Sample records for object kinetic monte

  1. OBJECT KINETIC MONTE CARLO SIMULATIONS OF MICROSTRUCTURE EVOLUTION

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

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

    2013-09-30

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

  2. OBJECT KINETIC MONTE CARLO SIMULATIONS OF CASCADE ANNEALING IN TUNGSTEN

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

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

    2014-03-31

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

  3. OBJECT KINETIC MONTE CARLO SIMULATIONS OF RADIATION DAMAGE ACCUMULATION IN TUNGSTEN

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

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

    2016-09-01

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

  4. OBJECT KINETIC MONTE CARLO SIMULATIONS OF RADIATION DAMAGE IN TUNGSTEN

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

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

    2015-04-16

    We used our recently developed lattice-based object kinetic Monte Carlo code; KSOME [1] to carryout simulations of radiation damage in bulk tungsten at temperatures of 300, and 2050 K for various dose rates. Displacement cascades generated from molecular dynamics (MD) simulations for PKA energies at 60, 75 and 100 keV provided residual point defect distributions. It was found that the number density of vacancies in the simulation box does not change with dose rate while the number density of vacancy clusters slightly decreases with dose rate indicating that bigger clusters are formed at larger dose rates. At 300 K, althoughmore » the average vacancy cluster size increases slightly, the vast majority of vacancies exist as mono-vacancies. At 2050 K no accumulation of defects was observed during irradiation over a wide range of dose rates for all PKA energies studied in this work.« less

  5. OBJECT KINETIC MONTE CARLO SIMULATIONS OF RADIATION DAMAGE IN TUNGSTEN SUBJECTED TO NEUTRON FLUX WITH PKA SPECTRUM CORRESPONDING TO THE HFIR

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

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

    2015-12-31

    The objective of this work is to study the damage accumulation in pure tungsten (W) subjected to neutron bombardment with a primary knock-on atom (PKA) spectrum corresponding to the High Flux Isotope Reactor (HFIR), using the object kinetic Monte Carlo (OKMC) method.

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

    DOE PAGES

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

    2015-01-29

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

  7. Displacement cascades and defect annealing in tungsten, Part II: Object kinetic Monte Carlo Simulation of Tungsten Cascade Aging

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

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

    2015-07-01

    The results of object kinetic Monte Carlo (OKMC) simulations of the annealing of primary cascade damage in bulk tungsten using a comprehensive database of cascades obtained from molecular dynamics (Setyawan et al.) are described as a function of primary knock-on atom (PKA) energy at temperatures of 300, 1025 and 2050 K. An increase in SIA clustering coupled with a decrease in vacancy clustering with increasing temperature, in addition to the disparate mobilities of SIAs versus vacancies, causes an interesting effect of temperature on cascade annealing. The annealing efficiency (the ratio of the number of defects after and before annealing) exhibitsmore » an inverse U-shape curve as a function of temperature. The capabilities of the newly developed OKMC code KSOME (kinetic simulations of microstructure evolution) used to carry out these simulations are described.« less

  8. RNA folding kinetics using Monte Carlo and Gillespie algorithms.

    PubMed

    Clote, Peter; Bayegan, Amir H

    2018-04-01

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

  9. Kinetic Activation-Relaxation Technique and Self-Evolving Atomistic Kinetic Monte Carlo: Comparison of on-the-fly kinetic Monte Carlo algorithms

    DOE PAGES

    Beland, Laurent Karim; Osetskiy, Yury N.; Stoller, Roger E.; ...

    2015-02-07

    Here, we present a comparison of the Kinetic Activation–Relaxation Technique (k-ART) and the Self-Evolving Atomistic Kinetic Monte Carlo (SEAKMC), two off-lattice, on-the-fly Kinetic Monte Carlo (KMC) techniques that were recently used to solve several materials science problems. We show that if the initial displacements are localized the dimer method and the Activation–Relaxation Technique nouveau provide similar performance. We also show that k-ART and SEAKMC, although based on different approximations, are in agreement with each other, as demonstrated by the examples of 50 vacancies in a 1950-atom Fe box and of interstitial loops in 16,000-atom boxes. Generally speaking, k-ART’s treatment ofmore » geometry and flickers is more flexible, e.g. it can handle amorphous systems, and rigorous than SEAKMC’s, while the later’s concept of active volumes permits a significant speedup of simulations for the systems under consideration and therefore allows investigations of processes requiring large systems that are not accessible if not localizing calculations.« less

  10. On the onset of void swelling in pure tungsten under neutron irradiation: An object kinetic Monte Carlo approach

    NASA Astrophysics Data System (ADS)

    Castin, N.; Bakaev, A.; Bonny, G.; Sand, A. E.; Malerba, L.; Terentyev, D.

    2017-09-01

    We propose an object kinetic Monte Carlo (OKMC) model for describing the microstructural evolution in pure tungsten under neutron irradiation. We here focus on low doses (under 1 dpa), and we neglect transmutation in first approximation. The emphasis is mainly centred on an adequate description of neutron irradiation, the subsequent introduction of primary defects, and their thermal diffusion properties. Besides grain boundaries and the dislocation network, our model includes the contribution of carbon impurities, which are shown to have a strong influence on the onset of void swelling. Our parametric study analyses the quality of our model in detail, and confronts its predictions with experimental microstructural observations with satisfactory agreement. We highlight the importance for an accurate determination of the dissolved carbon content in the tungsten matrix, and we advocate for an accurate description of atomic collision cascades, in light of the sensitivity of our results with respect to correlated recombination.

  11. Object kinetic Monte Carlo model for neutron and ion irradiation in tungsten: Impact of transmutation and carbon impurities

    NASA Astrophysics Data System (ADS)

    Castin, N.; Bonny, G.; Bakaev, A.; Ortiz, C. J.; Sand, A. E.; Terentyev, D.

    2018-03-01

    We upgrade our object kinetic Monte Carlo (OKMC) model, aimed at describing the microstructural evolution in tungsten (W) under neutron and ion irradiation. Two main improvements are proposed based on recently published atomistic data: (a) interstitial carbon impurities, and their interaction with radiation-induced defects (point defect clusters and loops), are more accurately parameterized thanks to ab initio findings; (b) W transmutation to rhenium (Re) upon neutron irradiation, impacting the diffusivity of radiation defects, is included, also relying on recent atomistic data. These essential amendments highly improve the portability of our OKMC model, providing a description for the formation of SIA-type loops under different irradiation conditions. The model is applied to simulate neutron and ion irradiation in pure W samples, in a wide range of fluxes and temperatures. We demonstrate that it performs a realistic prediction of the population of TEM-visible voids and loops, as compared to experimental evidence. The impact of the transmutation of W to Re, and of carbon trapping, is assessed.

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

    DOE PAGES

    Hoffmann, Max J.; Bligaard, Thomas

    2018-01-22

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

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

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

    Hoffmann, Max J.; Bligaard, Thomas

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

  14. Simulation of Nuclear Reactor Kinetics by the Monte Carlo Method

    NASA Astrophysics Data System (ADS)

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

    2017-12-01

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

  15. IMPLEMENTATION OF FIRST-PASSAGE TIME APPROACH FOR OBJECT KINETIC MONTE CARLO SIMULATIONS OF IRRADIATION

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

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

    2014-06-30

    The objective of the work is to implement a first-passage time (FPT) approach to deal with very fast 1D diffusing SIA clusters in KSOME (kinetic simulations of microstructural evolution) [1] to achieve longer time-scales during irradiation damage simulations. The goal is to develop FPT-KSOME, which has the same flexibility as KSOME.

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

    PubMed

    Serebrinsky, Santiago A

    2011-03-01

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

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

    NASA Astrophysics Data System (ADS)

    Mousseau, Nomand

    2012-02-01

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

  18. Kinetic Monte Carlo simulation of intermixing during semiconductor heteroepitaxy

    NASA Astrophysics Data System (ADS)

    Rouhani, M. Djafari; Kassem, H.; Dalla Torre, J.; Landa, G.; Estève, D.

    2002-03-01

    We have used the kinetic Monte Carlo technique to investigate the intermixing mechanisms during the heteroepitaxial growth of semiconductors. We have shown that the temperature increases the intermixing between the substrate and deposited film, while an increasing growth rate inhibits this intermixing. We have also observed that intermixing is reduced when the energetics becomes unfavorable, i.e. with high lattice mismatches or hard-deposited materials.

  19. Hierarchical fractional-step approximations and parallel kinetic Monte Carlo algorithms

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

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

    2012-10-01

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

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

    PubMed

    Lecca, Paola

    2018-01-01

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

  1. Kinetic Monte Carlo simulations of nucleation and growth in electrodeposition.

    PubMed

    Guo, Lian; Radisic, Aleksandar; Searson, Peter C

    2005-12-22

    Nucleation and growth during bulk electrodeposition is studied using kinetic Monte Carlo (KMC) simulations. Ion transport in solution is modeled using Brownian dynamics, and the kinetics of nucleation and growth are dependent on the probabilities of metal-on-substrate and metal-on-metal deposition. Using this approach, we make no assumptions about the nucleation rate, island density, or island distribution. The influence of the attachment probabilities and concentration on the time-dependent island density and current transients is reported. Various models have been assessed by recovering the nucleation rate and island density from the current-time transients.

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

    NASA Astrophysics Data System (ADS)

    Yasuda, Shugo

    2017-02-01

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

  3. First-Order or Second-Order Kinetics? A Monte Carlo Answer

    ERIC Educational Resources Information Center

    Tellinghuisen, Joel

    2005-01-01

    Monte Carlo computational experiments reveal that the ability to discriminate between first- and second-order kinetics from least-squares analysis of time-dependent concentration data is better than implied in earlier discussions of the problem. The problem is rendered as simple as possible by assuming that the order must be either 1 or 2 and that…

  4. Monte Carlo Simulations of the Kinetics of Protein Adsorption

    NASA Astrophysics Data System (ADS)

    Zhdanov, V. P.; Kasemo, B.

    The past decade has been characterized by rapid progress in Monte Carlo simulations of protein folding in a solution. This review summarizes the main results obtained in the field, as a background to the major topic, namely corresponding advances in simulations of protein adsorption kinetics at solid-liquid interfaces. The latter occur via diffusion in the liquid towards the interface followed by actual adsorption, and subsequent irreversible conformational changes, resulting in more or less pronounced denaturation of the native protein structure. The conventional kinetic models describing these steps are based on the assumption that the denaturation transitions obey the first-order law with a single value of the denaturation rate constant kr. The validity of this assumption has been studied in recent lattice Monte Carlo simulations of denaturation of model protein-like molecules with different types of the monomer-monomer interactions. The results obtained indicate that, due to trapping in metastable states, (i) the transition of a molecule to the denatured state is usually nonexponential in time, i.e. it does not obey the first-order law, and (ii) the denaturation transitions of an ensemble of different molecules are characterized by different time scales, i.e. the denaturation process cannot be described by a single rate constant kr. One should, rather, introduce a distribution of values of this rate constant (physically, different values of kr reflect the fact that the transitions to the altered state occurs via different metastable states). The phenomenological kinetics of irreversible adsorption of proteins with and without a distribution of the denaturation rate constant values have been calculated in the limits where protein diffusion in the solution is, respectively, rapid or slow. In both cases, the adsorption kinetics with a distribution of kr are found to be close to those with a single-valued rate constant kr, provided that the average value of kr in

  5. A novel Kinetic Monte Carlo algorithm for Non-Equilibrium Simulations

    NASA Astrophysics Data System (ADS)

    Jha, Prateek; Kuzovkov, Vladimir; Grzybowski, Bartosz; Olvera de La Cruz, Monica

    2012-02-01

    We have developed an off-lattice kinetic Monte Carlo simulation scheme for reaction-diffusion problems in soft matter systems. The definition of transition probabilities in the Monte Carlo scheme are taken identical to the transition rates in a renormalized master equation of the diffusion process and match that of the Glauber dynamics of Ising model. Our scheme provides several advantages over the Brownian dynamics technique for non-equilibrium simulations. Since particle displacements are accepted/rejected in a Monte Carlo fashion as opposed to moving particles following a stochastic equation of motion, nonphysical movements (e.g., violation of a hard core assumption) are not possible (these moves have zero acceptance). Further, the absence of a stochastic ``noise'' term resolves the computational difficulties associated with generating statistically independent trajectories with definitive mean properties. Finally, since the timestep is independent of the magnitude of the interaction forces, much longer time-steps can be employed than Brownian dynamics. We discuss the applications of this scheme for dynamic self-assembly of photo-switchable nanoparticles and dynamical problems in polymeric systems.

  6. Kinetic Monte Carlo Simulation of Cation Diffusion in Low-K Ceramics

    NASA Technical Reports Server (NTRS)

    Good, Brian

    2013-01-01

    Low thermal conductivity (low-K) ceramic materials are of interest to the aerospace community for use as the thermal barrier component of coating systems for turbine engine components. In particular, zirconia-based materials exhibit both low thermal conductivity and structural stability at high temperature, making them suitable for such applications. Because creep is one of the potential failure modes, and because diffusion is a mechanism by which creep takes place, we have performed computer simulations of cation diffusion in a variety of zirconia-based low-K materials. The kinetic Monte Carlo simulation method is an alternative to the more widely known molecular dynamics (MD) method. It is designed to study "infrequent-event" processes, such as diffusion, for which MD simulation can be highly inefficient. We describe the results of kinetic Monte Carlo computer simulations of cation diffusion in several zirconia-based materials, specifically, zirconia doped with Y, Gd, Nb and Yb. Diffusion paths are identified, and migration energy barriers are obtained from density functional calculations and from the literature. We present results on the temperature dependence of the diffusivity, and on the effects of the presence of oxygen vacancies in cation diffusion barrier complexes as well.

  7. A kinetic Monte Carlo approach to diffusion-controlled thermal desorption spectroscopy

    NASA Astrophysics Data System (ADS)

    Schablitzki, T.; Rogal, J.; Drautz, R.

    2017-06-01

    Atomistic simulations of thermal desorption spectra for effusion from bulk materials to characterize binding or trapping sites are a challenging task as large system sizes as well as extended time scales are required. Here, we introduce an approach where we combine kinetic Monte Carlo with an analytic approximation of the superbasins within the framework of absorbing Markov chains. We apply our approach to the effusion of hydrogen from BCC iron, where the diffusion within bulk grains is coarse grained using absorbing Markov chains, which provide an exact solution of the dynamics within a superbasin. Our analytic approximation to the superbasin is transferable with respect to grain size and elliptical shapes and can be applied in simulations with constant temperature as well as constant heating rate. The resulting thermal desorption spectra are in close agreement with direct kinetic Monte Carlo simulations, but the calculations are computationally much more efficient. Our approach is thus applicable to much larger system sizes and provides a first step towards an atomistic understanding of the influence of structural features on the position and shape of peaks in thermal desorption spectra. This article is part of the themed issue 'The challenges of hydrogen and metals'.

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

    PubMed

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

    2016-07-14

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

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

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

    Mitchell, Izaac; Page, Alister J., E-mail: sirle@chem.nagoya-u.ac.jp, E-mail: alister.page@newcastle.edu.au; Irle, Stephan, E-mail: sirle@chem.nagoya-u.ac.jp, E-mail: alister.page@newcastle.edu.au

    2016-07-14

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-07-01

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

  11. Kinetic Monte Carlo simulations of scintillation processes in NaI(Tl)

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

    Kerisit, Sebastien N.; Wang, Zhiguo; Williams, Richard

    2014-04-26

    Developing a comprehensive understanding of the processes that govern the scintillation behavior of inorganic scintillators provides a pathway to optimize current scintillators and allows for the science-driven search for new scintillator materials. Recent experimental data on the excitation density dependence of the light yield of inorganic scintillators presents an opportunity to incorporate parameterized interactions between excitations in scintillation models and thus enable more realistic simulations of the nonproportionality of inorganic scintillators. Therefore, a kinetic Monte Carlo (KMC) model of elementary scintillation processes in NaI(Tl) is developed in this work to simulate the kinetics of scintillation for a range of temperaturesmore » and Tl concentrations as well as the scintillation efficiency as a function of excitation density. The ability of the KMC model to reproduce available experimental data allows for elucidating the elementary processes that give rise to the kinetics and efficiency of scintillation observed experimentally for a range of conditions.« less

  12. Kinetic Monte Carlo Simulations of Scintillation Processes in NaI(Tl)

    NASA Astrophysics Data System (ADS)

    Kerisit, Sebastien; Wang, Zhiguo; Williams, Richard T.; Grim, Joel Q.; Gao, Fei

    2014-04-01

    Developing a comprehensive understanding of the processes that govern the scintillation behavior of inorganic scintillators provides a pathway to optimize current scintillators and allows for the science-driven search for new scintillator materials. Recent experimental data on the excitation density dependence of the light yield of inorganic scintillators presents an opportunity to incorporate parameterized interactions between excitations in scintillation models and thus enable more realistic simulations of the nonproportionality of inorganic scintillators. Therefore, a kinetic Monte Carlo (KMC) model of elementary scintillation processes in NaI(Tl) is developed in this paper to simulate the kinetics of scintillation for a range of temperatures and Tl concentrations as well as the scintillation efficiency as a function of excitation density. The ability of the KMC model to reproduce available experimental data allows for elucidating the elementary processes that give rise to the kinetics and efficiency of scintillation observed experimentally for a range of conditions.

  13. Kinetic Monte Carlo Method for Rule-based Modeling of Biochemical Networks

    PubMed Central

    Yang, Jin; Monine, Michael I.; Faeder, James R.; Hlavacek, William S.

    2009-01-01

    We present a kinetic Monte Carlo method for simulating chemical transformations specified by reaction rules, which can be viewed as generators of chemical reactions, or equivalently, definitions of reaction classes. A rule identifies the molecular components involved in a transformation, how these components change, conditions that affect whether a transformation occurs, and a rate law. The computational cost of the method, unlike conventional simulation approaches, is independent of the number of possible reactions, which need not be specified in advance or explicitly generated in a simulation. To demonstrate the method, we apply it to study the kinetics of multivalent ligand-receptor interactions. We expect the method will be useful for studying cellular signaling systems and other physical systems involving aggregation phenomena. PMID:18851068

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

    PubMed

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

    2011-11-07

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

  15. A Large-Particle Monte Carlo Code for Simulating Non-Linear High-Energy Processes Near Compact Objects

    NASA Technical Reports Server (NTRS)

    Stern, Boris E.; Svensson, Roland; Begelman, Mitchell C.; Sikora, Marek

    1995-01-01

    High-energy radiation processes in compact cosmic objects are often expected to have a strongly non-linear behavior. Such behavior is shown, for example, by electron-positron pair cascades and the time evolution of relativistic proton distributions in dense radiation fields. Three independent techniques have been developed to simulate these non-linear problems: the kinetic equation approach; the phase-space density (PSD) Monte Carlo method; and the large-particle (LP) Monte Carlo method. In this paper, we present the latest version of the LP method and compare it with the other methods. The efficiency of the method in treating geometrically complex problems is illustrated by showing results of simulations of 1D, 2D and 3D systems. The method is shown to be powerful enough to treat non-spherical geometries, including such effects as bulk motion of the background plasma, reflection of radiation from cold matter, and anisotropic distributions of radiating particles. It can therefore be applied to simulate high-energy processes in such astrophysical systems as accretion discs with coronae, relativistic jets, pulsar magnetospheres and gamma-ray bursts.

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

    NASA Astrophysics Data System (ADS)

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

    2011-10-01

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

  17. Monte carlo simulations of enzyme reactions in two dimensions: fractal kinetics and spatial segregation.

    PubMed

    Berry, Hugues

    2002-10-01

    Conventional equations for enzyme kinetics are based on mass-action laws, that may fail in low-dimensional and disordered media such as biological membranes. We present Monte Carlo simulations of an isolated Michaelis-Menten enzyme reaction on two-dimensional lattices with varying obstacle densities, as models of biological membranes. The model predicts that, as a result of anomalous diffusion on these low-dimensional media, the kinetics are of the fractal type. Consequently, the conventional equations for enzyme kinetics fail to describe the reaction. In particular, we show that the quasi-stationary-state assumption can hardly be retained in these conditions. Moreover, the fractal characteristics of the kinetics are increasingly pronounced as obstacle density and initial substrate concentration increase. The simulations indicate that these two influences are mainly additive. Finally, the simulations show pronounced S-P segregation over the lattice at obstacle densities compatible with in vivo conditions. This phenomenon could be a source of spatial self organization in biological membranes.

  18. Monte carlo simulations of enzyme reactions in two dimensions: fractal kinetics and spatial segregation.

    PubMed Central

    Berry, Hugues

    2002-01-01

    Conventional equations for enzyme kinetics are based on mass-action laws, that may fail in low-dimensional and disordered media such as biological membranes. We present Monte Carlo simulations of an isolated Michaelis-Menten enzyme reaction on two-dimensional lattices with varying obstacle densities, as models of biological membranes. The model predicts that, as a result of anomalous diffusion on these low-dimensional media, the kinetics are of the fractal type. Consequently, the conventional equations for enzyme kinetics fail to describe the reaction. In particular, we show that the quasi-stationary-state assumption can hardly be retained in these conditions. Moreover, the fractal characteristics of the kinetics are increasingly pronounced as obstacle density and initial substrate concentration increase. The simulations indicate that these two influences are mainly additive. Finally, the simulations show pronounced S-P segregation over the lattice at obstacle densities compatible with in vivo conditions. This phenomenon could be a source of spatial self organization in biological membranes. PMID:12324410

  19. Towards the reliable calculation of residence time for off-lattice kinetic Monte Carlo simulations

    NASA Astrophysics Data System (ADS)

    Alexander, Kathleen C.; Schuh, Christopher A.

    2016-08-01

    Kinetic Monte Carlo (KMC) methods have the potential to extend the accessible timescales of off-lattice atomistic simulations beyond the limits of molecular dynamics by making use of transition state theory and parallelization. However, it is a challenge to identify a complete catalog of events accessible to an off-lattice system in order to accurately calculate the residence time for KMC. Here we describe possible approaches to some of the key steps needed to address this problem. These include methods to compare and distinguish individual kinetic events, to deterministically search an energy landscape, and to define local atomic environments. When applied to the ground state  ∑5(2 1 0) grain boundary in copper, these methods achieve a converged residence time, accounting for the full set of kinetically relevant events for this off-lattice system, with calculable uncertainty.

  20. Goal-oriented sensitivity analysis for lattice kinetic Monte Carlo simulations

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

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

    2014-03-28

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

  1. Studies of concentration and temperature dependences of precipitation kinetics in iron-copper alloys using kinetic Monte Carlo and stochastic statistical simulations

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

    Khromov, K. Yu.; Vaks, V. G., E-mail: vaks@mbslab.kiae.ru; Zhuravlev, I. A.

    2013-02-15

    The previously developed ab initio model and the kinetic Monte Carlo method (KMCM) are used to simulate precipitation in a number of iron-copper alloys with different copper concentrations x and temperatures T. The same simulations are also made using an improved version of the previously suggested stochastic statistical method (SSM). The results obtained enable us to make a number of general conclusions about the dependences of the decomposition kinetics in Fe-Cu alloys on x and T. We also show that the SSM usually describes the precipitation kinetics in good agreement with the KMCM, and using the SSM in conjunction withmore » the KMCM allows extending the KMC simulations to the longer evolution times. The results of simulations seem to agree with available experimental data for Fe-Cu alloys within statistical errors of simulations and the scatter of experimental results. Comparison of simulation results with experiments for some multicomponent Fe-Cu-based alloys allows making certain conclusions about the influence of alloying elements in these alloys on the precipitation kinetics at different stages of evolution.« less

  2. Dendritic growth shapes in kinetic Monte Carlo models

    NASA Astrophysics Data System (ADS)

    Krumwiede, Tim R.; Schulze, Tim P.

    2017-02-01

    For the most part, the study of dendritic crystal growth has focused on continuum models featuring surface energies that yield six pointed dendrites. In such models, the growth shape is a function of the surface energy anisotropy, and recent work has shown that considering a broader class of anisotropies yields a correspondingly richer set of growth morphologies. Motivated by this work, we generalize nanoscale models of dendritic growth based on kinetic Monte Carlo simulation. In particular, we examine the effects of extending the truncation radius for atomic interactions in a bond-counting model. This is done by calculating the model’s corresponding surface energy and equilibrium shape, as well as by running KMC simulations to obtain nanodendritic growth shapes. Additionally, we compare the effects of extending the interaction radius in bond-counting models to that of extending the number of terms retained in the cubic harmonic expansion of surface energy anisotropy in the context of continuum models.

  3. Study of photo-oxidative reactivity of sunscreening agents based on photo-oxidation of uric acid by kinetic Monte Carlo simulation.

    PubMed

    Moradmand Jalali, Hamed; Bashiri, Hadis; Rasa, Hossein

    2015-05-01

    In the present study, the mechanism of free radical production by light-reflective agents in sunscreens (TiO2, ZnO and ZrO2) was obtained by applying kinetic Monte Carlo simulation. The values of the rate constants for each step of the suggested mechanism have been obtained by simulation. The effect of the initial concentration of mineral oxides and uric acid on the rate of uric acid photo-oxidation by irradiation of some sun care agents has been studied. The kinetic Monte Carlo simulation results agree qualitatively with the existing experimental data for the production of free radicals by sun care agents. Copyright © 2015 Elsevier B.V. All rights reserved.

  4. Kinetic Monte Carlo simulation of dopant-defect systems under submicrosecond laser thermal processes

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

    Fisicaro, G.; Pelaz, Lourdes; Lopez, P.

    2012-11-06

    An innovative Kinetic Monte Carlo (KMC) code has been developed, which rules the post-implant kinetics of the defects system in the extremely far-from-the equilibrium conditions caused by the laser irradiation close to the liquid-solid interface. It considers defect diffusion, annihilation and clustering. The code properly implements, consistently to the stochastic formalism, the fast varying local event rates related to the thermal field T(r,t) evolution. This feature of our numerical method represents an important advancement with respect to current state of the art KMC codes. The reduction of the implantation damage and its reorganization in defect aggregates are studied as amore » function of the process conditions. Phosphorus activation efficiency, experimentally determined in similar conditions, has been related to the emerging damage scenario.« less

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

    PubMed

    Schaefer, C; Jansen, A P J

    2013-02-07

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

  6. Object-oriented code SUR for plasma kinetic simulation

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

    Levchenko, V.D.; Sigov, Y.S.

    1995-12-31

    We have developed a self-consistent simulation code based on object-oriented model of plasma (OOMP) for solving the Vlasov/Poisson (V/P), Vlasov/Maxwell (V/M), Bhatnagar-Gross-Krook (BGK) as well as Fokker-Planck (FP) kinetic equations. The application of an object-oriented approach (OOA) to simulation of plasmas and plasma-like media by means of splitting methods permits to uniformly describe and solve the wide circle of plasma kinetics problems, including those being very complicated: many-dimensional, relativistic, with regard for collisions, specific boundary conditions etc. This paper gives the brief description of possibilities of the SUR code, as a concrete realization of OOMP.

  7. Introducing ab initio based neural networks for transition-rate prediction in kinetic Monte Carlo simulations

    NASA Astrophysics Data System (ADS)

    Messina, Luca; Castin, Nicolas; Domain, Christophe; Olsson, Pär

    2017-02-01

    The quality of kinetic Monte Carlo (KMC) simulations of microstructure evolution in alloys relies on the parametrization of point-defect migration rates, which are complex functions of the local chemical composition and can be calculated accurately with ab initio methods. However, constructing reliable models that ensure the best possible transfer of physical information from ab initio to KMC is a challenging task. This work presents an innovative approach, where the transition rates are predicted by artificial neural networks trained on a database of 2000 migration barriers, obtained with density functional theory (DFT) in place of interatomic potentials. The method is tested on copper precipitation in thermally aged iron alloys, by means of a hybrid atomistic-object KMC model. For the object part of the model, the stability and mobility properties of copper-vacancy clusters are analyzed by means of independent atomistic KMC simulations, driven by the same neural networks. The cluster diffusion coefficients and mean free paths are found to increase with size, confirming the dominant role of coarsening of medium- and large-sized clusters in the precipitation kinetics. The evolution under thermal aging is in better agreement with experiments with respect to a previous interatomic-potential model, especially concerning the experiment time scales. However, the model underestimates the solubility of copper in iron due to the excessively high solution energy predicted by the chosen DFT method. Nevertheless, this work proves the capability of neural networks to transfer complex ab initio physical properties to higher-scale models, and facilitates the extension to systems with increasing chemical complexity, setting the ground for reliable microstructure evolution simulations in a wide range of alloys and applications.

  8. Kinetic Monte Carlo Simulation of Oxygen and Cation Diffusion in Yttria-Stabilized Zirconia

    NASA Technical Reports Server (NTRS)

    Good, Brian

    2011-01-01

    Yttria-stabilized zirconia (YSZ) is of interest to the aerospace community, notably for its application as a thermal barrier coating for turbine engine components. In such an application, diffusion of both oxygen ions and cations is of concern. Oxygen diffusion can lead to deterioration of a coated part, and often necessitates an environmental barrier coating. Cation diffusion in YSZ is much slower than oxygen diffusion. However, such diffusion is a mechanism by which creep takes place, potentially affecting the mechanical integrity and phase stability of the coating. In other applications, the high oxygen diffusivity of YSZ is useful, and makes the material of interest for use as a solid-state electrolyte in fuel cells. The kinetic Monte Carlo (kMC) method offers a number of advantages compared with the more widely known molecular dynamics simulation method. In particular, kMC is much more efficient for the study of processes, such as diffusion, that involve infrequent events. We describe the results of kinetic Monte Carlo computer simulations of oxygen and cation diffusion in YSZ. Using diffusive energy barriers from ab initio calculations and from the literature, we present results on the temperature dependence of oxygen and cation diffusivity, and on the dependence of the diffusivities on yttria concentration and oxygen sublattice vacancy concentration. We also present results of the effect on diffusivity of oxygen vacancies in the vicinity of the barrier cations that determine the oxygen diffusion energy barriers.

  9. Miming the cancer-immune system competition by kinetic Monte Carlo simulations

    NASA Astrophysics Data System (ADS)

    Bianca, Carlo; Lemarchand, Annie

    2016-10-01

    In order to mimic the interactions between cancer and the immune system at cell scale, we propose a minimal model of cell interactions that is similar to a chemical mechanism including autocatalytic steps. The cells are supposed to bear a quantity called activity that may increase during the interactions. The fluctuations of cell activity are controlled by a so-called thermostat. We develop a kinetic Monte Carlo algorithm to simulate the cell interactions and thermalization of cell activity. The model is able to reproduce the well-known behavior of tumors treated by immunotherapy: the first apparent elimination of the tumor by the immune system is followed by a long equilibrium period and the final escape of cancer from immunosurveillance.

  10. Kinetic Monte Carlo Simulation of Oxygen Diffusion in Ytterbium Disilicate

    NASA Astrophysics Data System (ADS)

    Good, Brian

    2015-03-01

    Ytterbium disilicate is of interest as a potential environmental barrier coating for aerospace applications, notably for use in next generation jet turbine engines. In such applications, the diffusion of oxygen and water vapor through these coatings is undesirable if high temperature corrosion is to be avoided. In an effort to understand the diffusion process in these materials, we have performed kinetic Monte Carlo simulations of vacancy-mediated oxygen diffusion in Ytterbium Disilicate. Oxygen vacancy site energies and diffusion barrier energies are computed using Density Functional Theory. We find that many potential diffusion paths involve large barrier energies, but some paths have barrier energies smaller than one electron volt. However, computed vacancy formation energies suggest that the intrinsic vacancy concentration is small in the pure material, with the result that the material is unlikely to exhibit significant oxygen permeability.

  11. Kinetic isotope effect in malonaldehyde determined from path integral Monte Carlo simulations.

    PubMed

    Huang, Jing; Buchowiecki, Marcin; Nagy, Tibor; Vaníček, Jiří; Meuwly, Markus

    2014-01-07

    The primary H/D kinetic isotope effect on the intramolecular proton transfer in malonaldehyde is determined from quantum instanton path integral Monte Carlo simulations on a fully dimensional and validated potential energy surface for temperatures between 250 and 1500 K. Our calculations, based on thermodynamic integration with respect to the mass of the transferring particle, are significantly accelerated by the direct evaluation of the kinetic isotope effect instead of computing it as a ratio of two rate constants. At room temperature, the KIE from the present simulations is 5.2 ± 0.4. The KIE is found to vary considerably as a function of temperature and the low-T behaviour is dominated by the fact that the free energy derivative in the reactant state increases more rapidly than in the transition state. Detailed analysis of the various contributions to the quantum rate constant together with estimates for rates from conventional transition state theory and from periodic orbit theory suggest that the KIE in malonaldehyde is dominated by zero point energy effects and that tunneling plays a minor role at room temperature.

  12. Raman Monte Carlo simulation for light propagation for tissue with embedded objects

    NASA Astrophysics Data System (ADS)

    Periyasamy, Vijitha; Jaafar, Humaira Bte; Pramanik, Manojit

    2018-02-01

    Monte Carlo (MC) stimulation is one of the prominent simulation technique and is rapidly becoming the model of choice to study light-tissue interaction. Monte Carlo simulation for light transport in multi-layered tissue (MCML) is adapted and modelled with different geometry by integrating embedded objects of various shapes (i.e., sphere, cylinder, cuboid and ellipsoid) into the multi-layered structure. These geometries would be useful in providing a realistic tissue structure such as modelling for lymph nodes, tumors, blood vessels, head and other simulation medium. MC simulations were performed on various geometric medium. Simulation of MCML with embedded object (MCML-EO) was improvised for propagation of the photon in the defined medium with Raman scattering. The location of Raman photon generation is recorded. Simulations were experimented on a modelled breast tissue with tumor (spherical and ellipsoidal) and blood vessels (cylindrical). Results were presented in both A-line and B-line scans for embedded objects to determine spatial location where Raman photons were generated. Studies were done for different Raman probabilities.

  13. Kinetic Monte Carlo simulations of water ice porosity: extrapolations of deposition parameters from the laboratory to interstellar space

    NASA Astrophysics Data System (ADS)

    Clements, Aspen R.; Berk, Brandon; Cooke, Ilsa R.; Garrod, Robin T.

    2018-02-01

    Using an off-lattice kinetic Monte Carlo model we reproduce experimental laboratory trends in the density of amorphous solid water (ASW) for varied deposition angle, rate and surface temperature. Extrapolation of the model to conditions appropriate to protoplanetary disks and interstellar dark clouds indicate that these ices may be less porous than laboratory ices.

  14. Kinetic Monte Carlo Simulations of Oxygen Diffusion in Environmental Barrier Coating Materials

    NASA Technical Reports Server (NTRS)

    Good, Brian S.

    2017-01-01

    Ceramic Matrix Composite (CMC) materials are of interest for use in next-generation turbine engine components, offering a number of significant advantages, including reduced weight and high operating temperatures. However, in the hot environment in which such components operate, the presence of water vapor can lead to corrosion and recession, limiting the useful life of the components. Such degradation can be reduced through the use of Environmental Barrier Coatings (EBCs) that limit the amount of oxygen and water vapor reaching the component. Candidate EBC materials include Yttrium and Ytterbium silicates. In this work we present results of kinetic Monte Carlo (kMC) simulations of oxygen diffusion, via the vacancy mechanism, in Yttrium and Ytterbium disilicates, along with a brief discussion of interstitial diffusion.

  15. A new class of accelerated kinetic Monte Carlo algorithms

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

    Bulatov, V V; Oppelstrup, T; Athenes, M

    2011-11-30

    Kinetic (aka dynamic) Monte Carlo (KMC) is a powerful method for numerical simulations of time dependent evolution applied in a wide range of contexts including biology, chemistry, physics, nuclear sciences, financial engineering, etc. Generally, in a KMC the time evolution takes place one event at a time, where the sequence of events and the time intervals between them are selected (or sampled) using random numbers. While details of the method implementation vary depending on the model and context, there exist certain common issues that limit KMC applicability in almost all applications. Among such is the notorious 'flicker problem' where themore » same states of the systems are repeatedly visited but otherwise no essential evolution is observed. In its simplest form the flicker problem arises when two states are connected to each other by transitions whose rates far exceed the rates of all other transitions out of the same two states. In such cases, the model will endlessly hop between the two states otherwise producing no meaningful evolution. In most situation of practical interest, the trapping cluster includes more than two states making the flicker somewhat more difficult to detect and to deal with. Several methods have been proposed to overcome or mitigate the flicker problem, exactly [1-3] or approximately [4,5]. Of the exact methods, the one proposed by Novotny [1] is perhaps most relevant to our research. Novotny formulates the problem of escaping from a trapping cluster as a Markov system with absorbing states. Given an initial state inside the cluster, it is in principle possible to solve the Master Equation for the time dependent probabilities to find the walker in a given state (transient or absorbing) of the cluster at any time in the future. Novotny then proceeds to demonstrate implementation of his general method to trapping clusters containing the initial state plus one or two transient states and all of their absorbing states. Similar methods

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

    PubMed

    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.

  17. Solving the master equation without kinetic Monte Carlo: Tensor train approximations for a CO oxidation model

    NASA Astrophysics Data System (ADS)

    Gelß, Patrick; Matera, Sebastian; Schütte, Christof

    2016-06-01

    In multiscale modeling of heterogeneous catalytic processes, one crucial point is the solution of a Markovian master equation describing the stochastic reaction kinetics. Usually, this is too high-dimensional to be solved with standard numerical techniques and one has to rely on sampling approaches based on the kinetic Monte Carlo method. In this study we break the curse of dimensionality for the direct solution of the Markovian master equation by exploiting the Tensor Train Format for this purpose. The performance of the approach is demonstrated on a first principles based, reduced model for the CO oxidation on the RuO2(110) surface. We investigate the complexity for increasing system size and for various reaction conditions. The advantage over the stochastic simulation approach is illustrated by a problem with increased stiffness.

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

    PubMed

    Numazawa, Satoshi; Smith, Roger

    2011-10-01

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

  19. Temporal acceleration of spatially distributed kinetic Monte Carlo simulations

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

    Chatterjee, Abhijit; Vlachos, Dionisios G.

    The computational intensity of kinetic Monte Carlo (KMC) simulation is a major impediment in simulating large length and time scales. In recent work, an approximate method for KMC simulation of spatially uniform systems, termed the binomial {tau}-leap method, was introduced [A. Chatterjee, D.G. Vlachos, M.A. Katsoulakis, Binomial distribution based {tau}-leap accelerated stochastic simulation, J. Chem. Phys. 122 (2005) 024112], where molecular bundles instead of individual processes are executed over coarse-grained time increments. This temporal coarse-graining can lead to significant computational savings but its generalization to spatially lattice KMC simulation has not been realized yet. Here we extend the binomial {tau}-leapmore » method to lattice KMC simulations by combining it with spatially adaptive coarse-graining. Absolute stability and computational speed-up analyses for spatial systems along with simulations provide insights into the conditions where accuracy and substantial acceleration of the new spatio-temporal coarse-graining method are ensured. Model systems demonstrate that the r-time increment criterion of Chatterjee et al. obeys the absolute stability limit for values of r up to near 1.« less

  20. Kinetic Monte Carlo modeling of chemical reactions coupled with heat transfer.

    PubMed

    Castonguay, Thomas C; Wang, Feng

    2008-03-28

    In this paper, we describe two types of effective events for describing heat transfer in a kinetic Monte Carlo (KMC) simulation that may involve stochastic chemical reactions. Simulations employing these events are referred to as KMC-TBT and KMC-PHE. In KMC-TBT, heat transfer is modeled as the stochastic transfer of "thermal bits" between adjacent grid points. In KMC-PHE, heat transfer is modeled by integrating the Poisson heat equation for a short time. Either approach is capable of capturing the time dependent system behavior exactly. Both KMC-PHE and KMC-TBT are validated by simulating pure heat transfer in a rod and a square and modeling a heated desorption problem where exact numerical results are available. KMC-PHE is much faster than KMC-TBT and is used to study the endothermic desorption of a lattice gas. Interesting findings from this study are reported.

  1. Kinetic Monte Carlo modeling of chemical reactions coupled with heat transfer

    NASA Astrophysics Data System (ADS)

    Castonguay, Thomas C.; Wang, Feng

    2008-03-01

    In this paper, we describe two types of effective events for describing heat transfer in a kinetic Monte Carlo (KMC) simulation that may involve stochastic chemical reactions. Simulations employing these events are referred to as KMC-TBT and KMC-PHE. In KMC-TBT, heat transfer is modeled as the stochastic transfer of "thermal bits" between adjacent grid points. In KMC-PHE, heat transfer is modeled by integrating the Poisson heat equation for a short time. Either approach is capable of capturing the time dependent system behavior exactly. Both KMC-PHE and KMC-TBT are validated by simulating pure heat transfer in a rod and a square and modeling a heated desorption problem where exact numerical results are available. KMC-PHE is much faster than KMC-TBT and is used to study the endothermic desorption of a lattice gas. Interesting findings from this study are reported.

  2. Solving the master equation without kinetic Monte Carlo: Tensor train approximations for a CO oxidation model

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

    Gelß, Patrick, E-mail: p.gelss@fu-berlin.de; Matera, Sebastian, E-mail: matera@math.fu-berlin.de; Schütte, Christof, E-mail: schuette@mi.fu-berlin.de

    2016-06-01

    In multiscale modeling of heterogeneous catalytic processes, one crucial point is the solution of a Markovian master equation describing the stochastic reaction kinetics. Usually, this is too high-dimensional to be solved with standard numerical techniques and one has to rely on sampling approaches based on the kinetic Monte Carlo method. In this study we break the curse of dimensionality for the direct solution of the Markovian master equation by exploiting the Tensor Train Format for this purpose. The performance of the approach is demonstrated on a first principles based, reduced model for the CO oxidation on the RuO{sub 2}(110) surface.more » We investigate the complexity for increasing system size and for various reaction conditions. The advantage over the stochastic simulation approach is illustrated by a problem with increased stiffness.« less

  3. kmos: A lattice kinetic Monte Carlo framework

    NASA Astrophysics Data System (ADS)

    Hoffmann, Max J.; Matera, Sebastian; Reuter, Karsten

    2014-07-01

    Kinetic Monte Carlo (kMC) simulations have emerged as a key tool for microkinetic modeling in heterogeneous catalysis and other materials applications. Systems, where site-specificity of all elementary reactions allows a mapping onto a lattice of discrete active sites, can be addressed within the particularly efficient lattice kMC approach. To this end we describe the versatile kmos software package, which offers a most user-friendly implementation, execution, and evaluation of lattice kMC models of arbitrary complexity in one- to three-dimensional lattice systems, involving multiple active sites in periodic or aperiodic arrangements, as well as site-resolved pairwise and higher-order lateral interactions. Conceptually, kmos achieves a maximum runtime performance which is essentially independent of lattice size by generating code for the efficiency-determining local update of available events that is optimized for a defined kMC model. For this model definition and the control of all runtime and evaluation aspects kmos offers a high-level application programming interface. Usage proceeds interactively, via scripts, or a graphical user interface, which visualizes the model geometry, the lattice occupations and rates of selected elementary reactions, while allowing on-the-fly changes of simulation parameters. We demonstrate the performance and scaling of kmos with the application to kMC models for surface catalytic processes, where for given operation conditions (temperature and partial pressures of all reactants) central simulation outcomes are catalytic activity and selectivities, surface composition, and mechanistic insight into the occurrence of individual elementary processes in the reaction network.

  4. Effect of nonlinearity in hybrid kinetic Monte Carlo-continuum models.

    PubMed

    Balter, Ariel; Lin, Guang; Tartakovsky, Alexandre M

    2012-01-01

    Recently there has been interest in developing efficient ways to model heterogeneous surface reactions with hybrid computational models that couple a kinetic Monte Carlo (KMC) model for a surface to a finite-difference model for bulk diffusion in a continuous domain. We consider two representative problems that validate a hybrid method and show that this method captures the combined effects of nonlinearity and stochasticity. We first validate a simple deposition-dissolution model with a linear rate showing that the KMC-continuum hybrid agrees with both a fully deterministic model and its analytical solution. We then study a deposition-dissolution model including competitive adsorption, which leads to a nonlinear rate, and show that in this case the KMC-continuum hybrid and fully deterministic simulations do not agree. However, we are able to identify the difference as a natural result of the stochasticity coming from the KMC surface process. Because KMC captures inherent fluctuations, we consider it to be more realistic than a purely deterministic model. Therefore, we consider the KMC-continuum hybrid to be more representative of a real system.

  5. Building a kinetic Monte Carlo model with a chosen accuracy.

    PubMed

    Bhute, Vijesh J; Chatterjee, Abhijit

    2013-06-28

    The kinetic Monte Carlo (KMC) method is a popular modeling approach for reaching large materials length and time scales. The KMC dynamics is erroneous when atomic processes that are relevant to the dynamics are missing from the KMC model. Recently, we had developed for the first time an error measure for KMC in Bhute and Chatterjee [J. Chem. Phys. 138, 084103 (2013)]. The error measure, which is given in terms of the probability that a missing process will be selected in the correct dynamics, requires estimation of the missing rate. In this work, we present an improved procedure for estimating the missing rate. The estimate found using the new procedure is within an order of magnitude of the correct missing rate, unlike our previous approach where the estimate was larger by orders of magnitude. This enables one to find the error in the KMC model more accurately. In addition, we find the time for which the KMC model can be used before a maximum error in the dynamics has been reached.

  6. Simulation of metal additive manufacturing microstructures using kinetic Monte Carlo

    DOE PAGES

    Rodgers, Theron M.; Madison, Jonathan D.; Tikare, Veena

    2017-04-19

    Additive manufacturing (AM) is of tremendous interest given its ability to realize complex, non-traditional geometries in engineered structural materials. But, microstructures generated from AM processes can be equally, if not more, complex than their conventionally processed counterparts. While some microstructural features observed in AM may also occur in more traditional solidification processes, the introduction of spatially and temporally mobile heat sources can result in significant microstructural heterogeneity. While grain size and shape in metal AM structures are understood to be highly dependent on both local and global temperature profiles, the exact form of this relation is not well understood. Wemore » implement an idealized molten zone and temperature-dependent grain boundary mobility in a kinetic Monte Carlo model to predict three-dimensional grain structure in additively manufactured metals. In order to demonstrate the flexibility of the model, synthetic microstructures are generated under conditions mimicking relatively diverse experimental results present in the literature. Simulated microstructures are then qualitatively and quantitatively compared to their experimental complements and are shown to be in good agreement.« less

  7. Growth of vertically aligned nanowires in metal-oxide nanocomposites: kinetic Monte-Carlo modeling versus experiments.

