shop floor, causing additional cost and time delay. This paper introduces a new approach to predict the product quality variation and identify the sensitive design / process parameters. The new approach is based on a combination of inverse Finite Element Modeling (FEM) and Monte Carlo Simulation (more specifically, the Latin Hypercube Sampling (LHS) approach). With an acceptable accuracy, the inverse FEM (also called one-step FEM) requires much less computation load than that of the usual incremental FEM and hence, can be used to predict the quality variations under various conditions. LHS is a statistical method, through which the sensitivity analysis can be carried out. The result of the sensitivity analysis has clear physical meaning and can be used to optimize the die design and / or the process design. Two simulation examples are presented including drawing a rectangular box and drawing a two-step rectangular box.

  1. Modelling dose distribution in tubing and cable using CYLTRAN and ACCEPT Monte Carlo simulation code

    SciTech Connect

    Weiss, D.E.; Kensek, R.P.

    1993-12-31

    One of the difficulties in the irradiation of non-slab geometries, such as a tube, is the uneven penetration of the electrons. A simple model of the distribution of dose in a tube or cable in relationship to voltage, composition, wall thickness and diameter can be mapped using the cylinder geometry provided for in the ITS/CYLTRAN code, complete with automatic subzoning. The reality of more complex 3D geometry to include effects of window foil, backscattering fixtures and beam scanning angles can be more completely accounted for by using the ITS/ACCEPT code with a line source update and a system of intersecting wedges to define input zones for mapping dose distributions in a tube. Thus, all of the variables that affect dose distribution can be modelled without the need to run time consuming and costly factory experiments. The effects of composition changes on dose distribution can also be anticipated.

  2. Monte Carlo simulation of intercalated carbon nanotubes.

    PubMed

    Mykhailenko, Oleksiy; Matsui, Denis; Prylutskyy, Yuriy; Le Normand, Francois; Eklund, Peter; Scharff, Peter

    2007-01-01

    Monte Carlo simulations of the single- and double-walled carbon nanotubes (CNT) intercalated with different metals have been carried out. The interrelation between the length of a CNT, the number and type of metal atoms has also been established. This research is aimed at studying intercalated systems based on CNTs and d-metals such as Fe and Co. Factors influencing the stability of these composites have been determined theoretically by the Monte Carlo method with the Tersoff potential. The modeling of CNTs intercalated with metals by the Monte Carlo method has proved that there is a correlation between the length of a CNT and the number of endo-atoms of specific type. Thus, in the case of a metallic CNT (9,0) with length 17 bands (3.60 nm), in contrast to Co atoms, Fe atoms are extruded out of the CNT if the number of atoms in the CNT is not less than eight. Thus, this paper shows that a CNT of a certain size can be intercalated with no more than eight Fe atoms. The systems investigated are stabilized by coordination of 3d-atoms close to the CNT wall with a radius-vector of (0.18-0.20) nm. Another characteristic feature is that, within the temperature range of (400-700) K, small systems exhibit ground-state stabilization which is not characteristic of the higher ones. The behavior of Fe and Co endo-atoms between the walls of a double-walled carbon nanotube (DW CNT) is explained by a dominating van der Waals interaction between the Co atoms themselves, which is not true for the Fe atoms. PMID:17033783

  3. Validation of the GATE Monte Carlo simulation platform for modelling a CsI(Tl) scintillation camera dedicated to small-animal imaging.

    PubMed

    Lazaro, D; Buvat, I; Loudos, G; Strul, D; Santin, G; Giokaris, N; Donnarieix, D; Maigne, L; Spanoudaki, V; Styliaris, S; Staelens, S; Breton, V

    2004-01-21

    Monte Carlo simulations are increasingly used in scintigraphic imaging to model imaging systems and to develop and assess tomographic reconstruction algorithms and correction methods for improved image quantitation. GATE (GEANT4 application for tomographic emission) is a new Monte Carlo simulation platform based on GEANT4 dedicated to nuclear imaging applications. This paper describes the GATE simulation of a prototype of scintillation camera dedicated to small-animal imaging and consisting of a CsI(Tl) crystal array coupled to a position-sensitive photomultiplier tube. The relevance of GATE to model the camera prototype was assessed by comparing simulated 99mTc point spread functions, energy spectra, sensitivities, scatter fractions and image of a capillary phantom with the corresponding experimental measurements. Results showed an excellent agreement between simulated and experimental data: experimental spatial resolutions were predicted with an error less than 100 microns. The difference between experimental and simulated system sensitivities for different source-to-collimator distances was within 2%. Simulated and experimental scatter fractions in a [98-182 keV] energy window differed by less than 2% for sources located in water. Simulated and experimental energy spectra agreed very well between 40 and 180 keV. These results demonstrate the ability and flexibility of GATE for simulating original detector designs. The main weakness of GATE concerns the long computation time it requires: this issue is currently under investigation by the GEANT4 and the GATE collaborations. PMID:15083671

  4. Validation of the GATE Monte Carlo simulation platform for modelling a CsI(Tl) scintillation camera dedicated to small-animal imaging

    NASA Astrophysics Data System (ADS)

    Lazaro, D.; Buvat, I.; Loudos, G.; Strul, D.; Santin, G.; Giokaris, N.; Donnarieix, D.; Maigne, L.; Spanoudaki, V.; Styliaris, S.; Staelens, S.; Breton, V.

    2004-01-01

    Monte Carlo simulations are increasingly used in scintigraphic imaging to model imaging systems and to develop and assess tomographic reconstruction algorithms and correction methods for improved image quantitation. GATE (GEANT4 application for tomographic emission) is a new Monte Carlo simulation platform based on GEANT4 dedicated to nuclear imaging applications. This paper describes the GATE simulation of a prototype of scintillation camera dedicated to small-animal imaging and consisting of a CsI(Tl) crystal array coupled to a position-sensitive photomultiplier tube. The relevance of GATE to model the camera prototype was assessed by comparing simulated 99mTc point spread functions, energy spectra, sensitivities, scatter fractions and image of a capillary phantom with the corresponding experimental measurements. Results showed an excellent agreement between simulated and experimental data: experimental spatial resolutions were predicted with an error less than 100 µm. The difference between experimental and simulated system sensitivities for different source-to-collimator distances was within 2%. Simulated and experimental scatter fractions in a [98-182 keV] energy window differed by less than 2% for sources located in water. Simulated and experimental energy spectra agreed very well between 40 and 180 keV. These results demonstrate the ability and flexibility of GATE for simulating original detector designs. The main weakness of GATE concerns the long computation time it requires: this issue is currently under investigation by the GEANT4 and the GATE collaborations.

  5. Sequence-based Parameter Estimation for an Epidemiological Temporal Aftershock Forecasting Model using Markov Chain Monte Carlo Simulation

    NASA Astrophysics Data System (ADS)

    Jalayer, Fatemeh; Ebrahimian, Hossein

    2014-05-01

    Introduction The first few days elapsed after the occurrence of a strong earthquake and in the presence of an ongoing aftershock sequence are quite critical for emergency decision-making purposes. Epidemic Type Aftershock Sequence (ETAS) models are used frequently for forecasting the spatio-temporal evolution of seismicity in the short-term (Ogata, 1988). The ETAS models are epidemic stochastic point process models in which every earthquake is a potential triggering event for subsequent earthquakes. The ETAS model parameters are usually calibrated a priori and based on a set of events that do not belong to the on-going seismic sequence (Marzocchi and Lombardi 2009). However, adaptive model parameter estimation, based on the events in the on-going sequence, may have several advantages such as, tuning the model to the specific sequence characteristics, and capturing possible variations in time of the model parameters. Simulation-based methods can be employed in order to provide a robust estimate for the spatio-temporal seismicity forecasts in a prescribed forecasting time interval (i.e., a day) within a post-main shock environment. This robust estimate takes into account the uncertainty in the model parameters expressed as the posterior joint probability distribution for the model parameters conditioned on the events that have already occurred (i.e., before the beginning of the forecasting interval) in the on-going seismic sequence. The Markov Chain Monte Carlo simulation scheme is used herein in order to sample directly from the posterior probability distribution for ETAS model parameters. Moreover, the sequence of events that is going to occur during the forecasting interval (and hence affecting the seismicity in an epidemic type model like ETAS) is also generated through a stochastic procedure. The procedure leads to two spatio-temporal outcomes: (1) the probability distribution for the forecasted number of events, and (2) the uncertainty in estimating the

  6. Monte Carlo simulation framework for TMT

    NASA Astrophysics Data System (ADS)

    Vogiatzis, Konstantinos; Angeli, George Z.

    2008-07-01

    This presentation describes a strategy for assessing the performance of the Thirty Meter Telescope (TMT). A Monte Carlo Simulation Framework has been developed to combine optical modeling with Computational Fluid Dynamics simulations (CFD), Finite Element Analysis (FEA) and controls to model the overall performance of TMT. The framework consists of a two year record of observed environmental parameters such as atmospheric seeing, site wind speed and direction, ambient temperature and local sunset and sunrise times, along with telescope azimuth and elevation with a given sampling rate. The modeled optical, dynamic and thermal seeing aberrations are available in a matrix form for distinct values within the range of influencing parameters. These parameters are either part of the framework parameter set or can be derived from them at each time-step. As time advances, the aberrations are interpolated and combined based on the current value of their parameters. Different scenarios can be generated based on operating parameters such as venting strategy, optical calibration frequency and heat source control. Performance probability distributions are obtained and provide design guidance. The sensitivity of the system to design, operating and environmental parameters can be assessed in order to maximize the % of time the system meets the performance specifications.

  7. Monte Carlo simulations of phosphate polyhedron connectivity in glasses

    SciTech Connect

    ALAM,TODD M.

    2000-01-01

    Monte Carlo simulations of phosphate tetrahedron connectivity distributions in alkali and alkaline earth phosphate glasses are reported. By utilizing a discrete bond model, the distribution of next-nearest neighbor connectivities between phosphate polyhedron for random, alternating and clustering bonding scenarios was evaluated as a function of the relative bond energy difference. The simulated distributions are compared to experimentally observed connectivities reported for solid-state two-dimensional exchange and double-quantum NMR experiments of phosphate glasses. These Monte Carlo simulations demonstrate that the polyhedron connectivity is best described by a random distribution in lithium phosphate and calcium phosphate glasses.

  8. Monte Carlo Simulations of Phosphate Polyhedron Connectivity in Glasses

    SciTech Connect

    ALAM,TODD M.

    1999-12-21

    Monte Carlo simulations of phosphate tetrahedron connectivity distributions in alkali and alkaline earth phosphate glasses are reported. By utilizing a discrete bond model, the distribution of next-nearest neighbor connectivities between phosphate polyhedron for random, alternating and clustering bonding scenarios was evaluated as a function of the relative bond energy difference. The simulated distributions are compared to experimentally observed connectivities reported for solid-state two-dimensional exchange and double-quantum NMR experiments of phosphate glasses. These Monte Carlo simulations demonstrate that the polyhedron connectivity is best described by a random distribution in lithium phosphate and calcium phosphate glasses.

  9. Monte Carlo simulation of chromatin stretching.

    PubMed

    Aumann, Frank; Lankas, Filip; Caudron, Maïwen; Langowski, Jörg

    2006-04-01

    We present Monte Carlo (MC) simulations of the stretching of a single chromatin fiber. The model approximates the DNA by a flexible polymer chain with Debye-Hückel electrostatics and uses a two-angle zigzag model for the geometry of the linker DNA connecting the nucleosomes. The latter are represented by flat disks interacting via an attractive Gay-Berne potential. Our results show that the stiffness of the chromatin fiber strongly depends on the linker DNA length. Furthermore, changing the twisting angle between nucleosomes from 90 degrees to 130 degrees increases the stiffness significantly. An increase in the opening angle from 22 degrees to 34 degrees leads to softer fibers for small linker lengths. We observe that fibers containing a linker histone at each nucleosome are stiffer compared to those without the linker histone. The simulated persistence lengths and elastic moduli agree with experimental data. Finally, we show that the chromatin fiber does not behave as an isotropic elastic rod, but its rigidity depends on the direction of deformation: Chromatin is much more resistant to stretching than to bending. PMID:16711856

  10. Monte Carlo simulation of chromatin stretching

    NASA Astrophysics Data System (ADS)

    Aumann, Frank; Lankas, Filip; Caudron, Maïwen; Langowski, Jörg

    2006-04-01

    We present Monte Carlo (MC) simulations of the stretching of a single 30nm chromatin fiber. The model approximates the DNA by a flexible polymer chain with Debye-Hückel electrostatics and uses a two-angle zigzag model for the geometry of the linker DNA connecting the nucleosomes. The latter are represented by flat disks interacting via an attractive Gay-Berne potential. Our results show that the stiffness of the chromatin fiber strongly depends on the linker DNA length. Furthermore, changing the twisting angle between nucleosomes from 90° to 130° increases the stiffness significantly. An increase in the opening angle from 22° to 34° leads to softer fibers for small linker lengths. We observe that fibers containing a linker histone at each nucleosome are stiffer compared to those without the linker histone. The simulated persistence lengths and elastic moduli agree with experimental data. Finally, we show that the chromatin fiber does not behave as an isotropic elastic rod, but its rigidity depends on the direction of deformation: Chromatin is much more resistant to stretching than to bending.