    PubMed

    Hennes, M; Schuler, V; Weng, X; Buchwald, J; Demaille, D; Zheng, Y; Vidal, F

    2018-04-26

    We employ kinetic Monte-Carlo simulations to study the growth process of metal-oxide nanocomposites obtained via sequential pulsed laser deposition. Using Ni-SrTiO3 (Ni-STO) as a model system, we reduce the complexity of the computational problem by choosing a coarse-grained approach mapping Sr, Ti and O atoms onto a single effective STO pseudo-atom species. With this ansatz, we scrutinize the kinetics of the sequential synthesis process, governed by alternating deposition and relaxation steps, and analyze the self-organization propensity of Ni atoms into straight vertically aligned nanowires embedded in the surrounding STO matrix. We finally compare the predictions of our binary toy model with experiments and demonstrate that our computational approach captures fundamental aspects of self-assembled nanowire synthesis. Despite its simplicity, our modeling strategy successfully describes the impact of relevant parameters like the concentration or laser frequency on the final nanoarchitecture of metal-oxide thin films grown via pulsed laser deposition.

  8. Kinetic Monte Carlo and cellular particle dynamics simulations of multicellular systems

    NASA Astrophysics Data System (ADS)

    Flenner, Elijah; Janosi, Lorant; Barz, Bogdan; Neagu, Adrian; Forgacs, Gabor; Kosztin, Ioan

    2012-03-01

    Computer modeling of multicellular systems has been a valuable tool for interpreting and guiding in vitro experiments relevant to embryonic morphogenesis, tumor growth, angiogenesis and, lately, structure formation following the printing of cell aggregates as bioink particles. Here we formulate two computer simulation methods: (1) a kinetic Monte Carlo (KMC) and (2) a cellular particle dynamics (CPD) method, which are capable of describing and predicting the shape evolution in time of three-dimensional multicellular systems during their biomechanical relaxation. Our work is motivated by the need of developing quantitative methods for optimizing postprinting structure formation in bioprinting-assisted tissue engineering. The KMC and CPD model parameters are determined and calibrated by using an original computational-theoretical-experimental framework applied to the fusion of two spherical cell aggregates. The two methods are used to predict the (1) formation of a toroidal structure through fusion of spherical aggregates and (2) cell sorting within an aggregate formed by two types of cells with different adhesivities.

  9. Kinetic Monte Carlo (kMC) simulation of carbon co-implant on pre-amorphization process.

    PubMed

    Park, Soonyeol; Cho, Bumgoo; Yang, Seungsu; Won, Taeyoung

    2010-05-01

    We report our kinetic Monte Carlo (kMC) study of the effect of carbon co-implant on the pre-amorphization implant (PAL) process. We employed BCA (Binary Collision Approximation) approach for the acquisition of the initial as-implant dopant profile and kMC method for the simulation of diffusion process during the annealing process. The simulation results implied that carbon co-implant suppresses the boron diffusion due to the recombination with interstitials. Also, we could compare the boron diffusion with carbon diffusion by calculating carbon reaction with interstitial. And we can find that boron diffusion is affected from the carbon co-implant energy by enhancing the trapping of interstitial between boron and interstitial.

  10. Modeling the migration of platinum nanoparticles on surfaces using a kinetic Monte Carlo approach

    DOE PAGES

    Li, Lin; Plessow, Philipp N.; Rieger, Michael; ...

    2017-02-15

    We propose a kinetic Monte Carlo (kMC) model for simulating the movement of platinum particles on supports, based on atom-by-atom diffusion on the surface of the particle. The proposed model was able to reproduce equilibrium cluster shapes predicted using Wulff-construction. The diffusivity of platinum particles was simulated both purely based on random motion and assisted using an external field that causes a drift velocity. The overall particle diffusivity increases with temperature; however, the extracted activation barrier appears to be temperature independent. Additionally, this barrier was found to increase with particle size, as well as, with the adhesion between the particlemore » and the support.« less

  11. The diffusion of a Ga atom on GaAs(001)β2(2 × 4): Local superbasin kinetic Monte Carlo

    NASA Astrophysics Data System (ADS)

    Lin, Yangzheng; Fichthorn, Kristen A.

    2017-10-01

    We use first-principles density-functional theory to characterize the binding sites and diffusion mechanisms for a Ga adatom on the GaAs(001)β 2(2 × 4) surface. Diffusion in this system is a complex process involving eleven unique binding sites and sixteen different hops between neighboring binding sites. Among the binding sites, we can identify four different superbasins such that the motion between binding sites within a superbasin is much faster than hops exiting the superbasin. To describe diffusion, we use a recently developed local superbasin kinetic Monte Carlo (LSKMC) method, which accelerates a conventional kinetic Monte Carlo (KMC) simulation by describing the superbasins as absorbing Markov chains. We find that LSKMC is up to 4300 times faster than KMC for the conditions probed in this study. We characterize the distribution of exit times from the superbasins and find that these are sometimes, but not always, exponential and we characterize the conditions under which the superbasin exit-time distribution should be exponential. We demonstrate that LSKMC simulations assuming an exponential superbasin exit-time distribution yield the same diffusion coefficients as conventional KMC.

  12. Kinetic Monte Carlo Simulation of Oxygen Diffusion in Ytterbium Disilicate

    NASA Technical Reports Server (NTRS)

    Good, Brian S.

    2015-01-01

    Silicon-based ceramic components for next-generation jet turbine engines offer potential weight savings, as well as higher operating temperatures, both of which lead to increased efficiency and lower fuel costs. Silicon carbide (SiC), in particular, offers low density, good strength at high temperatures, and good oxidation resistance in dry air. However, reaction of SiC with high-temperature water vapor, as found in the hot section of jet turbine engines in operation, can cause rapid surface recession, which limits the lifetime of such components. Environmental Barrier Coatings (EBCs) are therefore needed if long component lifetime is to be achieved. Rare earth silicates such as Yb2Si2O7 and Yb2SiO5 have been proposed for such applications; in an effort to better understand diffusion in such materials, we have performed kinetic Monte Carlo (kMC) simulations of oxygen diffusion in Ytterbium disilicate, Yb2- Si2O7. The diffusive process is assumed to take place via the thermally activated hopping of oxygen atoms among oxygen vacancy sites or among interstitial sites. Migration barrier energies are computed using density functional theory (DFT).

  13. Kinetic Monte Carlo Simulation of Oxygen Diffusion in Ytterbium Disilicate

    NASA Technical Reports Server (NTRS)

    Good, Brian S.

    2015-01-01

    Ytterbium disilicate is of interest as a potential environmental barrier coating for aerospace applications, notably for use in next generation jet turbine engines. In such applications, the transport of oxygen and water vapor through these coatings to the ceramic substrate is undesirable if high temperature oxidation is to be avoided. In an effort to understand the diffusion process in these materials, we have performed kinetic Monte Carlo simulations of vacancy-mediated and interstitial oxygen diffusion in Ytterbium disilicate. Oxygen vacancy and interstitial site energies, vacancy and interstitial formation energies, and migration barrier energies were computed using Density Functional Theory. We have found that, in the case of vacancy-mediated diffusion, many potential diffusion paths involve large barrier energies, but some paths have barrier energies smaller than one electron volt. However, computed vacancy formation energies suggest that the intrinsic vacancy concentration is small. In the case of interstitial diffusion, migration barrier energies are typically around one electron volt, but the interstitial defect formation energies are positive, with the result that the disilicate is unlikely to exhibit experience significant oxygen permeability except at very high temperature.

  14. Kinetic energy classification and smoothing for compact B-spline basis sets in quantum Monte Carlo

    DOE PAGES

    Krogel, Jaron T.; Reboredo, Fernando A.

    2018-01-25

    Quantum Monte Carlo calculations of defect properties of transition metal oxides have become feasible in recent years due to increases in computing power. As the system size has grown, availability of on-node memory has become a limiting factor. Saving memory while minimizing computational cost is now a priority. The main growth in memory demand stems from the B-spline representation of the single particle orbitals, especially for heavier elements such as transition metals where semi-core states are present. Despite the associated memory costs, splines are computationally efficient. In this paper, we explore alternatives to reduce the memory usage of splined orbitalsmore » without significantly affecting numerical fidelity or computational efficiency. We make use of the kinetic energy operator to both classify and smooth the occupied set of orbitals prior to splining. By using a partitioning scheme based on the per-orbital kinetic energy distributions, we show that memory savings of about 50% is possible for select transition metal oxide systems. Finally, for production supercells of practical interest, our scheme incurs a performance penalty of less than 5%.« less

  15. Kinetic energy classification and smoothing for compact B-spline basis sets in quantum Monte Carlo

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

    Krogel, Jaron T.; Reboredo, Fernando A.

    Quantum Monte Carlo calculations of defect properties of transition metal oxides have become feasible in recent years due to increases in computing power. As the system size has grown, availability of on-node memory has become a limiting factor. Saving memory while minimizing computational cost is now a priority. The main growth in memory demand stems from the B-spline representation of the single particle orbitals, especially for heavier elements such as transition metals where semi-core states are present. Despite the associated memory costs, splines are computationally efficient. In this paper, we explore alternatives to reduce the memory usage of splined orbitalsmore » without significantly affecting numerical fidelity or computational efficiency. We make use of the kinetic energy operator to both classify and smooth the occupied set of orbitals prior to splining. By using a partitioning scheme based on the per-orbital kinetic energy distributions, we show that memory savings of about 50% is possible for select transition metal oxide systems. Finally, for production supercells of practical interest, our scheme incurs a performance penalty of less than 5%.« less

  16. Kinetic energy classification and smoothing for compact B-spline basis sets in quantum Monte Carlo

    NASA Astrophysics Data System (ADS)

    Krogel, Jaron T.; Reboredo, Fernando A.

    2018-01-01

    Quantum Monte Carlo calculations of defect properties of transition metal oxides have become feasible in recent years due to increases in computing power. As the system size has grown, availability of on-node memory has become a limiting factor. Saving memory while minimizing computational cost is now a priority. The main growth in memory demand stems from the B-spline representation of the single particle orbitals, especially for heavier elements such as transition metals where semi-core states are present. Despite the associated memory costs, splines are computationally efficient. In this work, we explore alternatives to reduce the memory usage of splined orbitals without significantly affecting numerical fidelity or computational efficiency. We make use of the kinetic energy operator to both classify and smooth the occupied set of orbitals prior to splining. By using a partitioning scheme based on the per-orbital kinetic energy distributions, we show that memory savings of about 50% is possible for select transition metal oxide systems. For production supercells of practical interest, our scheme incurs a performance penalty of less than 5%.

  17. First-principles-based kinetic Monte Carlo simulation of nitric oxide decomposition over Pt and Rh surfaces under lean-burn conditions

    NASA Astrophysics Data System (ADS)

    Mei, Donghai; Ge, Qingfeng; Neurock, Matthew; Kieken, Laurent; Lerou, Jan

    First-principles-based kinetic Monte Carlo simulation was used to track the elementary surface transformations involved in the catalytic decomposition of NO over Pt(100) and Rh(100) surfaces under lean-burn operating conditions. Density functional theory (DFT) calculations were carried out to establish the structure and energetics for all reactants, intermediates and products over Pt(100) and Rh(100). Lateral interactions which arise from neighbouring adsorbates were calculated by examining changes in the binding energies as a function of coverage and different coadsorbed configurations. These data were fitted to a bond order conservation (BOC) model which is subsequently used to establish the effects of coverage within the simulation. The intrinsic activation barriers for all the elementary reaction steps in the proposed mechanism of NO reduction over Pt(100) were calculated by using DFT. These values are corrected for coverage effects by using the parametrized BOC model internally within the simulation. This enables a site-explicit kinetic Monte Carlo simulation that can follow the kinetics of NO decomposition over Pt(100) and Rh(100) in the presence of excess oxygen. The simulations are used here to model various experimental protocols including temperature programmed desorption as well as batch catalytic kinetics. The simulation results for the temperature programmed desorption and decomposition of NO over Pt(100) and Rh(100) under vacuum condition were found to be in very good agreement with experimental results. NO decomposition is strongly tied to the temporal number of sites that remain vacant. Experimental results show that Pt is active in the catalytic reaction of NO into N2 and NO2 under lean-burn conditions. The simulated reaction orders for NO and O2 were found to be +0.9 and -0.4 at 723 K, respectively. The simulation also indicates that there is no activity over Rh(100) since the surface becomes poisoned by oxygen.

  18. Kinetic Monte Carlo simulation of nanoparticle film formation via nanocolloid drying

    NASA Astrophysics Data System (ADS)

    Kameya, Yuki

    2017-06-01

    A kinetic Monte Carlo simulation of nanoparticle film formation via nanocolloid drying is presented. The proposed two-dimensional model addresses the dynamics of nanoparticles in the vertical plane of a drying nanocolloid film. The gas-liquid interface movement due to solvent evaporation was controlled by a time-dependent chemical potential, and the resultant particle dynamics including Brownian diffusion and aggregate growth were calculated. Simulations were performed at various Peclet numbers defined based on the rate ratio of solvent evaporation and nanoparticle diffusion. At high Peclet numbers, nanoparticles accumulated at the top layer of the liquid film and eventually formed a skin layer, causing the formation of a particulate film with a densely packed structure. At low Peclet numbers, enhanced particle diffusion led to significant particle aggregation in the bulk colloid, and the resulting film structure became highly porous. The simulated results showed some typical characteristics of a drying nanocolloid that had been reported experimentally. Finally, the potential of the model as well as the remaining challenges are discussed.

  19. Analysis of Radiation Effects in Silicon using Kinetic Monte Carlo Methods

    DOE PAGES

    Hehr, Brian Douglas

    2014-11-25

    The transient degradation of semiconductor device performance under irradiation has long been an issue of concern. Neutron irradiation can instigate the formation of quasi-stable defect structures, thereby introducing new energy levels into the bandgap that alter carrier lifetimes and give rise to such phenomena as gain degradation in bipolar junction transistors. Normally, the initial defect formation phase is followed by a recovery phase in which defect-defect or defect-dopant interactions modify the characteristics of the damaged structure. A kinetic Monte Carlo (KMC) code has been developed to model both thermal and carrier injection annealing of initial defect structures in semiconductor materials.more » The code is employed to investigate annealing in electron-irradiated, p-type silicon as well as the recovery of base current in silicon transistors bombarded with neutrons at the Los Alamos Neutron Science Center (LANSCE) “Blue Room” facility. Our results reveal that KMC calculations agree well with these experiments once adjustments are made, within the appropriate uncertainty bounds, to some of the sensitive defect parameters.« less

  20. Kinetic Monte Carlo Simulations of Rod Eutectics and the Surface Roughening Transition in Binary Alloys

    NASA Technical Reports Server (NTRS)

    Bentz, Daniel N.; Betush, William; Jackson, Kenneth A.

    2003-01-01

    In this paper we report on two related topics: Kinetic Monte Carlo simulations of the steady state growth of rod eutectics from the melt, and a study of the surface roughness of binary alloys. We have implemented a three dimensional kinetic Monte Carlo (kMC) simulation with diffusion by pair exchange only in the liquid phase. Entropies of fusion are first chosen to fit the surface roughness of the pure materials, and the bond energies are derived from the equilibrium phase diagram, by treating the solid and liquid as regular and ideal solutions respectively. A simple cubic lattice oriented in the {100} direction is used. Growth of the rods is initiated from columns of pure B material embedded in an A matrix, arranged in a close packed array with semi-periodic boundary conditions. The simulation cells typically have dimensions of 50 by 87 by 200 unit cells. Steady state growth is compliant with the Jackson-Hunt model. In the kMC simulations, using the spin-one Ising model, growth of each phase is faceted or nonfaceted phases depending on the entropy of fusion. There have been many studies of the surface roughening transition in single component systems, but none for binary alloy systems. The location of the surface roughening transition for the phases of a eutectic alloy determines whether the eutectic morphology will be regular or irregular. We have conducted a study of surface roughness on the spin-one Ising Model with diffusion using kMC. The surface roughness was found to scale with the melting temperature of the alloy as given by the liquidus line on the equilibrium phase diagram. The density of missing lateral bonds at the surface was used as a measure of surface roughness.

  1. Origin of two time-scale regimes in potentiometric titration of metal oxides. A replica kinetic Monte Carlo study.

    PubMed

    Zarzycki, Piotr; Rosso, Kevin M

    2009-06-16

    Replica kinetic Monte Carlo simulations were used to study the characteristic time scales of potentiometric titration of the metal oxides and (oxy)hydroxides. The effect of surface heterogeneity and surface transformation on the titration kinetics were also examined. Two characteristic relaxation times are often observed experimentally, with the trailing slower part attributed to surface nonuniformity, porosity, polymerization, amorphization, and other dynamic surface processes induced by unbalanced surface charge. However, our simulations show that these two characteristic relaxation times are intrinsic to the proton-binding reaction for energetically homogeneous surfaces, and therefore surface heterogeneity or transformation does not necessarily need to be invoked. However, all such second-order surface processes are found to intensify the separation and distinction of the two kinetic regimes. The effect of surface energetic-topographic nonuniformity, as well dynamic surface transformation, interface roughening/smoothing were described in a statistical fashion. Furthermore, our simulations show that a shift in the point-of-zero charge is expected from increased titration speed, and the pH-dependence of the titration measurement error is in excellent agreement with experimental studies.

  2. Simulation of atomic diffusion in the Fcc NiAl system: A kinetic Monte Carlo study

    DOE PAGES

    Alfonso, Dominic R.; Tafen, De Nyago

    2015-04-28

    The atomic diffusion in fcc NiAl binary alloys was studied by kinetic Monte Carlo simulation. The environment dependent hopping barriers were computed using a pair interaction model whose parameters were fitted to relevant data derived from electronic structure calculations. Long time diffusivities were calculated and the effect of composition change on the tracer diffusion coefficients was analyzed. These results indicate that this variation has noticeable impact on the atomic diffusivities. A reduction in the mobility of both Ni and Al is demonstrated with increasing Al content. As a result, examination of the pair interaction between atoms was carried out formore » the purpose of understanding the predicted trends.« less

  3. Hedged Monte-Carlo: low variance derivative pricing with objective probabilities

    NASA Astrophysics Data System (ADS)

    Potters, Marc; Bouchaud, Jean-Philippe; Sestovic, Dragan

    2001-01-01

    We propose a new ‘hedged’ Monte-Carlo ( HMC) method to price financial derivatives, which allows to determine simultaneously the optimal hedge. The inclusion of the optimal hedging strategy allows one to reduce the financial risk associated with option trading, and for the very same reason reduces considerably the variance of our HMC scheme as compared to previous methods. The explicit accounting of the hedging cost naturally converts the objective probability into the ‘risk-neutral’ one. This allows a consistent use of purely historical time series to price derivatives and obtain their residual risk. The method can be used to price a large class of exotic options, including those with path dependent and early exercise features.

  4. Comparing kinetic Monte Carlo and thin-film modeling of transversal instabilities of ridges on patterned substrates

    NASA Astrophysics Data System (ADS)

    Tewes, Walter; Buller, Oleg; Heuer, Andreas; Thiele, Uwe; Gurevich, Svetlana V.

    2017-03-01

    We employ kinetic Monte Carlo (KMC) simulations and a thin-film continuum model to comparatively study the transversal (i.e., Plateau-Rayleigh) instability of ridges formed by molecules on pre-patterned substrates. It is demonstrated that the evolution of the occurring instability qualitatively agrees between the two models for a single ridge as well as for two weakly interacting ridges. In particular, it is shown for both models that the instability occurs on well defined length and time scales which are, for the KMC model, significantly larger than the intrinsic scales of thermodynamic fluctuations. This is further evidenced by the similarity of dispersion relations characterizing the linear instability modes.

  5. Anisotropic hydrogen diffusion in α-Zr and Zircaloy predicted by accelerated kinetic Monte Carlo simulations

    NASA Astrophysics Data System (ADS)

    Zhang, Yongfeng; Jiang, Chao; Bai, Xianming

    2017-01-01

    This report presents an accelerated kinetic Monte Carlo (KMC) method to compute the diffusivity of hydrogen in hcp metals and alloys, considering both thermally activated hopping and quantum tunneling. The acceleration is achieved by replacing regular KMC jumps in trapping energy basins formed by neighboring tetrahedral interstitial sites, with analytical solutions for basin exiting time and probability. Parameterized by density functional theory (DFT) calculations, the accelerated KMC method is shown to be capable of efficiently calculating hydrogen diffusivity in α-Zr and Zircaloy, without altering the kinetics of long-range diffusion. Above room temperature, hydrogen diffusion in α-Zr and Zircaloy is dominated by thermal hopping, with negligible contribution from quantum tunneling. The diffusivity predicted by this DFT + KMC approach agrees well with that from previous independent experiments and theories, without using any data fitting. The diffusivity along is found to be slightly higher than that along , with the anisotropy saturated at about 1.20 at high temperatures, resolving contradictory results in previous experiments. Demonstrated using hydrogen diffusion in α-Zr, the same method can be extended for on-lattice diffusion in hcp metals, or systems with similar trapping basins.

  6. Anisotropic hydrogen diffusion in α-Zr and Zircaloy predicted by accelerated kinetic Monte Carlo simulations

    PubMed Central

    Zhang, Yongfeng; Jiang, Chao; Bai, Xianming

    2017-01-01

    This report presents an accelerated kinetic Monte Carlo (KMC) method to compute the diffusivity of hydrogen in hcp metals and alloys, considering both thermally activated hopping and quantum tunneling. The acceleration is achieved by replacing regular KMC jumps in trapping energy basins formed by neighboring tetrahedral interstitial sites, with analytical solutions for basin exiting time and probability. Parameterized by density functional theory (DFT) calculations, the accelerated KMC method is shown to be capable of efficiently calculating hydrogen diffusivity in α-Zr and Zircaloy, without altering the kinetics of long-range diffusion. Above room temperature, hydrogen diffusion in α-Zr and Zircaloy is dominated by thermal hopping, with negligible contribution from quantum tunneling. The diffusivity predicted by this DFT + KMC approach agrees well with that from previous independent experiments and theories, without using any data fitting. The diffusivity along is found to be slightly higher than that along , with the anisotropy saturated at about 1.20 at high temperatures, resolving contradictory results in previous experiments. Demonstrated using hydrogen diffusion in α-Zr, the same method can be extended for on-lattice diffusion in hcp metals, or systems with similar trapping basins. PMID:28106154

  7. Anisotropic hydrogen diffusion in α-Zr and Zircaloy predicted by accelerated kinetic Monte Carlo simulations

    DOE PAGES

    Zhang, Yongfeng; Jiang, Chao; Bai, Xianming

    2017-01-20

    Here, this report presents an accelerated kinetic Monte Carlo (KMC) method to compute the diffusivity of hydrogen in hcp metals and alloys, considering both thermally activated hopping and quantum tunneling. The acceleration is achieved by replacing regular KMC jumps in trapping energy basins formed by neighboring tetrahedral interstitial sites, with analytical solutions for basin exiting time and probability. Parameterized by density functional theory (DFT) calculations, the accelerated KMC method is shown to be capable of efficiently calculating hydrogen diffusivity in α-Zr and Zircaloy, without altering the kinetics of long-range diffusion. Above room temperature, hydrogen diffusion in α-Zr and Zircaloy ismore » dominated by thermal hopping, with negligible contribution from quantum tunneling. The diffusivity predicted by this DFT + KMC approach agrees well with that from previous independent experiments and theories, without using any data fitting. The diffusivity along < c > is found to be slightly higher than that along < a >, with the anisotropy saturated at about 1.20 at high temperatures, resolving contradictory results in previous experiments. Demonstrated using hydrogen diffusion in α-Zr, the same method can be extended for on-lattice diffusion in hcp metals, or systems with similar trapping basins.« less

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

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

    Matthew Ellis; Derek Gaston; Benoit Forget

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

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

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

    Nandipati, Giridhar; Govind, Niranjan; Andersen, Amity

    2016-03-16

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

  10. Monte Carlo kinetics simulations of ice-mantle formation on interstellar grains

    NASA Astrophysics Data System (ADS)

    Garrod, Robin

    2015-08-01

    The majority of interstellar dust-grain chemical kinetics models use rate equations, or alternative population-based simulation methods, to trace the time-dependent formation of grain-surface molecules and ice mantles. Such methods are efficient, but are incapable of considering explicitly the morphologies of the dust grains, the structure of the ices formed thereon, or the influence of local surface composition on the chemistry.A new Monte Carlo chemical kinetics model, MIMICK, is presented here, whose prototype results were published recently (Garrod 2013, ApJ, 778, 158). The model calculates the strengths and positions of the potential mimima on the surface, on the fly, according to the individual pair-wise (van der Waals) bonds between surface species, allowing the structure of the ice to build up naturally as surface diffusion and chemistry occur. The prototype model considered contributions to a surface particle's potential only from contiguous (or "bonded") neighbors; the full model considers contributions from surface constituents from short to long range. Simulations are conducted on a fully 3-D user-generated dust-grain with amorphous surface characteristics. The chemical network has also been extended from the simple water system previously published, and now includes 33 chemical species and 55 reactions. This allows the major interstellar ice components to be simulated, such as water, methane, ammonia and methanol, as well as a small selection of more complex molecules, including methyl formate (HCOOCH3).The new model results indicate that the porosity of interstellar ices are dependent on multiple variables, including gas density, the dust temperature, and the relative accretion rates of key gas-phase species. The results presented also have implications for the formation of complex organic molecules on dust-grain surfaces at very low temperatures.

  11. Kinetic Monte Carlo Simulation of the Growth of Various Nanostructures through Atomic and Cluster Deposition: Application to Gold Nanostructure Growth on Graphite

    NASA Astrophysics Data System (ADS)

    Claassens, C. H.; Hoffman, M. J. H.; Terblans, J. J.; Swart, H. C.

    2006-01-01

    A Kinetic Monte Carlo (KMC) method is presented to describe the growth of metallic nanostructures through atomic and cluster deposition in the mono -and multilayer regime. The model makes provision for homo- and heteroepitaxial systems with small lattice mismatch. The accuracy of the model is tested with simulations of the growth of gold nanostructures on HOPG and comparisons are made with existing experimental data.

  12. On the Connection between Kinetic Monte Carlo and the Burton-Cabrera-Frank Theory

    NASA Astrophysics Data System (ADS)

    Patrone, Paul; Margetis, Dionisios; Einstein, T. L.

    2013-03-01

    In the many years since it was first proposed, the Burton- Cabrera-Frank (BCF) model of step-flow has been experimentally established as one of the cornerstones of surface physics. However, many questions remain regarding the underlying physical processes and theoretical assumptions that give rise to the BCF theory. In this work, we formally derive the BCF theory from an atomistic, kinetic Monte Carlo model of the surface in 1 +1 dimensions with one step. Our analysis (i) shows how the BCF theory describes a surface with a low density of adsorbed atoms, and (ii) establishes a set of near-equilibrium conditions ensuring that the theory remains valid for all times. Support for PP was provided by the NIST-ARRA Fellowship Award No. 70NANB10H026 through UMD. Support for TLE and PP was also provided by the CMTC at UMD, with ancillary support from the UMD MRSEC. Support for DM was provided by NSF DMS0847587 at UMD.

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

    NASA Astrophysics Data System (ADS)

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

    2017-02-01

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

  14. Mobility of large clusters on a semiconductor surface: Kinetic Monte Carlo simulation results

    NASA Astrophysics Data System (ADS)

    M, Esen; A, T. Tüzemen; M, Ozdemir

    2016-01-01

    The mobility of clusters on a semiconductor surface for various values of cluster size is studied as a function of temperature by kinetic Monte Carlo method. The cluster resides on the surface of a square grid. Kinetic processes such as the diffusion of single particles on the surface, their attachment and detachment to/from clusters, diffusion of particles along cluster edges are considered. The clusters considered in this study consist of 150-6000 atoms per cluster on average. A statistical probability of motion to each direction is assigned to each particle where a particle with four nearest neighbors is assumed to be immobile. The mobility of a cluster is found from the root mean square displacement of the center of mass of the cluster as a function of time. It is found that the diffusion coefficient of clusters goes as D = A(T)Nα where N is the average number of particles in the cluster, A(T) is a temperature-dependent constant and α is a parameter with a value of about -0.64 < α < -0.75. The value of α is found to be independent of cluster sizes and temperature values (170-220 K) considered in this study. As the diffusion along the perimeter of the cluster becomes prohibitive, the exponent approaches a value of -0.5. The diffusion coefficient is found to change by one order of magnitude as a function of cluster size.

  15. Kinetic Monte Carlo simulations of thermally activated magnetization reversal in dual-layer Exchange Coupled Composite recording media

    NASA Astrophysics Data System (ADS)

    Plumer, M. L.; Almudallal, A. M.; Mercer, J. I.; Whitehead, J. P.; Fal, T. J.

    The kinetic Monte Carlo (KMC) method developed for thermally activated magnetic reversal processes in single-layer recording media has been extended to study dual-layer Exchange Coupled Composition (ECC) media used in current and next generations of disc drives. The attempt frequency is derived from the Langer formalism with the saddle point determined using a variant of Bellman Ford algorithm. Complication (such as stagnation) arising from coupled grains having metastable states are addressed. MH-hysteresis loops are calculated over a wide range of anisotropy ratios, sweep rates and inter-layer coupling parameter. Results are compared with standard micromagnetics at fast sweep rates and experimental results at slow sweep rates.

  16. Clustering and heterogeneous dynamics in a kinetic Monte Carlo model of self-propelled hard disks

    NASA Astrophysics Data System (ADS)

    Levis, Demian; Berthier, Ludovic

    2014-06-01

    We introduce a kinetic Monte Carlo model for self-propelled hard disks to capture with minimal ingredients the interplay between thermal fluctuations, excluded volume, and self-propulsion in large assemblies of active particles. We analyze in detail the resulting (density, self-propulsion) nonequilibrium phase diagram over a broad range of parameters. We find that purely repulsive hard disks spontaneously aggregate into fractal clusters as self-propulsion is increased and rationalize the evolution of the average cluster size by developing a kinetic model of reversible aggregation. As density is increased, the nonequilibrium clusters percolate to form a ramified structure reminiscent of a physical gel. We show that the addition of a finite amount of noise is needed to trigger a nonequilibrium phase separation, showing that demixing in active Brownian particles results from a delicate balance between noise, interparticle interactions, and self-propulsion. We show that self-propulsion has a profound influence on the dynamics of the active fluid. We find that the diffusion constant has a nonmonotonic behavior as self-propulsion is increased at finite density and that activity produces strong deviations from Fickian diffusion that persist over large time scales and length scales, suggesting that systems of active particles generically behave as dynamically heterogeneous systems.

  17. First-principles-based kinetic Monte Carlo studies of diffusion of hydrogen in Ni–Al and Ni–Fe binary alloys

    DOE PAGES

    Tafen, De Nyago

    2015-02-14

    The diffusion of dilute hydrogen in fcc Ni–Al and Ni–Fe binary alloys was examined using kinetic Monte Carlo method with input kinetic parameters obtained from first-principles density functional theory. The simulation involves the implementation of computationally efficient energy barrier model that describes the configuration dependence of the hydrogen hopping. The predicted hydrogen diffusion coefficients in Ni and Ni 89.4Fe 10.6 are compared well with the available experimental data. In Ni–Al, the model predicts lower hydrogen diffusivity compared to that in Ni. Overall, diffusion prefactors and the effective activation energies of H in Ni–Fe and Ni–Al are concentration dependent of themore » alloying element. Furthermore, the changes in their values are the results of the short-range order (nearest-neighbor) effect on the interstitial diffusion of hydrogen in fcc Ni-based alloys.« less

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

    NASA Astrophysics Data System (ADS)

    Ustinov, E. A.

    2017-01-01

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

  19. Kinetic Monte Carlo simulations of the effect of the exchange control layer thickness in CoPtCrB/CoPtCrSiO granular media

    NASA Astrophysics Data System (ADS)

    Almudallal, Ahmad M.; Mercer, J. I.; Whitehead, J. P.; Plumer, M. L.; van Ek, J.

    2018-05-01

    A hybrid Landau Lifshitz Gilbert/kinetic Monte Carlo algorithm is used to simulate experimental magnetic hysteresis loops for dual layer exchange coupled composite media. The calculation of the rate coefficients and difficulties arising from low energy barriers, a fundamental problem of the kinetic Monte Carlo method, are discussed and the methodology used to treat them in the present work is described. The results from simulations are compared with experimental vibrating sample magnetometer measurements on dual layer CoPtCrB/CoPtCrSiO media and a quantitative relationship between the thickness of the exchange control layer separating the layers and the effective exchange constant between the layers is obtained. Estimates of the energy barriers separating magnetically reversed states of the individual grains in zero applied field as well as the saturation field at sweep rates relevant to the bit write speeds in magnetic recording are also presented. The significance of this comparison between simulations and experiment and the estimates of the material parameters obtained from it are discussed in relation to optimizing the performance of magnetic storage media.

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

    DOE PAGES

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

    2014-12-24

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

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

    NASA Astrophysics Data System (ADS)

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

    2005-09-01

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

  2. First principles kinetic Monte Carlo study on the growth patterns of WSe2 monolayer

    NASA Astrophysics Data System (ADS)

    Nie, Yifan; Liang, Chaoping; Zhang, Kehao; Zhao, Rui; Eichfeld, Sarah M.; Cha, Pil-Ryung; Colombo, Luigi; Robinson, Joshua A.; Wallace, Robert M.; Cho, Kyeongjae

    2016-06-01

    The control of domain morphology and defect level of synthesized transition metal dichalcogenides (TMDs) is of crucial importance for their device applications. However, current TMDs synthesis by chemical vapor deposition and molecular beam epitaxy is in an early stage of development, where much of the understanding of the process-property relationships is highly empirical. In this work, we use a kinetic Monte Carlo coupled with first principles calculations to study one specific case of the deposition of monolayer WSe2 on graphene, which can be expanded to the entire TMD family. Monolayer WSe2 domains are investigated as a function of incident flux, temperature and precursor ratio. The quality of the grown WSe2 domains is analyzed by the stoichiometry and defect density. A phase diagram of domain morphology is developed in the space of flux and the precursor stoichiometry, in which the triangular compact, fractal and dendritic domains are identified. The phase diagram has inspired a new synthesis strategy for large TMD domains with improved quality.

  3. Efficient 3D kinetic Monte Carlo method for modeling of molecular structure and dynamics.

    PubMed

    Panshenskov, Mikhail; Solov'yov, Ilia A; Solov'yov, Andrey V

    2014-06-30

    Self-assembly of molecular systems is an important and general problem that intertwines physics, chemistry, biology, and material sciences. Through understanding of the physical principles of self-organization, it often becomes feasible to control the process and to obtain complex structures with tailored properties, for example, bacteria colonies of cells or nanodevices with desired properties. Theoretical studies and simulations provide an important tool for unraveling the principles of self-organization and, therefore, have recently gained an increasing interest. The present article features an extension of a popular code MBN EXPLORER (MesoBioNano Explorer) aiming to provide a universal approach to study self-assembly phenomena in biology and nanoscience. In particular, this extension involves a highly parallelized module of MBN EXPLORER that allows simulating stochastic processes using the kinetic Monte Carlo approach in a three-dimensional space. We describe the computational side of the developed code, discuss its efficiency, and apply it for studying an exemplary system. Copyright © 2014 Wiley Periodicals, Inc.

  4. Accurate acceleration of kinetic Monte Carlo simulations through the modification of rate constants.

    PubMed

    Chatterjee, Abhijit; Voter, Arthur F

    2010-05-21

    We present a novel computational algorithm called the accelerated superbasin kinetic Monte Carlo (AS-KMC) method that enables a more efficient study of rare-event dynamics than the standard KMC method while maintaining control over the error. In AS-KMC, the rate constants for processes that are observed many times are lowered during the course of a simulation. As a result, rare processes are observed more frequently than in KMC and the time progresses faster. We first derive error estimates for AS-KMC when the rate constants are modified. These error estimates are next employed to develop a procedure for lowering process rates with control over the maximum error. Finally, numerical calculations are performed to demonstrate that the AS-KMC method captures the correct dynamics, while providing significant CPU savings over KMC in most cases. We show that the AS-KMC method can be employed with any KMC model, even when no time scale separation is present (although in such cases no computational speed-up is observed), without requiring the knowledge of various time scales present in the system.

  5. Monte-Carlo modelling of nano-material photocatalysis: bridging photocatalytic activity and microscopic charge kinetics.

    PubMed

    Liu, Baoshun

    2016-04-28

    In photocatalysis, it is known that light intensity, organic concentration, and temperature affect the photocatalytic activity by changing the microscopic kinetics of holes and electrons. However, how the microscopic kinetics of holes and electrons relates to the photocatalytic activity was not well known. In the present research, we developed a Monte-Carlo random walking model that involved all of the charge kinetics, including the photo-generation, the recombination, the transport, and the interfacial transfer of holes and electrons, to simulate the overall photocatalytic reaction, which we called a "computer experiment" of photocatalysis. By using this model, we simulated the effect of light intensity, temperature, and organic surface coverage on the photocatalytic activity and the density of the free electrons that accumulate in the simulated system. It was seen that the increase of light intensity increases the electron density and its mobility, which increases the probability for a hole/electron to find an electron/hole for recombination, and consequently led to an apparent kinetics that the quantum yield (QY) decreases with the increase of light intensity. It was also seen that the increase of organic surface coverage could increase the rate of hole interfacial transfer and result in the decrease of the probability for an electron to recombine with a hole. Moreover, the increase of organic coverage on the nano-material surface can also increase the accumulation of electrons, which enhances the mobility for electrons to undergo interfacial transfer, and finally leads to the increase of photocatalytic activity. The simulation showed that the temperature had a more complicated effect, as it can simultaneously change the activation of electrons, the interfacial transfer of holes, and the interfacial transfer of electrons. It was shown that the interfacial transfer of holes might play a main role at low temperature, with the temperature-dependence of QY

  6. Object Kinetic Monte Carlo Simulations of Radiation Damage In Bulk Tungsten

    NASA Astrophysics Data System (ADS)

    Nandipati, Giridhar; Setyawan, Wahyu; Heinisch, Howard; Roche, Kenneth; Kurtz, Richard; Wirth, Brian

    2015-11-01

    Results are presented for the evolution of radiation damage in bulk tungsten investigated using the object KMC simulation tool, KSOME, as a function of dose, dose rate and primary knock-on atom (PKA) energies in the range of 10 to 100 keV, at temperatures of 300, 1025 and 2050 K. At 300 K, the number density of vacancies changes minimally with dose rate while the number density of vacancy clusters slightly decreases with dose rate indicating that larger clusters are formed at higher dose rates. Although the average vacancy cluster size increases slightly, the vast majority exists as mono-vacancies. At 1025 K void lattice formation was observed at all dose rates for cascades below 60 keV and at lower dose rates for higher PKA energies. After the appearance of initial features of the void lattice, vacancy cluster density increased minimally while the average vacancy cluster size increases rapidly with dose. At 2050 K, no accumulation of defects was observed over a broad range of dose rates for all PKA energies studied in this work. Further comparisons of results of irradiation simulations at various dose rates and PKA spectra, representative of the High Flux Isotope Reactor and future fusion relevant irradiation facilities will be discussed. The U.S. Department of Energy, Office of Fusion Energy Sciences (FES) and Office of Advanced Scientific Computing Research (ASCR) has supported this study through the SciDAC-3 program.

  7. Kinetic Monte Carlo Simulations of Diffusion in Environmental Barrier Coating Materials

    NASA Technical Reports Server (NTRS)

    Good, Brian

    2017-01-01

    Ceramic Matrix Components (CMC) components for use in turbine engines offer a number of advantages compared with current practice. However, such components are subject to degradation through a variety of mechanisms. In particular, in the hot environment inside a turbine in operation a considerable amount of water vapor is present, and this can lead to corrosion and recession. Environmental Barrier Coating (EBC) systems that limit the amount of oxygen and water reaching the component are required to reduce this degradation and extend component life. A number of silicate-based materials are under consideration for use in such coating systems, including Yttterbium and Yttrium di- and monosilicates. In this work, we present results of kinetic Monte Carlo computer simulations of oxygen diffusion in Yttrium disilicate, and compare with previous work on Yttterbium disilicate. Coatings may also exhibit cracking, and the cracks can provide a direct path for oxygen to reach the component. There is typically a bond coat between the coating and component surface, but the bond coat material is generally chosen for properties other than low oxygen diffusivity. Nevertheless, the degree to which the bond coat can inhibit oxygen diffusion is of interest, as it may form the final defense against oxygen impingement on the component. We have therefore performed similar simulations of oxygen diffusion through HfSiO4, a proposed bond coat material.

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

    PubMed

    Ustinov, E A; Do, D D

    2012-08-21

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

  9. Kinetic Monte Carlo simulations of ion-induced ripple formation: Dependence on flux, temperature, and defect concentration in the linear regime

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

    Chason, E.; Chan, W. L.; Bharathi, M. S.

    Low-energy ion bombardment produces spontaneous periodic structures (sputter ripples) on many surfaces. Continuum theories describe the pattern formation in terms of ion-surface interactions and surface relaxation kinetics, but many features of these models (such as defect concentration) are unknown or difficult to determine. In this work, we present results of kinetic Monte Carlo simulations that model surface evolution using discrete atomistic versions of the physical processes included in the continuum theories. From simulations over a range of parameters, we obtain the dependence of the ripple growth rate, wavelength, and velocity on the ion flux and temperature. The results are discussedmore » in terms of the thermally dependent concentration and diffusivity of ion-induced surface defects. We find that in the early stages of ripple formation the simulation results are surprisingly well described by the predictions of the continuum theory, in spite of simplifying approximations used in the continuum model.« less

  10. Kinetic Monte Carlo Simulations of Oxygen Diffusion in Environmental Barrier Coating Materials

    NASA Technical Reports Server (NTRS)

    Good, Brian S.

    2017-01-01

    Ceramic Matrix Composite (CMC) materials are of interest for use in next-generation turbine engine components, offering a number of significant advantages, including reduced weight and high operating temperatures. However, in the hot environment in which such components operate, the presence of water vapor can lead to corrosion and recession, limiting the useful life of the components. Such degradation can be reduced through the use of Environmental Barrier Coatings (EBCs) that limit the amount of oxygen and water vapor reaching the component. Candidate EBC materials include Yttrium and Ytterbium silicates. In this work we present results of kinetic Monte Carlo (kMC) simulations of oxygen diffusion, via the vacancy mechanism, in Yttrium and Ytterbium disilicates, along with a brief discussion of interstitial diffusion. An EBC system typically includes a bond coat located between the EBC and the component surface. Bond coat materials are generally chosen for properties other than low oxygen diffusivity, but low oxygen diffusivity is nevertheless a desirable characteristic, as the bond coat could provide some additional component protection, particularly in the case where cracks in the coating system provide a direct path from the environment to the bond coat interface. We have therefore performed similar kMC simulations of oxygen diffusion in this material.

  11. Fundamental properties of Fanaroff-Riley type II radio galaxies investigated via Monte Carlo simulations

    NASA Astrophysics Data System (ADS)

    Kapińska, A. D.; Uttley, P.; Kaiser, C. R.

    2012-08-01

    Radio galaxies and quasars are among the largest and most powerful single objects known and are believed to have had a significant impact on the evolving Universe and its large-scale structure. We explore the intrinsic and extrinsic properties of the population of Fanaroff-Riley type II (FR II) objects, i.e. their kinetic luminosities, lifetimes and the central densities of their environments. In particular, the radio and kinetic luminosity functions of these powerful radio sources are investigated using the complete, flux-limited radio catalogues of the Third Cambridge Revised Revised Catalogue (3CRR) and Best et al. We construct multidimensional Monte Carlo simulations using semi-analytical models of FR II source time evolution to create artificial samples of radio galaxies. Unlike previous studies, we compare radio luminosity functions found with both the observed and simulated data to explore the best-fitting fundamental source parameters. The new Monte Carlo method we present here allows us to (i) set better limits on the predicted fundamental parameters of which confidence intervals estimated over broad ranges are presented and (ii) generate the most plausible underlying parent populations of these radio sources. Moreover, as has not been done before, we allow the source physical properties (kinetic luminosities, lifetimes and central densities) to co-evolve with redshift, and we find that all the investigated parameters most likely undergo cosmological evolution. Strikingly, we find that the break in the kinetic luminosity function must undergo redshift evolution of at least (1 + z)3. The fundamental parameters are strongly degenerate, and independent constraints are necessary to draw more precise conclusions. We use the estimated kinetic luminosity functions to set constraints on the duty cycles of these powerful radio sources. A comparison of the duty cycles of powerful FR IIs with those determined from radiative luminosities of active galactic nuclei of

  12. Surface vacancies concentration of CeO2(1 1 1) using kinetic Monte Carlo simulations

    NASA Astrophysics Data System (ADS)

    Mattiello, S.; Kolling, S.; Heiliger, C.

    2016-01-01

    Kinetic Monte Carlo simulations (kMC) are useful tools for the investigation of the dynamics of surface properties. Within this method we investigate the oxygen vacancy concentration of \\text{Ce}{{\\text{O}}2}(1 1 1) at ultra high vacuum conditions (UHV). In order to achieve first principles calculations the input for the simulations, i.e. energy barriers for the microscopic processes, we use density functional theory (DFT) results from literature. We investigate the possibility of ad- and desorption of oxygen on ceria as well as the diffusion of oxygen vacancies to and from the subsurface. In particular, we focus on the vacancy surface concentration as well as on the ratio of the number of subsurface vacancies to the number of vacancies at the surface. The comparison of our dynamically obtained results to the experimental findings leads to several issues. In conclusion, we can claim a substantial incompatibility of the experimental results and the dynamical calculation using DFT inputs.

  13. "First-principles" kinetic Monte Carlo simulations revisited: CO oxidation over RuO2 (110).

    PubMed

    Hess, Franziska; Farkas, Attila; Seitsonen, Ari P; Over, Herbert

    2012-03-15

    First principles-based kinetic Monte Carlo (kMC) simulations are performed for the CO oxidation on RuO(2) (110) under steady-state reaction conditions. The simulations include a set of elementary reaction steps with activation energies taken from three different ab initio density functional theory studies. Critical comparison of the simulation results reveals that already small variations in the activation energies lead to distinctly different reaction scenarios on the surface, even to the point where the dominating elementary reaction step is substituted by another one. For a critical assessment of the chosen energy parameters, it is not sufficient to compare kMC simulations only to experimental turnover frequency (TOF) as a function of the reactant feed ratio. More appropriate benchmarks for kMC simulations are the actual distribution of reactants on the catalyst's surface during steady-state reaction, as determined by in situ infrared spectroscopy and in situ scanning tunneling microscopy, and the temperature dependence of TOF in the from of Arrhenius plots. Copyright © 2012 Wiley Periodicals, Inc.