  11. Combinatorial geometry domain decomposition strategies for Monte Carlo simulations

    SciTech Connect

    Li, G.; Zhang, B.; Deng, L.; Mo, Z.; Liu, Z.; Shangguan, D.; Ma, Y.; Li, S.; Hu, Z.

    2013-07-01

    Analysis and modeling of nuclear reactors can lead to memory overload for a single core processor when it comes to refined modeling. A method to solve this problem is called 'domain decomposition'. In the current work, domain decomposition algorithms for a combinatorial geometry Monte Carlo transport code are developed on the JCOGIN (J Combinatorial Geometry Monte Carlo transport INfrastructure). Tree-based decomposition and asynchronous communication of particle information between domains are described in the paper. Combination of domain decomposition and domain replication (particle parallelism) is demonstrated and compared with that of MERCURY code. A full-core reactor model is simulated to verify the domain decomposition algorithms using the Monte Carlo particle transport code JMCT (J Monte Carlo Transport Code), which has being developed on the JCOGIN infrastructure. Besides, influences of the domain decomposition algorithms to tally variances are discussed. (authors)

  12. Monte Carlo Simulation of Critical Casimir Forces

    NASA Astrophysics Data System (ADS)

    Vasilyev, Oleg A.

    2015-03-01

    In the vicinity of the second order phase transition point long-range critical fluctuations of the order parameter appear. The second order phase transition in a critical binary mixture in the vicinity of the demixing point belongs to the universality class of the Ising model. The superfluid transition in liquid He belongs to the universality class of the XY model. The confinement of long-range fluctuations causes critical Casimir forces acting on confining surfaces or particles immersed in the critical substance. Last decade critical Casimir forces in binary mixtures and liquid helium were studied experimentally. The critical Casimir force in a film of a given thickness scales as a universal scaling function of the ratio of the film thickness to the bulk correlation length divided over the cube of the film thickness. Using Monte Carlo simulations we can compute critical Casimir forces and their scaling functions for lattice Ising and XY models which correspond to experimental results for the binary mixture and liquid helium, respectively. This chapter provides the description of numerical methods for computation of critical Casimir interactions for lattice models for plane-plane, plane-particle, and particle-particle geometries.

  13. A multicomb variance reduction scheme for Monte Carlo semiconductor simulators

    SciTech Connect

    Gray, M.G.; Booth, T.E.; Kwan, T.J.T.; Snell, C.M.

    1998-04-01

    The authors adapt a multicomb variance reduction technique used in neutral particle transport to Monte Carlo microelectronic device modeling. They implement the method in a two-dimensional (2-D) MOSFET device simulator and demonstrate its effectiveness in the study of hot electron effects. The simulations show that the statistical variance of hot electrons is significantly reduced with minimal computational cost. The method is efficient, versatile, and easy to implement in existing device simulators.

  14. Lattice Monte Carlo simulations of polymer melts

    NASA Astrophysics Data System (ADS)

    Hsu, Hsiao-Ping

    2014-12-01

    We use Monte Carlo simulations to study polymer melts consisting of fully flexible and moderately stiff chains in the bond fluctuation model at a volume fraction 0.5. In order to reduce the local density fluctuations, we test a pre-packing process for the preparation of the initial configurations of the polymer melts, before the excluded volume interaction is switched on completely. This process leads to a significantly faster decrease of the number of overlapping monomers on the lattice. This is useful for simulating very large systems, where the statistical properties of the model with a marginally incomplete elimination of excluded volume violations are the same as those of the model with strictly excluded volume. We find that the internal mean square end-to-end distance for moderately stiff chains in a melt can be very well described by a freely rotating chain model with a precise estimate of the bond-bond orientational correlation between two successive bond vectors in equilibrium. The plot of the probability distributions of the reduced end-to-end distance of chains of different stiffness also shows that the data collapse is excellent and described very well by the Gaussian distribution for ideal chains. However, while our results confirm the systematic deviations between Gaussian statistics for the chain structure factor Sc(q) [minimum in the Kratky-plot] found by Wittmer et al. [EPL 77, 56003 (2007)] for fully flexible chains in a melt, we show that for the available chain length these deviations are no longer visible, when the chain stiffness is included. The mean square bond length and the compressibility estimated from collective structure factors depend slightly on the stiffness of the chains.

  15. The structure of PX{sub 3} (X = Cl, Br, I) molecular liquids from X-ray diffraction, molecular dynamics simulations, and reverse Monte Carlo modeling

    SciTech Connect

    Pothoczki, Szilvia Temleitner, László; Pusztai, László

    2014-02-07

    Synchrotron X-ray diffraction measurements have been conducted on liquid phosphorus trichloride, tribromide, and triiodide. Molecular Dynamics simulations for these molecular liquids were performed with a dual purpose: (1) to establish whether existing intermolecular potential functions can provide a picture that is consistent with diffraction data and (2) to generate reliable starting configurations for subsequent Reverse Monte Carlo modelling. Structural models (i.e., sets of coordinates of thousands of atoms) that were fully consistent with experimental diffraction information, within errors, have been prepared by means of the Reverse Monte Carlo method. Comparison with reference systems, generated by hard sphere-like Monte Carlo simulations, was also carried out to demonstrate the extent to which simple space filling effects determine the structure of the liquids (and thus, also estimating the information content of measured data). Total scattering structure factors, partial radial distribution functions and orientational correlations as a function of distances between the molecular centres have been calculated from the models. In general, more or less antiparallel arrangements of the primary molecular axes that are found to be the most favourable orientation of two neighbouring molecules. In liquid PBr{sub 3} electrostatic interactions seem to play a more important role in determining intermolecular correlations than in the other two liquids; molecular arrangements in both PCl{sub 3} and PI{sub 3} are largely driven by steric effects.

  16. The structure of PX3 (X = Cl, Br, I) molecular liquids from X-ray diffraction, molecular dynamics simulations, and reverse Monte Carlo modeling

    NASA Astrophysics Data System (ADS)

    Pothoczki, Szilvia; Temleitner, László; Pusztai, László

    2014-02-01

    Synchrotron X-ray diffraction measurements have been conducted on liquid phosphorus trichloride, tribromide, and triiodide. Molecular Dynamics simulations for these molecular liquids were performed with a dual purpose: (1) to establish whether existing intermolecular potential functions can provide a picture that is consistent with diffraction data and (2) to generate reliable starting configurations for subsequent Reverse Monte Carlo modelling. Structural models (i.e., sets of coordinates of thousands of atoms) that were fully consistent with experimental diffraction information, within errors, have been prepared by means of the Reverse Monte Carlo method. Comparison with reference systems, generated by hard sphere-like Monte Carlo simulations, was also carried out to demonstrate the extent to which simple space filling effects determine the structure of the liquids (and thus, also estimating the information content of measured data). Total scattering structure factors, partial radial distribution functions and orientational correlations as a function of distances between the molecular centres have been calculated from the models. In general, more or less antiparallel arrangements of the primary molecular axes that are found to be the most favourable orientation of two neighbouring molecules. In liquid PBr3 electrostatic interactions seem to play a more important role in determining intermolecular correlations than in the other two liquids; molecular arrangements in both PCl3 and PI3 are largely driven by steric effects.

  17. Anisotropy of electrical transport in pnictide superconductors studied using Monte Carlo simulations of the spin-fermion model.

    PubMed

    Liang, Shuhua; Alvarez, Gonzalo; Şen, Cengiz; Moreo, Adriana; Dagotto, Elbio

    2012-07-27

    An undoped three-orbital spin-fermion model for the Fe-based superconductors is studied via Monte Carlo techniques in two-dimensional clusters. At low temperatures, the magnetic and one-particle spectral properties are in agreement with neutron and photoemission experiments. Our main results are the resistance versus temperature curves that display the same features observed in BaFe(2)As(2) detwinned single crystals (under uniaxial stress), including a low-temperature anisotropy between the two directions followed by a peak at the magnetic ordering temperature, that qualitatively appears related to short-range spin order and concomitant Fermi surface orbital order. PMID:23006104

  18. Treatment plan evaluation for interstitial photodynamic therapy in a mouse model by Monte Carlo simulation with FullMonte

    NASA Astrophysics Data System (ADS)

    Cassidy, Jeffrey; Betz, Vaughn; Lilge, Lothar

    2015-02-01

    Monte Carlo (MC) simulation is recognized as the “gold standard” for biophotonic simulation, capturing all relevant physics and material properties at the perceived cost of high computing demands. Tetrahedral-mesh-based MC simulations particularly are attractive due to the ability to refine the mesh at will to conform to complicated geometries or user-defined resolution requirements. Since no approximations of material or light-source properties are required, MC methods are applicable to the broadest set of biophotonic simulation problems. MC methods also have other implementation features including inherent parallelism, and permit a continuously-variable quality-runtime tradeoff. We demonstrate here a complete MC-based prospective fluence dose evaluation system for interstitial PDT to generate dose-volume histograms on a tetrahedral mesh geometry description. To our knowledge, this is the first such system for general interstitial photodynamic therapy employing MC methods and is therefore applicable to a very broad cross-section of anatomy and material properties. We demonstrate that evaluation of dose-volume histograms is an effective variance-reduction scheme in its own right which greatly reduces the number of packets required and hence runtime required to achieve acceptable result confidence. We conclude that MC methods are feasible for general PDT treatment evaluation and planning, and considerably less costly than widely believed.

  19. Monte Carlo simulations of lattice gauge theories

    SciTech Connect

    Rebbi, C

    1980-02-01

    Monte Carlo simulations done for four-dimensional lattice gauge systems are described, where the gauge group is one of the following: U(1); SU(2); Z/sub N/, i.e., the subgroup of U(1) consisting of the elements e 2..pi..in/N with integer n and N; the eight-element group of quaternions, Q; the 24- and 48-element subgroups of SU(2), denoted by T and O, which reduce to the rotation groups of the tetrahedron and the octahedron when their centers Z/sub 2/, are factored out. All of these groups can be considered subgroups of SU(2) and a common normalization was used for the action. The following types of Monte Carlo experiments are considered: simulations of a thermal cycle, where the temperature of the system is varied slightly every few Monte Carlo iterations and the internal energy is measured; mixed-phase runs, where several Monte Carlo iterations are done at a few temperatures near a phase transition starting with a lattice which is half ordered and half disordered; measurements of averages of Wilson factors for loops of different shape. 5 figures, 1 table. (RWR)

  20. Track structure modeling in liquid water: A review of the Geant4-DNA very low energy extension of the Geant4 Monte Carlo simulation toolkit.

    PubMed

    Bernal, M A; Bordage, M C; Brown, J M C; Davídková, M; Delage, E; El Bitar, Z; Enger, S A; Francis, Z; Guatelli, S; Ivanchenko, V N; Karamitros, M; Kyriakou, I; Maigne, L; Meylan, S; Murakami, K; Okada, S; Payno, H; Perrot, Y; Petrovic, I; Pham, Q T; Ristic-Fira, A; Sasaki, T; Štěpán, V; Tran, H N; Villagrasa, C; Incerti, S

    2015-12-01

    Understanding the fundamental mechanisms involved in the induction of biological damage by ionizing radiation remains a major challenge of today's radiobiology research. The Monte Carlo simulation of physical, physicochemical and chemical processes involved may provide a powerful tool for the simulation of early damage induction. The Geant4-DNA extension of the general purpose Monte Carlo Geant4 simulation toolkit aims to provide the scientific community with an open source access platform for the mechanistic simulation of such early damage. This paper presents the most recent review of the Geant4-DNA extension, as available to Geant4 users since June 2015 (release 10.2 Beta). In particular, the review includes the description of new physical models for the description of electron elastic and inelastic interactions in liquid water, as well as new examples dedicated to the simulation of physicochemical and chemical stages of water radiolysis. Several implementations of geometrical models of biological targets are presented as well, and the list of Geant4-DNA examples is described. PMID:26653251

  1. Modeling of body tissues for Monte Carlo simulation of radiotherapy treatments planned with conventional x-ray CT systems.