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

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

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

    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. Moremore » 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.« less

  15. A kinetic Monte Carlo simulation method of van der Waals epitaxy for atomistic nucleation-growth processes of transition metal dichalcogenides.

    PubMed

    Nie, Yifan; Liang, Chaoping; Cha, Pil-Ryung; Colombo, Luigi; Wallace, Robert M; Cho, Kyeongjae

    2017-06-07

    Controlled growth of crystalline solids is critical for device applications, and atomistic modeling methods have been developed for bulk crystalline solids. Kinetic Monte Carlo (KMC) simulation method provides detailed atomic scale processes during a solid growth over realistic time scales, but its application to the growth modeling of van der Waals (vdW) heterostructures has not yet been developed. Specifically, the growth of single-layered transition metal dichalcogenides (TMDs) is currently facing tremendous challenges, and a detailed understanding based on KMC simulations would provide critical guidance to enable controlled growth of vdW heterostructures. In this work, a KMC simulation method is developed for the growth modeling on the vdW epitaxy of TMDs. The KMC method has introduced full material parameters for TMDs in bottom-up synthesis: metal and chalcogen adsorption/desorption/diffusion on substrate and grown TMD surface, TMD stacking sequence, chalcogen/metal ratio, flake edge diffusion and vacancy diffusion. The KMC processes result in multiple kinetic behaviors associated with various growth behaviors observed in experiments. Different phenomena observed during vdW epitaxy process are analysed in terms of complex competitions among multiple kinetic processes. The KMC method is used in the investigation and prediction of growth mechanisms, which provide qualitative suggestions to guide experimental study.

  16. MCViNE- An object oriented Monte Carlo neutron ray tracing simulation package

    DOE PAGES

    Lin, J. Y. Y.; Smith, Hillary L.; Granroth, Garrett E.; ...

    2015-11-28

    MCViNE (Monte-Carlo VIrtual Neutron Experiment) is an open-source Monte Carlo (MC) neutron ray-tracing software for performing computer modeling and simulations that mirror real neutron scattering experiments. We exploited the close similarity between how instrument components are designed and operated and how such components can be modeled in software. For example we used object oriented programming concepts for representing neutron scatterers and detector systems, and recursive algorithms for implementing multiple scattering. Combining these features together in MCViNE allows one to handle sophisticated neutron scattering problems in modern instruments, including, for example, neutron detection by complex detector systems, and single and multiplemore » scattering events in a variety of samples and sample environments. In addition, MCViNE can use simulation components from linear-chain-based MC ray tracing packages which facilitates porting instrument models from those codes. Furthermore it allows for components written solely in Python, which expedites prototyping of new components. These developments have enabled detailed simulations of neutron scattering experiments, with non-trivial samples, for time-of-flight inelastic instruments at the Spallation Neutron Source. Examples of such simulations for powder and single-crystal samples with various scattering kernels, including kernels for phonon and magnon scattering, are presented. As a result, with simulations that closely reproduce experimental results, scattering mechanisms can be turned on and off to determine how they contribute to the measured scattering intensities, improving our understanding of the underlying physics.« less

  17. KMCLib 1.1: Extended random number support and technical updates to the KMCLib general framework for kinetic Monte-Carlo simulations

    NASA Astrophysics Data System (ADS)

    Leetmaa, Mikael; Skorodumova, Natalia V.

    2015-11-01

    We here present a revised version, v1.1, of the KMCLib general framework for kinetic Monte-Carlo (KMC) simulations. The generation of random numbers in KMCLib now relies on the C++11 standard library implementation, and support has been added for the user to choose from a set of C++11 implemented random number generators. The Mersenne-twister, the 24 and 48 bit RANLUX and a 'minimal-standard' PRNG are supported. We have also included the possibility to use true random numbers via the C++11 std::random_device generator. This release also includes technical updates to support the use of an extended range of operating systems and compilers.

  18. Atomistic kinetic Monte Carlo study of atomic layer deposition derived from density functional theory.

    PubMed

    Shirazi, Mahdi; Elliott, Simon D

    2014-01-30

    To describe the atomic layer deposition (ALD) reactions of HfO2 from Hf(N(CH3)2)4 and H2O, a three-dimensional on-lattice kinetic Monte-Carlo model is developed. In this model, all atomistic reaction pathways in density functional theory (DFT) are implemented as reaction events on the lattice. This contains all steps, from the early stage of adsorption of each ALD precursor, kinetics of the surface protons, interaction between the remaining precursors (steric effect), influence of remaining fragments on adsorption sites (blocking), densification of each ALD precursor, migration of each ALD precursors, and cooperation between the remaining precursors to adsorb H2O (cooperative effect). The essential chemistry of the ALD reactions depends on the local environment at the surface. The coordination number and a neighbor list are used to implement the dependencies. The validity and necessity of the proposed reaction pathways are statistically established at the mesoscale. The formation of one monolayer of precursor fragments is shown at the end of the metal pulse. Adsorption and dissociation of the H2O precursor onto that layer is described, leading to the delivery of oxygen and protons to the surface during the H2O pulse. Through these processes, the remaining precursor fragments desorb from the surface, leaving the surface with bulk-like and OH-terminated HfO2, ready for the next cycle. The migration of the low coordinated remaining precursor fragments is also proposed. This process introduces a slow reordering motion (crawling) at the mesoscale, leading to the smooth and conformal thin film that is characteristic of ALD. Copyright © 2013 Wiley Periodicals, Inc.

  19. Effective description of a 3D object for photon transportation in Monte Carlo simulation

    NASA Astrophysics Data System (ADS)

    Suganuma, R.; Ogawa, K.

    2000-06-01

    Photon transport simulation by means of the Monte Carlo method is an indispensable technique for examining scatter and absorption correction methods in SPECT and PET. The authors have developed a method for object description with maximum size regions (maximum rectangular regions: MRRs) to speed up photon transport simulation, and compared the computation time with that for conventional object description methods, a voxel-based (VB) method and an octree method, in the simulations of two kinds of phantoms. The simulation results showed that the computation time with the proposed method became about 50% of that with the VD method and about 70% of that with the octree method for a high resolution MCAT phantom. Here, details of the expansion of the MRR method to three dimensions are given. Moreover, the effectiveness of the proposed method was compared with the VB and octree methods.

  20. Parallelized Monte Carlo software to efficiently simulate the light propagation in arbitrarily shaped objects and aligned scattering media.

    PubMed

    Zoller, Christian Johannes; Hohmann, Ansgar; Foschum, Florian; Geiger, Simeon; Geiger, Martin; Ertl, Thomas Peter; Kienle, Alwin

    2018-06-01

    A GPU-based Monte Carlo software (MCtet) was developed to calculate the light propagation in arbitrarily shaped objects, like a human tooth, represented by a tetrahedral mesh. A unique feature of MCtet is a concept to realize different kinds of light-sources illuminating the complex-shaped surface of an object, for which no preprocessing step is needed. With this concept, it is also possible to consider photons leaving a turbid media and reentering again in case of a concave object. The correct implementation was shown by comparison with five other Monte Carlo software packages. A hundredfold acceleration compared with central processing units-based programs was found. MCtet can simulate anisotropic light propagation, e.g., by accounting for scattering at cylindrical structures. The important influence of the anisotropic light propagation, caused, e.g., by the tubules in human dentin, is shown for the transmission spectrum through a tooth. It was found that the sensitivity to a change in the oxygen saturation inside the pulp for transmission spectra is much larger if the tubules are considered. Another "light guiding" effect based on a combination of a low scattering and a high refractive index in enamel is described. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

  1. Metal-Insulator Transition in Nanoparticle Solids: Insights from Kinetic Monte Carlo Simulations

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

    Qu, Luman; Vörös, Márton; Zimanyi, Gergely T.

    Progress has been rapid in increasing the efficiency of energy conversion in nanoparticles. However, extraction of the photo-generated charge carriers remains challenging. Encouragingly, the charge mobility has been improved recently by driving nanoparticle (NP) films across the metal-insulator transition (MIT). To simulate MIT in NP films, we developed a hierarchical Kinetic Monte Carlo transport model. Electrons transfer between neighboring NPs via activated hopping when the NP energies differ by more than an overlap energy, but transfer by a non-activated quantum delocalization, if the NP energies are closer than the overlap energy. As the overlap energy increases, emerging percolating clusters supportmore » a metallic transport across the entire film. We simulated the evolution of the temperature-dependent electron mobility. We analyzed our data in terms of two candidate models of the MIT: (a) as a Quantum Critical Transition, signaled by an effective gap going to zero; and (b) as a Quantum Percolation Transition, where a sample-spanning metallic percolation path is formed as the fraction of the hopping bonds in the transport paths is going to zero. We found that the Quantum Percolation Transition theory provides a better description of the MIT. We also observed an anomalously low gap region next to the MIT. We discuss the relevance of our results in the light of recent experimental measurements.« less

  2. Metal-Insulator Transition in Nanoparticle Solids: Insights from Kinetic Monte Carlo Simulations

    DOE PAGES

    Qu, Luman; Vörös, Márton; Zimanyi, Gergely T.

    2017-08-01

    Progress has been rapid in increasing the efficiency of energy conversion in nanoparticles. However, extraction of the photo-generated charge carriers remains challenging. Encouragingly, the charge mobility has been improved recently by driving nanoparticle (NP) films across the metal-insulator transition (MIT). To simulate MIT in NP films, we developed a hierarchical Kinetic Monte Carlo transport model. Electrons transfer between neighboring NPs via activated hopping when the NP energies differ by more than an overlap energy, but transfer by a non-activated quantum delocalization, if the NP energies are closer than the overlap energy. As the overlap energy increases, emerging percolating clusters supportmore » a metallic transport across the entire film. We simulated the evolution of the temperature-dependent electron mobility. We analyzed our data in terms of two candidate models of the MIT: (a) as a Quantum Critical Transition, signaled by an effective gap going to zero; and (b) as a Quantum Percolation Transition, where a sample-spanning metallic percolation path is formed as the fraction of the hopping bonds in the transport paths is going to zero. We found that the Quantum Percolation Transition theory provides a better description of the MIT. We also observed an anomalously low gap region next to the MIT. We discuss the relevance of our results in the light of recent experimental measurements.« less

  3. Hybrid Parallelization of Adaptive MHD-Kinetic Module in Multi-Scale Fluid-Kinetic Simulation Suite

    DOE PAGES

    Borovikov, Sergey; Heerikhuisen, Jacob; Pogorelov, Nikolai

    2013-04-01

    The Multi-Scale Fluid-Kinetic Simulation Suite has a computational tool set for solving partially ionized flows. In this paper we focus on recent developments of the kinetic module which solves the Boltzmann equation using the Monte-Carlo method. The module has been recently redesigned to utilize intra-node hybrid parallelization. We describe in detail the redesign process, implementation issues, and modifications made to the code. Finally, we conduct a performance analysis.

  4. Three-dimensional kinetic Monte Carlo simulations of cubic transition metal nitride thin film growth

    NASA Astrophysics Data System (ADS)

    Nita, F.; Mastail, C.; Abadias, G.

    2016-02-01

    A three-dimensional kinetic Monte Carlo (KMC) model has been developed and used to simulate the microstructure and growth morphology of cubic transition metal nitride (TMN) thin films deposited by reactive magnetron sputtering. Results are presented for the case of stoichiometric TiN, chosen as a representative TMN prototype. The model is based on a NaCl-type rigid lattice and includes deposition and diffusion events for both N and Ti species. It is capable of reproducing voids and overhangs, as well as surface faceting. Simulations were carried out assuming a uniform flux of incoming particles approaching the surface at normal incidence. The ballistic deposition model is parametrized with an interaction parameter r0 that mimics the capture distance at which incoming particles may stick on the surface, equivalently to a surface trapping mechanism. Two diffusion models are implemented, based on the different ways to compute the site-dependent activation energy for hopping atoms. The influence of temperature (300-500 K), deposition flux (0.1-100 monolayers/s), and interaction parameter r0 (1.5-6.0 Å) on the obtained growth morphology are presented. Microstructures ranging from highly porous, [001]-oriented straight columns with smooth top surface to rough columns emerging with different crystallographic facets are reproduced, depending on kinetic restrictions, deposited energy (seemingly captured by r0), and shadowing effect. The development of facets is a direct consequence of the diffusion model which includes an intrinsic (minimum energy-based) diffusion anisotropy, although no crystallographic diffusion anisotropy was explicitly taken into account at this stage. The time-dependent morphological evolution is analyzed quantitatively to extract the growth exponent β and roughness exponent α , as indicators of kinetic roughening behavior. For dense TiN films, values of α ≈0.7 and β =0.24 are obtained in good agreement with existing experimental data. At this

  5. Empirical force field-based kinetic Monte Carlo simulation of precipitate evolution and growth in Al-Cu alloys

    NASA Astrophysics Data System (ADS)

    Joshi, Kaushik; Chaudhuri, Santanu

    2016-10-01

    Ability to accelerate the morphological evolution of nanoscale precipitates is a fundamental challenge for atomistic simulations. Kinetic Monte Carlo (KMC) methodology is an effective approach for accelerating the evolution of nanoscale systems that are dominated by so-called rare events. The quality and accuracy of energy landscape used in KMC calculations can be significantly improved using DFT-informed interatomic potentials. Using newly developed computational framework that uses molecular simulator LAMMPS as a library function inside KMC solver SPPARKS, we investigated formation and growth of Guiner-Preston (GP) zones in dilute Al-Cu alloys at different temperature and copper concentrations. The KMC simulations with angular dependent potential (ADP) predict formation of coherent disc-shaped monolayers of copper atoms (GPI zones) in early stage. Such monolayers are then gradually transformed into energetically favored GPII phase that has two aluminum layers sandwiched between copper layers. We analyzed the growth kinetics of KMC trajectory using Johnson-Mehl-Avrami (JMA) theory and obtained a phase transformation index close to 1.0. In the presence of grain boundaries, the KMC calculations predict the segregation of copper atoms near the grain boundaries instead of formation of GP zones. The computational framework presented in this work is based on open source potentials and MD simulator and can predict morphological changes during the evolution of the alloys in the bulk and around grain boundaries.

  6. Learning Kinetic Monte Carlo Models of Condensed Phase High Temperature Chemistry from Molecular Dynamics

    NASA Astrophysics Data System (ADS)

    Yang, Qian; Sing-Long, Carlos; Chen, Enze; Reed, Evan

    2017-06-01

    Complex chemical processes, such as the decomposition of energetic materials and the chemistry of planetary interiors, are typically studied using large-scale molecular dynamics simulations that run for weeks on high performance parallel machines. These computations may involve thousands of atoms forming hundreds of molecular species and undergoing thousands of reactions. It is natural to wonder whether this wealth of data can be utilized to build more efficient, interpretable, and predictive models. In this talk, we will use techniques from statistical learning to develop a framework for constructing Kinetic Monte Carlo (KMC) models from molecular dynamics data. We will show that our KMC models can not only extrapolate the behavior of the chemical system by as much as an order of magnitude in time, but can also be used to study the dynamics of entirely different chemical trajectories with a high degree of fidelity. Then, we will discuss three different methods for reducing our learned KMC models, including a new and efficient data-driven algorithm using L1-regularization. We demonstrate our framework throughout on a system of high-temperature high-pressure liquid methane, thought to be a major component of gas giant planetary interiors.

  7. Mesoscopic kinetic Monte Carlo modeling of organic photovoltaic device characteristics

    NASA Astrophysics Data System (ADS)

    Kimber, Robin G. E.; Wright, Edward N.; O'Kane, Simon E. J.; Walker, Alison B.; Blakesley, James C.

    2012-12-01

    Measured mobility and current-voltage characteristics of single layer and photovoltaic (PV) devices composed of poly{9,9-dioctylfluorene-co-bis[N,N'-(4-butylphenyl)]bis(N,N'-phenyl-1,4-phenylene)diamine} (PFB) and poly(9,9-dioctylfluorene-co-benzothiadiazole) (F8BT) have been reproduced by a mesoscopic model employing the kinetic Monte Carlo (KMC) approach. Our aim is to show how to avoid the uncertainties common in electrical transport models arising from the need to fit a large number of parameters when little information is available, for example, a single current-voltage curve. Here, simulation parameters are derived from a series of measurements using a self-consistent “building-blocks” approach, starting from data on the simplest systems. We found that site energies show disorder and that correlations in the site energies and a distribution of deep traps must be included in order to reproduce measured charge mobility-field curves at low charge densities in bulk PFB and F8BT. The parameter set from the mobility-field curves reproduces the unipolar current in single layers of PFB and F8BT and allows us to deduce charge injection barriers. Finally, by combining these disorder descriptions and injection barriers with an optical model, the external quantum efficiency and current densities of blend and bilayer organic PV devices can be successfully reproduced across a voltage range encompassing reverse and forward bias, with the recombination rate the only parameter to be fitted, found to be 1×107 s-1. These findings demonstrate an approach that removes some of the arbitrariness present in transport models of organic devices, which validates the KMC as an accurate description of organic optoelectronic systems, and provides information on the microscopic origins of the device behavior.

  8. A Simple "Boxed Molecular Kinetics" Approach To Accelerate Rare Events in the Stochastic Kinetic Master Equation.

    PubMed

    Shannon, Robin; Glowacki, David R

    2018-02-15

    The chemical master equation is a powerful theoretical tool for analyzing the kinetics of complex multiwell potential energy surfaces in a wide range of different domains of chemical kinetics spanning combustion, atmospheric chemistry, gas-surface chemistry, solution phase chemistry, and biochemistry. There are two well-established methodologies for solving the chemical master equation: a stochastic "kinetic Monte Carlo" approach and a matrix-based approach. In principle, the results yielded by both approaches are identical; the decision of which approach is better suited to a particular study depends on the details of the specific system under investigation. In this Article, we present a rigorous method for accelerating stochastic approaches by several orders of magnitude, along with a method for unbiasing the accelerated results to recover the "true" value. The approach we take in this paper is inspired by the so-called "boxed molecular dynamics" (BXD) method, which has previously only been applied to accelerate rare events in molecular dynamics simulations. Here we extend BXD to design a simple algorithmic strategy for accelerating rare events in stochastic kinetic simulations. Tests on a number of systems show that the results obtained using the BXD rare event strategy are in good agreement with unbiased results. To carry out these tests, we have implemented a kinetic Monte Carlo approach in MESMER, which is a cross-platform, open-source, and freely available master equation solver.

  9. Dust environment of an airless object: A phase space study with kinetic models

    NASA Astrophysics Data System (ADS)

    Kallio, E.; Dyadechkin, S.; Fatemi, S.; Holmström, M.; Futaana, Y.; Wurz, P.; Fernandes, V. A.; Álvarez, F.; Heilimo, J.; Jarvinen, R.; Schmidt, W.; Harri, A.-M.; Barabash, S.; Mäkelä, J.; Porjo, N.; Alho, M.

    2016-01-01

    The study of dust above the lunar surface is important for both science and technology. Dust particles are electrically charged due to impact of the solar radiation and the solar wind plasma and, therefore, they affect the plasma above the lunar surface. Dust is also a health hazard for crewed missions because micron and sub-micron sized dust particles can be toxic and harmful to the human body. Dust also causes malfunctions in mechanical devices and is therefore a risk for spacecraft and instruments on the lunar surface. Properties of dust particles above the lunar surface are not fully known. However, it can be stated that their large surface area to volume ratio due to their irregular shape, broken chemical bonds on the surface of each dust particle, together with the reduced lunar environment cause the dust particles to be chemically very reactive. One critical unknown factor is the electric field and the electric potential near the lunar surface. We have developed a modelling suite, Dusty Plasma Environments: near-surface characterisation and Modelling (DPEM), to study globally and locally dust environments of the Moon and other airless bodies. The DPEM model combines three independent kinetic models: (1) a 3D hybrid model, where ions are modelled as particles and electrons are modelled as a charged neutralising fluid, (2) a 2D electrostatic Particle-in-Cell (PIC) model where both ions and electrons are treated as particles, and (3) a 3D Monte Carlo (MC) model where dust particles are modelled as test particles. The three models are linked to each other unidirectionally; the hybrid model provides upstream plasma parameters to be used as boundary conditions for the PIC model which generates the surface potential for the MC model. We have used the DPEM model to study properties of dust particles injected from the surface of airless objects such as the Moon, the Martian moon Phobos and the asteroid RQ36. We have performed a (v0, m/q)-phase space study where the

  10. A kinetic Monte Carlo approach to study fluid transport in pore networks

    NASA Astrophysics Data System (ADS)

    Apostolopoulou, M.; Day, R.; Hull, R.; Stamatakis, M.; Striolo, A.

    2017-10-01

    The mechanism of fluid migration in porous networks continues to attract great interest. Darcy's law (phenomenological continuum theory), which is often used to describe macroscopically fluid flow through a porous material, is thought to fail in nano-channels. Transport through heterogeneous and anisotropic systems, characterized by a broad distribution of pores, occurs via a contribution of different transport mechanisms, all of which need to be accounted for. The situation is likely more complicated when immiscible fluid mixtures are present. To generalize the study of fluid transport through a porous network, we developed a stochastic kinetic Monte Carlo (KMC) model. In our lattice model, the pore network is represented as a set of connected finite volumes (voxels), and transport is simulated as a random walk of molecules, which "hop" from voxel to voxel. We simulated fluid transport along an effectively 1D pore and we compared the results to those expected by solving analytically the diffusion equation. The KMC model was then implemented to quantify the transport of methane through hydrated micropores, in which case atomistic molecular dynamic simulation results were reproduced. The model was then used to study flow through pore networks, where it was able to quantify the effect of the pore length and the effect of the network's connectivity. The results are consistent with experiments but also provide additional physical insights. Extension of the model will be useful to better understand fluid transport in shale rocks.

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

    NASA Astrophysics Data System (ADS)

    Danielson, Thomas; Savara, Aditya; Hin, Celine

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

  12. Kinetic Monte Carlo study of vinyl acetate synthesis from ethylene acetoxylation on Pd(100) and Pd/Au(100)

    NASA Astrophysics Data System (ADS)

    Huang, Yanping; Dong, Xiuqin; Yu, Yingzhe; Zhang, Minhua

    2017-11-01

    On the basis of the activation barriers and reaction energies from DFT calculations, kinetic Monte Carlo (kMC) simulations of vinyl acetate (VA) synthesis from ethylene acetoxylation on Pd(100) and Pd/Au(100) were carried out. Through kMC simulation, it was found that VA synthesis from ethylene acetoxylation proceeds via Moiseev mechanism on both Pd(100) and Pd/Au(100). The addition of Au into Pd can suppress ethylene dehydrogenation while it can promote acetic acid dehydrogenation, which can eventually facilitate VA synthesis as a whole. The addition of Au into Pd can further improve the conversion and selectivity of VA synthesis from ethylene acetoxylation. When the reaction network is analyzed, besides the energetics of each elementary reaction, the surface coverage of each species and the occupancy of the surface sites on the catalyst should also be taken into consideration.

  13. Kinetic Monte Carlo simulations for transient thermal fields: Computational methodology and application to the submicrosecond laser processes in implanted silicon.

    PubMed

    Fisicaro, G; Pelaz, L; Lopez, P; La Magna, A

    2012-09-01

    Pulsed laser irradiation of damaged solids promotes ultrafast nonequilibrium kinetics, on the submicrosecond scale, leading to microscopic modifications of the material state. Reliable theoretical predictions of this evolution can be achieved only by simulating particle interactions in the presence of large and transient gradients of the thermal field. We propose a kinetic Monte Carlo (KMC) method for the simulation of damaged systems in the extremely far-from-equilibrium conditions caused by the laser irradiation. The reference systems are nonideal crystals containing point defect excesses, an order of magnitude larger than the equilibrium density, due to a preirradiation ion implantation process. The thermal and, eventual, melting problem is solved within the phase-field methodology, and the numerical solutions for the space- and time-dependent thermal field were then dynamically coupled to the KMC code. The formalism, implementation, and related tests of our computational code are discussed in detail. As an application example we analyze the evolution of the defect system caused by P ion implantation in Si under nanosecond pulsed irradiation. The simulation results suggest a significant annihilation of the implantation damage which can be well controlled by the laser fluence.

  14. Kinetic Monte Carlo simulations of electrodeposition: Crossover from continuous to instantaneous homogeneous nucleation within Avrami’s law

    NASA Astrophysics Data System (ADS)

    Frank, Stefan; Rikvold, Per Arne

    2006-06-01

    The influence of lateral adsorbate diffusion on the dynamics of the first-order phase transition in a two-dimensional Ising lattice gas with attractive nearest-neighbor interactions is investigated by means of kinetic Monte Carlo simulations. For example, electrochemical underpotential deposition proceeds by this mechanism. One major difference from adsorption in vacuum surface science is that under control of the electrode potential and in the absence of mass-transport limitations, local adsorption equilibrium is approximately established. We analyze our results using the theory of Kolmogorov, Johnson and Mehl, and Avrami (KJMA), which we extend to an exponentially decaying nucleation rate. Such a decay may occur due to a suppression of nucleation around existing clusters in the presence of lateral adsorbate diffusion. Correlation functions prove the existence of such exclusion zones. By comparison with microscopic results for the nucleation rate I and the interface velocity of the growing clusters v, we can show that the KJMA theory yields the correct order of magnitude for Iv2. This is true even though the spatial correlations mediated by diffusion are neglected. The decaying nucleation rate causes a gradual crossover from continuous to instantaneous nucleation, which is complete when the decay of the nucleation rate is very fast on the time scale of the phase transformation. Hence, instantaneous nucleation can be homogeneous, producing negative minima in the two-point correlation functions. We also present in this paper an n-fold way Monte Carlo algorithm for a square lattice gas with adsorption/desorption and lateral diffusion.

  15. One-dimensional model of interacting-step fluctuations on vicinal surfaces: Analytical formulas and kinetic Monte-Carlo simulations

    NASA Astrophysics Data System (ADS)

    Patrone, Paul; Einstein, T. L.; Margetis, Dionisios

    2011-03-01

    We study a 1+1D, stochastic, Burton-Cabrera-Frank (BCF) model of interacting steps fluctuating on a vicinal crystal. The step energy accounts for entropic and nearest-neighbor elastic-dipole interactions. Our goal is to formulate and validate a self-consistent mean-field (MF) formalism to approximately solve the system of coupled, nonlinear stochastic differential equations (SDEs) governing fluctuations in surface motion. We derive formulas for the time-dependent terrace width distribution (TWD) and its steady-state limit. By comparison with kinetic Monte-Carlo simulations, we show that our MF formalism improves upon models in which step interactions are linearized. We also indicate how fitting parameters of our steady state MF TWD may be used to determine the mass transport regime and step interaction energy of certain experimental systems. PP and TLE supported by NSF MRSEC under Grant DMR 05-20471 at U. of Maryland; DM supported by NSF under Grant DMS 08-47587.

  16. Theoretical prediction and atomic kinetic Monte Carlo simulations of void superlattice self-organization under irradiation.

    PubMed

    Gao, Yipeng; Zhang, Yongfeng; Schwen, Daniel; Jiang, Chao; Sun, Cheng; Gan, Jian; Bai, Xian-Ming

    2018-04-26

    Nano-structured superlattices may have novel physical properties and irradiation is a powerful mean to drive their self-organization. However, the formation mechanism of superlattice under irradiation is still open for debate. Here we use atomic kinetic Monte Carlo simulations in conjunction with a theoretical analysis to understand and predict the self-organization of nano-void superlattices under irradiation, which have been observed in various types of materials for more than 40 years but yet to be well understood. The superlattice is found to be a result of spontaneous precipitation of voids from the matrix, a process similar to phase separation in regular solid solution, with the symmetry dictated by anisotropic materials properties such as one-dimensional interstitial atom diffusion. This discovery challenges the widely accepted empirical rule of the coherency between the superlattice and host matrix crystal lattice. The atomic scale perspective has enabled a new theoretical analysis to successfully predict the superlattice parameters, which are in good agreement with independent experiments. The theory developed in this work can provide guidelines for designing target experiments to tailor desired microstructure under irradiation. It may also be generalized for situations beyond irradiation, such as spontaneous phase separation with reaction.

  17. Kinetic Monte Carlo Simulations and Molecular Conductance Measurements of the Bacterial Decaheme Cytochrome MtrF

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

    Byun, H. S.; Pirbadian, S.; Nakano, Aiichiro

    2014-09-05

    Microorganisms overcome the considerable hurdle of respiring extracellular solid substrates by deploying large multiheme cytochrome complexes that form 20 nanometer conduits to traffic electrons through the periplasm and across the cellular outer membrane. Here we report the first kinetic Monte Carlo simulations and single-molecule scanning tunneling microscopy (STM) measurements of the Shewanella oneidensis MR-1 outer membrane decaheme cytochrome MtrF, which can perform the final electron transfer step from cells to minerals and microbial fuel cell anodes. We find that the calculated electron transport rate through MtrF is consistent with previously reported in vitro measurements of the Shewanella Mtr complex, asmore » well as in vivo respiration rates on electrode surfaces assuming a reasonable (experimentally verified) coverage of cytochromes on the cell surface. The simulations also reveal a rich phase diagram in the overall electron occupation density of the hemes as a function of electron injection and ejection rates. Single molecule tunneling spectroscopy confirms MtrF's ability to mediate electron transport between an STM tip and an underlying Au(111) surface, but at rates higher than expected from previously calculated heme-heme electron transfer rates for solvated molecules.« less

  18. Self-Learning Off-Lattice Kinetic Monte Carlo method as applied to growth on metal surfaces

    NASA Astrophysics Data System (ADS)

    Trushin, Oleg; Kara, Abdelkader; Rahman, Talat

    2007-03-01

    We propose a new development in the Self-Learning Kinetic Monte Carlo (SLKMC) method with the goal of improving the accuracy with which atomic mechanisms controlling diffusive processes on metal surfaces may be identified. This is important for diffusion of small clusters (2 - 20 atoms) in which atoms may occupy Off-Lattice positions. Such a procedure is also necessary for consideration of heteroepitaxial growth. The new technique combines an earlier version of SLKMC [1] with the inclusion of off-lattice occupancy. This allows us to include arbitrary positions of adatoms in the modeling and makes the simulations more realistic and reliable. We have tested this new approach for the case of the diffusion of small 2D Cu clusters diffusion on Cu(111) and found good performance and satisfactory agreement with results obtained from previous version of SLKMC. The new method also helped reveal a novel atomic mechanism contributing to cluster migration. We have also applied this method to study the diffusion of Cu clusters on Ag(111), and find that Cu atoms generally prefer to occupy off-lattice sites. [1] O. Trushin, A. Kara, A. Karim, T.S. Rahman Phys. Rev B 2005

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

    NASA Technical Reports Server (NTRS)

    Liechty, Derek S.

    2014-01-01

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

  20. A practical approach to the sensitivity analysis for kinetic Monte Carlo simulation of heterogeneous catalysis

    DOE PAGES

    Hoffmann, Max J.; Engelmann, Felix; Matera, Sebastian

    2017-01-31

    Lattice kinetic Monte Carlo simulations have become a vital tool for predictive quality atomistic understanding of complex surface chemical reaction kinetics over a wide range of reaction conditions. In order to expand their practical value in terms of giving guidelines for atomic level design of catalytic systems, it is very desirable to readily evaluate a sensitivity analysis for a given model. The result of such a sensitivity analysis quantitatively expresses the dependency of the turnover frequency, being the main output variable, on the rate constants entering the model. In the past the application of sensitivity analysis, such as Degree ofmore » Rate Control, has been hampered by its exuberant computational effort required to accurately sample numerical derivatives of a property that is obtained from a stochastic simulation method. Here in this study we present an efficient and robust three stage approach that is capable of reliably evaluating the sensitivity measures for stiff microkinetic models as we demonstrate using CO oxidation on RuO 2(110) as a prototypical reaction. In a first step, we utilize the Fisher Information Matrix for filtering out elementary processes which only yield negligible sensitivity. Then we employ an estimator based on linear response theory for calculating the sensitivity measure for non-critical conditions which covers the majority of cases. Finally we adopt a method for sampling coupled finite differences for evaluating the sensitivity measure of lattice based models. This allows efficient evaluation even in critical regions near a second order phase transition that are hitherto difficult to control. The combined approach leads to significant computational savings over straightforward numerical derivatives and should aid in accelerating the nano scale design of heterogeneous catalysts.« less

  1. A practical approach to the sensitivity analysis for kinetic Monte Carlo simulation of heterogeneous catalysis.

    PubMed

    Hoffmann, Max J; Engelmann, Felix; Matera, Sebastian

    2017-01-28

    Lattice kinetic Monte Carlo simulations have become a vital tool for predictive quality atomistic understanding of complex surface chemical reaction kinetics over a wide range of reaction conditions. In order to expand their practical value in terms of giving guidelines for the atomic level design of catalytic systems, it is very desirable to readily evaluate a sensitivity analysis for a given model. The result of such a sensitivity analysis quantitatively expresses the dependency of the turnover frequency, being the main output variable, on the rate constants entering the model. In the past, the application of sensitivity analysis, such as degree of rate control, has been hampered by its exuberant computational effort required to accurately sample numerical derivatives of a property that is obtained from a stochastic simulation method. In this study, we present an efficient and robust three-stage approach that is capable of reliably evaluating the sensitivity measures for stiff microkinetic models as we demonstrate using the CO oxidation on RuO 2 (110) as a prototypical reaction. In the first step, we utilize the Fisher information matrix for filtering out elementary processes which only yield negligible sensitivity. Then we employ an estimator based on the linear response theory for calculating the sensitivity measure for non-critical conditions which covers the majority of cases. Finally, we adapt a method for sampling coupled finite differences for evaluating the sensitivity measure for lattice based models. This allows for an efficient evaluation even in critical regions near a second order phase transition that are hitherto difficult to control. The combined approach leads to significant computational savings over straightforward numerical derivatives and should aid in accelerating the nano-scale design of heterogeneous catalysts.

  2. A practical approach to the sensitivity analysis for kinetic Monte Carlo simulation of heterogeneous catalysis

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

    Hoffmann, Max J.; Engelmann, Felix; Matera, Sebastian

    Lattice kinetic Monte Carlo simulations have become a vital tool for predictive quality atomistic understanding of complex surface chemical reaction kinetics over a wide range of reaction conditions. In order to expand their practical value in terms of giving guidelines for atomic level design of catalytic systems, it is very desirable to readily evaluate a sensitivity analysis for a given model. The result of such a sensitivity analysis quantitatively expresses the dependency of the turnover frequency, being the main output variable, on the rate constants entering the model. In the past the application of sensitivity analysis, such as Degree ofmore » Rate Control, has been hampered by its exuberant computational effort required to accurately sample numerical derivatives of a property that is obtained from a stochastic simulation method. Here in this study we present an efficient and robust three stage approach that is capable of reliably evaluating the sensitivity measures for stiff microkinetic models as we demonstrate using CO oxidation on RuO 2(110) as a prototypical reaction. In a first step, we utilize the Fisher Information Matrix for filtering out elementary processes which only yield negligible sensitivity. Then we employ an estimator based on linear response theory for calculating the sensitivity measure for non-critical conditions which covers the majority of cases. Finally we adopt a method for sampling coupled finite differences for evaluating the sensitivity measure of lattice based models. This allows efficient evaluation even in critical regions near a second order phase transition that are hitherto difficult to control. The combined approach leads to significant computational savings over straightforward numerical derivatives and should aid in accelerating the nano scale design of heterogeneous catalysts.« less

  3. A practical approach to the sensitivity analysis for kinetic Monte Carlo simulation of heterogeneous catalysis

    NASA Astrophysics Data System (ADS)

    Hoffmann, Max J.; Engelmann, Felix; Matera, Sebastian

    2017-01-01

    Lattice kinetic Monte Carlo simulations have become a vital tool for predictive quality atomistic understanding of complex surface chemical reaction kinetics over a wide range of reaction conditions. In order to expand their practical value in terms of giving guidelines for the atomic level design of catalytic systems, it is very desirable to readily evaluate a sensitivity analysis for a given model. The result of such a sensitivity analysis quantitatively expresses the dependency of the turnover frequency, being the main output variable, on the rate constants entering the model. In the past, the application of sensitivity analysis, such as degree of rate control, has been hampered by its exuberant computational effort required to accurately sample numerical derivatives of a property that is obtained from a stochastic simulation method. In this study, we present an efficient and robust three-stage approach that is capable of reliably evaluating the sensitivity measures for stiff microkinetic models as we demonstrate using the CO oxidation on RuO2(110) as a prototypical reaction. In the first step, we utilize the Fisher information matrix for filtering out elementary processes which only yield negligible sensitivity. Then we employ an estimator based on the linear response theory for calculating the sensitivity measure for non-critical conditions which covers the majority of cases. Finally, we adapt a method for sampling coupled finite differences for evaluating the sensitivity measure for lattice based models. This allows for an efficient evaluation even in critical regions near a second order phase transition that are hitherto difficult to control. The combined approach leads to significant computational savings over straightforward numerical derivatives and should aid in accelerating the nano-scale design of heterogeneous catalysts.

  4. Kinetic Monte Carlo simulations of water ice porosity: extrapolations of deposition parameters from the laboratory to interstellar space.

    PubMed

    Clements, Aspen R; Berk, Brandon; Cooke, Ilsa R; Garrod, Robin T

    2018-02-21

    Dust grains in cold, dense interstellar clouds build up appreciable ice mantles through the accretion and subsequent surface chemistry of atoms and molecules from the gas. These mantles, of thicknesses on the order of 100 monolayers, are primarily composed of H 2 O, CO, and CO 2 . Laboratory experiments using interstellar ice analogues have shown that porosity could be present and can facilitate diffusion of molecules along the inner pore surfaces. However, the movement of molecules within and upon the ice is poorly described by current chemical kinetics models, making it difficult either to reproduce the formation of experimental porous ice structures or to extrapolate generalized laboratory results to interstellar conditions. Here we use the off-lattice Monte Carlo kinetics model MIMICK to investigate the effects that various deposition parameters have on laboratory ice structures. The model treats molecules as isotropic spheres of a uniform size, using a Lennard-Jones potential. We reproduce experimental trends in the density of amorphous solid water (ASW) for varied deposition angle, rate and surface temperature; ice density decreases when the incident angle or deposition rate is increased, while increasing temperature results in a more-compact water ice. The models indicate that the density behaviour at higher temperatures (≥80 K) is dependent on molecular rearrangement resulting from thermal diffusion. To reproduce trends at lower temperatures, it is necessary to take account of non-thermal diffusion by newly-adsorbed molecules, which bring kinetic energy both from the gas phase and from their acceleration into a surface binding site. Extrapolation of the model to conditions appropriate to protoplanetary disks, in which direct accretion of water from the gas-phase may be the dominant ice formation mechanism, indicate that these ices may be less porous than laboratory ices.

  5. Structure sensitivity in oxide catalysis: First-principles kinetic Monte Carlo simulations for CO oxidation at RuO 2(111)

    DOE PAGES

    Wang, Tongyu; Reuter, Karsten

    2015-11-24

    We present a density-functional theory based kinetic Monte Carlo study of CO oxidation at the (111) facet of RuO 2. We compare the detailed insight into elementary processes, steady-state surface coverages, and catalytic activity to equivalent published simulation data for the frequently studied RuO 2(110) facet. Qualitative differences are identified in virtually every aspect ranging from binding energetics over lateral interactions to the interplay of elementary processes at the different active sites. Nevertheless, particularly at technologically relevant elevated temperatures, near-ambient pressures and near-stoichiometric feeds both facets exhibit almost identical catalytic activity. As a result, these findings challenge the traditional definitionmore » of structure sensitivity based on macroscopically observable turnover frequencies and prompt scrutiny of the applicability of structure sensitivity classifications developed for metals to oxide catalysis.« less

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

    NASA Astrophysics Data System (ADS)

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

    2017-10-01

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

  7. Displacement cascades and defect annealing in tungsten, Part III: The sensitivity of cascade annealing in tungsten to the values of kinetic parameters

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

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

    2015-07-01

    Object kinetic Monte Carlo (OKMC) simulations have been performed to investigate various aspects of cascade aging in bulk tungsten and to determine the sensitivity of the results to the kinetic parameters. The primary focus is on how the kinetic parameters affect the initial recombination of defects in the first few ns of a simulation. The simulations were carried out using the object kinetic Monte Carlo (OKMC) code KSOME (kinetic simulations of microstructure evolution), using a database of cascades obtained from results of molecular dynamics (MD) simulations at various primary knock-on atom (PKA) energies and directions at temperatures of 300, 1025more » and 2050 K. The OKMC model was parameterized using defect migration barriers and binding energies from ab initio calculations. Results indicate that, due to the disparate mobilities of SIA and vacancy clusters in tungsten, annealing is dominated by SIA migration even at temperatures as high as 2050 K. For 100 keV cascades initiated at 300 K recombination is dominated by annihilation of large defect clusters. But for all other PKA energies and temperatures most of the recombination is due to the migration and rotation of small SIA clusters, while all the large SIA clusters escape the cubic simulation cell. The inverse U-shape behavior exhibited by the annealing efficiency as a function of temperature curve, especially for cascades of large PKA energies, is due to asymmetry in SIA and vacancy clustering assisted by the large difference in mobilities of SIAs and vacancies. This annealing behavior is unaffected by the dimensionality of SIA migration persists over a broad range of relative mobilities of SIAs and vacancies.« less

  8. SQERTSS: Dynamic rank based throttling of transition probabilities in kinetic Monte Carlo simulations

    NASA Astrophysics Data System (ADS)

    Danielson, Thomas; Sutton, Jonathan E.; Hin, Céline; Savara, Aditya

    2017-10-01

    Lattice based Kinetic Monte Carlo (KMC) simulations offer a powerful simulation technique for investigating large reaction networks while retaining spatial configuration information, unlike ordinary differential equations. However, large chemical reaction networks can contain reaction processes with rates spanning multiple orders of magnitude. This can lead to the problem of "KMC stiffness" (similar to stiffness in differential equations), where the computational expense has the potential to be overwhelmed by very short time-steps during KMC simulations, with the simulation spending an inordinate amount of KMC steps/CPU time simulating fast frivolous processes (FFPs) without progressing the system (reaction network). In order to achieve simulation times that are experimentally relevant or desired for predictions, a dynamic throttling algorithm involving separation of the processes into speed-ranks based on event frequencies has been designed and implemented with the intent of decreasing the probability of FFP events, and increasing the probability of slow process events-allowing rate limiting events to become more likely to be observed in KMC simulations. This Staggered Quasi-Equilibrium Rank-based Throttling for Steady-state (SQERTSS) algorithm is designed for use in achieving and simulating steady-state conditions in KMC simulations. As shown in this work, the SQERTSS algorithm also works for transient conditions: the correct configuration space and final state will still be achieved if the required assumptions are not violated, with the caveat that the sizes of the time-steps may be distorted during the transient period.

  9. SQERTSS: Dynamic rank based throttling of transition probabilities in kinetic Monte Carlo simulations

    DOE PAGES

    Danielson, Thomas; Sutton, Jonathan E.; Hin, Céline; ...

    2017-06-09

    Lattice based Kinetic Monte Carlo (KMC) simulations offer a powerful simulation technique for investigating large reaction networks while retaining spatial configuration information, unlike ordinary differential equations. However, large chemical reaction networks can contain reaction processes with rates spanning multiple orders of magnitude. This can lead to the problem of “KMC stiffness” (similar to stiffness in differential equations), where the computational expense has the potential to be overwhelmed by very short time-steps during KMC simulations, with the simulation spending an inordinate amount of KMC steps / cpu-time simulating fast frivolous processes (FFPs) without progressing the system (reaction network). In order tomore » achieve simulation times that are experimentally relevant or desired for predictions, a dynamic throttling algorithm involving separation of the processes into speed-ranks based on event frequencies has been designed and implemented with the intent of decreasing the probability of FFP events, and increasing the probability of slow process events -- allowing rate limiting events to become more likely to be observed in KMC simulations. This Staggered Quasi-Equilibrium Rank-based Throttling for Steady-state (SQERTSS) algorithm designed for use in achieving and simulating steady-state conditions in KMC simulations. Lastly, as shown in this work, the SQERTSS algorithm also works for transient conditions: the correct configuration space and final state will still be achieved if the required assumptions are not violated, with the caveat that the sizes of the time-steps may be distorted during the transient period.« less

  10. Diffusion of small Cu islands on the Ni(111) surface: A self-learning kinetic Monte Carlo study

    NASA Astrophysics Data System (ADS)

    Acharya, Shree Ram; Shah, Syed Islamuddin; Rahman, Talat S.

    2017-08-01

    We elucidate the diffusion kinetics of a heteroepitaxial system consisting of two-dimensional small (1-8 atoms) Cu islands on the Ni(111) surface at (100-600) K using the Self-Learning Kinetic Monte Carlo (SLKMC-II) method. Study of the statics of the system shows that compact CuN (3≤N≤8) clusters made up of triangular units on fcc occupancy sites are the energetically most stable structures of those clusters. Interestingly, we find a correlation between the height of the activation energy barrier (Ea) and the location of the transition state (TS). The Ea of processes for Cu islands on the Ni(111) surface are in general smaller than those of their counterpart Ni islands on the same surface. We find this difference to correlate with the relative strength of the lateral interaction of the island atoms in the two systems. While our database consists of hundreds of possible processes, we identify and discuss the energetics of those that are the most dominant, or are rate-limiting, or most contributory to the diffusion of the islands. Since the Ea of single- and multi-atom processes that convert compact island shapes into non-compact ones are larger (with a significantly smaller Ea for their reverse processes) than that for the collective (concerted) motion of the island, the later dominate in the system kinetics - except for the cases of the dimer, pentamer and octamer. Short-jump involving one atom, long jump dimer-shearing, and long-jump corner shearing (via a single-atom) are, respectively, the dominating processes in the diffusion of the dimer, pentamer and octamer. Furthermore single-atom corner-rounding are the rate-limiting processes for the pentamer and octamer islands. Comparison of the energetics of selected processes and lateral interactions obtained from semi-empirical interatomic potentials with those from density functional theory show minor quantitative differences and overall qualitative agreement.

  11. Acceleration and sensitivity analysis of lattice kinetic Monte Carlo simulations using parallel processing and rate constant rescaling

    NASA Astrophysics Data System (ADS)

    Núñez, M.; Robie, T.; Vlachos, D. G.

    2017-10-01

    Kinetic Monte Carlo (KMC) simulation provides insights into catalytic reactions unobtainable with either experiments or mean-field microkinetic models. Sensitivity analysis of KMC models assesses the robustness of the predictions to parametric perturbations and identifies rate determining steps in a chemical reaction network. Stiffness in the chemical reaction network, a ubiquitous feature, demands lengthy run times for KMC models and renders efficient sensitivity analysis based on the likelihood ratio method unusable. We address the challenge of efficiently conducting KMC simulations and performing accurate sensitivity analysis in systems with unknown time scales by employing two acceleration techniques: rate constant rescaling and parallel processing. We develop statistical criteria that ensure sufficient sampling of non-equilibrium steady state conditions. Our approach provides the twofold benefit of accelerating the simulation itself and enabling likelihood ratio sensitivity analysis, which provides further speedup relative to finite difference sensitivity analysis. As a result, the likelihood ratio method can be applied to real chemistry. We apply our methodology to the water-gas shift reaction on Pt(111).