    PubMed

    Kanematsu, Nobuyuki; Inaniwa, Taku; Nakao, Minoru

    2016-07-01

    In the conventional procedure for accurate Monte Carlo simulation of radiotherapy, a CT number given to each pixel of a patient image is directly converted to mass density and elemental composition using their respective functions that have been calibrated specifically for the relevant x-ray CT system. We propose an alternative approach that is a conversion in two steps: the first from CT number to density and the second from density to composition. Based on the latest compilation of standard tissues for reference adult male and female phantoms, we sorted the standard tissues into groups by mass density and defined the representative tissues by averaging the material properties per group. With these representative tissues, we formulated polyline relations between mass density and each of the following; electron density, stopping-power ratio and elemental densities. We also revised a procedure of stoichiometric calibration for CT-number conversion and demonstrated the two-step conversion method for a theoretically emulated CT system with hypothetical 80 keV photons. For the standard tissues, high correlation was generally observed between mass density and the other densities excluding those of C and O for the light spongiosa tissues between 1.0 g cm(-3) and 1.1 g cm(-3) occupying 1% of the human body mass. The polylines fitted to the dominant tissues were generally consistent with similar formulations in the literature. The two-step conversion procedure was demonstrated to be practical and will potentially facilitate Monte Carlo simulation for treatment planning and for retrospective analysis of treatment plans with little impact on the management of planning CT systems. PMID:27300449

  2. Modeling of body tissues for Monte Carlo simulation of radiotherapy treatments planned with conventional x-ray CT systems

    NASA Astrophysics Data System (ADS)

    Kanematsu, Nobuyuki; Inaniwa, Taku; Nakao, Minoru

    2016-07-01

    In the conventional procedure for accurate Monte Carlo simulation of radiotherapy, a CT number given to each pixel of a patient image is directly converted to mass density and elemental composition using their respective functions that have been calibrated specifically for the relevant x-ray CT system. We propose an alternative approach that is a conversion in two steps: the first from CT number to density and the second from density to composition. Based on the latest compilation of standard tissues for reference adult male and female phantoms, we sorted the standard tissues into groups by mass density and defined the representative tissues by averaging the material properties per group. With these representative tissues, we formulated polyline relations between mass density and each of the following; electron density, stopping-power ratio and elemental densities. We also revised a procedure of stoichiometric calibration for CT-number conversion and demonstrated the two-step conversion method for a theoretically emulated CT system with hypothetical 80 keV photons. For the standard tissues, high correlation was generally observed between mass density and the other densities excluding those of C and O for the light spongiosa tissues between 1.0 g cm‑3 and 1.1 g cm‑3 occupying 1% of the human body mass. The polylines fitted to the dominant tissues were generally consistent with similar formulations in the literature. The two-step conversion procedure was demonstrated to be practical and will potentially facilitate Monte Carlo simulation for treatment planning and for retrospective analysis of treatment plans with little impact on the management of planning CT systems.

  3. Validation of a Monte Carlo model used for simulating tube current modulation in computed tomography over a wide range of phantom conditions/challenges

    SciTech Connect

    Bostani, Maryam McMillan, Kyle; Cagnon, Chris H.; McNitt-Gray, Michael F.; DeMarco, John J.

    2014-11-01

    Purpose: Monte Carlo (MC) simulation methods have been widely used in patient dosimetry in computed tomography (CT), including estimating patient organ doses. However, most simulation methods have undergone a limited set of validations, often using homogeneous phantoms with simple geometries. As clinical scanning has become more complex and the use of tube current modulation (TCM) has become pervasive in the clinic, MC simulations should include these techniques in their methodologies and therefore should also be validated using a variety of phantoms with different shapes and material compositions to result in a variety of differently modulated tube current profiles. The purpose of this work is to perform the measurements and simulations to validate a Monte Carlo model under a variety of test conditions where fixed tube current (FTC) and TCM were used. Methods: A previously developed MC model for estimating dose from CT scans that models TCM, built using the platform of MCNPX, was used for CT dose quantification. In order to validate the suitability of this model to accurately simulate patient dose from FTC and TCM CT scan, measurements and simulations were compared over a wide range of conditions. Phantoms used for testing range from simple geometries with homogeneous composition (16 and 32 cm computed tomography dose index phantoms) to more complex phantoms including a rectangular homogeneous water equivalent phantom, an elliptical shaped phantom with three sections (where each section was a homogeneous, but different material), and a heterogeneous, complex geometry anthropomorphic phantom. Each phantom requires varying levels of x-, y- and z-modulation. Each phantom was scanned on a multidetector row CT (Sensation 64) scanner under the conditions of both FTC and TCM. Dose measurements were made at various surface and depth positions within each phantom. Simulations using each phantom were performed for FTC, detailed x–y–z TCM, and z-axis-only TCM to obtain

  4. Using Monte Carlo ray tracing simulations to model the quantum harmonic oscillator modes observed in uranium nitride

    NASA Astrophysics Data System (ADS)

    Lin, J. Y. Y.; Aczel, A. A.; Abernathy, D. L.; Nagler, S. E.; Buyers, W. J. L.; Granroth, G. E.

    2014-04-01

    Recently an extended series of equally spaced vibrational modes was observed in uranium nitride (UN) by performing neutron spectroscopy measurements using the ARCS and SEQUOIA time-of-flight chopper spectrometers [A. A. Aczel et al., Nat. Commun. 3, 1124 (2012), 10.1038/ncomms2117]. These modes are well described by three-dimensional isotropic quantum harmonic oscillator (QHO) behavior of the nitrogen atoms, but there are additional contributions to the scattering that complicate the measured response. In an effort to better characterize the observed neutron scattering spectrum of UN, we have performed Monte Carlo ray tracing simulations of the ARCS and SEQUOIA experiments with various sample kernels, accounting for nitrogen QHO scattering, contributions that arise from the acoustic portion of the partial phonon density of states, and multiple scattering. These simulations demonstrate that the U and N motions can be treated independently, and show that multiple scattering contributes an approximate Q-independent background to the spectrum at the oscillator mode positions. Temperature-dependent studies of the lowest few oscillator modes have also been made with SEQUOIA, and our simulations indicate that the T dependence of the scattering from these modes is strongly influenced by the uranium lattice.

  5. Using Monte Carlo ray tracing simulations to model the quantum harmonic oscillator modes observed in uranium nitride

    SciTech Connect

    Lin, J. Y. Y.; Aczel, Adam A; Abernathy, Douglas L; Nagler, Stephen E; Buyers, W. J. L.; Granroth, Garrett E

    2014-01-01

    Recently an extended series of equally spaced vibrational modes was observed in uranium nitride (UN) by performing neutron spectroscopy measurements using the ARCS and SEQUOIA time-of- flight chopper spectrometers [A.A. Aczel et al, Nature Communications 3, 1124 (2012)]. These modes are well described by 3D isotropic quantum harmonic oscillator (QHO) behavior of the nitrogen atoms, but there are additional contributions to the scattering that complicate the measured response. In an effort to better characterize the observed neutron scattering spectrum of UN, we have performed Monte Carlo ray tracing simulations of the ARCS and SEQUOIA experiments with various sample kernels, accounting for the nitrogen QHO scattering, contributions that arise from the acoustic portion of the partial phonon density of states (PDOS), and multiple scattering. These simulations demonstrate that the U and N motions can be treated independently, and show that multiple scattering contributes an approximate Q-independent background to the spectrum at the oscillator mode positions. Temperature dependent studies of the lowest few oscillator modes have also been made with SEQUOIA, and our simulations indicate that the T-dependence of the scattering from these modes is strongly influenced by the uranium lattice.

  6. Monte Carlo simulation of Alaska wolf survival

    NASA Astrophysics Data System (ADS)

    Feingold, S. J.

    1996-02-01

    Alaskan wolves live in a harsh climate and are hunted intensively. Penna's biological aging code, using Monte Carlo methods, has been adapted to simulate wolf survival. It was run on the case in which hunting causes the disruption of wolves' social structure. Social disruption was shown to increase the number of deaths occurring at a given level of hunting. For high levels of social disruption, the population did not survive.

  7. Numerical reproducibility for implicit Monte Carlo simulations

    SciTech Connect

    Cleveland, M.; Brunner, T.; Gentile, N.

    2013-07-01

    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. In [1], a way of eliminating this roundoff error 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 reproducibility techniques, are described and compared in this work. Increased precision alone is not enough to ensure reproducibility of photon Monte Carlo simulations. A non-arbitrary precision approaches required 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. (authors)

  8. Monte Carlo simulations in Nuclear Medicine

    SciTech Connect

    Loudos, George K.

    2007-11-26

    Molecular imaging technologies provide unique abilities to localise signs of disease before symptoms appear, assist in drug testing, optimize and personalize therapy, and assess the efficacy of treatment regimes for different types of cancer. Monte Carlo simulation packages are used as an important tool for the optimal design of detector systems. In addition they have demonstrated potential to improve image quality and acquisition protocols. Many general purpose (MCNP, Geant4, etc) or dedicated codes (SimSET etc) have been developed aiming to provide accurate and fast results. Special emphasis will be given to GATE toolkit. The GATE code currently under development by the OpenGATE collaboration is the most accurate and promising code for performing realistic simulations. The purpose of this article is to introduce the non expert reader to the current status of MC simulations in nuclear medicine and briefly provide examples of current simulated systems, and present future challenges that include simulation of clinical studies and dosimetry applications.

  9. Monte Carlo simulations in Nuclear Medicine

    NASA Astrophysics Data System (ADS)

    Loudos, George K.

    2007-11-01

    Molecular imaging technologies provide unique abilities to localise signs of disease before symptoms appear, assist in drug testing, optimize and personalize therapy, and assess the efficacy of treatment regimes for different types of cancer. Monte Carlo simulation packages are used as an important tool for the optimal design of detector systems. In addition they have demonstrated potential to improve image quality and acquisition protocols. Many general purpose (MCNP, Geant4, etc) or dedicated codes (SimSET etc) have been developed aiming to provide accurate and fast results. Special emphasis will be given to GATE toolkit. The GATE code currently under development by the OpenGATE collaboration is the most accurate and promising code for performing realistic simulations. The purpose of this article is to introduce the non expert reader to the current status of MC simulations in nuclear medicine and briefly provide examples of current simulated systems, and present future challenges that include simulation of clinical studies and dosimetry applications.

  10. Monte Carlo simulation for the transport beamline

    SciTech Connect

    Romano, F.; Cuttone, G.; Jia, S. B.; Varisano, A.; Attili, A.; Marchetto, F.; Russo, G.; Cirrone, G. A. P.; Schillaci, F.; Scuderi, V.; Carpinelli, M.

    2013-07-26

    In the framework of the ELIMED project, Monte Carlo (MC) simulations are widely used to study the physical transport of charged particles generated by laser-target interactions and to preliminarily evaluate fluence and dose distributions. An energy selection system and the experimental setup for the TARANIS laser facility in Belfast (UK) have been already simulated with the GEANT4 (GEometry ANd Tracking) MC toolkit. Preliminary results are reported here. Future developments are planned to implement a MC based 3D treatment planning in order to optimize shots number and dose delivery.

  11. Interstellar simulations using a unified microscopic-macroscopic Monte Carlo model with a full gas-grain network including bulk diffusion in ice mantles

    SciTech Connect

    Chang, Qiang; Herbst, Eric

    2014-06-01

    We have designed an improved algorithm that enables us to simulate the chemistry of cold dense interstellar clouds with a full gas-grain reaction network. The chemistry is treated by a unified microscopic-macroscopic Monte Carlo approach that includes photon penetration and bulk diffusion. To determine the significance of these two processes, we simulate the chemistry with three different models. In Model 1, we use an exponential treatment to follow how photons penetrate and photodissociate ice species throughout the grain mantle. Moreover, the products of photodissociation are allowed to diffuse via bulk diffusion and react within the ice mantle. Model 2 is similar to Model 1 but with a slower bulk diffusion rate. A reference Model 0, which only allows photodissociation reactions to occur on the top two layers, is also simulated. Photodesorption is assumed to occur from the top two layers in all three models. We found that the abundances of major stable species in grain mantles do not differ much among these three models, and the results of our simulation for the abundances of these species agree well with observations. Likewise, the abundances of gas-phase species in the three models do not vary. However, the abundances of radicals in grain mantles can differ by up to two orders of magnitude depending upon the degree of photon penetration and the bulk diffusion of photodissociation products. We also found that complex molecules can be formed at temperatures as low as 10 K in all three models.

  12. Representation and simulation for pyrochlore lattice via Monte Carlo technique

    NASA Astrophysics Data System (ADS)

    Passos, André Luis; de Albuquerque, Douglas F.; Filho, João Batista Santos

    2016-05-01

    This work presents a representation of the Kagome and pyrochlore lattices using Monte Carlo simulation as well as some results of the critical properties. These lattices are composed corner sharing triangles and tetrahedrons respectively. The simulation was performed employing the Cluster Wolf Algorithm for the spin updates through the standard ferromagnetic Ising Model. The determination of the critical temperature and exponents was based on the Histogram Technique and the Finite-Size Scaling Theory.

  13. Shell model Monte Carlo methods

    SciTech Connect

    Koonin, S.E.; Dean, D.J.

    1996-10-01

    We review quantum Monte Carlo methods for dealing with large shell model problems. These methods reduce the imaginary-time many-body evolution operator to a coherent superposition of one-body evolutions in fluctuating one-body fields; resultant path integral is evaluated stochastically. We first discuss the motivation, formalism, and implementation of such Shell Model Monte Carlo methods. There then follows a sampler of results and insights obtained from a number of applications. These include the ground state and thermal properties of pf-shell nuclei, thermal behavior of {gamma}-soft nuclei, and calculation of double beta-decay matrix elements. Finally, prospects for further progress in such calculations are discussed. 87 refs.