  12. Kinetic Monte Carlo Investigation of the Effects of Vacancy Pairing on Oxygen Diffusivity in Yttria-Stabilized Zirconia

    NASA Technical Reports Server (NTRS)

    Good, Brian S.

    2011-01-01

    Yttria-stabilized zirconia s high oxygen diffusivity and corresponding high ionic conductivity, and its structural stability over a broad range of temperatures, have made the material of interest for use in a number of applications, for example, as solid electrolytes in fuel cells. At low concentrations, the stabilizing yttria also serves to increase the oxygen diffusivity through the presence of corresponding oxygen vacancies, needed to maintain charge neutrality. At higher yttria concentration, however, diffusivity is impeded by the larger number of relatively high energy migration barriers associated with yttrium cations. In addition, there is evidence that oxygen vacancies preferentially occupy nearest-neighbor sites around either dopant or Zr cations, further affecting vacancy diffusion. We present the results of ab initio calculations that indicate that it is energetically favorable for oxygen vacancies to occupy nearest-neighbor sites adjacent to Y ions, and that the presence of vacancies near either species of cation lowers the migration barriers. Kinetic Monte Carlo results from simulations incorporating this effect are presented and compared with results from simulations in which the effect is not present.

  13. Generating relevant kinetic Monte Carlo catalogs using temperature accelerated dynamics with control over the accuracy

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

    Chatterjee, Abhijit; Voter, Arthur

    2009-01-01

    We develop a variation of the temperature accelerated dynamics (TAD) method, called the p-TAD method, that efficiently generates an on-the-fly kinetic Monte Carlo (KMC) process catalog with control over the accuracy of the catalog. It is assumed that transition state theory is valid. The p-TAD method guarantees that processes relevant at the timescales of interest to the simulation are present in the catalog with a chosen confidence. A confidence measure associated with the process catalog is derived. The dynamics is then studied using the process catalog with the KMC method. Effective accuracy of a p-TAD calculation is derived when amore » KMC catalog is reused for conditions different from those the catalog was originally generated for. Different KMC catalog generation strategies that exploit the features of the p-TAD method and ensure higher accuracy and/or computational efficiency are presented. The accuracy and the computational requirements of the p-TAD method are assessed. Comparisons to the original TAD method are made. As an example, we study dynamics in sub-monolayer Ag/Cu(110) at the time scale of seconds using the p-TAD method. It is demonstrated that the p-TAD method overcomes several challenges plaguing the conventional KMC method.« less

  14. An Ab Initio and Kinetic Monte Carlo Simulation Study of Lithium Ion Diffusion on Graphene

    PubMed Central

    Zhong, Kehua; Yang, Yanmin; Xu, Guigui; Zhang, Jian-Min; Huang, Zhigao

    2017-01-01

    The Li+ diffusion coefficients in Li+-adsorbed graphene systems were determined by combining first-principle calculations based on density functional theory with Kinetic Monte Carlo simulations. The calculated results indicate that the interactions between Li ions have a very important influence on lithium diffusion. Based on energy barriers directly obtained from first-principle calculations for single-Li+ and two-Li+ adsorbed systems, a new equation predicting energy barriers with more than two Li ions was deduced. Furthermore, it is found that the temperature dependence of Li+ diffusion coefficients fits well to the Arrhenius equation, rather than meeting the equation from electrochemical impedance spectroscopy applied to estimate experimental diffusion coefficients. Moreover, the calculated results also reveal that Li+ concentration dependence of diffusion coefficients roughly fits to the equation from electrochemical impedance spectroscopy in a low concentration region; however, it seriously deviates from the equation in a high concentration region. So, the equation from electrochemical impedance spectroscopy technique could not be simply used to estimate the Li+ diffusion coefficient for all Li+-adsorbed graphene systems with various Li+ concentrations. Our work suggests that interactions between Li ions, and among Li ion and host atoms will influence the Li+ diffusion, which determines that the Li+ intercalation dependence of Li+ diffusion coefficient should be changed and complex. PMID:28773122

  15. Morphological stability and kinetics in crystal growth from vapors

    NASA Technical Reports Server (NTRS)

    Rosenberger, Franz

    1990-01-01

    The following topics are discussed: (1) microscopy image storage and processing system; (2) growth kinetics and morphology study with carbon tetrabromide; (3) photothermal deflection vapor growth setup; (4) bridgman growth of iodine single crystals; (5) vapor concentration distribution measurement during growth; and (6) Monte Carlo modeling of anisotropic growth kinetics and morphology. A collection of presentations and publications of these results are presented.

  16. Kinetic Monte Carlo simulations of excitation density dependent scintillation in CsI and CsI(Tl)

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

    Wang, Zhiguo; Williams, Richard; Grim, Joel

    2013-08-15

    Nonlinear quenching of electron-hole pairs in the denser regions of ionization tracks created by γ-ray and high-energy electrons is a likely cause of the light yield nonproportionality of many inorganic scintillators. Therefore, kinetic Monte Carlo (KMC) simulations were carried out to investigate the scintillation properties of pure and thallium-doped CsI as a function of electron-hole pair density. The availability of recent experimental data on the excitation density dependence of the light yield of CsI following ultraviolet excitation allowed for an improved parameterization of the interactions between self-trapped excitons (STE) in the KMC model via dipole-dipole Förster transfer. The KMC simulationsmore » reveal that nonlinear quenching occurs very rapidly (within a few picoseconds) in the early stages of the scintillation process. In addition, the simulations predict that the concentration of thallium activators can affect the extent of nonlinear quenching as it has a direct influence on the STE density through STE dissociation and electron scavenging. This improved model will enable more realistic simulations of the nonproportional γ-ray and electron response of inorganic scintillators.« less

  17. Structure sensitivity in oxide catalysis: First-principles kinetic Monte Carlo simulations for CO oxidation at RuO{sub 2}(111)

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

    Wang, Tongyu; Reuter, Karsten, E-mail: karsten.reuter@ch.tum.de; SUNCAT Center for Interface Science and Catalysis, SLAC National Accelerator Laboratory and Stanford University, 443 Via Ortega, Stanford, California 94035-4300

    2015-11-28

    We present a density-functional theory based kinetic Monte Carlo study of CO oxidation at the (111) facet of RuO{sub 2}. We compare the detailed insight into elementary processes, steady-state surface coverages, and catalytic activity to equivalent published simulation data for the frequently studied RuO{sub 2}(110) facet. Qualitative differences are identified in virtually every aspect ranging from binding energetics over lateral interactions to the interplay of elementary processes at the different active sites. Nevertheless, particularly at technologically relevant elevated temperatures, near-ambient pressures and near-stoichiometric feeds both facets exhibit almost identical catalytic activity. These findings challenge the traditional definition of structure sensitivitymore » based on macroscopically observable turnover frequencies and prompt scrutiny of the applicability of structure sensitivity classifications developed for metals to oxide catalysis.« less

  18. Oxygen Reduction Reaction on Ag(111) in Alkaline Solution: A Combined Density Functional Theory and Kinetic Monte Carlo Study

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

    Liu, Shizhong; White, Michael G.; Liu, Ping

    We reported a detailed mechanistic study of the oxygen reduction reaction (ORR) on the model Ag(111) surface in alkaline solution by using density functional theory (DFT) and Kinetic Monte Carlo (KMC) simulations, in which multiple pathways involving either 2 e - or 4 e - mechanisms were included. The theoretical modelling presented here is able to reproduce the experimentally measured polarization curves in both low and high potential regions. An electrochemical 4 e - network including both a chemisorbed water (*H 2O)-mediated 4 e - associative pathway and the conventional associative pathway was identified to dominate the ORR mechanism. Onmore » the basis of the mechanistic understanding derived from these calculations, the ways to promote the ORR on Ag(111) were provided, including facilitating *OH removal, **O 2 reduction by *H 2O, and suppressing **O 2 desorption. Finally, the origin of the different ORR behaviors of Ag(111) and Pt(111) was also discussed in detail.« less

  19. Oxygen Reduction Reaction on Ag(111) in Alkaline Solution: A Combined Density Functional Theory and Kinetic Monte Carlo Study

    DOE PAGES

    Liu, Shizhong; White, Michael G.; Liu, Ping

    2018-01-25

    We reported a detailed mechanistic study of the oxygen reduction reaction (ORR) on the model Ag(111) surface in alkaline solution by using density functional theory (DFT) and Kinetic Monte Carlo (KMC) simulations, in which multiple pathways involving either 2 e - or 4 e - mechanisms were included. The theoretical modelling presented here is able to reproduce the experimentally measured polarization curves in both low and high potential regions. An electrochemical 4 e - network including both a chemisorbed water (*H 2O)-mediated 4 e - associative pathway and the conventional associative pathway was identified to dominate the ORR mechanism. Onmore » the basis of the mechanistic understanding derived from these calculations, the ways to promote the ORR on Ag(111) were provided, including facilitating *OH removal, **O 2 reduction by *H 2O, and suppressing **O 2 desorption. Finally, the origin of the different ORR behaviors of Ag(111) and Pt(111) was also discussed in detail.« less

  20. Learning reduced kinetic Monte Carlo models of complex chemistry from molecular dynamics.

    PubMed

    Yang, Qian; Sing-Long, Carlos A; Reed, Evan J

    2017-08-01

    We propose a novel statistical learning framework for automatically and efficiently building reduced kinetic Monte Carlo (KMC) models of large-scale elementary reaction networks from data generated by a single or few molecular dynamics simulations (MD). Existing approaches for identifying species and reactions from molecular dynamics typically use bond length and duration criteria, where bond duration is a fixed parameter motivated by an understanding of bond vibrational frequencies. In contrast, we show that for highly reactive systems, bond duration should be a model parameter that is chosen to maximize the predictive power of the resulting statistical model. We demonstrate our method on a high temperature, high pressure system of reacting liquid methane, and show that the learned KMC model is able to extrapolate more than an order of magnitude in time for key molecules. Additionally, our KMC model of elementary reactions enables us to isolate the most important set of reactions governing the behavior of key molecules found in the MD simulation. We develop a new data-driven algorithm to reduce the chemical reaction network which can be solved either as an integer program or efficiently using L1 regularization, and compare our results with simple count-based reduction. For our liquid methane system, we discover that rare reactions do not play a significant role in the system, and find that less than 7% of the approximately 2000 reactions observed from molecular dynamics are necessary to reproduce the molecular concentration over time of methane. The framework described in this work paves the way towards a genomic approach to studying complex chemical systems, where expensive MD simulation data can be reused to contribute to an increasingly large and accurate genome of elementary reactions and rates.

  1. Kinetic Monte Carlo Study of Li Intercalation in LiFePO4.

    PubMed

    Xiao, Penghao; Henkelman, Graeme

    2018-01-23

    Even as a commercial cathode material, LiFePO 4 remains of tremendous research interest for understanding Li intercalation dynamics. The partially lithiated material spontaneously separates into Li-poor and Li-rich phases at equilibrium. Phase segregation is a surprising property of LiFePO 4 given its high measured rate capability. Previous theoretical studies, aiming to describe Li intercalation in LiFePO 4 , include both atomic-scale density functional theory (DFT) calculations of static Li distributions and entire-particle-scale phase field models, based upon empirical parameters, studying the dynamics of the phase separation. Little effort has been made to bridge the gap between these two scales. In this work, DFT calculations are used to fit a cluster expansion for the basis of kinetic Monte Carlo calculations, which enables long time scale simulations with accurate atomic interactions. This atomistic model shows how the phases evolve in Li x FePO 4 without parameters from experiments. Our simulations reveal that an ordered Li 0.5 FePO4 phase with alternating Li-rich and Li-poor planes along the ac direction forms between the LiFePO 4 and FePO 4 phases, which is consistent with recent X-ray diffraction experiments showing peaks associated with an intermediate-Li phase. The calculations also help to explain a recent puzzling experiment showing that LiFePO 4 particles with high aspect ratios that are narrower along the [100] direction, perpendicular to the [010] Li diffusion channels, actually have better rate capabilities. Our calculations show that lateral surfaces parallel to the Li diffusion channels, as well as other preexisting sites that bind Li weakly, are important for phase nucleation and rapid cycling performance.

  2. Learning reduced kinetic Monte Carlo models of complex chemistry from molecular dynamics

    PubMed Central

    Sing-Long, Carlos A.

    2017-01-01

    We propose a novel statistical learning framework for automatically and efficiently building reduced kinetic Monte Carlo (KMC) models of large-scale elementary reaction networks from data generated by a single or few molecular dynamics simulations (MD). Existing approaches for identifying species and reactions from molecular dynamics typically use bond length and duration criteria, where bond duration is a fixed parameter motivated by an understanding of bond vibrational frequencies. In contrast, we show that for highly reactive systems, bond duration should be a model parameter that is chosen to maximize the predictive power of the resulting statistical model. We demonstrate our method on a high temperature, high pressure system of reacting liquid methane, and show that the learned KMC model is able to extrapolate more than an order of magnitude in time for key molecules. Additionally, our KMC model of elementary reactions enables us to isolate the most important set of reactions governing the behavior of key molecules found in the MD simulation. We develop a new data-driven algorithm to reduce the chemical reaction network which can be solved either as an integer program or efficiently using L1 regularization, and compare our results with simple count-based reduction. For our liquid methane system, we discover that rare reactions do not play a significant role in the system, and find that less than 7% of the approximately 2000 reactions observed from molecular dynamics are necessary to reproduce the molecular concentration over time of methane. The framework described in this work paves the way towards a genomic approach to studying complex chemical systems, where expensive MD simulation data can be reused to contribute to an increasingly large and accurate genome of elementary reactions and rates. PMID:28989618

  3. Learning reduced kinetic Monte Carlo models of complex chemistry from molecular dynamics

    DOE PAGES

    Yang, Qian; Sing-Long, Carlos A.; Reed, Evan J.

    2017-06-19

    Here, we propose a novel statistical learning framework for automatically and efficiently building reduced kinetic Monte Carlo (KMC) models of large-scale elementary reaction networks from data generated by a single or few molecular dynamics simulations (MD). Existing approaches for identifying species and reactions from molecular dynamics typically use bond length and duration criteria, where bond duration is a fixed parameter motivated by an understanding of bond vibrational frequencies. Conversely, we show that for highly reactive systems, bond duration should be a model parameter that is chosen to maximize the predictive power of the resulting statistical model. We demonstrate our methodmore » on a high temperature, high pressure system of reacting liquid methane, and show that the learned KMC model is able to extrapolate more than an order of magnitude in time for key molecules. Additionally, our KMC model of elementary reactions enables us to isolate the most important set of reactions governing the behavior of key molecules found in the MD simulation. We develop a new data-driven algorithm to reduce the chemical reaction network which can be solved either as an integer program or efficiently using L1 regularization, and compare our results with simple count-based reduction. For our liquid methane system, we discover that rare reactions do not play a significant role in the system, and find that less than 7% of the approximately 2000 reactions observed from molecular dynamics are necessary to reproduce the molecular concentration over time of methane. Furthermore, we describe a framework in this work that paves the way towards a genomic approach to studying complex chemical systems, where expensive MD simulation data can be reused to contribute to an increasingly large and accurate genome of elementary reactions and rates.« less

  4. Stochastic kinetic mean field model

    NASA Astrophysics Data System (ADS)

    Erdélyi, Zoltán; Pasichnyy, Mykola; Bezpalchuk, Volodymyr; Tomán, János J.; Gajdics, Bence; Gusak, Andriy M.

    2016-07-01

    This paper introduces a new model for calculating the change in time of three-dimensional atomic configurations. The model is based on the kinetic mean field (KMF) approach, however we have transformed that model into a stochastic approach by introducing dynamic Langevin noise. The result is a stochastic kinetic mean field model (SKMF) which produces results similar to the lattice kinetic Monte Carlo (KMC). SKMF is, however, far more cost-effective and easier to implement the algorithm (open source program code is provided on http://skmf.eu website). We will show that the result of one SKMF run may correspond to the average of several KMC runs. The number of KMC runs is inversely proportional to the amplitude square of the noise in SKMF. This makes SKMF an ideal tool also for statistical purposes.

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

    NASA Astrophysics Data System (ADS)

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

    2017-10-01

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

  6. Montelukast photodegradation: elucidation of Ф-order kinetics, determination of quantum yields and application to actinometry.

    PubMed

    Maafi, Mounir; Maafi, Wassila

    2014-08-25

    A recently developed Ф-order semi-emperical integrated rate-law for photoreversible AB(2Ф) reactions has been successfully applied to investigate Montelukast sodium (Monte) photodegradation kinetics in ethanol. The model equations also served to propose a new stepwise kinetic elucidation method valid for any AB(2Ф) system and its application to the determination of Monte's forward (Ф(λ(irr))(A-->B)) and reverse (Ф(λ(irr))(B-->A)) quantum yields at various irradiation wavelengths. It has been found that Ф(λ(irr))(A-->B) undergoes a 15-fold increase with wavelength between 220 and 360 nm, with the spectral section 250-360 nm representing Monte effective photodegradation causative range. The reverse quantum yield values were generally between 12 and 54% lower than those recorded for Ф(λ(irr))(A-->B), with the trans-isomer (Monte) converting almost completely to its cis-counterpart at high irradiation wavelengths. Furthermore, the potential use of Monte as an actinometer has been investigated, and an actinometric method was proposed. This study demonstrated the usefulness of Monte for monochromatic light actinometry for the dynamic range 258-380 nm. Copyright © 2014 Elsevier B.V. All rights reserved.

  7. Space Object Collision Probability via Monte Carlo on the Graphics Processing Unit

    NASA Astrophysics Data System (ADS)

    Vittaldev, Vivek; Russell, Ryan P.

    2017-09-01

    Fast and accurate collision probability computations are essential for protecting space assets. Monte Carlo (MC) simulation is the most accurate but computationally intensive method. A Graphics Processing Unit (GPU) is used to parallelize the computation and reduce the overall runtime. Using MC techniques to compute the collision probability is common in literature as the benchmark. An optimized implementation on the GPU, however, is a challenging problem and is the main focus of the current work. The MC simulation takes samples from the uncertainty distributions of the Resident Space Objects (RSOs) at any time during a time window of interest and outputs the separations at closest approach. Therefore, any uncertainty propagation method may be used and the collision probability is automatically computed as a function of RSO collision radii. Integration using a fixed time step and a quartic interpolation after every Runge Kutta step ensures that no close approaches are missed. Two orders of magnitude speedups over a serial CPU implementation are shown, and speedups improve moderately with higher fidelity dynamics. The tool makes the MC approach tractable on a single workstation, and can be used as a final product, or for verifying surrogate and analytical collision probability methods.

  8. Kinetic Monte Carlo modeling of the efficiency roll-off in a multilayer white organic light-emitting device

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

    Mesta, M.; Coehoorn, R.; Bobbert, P. A.

    2016-03-28

    Triplet-triplet annihilation (TTA) and triplet-polaron quenching (TPQ) in organic light-emitting devices (OLEDs) lead to a roll-off of the internal quantum efficiency (IQE) with increasing current density J. We employ a kinetic Monte Carlo modeling study to analyze the measured IQE and color balance as a function of J in a multilayer hybrid white OLED that combines fluorescent blue with phosphorescent green and red emission. We investigate two models for TTA and TPQ involving the phosphorescent green and red emitters: short-range nearest-neighbor quenching and long-range Förster-type quenching. Short-range quenching predicts roll-off to occur at much higher J than measured. Taking long-rangemore » quenching with Förster radii for TTA and TPQ equal to twice the Förster radii for exciton transfer leads to a fair description of the measured IQE-J curve, with the major contribution to the roll-off coming from TPQ. The measured decrease of the ratio of phosphorescent to fluorescent component of the emitted light with increasing J is correctly predicted. A proper description of the J-dependence of the ratio of red and green phosphorescent emission needs further model refinements.« less

  9. Kinetic Monte Carlo modeling of the efficiency roll-off in a multilayer white organic light-emitting device

    NASA Astrophysics Data System (ADS)

    Mesta, M.; van Eersel, H.; Coehoorn, R.; Bobbert, P. A.

    2016-03-01

    Triplet-triplet annihilation (TTA) and triplet-polaron quenching (TPQ) in organic light-emitting devices (OLEDs) lead to a roll-off of the internal quantum efficiency (IQE) with increasing current density J. We employ a kinetic Monte Carlo modeling study to analyze the measured IQE and color balance as a function of J in a multilayer hybrid white OLED that combines fluorescent blue with phosphorescent green and red emission. We investigate two models for TTA and TPQ involving the phosphorescent green and red emitters: short-range nearest-neighbor quenching and long-range Förster-type quenching. Short-range quenching predicts roll-off to occur at much higher J than measured. Taking long-range quenching with Förster radii for TTA and TPQ equal to twice the Förster radii for exciton transfer leads to a fair description of the measured IQE-J curve, with the major contribution to the roll-off coming from TPQ. The measured decrease of the ratio of phosphorescent to fluorescent component of the emitted light with increasing J is correctly predicted. A proper description of the J-dependence of the ratio of red and green phosphorescent emission needs further model refinements.

  10. Centrality measures highlight proton traps and access points to proton highways in kinetic Monte Carlo trajectories

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

    Krueger, Rachel A.; Haibach, Frederick G.; Fry, Dana L.

    2015-04-21

    A centrality measure based on the time of first returns rather than the number of steps is developed and applied to finding proton traps and access points to proton highways in the doped perovskite oxides: AZr{sub 0.875}D{sub 0.125}O{sub 3}, where A is Ba or Sr and the dopant D is Y or Al. The high centrality region near the dopant is wider in the SrZrO{sub 3} systems than the BaZrO{sub 3} systems. In the aluminum-doped systems, a region of intermediate centrality (secondary region) is found in a plane away from the dopant. Kinetic Monte Carlo (kMC) trajectories show that thismore » secondary region is an entry to fast conduction planes in the aluminum-doped systems in contrast to the highest centrality area near the dopant trap. The yttrium-doped systems do not show this secondary region because the fast conduction routes are in the same plane as the dopant and hence already in the high centrality trapped area. This centrality measure complements kMC by highlighting key areas in trajectories. The limiting activation barriers found via kMC are in very good agreement with experiments and related to the barriers to escape dopant traps.« less

  11. Ab initio and kinetic Monte Carlo study of lithium diffusion in LiSi, Li12Si7, Li13Si5 and Li15Si4

    NASA Astrophysics Data System (ADS)

    Moon, Janghyuk; Lee, Byeongchan; Cho, Maenghyo; Cho, Kyeongjae

    2016-10-01

    The kinetics of lithium atoms in various Li-Si binary compounds are investigated using density functional theory calculations and kinetic Monte Carlo calculations. The values of the Li migration energy barriers are identified by NEB calculations with vacancy-mediated, interstitial and exchange migration mechanisms in crystalline LiSi, Li12Si7, Li13Si4, and Li15Si4. A comparison of these NEB results shows that the vacancy-mediated Li migration is identified as the dominant diffusion mechanisms in Li-Si compounds. The diffusion coefficients of Li in Li-Si compounds at room temperature are determined by KMC simulation. From the KMC results, the recalculated migration energy barriers in LiSi, Li12Si7, Li13Si4, and Li15Si4 correspond to 0.306, 0.301, 0.367 and 0.320 eV, respectively. Compared to the Li migration energy barrier of 0.6 eV in crystalline Si, the drastic reduction in the Li migration energy barriers in the lithiated silicon indicates that the initial lithiation of the Si anode is the rate-limiting step. Furthermore, it is also found that Si migration is possible in Li-rich configurations. On the basis of these findings, the underlying mechanisms of kinetics on the atomic scale details are elucidated.

  12. Sensory Agreement Guides Kinetic Energy Optimization of Arm Movements during Object Manipulation.

    PubMed

    Farshchiansadegh, Ali; Melendez-Calderon, Alejandro; Ranganathan, Rajiv; Murphey, Todd D; Mussa-Ivaldi, Ferdinando A

    2016-04-01

    The laws of physics establish the energetic efficiency of our movements. In some cases, like locomotion, the mechanics of the body dominate in determining the energetically optimal course of action. In other tasks, such as manipulation, energetic costs depend critically upon the variable properties of objects in the environment. Can the brain identify and follow energy-optimal motions when these motions require moving along unfamiliar trajectories? What feedback information is required for such optimal behavior to occur? To answer these questions, we asked participants to move their dominant hand between different positions while holding a virtual mechanical system with complex dynamics (a planar double pendulum). In this task, trajectories of minimum kinetic energy were along curvilinear paths. Our findings demonstrate that participants were capable of finding the energy-optimal paths, but only when provided with veridical visual and haptic information pertaining to the object, lacking which the trajectories were executed along rectilinear paths.

  13. Density controls the kinetic stability of ultrastable glasses

    NASA Astrophysics Data System (ADS)

    Fullerton, Christopher J.; Berthier, Ludovic

    2017-08-01

    We use a swap Monte Carlo algorithm to numerically prepare bulk glasses with kinetic stability comparable to that of glass films produced experimentally by physical vapor deposition. By melting these systems into the liquid state, we show that some of our glasses retain their amorphous structures longer than 105 times the equilibrium structural relaxation time. This “exceptional” kinetic stability cannot be achieved for bulk glasses produced by slow cooling. We perform simulations at both constant volume and constant pressure to demonstrate that the density mismatch between the ultrastable glass and the equilibrium liquid accounts for a major part of the observed kinetic stability.

  14. Kinetic theory for dilute cohesive granular gases with a square well potential.

    PubMed

    Takada, Satoshi; Saitoh, Kuniyasu; Hayakawa, Hisao

    2016-07-01

    We develop the kinetic theory of dilute cohesive granular gases in which the attractive part is described by a square well potential. We derive the hydrodynamic equations from the kinetic theory with the microscopic expressions for the dissipation rate and the transport coefficients. We check the validity of our theory by performing the direct simulation Monte Carlo.

  15. Kinetic Monte Carlo simulations of GaN homoepitaxy on c- and m-plane surfaces

    DOE PAGES

    Xu, Dongwei; Zapol, Peter; Stephenson, G. Brian; ...

    2017-04-12

    The surface orientation can have profound effects on the atomic-scale processes of crystal growth and is essential to such technologies as GaN-based light-emitting diodes and high-power electronics. We investigate the dependence of homoepitaxial growth mechanisms on the surface orientation of a hexagonal crystal using kinetic Monte Carlo simulations. To model GaN metal-organic vapor phase epitaxy, in which N species are supplied in excess, only Ga atoms on a hexagonal close-packed (HCP) lattice are considered. The results are thus potentially applicable to any HCP material. Growth behaviors on c-plane (0001) and m-plane (011¯0) surfaces are compared. We present a reciprocal spacemore » analysis of the surface morphology, which allows extraction of growth mode boundaries and direct comparison with surface X-ray diffraction experiments. For each orientation, we map the boundaries between 3-dimensional, layer-by-layer, and step flow growth modes as a function of temperature and growth rate. Two models for surface diffusion are used, which produce different effective Ehrlich-Schwoebel step-edge barriers and different adatom diffusion anisotropies on m-plane surfaces. Simulation results in agreement with observed GaN island morphologies and growth mode boundaries are obtained. These indicate that anisotropy of step edge energy, rather than adatom diffusion, is responsible for the elongated islands observed on m-plane surfaces. As a result, island nucleation spacing obeys a power-law dependence on growth rate, with exponents of –0.24 and –0.29 for the m- and c-plane, respectively.« less

  16. Kinetic Monte Carlo simulations of GaN homoepitaxy on c- and m-plane surfaces

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

    Xu, Dongwei; Zapol, Peter; Stephenson, G. Brian

    The surface orientation can have profound effects on the atomic-scale processes of crystal growth and is essential to such technologies as GaN-based light-emitting diodes and high-power electronics. We investigate the dependence of homoepitaxial growth mechanisms on the surface orientation of a hexagonal crystal using kinetic Monte Carlo simulations. To model GaN metal-organic vapor phase epitaxy, in which N species are supplied in excess, only Ga atoms on a hexagonal close-packed (HCP) lattice are considered. The results are thus potentially applicable to any HCP material. Growth behaviors on c-plane (0001) and m-plane (011¯0) surfaces are compared. We present a reciprocal spacemore » analysis of the surface morphology, which allows extraction of growth mode boundaries and direct comparison with surface X-ray diffraction experiments. For each orientation, we map the boundaries between 3-dimensional, layer-by-layer, and step flow growth modes as a function of temperature and growth rate. Two models for surface diffusion are used, which produce different effective Ehrlich-Schwoebel step-edge barriers and different adatom diffusion anisotropies on m-plane surfaces. Simulation results in agreement with observed GaN island morphologies and growth mode boundaries are obtained. These indicate that anisotropy of step edge energy, rather than adatom diffusion, is responsible for the elongated islands observed on m-plane surfaces. As a result, island nucleation spacing obeys a power-law dependence on growth rate, with exponents of –0.24 and –0.29 for the m- and c-plane, respectively.« less

  17. Reliability investigation of high-k/metal gate in nMOSFETs by three-dimensional kinetic Monte-Carlo simulation with multiple trap interactions

    NASA Astrophysics Data System (ADS)

    Li, Yun; Jiang, Hai; Lun, Zhiyuan; Wang, Yijiao; Huang, Peng; Hao, Hao; Du, Gang; Zhang, Xing; Liu, Xiaoyan

    2016-04-01

    Degradation behaviors in the high-k/metal gate stacks of nMOSFETs are investigated by three-dimensional (3D) kinetic Monte-Carlo (KMC) simulation with multiple trap coupling. Novel microscopic mechanisms are simultaneously considered in a compound system: (1) trapping/detrapping from/to substrate/gate; (2) trapping/detrapping to other traps; (3) trap generation and recombination. Interacting traps can contribute to random telegraph noise (RTN), bias temperature instability (BTI), and trap-assisted tunneling (TAT). Simulation results show that trap interaction induces higher probability and greater complexity in trapping/detrapping processes and greatly affects the characteristics of RTN and BTI. Different types of trap distribution cause largely different behaviors of RTN, BTI, and TAT. TAT currents caused by multiple trap coupling are sensitive to the gate voltage. Moreover, trap generation and recombination have great effects on the degradation of HfO2-based nMOSFETs under a large stress.

  18. Dynamic Monte Carlo description of thermal desorption processes

    NASA Astrophysics Data System (ADS)

    Weinketz, Sieghard

    1994-07-01

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

  19. On-the-Fly Kinetic Monte Carlo Simulation of Aqueous Phase Advanced Oxidation Processes.

    PubMed

    Guo, Xin; Minakata, Daisuke; Crittenden, John

    2015-08-04

    We have developed an on-the-fly kinetic Monte Carlo (KMC) model to predict the degradation mechanisms and fates of intermediates and byproducts that are produced during aqueous-phase advanced oxidation processes (AOPs). The on-the-fly KMC model is composed of a reaction pathway generator, a reaction rate constant estimator, a mechanistic reduction module, and a KMC solver. The novelty of this work is that we develop the pathway as we march forward in time rather than developing the pathway before we use the KMC method to solve the equations. As a result, we have fewer reactions to consider, and we have greater computational efficiency. We have verified this on-the-fly KMC model for the degradation of polyacrylamide (PAM) using UV light and titanium dioxide (i.e., UV/TiO2). Using the on-the-fly KMC model, we were able to predict the time-dependent profiles of the average molecular weight for PAM. The model provided detailed and quantitative insights into the time evolution of the molecular weight distribution and reaction mechanism. We also verified our on-the-fly KMC model for the destruction of (1) acetone, (2) trichloroethylene (TCE), and (3) polyethylene glycol (PEG) for the ultraviolet light and hydrogen peroxide AOP. We demonstrated that the on-the-fly KMC model can achieve the same accuracy as the computer-based first-principles KMC (CF-KMC) model, which has already been validated in our earlier work. The on-the-fly KMC is particularly suitable for molecules with large molecular weights (e.g., polymers) because the degradation mechanisms for large molecules can result in hundreds of thousands to even millions of reactions. The ordinary differential equations (ODEs) that describe the degradation pathways cannot be solved using traditional numerical methods, but the KMC can solve these equations.

  20. A kinetic Monte Carlo model with improved charge injection model for the photocurrent characteristics of organic solar cells

    NASA Astrophysics Data System (ADS)

    Kipp, Dylan; Ganesan, Venkat

    2013-06-01

    We develop a kinetic Monte Carlo model for photocurrent generation in organic solar cells that demonstrates improved agreement with experimental illuminated and dark current-voltage curves. In our model, we introduce a charge injection rate prefactor to correct for the electrode grid-size and electrode charge density biases apparent in the coarse-grained approximation of the electrode as a grid of single occupancy, charge-injecting reservoirs. We use the charge injection rate prefactor to control the portion of dark current attributed to each of four kinds of charge injection. By shifting the dark current between electrode-polymer pairs, we align the injection timescales and expand the applicability of the method to accommodate ohmic energy barriers. We consider the device characteristics of the ITO/PEDOT/PSS:PPDI:PBTT:Al system and demonstrate the manner in which our model captures the device charge densities unique to systems with small injection energy barriers. To elucidate the defining characteristics of our model, we first demonstrate the manner in which charge accumulation and band bending affect the shape and placement of the various current-voltage regimes. We then discuss the influence of various model parameters upon the current-voltage characteristics.

  1. Assessment of mean-field microkinetic models for CO methanation on stepped metal surfaces using accelerated kinetic Monte Carlo

    NASA Astrophysics Data System (ADS)

    Andersen, Mie; Plaisance, Craig P.; Reuter, Karsten

    2017-10-01

    First-principles screening studies aimed at predicting the catalytic activity of transition metal (TM) catalysts have traditionally been based on mean-field (MF) microkinetic models, which neglect the effect of spatial correlations in the adsorbate layer. Here we critically assess the accuracy of such models for the specific case of CO methanation over stepped metals by comparing to spatially resolved kinetic Monte Carlo (kMC) simulations. We find that the typical low diffusion barriers offered by metal surfaces can be significantly increased at step sites, which results in persisting correlations in the adsorbate layer. As a consequence, MF models may overestimate the catalytic activity of TM catalysts by several orders of magnitude. The potential higher accuracy of kMC models comes at a higher computational cost, which can be especially challenging for surface reactions on metals due to a large disparity in the time scales of different processes. In order to overcome this issue, we implement and test a recently developed algorithm for achieving temporal acceleration of kMC simulations. While the algorithm overall performs quite well, we identify some challenging cases which may lead to a breakdown of acceleration algorithms and discuss possible directions for future algorithm development.

  2. One-dimensional model of interacting-step fluctuations on vicinal surfaces: Analytical formulas and kinetic Monte Carlo simulations

    NASA Astrophysics Data System (ADS)

    Patrone, Paul N.; Einstein, T. L.; Margetis, Dionisios

    2010-12-01

    We study analytically and numerically a one-dimensional model of interacting line defects (steps) fluctuating on a vicinal crystal. Our goal is to formulate and validate analytical techniques for approximately solving systems of coupled nonlinear stochastic differential equations (SDEs) governing fluctuations in surface motion. In our analytical approach, the starting point is the Burton-Cabrera-Frank (BCF) model by which step motion is driven by diffusion of adsorbed atoms on terraces and atom attachment-detachment at steps. The step energy accounts for entropic and nearest-neighbor elastic-dipole interactions. By including Gaussian white noise to the equations of motion for terrace widths, we formulate large systems of SDEs under different choices of diffusion coefficients for the noise. We simplify this description via (i) perturbation theory and linearization of the step interactions and, alternatively, (ii) a mean-field (MF) approximation whereby widths of adjacent terraces are replaced by a self-consistent field but nonlinearities in step interactions are retained. We derive simplified formulas for the time-dependent terrace-width distribution (TWD) and its steady-state limit. Our MF analytical predictions for the TWD compare favorably with kinetic Monte Carlo simulations under the addition of a suitably conservative white noise in the BCF equations.

  3. Non-Arrhenius temperature dependence of the island density of one-dimensional Al chains on Si(100): A kinetic Monte Carlo study

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

    Albia, Jason R.; Albao, Marvin A., E-mail: maalbao@uplb.edu.ph

    Classical nucleation theory predicts that the evolution of mean island density with temperature during growth in one-dimensional systems obeys the Arrhenius relation. In this study, kinetic Monte Carlo simulations of a suitable atomistic lattice-gas model were performed to investigate the experimentally observed non-Arrhenius scaling behavior of island density in the case of one-dimensional Al islands grown on Si(100). Previously, it was proposed that adatom desorption resulted in a transition temperature signaling the departure from classical predictions. Here, the authors demonstrate that desorption above the transition temperature is not possible. Instead, the authors posit that the existence of a transition temperaturemore » is due to a combination of factors such as reversibility of island growth, presence of C-defects, adatom diffusion rates, as well as detachment rates at island ends. In addition, the authors show that the anomalous non-Arrhenius behavior vanishes when adatom binds irreversibly with C-defects as observed in In on Si(100) studies.« less

  4. Mechanism of CO 2 hydrogenation over Cu/ZrO 2(2̅12) interface from first-principles kinetics Monte Carlo simulations

    NASA Astrophysics Data System (ADS)

    Hong, Qi-Jun; Liu, Zhi-Pan

    2010-10-01

    It has been a goal consistently pursued by chemists to understand and control the catalytic process over composite materials. In order to provide deeper insight on complex interfacial catalysis at the experimental conditions, we performed an extensive analysis on CO 2 hydrogenation over a Cu/ZrO 2 model catalyst by employing density functional theory (DFT) calculations and kinetic Monte Carlo (kMC) simulations based on the continuous stirred tank model. The free energy profiles are determined for the reaction at the oxygen-rich Cu/m-ZrO 2 (2̅12) interface, where all interfacial Zr are six-coordinated since the interface accumulates oxidative species at the reaction conditions. We show that not only methanol but also CO are produced through the formate pathway dominantly, whilst the reverse-water-gas-shift (RWGS) channel has only a minor contribution. H 2CO is a key intermediate species in the reaction pathway, the hydrogenation of which dictates the high temperature of CO 2 hydrogenation. The kinetics simulation shows that the CO 2 conversion is 1.20%, the selectivity towards methanol is 68% at 500 K and the activation energies for methanol and CO formation are 0.79 and 1.79 eV, respectively. The secondary reactions due to the product readsorption lower the overall turnover frequency (TOF) but increase the selectivity towards methanol by 16%. We also show that kMC is a more reliable tool for simulating heterogeneous catalytic processes compared to the microkinetics approach.

  5. Two-dimensional implosion simulations with a kinetic particle code [2D implosion simulations with a kinetic particle code

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

    Sagert, Irina; Even, Wesley Paul; Strother, Terrance Timothy

    Here, we perform two-dimensional implosion simulations using a Monte Carlo kinetic particle code. The application of a kinetic transport code is motivated, in part, by the occurrence of nonequilibrium effects in inertial confinement fusion capsule implosions, which cannot be fully captured by hydrodynamic simulations. Kinetic methods, on the other hand, are able to describe both continuum and rarefied flows. We perform simple two-dimensional disk implosion simulations using one-particle species and compare the results to simulations with the hydrodynamics code rage. The impact of the particle mean free path on the implosion is also explored. In a second study, we focusmore » on the formation of fluid instabilities from induced perturbations. We find good agreement with hydrodynamic studies regarding the location of the shock and the implosion dynamics. Differences are found in the evolution of fluid instabilities, originating from the higher resolution of rage and statistical noise in the kinetic studies.« less

  6. Two-dimensional implosion simulations with a kinetic particle code [2D implosion simulations with a kinetic particle code

    DOE PAGES

    Sagert, Irina; Even, Wesley Paul; Strother, Terrance Timothy

    2017-05-17

    Here, we perform two-dimensional implosion simulations using a Monte Carlo kinetic particle code. The application of a kinetic transport code is motivated, in part, by the occurrence of nonequilibrium effects in inertial confinement fusion capsule implosions, which cannot be fully captured by hydrodynamic simulations. Kinetic methods, on the other hand, are able to describe both continuum and rarefied flows. We perform simple two-dimensional disk implosion simulations using one-particle species and compare the results to simulations with the hydrodynamics code rage. The impact of the particle mean free path on the implosion is also explored. In a second study, we focusmore » on the formation of fluid instabilities from induced perturbations. We find good agreement with hydrodynamic studies regarding the location of the shock and the implosion dynamics. Differences are found in the evolution of fluid instabilities, originating from the higher resolution of rage and statistical noise in the kinetic studies.« less

  7. Monte Carlo simulations in X-ray imaging

    NASA Astrophysics Data System (ADS)

    Giersch, Jürgen; Durst, Jürgen

    2008-06-01

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

  8. KMCLib: A general framework for lattice kinetic Monte Carlo (KMC) simulations

    NASA Astrophysics Data System (ADS)

    Leetmaa, Mikael; Skorodumova, Natalia V.

    2014-09-01

    KMCLib is a general framework for lattice kinetic Monte Carlo (KMC) simulations. The program can handle simulations of the diffusion and reaction of millions of particles in one, two, or three dimensions, and is designed to be easily extended and customized by the user to allow for the development of complex custom KMC models for specific systems without having to modify the core functionality of the program. Analysis modules and on-the-fly elementary step diffusion rate calculations can be implemented as plugins following a well-defined API. The plugin modules are loosely coupled to the core KMCLib program via the Python scripting language. KMCLib is written as a Python module with a backend C++ library. After initial compilation of the backend library KMCLib is used as a Python module; input to the program is given as a Python script executed using a standard Python interpreter. We give a detailed description of the features and implementation of the code and demonstrate its scaling behavior and parallel performance with a simple one-dimensional A-B-C lattice KMC model and a more complex three-dimensional lattice KMC model of oxygen-vacancy diffusion in a fluorite structured metal oxide. KMCLib can keep track of individual particle movements and includes tools for mean square displacement analysis, and is therefore particularly well suited for studying diffusion processes at surfaces and in solids. Catalogue identifier: AESZ_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AESZ_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public License, version 3 No. of lines in distributed program, including test data, etc.: 49 064 No. of bytes in distributed program, including test data, etc.: 1 575 172 Distribution format: tar.gz Programming language: Python and C++. Computer: Any computer that can run a C++ compiler and a Python interpreter. Operating system: Tested on Ubuntu 12

  9. An in-depth description of bipolar resistive switching in Cu/HfOx/Pt devices, a 3D kinetic Monte Carlo simulation approach

    NASA Astrophysics Data System (ADS)

    Aldana, S.; Roldán, J. B.; García-Fernández, P.; Suñe, J.; Romero-Zaliz, R.; Jiménez-Molinos, F.; Long, S.; Gómez-Campos, F.; Liu, M.

    2018-04-01

    A simulation tool based on a 3D kinetic Monte Carlo algorithm has been employed to analyse bipolar conductive bridge RAMs fabricated with Cu/HfOx/Pt stacks. Resistive switching mechanisms are described accounting for the electric field and temperature distributions within the dielectric. The formation and destruction of conductive filaments (CFs) are analysed taking into consideration redox reactions and the joint action of metal ion thermal diffusion and electric field induced drift. Filamentary conduction is considered when different percolation paths are formed in addition to other conventional transport mechanisms in dielectrics. The simulator was tuned by using the experimental data for Cu/HfOx/Pt bipolar devices that were fabricated. Our simulation tool allows for the study of different experimental results, in particular, the current variations due to the electric field changes between the filament tip and the electrode in the High Resistance State. In addition, the density of metallic atoms within the CF can also be characterized along with the corresponding CF resistance description.

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

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

    Ogawa, K.; Maeda, S.

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

  11. In-silico analysis on biofabricating vascular networks using kinetic Monte Carlo simulations.

    PubMed

    Sun, Yi; Yang, Xiaofeng; Wang, Qi

    2014-03-01

    We present a computational modeling approach to study the fusion of multicellular aggregate systems in a novel scaffold-less biofabrication process, known as 'bioprinting'. In this novel technology, live multicellular aggregates are used as fundamental building blocks to make tissues or organs (collectively known as the bio-constructs,) via the layer-by-layer deposition technique or other methods; the printed bio-constructs embedded in maturogens, consisting of nutrient-rich bio-compatible hydrogels, are then placed in bioreactors to undergo the cellular aggregate fusion process to form the desired functional bio-structures. Our approach reported here is an agent-based modeling method, which uses the kinetic Monte Carlo (KMC) algorithm to evolve the cellular system on a lattice. In this method, the cells and the hydrogel media, in which cells are embedded, are coarse-grained to material's points on a three-dimensional (3D) lattice, where the cell-cell and cell-medium interactions are quantified by adhesion and cohesion energies. In a multicellular aggregate system with a fixed number of cells and fixed amount of hydrogel media, where the effect of cell differentiation, proliferation and death are tactically neglected, the interaction energy is primarily dictated by the interfacial energy between cell and cell as well as between cell and medium particles on the lattice, respectively, based on the differential adhesion hypothesis. By using the transition state theory to track the time evolution of the multicellular system while minimizing the interfacial energy, KMC is shown to be an efficient time-dependent simulation tool to study the evolution of the multicellular aggregate system. In this study, numerical experiments are presented to simulate fusion and cell sorting during the biofabrication process of vascular networks, in which the bio-constructs are fabricated via engineering designs. The results predict the feasibility of fabricating the vascular structures

  12. OBJECT KINETIC MONTE CARLO SIMULATIONS OF RADIATION DAMAGE IN BULK TUNGSTEN

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

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

    2015-09-22

    We used our recently developed lattice based OKMC code; KSOME [1] to carryout simulations of radiation damage in bulk W. We study the effect of dimensionality of self interstitial atom (SIA) diffusion i.e. 1D versus 3D on the defect accumulation during irradiation with a primary knock-on atom (PKA) energy of 100 keV at 300 K for the dose rates of 10-5 and 10-6 dpa/s. As expected 3D SIA diffusion significantly reduces damage accumulation due to increased probability of recombination events. In addition, dose rate, over the limited range examined here, appears to have no effect in both cases of SIAmore » diffusion.« less

  13. Equivalence principle and bound kinetic energy.

    PubMed

    Hohensee, Michael A; Müller, Holger; Wiringa, R B

    2013-10-11

    We consider the role of the internal kinetic energy of bound systems of matter in tests of the Einstein equivalence principle. Using the gravitational sector of the standard model extension, we show that stringent limits on equivalence principle violations in antimatter can be indirectly obtained from tests using bound systems of normal matter. We estimate the bound kinetic energy of nucleons in a range of light atomic species using Green's function Monte Carlo calculations, and for heavier species using a Woods-Saxon model. We survey the sensitivities of existing and planned experimental tests of the equivalence principle, and report new constraints at the level of between a few parts in 10(6) and parts in 10(8) on violations of the equivalence principle for matter and antimatter.

  14. Subtle Monte Carlo Updates in Dense Molecular Systems.

    PubMed

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

    2012-02-14

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

  15. Monte Carlo technique for very large ising models

    NASA Astrophysics Data System (ADS)

    Kalle, C.; Winkelmann, V.

    1982-08-01

    Rebbi's multispin coding technique is improved and applied to the kinetic Ising model with size 600*600*600. We give the central part of our computer program (for a CDC Cyber 76), which will be helpful also in a simulation of smaller systems, and describe the other tricks necessary to go to large lattices. The magnetization M at T=1.4* T c is found to decay asymptotically as exp(-t/2.90) if t is measured in Monte Carlo steps per spin, and M( t = 0) = 1 initially.

  16. Are hot charge transfer states the primary cause of efficient free-charge generation in polymer:fullerene organic photovoltaic devices? A kinetic Monte Carlo study.

    PubMed

    Jones, Matthew L; Dyer, Reesha; Clarke, Nigel; Groves, Chris

    2014-10-14

    Kinetic Monte Carlo simulations are used to examine the effect of high-energy, 'hot' delocalised charge transfer (HCT) states for donor:acceptor and mixed:aggregate blends, the latter relating to polymer:fullerene photovoltaic devices. Increased fullerene aggregation is shown to enhance charge generation and short-circuit device current - largely due to the increased production of HCT states at the aggregate interface. However, the instances where HCT states are predicted to give internal quantum efficiencies in the region of 50% do not correspond to HCT delocalisation or electron mobility measured in experiments. These data therefore suggest that HCT states are not the primary cause of high quantum efficiencies in some polymer:fullerene OPVs. Instead it is argued that HCT states are responsible for the fast charge generation seen in spectroscopy, but that regional variation in energy levels are the cause of long-term, efficient free-charge generation.

  17. Oxygen self-diffusion mechanisms in monoclinic Zr O2 revealed and quantified by density functional theory, random walk analysis, and kinetic Monte Carlo calculations

    NASA Astrophysics Data System (ADS)

    Yang, Jing; Youssef, Mostafa; Yildiz, Bilge

    2018-01-01

    In this work, we quantify oxygen self-diffusion in monoclinic-phase zirconium oxide as a function of temperature and oxygen partial pressure. A migration barrier of each type of oxygen defect was obtained by first-principles calculations. Random walk theory was used to quantify the diffusivities of oxygen interstitials by using the calculated migration barriers. Kinetic Monte Carlo simulations were used to calculate diffusivities of oxygen vacancies by distinguishing the threefold- and fourfold-coordinated lattice oxygen. By combining the equilibrium defect concentrations obtained in our previous work together with the herein calculated diffusivity of each defect species, we present the resulting oxygen self-diffusion coefficients and the corresponding atomistically resolved transport mechanisms. The predicted effective migration barriers and diffusion prefactors are in reasonable agreement with the experimentally reported values. This work provides insights into oxygen diffusion engineering in Zr O2 -related devices and parametrization for continuum transport modeling.

  18. CO adsorption on W(100) during temperature-programmed desorption: A combined density functional theory and kinetic Monte Carlo study

    NASA Astrophysics Data System (ADS)

    Albao, Marvin A.; Padama, Allan Abraham B.

    2017-02-01

    Using a combined density functional theory (DFT) and kinetic Monte Carlo (KMC) simulations, we study the adsorption at 800 K and subsequent desorption of CO on W(100) at higher temperatures. The resulting TPD profiles are known experimentally to exhibit three desorption peaks β1, β2, and β3 at 930 K, 1070 K, and 1375 K, respectively. Unlike more recent theoretical studies that propose that all three aforementioned peaks are molecularly rather than associatively desorbed, our KMC analyses are in support of the latter, since at 800 K dissociation is facile and that CO exists as dissociation fragments C and O. We show that these peaks arise from desorption from the same adsorption site but whose binding energy varies depending on local environment, that is, the presence of CO as well as dissociation fragments C and O nearby. Furthermore we show that several key parameters, such as desorption, dissociation and recombination barriers all play a key role in the TPD spectra-these parameter effectively controls not only the location of the TPD peaks but the shape and width of the desorption peaks as well. Moreover, our KMC simulations reveal that varying the heating rate shifts the peaks but leaves their shape intact.

  19. Monte Carlo simulation: Its status and future

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

    Murtha, J.A.

    1997-04-01

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

  20. Subdiffusion kinetics of nanoprecipitate growth and destruction in solid solutions

    NASA Astrophysics Data System (ADS)

    Sibatov, R. T.; Svetukhin, V. V.

    2015-06-01

    Based on fractional differential generalizations of the Ham and Aaron-Kotler precipitation models, we study the kinetics of subdiffusion-limited growth and dissolution of new-phase precipitates. We obtain the time dependence of the number of impurities and dimensions of new-phase precipitates. The solutions agree with the Monte Carlo simulation results.

  1. EChem++--an object-oriented problem solving environment for electrochemistry. 2. The kinetic facilities of Ecco--a compiler for (electro-)chemistry.

    PubMed

    Ludwig, Kai; Speiser, Bernd

    2004-01-01

    We describe a modeling software component Ecco, implemented in the C++ programming language. It assists in the formulation of physicochemical systems including, in particular, electrochemical processes within general geometries. Ecco's kinetic part then translates any user defined reaction mechanism into an object-oriented representation and generates the according mathematical model equations. The input language, its grammar, the object-oriented design of Ecco, based on design patterns, and its integration into the open source software project EChem++ are discussed. Application Strategies are given.

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

    NASA Technical Reports Server (NTRS)

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

    2008-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2007-01-01

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

  4. Computational characterization of HPGe detectors usable for a wide variety of source geometries by using Monte Carlo simulation and a multi-objective evolutionary algorithm

    NASA Astrophysics Data System (ADS)

    Guerra, J. G.; Rubiano, J. G.; Winter, G.; Guerra, A. G.; Alonso, H.; Arnedo, M. A.; Tejera, A.; Martel, P.; Bolivar, J. P.

    2017-06-01

    In this work, we have developed a computational methodology for characterizing HPGe detectors by implementing in parallel a multi-objective evolutionary algorithm, together with a Monte Carlo simulation code. The evolutionary algorithm is used for searching the geometrical parameters of a model of detector by minimizing the differences between the efficiencies calculated by Monte Carlo simulation and two reference sets of Full Energy Peak Efficiencies (FEPEs) corresponding to two given sample geometries, a beaker of small diameter laid over the detector window and a beaker of large capacity which wrap the detector. This methodology is a generalization of a previously published work, which was limited to beakers placed over the window of the detector with a diameter equal or smaller than the crystal diameter, so that the crystal mount cap (which surround the lateral surface of the crystal), was not considered in the detector model. The generalization has been accomplished not only by including such a mount cap in the model, but also using multi-objective optimization instead of mono-objective, with the aim of building a model sufficiently accurate for a wider variety of beakers commonly used for the measurement of environmental samples by gamma spectrometry, like for instance, Marinellis, Petris, or any other beaker with a diameter larger than the crystal diameter, for which part of the detected radiation have to pass through the mount cap. The proposed methodology has been applied to an HPGe XtRa detector, providing a model of detector which has been successfully verificated for different source-detector geometries and materials and experimentally validated using CRMs.

  5. 2D Implosion Simulations with a Kinetic Particle Code

    NASA Astrophysics Data System (ADS)

    Sagert, Irina; Even, Wesley; Strother, Terrance

    2017-10-01

    Many problems in laboratory and plasma physics are subject to flows that move between the continuum and the kinetic regime. We discuss two-dimensional (2D) implosion simulations that were performed using a Monte Carlo kinetic particle code. The application of kinetic transport theory is motivated, in part, by the occurrence of non-equilibrium effects in inertial confinement fusion (ICF) capsule implosions, which cannot be fully captured by hydrodynamics simulations. Kinetic methods, on the other hand, are able to describe both, continuum and rarefied flows. We perform simple 2D disk implosion simulations using one particle species and compare the results to simulations with the hydrodynamics code RAGE. The impact of the particle mean-free-path on the implosion is also explored. In a second study, we focus on the formation of fluid instabilities from induced perturbations. I.S. acknowledges support through the Director's fellowship from Los Alamos National Laboratory. This research used resources provided by the LANL Institutional Computing Program.

  6. Kinetic Monte Carlo simulations of fluorine and vacancies concentration at the CeO2(111) surface

    NASA Astrophysics Data System (ADS)

    Mattiello, S.; Kolling, S.; Heiliger, C.

    2017-09-01

    Recently, a new identification of the experimental depressions of scanning tunnelling microscopy images on the {{CeO}}2(111) surface as fluorine impurities has been proposed in Kullgren et al (2014 Phys. Rev. Lett. 112 156102). In particular, the high immobility of the depressions seems to be in contradiction with the low diffusion barrier for the oxygen vacancies. Consequently, the oxygen vacancies concentration has to disappear. The first aim of this paper is to confirm dynamically the recent interpretation of the experimental finding. For this purpose, we investigate the competition between fluorine and oxygen vacancies using two dimensional kinetic Monte Carlo simulations (kMC) as compared to an appropriate Langmuir model. We calculate the concentration of the vacancies and of the fluorine for the surface (111) of {{CeO}}2 for a UHV condition as a function of the fluorine-oxygen mixture in the gas phase as well as of the binding energies of fluorine and oxygen. We found that at a temperature of T=573 {{K}}, at which the experimental measurements were conducted, vacancies cannot exist. This confirms the possibility of fluorine impurities in Kullgren et al (2014 Phys. Rev. Lett. 112 156102). The second aim of the present paper is to perform a first dynamical estimation of the fluorine binding energy value {E}{Fl} that allows one to describe the experimental data in Pieper et al (2012 Phys. Chem. Chem. Phys. 14 15361). Using 2D-kMC simulations, we found {E}{Fl}\\in [-5.53,-5.27] {eV} which can be used for comparison to density functional theory calculations in further works.

  7. Kinetics of surfactant-mediated epitaxy of III-V semiconductors

    NASA Astrophysics Data System (ADS)

    Grandjean, N.; Massies, J.

    1996-05-01

    Surfactant-mediated epitaxy (SME) of III-V semiconductors is studied in the case of the GaAs(001) growth using Te as surfactant. To account for the strong surface segregation of Te, a phenomenological exchange mechanism is used. This process explains the reduction of the surface diffusion length evidenced by scanning tunneling microscopy (STM). However, this kinetics effect is observed only for restricted growth conditions: the As surface coverage should be sufficient to allow the exchange process. STM results as well as Monte Carlo simulations clearly show that the group-V element surface coverage plays a key role in the kinetics of SME of III-V semiconductors.

  8. Antihydrogen from positronium impact with cold antiprotons: a Monte Carlo simulation

    NASA Astrophysics Data System (ADS)

    Cassidy, D. B.; Merrison, J. P.; Charlton, M.; Mitroy, J.; Ryzhikh, G.

    1999-04-01

    A Monte Carlo simulation of the reaction to form antihydrogen by positronium impact upon antiprotons has been undertaken. Total and differential cross sections have been utilized as inputs to the simulation which models the conditions foreseen in planned antihydrogen formation experiments using positrons and antiprotons held in Penning traps. Thus, predictions of antihydrogen production rates, angular distributions and the variation of the mean antihydrogen temperature as a function of incident positronium kinetic energy have been produced.

  9. Study on formation of step bunching on 6H-SiC (0001) surface by kinetic Monte Carlo method

    NASA Astrophysics Data System (ADS)

    Li, Yuan; Chen, Xuejiang; Su, Juan

    2016-05-01

    The formation and evolution of step bunching during step-flow growth of 6H-SiC (0001) surfaces were studied by three-dimensional kinetic Monte Carlo (KMC) method and compared with the analytic model based on the theory of Burton-Cabera-Frank (BCF). In the KMC model the crystal lattice was represented by a structured mesh which fixed the position of atoms and interatomic bonding. The events considered in the model were adatoms adsorption and diffusion on the terrace, and adatoms attachment, detachment and interlayer transport at the step edges. In addition, effects of Ehrlich-Schwoebel (ES) barriers at downward step edges and incorporation barriers at upwards step edges were also considered. In order to obtain more elaborate information for the behavior of atoms in the crystal surface, silicon and carbon atoms were treated as the minimal diffusing species. KMC simulation results showed that multiple-height steps were formed on the vicinal surface oriented toward [ 1 1 bar 00 ] or [ 11 2 bar 0 ] directions. And then the formation mechanism of the step bunching was analyzed. Finally, to further analyze the formation processes of step bunching, a one-dimensional BCF analytic model with ES and incorporation barriers was used, and then it was solved numerically. In the BCF model, the periodic boundary conditions (PBC) were applied, and the parameters were corresponded to those used in the KMC model. The evolution character of step bunching was consistent with the results obtained by KMC simulation.

  10. Numerical simulation of photocurrent generation in bilayer organic solar cells: Comparison of master equation and kinetic Monte Carlo approaches

    NASA Astrophysics Data System (ADS)

    Casalegno, Mosè; Bernardi, Andrea; Raos, Guido

    2013-07-01

    Numerical approaches can provide useful information about the microscopic processes underlying photocurrent generation in organic solar cells (OSCs). Among them, the Kinetic Monte Carlo (KMC) method is conceptually the simplest, but computationally the most intensive. A less demanding alternative is potentially represented by so-called Master Equation (ME) approaches, where the equations describing particle dynamics rely on the mean-field approximation and their solution is attained numerically, rather than stochastically. The description of charge separation dynamics, the treatment of electrostatic interactions and numerical stability are some of the key issues which have prevented the application of these methods to OSC modelling, despite of their successes in the study of charge transport in disordered system. Here we describe a three-dimensional ME approach to photocurrent generation in OSCs which attempts to deal with these issues. The reliability of the proposed method is tested against reference KMC simulations on bilayer heterojunction solar cells. Comparison of the current-voltage curves shows that the model well approximates the exact result for most devices. The largest deviations in current densities are mainly due to the adoption of the mean-field approximation for electrostatic interactions. The presence of deep traps, in devices characterized by strong energy disorder, may also affect result quality. Comparison of the simulation times reveals that the ME algorithm runs, on the average, one order of magnitude faster than KMC.

  11. Understanding the kinetic mechanism of RNA single base pair formation

    PubMed Central

    Xu, Xiaojun; Yu, Tao; Chen, Shi-Jie

    2016-01-01

    RNA functions are intrinsically tied to folding kinetics. The most elementary step in RNA folding is the closing and opening of a base pair. Understanding this elementary rate process is the basis for RNA folding kinetics studies. Previous studies mostly focused on the unfolding of base pairs. Here, based on a hybrid approach, we investigate the folding process at level of single base pairing/stacking. The study, which integrates molecular dynamics simulation, kinetic Monte Carlo simulation, and master equation methods, uncovers two alternative dominant pathways: Starting from the unfolded state, the nucleotide backbone first folds to the native conformation, followed by subsequent adjustment of the base conformation. During the base conformational rearrangement, the backbone either retains the native conformation or switches to nonnative conformations in order to lower the kinetic barrier for base rearrangement. The method enables quantification of kinetic partitioning among the different pathways. Moreover, the simulation reveals several intriguing ion binding/dissociation signatures for the conformational changes. Our approach may be useful for developing a base pair opening/closing rate model. PMID:26699466

  12. Unraveling reaction pathways and specifying reaction kinetics for complex systems.

    PubMed

    Vinu, R; Broadbelt, Linda J

    2012-01-01

    Many natural and industrial processes involve a complex set of competing reactions that include several different species. Detailed kinetic modeling of such systems can shed light on the important pathways involved in various transformations and therefore can be used to optimize the process conditions for the desired product composition and properties. This review focuses on elucidating the various components involved in modeling the kinetics of pyrolysis and oxidation of polymers. The elementary free radical steps that constitute the chain reaction mechanism of gas-phase/nonpolar liquid-phase processes are outlined. Specification of the rate coefficients of the various reaction families, which is central to the theme of kinetics, is described. Construction of the reaction network on the basis of the types of end groups and reactive moieties in a polymer chain is discussed. Modeling frameworks based on the method of moments and kinetic Monte Carlo are evaluated using illustrations. Finally, the prospects and challenges in modeling biomass conversion are addressed.

  13. Algorithmic developments of the kinetic activation-relaxation technique: Accessing long-time kinetics of larger and more complex systems

    NASA Astrophysics Data System (ADS)

    Trochet, Mickaël; Sauvé-Lacoursière, Alecsandre; Mousseau, Normand

    2017-10-01

    In spite of the considerable computer speed increase of the last decades, long-time atomic simulations remain a challenge and most molecular dynamical simulations are limited to 1 μ s at the very best in condensed matter and materials science. There is a need, therefore, for accelerated methods that can bridge the gap between the full dynamical description of molecular dynamics and experimentally relevant time scales. This is the goal of the kinetic Activation-Relaxation Technique (k-ART), an off-lattice kinetic Monte-Carlo method with on-the-fly catalog building capabilities based on the topological tool NAUTY and the open-ended search method Activation-Relaxation Technique (ART nouveau) that has been applied with success to the study of long-time kinetics of complex materials, including grain boundaries, alloys, and amorphous materials. We present a number of recent algorithmic additions, including the use of local force calculation, two-level parallelization, improved topological description, and biased sampling and show how they perform on two applications linked to defect diffusion and relaxation after ion bombardement in Si.

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  15. Kinetic modeling of the photocatalytic degradation of clofibric acid in a slurry reactor.

    PubMed

    Manassero, Agustina; Satuf, María Lucila; Alfano, Orlando Mario

    2015-01-01

    A kinetic study of the photocatalytic degradation of the pharmaceutical clofibric acid is presented. Experiments were carried out under UV radiation employing titanium dioxide in water suspension. The main reaction intermediates were identified and quantified. Intrinsic expressions to represent the kinetics of clofibric acid and the main intermediates were derived. The modeling of the radiation field in the reactor was carried out by Monte Carlo simulation. Experimental runs were performed by varying the catalyst concentration and the incident radiation. Kinetic parameters were estimated from the experiments by applying a non-linear regression procedure. Good agreement was obtained between model predictions and experimental data, with an error of 5.9 % in the estimations of the primary pollutant concentration.

  16. Diffusion of oxygen interstitials in UO2+x using kinetic Monte Carlo simulations: Role of O/M ratio and sensitivity analysis

    NASA Astrophysics Data System (ADS)

    Behera, Rakesh K.; Watanabe, Taku; Andersson, David A.; Uberuaga, Blas P.; Deo, Chaitanya S.

    2016-04-01

    Oxygen interstitials in UO2+x significantly affect the thermophysical properties and microstructural evolution of the oxide nuclear fuel. In hyperstoichiometric Urania (UO2+x), these oxygen interstitials form different types of defect clusters, which have different migration behavior. In this study we have used kinetic Monte Carlo (kMC) to evaluate diffusivities of oxygen interstitials accounting for mono- and di-interstitial clusters. Our results indicate that the predicted diffusivities increase significantly at higher non-stoichiometry (x > 0.01) for di-interstitial clusters compared to a mono-interstitial only model. The diffusivities calculated at higher temperatures compare better with experimental values than at lower temperatures (< 973 K). We have discussed the resulting activation energies achieved for diffusion with all the mono- and di-interstitial models. We have carefully performed sensitivity analysis to estimate the effect of input di-interstitial binding energies on the predicted diffusivities and activation energies. While this article only discusses mono- and di-interstitials in evaluating oxygen diffusion response in UO2+x, future improvements to the model will primarily focus on including energetic definitions of larger stable interstitial clusters reported in the literature. The addition of larger clusters to the kMC model is expected to improve the comparison of oxygen transport in UO2+x with experiment.

  17. Efficient chemical potential evaluation with kinetic Monte Carlo method and non-uniform external potential: Lennard-Jones fluid, liquid, and solid

    NASA Astrophysics Data System (ADS)

    Ustinov, E. A.

    2017-07-01

    The aim of this paper is to present a method of a direct evaluation of the chemical potential of fluid, liquid, and solid with kinetic Monte Carlo simulation. The method is illustrated with the 12-6 Lennard-Jones (LJ) system over a wide range of density and temperature. A distinctive feature of the methodology used in the present study is imposing an external potential on the elongated simulation box to split the system into two equilibrium phases, one of which is substantially diluted. This technique provides a reliable direct evaluation of the chemical potential of the whole non-uniform system (including that of the uniformly distributed dense phase in the central zone of the box), which, for example, is impossible in simulation of the uniform crystalline phase. The parameters of the vapor-liquid, liquid-solid, and fluid-solid transitions have been reliably determined. The chemical potential and the pressure are defined as thermodynamically consistent functions of density and temperature separately for the liquid and the solid (FCC) phases. It has been shown that in two-phase systems separated by a flat interface, the crystal melting always occurs at equilibrium conditions. It is also proved that in the limit of zero temperature, the specific heat capacity of an LJ crystal at constant volume is exactly 3Rg (where Rg is the gas constant) without resorting to harmonic oscillators.

  18. A first principles kinetic Monte Carlo investigation of the adsorption and mobility of gadolinium on the (100) surface of tungsten

    NASA Astrophysics Data System (ADS)

    Samin, Adib J.; Zhang, Jinsuo

    2017-05-01

    An accurate characterization of lanthanide adsorption and mobility on tungsten surfaces is important for pyroprocessing. In the present study, the adsorption and diffusion of gadolinium on the (100) surface of tungsten was investigated. It was found that the hollow sites were the most energetically favorable for the adsorption. It was further observed that a magnetic moment was induced following the adsorption of gadolinium on the tungsten surface and that the system with adsorbed hollow sites had the largest magnetization. A pathway for the surface diffusion of gadolinium was determined to occur by hopping between the nearest neighbor hollow sites via the bridge site and the activation energy for the hop was calculated to be 0.75 eV. The surface diffusion process was further assessed using two distinct kinetic Monte Carlo models; one that accounted for lateral adsorbate interactions up to the second nearest neighbor and one that did not account for such interatomic interactions in the adlayer. When the lateral interactions were included in the simulations, the diffusivity was observed to have a strong dependence on coverage (for the coverage values being studied). The effects of lateral interactions were further observed in a one-dimensional simulation of the diffusion equation where the asymmetry in the surface coverage profile upon its approach to a steady state distribution was clear in comparison with the simulations which did not account for those interactions.

  19. Investigation of resistance switching in SiO x RRAM cells using a 3D multi-scale kinetic Monte Carlo simulator

    NASA Astrophysics Data System (ADS)

    Sadi, Toufik; Mehonic, Adnan; Montesi, Luca; Buckwell, Mark; Kenyon, Anthony; Asenov, Asen

    2018-02-01

    We employ an advanced three-dimensional (3D) electro-thermal simulator to explore the physics and potential of oxide-based resistive random-access memory (RRAM) cells. The physical simulation model has been developed recently, and couples a kinetic Monte Carlo study of electron and ionic transport to the self-heating phenomenon while accounting carefully for the physics of vacancy generation and recombination, and trapping mechanisms. The simulation framework successfully captures resistance switching, including the electroforming, set and reset processes, by modeling the dynamics of conductive filaments in the 3D space. This work focuses on the promising yet less studied RRAM structures based on silicon-rich silica (SiO x ) RRAMs. We explain the intrinsic nature of resistance switching of the SiO x layer, analyze the effect of self-heating on device performance, highlight the role of the initial vacancy distributions acting as precursors for switching, and also stress the importance of using 3D physics-based models to capture accurately the switching processes. The simulation work is backed by experimental studies. The simulator is useful for improving our understanding of the little-known physics of SiO x resistive memory devices, as well as other oxide-based RRAM systems (e.g. transition metal oxide RRAMs), offering design and optimization capabilities with regard to the reliability and variability of memory cells.

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

    PubMed

    Garcia, Alejandro L; Wagner, Wolfgang

    2003-11-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2017-12-01

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

  2. A coarse-grained Monte Carlo approach to diffusion processes in metallic nanoparticles

    NASA Astrophysics Data System (ADS)

    Hauser, Andreas W.; Schnedlitz, Martin; Ernst, Wolfgang E.

    2017-06-01

    A kinetic Monte Carlo approach on a coarse-grained lattice is developed for the simulation of surface diffusion processes of Ni, Pd and Au structures with diameters in the range of a few nanometers. Intensity information obtained via standard two-dimensional transmission electron microscopy imaging techniques is used to create three-dimensional structure models as input for a cellular automaton. A series of update rules based on reaction kinetics is defined to allow for a stepwise evolution in time with the aim to simulate surface diffusion phenomena such as Rayleigh breakup and surface wetting. The material flow, in our case represented by the hopping of discrete portions of metal on a given grid, is driven by the attempt to minimize the surface energy, which can be achieved by maximizing the number of filled neighbor cells.

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

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

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

    2015-12-31

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

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

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

    Giuseppe Palmiotti

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

  5. Mechanism of Kinetically Controlled Capillary Condensation in Nanopores: A Combined Experimental and Monte Carlo Approach.

    PubMed

    Hiratsuka, Tatsumasa; Tanaka, Hideki; Miyahara, Minoru T

    2017-01-24

    We find the rule of capillary condensation from the metastable state in nanoscale pores based on the transition state theory. The conventional thermodynamic theories cannot achieve it because the metastable capillary condensation inherently includes an activated process. We thus compute argon adsorption isotherms on cylindrical pore models and atomistic silica pore models mimicking the MCM-41 materials by the grand canonical Monte Carlo and the gauge cell Monte Carlo methods and evaluate the rate constant for the capillary condensation by the transition state theory. The results reveal that the rate drastically increases with a small increase in the chemical potential of the system, and the metastable capillary condensation occurs for any mesopores when the rate constant reaches a universal critical value. Furthermore, a careful comparison between experimental adsorption isotherms and the simulated ones on the atomistic silica pore models reveals that the rate constant of the real system also has a universal value. With this finding, we can successfully estimate the experimental capillary condensation pressure over a wide range of temperatures and pore sizes by simply applying the critical rate constant.

  6. Monte Carlo simulation of ferroelectric domain growth

    NASA Astrophysics Data System (ADS)

    Li, B. L.; Liu, X. P.; Fang, F.; Zhu, J. L.; Liu, J.-M.

    2006-01-01

    The kinetics of two-dimensional isothermal domain growth in a quenched ferroelectric system is investigated using Monte Carlo simulation based on a realistic Ginzburg-Landau ferroelectric model with cubic-tetragonal (square-rectangle) phase transitions. The evolution of the domain pattern and domain size with annealing time is simulated, and the stability of trijunctions and tetrajunctions of domain walls is analyzed. It is found that in this much realistic model with strong dipole alignment anisotropy and long-range Coulomb interaction, the powerlaw for normal domain growth still stands applicable. Towards the late stage of domain growth, both the average domain area and reciprocal density of domain wall junctions increase linearly with time, and the one-parameter dynamic scaling of the domain growth is demonstrated.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

    We describe CPMC-Lab, a MATLAB program for the constrained-path and phaseless auxiliary-field Monte Carlo methods. These methods have allowed applications ranging from the study of strongly correlated models, such as the Hubbard model, to ab initio calculations in molecules and solids. The present package implements the full ground-state constrained-path Monte Carlo (CPMC) method in MATLAB with a graphical interface, using the Hubbard model as an example. The package can perform calculations in finite supercells in any dimensions, under periodic or twist boundary conditions. Importance sampling and all other algorithmic details of a total energy calculation are included and illustrated. This open-source tool allows users to experiment with various model and run parameters and visualize the results. It provides a direct and interactive environment to learn the method and study the code with minimal overhead for setup. Furthermore, the package can be easily generalized for auxiliary-field quantum Monte Carlo (AFQMC) calculations in many other models for correlated electron systems, and can serve as a template for developing a production code for AFQMC total energy calculations in real materials. Several illustrative studies are carried out in one- and two-dimensional lattices on total energy, kinetic energy, potential energy, and charge- and spin-gaps.

  8. Characterizing Quality Factor of Niobium Resonators Using a Markov Chain Monte Carlo Approach

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

    Basu Thakur, Ritoban; Tang, Qing Yang; McGeehan, Ryan

    The next generation of radiation detectors in high precision Cosmology, Astronomy, and particle-astrophysics experiments will rely heavily on superconducting microwave resonators and kinetic inductance devices. Understanding the physics of energy loss in these devices, in particular at low temperatures and powers, is vital. We present a comprehensive analysis framework, using Markov Chain Monte Carlo methods, to characterize loss due to two-level system in concert with quasi-particle dynamics in thin-film Nb resonators in the GHz range.

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

    NASA Astrophysics Data System (ADS)

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

    2017-07-01

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

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

    NASA Technical Reports Server (NTRS)

    Thipphavong, David

    2010-01-01

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

  11. Theoretical study of the ammonia nitridation rate on an Fe (100) surface: A combined density functional theory and kinetic Monte Carlo study

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

    Yeo, Sang Chul; Lee, Hyuck Mo, E-mail: hmlee@kaist.ac.kr; Lo, Yu Chieh

    2014-10-07

    Ammonia (NH{sub 3}) nitridation on an Fe surface was studied by combining density functional theory (DFT) and kinetic Monte Carlo (kMC) calculations. A DFT calculation was performed to obtain the energy barriers (E{sub b}) of the relevant elementary processes. The full mechanism of the exact reaction path was divided into five steps (adsorption, dissociation, surface migration, penetration, and diffusion) on an Fe (100) surface pre-covered with nitrogen. The energy barrier (E{sub b}) depended on the N surface coverage. The DFT results were subsequently employed as a database for the kMC simulations. We then evaluated the NH{sub 3} nitridation rate onmore » the N pre-covered Fe surface. To determine the conditions necessary for a rapid NH{sub 3} nitridation rate, the eight reaction events were considered in the kMC simulations: adsorption, desorption, dissociation, reverse dissociation, surface migration, penetration, reverse penetration, and diffusion. This study provides a real-time-scale simulation of NH{sub 3} nitridation influenced by nitrogen surface coverage that allowed us to theoretically determine a nitrogen coverage (0.56 ML) suitable for rapid NH{sub 3} nitridation. In this way, we were able to reveal the coverage dependence of the nitridation reaction using the combined DFT and kMC simulations.« less

  12. Theoretical study of the ammonia nitridation rate on an Fe (100) surface: a combined density functional theory and kinetic Monte Carlo study.

    PubMed

    Yeo, Sang Chul; Lo, Yu Chieh; Li, Ju; Lee, Hyuck Mo

    2014-10-07

    Ammonia (NH3) nitridation on an Fe surface was studied by combining density functional theory (DFT) and kinetic Monte Carlo (kMC) calculations. A DFT calculation was performed to obtain the energy barriers (Eb) of the relevant elementary processes. The full mechanism of the exact reaction path was divided into five steps (adsorption, dissociation, surface migration, penetration, and diffusion) on an Fe (100) surface pre-covered with nitrogen. The energy barrier (Eb) depended on the N surface coverage. The DFT results were subsequently employed as a database for the kMC simulations. We then evaluated the NH3 nitridation rate on the N pre-covered Fe surface. To determine the conditions necessary for a rapid NH3 nitridation rate, the eight reaction events were considered in the kMC simulations: adsorption, desorption, dissociation, reverse dissociation, surface migration, penetration, reverse penetration, and diffusion. This study provides a real-time-scale simulation of NH3 nitridation influenced by nitrogen surface coverage that allowed us to theoretically determine a nitrogen coverage (0.56 ML) suitable for rapid NH3 nitridation. In this way, we were able to reveal the coverage dependence of the nitridation reaction using the combined DFT and kMC simulations.

  13. Self-Diffusion of small Ag and Ni islands on Ag(111) and Ni(111) using the self-learning kinetic Monte Carlo method

    NASA Astrophysics Data System (ADS)

    Islamuddin Shah, Syed; Nandipati, Giridhar; Kara, Abdelkader; Rahman, Talat S.

    2012-02-01

    We have applied a modified Self-Learning Kinetic Monte Carlo (SLKMC) method [1] to examine the self-diffusion of small Ag and Ni islands, containing up to 10 atom, on the (111) surface of the respective metal. The pattern recognition scheme in this new SLKMC method allows occupancy of the fcc, hcp and top sites on the fcc(111) surface and employs them to identify the local neighborhood around a central atom. Molecular static calculations with semi empirical interatomic potential and reliable techniques for saddle point search revealed several new diffusion mechanisms that contribute to the diffusion of small islands. For comparison we have also evaluated the diffusion characteristics of Cu clusters on Cu(111) and compared results with previous findings [2]. Our results show a linear increase in effective energy barriers scaling almost as 0.043, 0.051 and 0.064 eV/atom for the Cu/Cu(111), Ag/Ag(111), and Ni/Ni(111) systems, respectively. For all three systems, diffusion of small islands proceeds mainly through concerted motion, although several multiple and single atom processes also contribute. [1] Oleg Trushin et al. Phys. Rev. B 72, 115401 (2005) [2] Altaf Karim et al. Phys. Rev. B 73, 165411 (2006)

  14. Exploring Mass Perception with Markov Chain Monte Carlo

    ERIC Educational Resources Information Center

    Cohen, Andrew L.; Ross, Michael G.

    2009-01-01

    Several previous studies have examined the ability to judge the relative mass of objects in idealized collisions. With a newly developed technique of psychological Markov chain Monte Carlo sampling (A. N. Sanborn & T. L. Griffiths, 2008), this work explores participants; perceptions of different collision mass ratios. The results reveal…

  15. Thermodynamic properties of water in confined environments: a Monte Carlo study

    NASA Astrophysics Data System (ADS)

    Gladovic, Martin; Bren, Urban; Urbic, Tomaž

    2018-05-01

    Monte Carlo simulations of Mercedes-Benz water in a crowded environment were performed. The simulated systems are representative of both composite, porous or sintered materials and living cells with typical matrix packings. We studied the influence of overall temperature as well as the density and size of matrix particles on water density, particle distributions, hydrogen bond formation and thermodynamic quantities. Interestingly, temperature and space occupancy of matrix exhibit a similar effect on water properties following the competition between the kinetic and the potential energy of the system, whereby temperature increases the kinetic and matrix packing decreases the potential contribution. A novel thermodynamic decomposition approach was applied to gain insight into individual contributions of different types of inter-particle interactions. This decomposition proved to be useful and in good agreement with the total thermodynamic quantities especially at higher temperatures and matrix packings, where higher-order potential-energy mixing terms lose their importance.

  16. Recognizing Chromospheric Objects via Markov Chain Monte Carlo

    NASA Technical Reports Server (NTRS)

    Mukhtar, Saleem; Turmon, Michael J.

    1997-01-01

    The solar chromosphere consists of three classes which contribute differentially to ultraviolet radiation reaching the earth. We describe a data set of solar images, means of segmenting the images into the constituent classes, and a novel high-level representation for compact objects based on a triangulated spatial membership function.

  17. Using the Markov chain Monte Carlo method to study the physical properties of GeV-TeV BL Lac objects

    NASA Astrophysics Data System (ADS)

    Qin, Longhua; Wang, Jiancheng; Yang, Chuyuan; Yuan, Zunli; Mao, Jirong; Kang, Shiju

    2018-01-01

    We fit the spectral energy distributions (SEDs) of 46 GeV-TeV BL Lac objects in the frame of leptonic one-zone synchrotron self-Compton (SSC) model and investigate the physical properties of these objects. We use the Markov chain Monte Carlo (MCMC) method to obtain the basic parameters, such as magnetic field (B), the break energy of the relativistic electron distribution (γ ^' }b), and the electron energy spectral index. Based on the modeling results, we support the following scenarios for GeV-TeV BL Lac objects. (1) Some sources have large Doppler factors, implying other radiation mechanism should be considered. (2) Compared with flat spectrum quasars (FSRQs), GeV-TeV BL Lac objects have weaker magnetic fields and larger Doppler factors, which cause the ineffective cooling and shift the SEDs to higher bands. Their jet powers are around 4.0 × 1045 erg s-1, compared with radiation power, 5.0 × 1042 erg s-1, indicating that only a small fraction of jet power is transformed into the emission power. (3) For some BL Lacs with large Doppler factors, their jet components could have two substructures, e.g., the fast core and the slow sheath. For most GeV-TeV BL Lacs, Kelvin-Helmholtz instabilities are suppressed by their higher magnetic fields, leading to micro-variability or intro-day variability in the optical bands. (4) Combined with a sample of FSRQs, an anti-correlation between the peak luminosity, Lpk, and the peak frequency, νpk, is obtained, favoring the blazar sequence scenario. In addition, an anti-correlation between the jet power, Pjet, and the break Lorentz factor, γb, also supports the blazar sequence.

  18. Kinetic Monte Carlo simulation of the efficiency roll-off, emission color, and degradation of organic light-emitting diodes (Presentation Recording)

    NASA Astrophysics Data System (ADS)

    Coehoorn, Reinder; van Eersel, Harm; Bobbert, Peter A.; Janssen, Rene A. J.

    2015-10-01

    The performance of Organic Light Emitting Diodes (OLEDs) is determined by a complex interplay of the charge transport and excitonic processes in the active layer stack. We have developed a three-dimensional kinetic Monte Carlo (kMC) OLED simulation method which includes all these processes in an integral manner. The method employs a physically transparent mechanistic approach, and is based on measurable parameters. All processes can be followed with molecular-scale spatial resolution and with sub-nanosecond time resolution, for any layer structure and any mixture of materials. In the talk, applications to the efficiency roll-off, emission color and lifetime of white and monochrome phosphorescent OLEDs [1,2] are demonstrated, and a comparison with experimental results is given. The simulations show to which extent the triplet-polaron quenching (TPQ) and triplet-triplet-annihilation (TTA) contribute to the roll-off, and how the microscopic parameters describing these processes can be deduced properly from dedicated experiments. Degradation is treated as a result of the (accelerated) conversion of emitter molecules to non-emissive sites upon a triplet-polaron quenching (TPQ) process. The degradation rate, and hence the device lifetime, is shown to depend on the emitter concentration and on the precise type of TPQ process. Results for both single-doped and co-doped OLEDs are presented, revealing that the kMC simulations enable efficient simulation-assisted layer stack development. [1] H. van Eersel et al., Appl. Phys. Lett. 105, 143303 (2014). [2] R. Coehoorn et al., Adv. Funct. Mater. (2015), publ. online (DOI: 10.1002/adfm.201402532)

  19. Prediction of La0.6Sr0.4Co0.2Fe0.8O3 cathode microstructures during sintering: Kinetic Monte Carlo (KMC) simulations calibrated by artificial neural networks

    NASA Astrophysics Data System (ADS)

    Yan, Zilin; Kim, Yongtae; Hara, Shotaro; Shikazono, Naoki

    2017-04-01

    The Potts Kinetic Monte Carlo (KMC) model, proven to be a robust tool to study all stages of sintering process, is an ideal tool to analyze the microstructure evolution of electrodes in solid oxide fuel cells (SOFCs). Due to the nature of this model, the input parameters of KMC simulations such as simulation temperatures and attempt frequencies are difficult to identify. We propose a rigorous and efficient approach to facilitate the input parameter calibration process using artificial neural networks (ANNs). The trained ANN reduces drastically the number of trial-and-error of KMC simulations. The KMC simulation using the calibrated input parameters predicts the microstructures of a La0.6Sr0.4Co0.2Fe0.8O3 cathode material during sintering, showing both qualitative and quantitative congruence with real 3D microstructures obtained by focused ion beam scanning electron microscopy (FIB-SEM) reconstruction.

  20. Diffusion of point defects in crystalline silicon using the kinetic activation-relaxation technique method

    DOE PAGES

    Trochet, Mickaël; Béland, Laurent Karim; Joly, Jean -François; ...

    2015-06-16

    We study point-defect diffusion in crystalline silicon using the kinetic activation-relaxation technique (k-ART), an off-lattice kinetic Monte Carlo method with on-the-fly catalog building capabilities based on the activation-relaxation technique (ART nouveau), coupled to the standard Stillinger-Weber potential. We focus more particularly on the evolution of crystalline cells with one to four vacancies and one to four interstitials in order to provide a detailed picture of both the atomistic diffusion mechanisms and overall kinetics. We show formation energies, activation barriers for the ground state of all eight systems, and migration barriers for those systems that diffuse. Additionally, we characterize diffusion pathsmore » and special configurations such as dumbbell complex, di-interstitial (IV-pair+2I) superdiffuser, tetrahedral vacancy complex, and more. In conclusion, this study points to an unsuspected dynamical richness even for this apparently simple system that can only be uncovered by exhaustive and systematic approaches such as the kinetic activation-relaxation technique.« less

  1. GUINEVERE experiment: Kinetic analysis of some reactivity measurement methods by deterministic and Monte Carlo codes

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

    Bianchini, G.; Burgio, N.; Carta, M.

    The GUINEVERE experiment (Generation of Uninterrupted Intense Neutrons at the lead Venus Reactor) is an experimental program in support of the ADS technology presently carried out at SCK-CEN in Mol (Belgium). In the experiment a modified lay-out of the original thermal VENUS critical facility is coupled to an accelerator, built by the French body CNRS in Grenoble, working in both continuous and pulsed mode and delivering 14 MeV neutrons by bombardment of deuterons on a tritium-target. The modified lay-out of the facility consists of a fast subcritical core made of 30% U-235 enriched metallic Uranium in a lead matrix. Severalmore » off-line and on-line reactivity measurement techniques will be investigated during the experimental campaign. This report is focused on the simulation by deterministic (ERANOS French code) and Monte Carlo (MCNPX US code) calculations of three reactivity measurement techniques, Slope ({alpha}-fitting), Area-ratio and Source-jerk, applied to a GUINEVERE subcritical configuration (namely SC1). The inferred reactivity, in dollar units, by the Area-ratio method shows an overall agreement between the two deterministic and Monte Carlo computational approaches, whereas the MCNPX Source-jerk results are affected by large uncertainties and allow only partial conclusions about the comparison. Finally, no particular spatial dependence of the results is observed in the case of the GUINEVERE SC1 subcritical configuration. (authors)« less

  2. A Monte Carlo approach to the microdosimetric kinetic model to account for dose rate time structure effects in ion beam therapy with application in treatment planning simulations.

    PubMed

    Manganaro, Lorenzo; Russo, Germano; Cirio, Roberto; Dalmasso, Federico; Giordanengo, Simona; Monaco, Vincenzo; Muraro, Silvia; Sacchi, Roberto; Vignati, Anna; Attili, Andrea

    2017-04-01

    Advanced ion beam therapeutic techniques, such as hypofractionation, respiratory gating, or laser-based pulsed beams, have dose rate time structures which are substantially different from those found in conventional approaches. The biological impact of the time structure is mediated through the β parameter in the linear quadratic (LQ) model. The aim of this study was to assess the impact of changes in the value of the β parameter on the treatment outcomes, also accounting for noninstantaneous intrafraction dose delivery or fractionation and comparing the effects of using different primary ions. An original formulation of the microdosimetric kinetic model (MKM) is used (named MCt-MKM), in which a Monte Carlo (MC) approach was introduced to account for the stochastic spatio-temporal correlations characteristic of the irradiations and the cellular repair kinetics. A modified version of the kinetic equations, validated on experimental cell survival in vitro data, was also introduced. The model, trained on the HSG cells, was used to evaluate the relative biological effectiveness (RBE) for treatments with acute and protracted fractions. Exemplary cases of prostate cancer irradiated with different ion beams were evaluated to assess the impact of the temporal effects. The LQ parameters for a range of cell lines (V79, HSG, and T1) and ion species (H, He, C, and Ne) were evaluated and compared with the experimental data available in the literature, with good results. Notably, in contrast to the original MKM formulation, the MCt-MKM explicitly predicts an ion and LET-dependent β compatible with observations. The data from a split-dose experiment were used to experimentally determine the value of the parameter related to the cellular repair kinetics. Concerning the clinical case considered, an RBE decrease was observed, depending on the dose, ion, and LET, exceeding up to 3% of the acute value in the case of a protraction in the delivery of 10 min. The intercomparison

  3. Accelerated procedure to solve kinetic equation for neutral atoms in a hot plasma

    NASA Astrophysics Data System (ADS)

    Tokar, Mikhail Z.

    2017-12-01

    The recombination of plasma charged components, electrons and ions of hydrogen isotopes, on the wall of a fusion reactor is a source of neutral molecules and atoms, recycling back into the plasma volume. Here neutral species participate, in particular, in charge-exchange (c-x) collisions with the plasma ions and, as a result, atoms of high energies with chaotically directed velocities are generated. Some fraction of these hot atoms hit the wall. Statistical Monte Carlo methods normally used to model c-x atoms are too time consuming for reasonably small level of accident errors and extensive parameter studies are problematic. By applying pass method to evaluate integrals from functions, including the ion velocity distribution, an iteration approach to solve one-dimensional kinetic equation [1], being alternative to Monte Carlo procedure, has been tremendously accelerated, at least by a factor of 30-50 [2]. Here this approach is developed further to solve the 2-D kinetic equation, applied to model the transport of c-x atoms in the vicinity of an opening in the wall, e.g., the entrance of the duct guiding to a diagnostic installation. This is necessary to determine firmly the energy spectrum of c-x atoms penetrating into the duct and to assess the erosion of the installation there. The results of kinetic modeling are compared with those obtained with the diffusion description for c-x atoms, being strictly relevant under plasma conditions of low temperature and high density, where the mean free path length between c-x collisions is much smaller than that till the atom ionization by electrons. It is demonstrated that the previous calculations [3], done with the diffusion approximation for c-x atoms, overestimate the erosion rate of Mo mirrors in a reactor by a factor of 3 compared to the result of the present kinetic study.

  4. The Harrison Diffusion Kinetics Regimes in Solute Grain Boundary Diffusion

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

    Belova, Irina; Fiedler, T; Kulkarni, Nagraj S

    2012-01-01

    Knowledge of the limits of the principal Harrison kinetics regimes (Type-A, B and C) for grain boundary diffusion is very important for the correct analysis of the depth profiles in a tracer diffusion experiment. These regimes for self-diffusion have been extensively studied in the past by making use of the phenomenological Lattice Monte Carlo (LMC) method with the result that the limits are now well established. The relationship of those self-diffusion limits to the corresponding ones for solute diffusion in the presence of solute segregation to the grain boundaries remains unclear. In the present study, the influence of solute segregationmore » on the limits is investigated with the LMC method for the well-known parallel grain boundary slab model by showing the equivalence of two diffusion models. It is shown which diffusion parameters are useful for identifying the limits of the Harrison kinetics regimes for solute grain boundary diffusion. It is also shown how the measured segregation factor from the diffusion experiment in the Harrison Type-B kinetics regime may differ from the global segregation factor.« less

  5. Interplay of bistable kinetics of gene expression during cellular growth

    NASA Astrophysics Data System (ADS)

    Zhdanov, Vladimir P.