  14. Combined Monte Carlo and path-integral method for simulated library of time-resolved reflectance curves from layered tissue models

    NASA Astrophysics Data System (ADS)

    Wilson, Robert H.; Vishwanath, Karthik; Mycek, Mary-Ann

    2009-02-01

    Monte Carlo (MC) simulations are considered the "gold standard" for mathematical description of photon transport in tissue, but they can require large computation times. Therefore, it is important to develop simple and efficient methods for accelerating MC simulations, especially when a large "library" of related simulations is needed. A semi-analytical method involving MC simulations and a path-integral (PI) based scaling technique generated time-resolved reflectance curves from layered tissue models. First, a zero-absorption MC simulation was run for a tissue model with fixed scattering properties in each layer. Then, a closed-form expression for the average classical path of a photon in tissue was used to determine the percentage of time that the photon spent in each layer, to create a weighted Beer-Lambert factor to scale the time-resolved reflectance of the simulated zero-absorption tissue model. This method is a unique alternative to other scaling techniques in that it does not require the path length or number of collisions of each photon to be stored during the initial simulation. Effects of various layer thicknesses and absorption and scattering coefficients on the accuracy of the method will be discussed.

  15. Inhomogeneous Monte Carlo simulations of dermoscopic spectroscopy

    NASA Astrophysics Data System (ADS)

    Gareau, Daniel S.; Li, Ting; Jacques, Steven; Krueger, James

    2012-03-01

    Clinical skin-lesion diagnosis uses dermoscopy: 10X epiluminescence microscopy. Skin appearance ranges from black to white with shades of blue, red, gray and orange. Color is an important diagnostic criteria for diseases including melanoma. Melanin and blood content and distribution impact the diffuse spectral remittance (300-1000nm). Skin layers: immersion medium, stratum corneum, spinous epidermis, basal epidermis and dermis as well as laterally asymmetric features (eg. melanocytic invasion) were modeled in an inhomogeneous Monte Carlo model.

  16. Dynamic Cluster Quantum Monte Carlo Simulations of a Two-Dimensional Hubbard Model with Stripelike Charge-Density-Wave Modulations: Interplay between Inhomogeneities and the Superconducting State

    SciTech Connect

    Maier, Thomas A; Alvarez, Gonzalo; Summers, Michael Stuart; Schulthess, Thomas C

    2010-01-01

    Using dynamic cluster quantum Monte Carlo simulations, we study the superconducting behavior of a 1=8 doped two-dimensional Hubbard model with imposed unidirectional stripelike charge-density-wave modulation. We find a significant increase of the pairing correlations and critical temperature relative to the homogeneous system when the modulation length scale is sufficiently large. With a separable form of the irreducible particle-particle vertex, we show that optimized superconductivity is obtained for a moderate modulation strength due to a delicate balance between the modulation enhanced pairing interaction, and a concomitant suppression of the bare particle-particle excitations by a modulation reduction of the quasiparticle weight.

  17. Monte-Carlo simulation of Callisto's exosphere

    NASA Astrophysics Data System (ADS)

    Vorburger, A.; Wurz, P.; Lammer, H.; Barabash, S.; Mousis, O.

    2015-12-01

    We model Callisto's exosphere based on its ice as well as non-ice surface via the use of a Monte-Carlo exosphere model. For the ice component we implement two putative compositions that have been computed from two possible extreme formation scenarios of the satellite. One composition represents the oxidizing state and is based on the assumption that the building blocks of Callisto were formed in the protosolar nebula and the other represents the reducing state of the gas, based on the assumption that the satellite accreted from solids condensed in the jovian sub-nebula. For the non-ice component we implemented the compositions of typical CI as well as L type chondrites. Both chondrite types have been suggested to represent Callisto's non-ice composition best. As release processes we consider surface sublimation, ion sputtering and photon-stimulated desorption. Particles are followed on their individual trajectories until they either escape Callisto's gravitational attraction, return to the surface, are ionized, or are fragmented. Our density profiles show that whereas the sublimated species dominate close to the surface on the sun-lit side, their density profiles (with the exception of H and H2) decrease much more rapidly than the sputtered particles. The Neutral gas and Ion Mass (NIM) spectrometer, which is part of the Particle Environment Package (PEP), will investigate Callisto's exosphere during the JUICE mission. Our simulations show that NIM will be able to detect sublimated and sputtered particles from both the ice and non-ice surface. NIM's measured chemical composition will allow us to distinguish between different formation scenarios.

  18. [Monte Carlo simulation of FCS in a laser gradient field].

    PubMed

    Chen, B; Meng, F; Ma, H; Ding, Y; Jin, L; Chen, D

    2001-06-01

    Fluorescence correlation spectroscopy (FCS) is a powerful tool for probing biological process inside living cells. It measures fluorescence fluctuations of small number of molecules and derive information on molecular kinetics and reactions. We have developed a Monte Carlo model to simulate Browning motion of Rayleigh particles in a laser gradient field. The simulation reveals relations between laser field strength and measured parameters from FCS, such as diffusion coefficient and number density of the particles. The simulated results agree qualitatively to the experimental results obtained using fluorescent spheres. Empirical relations from the simulation are also discussed. PMID:12947641

  19. Gibbs ensemble Monte Carlo simulation using an optimized potential model: pure acetic acid and a mixture of it with ethylene.

    PubMed

    Zhang, Minhua; Chen, Lihang; Yang, Huaming; Sha, Xijiang; Ma, Jing

    2016-07-01

    Gibbs ensemble Monte Carlo simulation with configurational bias was employed to study the vapor-liquid equilibrium (VLE) for pure acetic acid and for a mixture of acetic acid and ethylene. An improved united-atom force field for acetic acid based on a Lennard-Jones functional form was proposed. The Lennard-Jones well depth and size parameters for the carboxyl oxygen and hydroxyl oxygen were determined by fitting the interaction energies of acetic acid dimers to the Lennard-Jones potential function. Four different acetic acid dimers and the proportions of them were considered when the force field was optimized. It was found that the new optimized force field provides a reasonable description of the vapor-liquid phase equilibrium for pure acetic acid and for the mixture of acetic acid and ethylene. Accurate values were obtained for the saturated liquid density of the pure compound (average deviation: 0.84 %) and for the critical points. The new optimized force field demonstrated greater accuracy and reliability in calculations of the solubility of the mixture of acetic acid and ethylene as compared with the results obtained with the original TraPPE-UA force field. PMID:27324633

  20. Coherent Scattering Imaging Monte Carlo Simulation

    NASA Astrophysics Data System (ADS)

    Hassan, Laila Abdulgalil Rafik

    Conventional mammography has poor contrast between healthy and cancerous tissues due to the small difference in attenuation properties. Coherent scatter potentially provides more information because interference of coherently scattered radiation depends on the average intermolecular spacing, and can be used to characterize tissue types. However, typical coherent scatter analysis techniques are not compatible with rapid low dose screening techniques. Coherent scatter slot scan imaging is a novel imaging technique which provides new information with higher contrast. In this work a simulation of coherent scatter was performed for slot scan imaging to assess its performance and provide system optimization. In coherent scatter imaging, the coherent scatter is exploited using a conventional slot scan mammography system with anti-scatter grids tilted at the characteristic angle of cancerous tissues. A Monte Carlo simulation was used to simulate the coherent scatter imaging. System optimization was performed across several parameters, including source voltage, tilt angle, grid distances, grid ratio, and shielding geometry. The contrast increased as the grid tilt angle increased beyond the characteristic angle for the modeled carcinoma. A grid tilt angle of 16 degrees yielded the highest contrast and signal to noise ratio (SNR). Also, contrast increased as the source voltage increased. Increasing grid ratio improved contrast at the expense of decreasing SNR. A grid ratio of 10:1 was sufficient to give a good contrast without reducing the intensity to a noise level. The optimal source to sample distance was determined to be such that the source should be located at the focal distance of the grid. A carcinoma lump of 0.5x0.5x0.5 cm3 in size was detectable which is reasonable considering the high noise due to the usage of relatively small number of incident photons for computational reasons. A further study is needed to study the effect of breast density and breast thickness

  1. Multiresponse multilayer vadose zone model calibration using Markov chain Monte Carlo simulation and field water retention data

    NASA Astrophysics Data System (ADS)

    WöHling, Thomas; Vrugt, Jasper A.

    2011-04-01

    In the past two decades significant progress has been made toward the application of inverse modeling to estimate the water retention and hydraulic conductivity functions of the vadose zone at different spatial scales. Many of these contributions have focused on estimating only a few soil hydraulic parameters, without recourse to appropriately capturing and addressing spatial variability. The assumption of a homogeneous medium significantly simplifies the complexity of the resulting inverse problem, allowing the use of classical parameter estimation algorithms. Here we present an inverse modeling study with a high degree of vertical complexity that involves calibration of a 25 parameter Richards'-based HYDRUS-1D model using in situ measurements of volumetric water content and pressure head from multiple depths in a heterogeneous vadose zone in New Zealand. We first determine the trade-off in the fitting of both data types using the AMALGAM multiple objective evolutionary search algorithm. Then we adopt a Bayesian framework and derive posterior probability density functions of parameter and model predictive uncertainty using the recently developed differential evolution adaptive metropolis, DREAMZS adaptive Markov chain Monte Carlo scheme. We use four different formulations of the likelihood function each differing in their underlying assumption about the statistical properties of the error residual and data used for calibration. We show that AMALGAM and DREAMZS can solve for the 25 hydraulic parameters describing the water retention and hydraulic conductivity functions of the multilayer heterogeneous vadose zone. Our study clearly highlights that multiple data types are simultaneously required in the likelihood function to result in an accurate soil hydraulic characterization of the vadose zone of interest. Remaining error residuals are most likely caused by model deficiencies that are not encapsulated by the multilayer model and can not be accessed by the

  2. Monte Carlo simulations of medical imaging modalities

    SciTech Connect

    Estes, G.P.

    1998-09-01

    Because continuous-energy Monte Carlo radiation transport calculations can be nearly exact simulations of physical reality (within data limitations, geometric approximations, transport algorithms, etc.), it follows that one should be able to closely approximate the results of many experiments from first-principles computations. This line of reasoning has led to various MCNP studies that involve simulations of medical imaging modalities and other visualization methods such as radiography, Anger camera, computerized tomography (CT) scans, and SABRINA particle track visualization. It is the intent of this paper to summarize some of these imaging simulations in the hope of stimulating further work, especially as computer power increases. Improved interpretation and prediction of medical images should ultimately lead to enhanced medical treatments. It is also reasonable to assume that such computations could be used to design new or more effective imaging instruments.

  3. Monte-Carlo Simulation Balancing in Practice

    NASA Astrophysics Data System (ADS)

    Huang, Shih-Chieh; Coulom, Rémi; Lin, Shun-Shii

    Simulation balancing is a new technique to tune parameters of a playout policy for a Monte-Carlo game-playing program. So far, this algorithm had only been tested in a very artificial setting: it was limited to 5×5 and 6×6 Go, and required a stronger external program that served as a supervisor. In this paper, the effectiveness of simulation balancing is demonstrated in a more realistic setting. A state-of-the-art program, Erica, learned an improved playout policy on the 9×9 board, without requiring any external expert to provide position evaluations. The evaluations were collected by letting the program analyze positions by itself. The previous version of Erica learned pattern weights with the minorization-maximization algorithm. Thanks to simulation balancing, its playing strength was improved from a winning rate of 69% to 78% against Fuego 0.4.

  4. Gauss or Bernoulli? A Monte Carlo Comparison of the Performance of the Linear Mixed-Model and the Logistic Mixed-Model Analyses in Simulated Community Trials with a Dichotomous Outcome Variable at the Individual Level.

    ERIC Educational Resources Information Center

    Hannan, Peter J.; Murray, David M.

    1996-01-01

    A Monte Carlo study compared performance of linear and logistic mixed-model analyses of simulated community trials having specific event rates, intraclass correlations, and degrees of freedom. Results indicate that in studies with adequate denominator degrees of freedom, the researcher may use either method of analysis, with certain cautions. (SLD)

  5. Cluster evolution and critical cluster sizes for the square and triangular lattice Ising models using lattice animals and Monte Carlo simulations

    NASA Astrophysics Data System (ADS)

    Eising, G.; Kooi, B. J.

    2012-06-01

    Growth and decay of clusters at temperatures below Tc have been studied for a two-dimensional Ising model for both square and triangular lattices using Monte Carlo (MC) simulations and the enumeration of lattice animals. For the lattice animals, all unique cluster configurations with their internal bonds were identified up to 25 spins for the triangular lattice and up to 29 spins for the square lattice. From these configurations, the critical cluster sizes for nucleation have been determined based on two (thermodynamic) definitions. From the Monte Carlo simulations, the critical cluster size is also obtained by studying the decay and growth of inserted, most compact clusters of different sizes. A good agreement is found between the results from the MC simulations and one of the definitions of critical size used for the lattice animals at temperatures T > ˜0.4 Tc for the square lattice and T > ˜0.2 Tc for the triangular lattice (for the range of external fields H considered). At low temperatures (T ≈ 0.2 Tc for the square lattice and T ≈ 0.1 Tc for the triangular lattice), magic numbers are found in the size distributions during the MC simulations. However, these numbers are not present in the critical cluster sizes based on the MC simulations, as they are present for the lattice animal data. In order to achieve these magic numbers in the critical cluster sizes based on the MC simulation, the temperature has to be reduced further to T ≈ 0.15 Tc for the square lattice. The observed evolution of magic numbers as a function of temperature is rationalized in the present work.

  6. Monte Carlo Strategies for Selecting Parameter Values in Simulation Experiments.

    PubMed

    Leigh, Jessica W; Bryant, David

    2015-09-01

    Simulation experiments are used widely throughout evolutionary biology and bioinformatics to compare models, promote methods, and test hypotheses. The biggest practical constraint on simulation experiments is the computational demand, particularly as the number of parameters increases. Given the extraordinary success of Monte Carlo methods for conducting inference in phylogenetics, and indeed throughout the sciences, we investigate ways in which Monte Carlo framework can be used to carry out simulation experiments more efficiently. The key idea is to sample parameter values for the experiments, rather than iterate through them exhaustively. Exhaustive analyses become completely infeasible when the number of parameters gets too large, whereas sampled approaches can fare better in higher dimensions. We illustrate the framework with applications to phylogenetics and genetic archaeology. PMID:26012871

  7. A tetrahedron-based inhomogeneous Monte Carlo optical simulator

    PubMed Central

    Shen, H; Wang, G

    2010-01-01

    Optical imaging has been widely applied in preclinical and clinical applications. Fifteen years ago, an efficient Monte Carlo program ‘MCML’ was developed for use with multi-layered turbid media and has gained popularity in the field of biophotonics. Currently, there is an increasingly pressing need for simulating tools more powerful than MCML in order to study light propagation phenomena in complex inhomogeneous objects, such as the mouse. Here we report a tetrahedron-based inhomogeneous Monte Carlo optical simulator (TIM-OS) to address this issue. By modeling an object as a tetrahedron-based inhomogeneous finite-element mesh, TIM-OS can determine the photon– triangle interaction recursively and rapidly. In numerical simulation, we have demonstrated the correctness and efficiency of TIM-OS. PMID:20090182

  8. Monte Carlo simulations within avalanche rescue

    NASA Astrophysics Data System (ADS)

    Reiweger, Ingrid; Genswein, Manuel; Schweizer, Jürg

    2016-04-01

    Refining concepts for avalanche rescue involves calculating suitable settings for rescue strategies such as an adequate probing depth for probe line searches or an optimal time for performing resuscitation for a recovered avalanche victim in case of additional burials. In the latter case, treatment decisions have to be made in the context of triage. However, given the low number of incidents it is rarely possible to derive quantitative criteria based on historical statistics in the context of evidence-based medicine. For these rare, but complex rescue scenarios, most of the associated concepts, theories, and processes involve a number of unknown "random" parameters which have to be estimated in order to calculate anything quantitatively. An obvious approach for incorporating a number of random variables and their distributions into a calculation is to perform a Monte Carlo (MC) simulation. We here present Monte Carlo simulations for calculating the most suitable probing depth for probe line searches depending on search area and an optimal resuscitation time in case of multiple avalanche burials. The MC approach reveals, e.g., new optimized values for the duration of resuscitation that differ from previous, mainly case-based assumptions.

  9. Multilevel Monte Carlo simulation of Coulomb collisions

    DOE PAGESBeta

    Rosin, M. S.; Ricketson, L. F.; Dimits, A. M.; Caflisch, R. E.; Cohen, B. I.

    2014-05-29

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

  10. Multilevel Monte Carlo simulation of Coulomb collisions

    SciTech Connect

    Rosin, M. S.; Ricketson, L. F.; Dimits, A. M.; Caflisch, R. E.; Cohen, B. I.

    2014-05-29

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

  11. Coherent scatter imaging Monte Carlo simulation.

    PubMed

    Hassan, Laila; MacDonald, Carolyn A

    2016-07-01

    Conventional mammography can suffer from poor contrast between healthy and cancerous tissues due to the small difference in attenuation properties. Coherent scatter slot scan imaging is an imaging technique which provides additional information and is compatible with conventional mammography. A Monte Carlo simulation of coherent scatter slot scan imaging was performed to assess its performance and provide system optimization. Coherent scatter could be exploited using a system similar to conventional slot scan mammography system with antiscatter grids tilted at the characteristic angle of cancerous tissues. System optimization was performed across several parameters, including source voltage, tilt angle, grid distances, grid ratio, and shielding geometry. The simulated carcinomas were detectable for tumors as small as 5 mm in diameter, so coherent scatter analysis using a wide-slot setup could be promising as an enhancement for screening mammography. Employing coherent scatter information simultaneously with conventional mammography could yield a conventional high spatial resolution image with additional coherent scatter information. PMID:27610397

  12. Kinetic Monte Carlo simulations of proton conductivity

    NASA Astrophysics Data System (ADS)

    Masłowski, T.; Drzewiński, A.; Ulner, J.; Wojtkiewicz, J.; Zdanowska-Frączek, M.; Nordlund, K.; Kuronen, A.

    2014-07-01

    The kinetic Monte Carlo method is used to model the dynamic properties of proton diffusion in anhydrous proton conductors. The results have been discussed with reference to a two-step process called the Grotthuss mechanism. There is a widespread belief that this mechanism is responsible for fast proton mobility. We showed in detail that the relative frequency of reorientation and diffusion processes is crucial for the conductivity. Moreover, the current dependence on proton concentration has been analyzed. In order to test our microscopic model the proton transport in polymer electrolyte membranes based on benzimidazole C7H6N2 molecules is studied.

  13. Monte Carlo Simulations and Generation of the SPI Response

    NASA Technical Reports Server (NTRS)

    Sturner, S. J.; Shrader, C. R.; Weidenspointner, G.; Teegarden, B. J.; Attie, D.; Cordier, B.; Diehl, R.; Ferguson, C.; Jean, P.; vonKienlin, A.

    2003-01-01

    In this paper we discuss the methods developed for the production of the INTEGRAL/SPI instrument response. The response files were produced using a suite of Monte Carlo simulation software developed at NASA/GSFC based on the GEANT-3 package available from CERN. The production of the INTEGRAL/SPI instrument response also required the development of a detailed computer mass model for SPI. We discuss ow extensive investigations into methods to reduce both the computation time and storage requirements for the SPI response. We also discuss corrections to the simulated response based on our comparison of ground and infiight Calibration data with MGEANT simulations.

  14. Monte Carlo Simulations and Generation of the SPI Response

    NASA Technical Reports Server (NTRS)

    Sturner, S. J.; Shrader, C. R.; Weidenspointner, G.; Teegarden, B. J.; Attie, D.; Diehl, R.; Ferguson, C.; Jean, P.; vonKienlin, A.

    2003-01-01

    In this paper we discuss the methods developed for the production of the INTEGRAL/SPI instrument response. The response files were produced using a suite of Monte Carlo simulation software developed at NASA/GSFC based on the GEANT-3 package available from CERN. The production of the INTEGRAL/SPI instrument response also required the development of a detailed computer mass model for SPI. We discuss our extensive investigations into methods to reduce both the computation time and storage requirements for the SPI response. We also discuss corrections to the simulated response based on our comparison of ground and inflight calibration data with MGEANT simulation.

  15. MO-G-17A-04: Internal Dosimetric Calculations for Pediatric Nuclear Imaging Applications, Using Monte Carlo Simulations and High-Resolution Pediatric Computational Models

    SciTech Connect

    Papadimitroulas, P; Kagadis, GC; Loudos, G

    2014-06-15

    Purpose: Our purpose is to evaluate the administered absorbed dose in pediatric, nuclear imaging studies. Monte Carlo simulations with the incorporation of pediatric computational models can serve as reference for the accurate determination of absorbed dose. The procedure of the calculated dosimetric factors is described, while a dataset of reference doses is created. Methods: Realistic simulations were executed using the GATE toolkit and a series of pediatric computational models, developed by the “IT'IS Foundation”. The series of the phantoms used in our work includes 6 models in the range of 5–14 years old (3 boys and 3 girls). Pre-processing techniques were applied to the images, to incorporate the phantoms in GATE simulations. The resolution of the phantoms was set to 2 mm3. The most important organ densities were simulated according to the GATE “Materials Database”. Several used radiopharmaceuticals in SPECT and PET applications are being tested, following the EANM pediatric dosage protocol. The biodistributions of the several isotopes used as activity maps in the simulations, were derived by the literature. Results: Initial results of absorbed dose per organ (mGy) are presented in a 5 years old girl from the whole body exposure to 99mTc - SestaMIBI, 30 minutes after administration. Heart, kidney, liver, ovary, pancreas and brain are the most critical organs, in which the S-factors are calculated. The statistical uncertainty in the simulation procedure was kept lower than 5%. The Sfactors for each target organ are calculated in Gy/(MBq*sec) with highest dose being absorbed in kidneys and pancreas (9.29*10{sup 10} and 0.15*10{sup 10} respectively). Conclusion: An approach for the accurate dosimetry on pediatric models is presented, creating a reference dosage dataset for several radionuclides in children computational models with the advantages of MC techniques. Our study is ongoing, extending our investigation to other reference models and

  16. SU-E-T-58: Calculation of Dose Distribution of Accuboost Brachytherapy in Deformable Polyvinil Alcohol Breast Phantom Using Biomechanical Modeling and Monte Carlo Simulation

    SciTech Connect

    Mohammadyari, P; Faghihi, R; Shirazi, M Mosleh; Lotfi, M; Meigooni, A

    2014-06-01

    Purpose: the accuboost is the most modern method of breast brachytherapy that is a boost method in compressed tissue by a mammography unit. the dose distribution in uncompressed tissue, as compressed tissue is important that should be characterized. Methods: In this study, the mechanical behavior of breast in mammography loading, the displacement of breast tissue and the dose distribution in compressed and uncompressed tissue, are investigated. Dosimetry was performed by two dosimeter methods of Monte Carlo simulations using MCNP5 code and thermoluminescence dosimeters. For Monte Carlo simulations, the dose values in cubical lattice were calculated using tally F6. The displacement of the breast elements was simulated by Finite element model and calculated using ABAQUS software, from which the 3D dose distribution in uncompressed tissue was determined. The geometry of the model is constructed from MR images of 6 volunteers. Experimental dosimetery was performed by placing the thermoluminescence dosimeters into the polyvinyl alcohol breast equivalent phantom and on the proximal edge of compression plates to the chest. Results: The results indicate that using the cone applicators would deliver more than 95% of dose to the depth of 5 to 17mm, while round applicator will increase the skin dose. Nodal displacement, in presence of gravity and 60N forces, i.e. in mammography compression, was determined with 43% contraction in the loading direction and 37% expansion in orthogonal orientation. Finally, in comparison of the acquired from thermoluminescence dosimeters with MCNP5, they are consistent with each other in breast phantom and in chest's skin with average different percentage of 13.7±5.7 and 7.7±2.3, respectively. Conclusion: The major advantage of this kind of dosimetry is the ability of 3D dose calculation by FE Modeling. Finally, polyvinyl alcohol is a reliable material as a breast tissue equivalent dosimetric phantom that provides the ability of TLD dosimetry

  17. Monte Carlo simulation of electron swarm parameters in O2

    NASA Astrophysics Data System (ADS)

    Settaouti, A.; Settaouti, L.

    2007-03-01

    Oxygen plasmas have found numerous applications in plasma processing, such as reactive sputtering, dry etching of polymers, oxidation, and resist removal of semiconductors. Swarm and transport coefficients are essential for better understanding and modelling of these gas discharge processes. The electron swarms in a gas under the influence of an electric field can be simulated with the help of a Monte Carlo method. The swarm parameters evaluated are compared with experimental results.

  18. SciDAC Center for Simulation of Wave-Plasma Interactions - Iterated Finite-Orbit Monte Carlo Simulations with Full-Wave Fields for Modeling Tokamak ICRF Wave Heating Experiments - Final Report

    SciTech Connect

    Choi, Myunghee; Chan, Vincent S.

    2014-02-28

    This final report describes the work performed under U.S. Department of Energy Cooperative Agreement DE-FC02-08ER54954 for the period April 1, 2011 through March 31, 2013. The goal of this project was to perform iterated finite-orbit Monte Carlo simulations with full-wall fields for modeling tokamak ICRF wave heating experiments. In year 1, the finite-orbit Monte-Carlo code ORBIT-RF and its iteration algorithms with the full-wave code AORSA were improved to enable systematical study of the factors responsible for the discrepancy in the simulated and the measured fast-ion FIDA signals in the DIII-D and NSTX ICRF fast-wave (FW) experiments. In year 2, ORBIT-RF was coupled to the TORIC full-wave code for a comparative study of ORBIT-RF/TORIC and ORBIT-RF/AORSA results in FW experiments.