    2009-02-01

    In cells, the bistable kinetics of gene expression can be observed on the level of (i) one gene with positive feedback between protein and mRNA production, (ii) two genes with negative mutual feedback between protein and mRNA production, or (iii) in more complex cases. We analyse the interplay of two genes of type (ii) governed by a gene of type (i) during cellular growth. In particular, using kinetic Monte Carlo simulations, we show that in the case where gene 1, operating in the bistable regime, regulates mutually inhibiting genes 2 and 3, also operating in the bistable regime, the latter genes may eventually be trapped either to the state with high transcriptional activity of gene 2 and low activity of gene 3 or to the state with high transcriptional activity of gene 3 and low activity of gene 2. The probability to get to one of these states depends on the values of the model parameters. If genes 2 and 3 are kinetically equivalent, the probability is equal to 0.5. Thus, our model illustrates how different intracellular states can be chosen at random with predetermined probabilities. This type of kinetics of gene expression may be behind complex processes occurring in cells, e.g., behind the choice of the fate by stem cells.

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

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

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

    2016-12-15

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

  7. A New Monte Carlo Method for Estimating Marginal Likelihoods.

    PubMed

    Wang, Yu-Bo; Chen, Ming-Hui; Kuo, Lynn; Lewis, Paul O

    2018-06-01

    Evaluating the marginal likelihood in Bayesian analysis is essential for model selection. Estimators based on a single Markov chain Monte Carlo sample from the posterior distribution include the harmonic mean estimator and the inflated density ratio estimator. We propose a new class of Monte Carlo estimators based on this single Markov chain Monte Carlo sample. This class can be thought of as a generalization of the harmonic mean and inflated density ratio estimators using a partition weighted kernel (likelihood times prior). We show that our estimator is consistent and has better theoretical properties than the harmonic mean and inflated density ratio estimators. In addition, we provide guidelines on choosing optimal weights. Simulation studies were conducted to examine the empirical performance of the proposed estimator. We further demonstrate the desirable features of the proposed estimator with two real data sets: one is from a prostate cancer study using an ordinal probit regression model with latent variables; the other is for the power prior construction from two Eastern Cooperative Oncology Group phase III clinical trials using the cure rate survival model with similar objectives.

  8. pyNSMC: A Python Module for Null-Space Monte Carlo Uncertainty Analysis

    NASA Astrophysics Data System (ADS)

    White, J.; Brakefield, L. K.

    2015-12-01

    The null-space monte carlo technique is a non-linear uncertainty analyses technique that is well-suited to high-dimensional inverse problems. While the technique is powerful, the existing workflow for completing null-space monte carlo is cumbersome, requiring the use of multiple commandline utilities, several sets of intermediate files and even a text editor. pyNSMC is an open-source python module that automates the workflow of null-space monte carlo uncertainty analyses. The module is fully compatible with the PEST and PEST++ software suites and leverages existing functionality of pyEMU, a python framework for linear-based uncertainty analyses. pyNSMC greatly simplifies the existing workflow for null-space monte carlo by taking advantage of object oriented design facilities in python. The core of pyNSMC is the ensemble class, which draws and stores realized random vectors and also provides functionality for exporting and visualizing results. By relieving users of the tedium associated with file handling and command line utility execution, pyNSMC instead focuses the user on the important steps and assumptions of null-space monte carlo analysis. Furthermore, pyNSMC facilitates learning through flow charts and results visualization, which are available at many points in the algorithm. The ease-of-use of the pyNSMC workflow is compared to the existing workflow for null-space monte carlo for a synthetic groundwater model with hundreds of estimable parameters.

  9. Refined elasticity sampling for Monte Carlo-based identification of stabilizing network patterns.

    PubMed

    Childs, Dorothee; Grimbs, Sergio; Selbig, Joachim

    2015-06-15

    Structural kinetic modelling (SKM) is a framework to analyse whether a metabolic steady state remains stable under perturbation, without requiring detailed knowledge about individual rate equations. It provides a representation of the system's Jacobian matrix that depends solely on the network structure, steady state measurements, and the elasticities at the steady state. For a measured steady state, stability criteria can be derived by generating a large number of SKMs with randomly sampled elasticities and evaluating the resulting Jacobian matrices. The elasticity space can be analysed statistically in order to detect network positions that contribute significantly to the perturbation response. Here, we extend this approach by examining the kinetic feasibility of the elasticity combinations created during Monte Carlo sampling. Using a set of small example systems, we show that the majority of sampled SKMs would yield negative kinetic parameters if they were translated back into kinetic models. To overcome this problem, a simple criterion is formulated that mitigates such infeasible models. After evaluating the small example pathways, the methodology was used to study two steady states of the neuronal TCA cycle and the intrinsic mechanisms responsible for their stability or instability. The findings of the statistical elasticity analysis confirm that several elasticities are jointly coordinated to control stability and that the main source for potential instabilities are mutations in the enzyme alpha-ketoglutarate dehydrogenase. © The Author 2015. Published by Oxford University Press.

  10. Validation of Bayesian analysis of compartmental kinetic models in medical imaging.

    PubMed

    Sitek, Arkadiusz; Li, Quanzheng; El Fakhri, Georges; Alpert, Nathaniel M

    2016-10-01

    Kinetic compartmental analysis is frequently used to compute physiologically relevant quantitative values from time series of images. In this paper, a new approach based on Bayesian analysis to obtain information about these parameters is presented and validated. The closed-form of the posterior distribution of kinetic parameters is derived with a hierarchical prior to model the standard deviation of normally distributed noise. Markov chain Monte Carlo methods are used for numerical estimation of the posterior distribution. Computer simulations of the kinetics of F18-fluorodeoxyglucose (FDG) are used to demonstrate drawing statistical inferences about kinetic parameters and to validate the theory and implementation. Additionally, point estimates of kinetic parameters and covariance of those estimates are determined using the classical non-linear least squares approach. Posteriors obtained using methods proposed in this work are accurate as no significant deviation from the expected shape of the posterior was found (one-sided P>0.08). It is demonstrated that the results obtained by the standard non-linear least-square methods fail to provide accurate estimation of uncertainty for the same data set (P<0.0001). The results of this work validate new methods for a computer simulations of FDG kinetics. Results show that in situations where the classical approach fails in accurate estimation of uncertainty, Bayesian estimation provides an accurate information about the uncertainties in the parameters. Although a particular example of FDG kinetics was used in the paper, the methods can be extended for different pharmaceuticals and imaging modalities. Copyright © 2016 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

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

    NASA Astrophysics Data System (ADS)

    Schwarz, Karsten; Rieger, Heiko

    2013-03-01

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

  12. A Monte Carlo model for 3D grain evolution during welding

    NASA Astrophysics Data System (ADS)

    Rodgers, Theron M.; Mitchell, John A.; Tikare, Veena

    2017-09-01

    Welding is one of the most wide-spread processes used in metal joining. However, there are currently no open-source software implementations for the simulation of microstructural evolution during a weld pass. Here we describe a Potts Monte Carlo based model implemented in the SPPARKS kinetic Monte Carlo computational framework. The model simulates melting, solidification and solid-state microstructural evolution of material in the fusion and heat-affected zones of a weld. The model does not simulate thermal behavior, but rather utilizes user input parameters to specify weld pool and heat-affect zone properties. Weld pool shapes are specified by Bézier curves, which allow for the specification of a wide range of pool shapes. Pool shapes can range from narrow and deep to wide and shallow representing different fluid flow conditions within the pool. Surrounding temperature gradients are calculated with the aide of a closest point projection algorithm. The model also allows simulation of pulsed power welding through time-dependent variation of the weld pool size. Example simulation results and comparisons with laboratory weld observations demonstrate microstructural variation with weld speed, pool shape, and pulsed-power.

  13. A Monte Carlo model for 3D grain evolution during welding

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

    Rodgers, Theron M.; Mitchell, John A.; Tikare, Veena

    Welding is one of the most wide-spread processes used in metal joining. However, there are currently no open-source software implementations for the simulation of microstructural evolution during a weld pass. Here we describe a Potts Monte Carlo based model implemented in the SPPARKS kinetic Monte Carlo computational framework. The model simulates melting, solidification and solid-state microstructural evolution of material in the fusion and heat-affected zones of a weld. The model does not simulate thermal behavior, but rather utilizes user input parameters to specify weld pool and heat-affect zone properties. Weld pool shapes are specified by Bezier curves, which allow formore » the specification of a wide range of pool shapes. Pool shapes can range from narrow and deep to wide and shallow representing different fluid flow conditions within the pool. Surrounding temperature gradients are calculated with the aide of a closest point projection algorithm. Furthermore, the model also allows simulation of pulsed power welding through time-dependent variation of the weld pool size. Example simulation results and comparisons with laboratory weld observations demonstrate microstructural variation with weld speed, pool shape, and pulsed-power.« less

  14. A Monte Carlo model for 3D grain evolution during welding

    DOE PAGES

    Rodgers, Theron M.; Mitchell, John A.; Tikare, Veena

    2017-08-04

    Welding is one of the most wide-spread processes used in metal joining. However, there are currently no open-source software implementations for the simulation of microstructural evolution during a weld pass. Here we describe a Potts Monte Carlo based model implemented in the SPPARKS kinetic Monte Carlo computational framework. The model simulates melting, solidification and solid-state microstructural evolution of material in the fusion and heat-affected zones of a weld. The model does not simulate thermal behavior, but rather utilizes user input parameters to specify weld pool and heat-affect zone properties. Weld pool shapes are specified by Bezier curves, which allow formore » the specification of a wide range of pool shapes. Pool shapes can range from narrow and deep to wide and shallow representing different fluid flow conditions within the pool. Surrounding temperature gradients are calculated with the aide of a closest point projection algorithm. Furthermore, the model also allows simulation of pulsed power welding through time-dependent variation of the weld pool size. Example simulation results and comparisons with laboratory weld observations demonstrate microstructural variation with weld speed, pool shape, and pulsed-power.« less

  15. A calibrated Monte Carlo approach to quantify the impacts of misorientation and different driving forces on texture development

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

    Liangzhe Zhang; Anthony D. Rollett; Timothy Bartel

    2012-02-01

    A calibrated Monte Carlo (cMC) approach, which quantifies grain boundary kinetics within a generic setting, is presented. The influence of misorientation is captured by adding a scaling coefficient in the spin flipping probability equation, while the contribution of different driving forces is weighted using a partition function. The calibration process relies on the established parametric links between Monte Carlo (MC) and sharp-interface models. The cMC algorithm quantifies microstructural evolution under complex thermomechanical environments and remedies some of the difficulties associated with conventional MC models. After validation, the cMC approach is applied to quantify the texture development of polycrystalline materials withmore » influences of misorientation and inhomogeneous bulk energy across grain boundaries. The results are in good agreement with theory and experiments.« less

  16. CO oxidation reaction on Pt(111) studied by the dynamic Monte Carlo method including lateral interactions of adsorbates.

    PubMed

    Nagasaka, Masanari; Kondoh, Hiroshi; Nakai, Ikuyo; Ohta, Toshiaki

    2007-01-28

    The dynamics of adsorbate structures during CO oxidation on Pt(111) surfaces and its effects on the reaction were studied by the dynamic Monte Carlo method including lateral interactions of adsorbates. The lateral interaction energies between adsorbed species were calculated by the density functional theory method. Dynamic Monte Carlo simulations were performed for the oxidation reaction over a mesoscopic scale, where the experimentally determined activation energies of elementary paths were altered by the calculated lateral interaction energies. The simulated results reproduced the characteristics of the microscopic and mesoscopic scale adsorbate structures formed during the reaction, and revealed that the complicated reaction kinetics is comprehensively explained by a single reaction path affected by the surrounding adsorbates. We also propose from the simulations that weakly adsorbed CO molecules at domain boundaries promote the island-periphery specific reaction.

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

    NASA Astrophysics Data System (ADS)

    Gorji, M. Hossein; Jenny, Patrick

    2013-06-01

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

  18. Parallel and Portable Monte Carlo Particle Transport

    NASA Astrophysics Data System (ADS)

    Lee, S. R.; Cummings, J. C.; Nolen, S. D.; Keen, N. D.

    1997-08-01

    We have developed a multi-group, Monte Carlo neutron transport code in C++ using object-oriented methods and the Parallel Object-Oriented Methods and Applications (POOMA) class library. This transport code, called MC++, currently computes k and α eigenvalues of the neutron transport equation on a rectilinear computational mesh. It is portable to and runs in parallel on a wide variety of platforms, including MPPs, clustered SMPs, and individual workstations. It contains appropriate classes and abstractions for particle transport and, through the use of POOMA, for portable parallelism. Current capabilities are discussed, along with physics and performance results for several test problems on a variety of hardware, including all three Accelerated Strategic Computing Initiative (ASCI) platforms. Current parallel performance indicates the ability to compute α-eigenvalues in seconds or minutes rather than days or weeks. Current and future work on the implementation of a general transport physics framework (TPF) is also described. This TPF employs modern C++ programming techniques to provide simplified user interfaces, generic STL-style programming, and compile-time performance optimization. Physics capabilities of the TPF will be extended to include continuous energy treatments, implicit Monte Carlo algorithms, and a variety of convergence acceleration techniques such as importance combing.

  19. Liquefaction chemistry and kinetics: Hydrogen utilization studies

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

    Rothenberger, K.S.; Warzinski, R.P.; Cugini, A.V.

    1995-12-31

    The objectives of this project are to investigate the chemistry and kinetics that occur in the initial stages of coal liquefaction and to determine the effects of hydrogen pressure, catalyst activity, and solvent type on the quantity and quality of the products produced. The project comprises three tasks: (1) preconversion chemistry and kinetics, (2) hydrogen utilization studies, and (3) assessment of kinetic models for liquefaction. The hydrogen utilization studies work will be the main topic of this report. However, the other tasks are briefly described.

  20. A Multi-Objective Optimization Technique to Model the Pareto Front of Organic Dielectric Polymers

    NASA Astrophysics Data System (ADS)

    Gubernatis, J. E.; Mannodi-Kanakkithodi, A.; Ramprasad, R.; Pilania, G.; Lookman, T.

    Multi-objective optimization is an area of decision making that is concerned with mathematical optimization problems involving more than one objective simultaneously. Here we describe two new Monte Carlo methods for this type of optimization in the context of their application to the problem of designing polymers with more desirable dielectric and optical properties. We present results of applying these Monte Carlo methods to a two-objective problem (maximizing the total static band dielectric constant and energy gap) and a three objective problem (maximizing the ionic and electronic contributions to the static band dielectric constant and energy gap) of a 6-block organic polymer. Our objective functions were constructed from high throughput DFT calculations of 4-block polymers, following the method of Sharma et al., Nature Communications 5, 4845 (2014) and Mannodi-Kanakkithodi et al., Scientific Reports, submitted. Our high throughput and Monte Carlo methods of analysis extend to general N-block organic polymers. This work was supported in part by the LDRD DR program of the Los Alamos National Laboratory and in part by a Multidisciplinary University Research Initiative (MURI) Grant from the Office of Naval Research.

  1. SABRINA: an interactive solid geometry modeling program for Monte Carlo

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

    West, J.T.

    SABRINA is a fully interactive three-dimensional geometry modeling program for MCNP. In SABRINA, a user interactively constructs either body geometry, or surface geometry models, and interactively debugs spatial descriptions for the resulting objects. This enhanced capability significantly reduces the effort in constructing and debugging complicated three-dimensional geometry models for Monte Carlo Analysis.

  2. Fixed-node quantum Monte Carlo

    NASA Astrophysics Data System (ADS)

    Anderson, James B.

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

  3. Polychromatic wave-optics models for image-plane speckle. 2. Unresolved objects.

    PubMed

    Van Zandt, Noah R; Spencer, Mark F; Steinbock, Michael J; Anderson, Brian M; Hyde, Milo W; Fiorino, Steven T

    2018-05-20

    Polychromatic laser light can reduce speckle noise in many wavefront-sensing and imaging applications. To help quantify the achievable reduction in speckle noise, this study investigates the accuracy of three polychromatic wave-optics models under the specific conditions of an unresolved object. Because existing theory assumes a well-resolved object, laboratory experiments are used to evaluate model accuracy. The three models use Monte-Carlo averaging, depth slicing, and spectral slicing, respectively, to simulate the laser-object interaction. The experiments involve spoiling the temporal coherence of laser light via a fiber-based, electro-optic modulator. After the light scatters off of the rough object, speckle statistics are measured. The Monte-Carlo method is found to be highly inaccurate, while depth-slicing error peaks at 7.8% but is generally much lower in comparison. The spectral-slicing method is the most accurate, always producing results within the error bounds of the experiment.

  4. Kinetic Monte Carlo simulation of self-organized pattern formation induced by ion beam sputtering using crater functions

    NASA Astrophysics Data System (ADS)

    Yang, Zhangcan; Lively, Michael A.; Allain, Jean Paul

    2015-02-01

    The production of self-organized nanostructures by ion beam sputtering has been of keen interest to researchers for many decades. Despite numerous experimental and theoretical efforts to understand ion-induced nanostructures, there are still many basic questions open to discussion, such as the role of erosion or curvature-dependent sputtering. In this work, a hybrid MD/kMC (molecular dynamics/kinetic Monte Carlo) multiscale atomistic model is developed to investigate these knowledge gaps, and its predictive ability is validated across the experimental parameter space. This model uses crater functions, which were obtained from MD simulations, to model the prompt mass redistribution due to single-ion impacts. Defect migration, which is missing from previous models that use crater functions, is treated by a kMC Arrhenius method. Using this model, a systematic study was performed for silicon bombarded by Ar+ ions of various energies (100 eV, 250 eV, 500 eV, 700 eV, and 1000 eV) at incidence angles of 0∘ to 80∘. The simulation results were compared with experimental findings, showing good agreement in many aspects of surface evolution, such as the phase diagram. The underestimation of the ripple wavelength by the simulations suggests that surface diffusion is not the main smoothening mechanism for ion-induced pattern formation. Furthermore, the simulated results were compared with moment-description continuum theory and found to give better results, as the simulation did not suffer from the same mathematical inconsistencies as the continuum model. The key finding was that redistributive effects are dominant in the formation of flat surfaces and parallel-mode ripples, but erosive effects are dominant at high angles when perpendicular-mode ripples are formed. Ion irradiation with simultaneous sample rotation was also simulated, resulting in arrays of square-ordered dots. The patterns obtained from sample rotation were strongly correlated to the rotation speed and to

  5. Uncertainty Optimization Applied to the Monte Carlo Analysis of Planetary Entry Trajectories

    NASA Technical Reports Server (NTRS)

    Olds, John; Way, David

    2001-01-01

    Recently, strong evidence of liquid water under the surface of Mars and a meteorite that might contain ancient microbes have renewed interest in Mars exploration. With this renewed interest, NASA plans to send spacecraft to Mars approx. every 26 months. These future spacecraft will return higher-resolution images, make precision landings, engage in longer-ranging surface maneuvers, and even return Martian soil and rock samples to Earth. Future robotic missions and any human missions to Mars will require precise entries to ensure safe landings near science objective and pre-employed assets. Potential sources of water and other interesting geographic features are often located near hazards, such as within craters or along canyon walls. In order for more accurate landings to be made, spacecraft entering the Martian atmosphere need to use lift to actively control the entry. This active guidance results in much smaller landing footprints. Planning for these missions will depend heavily on Monte Carlo analysis. Monte Carlo trajectory simulations have been used with a high degree of success in recent planetary exploration missions. These analyses ascertain the impact of off-nominal conditions during a flight and account for uncertainty. Uncertainties generally stem from limitations in manufacturing tolerances, measurement capabilities, analysis accuracies, and environmental unknowns. Thousands of off-nominal trajectories are simulated by randomly dispersing uncertainty variables and collecting statistics on forecast variables. The dependability of Monte Carlo forecasts, however, is limited by the accuracy and completeness of the assumed uncertainties. This is because Monte Carlo analysis is a forward driven problem; beginning with the input uncertainties and proceeding to the forecasts outputs. It lacks a mechanism to affect or alter the uncertainties based on the forecast results. If the results are unacceptable, the current practice is to use an iterative, trial

  6. Monte Carlo method for computing density of states and quench probability of potential energy and enthalpy landscapes.

    PubMed

    Mauro, John C; Loucks, Roger J; Balakrishnan, Jitendra; Raghavan, Srikanth

    2007-05-21

    The thermodynamics and kinetics of a many-body system can be described in terms of a potential energy landscape in multidimensional configuration space. The partition function of such a landscape can be written in terms of a density of states, which can be computed using a variety of Monte Carlo techniques. In this paper, a new self-consistent Monte Carlo method for computing density of states is described that uses importance sampling and a multiplicative update factor to achieve rapid convergence. The technique is then applied to compute the equilibrium quench probability of the various inherent structures (minima) in the landscape. The quench probability depends on both the potential energy of the inherent structure and the volume of its corresponding basin in configuration space. Finally, the methodology is extended to the isothermal-isobaric ensemble in order to compute inherent structure quench probabilities in an enthalpy landscape.

  7. Kinetics of Lipofuscin Formation in Aging Retinal Pigment Epithelium Cells

    NASA Astrophysics Data System (ADS)

    Family, Fereydoon; Mazzitello, K. I.; Arizmendi, C. M.; Grossniklaus, Hans E.

    2010-03-01

    Lipofuscin is a deposit that is formed over time by aggregation and clustering of incompletely degraded membrane material in various types of cells. Lipofuscin is made of free-radical-damaged protein and fat and is known to be present in age- related macular dgeneration (AMD), Alzheimer disease, and Parkinson disease. AMD is the leading cause of blindness in adults. The degradation of retinal pigment epithelium cells (RPE) through accumulation of lipsofuscin is considered a significant pathogenic factor in the development of AMD. We will present the results of a study of the kinetics of lipofuscin growth in RPE cells using Kinetic Monte Carlo simulations and scaling theory on a cluster aggregation model. The model captures the essential physics of lipofuscin growth in the cells. A remarkable feature is that small particles may be removed from the cells while the larger ones become fixed and grow by aggregation. We compare our results with the number of lipofuscin granules in eyes with early age-related degeneration.

  8. Sodium dopants in helium clusters: Structure, equilibrium and submersion kinetics

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

    Calvo, F.

    Alkali impurities bind to helium nanodroplets very differently depending on their size and charge state, large neutral or charged dopants being wetted by the droplet whereas small neutral impurities prefer to reside aside. Using various computational modeling tools such as quantum Monte Carlo and path-integral molecular dynamics simulations, we have revisited some aspects of the physical chemistry of helium droplets interacting with sodium impurities, including the onset of snowball formation in presence of many-body polarization forces, the transition from non-wetted to wetted behavior in larger sodium clusters, and the kinetics of submersion of small dopants after sudden ionization.

  9. Collective translational and rotational Monte Carlo cluster move for general pairwise interaction

    NASA Astrophysics Data System (ADS)

    Růžička, Štěpán; Allen, Michael P.

    2014-09-01

    Virtual move Monte Carlo is a cluster algorithm which was originally developed for strongly attractive colloidal, molecular, or atomistic systems in order to both approximate the collective dynamics and avoid sampling of unphysical kinetic traps. In this paper, we present the algorithm in the form, which selects the moving cluster through a wider class of virtual states and which is applicable to general pairwise interactions, including hard-core repulsion. The newly proposed way of selecting the cluster increases the acceptance probability by up to several orders of magnitude, especially for rotational moves. The results have their applications in simulations of systems interacting via anisotropic potentials both to enhance the sampling of the phase space and to approximate the dynamics.

  10. Kinetic Model of Photoautotrophic Growth of Chlorella sp. Microalga, Isolated from the Setúbal Lagoon.

    PubMed

    Heinrich, Josué Miguel; Irazoqui, Horacio Antonio

    2015-01-01

    In this work, a kinetic expression relating light availability in the culture medium with the rate of microalgal growth is obtained. This expression, which is valid for low illumination conditions, was derived from the reactions that take part in the light-dependent stage of photosynthesis. The kinetic expression obtained is a function of the biomass concentration in the culture, as well as of the local volumetric rate of absorption of photons, and only includes two adjustable parameters. To determine the value of these parameters and to test the validity of the hypotheses made, autotrophic cultures of the Chlorella sp. strain were carried out in a modified BBM medium at three CO2 concentrations in the gas stream, namely 0.034%, 0.34% and 3.4%. Moreover, the local volumetric rate of photon absorption was predicted based on a physical model of the interaction of the radiant energy with the suspended biomass, together with a Monte Carlo simulation algorithm. The proposed intrinsic expression of the biomass growth rate, together with the Monte Carlo radiation field simulator, are key to scale up photobioreactors when operating under low irradiation conditions, independently of the configuration of the reactor and of its light source. © 2015 The American Society of Photobiology.

  11. Diffusion reordering kinetics in lattice-gas systems: Time evolution of configurational entropy and internal energy

    NASA Astrophysics Data System (ADS)

    Weinketz, Sieghard

    1998-07-01

    The reordering kinetics of a diffusion lattice-gas system of adsorbates with nearest- and next-nearest-neighbor interactions on a square lattice is studied within a dynamic Monte Carlo simulation, as it evolves towards the equilibrium from a given initial configuration, at a constant temperature. The diffusion kinetics proceeds through adsorbate hoppings to empty nearest-neighboring sites (Kawasaki dynamics). The Monte Carlo procedure allows a ``real'' time definition from the local transition rates, and the configurational entropy and internal energy can be obtained from the lattice configuration at any instant t by counting the local clusters and using the C2 approximation of the cluster variation method. These state functions are then used in their nonequilibrium form as a direct measure of reordering along the time. Different reordering processes are analyzed within this approach, presenting a rich variety of behaviors. It can also be shown that the time derivative of entropy (times temperature) is always equal to or lower than the time derivative of energy, and that the reordering path is always strongly dependent on the initial order, presenting in some cases an ``invariance'' of the entropy function to the magnitude of the interactions as far as the final order is unaltered.

  12. A determination of relativistic shock jump conditions using Monte Carlo techniques

    NASA Technical Reports Server (NTRS)

    Ellison, Donald C.; Reynolds, Stephen P.

    1991-01-01

    Monte Carlo techniques are used, assuming isotropic elastic scattering of all particles, to calculate jump conditions in parallel relativistic collisionless shocks in the absence of Fermi acceleration. The shock velocity and compression ratios are shown for arbitrary flow velocities and for any upstream temperature. Both single-component electron-positron plasma and two-component proton-electron plasmas are considered. It is shown that protons and electrons must share energy, directly or through the mediation of plasma waves, in order to satisfy the basic conservation conditions, and the electron and proton temperatures are determined for a particular microscopic, kinetic-theory model, namely, that protons always scatter elastically. The results are directly applicable to shocks in which waves of scattering superthermal particles are absent.

  13. Kinetic Damage from Meteorites

    NASA Technical Reports Server (NTRS)

    Cooke, William; Brown, Peter; Matney, Mark

    2017-01-01

    A Near Earth object impacting into Earth's atmosphere may produce damaging effects at the surface due to airblast, thermal pulse, or kinetic impact in the form of meteorites. At large sizes (>many tens of meters), the damage is amplified by the hypersonic impact of these large projectiles moving with cosmic velocity, leaving explosively produced craters. However, much more common is simple "kinetic" damage caused by the impact of smaller meteorites moving at terminal speeds. As of this date a handful of instances are definitively known of people or structures being directly hit and/or damaged by the kinetic impact of meteorites. Meteorites known to have struck humans include the Sylacauga, Alabama fall (1954) and the Mbale meteorite fall (1992). Much more common is kinetic meteorite damage to cars, buildings, and even a post box (Claxton, Georgia - 1984). Historical accounts indicate that direct kinetic damage by meteorites may be more common than recent accounts suggest (Yau et al., 1994). In this talk we will examine the contemporary meteorite flux and estimate the frequency of kinetic damage to various structures, as well as how the meteorite flux might affect the rate of human casualties. This will update an earlier study by Halliday et al (1985), adding variations expected in meteorite flux with latitude (Le Feuvre and Wieczorek, 2008) and validating these model predictions of speed and entry angle with observations from the NASA and SOMN fireball networks. In particular, we explore the physical characteristics of bright meteors which may be used as a diagnostic for estimating which fireballs produce meteorites and hence how early warning of such kinetic damage may be estimated in advance through observations and modelling.

  14. Kinetic Damage from Meteorites

    NASA Technical Reports Server (NTRS)

    Cooke, William; Brown, Peter; Matney, Mark

    2017-01-01

    A Near Earth object impacting into Earth's atmosphere may produce damaging effects at the surface due to airblast, thermal pulse, or kinetic impact in the form of meteorites. At large sizes (greater than many tens of meters), the damage is amplified by the hypersonic impact of these large projectiles moving with cosmic velocity, leaving explosively produced craters. However, much more common is simple "kinetic" damage caused by the impact of smaller meteorites moving at terminal speeds. As of this date a handful of instances are definitively known of people or structures being directly hit and/or damaged by the kinetic impact of meteorites. Meteorites known to have struck humans include the Sylacauga, Alabama fall (1954) and the Mbale meteorite fall (1992). Much more common is kinetic meteorite damage to cars, buildings, and even a post box (Claxton, Georgia - 1984). Historical accounts indicate that direct kinetic damage by meteorites may be more common than recent accounts suggest (Yau et al., 1994). In this talk we will examine the contemporary meteorite flux and estimate the frequency of kinetic damage to various structures, as well as how the meteorite flux might affect the rate of human casualties. This will update an earlier study by Halliday et al (1985), adding variations expected in meteorite flux with latitude (Le Feuvre and Wieczorek, 2008) and validating these model predictions of speed and entry angle with observations from the NASA and SOMN fireball networks. In particular, we explore the physical characteristics of bright meteors which may be used as a diagnostic for estimating which fireballs produce meteorites and hence how early warning of such kinetic damage may be estimated in advance through observations and modeling.

  15. A computational atomistic study of the relaxation of ion-bombarded c-Si on experimental time-scales: an application of the kinetic Activation Relaxation Technique

    NASA Astrophysics Data System (ADS)

    Béland, Laurent Karim; Mousseau, Normand

    2012-02-01

    The kinetic activation relaxation technique (kinetic ART) method, an off-lattice, self-learning kinetic Monte Carlo (KMC) algorithm with on-the-fly event search,ootnotetextL. K. B'eland, P. Brommer, F. El-Mellouhi, J.-F. Joly and N. Mousseau, Phys. Rev. E 84, 046704 (2011). is used to study the relaxation of c-Si after Si^- bombardment at 3 keV. We describe the evolution of the damaged areas at room-temperature and above for periods of the order of seconds, treating long-range elastic deformations exactly. We assess the stability of the nanoscale structures formed by the damage cascade and the mechanisms that govern post-implantation annealing.

  16. (U) Introduction to Monte Carlo Methods

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

    Hungerford, Aimee L.

    2017-03-20

    Monte Carlo methods are very valuable for representing solutions to particle transport problems. Here we describe a “cook book” approach to handling the terms in a transport equation using Monte Carlo methods. Focus is on the mechanics of a numerical Monte Carlo code, rather than the mathematical foundations of the method.

  17. Mission Analysis, Operations, and Navigation Toolkit Environment (Monte) Version 040

    NASA Technical Reports Server (NTRS)

    Sunseri, Richard F.; Wu, Hsi-Cheng; Evans, Scott E.; Evans, James R.; Drain, Theodore R.; Guevara, Michelle M.

    2012-01-01

    Monte is a software set designed for use in mission design and spacecraft navigation operations. The system can process measurement data, design optimal trajectories and maneuvers, and do orbit determination, all in one application. For the first time, a single software set can be used for mission design and navigation operations. This eliminates problems due to different models and fidelities used in legacy mission design and navigation software. The unique features of Monte 040 include a blowdown thruster model for GRAIL (Gravity Recovery and Interior Laboratory) with associated pressure models, as well as an updated, optimalsearch capability (COSMIC) that facilitated mission design for ARTEMIS. Existing legacy software lacked the capabilities necessary for these two missions. There is also a mean orbital element propagator and an osculating to mean element converter that allows long-term orbital stability analysis for the first time in compiled code. The optimized trajectory search tool COSMIC allows users to place constraints and controls on their searches without any restrictions. Constraints may be user-defined and depend on trajectory information either forward or backwards in time. In addition, a long-term orbit stability analysis tool (morbiter) existed previously as a set of scripts on top of Monte. Monte is becoming the primary tool for navigation operations, a core competency at JPL. The mission design capabilities in Monte are becoming mature enough for use in project proposals as well as post-phase A mission design. Monte has three distinct advantages over existing software. First, it is being developed in a modern paradigm: object- oriented C++ and Python. Second, the software has been developed as a toolkit, which allows users to customize their own applications and allows the development team to implement requirements quickly, efficiently, and with minimal bugs. Finally, the software is managed in accordance with the CMMI (Capability Maturity Model

  18. Quantum Gibbs ensemble Monte Carlo

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

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

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

  19. Comparison of shock structure solutions using independent continuum and kinetic theory approaches

    NASA Technical Reports Server (NTRS)

    Fiscko, Kurt A.; Chapman, Dean R.

    1988-01-01

    A vehicle traversing the atmosphere will experience flight regimes at high altitudes in which the thickness of a hypersonic shock wave is not small compared to the shock standoff distance from the hard body. When this occurs, it is essential to compute accurate flow field solutions within the shock structure. In this paper, one-dimensional shock structure is investigated for various monatomic gases from Mach 1.4 to Mach 35. Kinetic theory solutions are computed using the Direct Simulation Monte Carlo method. Steady-state solutions of the Navier-Stokes equations and of a slightly truncated form of the Burnett equations are determined by relaxation to a steady state of the time-dependent continuum equations. Monte Carlo results are in excellent agreement with published experimental data and are used as bases of comparison for continuum solutions. For a Maxwellian gas, the truncated Burnett equations are shown to produce far more accurate solutions of shock structure than the Navier-Stokes equations.

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

    NASA Astrophysics Data System (ADS)

    Alexander, Andrew William

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

  1. On the definition of a Monte Carlo model for binary crystal growth.

    PubMed

    Los, J H; van Enckevort, W J P; Meekes, H; Vlieg, E

    2007-02-01

    We show that consistency of the transition probabilities in a lattice Monte Carlo (MC) model for binary crystal growth with the thermodynamic properties of a system does not guarantee the MC simulations near equilibrium to be in agreement with the thermodynamic equilibrium phase diagram for that system. The deviations remain small for systems with small bond energies, but they can increase significantly for systems with large melting entropy, typical for molecular systems. These deviations are attributed to the surface kinetics, which is responsible for a metastable zone below the liquidus line where no growth occurs, even in the absence of a 2D nucleation barrier. Here we propose an extension of the MC model that introduces a freedom of choice in the transition probabilities while staying within the thermodynamic constraints. This freedom can be used to eliminate the discrepancy between the MC simulations and the thermodynamic equilibrium phase diagram. Agreement is achieved for that choice of the transition probabilities yielding the fastest decrease of the free energy (i.e., largest growth rate) of the system at a temperature slightly below the equilibrium temperature. An analytical model is developed, which reproduces quite well the MC results, enabling a straightforward determination of the optimal set of transition probabilities. Application of both the MC and analytical model to conditions well away from equilibrium, giving rise to kinetic phase diagrams, shows that the effect of kinetics on segregation is even stronger than that predicted by previous models.

  2. Kinetic phase transitions and reactive windows in reactions of monomers on two-dimensional lattices

    NASA Astrophysics Data System (ADS)

    Cortés, Joaquín; Puschmann, Heinrich; Valencia, Eliana

    1997-01-01

    Some conceptual considerations are made and Monte Carlo simulation studies are carried out to analyze a series of catalytic reactions of two and three monomers on a square lattice of sites. Two aspects are considered: The increase in the system's degrees of freedom, leading to the formation of reactive sites that allow a change in the character of one of the kinetic phase transitions from the first order to a second order transition, and the classification and reactivity of the new system class.

  3. Three-dimensional Monte Carlo model of pulsed-laser treatment of cutaneous vascular lesions

    NASA Astrophysics Data System (ADS)

    Milanič, Matija; Majaron, Boris

    2011-12-01

    We present a three-dimensional Monte Carlo model of optical transport in skin with a novel approach to treatment of side boundaries of the volume of interest. This represents an effective way to overcome the inherent limitations of ``escape'' and ``mirror'' boundary conditions and enables high-resolution modeling of skin inclusions with complex geometries and arbitrary irradiation patterns. The optical model correctly reproduces measured values of diffuse reflectance for normal skin. When coupled with a sophisticated model of thermal transport and tissue coagulation kinetics, it also reproduces realistic values of radiant exposure thresholds for epidermal injury and for photocoagulation of port wine stain blood vessels in various skin phototypes, with or without application of cryogen spray cooling.

  4. Shape transitions in strained Cu islands on Ni(100): kinetics versus energetics

    NASA Astrophysics Data System (ADS)

    Shim, Yunsic; Amar, Jacques

    2012-02-01

    We examine the shape transition from compact to ramified islands observed in submonolayer Cu/Ni(100) growth. Recently, it has been argued that this transition is not due to a growth instability but can be understood in terms of energetic arguments. In order to determine the responsible mechanisms we have carried out energetics calculations as well as temperature-accelerated dynamics (TAD) and kinetic Monte Carlo (KMC) simulations. Our results indicate that the shape transition cannot be explained by equilibrium arguments, but is instead due to kinetic effects which are mediated by strain. In particular, by calculating the relevant line-tension and strain energies, we find that the equilibrium critical island-width is at least four orders of magnitude larger than the experimentally observed arm-width. In contrast, our TAD simulations indicate that unexpected concerted motions occurring at step edges are responsible. The energy barriers for these concerted motions decrease with increasing island size and appear to saturate for islands larger than 300 - 400 atoms. By including these strain-induced kinetic processes in our KMC simulations of island-growth, we have been able to explain both the temperature- and coverage-dependence of the island morphology.

  5. Discrete range clustering using Monte Carlo methods

    NASA Technical Reports Server (NTRS)

    Chatterji, G. B.; Sridhar, B.

    1993-01-01

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

  6. A new class of enhanced kinetic sampling methods for building Markov state models

    NASA Astrophysics Data System (ADS)

    Bhoutekar, Arti; Ghosh, Susmita; Bhattacharya, Swati; Chatterjee, Abhijit

    2017-10-01

    Markov state models (MSMs) and other related kinetic network models are frequently used to study the long-timescale dynamical behavior of biomolecular and materials systems. MSMs are often constructed bottom-up using brute-force molecular dynamics (MD) simulations when the model contains a large number of states and kinetic pathways that are not known a priori. However, the resulting network generally encompasses only parts of the configurational space, and regardless of any additional MD performed, several states and pathways will still remain missing. This implies that the duration for which the MSM can faithfully capture the true dynamics, which we term as the validity time for the MSM, is always finite and unfortunately much shorter than the MD time invested to construct the model. A general framework that relates the kinetic uncertainty in the model to the validity time, missing states and pathways, network topology, and statistical sampling is presented. Performing additional calculations for frequently-sampled states/pathways may not alter the MSM validity time. A new class of enhanced kinetic sampling techniques is introduced that aims at targeting rare states/pathways that contribute most to the uncertainty so that the validity time is boosted in an effective manner. Examples including straightforward 1D energy landscapes, lattice models, and biomolecular systems are provided to illustrate the application of the method. Developments presented here will be of interest to the kinetic Monte Carlo community as well.

  7. Catastrophic Disruption Threshold and Maximum Deflection from Kinetic Impact

    NASA Astrophysics Data System (ADS)

    Cheng, A. F.

    2017-12-01

    The use of a kinetic impactor to deflect an asteroid on a collision course with Earth was described in the NASA Near-Earth Object Survey and Deflection Analysis of Alternatives (2007) as the most mature approach for asteroid deflection and mitigation. The NASA DART mission will demonstrate asteroid deflection by kinetic impact at the Potentially Hazardous Asteroid 65803 Didymos in October, 2022. The kinetic impactor approach is considered to be applicable with warning times of 10 years or more and with hazardous asteroid diameters of 400 m or less. In principle, a larger kinetic impactor bringing greater kinetic energy could cause a larger deflection, but input of excessive kinetic energy will cause catastrophic disruption of the target, leaving possibly large fragments still on collision course with Earth. Thus the catastrophic disruption threshold limits the maximum deflection from a kinetic impactor. An often-cited rule of thumb states that the maximum deflection is 0.1 times the escape velocity before the target will be disrupted. It turns out this rule of thumb does not work well. A comparison to numerical simulation results shows that a similar rule applies in the gravity limit, for large targets more than 300 m, where the maximum deflection is roughly the escape velocity at momentum enhancement factor β=2. In the gravity limit, the rule of thumb corresponds to pure momentum coupling (μ=1/3), but simulations find a slightly different scaling μ=0.43. In the smaller target size range that kinetic impactors would apply to, the catastrophic disruption limit is strength-controlled. A DART-like impactor won't disrupt any target asteroid down to significantly smaller size than the 50 m below which a hazardous object would not penetrate the atmosphere in any case unless it is unusually strong.

  8. 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…

  9. Lipid-protein interaction induced domains: Kinetics and conformational changes in multicomponent vesicles

    NASA Astrophysics Data System (ADS)

    Sreeja, K. K.; Sunil Kumar, P. B.

    2018-04-01

    The spatio-temporal organization of proteins and the associated morphological changes in membranes are of importance in cell signaling. Several mechanisms that promote the aggregation of proteins at low cell surface concentrations have been investigated in the past. We show, using Monte Carlo simulations, that the affinity of proteins for specific lipids can hasten their aggregation kinetics. The lipid membrane is modeled as a dynamically triangulated surface with the proteins defined as in-plane fields at the vertices. We show that, even at low protein concentrations, strong lipid-protein interactions can result in large protein clusters indicating a route to lipid mediated signal amplification. At high protein concentrations, the domains form buds similar to that seen in lipid-lipid interaction induced phase separation. Protein interaction induced domain budding is suppressed when proteins act as anisotropic inclusions and exhibit nematic orientational order. The kinetics of protein clustering and resulting conformational changes are shown to be significantly different for the isotropic and anisotropic curvature inducing proteins.

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

    NASA Astrophysics Data System (ADS)

    Rambalakos, Andreas

    Current federal aviation regulations in the United States and around the world mandate the need for aircraft structures to meet damage tolerance requirements through out the service life. These requirements imply that the damaged aircraft structure must maintain adequate residual strength in order to sustain its integrity that is accomplished by a continuous inspection program. The multifold objective of this research is to develop a methodology based on a direct Monte Carlo simulation process and to assess the reliability of aircraft structures. Initially, the structure is modeled as a parallel system with active redundancy comprised of elements with uncorrelated (statistically independent) strengths and subjected to an equal load distribution. Closed form expressions for the system capacity cumulative distribution function (CDF) are developed by expanding the current expression for the capacity CDF of a parallel system comprised by three elements to a parallel system comprised with up to six elements. These newly developed expressions will be used to check the accuracy of the implementation of a Monte Carlo simulation algorithm to determine the probability of failure of a parallel system comprised of an arbitrary number of statistically independent elements. The second objective of this work is to compute the probability of failure of a fuselage skin lap joint under static load conditions through a Monte Carlo simulation scheme by utilizing the residual strength of the fasteners subjected to various initial load distributions and then subjected to a new unequal load distribution resulting from subsequent fastener sequential failures. The final and main objective of this thesis is to present a methodology for computing the resulting gradual deterioration of the reliability of an aircraft structural component by employing a direct Monte Carlo simulation approach. The uncertainties associated with the time to crack initiation, the probability of crack detection, the

  11. Analysis of energy relaxation kinetics for control of the electron energy distributions in capacitively coupled RF discharges

    NASA Astrophysics Data System (ADS)

    Lee, Jung Yeol; Verboncoeur, John P.; Lee, Hae June

    2018-04-01

    The transition of electron energy probability functions (EEPFs) through the change of heating mode is an important issue in plasma science. A well-known example is that the increase of gas pressure, which was analyzed in terms of the ratio of the energy relaxation mean free path to the electrode gap distance, changes the EEPF from bi-Maxwellian to Maxwellian or Druyvesteyn. In this study, a new aspect of the temporal decay of kinetic energy during the energy relaxation time is theoretically analyzed and compared with a particle-in-cell Monte Carlo collision simulation of capacitively coupled plasmas. A fully kinetic description of electron transport and collisions shows drastic changes of EEPFs with the variation of the driving frequency due to the heating mode transition.

  12. A fully-implicit Particle-In-Cell Monte Carlo Collision code for the simulation of inductively coupled plasmas

    NASA Astrophysics Data System (ADS)

    Mattei, S.; Nishida, K.; Onai, M.; Lettry, J.; Tran, M. Q.; Hatayama, A.

    2017-12-01

    We present a fully-implicit electromagnetic Particle-In-Cell Monte Carlo collision code, called NINJA, written for the simulation of inductively coupled plasmas. NINJA employs a kinetic enslaved Jacobian-Free Newton Krylov method to solve self-consistently the interaction between the electromagnetic field generated by the radio-frequency coil and the plasma response. The simulated plasma includes a kinetic description of charged and neutral species as well as the collision processes between them. The algorithm allows simulations with cell sizes much larger than the Debye length and time steps in excess of the Courant-Friedrichs-Lewy condition whilst preserving the conservation of the total energy. The code is applied to the simulation of the plasma discharge of the Linac4 H- ion source at CERN. Simulation results of plasma density, temperature and EEDF are discussed and compared with optical emission spectroscopy measurements. A systematic study of the energy conservation as a function of the numerical parameters is presented.

  13. Fully kinetic simulations of magnetic reconnection in partially ionised gases

    NASA Astrophysics Data System (ADS)

    Innocenti, M. E.; Jiang, W.; Lapenta, G.; Markidis, S.

    2016-12-01

    Magnetic reconnection has been explored for decades as a way to convert magnetic energy into kinetic energy and heat and to accelerate particles in environments as different as the solar surface, planetary magnetospheres, the solar wind, accretion disks, laboratory plasmas. When studying reconnection via simulations, it is usually assumed that the plasma is fully ionised, as it is indeed the case in many of the above-mentioned cases. There are, however, exceptions, the most notable being the lower solar atmosphere. Small ionisation fractions are registered also in the warm neutral interstellar medium, in dense interstellar clouds, in protostellar and protoplanetary accreditation disks, in tokamak edge plasmas and in ad-hoc laboratory experiments [1]. We study here how magnetic reconnection is modified by the presence of a neutral background, i.e. when the majority of the gas is not ionised. The ionised plasma is simulated with the fully kinetic Particle-In-Cell (PIC) code iPic3D [2]. Collisions with the neutral background are introduced via a Monte Carlo plug-in. The standard Monte Carlo procedure [3] is employed to account for elastic, excitation and ionization electron-neutral collisions, as well as for elastic scattering and charge exchange ion-neutral collisions. Collisions with the background introduce resistivity in an otherwise collisionless plasma and modifications of the particle distribution functions: particles (and ions at a faster rate) tend to thermalise to the background. To pinpoint the consequences of this, we compare reconnection simulations with and without background. References [1] E E Lawrence et al. Physical review letters, 110(1):015001, 2013. [2] S Markidis et al. Mathematics and Computers in Simulation, 80(7):1509-1519, 2010. [3] K Nanbu. IEEE Transactions on plasma science, 28(3):971-990, 2000.