  19. Reconstruction of Exposure to m-Xylene from Human Biomonitoring Data Using PBPK Modelling, Bayesian Inference, and Markov Chain Monte Carlo Simulation

    PubMed Central

    McNally, Kevin; Cotton, Richard; Cocker, John; Jones, Kate; Bartels, Mike; Rick, David; Price, Paul; Loizou, George

    2012-01-01

    There are numerous biomonitoring programs, both recent and ongoing, to evaluate environmental exposure of humans to chemicals. Due to the lack of exposure and kinetic data, the correlation of biomarker levels with exposure concentrations leads to difficulty in utilizing biomonitoring data for biological guidance values. Exposure reconstruction or reverse dosimetry is the retrospective interpretation of external exposure consistent with biomonitoring data. We investigated the integration of physiologically based pharmacokinetic modelling, global sensitivity analysis, Bayesian inference, and Markov chain Monte Carlo simulation to obtain a population estimate of inhalation exposure to m-xylene. We used exhaled breath and venous blood m-xylene and urinary 3-methylhippuric acid measurements from a controlled human volunteer study in order to evaluate the ability of our computational framework to predict known inhalation exposures. We also investigated the importance of model structure and dimensionality with respect to its ability to reconstruct exposure. PMID:22719759

  20. Volcanic Event Recurrence Rate Model (VERRM): Incorporating Radiometric Ages, Volcanic Stratigraphy and Paleomagnetic Data into a Monte Carlo Simulation to Estimate Uncertainty in Recurrence Rate through Time

    NASA Astrophysics Data System (ADS)

    Wilson, J. A.; Richardson, J. A.

    2015-12-01

    Traditional methods used to calculate recurrence rate of volcanism, such as linear regression, maximum likelihood and Weibull-Poisson distributions, are effective at estimating recurrence rate and confidence level, but these methods are unable to estimate uncertainty in recurrence rate through time. We propose a new model for estimating recurrence rate and uncertainty, Volcanic Event Recurrence Rate Model. VERRM is an algorithm that incorporates radiometric ages, volcanic stratigraphy and paleomagnetic data into a Monte Carlo simulation, generating acceptable ages for each event. Each model run is used to calculate recurrence rate using a moving average window. These rates are binned into discrete time intervals and plotted using the 5th, 50th and 95th percentiles. We present recurrence rates from Cima Volcanic Field (CA), Yucca Mountain (NV) and Arsia Mons (Mars). Results from Cima Volcanic Field illustrate how several K-Ar ages with large uncertainties obscure three well documented volcanic episodes. Yucca Mountain results are similar to published rates and illustrate the use of using the same radiometric age for multiple events in a spatially defined cluster. Arsia Mons results show a clear waxing/waning of volcanism through time. VERRM output may be used for a spatio-temporal model or to plot uncertainty in quantifiable parameters such as eruption volume or geochemistry. Alternatively, the algorithm may be reworked to constrain geomagnetic chrons. VERRM is implemented in Python 2.7 and takes advantage of NumPy, SciPy and matplotlib libraries for optimization and quality plotting presentation. A typical Monte Carlo simulation of 40 volcanic events takes a few minutes to couple hours to complete, depending on the bin size used to assign ages.

  1. Poster — Thur Eve — 46: Monte Carlo model of the Novalis Classic 6MV stereotactic linear accelerator using the GATE simulation platform

    SciTech Connect

    Wiebe, J; Ploquin, N

    2014-08-15

    Monte Carlo (MC) simulation is accepted as the most accurate method to predict dose deposition when compared to other methods in radiation treatment planning. Current dose calculation algorithms used for treatment planning can become inaccurate when small radiation fields and tissue inhomogeneities are present. At our centre the Novalis Classic linear accelerator (linac) is used for Stereotactic Radiosurgery (SRS). The first MC model to date of the Novalis Classic linac was developed at our centre using the Geant4 Application for Tomographic Emission (GATE) simulation platform. GATE is relatively new, open source MC software built from CERN's Geometry and Tracking 4 (Geant4) toolkit. The linac geometry was modeled using manufacturer specifications, as well as in-house measurements of the micro MLC's. Among multiple model parameters, the initial electron beam was adjusted so that calculated depth dose curves agreed with measured values. Simulations were run on the European Grid Infrastructure through GateLab. Simulation time is approximately 8 hours on GateLab for a complete head model simulation to acquire a phase space file. Current results have a majority of points within 3% of the measured dose values for square field sizes ranging from 6×6 mm{sup 2} to 98×98 mm{sup 2} (maximum field size on the Novalis Classic linac) at 100 cm SSD. The x-ray spectrum was determined from the MC data as well. The model provides an investigation into GATE'S capabilities and has the potential to be used as a research tool and an independent dose calculation engine for clinical treatment plans.

  2. Calculating Remote Sensing Reflectance Uncertainties Using an Instrument Model Propagated Through Atmospheric Correction via Monte Carlo Simulations

    NASA Technical Reports Server (NTRS)

    Karakoylu, E.; Franz, B.

    2016-01-01

    First attempt at quantifying uncertainties in ocean remote sensing reflectance satellite measurements. Based on 1000 iterations of Monte Carlo. Data source is a SeaWiFS 4-day composite, 2003. The uncertainty is for remote sensing reflectance (Rrs) at 443 nm.

  3. Quantum Monte Carlo simulations in novel geometries

    NASA Astrophysics Data System (ADS)

    Iglovikov, Vladimir

    Quantum Monte Carlo simulations are giving increasing insight into the physics of strongly interacting bosons, spins, and fermions. Initial work focused on the simplest geometries, like a 2D square lattice. Increasingly, modern research is turning to more rich structures such as honeycomb lattice of graphene, the Lieb lattice of the CuO2 planes of cuprate superconductors, the triangular lattice, and coupled layers. These new geometries possess unique features which affect the physics in profound ways, eg a vanishing density of states and relativistic dispersion ("Dirac point'') of a honeycomb lattice, frustration on a triangular lattice, and a flat bands on a Lieb lattice. This thesis concerns both exploring the performance of QMC algorithms on different geometries(primarily via the "sign problem'') and also applying those algorithms to several interesting open problems.

  4. Resist develop prediction by Monte Carlo simulation

    NASA Astrophysics Data System (ADS)

    Sohn, Dong-Soo; Jeon, Kyoung-Ah; Sohn, Young-Soo; Oh, Hye-Keun

    2002-07-01

    Various resist develop models have been suggested to express the phenomena from the pioneering work of Dill's model in 1975 to the recent Shipley's enhanced notch model. The statistical Monte Carlo method can be applied to the process such as development and post exposure bake. The motions of developer during development process were traced by using this method. We have considered that the surface edge roughness of the resist depends on the weight percentage of protected and de-protected polymer in the resist. The results are well agreed with other papers. This study can be helpful for the developing of new photoresist and developer that can be used to pattern the device features smaller than 100 nm.

  5. Atomistic Monte Carlo Simulation of Lipid Membranes

    PubMed Central

    Wüstner, Daniel; Sklenar, Heinz

    2014-01-01

    Biological membranes are complex assemblies of many different molecules of which analysis demands a variety of experimental and computational approaches. In this article, we explain challenges and advantages of atomistic Monte Carlo (MC) simulation of lipid membranes. We provide an introduction into the various move sets that are implemented in current MC methods for efficient conformational sampling of lipids and other molecules. In the second part, we demonstrate for a concrete example, how an atomistic local-move set can be implemented for MC simulations of phospholipid monomers and bilayer patches. We use our recently devised chain breakage/closure (CBC) local move set in the bond-/torsion angle space with the constant-bond-length approximation (CBLA) for the phospholipid dipalmitoylphosphatidylcholine (DPPC). We demonstrate rapid conformational equilibration for a single DPPC molecule, as assessed by calculation of molecular energies and entropies. We also show transition from a crystalline-like to a fluid DPPC bilayer by the CBC local-move MC method, as indicated by the electron density profile, head group orientation, area per lipid, and whole-lipid displacements. We discuss the potential of local-move MC methods in combination with molecular dynamics simulations, for example, for studying multi-component lipid membranes containing cholesterol. PMID:24469314

  6. Simulations of atmospheric pressure discharge in a high-voltage nanosecond pulse using the particle-in-cell Monte Carlo collision model in noble gases

    NASA Astrophysics Data System (ADS)

    Shi, Feng; Wang, Dezhen; Ren, Chunsheng

    2008-06-01

    Atmospheric pressure discharge nonequilibrium plasmas have been applied to plasma processing with modern technology. Simulations of discharge in pure Ar and pure He gases at one atmospheric pressure by a high voltage trapezoidal nanosecond pulse have been performed using a one-dimensional particle-in-cell Monte Carlo collision (PIC-MCC) model coupled with a renormalization and weighting procedure (mapping algorithm). Numerical results show that the characteristics of discharge in both inert gases are very similar. There exist the effects of local reverse field and double-peak distributions of charged particles' density. The electron and ion energy distribution functions are also observed, and the discharge is concluded in the view of ionization avalanche in number. Furthermore, the independence of total current density is a function of time, but not of position.

  7. Solvent–amino acid interaction energies in three-dimensional-lattice Monte Carlo simulations of a model 27-mer protein: Folding thermodynamics and kinetics

    PubMed Central

    Leonhard, Kai; Prausnitz, John M.; Radke, Clayton J.

    2004-01-01

    Amino acid residue–solvent interactions are required for lattice Monte Carlo simulations of model proteins in water. In this study, we propose an interaction-energy scale that is based on the interaction scale by Miyazawa and Jernigan. It permits systematic variation of the amino acid–solvent interactions by introducing a contrast parameter for the hydrophobicity, Cs, and a mean attraction parameter for the amino acids, ω. Changes in the interaction energies strongly affect many protein properties. We present an optimized energy parameter set for best representing realistic behavior typical for many proteins (fast folding and high cooperativity for single chains). Our optimal parameters feature a much weaker hydrophobicity contrast and mean attraction than does the original interaction scale. The proposed interaction scale is designed for calculating the behavior of proteins in bulk and at interfaces as a function of solvent characteristics, as well as protein size and sequence. PMID:14739322

  8. Multi-wavelength simulations of atmospheric radiation from Io with a 3-D spherical-shell backward Monte Carlo radiative transfer model

    NASA Astrophysics Data System (ADS)

    Gratiy, Sergey L.; Walker, Andrew C.; Levin, Deborah A.; Goldstein, David B.; Varghese, Philip L.; Trafton, Laurence M.; Moore, Chris H.

    2010-05-01

    Conflicting observations regarding the dominance of either sublimation or volcanism as the source of the atmosphere on Io and disparate reports on the extent of its spatial distribution and the absolute column abundance invite the development of detailed computational models capable of improving our understanding of Io's unique atmospheric structure and origin. Improving upon previous models, Walker et al. (Walker, A.C., Gratiy, S.L., Levin, D.A., Goldstein, D.B., Varghese, P.L., Trafton, L.M., Moore, C.H., Stewart, B. [2009]. Icarus) developed a fully 3-D global rarefied gas dynamics model of Io's atmosphere including both sublimation and volcanic sources of SO 2 gas. The fidelity of the model is tested by simulating remote observations at selected wavelength bands and comparing them to the corresponding astronomical observations of Io's atmosphere. The simulations are performed with a new 3-D spherical-shell radiative transfer code utilizing a backward Monte Carlo method. We present: (1) simulations of the mid-infrared disk-integrated spectra of Io's sunlit hemisphere at 19 μm, obtained with TEXES during 2001-2004; (2) simulations of disk-resolved images at Lyman- α obtained with the Hubble Space Telescope (HST), Space Telescope Imaging Spectrograph (STIS) during 1997-2001; and (3) disk-integrated simulations of emission line profiles in the millimeter wavelength range obtained with the IRAM-30 m telescope in October-November 1999. We found that the atmospheric model generally reproduces the longitudinal variation in band depth from the mid-infrared data; however, the best match is obtained when our simulation results are shifted ˜30° toward lower orbital longitudes. The simulations of Lyman- α images do not reproduce the mid-to-high latitude bright patches seen in the observations, suggesting that the model atmosphere sustains columns that are too high at those latitudes. The simulations of emission line profiles in the millimeter spectral region support

  9. Dosimetric accuracy of a deterministic radiation transport based {sup 192}Ir brachytherapy treatment planning system. Part III. Comparison to Monte Carlo simulation in voxelized anatomical computational models

    SciTech Connect

    Zourari, K.; Pantelis, E.; Moutsatsos, A.; Sakelliou, L.; Georgiou, E.; Karaiskos, P.; Papagiannis, P.