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

    NASA Astrophysics Data System (ADS)

    Goldsworthy, M. J.

    2012-10-01

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

  15. Microstructure engineering of Pt-Al alloy thin films through Monte Carlo simulations

    NASA Astrophysics Data System (ADS)

    Harris, R. A.; Terblans, J. J.; Swart, H. C.

    2014-06-01

    A kinetic algorithm, based on the regular solution model, was used in conjunction with the Monte Carlo method to simulate the evolution of a micro-scaled thin film system during exposure to a high temperature environment. Pt-Al thin films were prepared via electron beam physical vapor deposition (EB-PVD) with an atomic concentration ratio of Pt63:Al37. These films were heat treated at an annealing temperature of 400 °C for 16 and 49 minutes. Scanning Auger Microscopy (SAM) (PHI 700) was used to obtain elemental maps while sputtering through the thin films. Simulations were run for the same annealing temperatures and thin-film composition. From these simulations theoretical depth profiles and simulated microstructures were obtained. These were compared to the experimentally measured depth profiles and elemental maps.

  16. Self-learning Monte Carlo method

    DOE PAGES

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

    2017-01-04

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

  17. Beyond mean-field approximations for accurate and computationally efficient models of on-lattice chemical kinetics

    NASA Astrophysics Data System (ADS)

    Pineda, M.; Stamatakis, M.

    2017-07-01

    Modeling the kinetics of surface catalyzed reactions is essential for the design of reactors and chemical processes. The majority of microkinetic models employ mean-field approximations, which lead to an approximate description of catalytic kinetics by assuming spatially uncorrelated adsorbates. On the other hand, kinetic Monte Carlo (KMC) methods provide a discrete-space continuous-time stochastic formulation that enables an accurate treatment of spatial correlations in the adlayer, but at a significant computation cost. In this work, we use the so-called cluster mean-field approach to develop higher order approximations that systematically increase the accuracy of kinetic models by treating spatial correlations at a progressively higher level of detail. We further demonstrate our approach on a reduced model for NO oxidation incorporating first nearest-neighbor lateral interactions and construct a sequence of approximations of increasingly higher accuracy, which we compare with KMC and mean-field. The latter is found to perform rather poorly, overestimating the turnover frequency by several orders of magnitude for this system. On the other hand, our approximations, while more computationally intense than the traditional mean-field treatment, still achieve tremendous computational savings compared to KMC simulations, thereby opening the way for employing them in multiscale modeling frameworks.

  18. Bayesian statistics and Monte Carlo methods

    NASA Astrophysics Data System (ADS)

    Koch, K. R.

    2018-03-01

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

  19. Accelerated Monte Carlo Methods for Coulomb Collisions

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

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

  20. Nonlinear Monte Carlo model of superdiffusive shock acceleration with magnetic field amplification

    NASA Astrophysics Data System (ADS)

    Bykov, Andrei M.; Ellison, Donald C.; Osipov, Sergei M.

    2017-03-01

    Fast collisionless shocks in cosmic plasmas convert their kinetic energy flow into the hot downstream thermal plasma with a substantial fraction of energy going into a broad spectrum of superthermal charged particles and magnetic fluctuations. The superthermal particles can penetrate into the shock upstream region producing an extended shock precursor. The cold upstream plasma flow is decelerated by the force provided by the superthermal particle pressure gradient. In high Mach number collisionless shocks, efficient particle acceleration is likely coupled with turbulent magnetic field amplification (MFA) generated by the anisotropic distribution of accelerated particles. This anisotropy is determined by fast particle transport, making the problem strongly nonlinear and multiscale. Here, we present a nonlinear Monte Carlo model of collisionless shock structure with superdiffusive propagation of high-energy Fermi accelerated particles coupled to particle acceleration and MFA, which affords a consistent description of strong shocks. A distinctive feature of the Monte Carlo technique is that it includes the full angular anisotropy of the particle distribution at all precursor positions. The model reveals that the superdiffusive transport of energetic particles (i.e., Lévy-walk propagation) generates a strong quadruple anisotropy in the precursor particle distribution. The resultant pressure anisotropy of the high-energy particles produces a nonresonant mirror-type instability that amplifies compressible wave modes with wavelengths longer than the gyroradii of the highest-energy protons produced by the shock.

  1. SU-C-209-05: Monte Carlo Model of a Prototype Backscatter X-Ray (BSX) Imager for Projective and Selective Object-Plane Imaging

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

    Rolison, L; Samant, S; Baciak, J

    Purpose: To develop a Monte Carlo N-Particle (MCNP) model for the validation of a prototype backscatter x-ray (BSX) imager, and optimization of BSX technology for medical applications, including selective object-plane imaging. Methods: BSX is an emerging technology that represents an alternative to conventional computed tomography (CT) and projective digital radiography (DR). It employs detectors located on the same side as the incident x-ray source, making use of backscatter and avoiding ring geometry to enclose the imaging object. Current BSX imagers suffer from low spatial resolution. A MCNP model was designed to replicate a BSX prototype used for flaw detection inmore » industrial materials. This prototype consisted of a 1.5mm diameter 60kVp pencil beam surrounded by a ring of four 5.0cm diameter NaI scintillation detectors. The imaging phantom consisted of a 2.9cm thick aluminum plate with five 0.6cm diameter holes drilled halfway. The experimental image was created using a raster scanning motion (in 1.5mm increments). Results: A qualitative comparison between the physical and simulated images showed very good agreement with 1.5mm spatial resolution in plane perpendicular to incident x-ray beam. The MCNP model developed the concept of radiography by selective plane detection (RSPD) for BSX, whereby specific object planes can be imaged by varying kVp. 10keV increments in mean x-ray energy yielded 4mm thick slice resolution in the phantom. Image resolution in the MCNP model can be further increased by increasing the number of detectors, and decreasing raster step size. Conclusion: MCNP modelling was used to validate a prototype BSX imager and introduce the RSPD concept, allowing for selective object-plane imaging. There was very good visual agreement between the experimental and MCNP imaging. Beyond optimizing system parameters for the existing prototype, new geometries can be investigated for volumetric image acquisition in medical applications. This material

  2. On the relationships between Michaelis–Menten kinetics, reverse Michaelis–Menten kinetics, Equilibrium Chemistry Approximation kinetics and quadratic kinetics

    DOE PAGES

    Tang, J. Y.

    2015-09-03

    The Michaelis–Menten kinetics and the reverse Michaelis–Menten kinetics are two popular mathematical formulations used in many land biogeochemical models to describe how microbes and plants would respond to changes in substrate abundance. However, the criteria of when to use which of the two are often ambiguous. Here I show that these two kinetics are special approximations to the Equilibrium Chemistry Approximation kinetics, which is the first order approximation to the quadratic kinetics that solves the equation of enzyme-substrate complex exactly for a single enzyme single substrate biogeochemical reaction with the law of mass action and the assumption of quasi-steady-state formore » the enzyme-substrate complex and that the product genesis from enzyme-substrate complex is much slower than the equilibration between enzyme-substrate complexes, substrates and enzymes. In particular, I showed that the derivation of the Michaelis–Menten kinetics does not consider the mass balance constraint of the substrate, and the reverse Michaelis–Menten kinetics does not consider the mass balance constraint of the enzyme, whereas both of these constraints are taken into account in the Equilibrium Chemistry Approximation kinetics. By benchmarking against predictions from the quadratic kinetics for a wide range of substrate and enzyme concentrations, the Michaelis–Menten kinetics was found to persistently under-predict the normalized sensitivity ∂ ln v / ∂ ln k 2 + of the reaction velocity v with respect to the maximum product genesis rate k 2 +, persistently over-predict the normalized sensitivity ∂ ln v / ∂ ln k 1 + of v with respect to the intrinsic substrate affinity k 1 +, persistently over-predict the normalized sensitivity ∂ ln v / ∂ ln [ E ] T of v with respect the total enzyme concentration [ E ] T and persistently under-predict the normalized sensitivity ∂ ln v / ∂ ln [ S ] T of v with respect to the total substrate concentration [ S ] T

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

    PubMed

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

    2018-06-21

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

  4. Determination of the effective diffusivity of water in a poly (methyl methacrylate) membrane containing carbon nanotubes using kinetic Monte Carlo simulations

    NASA Astrophysics Data System (ADS)

    Mermigkis, Panagiotis G.; Tsalikis, Dimitrios G.; Mavrantzas, Vlasis G.

    2015-10-01

    A kinetic Monte Carlo (kMC) simulation algorithm is developed for computing the effective diffusivity of water molecules in a poly(methyl methacrylate) (PMMA) matrix containing carbon nanotubes (CNTs) at several loadings. The simulations are conducted on a cubic lattice to the bonds of which rate constants are assigned governing the elementary jump events of water molecules from one lattice site to another. Lattice sites belonging to PMMA domains of the membrane are assigned different rates than lattice sites belonging to CNT domains. Values of these two rate constants are extracted from available numerical data for water diffusivity within a PMMA matrix and a CNT pre-computed on the basis of independent atomistic molecular dynamics simulations, which show that water diffusivity in CNTs is 3 orders of magnitude faster than in PMMA. Our discrete-space, continuum-time kMC simulation results for several PMMA-CNT nanocomposite membranes (characterized by different values of CNT length L and diameter D and by different loadings of the matrix in CNTs) demonstrate that the overall or effective diffusivity, Deff, of water in the entire polymeric membrane is of the same order of magnitude as its diffusivity in PMMA domains and increases only linearly with the concentration C (vol. %) in nanotubes. For a constant value of the concentration C, Deff is found to vary practically linearly also with the CNT aspect ratio L/D. The kMC data allow us to propose a simple bilinear expression for Deff as a function of C and L/D that can describe the numerical data for water mobility in the membrane extremely accurately. Additional simulations with two different CNT configurations (completely random versus aligned) show that CNT orientation in the polymeric matrix has only a minor effect on Deff (as long as CNTs do not fully penetrate the membrane). We have also extensively analyzed and quantified sublinear (anomalous) diffusive phenomena over small to moderate times and correlated them

  5. Direct Monte Carlo simulation of chemical reaction systems: Simple bimolecular reactions

    NASA Astrophysics Data System (ADS)

    Piersall, Shannon D.; Anderson, James B.

    1991-07-01

    In applications to several simple reaction systems we have explored a ``direct simulation'' method for predicting and understanding the behavior of gas phase chemical reaction systems. This Monte Carlo method, originated by Bird, has been found remarkably successful in treating a number of difficult problems in rarefied dynamics. Extension to chemical reactions offers a powerful tool for treating reaction systems with nonthermal distributions, with coupled gas-dynamic and reaction effects, with emission and adsorption of radiation, and with many other effects difficult to treat in any other way. The usual differential equations of chemical kinetics are eliminated. For a bimolecular reaction of the type A+B→C+D with a rate sufficiently low to allow a continued thermal equilibrium of reactants we find that direct simulation reproduces the expected second order kinetics. Simulations for a range of temperatures yield the activation energies expected for the reaction models specified. For faster reactions under conditions leading to a depletion of energetic reactant species, the expected slowing of reaction rates and departures from equilibrium distributions are observed. The minimum sample sizes required for adequate simulations are as low as 1000 molecules for these cases. The calculations are found to be simple and straightforward for the homogeneous systems considered. Although computation requirements may be excessively high for very slow reactions, they are reasonably low for fast reactions, for which nonequilibrium effects are most important.

  6. Assessment of bioethanol yield by S. cerevisiae grown on oil palm residues: Monte Carlo simulation and sensitivity analysis.

    PubMed

    Samsudin, Mohd Dinie Muhaimin; Mat Don, Mashitah

    2015-01-01

    Oil palm trunk (OPT) sap was utilized for growth and bioethanol production by Saccharomycescerevisiae with addition of palm oil mill effluent (POME) as nutrients supplier. Maximum yield (YP/S) was attained at 0.464g bioethanol/g glucose presence in the OPT sap-POME-based media. However, OPT sap and POME are heterogeneous in properties and fermentation performance might change if it is repeated. Contribution of parametric uncertainty analysis on bioethanol fermentation performance was then assessed using Monte Carlo simulation (stochastic variable) to determine probability distributions due to fluctuation and variation of kinetic model parameters. Results showed that based on 100,000 samples tested, the yield (YP/S) ranged 0.423-0.501g/g. Sensitivity analysis was also done to evaluate the impact of each kinetic parameter on the fermentation performance. It is found that bioethanol fermentation highly depend on growth of the tested yeast. Copyright © 2014 Elsevier Ltd. All rights reserved.

  7. Neutrino oscillation parameter sampling with MonteCUBES

    NASA Astrophysics Data System (ADS)

    Blennow, Mattias; Fernandez-Martinez, Enrique

    2010-01-01

    We present MonteCUBES ("Monte Carlo Utility Based Experiment Simulator"), a software package designed to sample the neutrino oscillation parameter space through Markov Chain Monte Carlo algorithms. MonteCUBES makes use of the GLoBES software so that the existing experiment definitions for GLoBES, describing long baseline and reactor experiments, can be used with MonteCUBES. MonteCUBES consists of two main parts: The first is a C library, written as a plug-in for GLoBES, implementing the Markov Chain Monte Carlo algorithm to sample the parameter space. The second part is a user-friendly graphical Matlab interface to easily read, analyze, plot and export the results of the parameter space sampling. Program summaryProgram title: MonteCUBES (Monte Carlo Utility Based Experiment Simulator) Catalogue identifier: AEFJ_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEFJ_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public Licence No. of lines in distributed program, including test data, etc.: 69 634 No. of bytes in distributed program, including test data, etc.: 3 980 776 Distribution format: tar.gz Programming language: C Computer: MonteCUBES builds and installs on 32 bit and 64 bit Linux systems where GLoBES is installed Operating system: 32 bit and 64 bit Linux RAM: Typically a few MBs Classification: 11.1 External routines: GLoBES [1,2] and routines/libraries used by GLoBES Subprograms used:Cat Id ADZI_v1_0, Title GLoBES, Reference CPC 177 (2007) 439 Nature of problem: Since neutrino masses do not appear in the standard model of particle physics, many models of neutrino masses also induce other types of new physics, which could affect the outcome of neutrino oscillation experiments. In general, these new physics imply high-dimensional parameter spaces that are difficult to explore using classical methods such as multi-dimensional projections and minimizations, such as those

  8. Filamentary and hierarchical pictures - Kinetic energy criterion

    NASA Technical Reports Server (NTRS)

    Klypin, Anatoly A.; Melott, Adrian L.

    1992-01-01

    We present a new criterion for formation of second-generation filaments. The criterion called the kinetic energy ratio, KR, is based on comparison of peculiar velocities at different scales. We suggest that the clumpiness of the distribution in some cases might be less important than the 'coldness' or 'hotness' of the flow for formation of coherent structures. The kinetic energy ratio is analogous to the Mach number except for one essential difference. If at some scale KR is greater than 1, as estimated at the linear stage, then when fluctuations of this scale reach nonlinearity, the objects they produce must be anisotropic ('filamentary'). In the case of power-law initial spectra the kinetic ratio criterion suggests that the border line is the power-spectrum with the slope n = -1.

  9. X-ray fluorescence spectroscopy and Monte Carlo characterization of a unique nuragic artifact (Sardinia, Italy)

    NASA Astrophysics Data System (ADS)

    Brunetti, Antonio; Depalmas, Anna; di Gennaro, Francesco; Serges, Alessandra; Schiavon, Nicola

    2016-07-01

    The chemical composition of a unique bronze artifact known as the "Cesta" ("Basket") belonging to the ancient Nuragic civilization of the Island of Sardinia, Italy has been analyzed by combining X-ray Fluorescence Spectroscopy (XRF) with Monte Carlo simulations using the XRMC code. The "Cesta" had been discovered probably in the XVIII century with the first graphic representation reported around 1761. In a later draft (dated 1764), the basket has been depicted as being carried upside-down on the shoulder of a large bronze warrior Barthélemy (1761), Pinza (1901), Winckelmann (1776) . The two pictorial representations differed only by the presence of handles in the most recent one. XRF measurements revealed that the handles of the object are composed by brass while the other parts are composed by bronze suggesting the handles as being a later addition to the original object. The artifact is covered at its surface by a fairly thick corrosion patina. In order to determine the bronze bulk composition without the need for removing the outer patina, the artifact has been modeled as a two layer object in Monte Carlo simulations.

  10. Cantera and Cantera Electrolyte Thermodynamics Objects

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

    John Hewson, Harry Moffat

    Cantera is a suite of object-oriented software tools for problems involving chemical kinetics, thermodynamics, and/or transport processes. It is a multi-organizational effort to create and formulate high quality 0D and 1D constitutive modeling tools for reactive transport codes.Institutions involved with the effort include Sandia, MIT, Colorado School of Mines, U. Texas, NASA, and Oak Ridge National Labs. Specific to Sandia's contributions, the Cantera Electrolyte Thermo Objects (CETO) packages is comprised of add-on routines for Cantera that handle electrolyte thermochemistry and reactions within the overall Cantera package. Cantera is a C++ Cal Tech code that handles gas phase species transport, reaction,more » and thermodynamics. With this addition, Cantera can be extended to handle problems involving liquid phase reactions and transport in electrolyte systems, and phase equilibrium problemsinvolving concentrated electrolytes and gas/solid phases. A full treatment of molten salt thermodynamics and transport has also been implemented in CETO. The routines themselves consist of .cpp and .h files containing C++ objects that are derived from parent Cantera objects representing thermodynamic functions. They are linked unto the main Cantera libraries when requested by the user. As an addendum to the main thermodynamics objects, several utility applications are provided. The first is multiphase Gibbs free energy minimizer based on the vcs algorithm, called vcs_cantera. This code allows for the calculation of thermodynamic equilibrium in multiple phases at constant temperature and pressure. Note, a similar code capability exists already in Cantera. This version follows the same algorithm, but gas a different code-base starting point, and is used as a research tool for algorithm development. The second program, cttables, prints out tables of thermodynamic and kinetic information for thermodynamic and kinetic objects within Cantera. This program serves as a "Get the

  11. Computational study of RNA folding kinetics and thermodynamics

    NASA Astrophysics Data System (ADS)

    Morgan, Steven Robert

    RNA in its many forms is involved in the processes of protein manufacture, gene splicing, catalysis and gene regulation. It is also the store of genetic information in some viruses. The function of the RNA is determined by its structure, and it is the purpose of this thesis to investigate kinetic and thermodynamic properties of RNA secondary structures in order to obtain a better understanding of their formation and function. Our main tenet is that kinetic formation of RNA structure is necessary to explain features found in natural RNA structures, as well as aspects of the biological function of RNA. Firstly we show that examination of the energies of fragments of RNA secondary structure provides evidence for kinetic formation of structure. Local regions of RNA of length less than about 100 nucleotides adopt a conformation with energy near or equal to the minimum possible for those regions, whilst the energies of larger domains are much further from the their respective minima. This is consistent with the patterns that would be expected if RNA structure is folded Idneticatic during transcription. A Monte-Carlo algorithm is then used to model the kinetic folding of RNA during transcriptional growth. The algorithm is capable of finding the correct structure of a natural RNA for which the minimum free energy approach is unsuccessful. In the viral phage MS2 Idneticatic formed RNA structure plays an important role in the regulation of gene expression. The folding algorithm can accurately model this by IdneticaUy controlling access to the gene initiation region. The algorithm is also successfully used to model the control of replication in the ColEl plasmid. Taking a different approach, we then use a simplified model of RNA secondary structure to investigate the size of energy barriers between degenerate minimum energy structures. This model has much in common with physical systems such as spin glasses, and in fact shows similar behaviour to these systems in that energy

  12. Self-Learning Monte Carlo Method

    NASA Astrophysics Data System (ADS)

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

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

  13. On the relationships between the Michaelis–Menten kinetics, reverse Michaelis–Menten kinetics, equilibrium chemistry approximation kinetics, and quadratic kinetics

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

    Tang, J. Y.

    The Michaelis–Menten kinetics and the reverse Michaelis–Menten kinetics are two popular mathematical formulations used in many land biogeochemical models to describe how microbes and plants would respond to changes in substrate abundance. However, the criteria of when to use either of the two are often ambiguous. Here I show that these two kinetics are special approximations to the equilibrium chemistry approximation (ECA) kinetics, which is the first-order approximation to the quadratic kinetics that solves the equation of an enzyme–substrate complex exactly for a single-enzyme and single-substrate biogeochemical reaction with the law of mass action and the assumption of a quasi-steadymore » state for the enzyme–substrate complex and that the product genesis from enzyme–substrate complex is much slower than the equilibration between enzyme–substrate complexes, substrates, and enzymes. In particular, I show that the derivation of the Michaelis–Menten kinetics does not consider the mass balance constraint of the substrate, and the reverse Michaelis–Menten kinetics does not consider the mass balance constraint of the enzyme, whereas both of these constraints are taken into account in deriving the equilibrium chemistry approximation kinetics. By benchmarking against predictions from the quadratic kinetics for a wide range of substrate and enzyme concentrations, the Michaelis–Menten kinetics was found to persistently underpredict the normalized sensitivity ∂ ln v / ∂ ln k 2 + of the reaction velocity v with respect to the maximum product genesis rate k 2 +, persistently overpredict the normalized sensitivity ∂ ln v / ∂ ln k 1 + of v with respect to the intrinsic substrate affinity k 1 +, persistently overpredict the normalized sensitivity ∂ ln v / ∂ ln [ E] T of v with respect the total enzyme concentration [ E] T, and persistently underpredict the normalized sensitivity ∂ ln v / ∂ ln [ S] T of v with respect to the total substrate

  14. On the relationships between the Michaelis–Menten kinetics, reverse Michaelis–Menten kinetics, equilibrium chemistry approximation kinetics, and quadratic kinetics

    DOE PAGES

    Tang, J. Y.

    2015-12-01

    The Michaelis–Menten kinetics and the reverse Michaelis–Menten kinetics are two popular mathematical formulations used in many land biogeochemical models to describe how microbes and plants would respond to changes in substrate abundance. However, the criteria of when to use either of the two are often ambiguous. Here I show that these two kinetics are special approximations to the equilibrium chemistry approximation (ECA) kinetics, which is the first-order approximation to the quadratic kinetics that solves the equation of an enzyme–substrate complex exactly for a single-enzyme and single-substrate biogeochemical reaction with the law of mass action and the assumption of a quasi-steadymore » state for the enzyme–substrate complex and that the product genesis from enzyme–substrate complex is much slower than the equilibration between enzyme–substrate complexes, substrates, and enzymes. In particular, I show that the derivation of the Michaelis–Menten kinetics does not consider the mass balance constraint of the substrate, and the reverse Michaelis–Menten kinetics does not consider the mass balance constraint of the enzyme, whereas both of these constraints are taken into account in deriving the equilibrium chemistry approximation kinetics. By benchmarking against predictions from the quadratic kinetics for a wide range of substrate and enzyme concentrations, the Michaelis–Menten kinetics was found to persistently underpredict the normalized sensitivity ∂ ln v / ∂ ln k 2 + of the reaction velocity v with respect to the maximum product genesis rate k 2 +, persistently overpredict the normalized sensitivity ∂ ln v / ∂ ln k 1 + of v with respect to the intrinsic substrate affinity k 1 +, persistently overpredict the normalized sensitivity ∂ ln v / ∂ ln [ E] T of v with respect the total enzyme concentration [ E] T, and persistently underpredict the normalized sensitivity ∂ ln v / ∂ ln [ S] T of v with respect to the total substrate

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

    PubMed Central

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

    2015-01-01

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

  16. Magnetization switching in nanoscale ferromagnetic grains: MFM observables from Monte Carlo simulations

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

    Richards, H.L.; Sides, S.W.; Novotny, M.A.

    1996-12-31

    Recently experimental techniques, such as magnetic force microscopy (MFM), have enabled the magnetic state of individual sub-micron particles to be resolved. Motivated by these experimental developments, the authors use Monte Carlo simulations of two-dimensional kinetic Ising ferromagnets to study the magnetic relaxation in a negative applied field of a grain with an initial magnetization m{sub 0} = + 1. They use classical droplet theory to predict the functional forms for some quantities which can be observed by MFM. An example is the probability that the magnetization is positive, which is a function of time, field, grain size, and grain dimensionality.more » The qualitative agreement between experiments and their simulations of switching in individual single-domain ferromagnets indicates that the switching mechanism in such particles may involve local nucleation and subsequent growth of droplets of the stable phase.« less

  17. Recent advances and future prospects for Monte Carlo

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

    Brown, Forrest B

    2010-01-01

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

  18. Monte Carlo Transport for Electron Thermal Transport

    NASA Astrophysics Data System (ADS)

    Chenhall, Jeffrey; Cao, Duc; Moses, Gregory

    2015-11-01

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

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

    NASA Astrophysics Data System (ADS)

    Sundqvist, Kyle

    2010-03-01

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

  20. Port wine oxidation management: a multiparametric kinetic approach.

    PubMed

    Martins, Rui Costa; Monforte, Ana Rita; Silva Ferreira, António

    2013-06-05

    Port wine is a flagship fortified wine of Portugal, which undergoes a particularly long aging period, developing a dynamic sensory profile over time, responsible for several wine categories, which is dependent upon the type of aging (bottle or barrel). Therefore, the quality of the product is dependent upon the chemical mechanisms occurring during the aging process, such as oxidation or Maillard reactions. To attain the desired quality management, it is necessary to understand how technological parameters, such as temperature or oxygen exposure, affect the kinetics of the formation of key odorants, such as sotolon. There is a lack of information about the impact of the storage conditions (oxygen and temperature) on Port wine quality. In this study, the effect of these two parameters were investigated to increase the knowledge database concerning aging management of Port wines. It was found that sotolon formation is highly dependent upon oxygen and temperature. There is however a synergistic effect between these two parameters that could significantly increase the concentration. The kinetic parameters of oxygen, sotolon, and other compounds related to Port aging (cis- and trans-5-hydroxy-2-methyl-1,3-dioxan, 2-furfural, 5-hydroxy-methyl-furfural, and 5-methyl-furfural) are also reported. Kinetic models with Monte Carlo simulations, where the oxygen permeability dispersion and temperature are the parameters under evaluation, were applied. On the basis of the modeling predictions, it would seem that the temperature of a cellar would have a more significant impact on the Port wines stored in containers where the oxygen intake is higher (barrels) when compared to containers with low oxygen permeability (bottles using cork stoppers).

  1. Response Matrix Monte Carlo for electron transport

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

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

    1990-11-01

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

  2. Deterministic theory of Monte Carlo variance

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

    Ueki, T.; Larsen, E.W.

    1996-12-31

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

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

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

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

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

  4. Vectorized Monte Carlo methods for reactor lattice analysis

    NASA Technical Reports Server (NTRS)

    Brown, F. B.

    1984-01-01

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

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

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

    Badal, A; Zbijewski, W; Bolch, W

    detail, with all necessary data on material composition, source, geometry, scoring and other parameters provided. The results of these simulations when performed with the four most common publicly available Monte Carlo packages are also provided in tabular form. The Task Group 195 Report will be useful for researchers needing to validate their Monte Carlo work, and for trainees needing to learn Monte Carlo simulation methods. In this symposium we will review the recent advancements in highperformance computing hardware enabling the reduction in computational resources needed for Monte Carlo simulations in medical imaging. We will review variance reduction techniques commonly applied in Monte Carlo simulations of medical imaging systems and present implementation strategies for efficient combination of these techniques with GPU acceleration. Trade-offs involved in Monte Carlo acceleration by means of denoising and “sparse sampling” will be discussed. A method for rapid scatter correction in cone-beam CT (<5 min/scan) will be presented as an illustration of the simulation speeds achievable with optimized Monte Carlo simulations. We will also discuss the development, availability, and capability of the various combinations of computational phantoms for Monte Carlo simulation of medical imaging systems. Finally, we will review some examples of experimental validation of Monte Carlo simulations and will present the AAPM Task Group 195 Report. Learning Objectives: Describe the advances in hardware available for performing Monte Carlo simulations in high performance computing environments. Explain variance reduction, denoising and sparse sampling techniques available for reduction of computational time needed for Monte Carlo simulations of medical imaging. List and compare the computational anthropomorphic phantoms currently available for more accurate assessment of medical imaging parameters in Monte Carlo simulations. Describe experimental methods used for validation of

  6. Monte Carlo Techniques for Nuclear Systems - Theory Lectures

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

    Brown, Forrest B.

    These are lecture notes for a Monte Carlo class given at the University of New Mexico. The following topics are covered: course information; nuclear eng. review & MC; random numbers and sampling; computational geometry; collision physics; tallies and statistics; eigenvalue calculations I; eigenvalue calculations II; eigenvalue calculations III; variance reduction; parallel Monte Carlo; parameter studies; fission matrix and higher eigenmodes; doppler broadening; Monte Carlo depletion; HTGR modeling; coupled MC and T/H calculations; fission energy deposition. Solving particle transport problems with the Monte Carlo method is simple - just simulate the particle behavior. The devil is in the details, however. Thesemore » lectures provide a balanced approach to the theory and practice of Monte Carlo simulation codes. The first lectures provide an overview of Monte Carlo simulation methods, covering the transport equation, random sampling, computational geometry, collision physics, and statistics. The next lectures focus on the state-of-the-art in Monte Carlo criticality simulations, covering the theory of eigenvalue calculations, convergence analysis, dominance ratio calculations, bias in Keff and tallies, bias in uncertainties, a case study of a realistic calculation, and Wielandt acceleration techniques. The remaining lectures cover advanced topics, including HTGR modeling and stochastic geometry, temperature dependence, fission energy deposition, depletion calculations, parallel calculations, and parameter studies. This portion of the class focuses on using MCNP to perform criticality calculations for reactor physics and criticality safety applications. It is an intermediate level class, intended for those with at least some familiarity with MCNP. Class examples provide hands-on experience at running the code, plotting both geometry and results, and understanding the code output. The class includes lectures & hands-on computer use for a variety of Monte Carlo

  7. Random Numbers and Monte Carlo Methods

    NASA Astrophysics Data System (ADS)

    Scherer, Philipp O. J.

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

  8. Evaluation of Interindividual Human Variation in Bioactivation and DNA Adduct Formation of Estragole in Liver Predicted by Physiologically Based Kinetic/Dynamic and Monte Carlo Modeling.

    PubMed

    Punt, Ans; Paini, Alicia; Spenkelink, Albertus; Scholz, Gabriele; Schilter, Benoit; van Bladeren, Peter J; Rietjens, Ivonne M C M

    2016-04-18

    Estragole is a known hepatocarcinogen in rodents at high doses following metabolic conversion to the DNA-reactive metabolite 1'-sulfooxyestragole. The aim of the present study was to model possible levels of DNA adduct formation in (individual) humans upon exposure to estragole. This was done by extending a previously defined PBK model for estragole in humans to include (i) new data on interindividual variation in the kinetics for the major PBK model parameters influencing the formation of 1'-sulfooxyestragole, (ii) an equation describing the relationship between 1'-sulfooxyestragole and DNA adduct formation, (iii) Monte Carlo modeling to simulate interindividual human variation in DNA adduct formation in the population, and (iv) a comparison of the predictions made to human data on DNA adduct formation for the related alkenylbenzene methyleugenol. Adequate model predictions could be made, with the predicted DNA adduct levels at the estimated daily intake of estragole of 0.01 mg/kg bw ranging between 1.6 and 8.8 adducts in 10(8) nucleotides (nts) (50th and 99th percentiles, respectively). This is somewhat lower than values reported in the literature for the related alkenylbenzene methyleugenol in surgical human liver samples. The predicted levels seem to be below DNA adduct levels that are linked with tumor formation by alkenylbenzenes in rodents, which were estimated to amount to 188-500 adducts per 10(8) nts at the BMD10 values of estragole and methyleugenol. Although this does not seem to point to a significant health concern for human dietary exposure, drawing firm conclusions may have to await further validation of the model's predictions.

  9. Monte Carlo simulation of steady state shock structure including cosmic ray mediation and particle escape

    NASA Technical Reports Server (NTRS)

    Ellison, D. C.; Jones, F. C.; Eichler, D.

    1983-01-01

    Both hydrodynamic calculations (Drury and Volk, 1981, and Axford et al., 1982) and kinetic simulations imply the existence of thermal subshocks in high-Mach-number cosmic-ray-mediated shocks. The injection efficiency of particles from the thermal background into the diffusive shock-acceleration process is determined in part by the sharpness and compression ratio of these subshocks. Results are reported for a Monte Carlo simulation that includes both the back reaction of accelerated particles on the inflowing plasma, producing a smoothing of the shock transition, and the free escape of particles allowing arbitrarily large overall compression ratios in high-Mach-number steady-state shocks. Energy spectra and estimates of the proportion of thermal ions accelerated to high energy are obtained.

  10. Monte Carlo simulation of steady state shock structure including cosmic ray mediation and particle escape

    NASA Astrophysics Data System (ADS)

    Ellison, D. C.; Jones, F. C.; Eichler, D.

    1983-08-01

    Both hydrodynamic calculations (Drury and Volk, 1981, and Axford et al., 1982) and kinetic simulations imply the existence of thermal subshocks in high-Mach-number cosmic-ray-mediated shocks. The injection efficiency of particles from the thermal background into the diffusive shock-acceleration process is determined in part by the sharpness and compression ratio of these subshocks. Results are reported for a Monte Carlo simulation that includes both the back reaction of accelerated particles on the inflowing plasma, producing a smoothing of the shock transition, and the free escape of particles allowing arbitrarily large overall compression ratios in high-Mach-number steady-state shocks. Energy spectra and estimates of the proportion of thermal ions accelerated to high energy are obtained.

  11. Effect of lag time distribution on the lag phase of bacterial growth - a Monte Carlo analysis

    USDA-ARS?s Scientific Manuscript database

    The objective of this study is to use Monte Carlo simulation to evaluate the effect of lag time distribution of individual bacterial cells incubated under isothermal conditions on the development of lag phase. The growth of bacterial cells of the same initial concentration and mean lag phase durati...

  12. Multilevel sequential Monte Carlo samplers

    DOE PAGES

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

    2016-08-24

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

  13. Monte Carlo Methods in Materials Science Based on FLUKA and ROOT

    NASA Technical Reports Server (NTRS)

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

    2003-01-01

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

  14. Combustor kinetic energy efficiency analysis of the hypersonic research engine data

    NASA Astrophysics Data System (ADS)

    Hoose, K. V.

    1993-11-01

    A one-dimensional method for measuring combustor performance is needed to facilitate design and development scramjet engines. A one-dimensional kinetic energy efficiency method is used for measuring inlet and nozzle performance. The objective of this investigation was to assess the use of kinetic energy efficiency as an indicator for scramjet combustor performance. A combustor kinetic energy efficiency analysis was performed on the Hypersonic Research Engine (HRE) data. The HRE data was chosen for this analysis due to its thorough documentation and availability. The combustor, inlet, and nozzle kinetic energy efficiency values were utilized to determine an overall engine kinetic energy efficiency. Finally, a kinetic energy effectiveness method was developed to eliminate thermochemical losses from the combustion of fuel and air. All calculated values exhibit consistency over the flight speed range. Effects from fuel injection, altitude, angle of attack, subsonic-supersonic combustion transition, and inlet spike position are shown and discussed. The results of analyzing the HRE data indicate that the kinetic energy efficiency method is effective as a measure of scramjet combustor performance.

  15. Microstructure development in Kolmogorov, Johnson-Mehl, and Avrami nucleation and growth kinetics

    NASA Astrophysics Data System (ADS)

    Pineda, Eloi; Crespo, Daniel

    1999-08-01

    A statistical model with the ability to evaluate the microstructure developed in nucleation and growth kinetics is built in the framework of the Kolmogorov, Johnson-Mehl, and Avrami theory. A populational approach is used to compute the observed grain-size distribution. The impingement process which delays grain growth is analyzed, and the effective growth rate of each population is estimated considering the previous grain history. The proposed model is integrated for a wide range of nucleation and growth protocols, including constant nucleation, pre-existing nuclei, and intermittent nucleation with interface or diffusion-controlled grain growth. The results are compared with Monte Carlo simulations, giving quantitative agreement even in cases where previous models fail.

  16. A kinetic study of the formation of organic solids from formaldehyde: Implications for the origin of extraterrestrial organic solids in primitive Solar System objects

    NASA Astrophysics Data System (ADS)

    Kebukawa, Yoko; Cody, George D.

    2015-03-01

    Aqueous organic solid formation from formaldehyde via the formose reaction and subsequent reactions is a possible candidate for the origin of complex primitive chondritic insoluble organic matter (IOM) and refractory carbon in comets. The rate of formation of organic solids from formaldehyde was studied as a function of temperature and time, with and without ammonia, in order to derive kinetic expressions for polymer yield. The evolution in molecular structure as a function of time and temperature was studied using infrared spectroscopy. Using these kinetic expressions, the yield of organic solids is estimated for extended time and temperature ranges. For example, the half-life for organic solid formation is ∼5 days at 373 K, ∼200 days at 323 K, and ∼70 years at 273 K with ammonia, and ∼25 days at 373 K, ∼13 years at 323 K, and ∼2 × 104 years at 273 K without ammonia. These results indicate that organic solids could form during the aqueous alteration in meteorite parent bodies. If liquid water existed early in the interiors of Kuiper belt objects (KBOs), formaldehyde could convert into organic solids at temperatures close to 273 K, and possibly even below 273 K in the ammonia-water system.

  17. The Metropolis Monte Carlo method with CUDA enabled Graphic Processing Units

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

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

    2014-02-01

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

  18. Dissociative adsorption of O2 on unreconstructed metal (100) surfaces: Pathways, energetics, and sticking kinetics

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

    Liu, Da-Jiang; Evans, James W.

    An accurate description of oxygen dissociation pathways and kinetics for various local adlayer environments is key for an understanding not just of the coverage dependence of oxygen sticking, but also of reactive steady states in oxidation reactions. Density functional theory analysis for M(100) surfaces with M=Pd, Rh, and Ni, where O prefers the fourfold hollow adsorption site, does not support the traditional Brundle-Behm-Barker picture of dissociative adsorption onto second-nearest-neighbor hollow sites with an additional blocking constraint. Rather adsorption via neighboring vicinal bridge sites dominates, although other pathways can be active. The same conclusion also applies for M=Pt and Ir, wheremore » oxygen prefers the bridge adsorption site. Statistical mechanical analysis is performed based on kinetic Monte Carlo simulation of a multisite lattice-gas model consistent with our revised picture of adsorption. This analysis determines the coverage and temperature dependence of sticking for a realistic treatment of the oxygen adlayer structure.« less

  19. Efficient Coupling of Fluid-Plasma and Monte-Carlo-Neutrals Models for Edge Plasma Transport

    NASA Astrophysics Data System (ADS)

    Dimits, A. M.; Cohen, B. I.; Friedman, A.; Joseph, I.; Lodestro, L. L.; Rensink, M. E.; Rognlien, T. D.; Sjogreen, B.; Stotler, D. P.; Umansky, M. V.

    2017-10-01

    UEDGE has been valuable for modeling transport in the tokamak edge and scrape-off layer due in part to its efficient fully implicit solution of coupled fluid neutrals and plasma models. We are developing an implicit coupling of the kinetic Monte-Carlo (MC) code DEGAS-2, as the neutrals model component, to the UEDGE plasma component, based on an extension of the Jacobian-free Newton-Krylov (JFNK) method to MC residuals. The coupling components build on the methods and coding already present in UEDGE. For the linear Krylov iterations, a procedure has been developed to ``extract'' a good preconditioner from that of UEDGE. This preconditioner may also be used to greatly accelerate the convergence rate of a relaxed fixed-point iteration, which may provide a useful ``intermediate'' algorithm. The JFNK method also requires calculation of Jacobian-vector products, for which any finite-difference procedure is inaccurate when a MC component is present. A semi-analytical procedure that retains the standard MC accuracy and fully kinetic neutrals physics is therefore being developed. Prepared for US DOE by LLNL under Contract DE-AC52-07NA27344 and LDRD project 15-ERD-059, by PPPL under Contract DE-AC02-09CH11466, and supported in part by the U.S. DOE, OFES.

  20. Understanding the presence of vacancy clusters in ZnO from a kinetic perspective

    NASA Astrophysics Data System (ADS)

    Bang, Junhyeok; Kim, Youg-Sung; Park, C. H.; Gao, F.; Zhang, S. B.

    2014-06-01

    Vacancy clusters have been observed in ZnO by positron-annihilation spectroscopy (PAS), but detailed mechanisms are unclear. This is because the clustering happens in non-equilibrium conditions, for which theoretical method has not been well established. Combining first-principles calculation and kinetic Monte Carlo simulation, we determine the roles of non-equilibrium kinetics on the vacancies clustering. We find that clustering starts with the formation of Zn and O vacancy pairs (VZn - Vo), which further grow by attracting additional mono-vacancies. At this stage, vacancy diffusivity becomes crucial: due to the larger diffusivity of VZn compared to VO, more VZn-abundant clusters are formed than VO-abundant clusters. The large dissociation energy barriers, e.g., over 2.5 eV for (VZn - Vo), suggest that, once formed, it is difficult for the clusters to dissociate. By promoting mono-vacancy diffusion, thermal annealing will increase the size of the clusters. As the PAS is insensitive to VO donor defects, our results suggest an interpretation of the experimental data that could not have been made without the in-depth calculations.

  1. Kinetics of the chiral phase transition in a linear σ model

    NASA Astrophysics Data System (ADS)

    Wesp, Christian; van Hees, Hendrik; Meistrenko, Alex; Greiner, Carsten

    2018-02-01

    We study the dynamics of the chiral phase transition in a linear quark-meson σ model using a novel approach based on semiclassical wave-particle duality. The quarks are treated as test particles in a Monte Carlo simulation of elastic collisions and the coupling to the σ meson, which is treated as a classical field, via a kinetic approach motivated by wave-particle duality. The exchange of energy and momentum between particles and fields is described in terms of appropriate Gaussian wave packets. It has been demonstrated that energy-momentum conservation and the principle of detailed balance are fulfilled, and that the dynamics leads to the correct equilibrium limit. First schematic studies of the dynamics of matter produced in heavy-ion collisions are presented.

  2. Electron kinetics in atmospheric-pressure argon and nitrogen microwave microdischarges

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

    Levko, Dmitry; Raja, Laxminarayan L.

    2016-04-28

    Electron kinetics in atmospheric-pressure argon and nitrogen microwave (4 GHz) microdischarges is studied using a self-consistent one-dimensional Particle-in-Cell Monte Carlo Collisions model. The reversal of electric field (i.e., inverted sheath formation) is obtained in nitrogen and is not obtained in argon. This is explained by the different energy dependencies of electron-neutral collision cross sections in atomic and molecular gases and, as a consequence, different drag force acting on electrons. A non-local behavior of electron energy distribution function is obtained in both gases owing to electrons are generated in the plasma sheath. In both gases, electron energy relaxation length is comparable withmore » the interelectrode gap, and therefore, they penetrate the plasma bulk with large energies.« less

  3. Determination of the effective diffusivity of water in a poly (methyl methacrylate) membrane containing carbon nanotubes using kinetic Monte Carlo simulations.

    PubMed

    Mermigkis, Panagiotis G; Tsalikis, Dimitrios G; Mavrantzas, Vlasis G

    2015-10-28

    A kinetic Monte Carlo (kMC) simulation algorithm is developed for computing the effective diffusivity of water molecules in a poly(methyl methacrylate) (PMMA) matrix containing carbon nanotubes (CNTs) at several loadings. The simulations are conducted on a cubic lattice to the bonds of which rate constants are assigned governing the elementary jump events of water molecules from one lattice site to another. Lattice sites belonging to PMMA domains of the membrane are assigned different rates than lattice sites belonging to CNT domains. Values of these two rate constants are extracted from available numerical data for water diffusivity within a PMMA matrix and a CNT pre-computed on the basis of independent atomistic molecular dynamics simulations, which show that water diffusivity in CNTs is 3 orders of magnitude faster than in PMMA. Our discrete-space, continuum-time kMC simulation results for several PMMA-CNT nanocomposite membranes (characterized by different values of CNT length L and diameter D and by different loadings of the matrix in CNTs) demonstrate that the overall or effective diffusivity, D(eff), of water in the entire polymeric membrane is of the same order of magnitude as its diffusivity in PMMA domains and increases only linearly with the concentration C (vol. %) in nanotubes. For a constant value of the concentration C, D(eff) is found to vary practically linearly also with the CNT aspect ratio L/D. The kMC data allow us to propose a simple bilinear expression for D(eff) as a function of C and L/D that can describe the numerical data for water mobility in the membrane extremely accurately. Additional simulations with two different CNT configurations (completely random versus aligned) show that CNT orientation in the polymeric matrix has only a minor effect on D(eff) (as long as CNTs do not fully penetrate the membrane). We have also extensively analyzed and quantified sublinear (anomalous) diffusive phenomena over small to moderate times and

  4. Summarizing Monte Carlo Results in Methodological Research.

    ERIC Educational Resources Information Center

    Harwell, Michael R.

    Monte Carlo studies of statistical tests are prominently featured in the methodological research literature. Unfortunately, the information from these studies does not appear to have significantly influenced methodological practice in educational and psychological research. One reason is that Monte Carlo studies lack an overarching theory to guide…

  5. Advanced Computational Methods for Monte Carlo Calculations

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

    Brown, Forrest B.

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

  6. Quantum speedup of Monte Carlo methods.

    PubMed

    Montanaro, Ashley

    2015-09-08

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

  7. 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.

  8. Kinetic Monte Carlo simulation on influence of vacancy on hydrogen diffusivity in tungsten

    NASA Astrophysics Data System (ADS)

    Oda, Takuji; Zhu, Deqiong; Watanabe, Yoshiyuki

    2015-12-01

    Kinetic Mote Carlo (KMC) simulations are performed to quantify the influence of trap in hydrogen diffusivity in tungsten. As a typical trap, mono-vacancy is considered in the simulation. Experimental results reported by Frauenfelder are nicely reproduced when hydrogen concentration and trap concentration expected in the experiment are employed in the simulation. The effective diffusivity of hydrogen is evidently decreased by traps even at high temperatures like 1300 K. These results suggest that only high-temperature experimental data, which are not significantly affected by traps, should be fitted to, in order to derive the true hydrogen diffusivity from experiments. Therefore, we recommend D = 1.58 ×10-7exp(- 0.25 eV / kT) m2 s-1 as the equation for hydrogen diffusion coefficient in tungsten, which was obtained by fitting only to experimental data at 1500-2400 K by Heinola and Ahlgren, rather than the most cited equation D = 4.1 ×10-7exp(- 0.39 eV / kT) m2 s-1, which was obtained by fitting to all experimental data at 1100-2400 K including some data that should be affected by traps.