    2013-01-15

    Purpose: To compare TG43-based and Acuros deterministic radiation transport-based calculations of the BrachyVision treatment planning system (TPS) with corresponding Monte Carlo (MC) simulation results in heterogeneous patient geometries, in order to validate Acuros and quantify the accuracy improvement it marks relative to TG43. Methods: Dosimetric comparisons in the form of isodose lines, percentage dose difference maps, and dose volume histogram results were performed for two voxelized mathematical models resembling an esophageal and a breast brachytherapy patient, as well as an actual breast brachytherapy patient model. The mathematical models were converted to digital imaging and communications in medicine (DICOM) image series for input to the TPS. The MCNP5 v.1.40 general-purpose simulation code input files for each model were prepared using information derived from the corresponding DICOM RT exports from the TPS. Results: Comparisons of MC and TG43 results in all models showed significant differences, as reported previously in the literature and expected from the inability of the TG43 based algorithm to account for heterogeneities and model specific scatter conditions. A close agreement was observed between MC and Acuros results in all models except for a limited number of points that lay in the penumbra of perfectly shaped structures in the esophageal model, or at distances very close to the catheters in all models. Conclusions: Acuros marks a significant dosimetry improvement relative to TG43. The assessment of the clinical significance of this accuracy improvement requires further work. Mathematical patient equivalent models and models prepared from actual patient CT series are useful complementary tools in the methodology outlined in this series of works for the benchmarking of any advanced dose calculation algorithm beyond TG43.

  10. A radiative transfer model to simulate light scattering in a compact granular medium using a Monte‒Carlo approach: Validation and first applications

    NASA Astrophysics Data System (ADS)

    Pilorget, C.; Vincendon, M.; Poulet, F.

    2013-12-01

    A new radiative transfer model to simulate light scattering in a compact granular medium using a Monte‒Carlo approach is presented. The physical and compositional properties of the sample can be specified at the grain scale, thus allowing to simulate different kinds of heterogeneties/mixtures within the sample. The radiative transfer is then calculated using a ray tracing approach between the grains, and probabilistic physical parameters such as a single scattering albedo and a phase function at the grain level. The reflectance and the albedo can be computed at different scales and for different geometries: from the grain scale to the sample one. The photometric behavior of the model is validated by comparing the bidirectional reflectance obtained for various media and geometries with the one of semi‒infinite multilayer models, and a few first applications are presented. This model will be used to refine our understanding of visible/NIR remote sensing data of planetary surfaces, as well as future measurements of hyperspectral microscopes which may be able to resolve spatial compositional heterogeneities within a given sample.

  11. Optimal dosing regimen of biapenem in Chinese patients with lower respiratory tract infections based on population pharmacokinetic/pharmacodynamic modelling and Monte Carlo simulation.

    PubMed

    Dong, Jing; Xiong, Wei; Chen, Yuancheng; Zhao, Yunfeng; Lu, Yang; Zhao, Di; Li, Wenyan; Liu, Yanhui; Chen, Xijing

    2016-03-01

    In this study, a population pharmacokinetic (PPK) model of biapenem in Chinese patients with lower respiratory tract infections (LRTIs) was developed and optimal dosage regimens based on Monte Carlo simulation were proposed. A total of 297 plasma samples from 124 Chinese patients were assayed chromatographically in a prospective, single-centre, open-label study, and pharmacokinetic parameters were analysed using NONMEN. Creatinine clearance (CLCr) was found to be the most significant covariate affecting drug clearance. The final PPK model was: CL (L/h)=9.89+(CLCr-66.56)×0.049; Vc (L)=13; Q (L/h)=8.74; and Vp (L)=4.09. Monte Carlo simulation indicated that for a target of ≥40% T>MIC (duration that the plasma level exceeds the causative pathogen's MIC), the biapenem pharmacokinetic/pharmacodynamic (PK/PD) breakpoint was 4μg/mL for doses of 0.3g every 6h (3-h infusion) and 1.2g (24-h continuous infusion). For a target of ≥80% T>MIC, the PK/PD breakpoint was 4μg/mL for a dose of 1.2g (24-h continuous infusion). The probability of target attainment (PTA) could not achieve ≥90% at the usual biapenem dosage regimen (0.3g every 12h, 0.5-h infusion) when the MIC of the pathogenic bacteria was 4μg/mL, which most likely resulted in unsatisfactory clinical outcomes in Chinese patients with LRTIs. Higher doses and longer infusion time would be appropriate for empirical therapy. When the patient's symptoms indicated a strong suspicion of Pseudomonas aeruginosa or Acinetobacter baumannii infection, it may be more appropriate for combination therapy with other antibacterial agents. PMID:26895604

  12. Dosimetric evaluation of nuclear interaction models in the Geant4 Monte Carlo simulation toolkit for carbon-ion radiotherapy.

    PubMed

    Kameoka, S; Amako, K; Iwai, G; Murakami, K; Sasaki, T; Toshito, T; Yamashita, T; Aso, T; Kimura, A; Kanai, T; Kanematsu, N; Komori, M; Takei, Y; Yonai, S; Tashiro, M; Koikegami, H; Tomita, H; Koi, T

    2008-07-01

    We tested the ability of two separate nuclear reaction models, the binary cascade and JQMD (Jaeri version of Quantum Molecular Dynamics), to predict the dose distribution in carbon-ion radiotherapy. This was done by use of a realistic simulation of the experimental irradiation of a water target. Comparison with measurement shows that the binary cascade model does a good job reproducing the spread-out Bragg peak in depth-dose distributions in water irradiated with a 290 MeV/u (per nucleon) beam. However, it significantly overestimates the peak dose for a 400 MeV/u beam. JQMD underestimates the overall dose because of a tendency to break a nucleus into lower-Z fragments than does the binary cascade model. As far as shape of the dose distribution is concerned, JQMD shows fairly good agreement with measurement for both beam energies of 290 and 400 MeV/u, which favors JQMD over the binary cascade model for the calculation of the relative dose distribution in treatment planning. PMID:20821145

  13. Neutron stimulated emission computed tomography: a Monte Carlo simulation approach.

    PubMed

    Sharma, A C; Harrawood, B P; Bender, J E; Tourassi, G D; Kapadia, A J

    2007-10-21

    A Monte Carlo simulation has been developed for neutron stimulated emission computed tomography (NSECT) using the GEANT4 toolkit. NSECT is a new approach to biomedical imaging that allows spectral analysis of the elements present within the sample. In NSECT, a beam of high-energy neutrons interrogates a sample and the nuclei in the sample are stimulated to an excited state by inelastic scattering of the neutrons. The characteristic gammas emitted by the excited nuclei are captured in a spectrometer to form multi-energy spectra. Currently, a tomographic image is formed using a collimated neutron beam to define the line integral paths for the tomographic projections. These projection data are reconstructed to form a representation of the distribution of individual elements in the sample. To facilitate the development of this technique, a Monte Carlo simulation model has been constructed from the GEANT4 toolkit. This simulation includes modeling of the neutron beam source and collimation, the samples, the neutron interactions within the samples, the emission of characteristic gammas, and the detection of these gammas in a Germanium crystal. In addition, the model allows the absorbed radiation dose to be calculated for internal components of the sample. NSECT presents challenges not typically addressed in Monte Carlo modeling of high-energy physics applications. In order to address issues critical to the clinical development of NSECT, this paper will describe the GEANT4 simulation environment and three separate simulations performed to accomplish three specific aims. First, comparison of a simulation to a tomographic experiment will verify the accuracy of both the gamma energy spectra produced and the positioning of the beam relative to the sample. Second, parametric analysis of simulations performed with different user-defined variables will determine the best way to effectively model low energy neutrons in tissue, which is a concern with the high hydrogen content in

  14. Monte Carlo beam capture and charge breeding simulation

    SciTech Connect

    Kim, J.S.; Liu, C.; Edgell, D.H.; Pardo, R.

    2006-03-15

    A full six-dimensional (6D) phase space Monte Carlo beam capture charge-breeding simulation code examines the beam capture processes of singly charged ion beams injected to an electron cyclotron resonance (ECR) charge breeder from entry to exit. The code traces injected beam ions in an ECR ion source (ECRIS) plasma including Coulomb collisions, ionization, and charge exchange. The background ECRIS plasma is modeled within the current frame work of the generalized ECR ion source model. A simple sample case of an oxygen background plasma with an injected Ar +1 ion beam produces lower charge breeding efficiencies than experimentally obtained. Possible reasons for discrepancies are discussed.

  15. Morphological evolution of growing crystals - A Monte Carlo simulation

    NASA Technical Reports Server (NTRS)

    Xiao, Rong-Fu; Alexander, J. Iwan D.; Rosenberger, Franz

    1988-01-01

    The combined effects of nutrient diffusion and surface kinetics on the crystal morphology were investigated using a Monte Carlo model to simulate the evolving morphology of a crystal growing from a two-component gaseous nutrient phase. The model combines nutrient diffusion, based on a modified diffusion-limited aggregation process, with anisotropic surface-attachment kinetics and surface diffusion. A variety of conditions, ranging from kinetic-controlled to diffusion-controlled growth, were examined. Successive transitions from compact faceted (dominant surface kinetics) to open dendritic morphologies (dominant volume diffusion) were obtained.

  16. Benchmarking of Proton Transport in Super Monte Carlo Simulation Program

    NASA Astrophysics Data System (ADS)

    Wang, Yongfeng; Li, Gui; Song, Jing; Zheng, Huaqing; Sun, Guangyao; Hao, Lijuan; Wu, Yican

    2014-06-01

    The Monte Carlo (MC) method has been traditionally applied in nuclear design and analysis due to its capability of dealing with complicated geometries and multi-dimensional physics problems as well as obtaining accurate results. The Super Monte Carlo Simulation Program (SuperMC) is developed by FDS Team in China for fusion, fission, and other nuclear applications. The simulations of radiation transport, isotope burn-up, material activation, radiation dose, and biology damage could be performed using SuperMC. Complicated geometries and the whole physical process of various types of particles in broad energy scale can be well handled. Bi-directional automatic conversion between general CAD models and full-formed input files of SuperMC is supported by MCAM, which is a CAD/image-based automatic modeling program for neutronics and radiation transport simulation. Mixed visualization of dynamical 3D dataset and geometry model is supported by RVIS, which is a nuclear radiation virtual simulation and assessment system. Continuous-energy cross section data from hybrid evaluated nuclear data library HENDL are utilized to support simulation. Neutronic fixed source and critical design parameters calculates for reactors of complex geometry and material distribution based on the transport of neutron and photon have been achieved in our former version of SuperMC. Recently, the proton transport has also been intergrated in SuperMC in the energy region up to 10 GeV. The physical processes considered for proton transport include electromagnetic processes and hadronic processes. The electromagnetic processes include ionization, multiple scattering, bremsstrahlung, and pair production processes. Public evaluated data from HENDL are used in some electromagnetic processes. In hadronic physics, the Bertini intra-nuclear cascade model with exitons, preequilibrium model, nucleus explosion model, fission model, and evaporation model are incorporated to treat the intermediate energy nuclear

  17. Accelerating population balance-Monte Carlo simulation for coagulation dynamics from the Markov jump model, stochastic algorithm and GPU parallel computing

    NASA Astrophysics Data System (ADS)

    Xu, Zuwei; Zhao, Haibo; Zheng, Chuguang

    2015-01-01

    This paper proposes a comprehensive framework for accelerating population balance-Monte Carlo (PBMC) simulation of particle coagulation dynamics. By combining Markov jump model, weighted majorant kernel and GPU (graphics processing unit) parallel computing, a significant gain in computational efficiency is achieved. The Markov jump model constructs a coagulation-rule matrix of differentially-weighted simulation particles, so as to capture the time evolution of particle size distribution with low statistical noise over the full size range and as far as possible to reduce the number of time loopings. Here three coagulation rules are highlighted and it is found that constructing appropriate coagulation rule provides a route to attain the compromise between accuracy and cost of PBMC methods. Further, in order to avoid double looping over all simulation particles when considering the two-particle events (typically, particle coagulation), the weighted majorant kernel is introduced to estimate the maximum coagulation rates being used for acceptance-rejection processes by single-looping over all particles, and meanwhile the mean time-step of coagulation event is estimated by summing the coagulation kernels of rejected and accepted particle pairs. The computational load of these fast differentially-weighted PBMC simulations (based on the Markov jump model) is reduced greatly to be proportional to the number of simulation particles in a zero-dimensional system (single cell). Finally, for a spatially inhomogeneous multi-dimensional (multi-cell) simulation, the proposed fast PBMC is performed in each cell, and multiple cells are parallel processed by multi-cores on a GPU that can implement the massively threaded data-parallel tasks to obtain remarkable speedup ratio (comparing with CPU computation, the speedup ratio of GPU parallel computing is as high as 200 in a case of 100 cells with 10 000 simulation particles per cell). These accelerating approaches of PBMC are

  18. Accelerating population balance-Monte Carlo simulation for coagulation dynamics from the Markov jump model, stochastic algorithm and GPU parallel computing

    SciTech Connect

    Xu, Zuwei; Zhao, Haibo Zheng, Chuguang

    2015-01-15

    This paper proposes a comprehensive framework for accelerating population balance-Monte Carlo (PBMC) simulation of particle coagulation dynamics. By combining Markov jump model, weighted majorant kernel and GPU (graphics processing unit) parallel computing, a significant gain in computational efficiency is achieved. The Markov jump model constructs a coagulation-rule matrix of differentially-weighted simulation particles, so as to capture the time evolution of particle size distribution with low statistical noise over the full size range and as far as possible to reduce the number of time loopings. Here three coagulation rules are highlighted and it is found that constructing appropriate coagulation rule provides a route to attain the compromise between accuracy and cost of PBMC methods. Further, in order to avoid double looping over all simulation particles when considering the two-particle events (typically, particle coagulation), the weighted majorant kernel is introduced to estimate the maximum coagulation rates being used for acceptance–rejection processes by single-looping over all particles, and meanwhile the mean time-step of coagulation event is estimated by summing the coagulation kernels of rejected and accepted particle pairs. The computational load of these fast differentially-weighted PBMC simulations (based on the Markov jump model) is reduced greatly to be proportional to the number of simulation particles in a zero-dimensional system (single cell). Finally, for a spatially inhomogeneous multi-dimensional (multi-cell) simulation, the proposed fast PBMC is performed in each cell, and multiple cells are parallel processed by multi-cores on a GPU that can implement the massively threaded data-parallel tasks to obtain remarkable speedup ratio (comparing with CPU computation, the speedup ratio of GPU parallel computing is as high as 200 in a case of 100 cells with 10 000 simulation particles per cell). These accelerating approaches of PBMC are

  19. Fast Monte Carlo-assisted simulation of cloudy Earth backgrounds

    NASA Astrophysics Data System (ADS)

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

    2012-11-01

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

  20. A Massively Parallel Hybrid Dusty-Gasdynamics and Kinetic Direct Simulation Monte Carlo Model for Planetary Applications

    NASA Technical Reports Server (NTRS)

    Combi, Michael R.

    2004-01-01

    In order to understand the global structure, dynamics, and physical and chemical processes occurring in the upper atmospheres, exospheres, and ionospheres of the Earth, the other planets, comets and planetary satellites and their interactions with their outer particles and fields environs, it is often necessary to address the fundamentally non-equilibrium aspects of the physical environment. These are regions where complex chemistry, energetics, and electromagnetic field influences are important. Traditional approaches are based largely on hydrodynamic or magnetohydrodynamic (MHD) formulations and are very important and highly useful. However, these methods often have limitations in rarefied physical regimes where the molecular collision rates and ion gyrofrequencies are small and where interactions with ionospheres and upper neutral atmospheres are important. At the University of Michigan we have an established base of experience and expertise in numerical simulations based on particle codes which address these physical regimes. The Principal Investigator, Dr. Michael Combi, has over 20 years of experience in the development of particle-kinetic and hybrid kinetichydrodynamics models and their direct use in data analysis. He has also worked in ground-based and space-based remote observational work and on spacecraft instrument teams. His research has involved studies of cometary atmospheres and ionospheres and their interaction with the solar wind, the neutral gas clouds escaping from Jupiter s moon Io, the interaction of the atmospheres/ionospheres of Io and Europa with Jupiter s corotating magnetosphere, as well as Earth s ionosphere. This report describes our progress during the year. The contained in section 2 of this report will serve as the basis of a paper describing the method and its application to the cometary coma that will be continued under a research and analysis grant that supports various applications of theoretical comet models to understanding the

  1. SU-E-J-82: Intra-Fraction Proton Beam-Range Verification with PET Imaging: Feasibility Studies with Monte Carlo Simulations and Statistical Modeling

    SciTech Connect

    Lou, K; Mirkovic, D; Sun, X; Zhu, X; Poenisch, F; Grosshans, D; Shao, Y; Clark, J

    2014-06-01

    Purpose: To study the feasibility of intra-fraction proton beam-range verification with PET imaging. Methods: Two phantoms homogeneous cylindrical PMMA phantoms (290 mm axial length, 38 mm and 200 mm diameter respectively) were studied using PET imaging: a small phantom using a mouse-sized PET (61 mm diameter field of view (FOV)) and a larger phantom using a human brain-sized PET (300 mm FOV). Monte Carlo (MC) simulations (MCNPX and GATE) were used to simulate 179.2 MeV proton pencil beams irradiating the two phantoms and be imaged by the two PET systems. A total of 50 simulations were conducted to generate 50 positron activity distributions and correspondingly 50 measured activity-ranges. The accuracy and precision of these activity-ranges were calculated under different conditions (including count statistics and other factors, such as crystal cross-section). Separate from the MC simulations, an activity distribution measured from a simulated PET image was modeled as a noiseless positron activity distribution corrupted by Poisson counting noise. The results from these two approaches were compared to assess the impact of count statistics on the accuracy and precision of activity-range calculations. Results: MC Simulations show that the accuracy and precision of an activity-range are dominated by the number (N) of coincidence events of the reconstructed image. They are improved in a manner that is inversely proportional to 1/sqrt(N), which can be understood from the statistical modeling. MC simulations also indicate that the coincidence events acquired within the first 60 seconds with 10{sup 9} protons (small phantom) and 10{sup 10} protons (large phantom) are sufficient to achieve both sub-millimeter accuracy and precision. Conclusion: Under the current MC simulation conditions, the initial study indicates that the accuracy and precision of beam-range verification are dominated by count statistics, and intra-fraction PET image-based beam-range verification is

  2. Where does methanol lose hydrogen to trigger steam reforming? A revisit of methanol dehydrogenation on the PdZn alloy model obtained from kinetic Monte Carlo simulations.

    PubMed

    Cheng, Feng; Chen, Zhao-Xu

    2016-02-01

    Pd/ZnO is a promising catalyst studied for methanol steam reforming (MSR) and the 1 : 1 PdZn alloy is demonstrated to be the active component. It is believed that MSR starts from methanol dehydrogenation to methoxy. Previous studies of methanol dehydrogenation on the ideal PdZn(111) surface show that methanol adsorbs weakly on the PdZn(111) surface and it is hard for methanol to transform into methoxy because of the high dehydrogenation barrier, indicating that the catalyst model is not appropriate for investigating the first step of MSR. Using the model derived from our recent kinetic Monte Carlo simulations, we examined the process CH3OH → CH3O → CH2O → CHO → CO. Compared with the ideal model, methanol adsorbs much more strongly and the barrier from CH3OH → CH3O is much lower on the kMC model. On the other hand, the C-H bond breaking of CH3O, CH2O and CHO becomes harder. We show that co-adsorbed water is important for refreshing the active sites. The present study shows that the first MSR step most likely takes place on three-fold hollow sites formed by Zn atoms, and the inhomogeneity of the PdZn alloy may exert significant influences on reactions. PMID:26771029

  3. General regression neural network and Monte Carlo simulation model for survival and growth of Salmonella on raw chicken skin as a function of serotype, temperature and time for use in risk assessment

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A general regression neural network and Monte Carlo simulation model for predicting survival and growth of Salmonella on raw chicken skin as a function of serotype (Typhimurium, Kentucky, Hadar), temperature (5 to 50C) and time (0 to 8 h) was developed. Poultry isolates of Salmonella with natural r...

  4. Monte Carlo modeling and meteor showers

    NASA Astrophysics Data System (ADS)

    Kulikova, N. V.

    1987-08-01

    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.

  5. 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.

  6. Numerical simulations of acoustics problems using the direct simulation Monte Carlo method

    NASA Astrophysics Data System (ADS)

    Hanford, Amanda Danforth

    In the current study, real gas effects in the propagation of sound waves are simulated using the direct simulation Monte Carlo method for a wide range of systems. This particle method allows for treatment of acoustic phenomena for a wide range of Knudsen numbers, defined as the ratio of molecular mean free path to wavelength. Continuum models such as the Euler and Navier-Stokes equations break down for flows greater than a Knudsen number of approximately 0.05. Continuum models also suffer from the inability to simultaneously model nonequilibrium conditions, diatomic or polyatomic molecules, nonlinearity and relaxation effects and are limited in their range of validity. Therefore, direct simulation Monte Carlo is capable of directly simulating acoustic waves with a level of detail not possible with continuum approaches. The basis of direct simulation Monte Carlo lies within kinetic theory where representative particles are followed as they move and collide with other particles. A parallel, object-oriented DSMC solver was developed for this problem. Despite excellent parallel efficiency, computation time is considerable. Monatomic gases, gases with internal energy, planetary environments, and amplitude effects spanning a large range of Knudsen number have all been modeled with the same method and compared to existing theory. With the direct simulation method, significant deviations from continuum predictions are observed for high Knudsen number flows.

  7. Calculation of the Gibbs Free Energy of Solvation and Dissociation of HCl in Water via Monte Carlo Simulations and Continuum Solvation Models

    SciTech Connect

    McGrath, Matthew; Kuo, I-F W.; Ngouana, Brice F.; Ghogomu, Julius N.; Mundy, Christopher J.; Marenich, Aleksandr; Cramer, Christopher J.; Truhlar, Donald G.; Siepmann, Joern I.

    2013-08-28

    The free energy of solvation and dissociation of hydrogen chloride in water is calculated through a combined molecular simulation quantum chemical approach at four temperatures between T = 300 and 450 K. The free energy is first decomposed into the sum of two components: the Gibbs free energy of transfer of molecular HCl from the vapor to the aqueous liquid phase and the standard-state free energy of acid dissociation of HCl in aqueous solution. The former quantity is calculated using Gibbs ensemble Monte Carlo simulations using either Kohn-Sham density functional theory or a molecular mechanics force field to determine the system’s potential energy. The latter free energy contribution is computed using a continuum solvation model utilizing either experimental reference data or micro-solvated clusters. The predicted combined solvation and dissociation free energies agree very well with available experimental data. CJM was supported by the US Department of Energy,Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences & Biosciences. Pacific Northwest National Laboratory is operated by Battelle for the US Department of Energy.

  8. An interface for simulating radiative transfer in and around volcanic plumes with the Monte Carlo radiative transfer model McArtim

    USGS Publications Warehouse

    Kern, Christoph

    2016-01-01

    This report describes two software tools that, when used as front ends for the three-dimensional backward Monte Carlo atmospheric-radiative-transfer model (RTM) McArtim, facilitate the generation of lookup tables of volcanic-plume optical-transmittance characteristics in the ultraviolet/visible-spectral region. In particular, the differential optical depth and derivatives thereof (that is, weighting functions), with regard to a change in SO2 column density or aerosol optical thickness, can be simulated for a specific measurement geometry and a representative range of plume conditions. These tables are required for the retrieval of SO2 column density in volcanic plumes, using the simulated radiative-transfer/differential optical-absorption spectroscopic (SRT-DOAS) approach outlined by Kern and others (2012). This report, together with the software tools published online, is intended to make this sophisticated SRT-DOAS technique available to volcanologists and gas geochemists in an operational environment, without the need for an indepth treatment of the underlying principles or the low-level interface of the RTM McArtim.

  9. Dynamic 99mTc-MAG3 renography: images for quality control obtained by combining pharmacokinetic modelling, an anthropomorphic computer phantom and Monte Carlo simulated scintillation camera imaging

    NASA Astrophysics Data System (ADS)

    Brolin, Gustav; Sjögreen Gleisner, Katarina; Ljungberg, Michael

    2013-05-01

    In dynamic renal scintigraphy, the main interest is the radiopharmaceutical redistribution as a function of time. Quality control (QC) of renal procedures often relies on phantom experiments to compare image-based results with the measurement setup. A phantom with a realistic anatomy and time-varying activity distribution is therefore desirable. This work describes a pharmacokinetic (PK) compartment model for 99mTc-MAG3, used for defining a dynamic whole-body activity distribution within a digital phantom (XCAT) for accurate Monte Carlo (MC)-based images for QC. Each phantom structure is assigned a time-activity curve provided by the PK model, employing parameter values consistent with MAG3 pharmacokinetics. This approach ensures that the total amount of tracer in the phantom is preserved between time points, and it allows for modifications of the pharmacokinetics in a controlled fashion. By adjusting parameter values in the PK model, different clinically realistic scenarios can be mimicked, regarding, e.g., the relative renal uptake and renal transit time. Using the MC code SIMIND, a complete set of renography images including effects of photon attenuation, scattering, limited spatial resolution and noise, are simulated. The obtained image data can be used to evaluate quantitative techniques and computer software in clinical renography.

  10. Monte Carlo Simulation of Massive Absorbers for Cryogenic Calorimeters

    SciTech Connect

    Brandt, D.; Asai, M.; Brink, P.L.; Cabrera, B.; Silva, E.do Couto e; Kelsey, M.; Leman, S.W.; McArthy, K.; Resch, R.; Wright, D.; Figueroa-Feliciano, E.; /MIT

    2012-06-12

    There is a growing interest in cryogenic calorimeters with macroscopic absorbers for applications such as dark matter direct detection and rare event search experiments. The physics of energy transport in calorimeters with absorber masses exceeding several grams is made complex by the anisotropic nature of the absorber crystals as well as the changing mean free paths as phonons decay to progressively lower energies. We present a Monte Carlo model capable of simulating anisotropic phonon transport in cryogenic crystals. We have initiated the validation process and discuss the level of agreement between our simulation and experimental results reported in the literature, focusing on heat pulse propagation in germanium. The simulation framework is implemented using Geant4, a toolkit originally developed for high-energy physics Monte Carlo simulations. Geant4 has also been used for nuclear and accelerator physics, and applications in medical and space sciences. We believe that our current work may open up new avenues for applications in material science and condensed matter physics.