  9. Mass fluctuation kinetics: Capturing stochastic effects in systems of chemical reactions through coupled mean-variance computations

    NASA Astrophysics Data System (ADS)

    Gómez-Uribe, Carlos A.; Verghese, George C.

    2007-01-01

    The intrinsic stochastic effects in chemical reactions, and particularly in biochemical networks, may result in behaviors significantly different from those predicted by deterministic mass action kinetics (MAK). Analyzing stochastic effects, however, is often computationally taxing and complex. The authors describe here the derivation and application of what they term the mass fluctuation kinetics (MFK), a set of deterministic equations to track the means, variances, and covariances of the concentrations of the chemical species in the system. These equations are obtained by approximating the dynamics of the first and second moments of the chemical master equation. Apart from needing knowledge of the system volume, the MFK description requires only the same information used to specify the MAK model, and is not significantly harder to write down or apply. When the effects of fluctuations are negligible, the MFK description typically reduces to MAK. The MFK equations are capable of describing the average behavior of the network substantially better than MAK, because they incorporate the effects of fluctuations on the evolution of the means. They also account for the effects of the means on the evolution of the variances and covariances, to produce quite accurate uncertainty bands around the average behavior. The MFK computations, although approximate, are significantly faster than Monte Carlo methods for computing first and second moments in systems of chemical reactions. They may therefore be used, perhaps along with a few Monte Carlo simulations of sample state trajectories, to efficiently provide a detailed picture of the behavior of a chemical system.

  10. Monte Carlo simulation of electron thermalization in scintillator materials: Implications for scintillator nonproportionality

    DOE PAGES

    Prange, Micah P.; Xie, YuLong; Campbell, Luke W.; ...

    2017-12-20

    The lack of reliable quantitative estimates of the length and time scales associated with hot electron thermalization after a gamma-ray induced energy cascade obscures the interplay of various microscopic processes controlling scintillator performance and hampers the search for improved detector materials. We apply a detailed microscopic kinetic Monte Carlo model of the creation and subsequent thermalization of hot electrons produced by gamma irradiation of six important scintillating crystals to determine the spatial extent of the cloud of excitations produced by gamma rays and the time required for the cloud to thermalize with the host lattice. The main ingredients of themore » model are ensembles of microscopic track structures produced upon gamma excitation (including the energy distribution of the excited carriers), numerical estimates of electron-phonon scattering rates, and a calculated particle dispersion to relate the speed and energy of excited carriers. All these ingredients are based on first-principles density functional theory calculations of the electronic and phonon band structures of the materials. The details of the Monte Carlo model are presented along with the results for thermalization time and distance distributions. Here, these results are discussed in light of previous work. It is found that among the studied materials, calculated thermalization distances are positively correlated with measured nonproportionality. In the important class of halide scintillators, the particle dispersion is found to be more influential than the largest phonon energy in determining the thermalization distance.« less

  11. Monte Carlo simulation of electron thermalization in scintillator materials: Implications for scintillator nonproportionality

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

    Prange, Micah P.; Xie, YuLong; Campbell, Luke W.

    2017-12-21

    The lack of reliable quantitative estimates of the length and time scales associated with hot electron thermalization after a gamma-ray induced energy cascade obscures the interplay of various microscopic processes controlling scintillator performance and hampers the search for improved detector materials. We apply a detailed microscopic kinetic Monte Carlo model of the creation and subsequent thermalization of hot electrons produced by gamma irradiation of six important scintillating crystals to determine the spatial extent of the cloud of excitations produced by gamma rays and the time required for the cloud to thermalize with the host lattice. The main ingredients of themore » model are ensembles of microscopic track structures produced upon gamma excitation (including the energy distribution of the excited carriers), numerical estimates of electron-phonon scattering rates, and a calculated particle dispersion to relate the speed and energy of excited carriers. All these ingredients are based on first-principles density functional theory calculations of the electronic and phonon band structures of the materials. Details of the Monte Carlo model are presented along with results for thermalization time and distance distributions. These results are discussed in light of previous work. It is found that among the studied materials, calculated thermalization distances are positively correlated with measured nonproportionality. In the important class of halide scintillators, the particle dispersion is found to be more influential than the largest phonon energy in determining the thermalization distance.« less

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

    PubMed

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

    2015-10-01

    before performing his/her own novel research. In addition, an investigator entering the field of Monte Carlo simulations can use these descriptions and results as a self-teaching tool to ensure that he/she is able to perform a specific simulation correctly. Finally, educators can assign these cases as learning projects as part of course objectives or training programs.

  13. Monte Carlo modeling of spatial coherence: free-space diffraction

    PubMed Central

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

    2008-01-01

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

  14. Joint reconstruction of dynamic PET activity and kinetic parametric images using total variation constrained dictionary sparse coding

    NASA Astrophysics Data System (ADS)

    Yu, Haiqing; Chen, Shuhang; Chen, Yunmei; Liu, Huafeng

    2017-05-01

    Dynamic positron emission tomography (PET) is capable of providing both spatial and temporal information of radio tracers in vivo. In this paper, we present a novel joint estimation framework to reconstruct temporal sequences of dynamic PET images and the coefficients characterizing the system impulse response function, from which the associated parametric images of the system macro parameters for tracer kinetics can be estimated. The proposed algorithm, which combines statistical data measurement and tracer kinetic models, integrates a dictionary sparse coding (DSC) into a total variational minimization based algorithm for simultaneous reconstruction of the activity distribution and parametric map from measured emission sinograms. DSC, based on the compartmental theory, provides biologically meaningful regularization, and total variation regularization is incorporated to provide edge-preserving guidance. We rely on techniques from minimization algorithms (the alternating direction method of multipliers) to first generate the estimated activity distributions with sub-optimal kinetic parameter estimates, and then recover the parametric maps given these activity estimates. These coupled iterative steps are repeated as necessary until convergence. Experiments with synthetic, Monte Carlo generated data, and real patient data have been conducted, and the results are very promising.

  15. Monte Carlo studies of ocean wind vector measurements by SCATT: Objective criteria and maximum likelihood estimates for removal of aliases, and effects of cell size on accuracy of vector winds

    NASA Technical Reports Server (NTRS)

    Pierson, W. J.

    1982-01-01

    The scatterometer on the National Oceanic Satellite System (NOSS) is studied by means of Monte Carlo techniques so as to determine the effect of two additional antennas for alias (or ambiguity) removal by means of an objective criteria technique and a normalized maximum likelihood estimator. Cells nominally 10 km by 10 km, 10 km by 50 km, and 50 km by 50 km are simulated for winds of 4, 8, 12 and 24 m/s and incidence angles of 29, 39, 47, and 53.5 deg for 15 deg changes in direction. The normalized maximum likelihood estimate (MLE) is correct a large part of the time, but the objective criterion technique is recommended as a reserve, and more quickly computed, procedure. Both methods for alias removal depend on the differences in the present model function at upwind and downwind. For 10 km by 10 km cells, it is found that the MLE method introduces a correlation between wind speed errors and aspect angle (wind direction) errors that can be as high as 0.8 or 0.9 and that the wind direction errors are unacceptably large, compared to those obtained for the SASS for similar assumptions.

  16. KMCThinFilm: A C++ Framework for the Rapid Development of Lattice Kinetic Monte Carlo (kMC) Simulations of Thin Film Growth

    DTIC Science & Technology

    2015-09-01

    direction, so if the simulation domain is set to be a certain size, then that presents a hard ceiling on the thickness of a film that may be grown in...FFA, Los J, Cuppen HM, Bennema P, Meekes H. MONTY:  Monte Carlo crystal growth on any crystal structure in any crystallographic orientation...mhoffman.github.io/kmos/. 23. Kiravittaya S, Schmidt OG. Quantum-dot crystal defects. Applied Physics Letters. 2008;93:173109. 24. Leetmaa M

  17. Kinetics and thermodynamics of chemical reactions in Li/SOCl2 cells

    NASA Technical Reports Server (NTRS)

    Hansen, Lee D.; Frank, Harvey

    1987-01-01

    Work is described that was designed to determine the kinetic constants necessary to extrapolate kinetic data on Li/SOCl2 cells over the temperature range from 25 to 75 C. A second objective was to characterize as far as possible the chemical reactions that occur in the cells since these reactions may be important in understanding the potential hazards of these cells. The kinetics of the corrosion processes in undischarged Li/SOCl2 cells were determined and separated according to their occurrence at the anode and cathode; the effects that switching the current on and off has on the corrosion reactions was determined; and the effects of discharge state on the kinetics of the corrosion process were found. A thermodynamic analysis of the current-producing reactions in the cell was done and is included.

  18. Quantum speedup of Monte Carlo methods

    PubMed Central

    Montanaro, Ashley

    2015-01-01

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

  19. Object Segmentation from Motion Discontinuities and Temporal Occlusions–A Biologically Inspired Model

    PubMed Central

    Beck, Cornelia; Ognibeni, Thilo; Neumann, Heiko

    2008-01-01

    Background Optic flow is an important cue for object detection. Humans are able to perceive objects in a scene using only kinetic boundaries, and can perform the task even when other shape cues are not provided. These kinetic boundaries are characterized by the presence of motion discontinuities in a local neighbourhood. In addition, temporal occlusions appear along the boundaries as the object in front covers the background and the objects that are spatially behind it. Methodology/Principal Findings From a technical point of view, the detection of motion boundaries for segmentation based on optic flow is a difficult task. This is due to the problem that flow detected along such boundaries is generally not reliable. We propose a model derived from mechanisms found in visual areas V1, MT, and MSTl of human and primate cortex that achieves robust detection along motion boundaries. It includes two separate mechanisms for both the detection of motion discontinuities and of occlusion regions based on how neurons respond to spatial and temporal contrast, respectively. The mechanisms are embedded in a biologically inspired architecture that integrates information of different model components of the visual processing due to feedback connections. In particular, mutual interactions between the detection of motion discontinuities and temporal occlusions allow a considerable improvement of the kinetic boundary detection. Conclusions/Significance A new model is proposed that uses optic flow cues to detect motion discontinuities and object occlusion. We suggest that by combining these results for motion discontinuities and object occlusion, object segmentation within the model can be improved. This idea could also be applied in other models for object segmentation. In addition, we discuss how this model is related to neurophysiological findings. The model was successfully tested both with artificial and real sequences including self and object motion. PMID:19043613

  20. Bayesian parameter inference for stochastic biochemical network models using particle Markov chain Monte Carlo

    PubMed Central

    Golightly, Andrew; Wilkinson, Darren J.

    2011-01-01

    Computational systems biology is concerned with the development of detailed mechanistic models of biological processes. Such models are often stochastic and analytically intractable, containing uncertain parameters that must be estimated from time course data. In this article, we consider the task of inferring the parameters of a stochastic kinetic model defined as a Markov (jump) process. Inference for the parameters of complex nonlinear multivariate stochastic process models is a challenging problem, but we find here that algorithms based on particle Markov chain Monte Carlo turn out to be a very effective computationally intensive approach to the problem. Approximations to the inferential model based on stochastic differential equations (SDEs) are considered, as well as improvements to the inference scheme that exploit the SDE structure. We apply the methodology to a Lotka–Volterra system and a prokaryotic auto-regulatory network. PMID:23226583

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

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

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

    2014-09-15

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

  2. MontePython 3: Parameter inference code for cosmology

    NASA Astrophysics Data System (ADS)

    Brinckmann, Thejs; Lesgourgues, Julien; Audren, Benjamin; Benabed, Karim; Prunet, Simon

    2018-05-01

    MontePython 3 provides numerous ways to explore parameter space using Monte Carlo Markov Chain (MCMC) sampling, including Metropolis-Hastings, Nested Sampling, Cosmo Hammer, and a Fisher sampling method. This improved version of the Monte Python (ascl:1307.002) parameter inference code for cosmology offers new ingredients that improve the performance of Metropolis-Hastings sampling, speeding up convergence and offering significant time improvement in difficult runs. Additional likelihoods and plotting options are available, as are post-processing algorithms such as Importance Sampling and Adding Derived Parameter.

  3. An unbiased Hessian representation for Monte Carlo PDFs.

    PubMed

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

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

  4. Diffusion Monte Carlo approach versus adiabatic computation for local Hamiltonians

    NASA Astrophysics Data System (ADS)

    Bringewatt, Jacob; Dorland, William; Jordan, Stephen P.; Mink, Alan

    2018-02-01

    Most research regarding quantum adiabatic optimization has focused on stoquastic Hamiltonians, whose ground states can be expressed with only real non-negative amplitudes and thus for whom destructive interference is not manifest. This raises the question of whether classical Monte Carlo algorithms can efficiently simulate quantum adiabatic optimization with stoquastic Hamiltonians. Recent results have given counterexamples in which path-integral and diffusion Monte Carlo fail to do so. However, most adiabatic optimization algorithms, such as for solving MAX-k -SAT problems, use k -local Hamiltonians, whereas our previous counterexample for diffusion Monte Carlo involved n -body interactions. Here we present a 6-local counterexample which demonstrates that even for these local Hamiltonians there are cases where diffusion Monte Carlo cannot efficiently simulate quantum adiabatic optimization. Furthermore, we perform empirical testing of diffusion Monte Carlo on a standard well-studied class of permutation-symmetric tunneling problems and similarly find large advantages for quantum optimization over diffusion Monte Carlo.

  5. Monte Carlo simulation of aorta autofluorescence

    NASA Astrophysics Data System (ADS)

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

    2016-08-01

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

  6. Quantum Monte Carlo Endstation for Petascale Computing

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

    Lubos Mitas

    2011-01-26

    NCSU research group has been focused on accomplising the key goals of this initiative: establishing new generation of quantum Monte Carlo (QMC) computational tools as a part of Endstation petaflop initiative for use at the DOE ORNL computational facilities and for use by computational electronic structure community at large; carrying out high accuracy quantum Monte Carlo demonstration projects in application of these tools to the forefront electronic structure problems in molecular and solid systems; expanding the impact of QMC methods and approaches; explaining and enhancing the impact of these advanced computational approaches. In particular, we have developed quantum Monte Carlomore » code (QWalk, www.qwalk.org) which was significantly expanded and optimized using funds from this support and at present became an actively used tool in the petascale regime by ORNL researchers and beyond. These developments have been built upon efforts undertaken by the PI's group and collaborators over the period of the last decade. The code was optimized and tested extensively on a number of parallel architectures including petaflop ORNL Jaguar machine. We have developed and redesigned a number of code modules such as evaluation of wave functions and orbitals, calculations of pfaffians and introduction of backflow coordinates together with overall organization of the code and random walker distribution over multicore architectures. We have addressed several bottlenecks such as load balancing and verified efficiency and accuracy of the calculations with the other groups of the Endstation team. The QWalk package contains about 50,000 lines of high quality object-oriented C++ and includes also interfaces to data files from other conventional electronic structure codes such as Gamess, Gaussian, Crystal and others. This grant supported PI for one month during summers, a full-time postdoc and partially three graduate students over the period of the grant duration, it has resulted in

  7. Extraction kinetics and properties of proanthocyanidins from pomegranate peel

    USDA-ARS?s Scientific Manuscript database

    With an objective of developing a safe and efficient method to extract proanthocyanidins products from pomegranate peel for use in nutraceuticals or as food additives, the effects of extraction parameters on the production efficiency, product properties, and extraction kinetics were systematically s...

  8. Atomistic Simulations of Graphene Growth: From Kinetics to Mechanism.

    PubMed

    Qiu, Zongyang; Li, Pai; Li, Zhenyu; Yang, Jinlong

    2018-03-20

    Epitaxial growth is a promising strategy to produce high-quality graphene samples. At the same time, this method has great flexibility for industrial scale-up. To optimize growth protocols, it is essential to understand the underlying growth mechanisms. This is, however, very challenging, as the growth process is complicated and involves many elementary steps. Experimentally, atomic-scale in situ characterization methods are generally not feasible at the high temperature of graphene growth. Therefore, kinetics is the main experimental information to study growth mechanisms. Theoretically, first-principles calculations routinely provide atomic structures and energetics but have a stringent limit on the accessible spatial and time scales. Such gap between experiment and theory can be bridged by atomistic simulations using first-principles atomic details as input and providing the overall growth kinetics, which can be directly compared with experiment, as output. Typically, system-specific approximations should be applied to make such simulations computationally feasible. By feeding kinetic Monte Carlo (kMC) simulations with first-principles parameters, we can directly simulate the graphene growth process and thus understand the growth mechanisms. Our simulations suggest that the carbon dimer is the dominant feeding species in the epitaxial growth of graphene on both Cu(111) and Cu(100) surfaces, which enables us to understand why the reaction is diffusion limited on Cu(111) but attachment limited on Cu(100). When hydrogen is explicitly considered in the simulation, the central role hydrogen plays in graphene growth is revealed, which solves the long-standing puzzle into why H 2 should be fed in the chemical vapor deposition of graphene. The simulation results can be directly compared with the experimental kinetic data, if available. Our kMC simulations reproduce the experimentally observed quintic-like behavior of graphene growth on Ir(111). By checking the

  9. Monte-Carlo background simulations of present and future detectors in x-ray astronomy

    NASA Astrophysics Data System (ADS)

    Tenzer, C.; Kendziorra, E.; Santangelo, A.

    2008-07-01

    Reaching a low-level and well understood internal instrumental background is crucial for the scientific performance of an X-ray detector and, therefore, a main objective of the instrument designers. Monte-Carlo simulations of the physics processes and interactions taking place in a space-based X-ray detector as a result of its orbital environment can be applied to explain the measured background of existing missions. They are thus an excellent tool to predict and optimize the background of future observatories. Weak points of a design and the main sources of the background can be identified and methods to reduce them can be implemented and studied within the simulations. Using the Geant4 Monte-Carlo toolkit, we have created a simulation environment for space-based detectors and we present results of such background simulations for XMM-Newton's EPIC pn-CCD camera. The environment is also currently used to estimate and optimize the background of the future instruments Simbol-X and eRosita.

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

    NASA Astrophysics Data System (ADS)

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

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

  11. Uncertainties in models of tropospheric ozone based on Monte Carlo analysis: Tropospheric ozone burdens, atmospheric lifetimes and surface distributions

    NASA Astrophysics Data System (ADS)

    Derwent, Richard G.; Parrish, David D.; Galbally, Ian E.; Stevenson, David S.; Doherty, Ruth M.; Naik, Vaishali; Young, Paul J.

    2018-05-01

    Recognising that global tropospheric ozone models have many uncertain input parameters, an attempt has been made to employ Monte Carlo sampling to quantify the uncertainties in model output that arise from global tropospheric ozone precursor emissions and from ozone production and destruction in a global Lagrangian chemistry-transport model. Ninety eight quasi-randomly Monte Carlo sampled model runs were completed and the uncertainties were quantified in tropospheric burdens and lifetimes of ozone, carbon monoxide and methane, together with the surface distribution and seasonal cycle in ozone. The results have shown a satisfactory degree of convergence and provide a first estimate of the likely uncertainties in tropospheric ozone model outputs. There are likely to be diminishing returns in carrying out many more Monte Carlo runs in order to refine further these outputs. Uncertainties due to model formulation were separately addressed using the results from 14 Atmospheric Chemistry Coupled Climate Model Intercomparison Project (ACCMIP) chemistry-climate models. The 95% confidence ranges surrounding the ACCMIP model burdens and lifetimes for ozone, carbon monoxide and methane were somewhat smaller than for the Monte Carlo estimates. This reflected the situation where the ACCMIP models used harmonised emissions data and differed only in their meteorological data and model formulations whereas a conscious effort was made to describe the uncertainties in the ozone precursor emissions and in the kinetic and photochemical data in the Monte Carlo runs. Attention was focussed on the model predictions of the ozone seasonal cycles at three marine boundary layer stations: Mace Head, Ireland, Trinidad Head, California and Cape Grim, Tasmania. Despite comprehensively addressing the uncertainties due to global emissions and ozone sources and sinks, none of the Monte Carlo runs were able to generate seasonal cycles that matched the observations at all three MBL stations. Although

  12. A kinetic model of the formation of organic monolayers on hydrogen-terminated silicon by hydrosilation of alkenes.

    PubMed

    Woods, M; Carlsson, S; Hong, Q; Patole, S N; Lie, L H; Houlton, A; Horrocks, B R

    2005-12-22

    We have analyzed a kinetic model for the formation of organic monolayers based on a previously suggested free radical chain mechanism for the reaction of unsaturated molecules with hydrogen-terminated silicon surfaces (Linford, M. R.; Fenter, P. M.; Chidsey, C. E. D. J. Am. Chem. Soc 1995, 117, 3145). A direct consequence of this mechanism is the nonexponential growth of the monolayer, and this has been observed spectroscopically. In the model, the initiation of silyl radicals on the surface is pseudo first order with rate constant, ki, and the rate of propagation is determined by the concentration of radicals and unreacted Si-H nearest neighbor sites with a rate constant, kp. This propagation step determines the rate at which the monolayer forms by addition of alkene molecules to form a track of molecules that constitute a self-avoiding random walk on the surface. The initiation step describes how frequently new random walks commence. A termination step by which the radicals are destroyed is also included. The solution of the kinetic equations yields the fraction of alkylated surface sites and the mean length of the random walks as a function of time. In mean-field approximation we show that (1) the average length of the random walk is proportional to (kp/ki)1/2, (2) the monolayer surface coverage grows exponentially only after an induction period, (3) the effective first-order rate constant describing the growth of the monolayer and the induction period (kt) is k = (2ki kp)1/2, (4) at long times the effective first-order rate constant drops to ki, and (5) the overall activation energy for the growth kinetics is the mean of the activation energies for the initiation and propagation steps. Monte Carlo simulations of the mechanism produce qualitatively similar kinetic plots, but the mean random walk length (and effective rate constant) is overestimated by the mean field approximation and when kp > ki, we find k approximately ki0.7kp0.3 and Ea = (0.7Ei+ 0.3Ep

  13. Risk assessment predictions of open dumping area after closure using Monte Carlo simulation

    NASA Astrophysics Data System (ADS)

    Pauzi, Nur Irfah Mohd; Radhi, Mohd Shahril Mat; Omar, Husaini

    2017-10-01

    Currently, there are many abandoned open dumping areas that were left without any proper mitigation measures. These open dumping areas could pose serious hazard to human and pollute the environment. The objective of this paper is to determine the risk assessment at the open dumping area after they has been closed using Monte Carlo Simulation method. The risk assessment exercise is conducted at the Kuala Lumpur dumping area. The rapid urbanisation of Kuala Lumpur coupled with increase in population lead to increase in waste generation. It leads to more dumping/landfill area in Kuala Lumpur. The first stage of this study involve the assessment of the dumping area and samples collections. It followed by measurement of settlement of dumping area using oedometer. The risk of the settlement is predicted using Monte Carlo simulation method. Monte Carlo simulation calculates the risk and the long-term settlement. The model simulation result shows that risk level of the Kuala Lumpur open dumping area ranges between Level III to Level IV i.e. between medium risk to high risk. These settlement (ΔH) is between 3 meters to 7 meters. Since the risk is between medium to high, it requires mitigation measures such as replacing the top waste soil with new sandy gravel soil. This will increase the strength of the soil and reduce the settlement.

  14. Discrete Diffusion Monte Carlo for Electron Thermal Transport

    NASA Astrophysics Data System (ADS)

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

    2014-10-01

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

  15. Off-diagonal expansion quantum Monte Carlo

    NASA Astrophysics Data System (ADS)

    Albash, Tameem; Wagenbreth, Gene; Hen, Itay

    2017-12-01

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

  16. Off-diagonal expansion quantum Monte Carlo.

    PubMed

    Albash, Tameem; Wagenbreth, Gene; Hen, Itay

    2017-12-01

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

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

    PubMed

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

    2018-01-01

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

  18. [Kinetics of the order-disorder transition in the system of two interacting macromolecules (computer simulation)].

    PubMed

    Taran, Iu A; Cihpev, K K; Stroganov, L B

    1977-01-01

    Kinetics of the model reaction between oligomeric planar lattice-model chains has been studied by Monte--Carlo method. Simulation of the chain's motion was performing using rules of Verdier--Stockmayer. The length of chains has been varied from 8 to 24 beads. The probabilities of breaking of a contact between two chains was given by w=exp(--U); the formation of an adjacent contact was controlled by mobility of chains. The probability of the formation of any isolated contact was given by w0=exp(--U0). Kinetic curves were obtained for mean number of contacts Z(t) with different initial conditions and U, U0 values. The estimation of mean rates of formation-breaking of contacts (V+ and V-) and their dependences on the time, U and U0 have been obtained. Rate constants for the formation-breaking of a contact (k+ and k-) were estimated as well as the distribution for k+/- over states of the binary complex. The calculations were made for the case of homopolymers, intrachain interactions were omitted.

  19. Application of Multi-Hypothesis Sequential Monte Carlo for Breakup Analysis

    NASA Astrophysics Data System (ADS)

    Faber, W. R.; Zaidi, W.; Hussein, I. I.; Roscoe, C. W. T.; Wilkins, M. P.; Schumacher, P. W., Jr.

    As more objects are launched into space, the potential for breakup events and space object collisions is ever increasing. These events create large clouds of debris that are extremely hazardous to space operations. Providing timely, accurate, and statistically meaningful Space Situational Awareness (SSA) data is crucial in order to protect assets and operations in space. The space object tracking problem, in general, is nonlinear in both state dynamics and observations, making it ill-suited to linear filtering techniques such as the Kalman filter. Additionally, given the multi-object, multi-scenario nature of the problem, space situational awareness requires multi-hypothesis tracking and management that is combinatorially challenging in nature. In practice, it is often seen that assumptions of underlying linearity and/or Gaussianity are used to provide tractable solutions to the multiple space object tracking problem. However, these assumptions are, at times, detrimental to tracking data and provide statistically inconsistent solutions. This paper details a tractable solution to the multiple space object tracking problem applicable to space object breakup events. Within this solution, simplifying assumptions of the underlying probability density function are relaxed and heuristic methods for hypothesis management are avoided. This is done by implementing Sequential Monte Carlo (SMC) methods for both nonlinear filtering as well as hypothesis management. This goal of this paper is to detail the solution and use it as a platform to discuss computational limitations that hinder proper analysis of large breakup events.

  20. Monte-Carlo Modeling of the Central Carbon Metabolism of Lactococcus lactis: Insights into Metabolic Regulation

    PubMed Central

    Murabito, Ettore; Verma, Malkhey; Bekker, Martijn; Bellomo, Domenico; Westerhoff, Hans V.; Teusink, Bas; Steuer, Ralf

    2014-01-01

    Metabolic pathways are complex dynamic systems whose response to perturbations and environmental challenges are governed by multiple interdependencies between enzyme properties, reactions rates, and substrate levels. Understanding the dynamics arising from such a network can be greatly enhanced by the construction of a computational model that embodies the properties of the respective system. Such models aim to incorporate mechanistic details of cellular interactions to mimic the temporal behavior of the biochemical reaction system and usually require substantial knowledge of kinetic parameters to allow meaningful conclusions. Several approaches have been suggested to overcome the severe data requirements of kinetic modeling, including the use of approximative kinetics and Monte-Carlo sampling of reaction parameters. In this work, we employ a probabilistic approach to study the response of a complex metabolic system, the central metabolism of the lactic acid bacterium Lactococcus lactis, subject to perturbations and brief periods of starvation. Supplementing existing methodologies, we show that it is possible to acquire a detailed understanding of the control properties of a corresponding metabolic pathway model that is directly based on experimental observations. In particular, we delineate the role of enzymatic regulation to maintain metabolic stability and metabolic recovery after periods of starvation. It is shown that the feedforward activation of the pyruvate kinase by fructose-1,6-bisphosphate qualitatively alters the bifurcation structure of the corresponding pathway model, indicating a crucial role of enzymatic regulation to prevent metabolic collapse for low external concentrations of glucose. We argue that similar probabilistic methodologies will help our understanding of dynamic properties of small-, medium- and large-scale metabolic networks models. PMID:25268481

  1. Hybrid Monte Carlo/deterministic methods for radiation shielding problems

    NASA Astrophysics Data System (ADS)

    Becker, Troy L.

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

  2. AREVA Developments for an Efficient and Reliable use of Monte Carlo codes for Radiation Transport Applications

    NASA Astrophysics Data System (ADS)

    Chapoutier, Nicolas; Mollier, François; Nolin, Guillaume; Culioli, Matthieu; Mace, Jean-Reynald

    2017-09-01

    In the context of the rising of Monte Carlo transport calculations for any kind of application, AREVA recently improved its suite of engineering tools in order to produce efficient Monte Carlo workflow. Monte Carlo codes, such as MCNP or TRIPOLI, are recognized as reference codes to deal with a large range of radiation transport problems. However the inherent drawbacks of theses codes - laboring input file creation and long computation time - contrast with the maturity of the treatment of the physical phenomena. The goals of the recent AREVA developments were to reach similar efficiency as other mature engineering sciences such as finite elements analyses (e.g. structural or fluid dynamics). Among the main objectives, the creation of a graphical user interface offering CAD tools for geometry creation and other graphical features dedicated to the radiation field (source definition, tally definition) has been reached. The computations times are drastically reduced compared to few years ago thanks to the use of massive parallel runs, and above all, the implementation of hybrid variance reduction technics. From now engineering teams are capable to deliver much more prompt support to any nuclear projects dealing with reactors or fuel cycle facilities from conceptual phase to decommissioning.

  3. Monte carlo simulations of the n_TOF lead spallation target with the Geant4 toolkit: A benchmark study

    NASA Astrophysics Data System (ADS)

    Lerendegui-Marco, J.; Cortés-Giraldo, M. A.; Guerrero, C.; Quesada, J. M.; Meo, S. Lo; Massimi, C.; Barbagallo, M.; Colonna, N.; Mancussi, D.; Mingrone, F.; Sabaté-Gilarte, M.; Vannini, G.; Vlachoudis, V.; Aberle, O.; Andrzejewski, J.; Audouin, L.; Bacak, M.; Balibrea, J.; Bečvář, F.; Berthoumieux, E.; Billowes, J.; Bosnar, D.; Brown, A.; Caamaño, M.; Calviño, F.; Calviani, M.; Cano-Ott, D.; Cardella, R.; Casanovas, A.; Cerutti, F.; Chen, Y. H.; Chiaveri, E.; Cortés, G.; Cosentino, L.; Damone, L. A.; Diakaki, M.; Domingo-Pardo, C.; Dressler, R.; Dupont, E.; Durán, I.; Fernández-Domínguez, B.; Ferrari, A.; Ferreira, P.; Finocchiaro, P.; Göbel, K.; Gómez-Hornillos, M. B.; García, A. R.; Gawlik, A.; Gilardoni, S.; Glodariu, T.; Gonçalves, I. F.; González, E.; Griesmayer, E.; Gunsing, F.; Harada, H.; Heinitz, S.; Heyse, J.; Jenkins, D. G.; Jericha, E.; Käppeler, F.; Kadi, Y.; Kalamara, A.; Kavrigin, P.; Kimura, A.; Kivel, N.; Kokkoris, M.; Krtička, M.; Kurtulgil, D.; Leal-Cidoncha, E.; Lederer, C.; Leeb, H.; Lonsdale, S. J.; Macina, D.; Marganiec, J.; Martínez, T.; Masi, A.; Mastinu, P.; Mastromarco, M.; Maugeri, E. A.; Mazzone, A.; Mendoza, E.; Mengoni, A.; Milazzo, P. M.; Musumarra, A.; Negret, A.; Nolte, R.; Oprea, A.; Patronis, N.; Pavlik, A.; Perkowski, J.; Porras, I.; Praena, J.; Radeck, D.; Rauscher, T.; Reifarth, R.; Rout, P. C.; Rubbia, C.; Ryan, J. A.; Saxena, A.; Schillebeeckx, P.; Schumann, D.; Smith, A. G.; Sosnin, N. V.; Stamatopoulos, A.; Tagliente, G.; Tain, J. L.; Tarifeño-Saldivia, A.; Tassan-Got, L.; Valenta, S.; Variale, V.; Vaz, P.; Ventura, A.; Vlastou, R.; Wallner, A.; Warren, S.; Woods, P. J.; Wright, T.; Žugec, P.

    2017-09-01

    Monte Carlo (MC) simulations are an essential tool to determine fundamental features of a neutron beam, such as the neutron flux or the γ-ray background, that sometimes can not be measured or at least not in every position or energy range. Until recently, the most widely used MC codes in this field had been MCNPX and FLUKA. However, the Geant4 toolkit has also become a competitive code for the transport of neutrons after the development of the native Geant4 format for neutron data libraries, G4NDL. In this context, we present the Geant4 simulations of the neutron spallation target of the n_TOF facility at CERN, done with version 10.1.1 of the toolkit. The first goal was the validation of the intra-nuclear cascade models implemented in the code using, as benchmark, the characteristics of the neutron beam measured at the first experimental area (EAR1), especially the neutron flux and energy distribution, and the time distribution of neutrons of equal kinetic energy, the so-called Resolution Function. The second goal was the development of a Monte Carlo tool aimed to provide useful calculations for both the analysis and planning of the upcoming measurements at the new experimental area (EAR2) of the facility.

  4. Improving the Kinetics and Thermodynamics of Mg(BH 4) 2 for Hydrogen Storage

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

    Wood, Brandon; Klebanoff, Lennie; Stavila, Vitalie

    The objective of this project is to (1) combine theory, synthesis, and characterization across multiple scales to understand the intrinsic kinetic and thermodynamic limitations in MgB 2/Mg(BH 4) 2; (2) construct and apply a flexible, validated, multiscale theoretical framework for modeling (de)hydrogenation kinetics of the Mg-B-H system and related metal hydrides; and (3) devise strategies for improving kinetics and thermodynamics, particularly through nanostructuring and doping. The project has an emphasis on understanding and improving rehydrogenation of MgB 2, which has generally been less explored and is key to enabling practical use.

  5. On coupling fluid plasma and kinetic neutral physics models

    DOE PAGES

    Joseph, I.; Rensink, M. E.; Stotler, D. P.; ...

    2017-03-01

    The coupled fluid plasma and kinetic neutral physics equations are analyzed through theory and simulation of benchmark cases. It is shown that coupling methods that do not treat the coupling rates implicitly are restricted to short time steps for stability. Fast charge exchange, ionization and recombination coupling rates exist, even after constraining the solution by requiring that the neutrals are at equilibrium. For explicit coupling, the present implementation of Monte Carlo correlated sampling techniques does not allow for complete convergence in slab geometry. For the benchmark case, residuals decay with particle number and increase with grid size, indicating that theymore » scale in a manner that is similar to the theoretical prediction for nonlinear bias error. Progress is reported on implementation of a fully implicit Jacobian-free Newton–Krylov coupling scheme. The present block Jacobi preconditioning method is still sensitive to time step and methods that better precondition the coupled system are under investigation.« less

  6. Wet-based glaciation in Phlegra Montes, Mars.

    NASA Astrophysics Data System (ADS)

    Gallagher, Colman; Balme, Matt

    2016-04-01

    Eskers are sinuous landforms composed of sediments deposited from meltwaters in ice-contact glacial conduits. This presentation describes the first definitive identification of eskers on Mars still physically linked with their parent system (1), a Late Amazonian-age glacier (~150 Ma) in Phlegra Montes. Previously described Amazonian-age glaciers on Mars are generally considered to have been dry based, having moved by creep in the absence of subglacial water required for sliding, but our observations indicate significant sub-glacial meltwater routing. The confinement of the Phlegra Montes glacial system to a regionally extensive graben is evidence that the esker formed due to sub-glacial melting in response to an elevated, but spatially restricted, geothermal heat flux rather than climate-induced warming. Now, however, new observations reveal the presence of many assemblages of glacial abrasion forms and associated channels that could be evidence of more widespread wet-based glaciation in Phlegra Montes, including the collapse of several distinct ice domes. This landform assemblage has not been described in other glaciated, mid-latitude regions of the martian northern hemisphere. Moreover, Phlegra Montes are flanked by lowlands displaying evidence of extensive volcanism, including contact between plains lava and piedmont glacial ice. These observations provide a rationale for investigating non-climatic forcing of glacial melting and associated landscape development on Mars, and can build on insights from Earth into the importance of geothermally-induced destabilisation of glaciers as a key amplifier of climate change. (1) Gallagher, C. and Balme, M. (2015). Eskers in a complete, wet-based glacial system in the Phlegra Montes region, Mars, Earth and Planetary Science Letters, 431, 96-109.

  7. Kinetic trapping through coalescence and the formation of patterned Ag-Cu nanoparticles

    NASA Astrophysics Data System (ADS)

    Grammatikopoulos, Panagiotis; Kioseoglou, Joseph; Galea, Antony; Vernieres, Jerome; Benelmekki, Maria; Diaz, Rosa E.; Sowwan, Mukhles

    2016-05-01

    In recent years, due to its inherent flexibility, magnetron-sputtering has been widely used to synthesise bi-metallic nanoparticles (NPs) via subsequent inert-gas cooling and gas-phase condensation of the sputtered atomic vapour. Utilising two separate sputter targets allows for good control over composition. Simultaneously, it involves fast kinetics and non-equilibrium processes, which can trap the nascent NPs into metastable configurations. In this study, we observed such configurations in immiscible, bi-metallic Ag-Cu NPs by scanning transmission electron microscopy (S/TEM) and electron energy-loss spectroscopy (EELS), and noticed a marked difference in the shape of NPs belonging to Ag- and Cu-rich samples. We explained the formation of Janus or Ag@Cu core/shell metastable structures on the grounds of in-flight mixed NP coalescence. We utilised molecular dynamics (MD) and Monte Carlo (MC) computer simulations to demonstrate that such configurations cannot occur as a result of nanoalloy segregation. Instead, sintering at relatively low temperatures can give rise to metastable structures, which eventually can be stabilised by subsequent quenching. Furthermore, we compared the heteroepitaxial diffusivities along various surfaces of both Ag and Cu NPs, and emphasised the differences between the sintering mechanisms of Ag- and Cu-rich NP compositions: small Cu NPs deform as coherent objects on large Ag NPs, whereas small Ag NPs dissolve into large Cu NPs, with their atoms diffusing along specific directions. Taking advantage of this observation, we propose controlled NP coalescence as a method to engineer mixed NPs of a unique, patterned core@partial-shell structure, which we refer to as a ``glass-float'' (ukidama) structure.In recent years, due to its inherent flexibility, magnetron-sputtering has been widely used to synthesise bi-metallic nanoparticles (NPs) via subsequent inert-gas cooling and gas-phase condensation of the sputtered atomic vapour. Utilising two

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

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

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

    2014-01-01

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

  9. A Primer in Monte Carlo Integration Using Mathcad

    ERIC Educational Resources Information Center

    Hoyer, Chad E.; Kegerreis, Jeb S.

    2013-01-01

    The essentials of Monte Carlo integration are presented for use in an upper-level physical chemistry setting. A Mathcad document that aids in the dissemination and utilization of this information is described and is available in the Supporting Information. A brief outline of Monte Carlo integration is given, along with ideas and pedagogy for…

  10. The feasibility of polychromatic cone-beam x-ray fluorescence computed tomography (XFCT) imaging of gold nanoparticle-loaded objects: a Monte Carlo study.

    PubMed

    Jones, Bernard L; Cho, Sang Hyun

    2011-06-21

    A recent study investigated the feasibility to develop a bench-top x-ray fluorescence computed tomography (XFCT) system capable of determining the spatial distribution and concentration of gold nanoparticles (GNPs) in vivo using a diagnostic energy range polychromatic (i.e. 110 kVp) pencil-beam source. In this follow-up study, we examined the feasibility of a polychromatic cone-beam implementation of XFCT by Monte Carlo (MC) simulations using the MCNP5 code. In the current MC model, cylindrical columns with various sizes (5-10 mm in diameter) containing water loaded with GNPs (0.1-2% gold by weight) were inserted into a 5 cm diameter cylindrical polymethyl methacrylate phantom. The phantom was then irradiated by a lead-filtered 110 kVp x-ray source, and the resulting gold fluorescence and Compton-scattered photons were collected by a series of energy-sensitive tallies after passing through lead parallel-hole collimators. A maximum-likelihood iterative reconstruction algorithm was implemented to reconstruct the image of GNP-loaded objects within the phantom. The effects of attenuation of both the primary beam through the phantom and the gold fluorescence photons en route to the detector were corrected during the image reconstruction. Accurate images of the GNP-containing phantom were successfully reconstructed for three different phantom configurations, with both spatial distribution and relative concentration of GNPs well identified. The pixel intensity of regions containing GNPs was linearly proportional to the gold concentration. The current MC study strongly suggests the possibility of developing a bench-top, polychromatic, cone-beam XFCT system for in vivo imaging.

  11. Baseball Monte Carlo Style.

    ERIC Educational Resources Information Center

    Houser, Larry L.

    1981-01-01

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

  12. The Monte Carlo Method. Popular Lectures in Mathematics.

    ERIC Educational Resources Information Center

    Sobol', I. M.

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

  13. Charge Transport Properties in Disordered Organic Semiconductor as a Function of Charge Density: Monte Carlo Simulation

    NASA Astrophysics Data System (ADS)

    Shukri, Seyfan Kelil

    2017-01-01

    We have done Kinetic Monte Carlo (KMC) simulations to investigate the effect of charge carrier density on the electrical conductivity and carrier mobility in disordered organic semiconductors using a lattice model. The density of state (DOS) of the system are considered to be Gaussian and exponential. Our simulations reveal that the mobility of the charge carrier increases with charge carrier density for both DOSs. In contrast, the mobility of charge carriers decreases as the disorder increases. In addition the shape of the DOS has a significance effect on the charge transport properties as a function of density which are clearly seen. On the other hand, for the same distribution width and at low carrier density, the change occurred on the conductivity and mobility for a Gaussian DOS is more pronounced than that for the exponential DOS.

  14. On the use of Bayesian Monte-Carlo in evaluation of nuclear data

    NASA Astrophysics Data System (ADS)

    De Saint Jean, Cyrille; Archier, Pascal; Privas, Edwin; Noguere, Gilles

    2017-09-01

    As model parameters, necessary ingredients of theoretical models, are not always predicted by theory, a formal mathematical framework associated to the evaluation work is needed to obtain the best set of parameters (resonance parameters, optical models, fission barrier, average width, multigroup cross sections) with Bayesian statistical inference by comparing theory to experiment. The formal rule related to this methodology is to estimate the posterior density probability function of a set of parameters by solving an equation of the following type: pdf(posterior) ˜ pdf(prior) × a likelihood function. A fitting procedure can be seen as an estimation of the posterior density probability of a set of parameters (referred as x→?) knowing a prior information on these parameters and a likelihood which gives the probability density function of observing a data set knowing x→?. To solve this problem, two major paths could be taken: add approximations and hypothesis and obtain an equation to be solved numerically (minimum of a cost function or Generalized least Square method, referred as GLS) or use Monte-Carlo sampling of all prior distributions and estimate the final posterior distribution. Monte Carlo methods are natural solution for Bayesian inference problems. They avoid approximations (existing in traditional adjustment procedure based on chi-square minimization) and propose alternative in the choice of probability density distribution for priors and likelihoods. This paper will propose the use of what we are calling Bayesian Monte Carlo (referred as BMC in the rest of the manuscript) in the whole energy range from thermal, resonance and continuum range for all nuclear reaction models at these energies. Algorithms will be presented based on Monte-Carlo sampling and Markov chain. The objectives of BMC are to propose a reference calculation for validating the GLS calculations and approximations, to test probability density distributions effects and to provide the

  15. Improved Understanding of In Situ Chemical Oxidation. Technical Objective I: Contaminant Oxidation Kinetics Contaminant Oxidation Kinetics

    DTIC Science & Technology

    2009-05-01

    methyl tert butyl ether NAPL non-aqueous phase liquid NOD natural oxidant demand •OH hydroxide radical Ox oxidant O3 ozone PCE...and persulfate; and Technical Objective 2, assess how soil properties (e.g., soil mineralogy , natural carbon content) affect oxidant mobility and...to develop a general description of kobs vs. T because there are many reactions that can contribute to the concentration of the reactive intermediate

  16. A consistent hierarchy of generalized kinetic equation approximations to the master equation applied to surface catalysis.

    PubMed

    Herschlag, Gregory J; Mitran, Sorin; Lin, Guang

    2015-06-21

    We develop a hierarchy of approximations to the master equation for systems that exhibit translational invariance and finite-range spatial correlation. Each approximation within the hierarchy is a set of ordinary differential equations that considers spatial correlations of varying lattice distance; the assumption is that the full system will have finite spatial correlations and thus the behavior of the models within the hierarchy will approach that of the full system. We provide evidence of this convergence in the context of one- and two-dimensional numerical examples. Lower levels within the hierarchy that consider shorter spatial correlations are shown to be up to three orders of magnitude faster than traditional kinetic Monte Carlo methods (KMC) for one-dimensional systems, while predicting similar system dynamics and steady states as KMC methods. We then test the hierarchy on a two-dimensional model for the oxidation of CO on RuO2(110), showing that low-order truncations of the hierarchy efficiently capture the essential system dynamics. By considering sequences of models in the hierarchy that account for longer spatial correlations, successive model predictions may be used to establish empirical approximation of error estimates. The hierarchy may be thought of as a class of generalized phenomenological kinetic models since each element of the hierarchy approximates the master equation and the lowest level in the hierarchy is identical to a simple existing phenomenological kinetic models.

  17. Coarse-grained stochastic processes and kinetic Monte Carlo simulators for the diffusion of interacting particles

    NASA Astrophysics Data System (ADS)

    Katsoulakis, Markos A.; Vlachos, Dionisios G.

    2003-11-01

    We derive a hierarchy of successively coarse-grained stochastic processes and associated coarse-grained Monte Carlo (CGMC) algorithms directly from the microscopic processes as approximations in larger length scales for the case of diffusion of interacting particles on a lattice. This hierarchy of models spans length scales between microscopic and mesoscopic, satisfies a detailed balance, and gives self-consistent fluctuation mechanisms whose noise is asymptotically identical to the microscopic MC. Rigorous, detailed asymptotics justify and clarify these connections. Gradient continuous time microscopic MC and CGMC simulations are compared under far from equilibrium conditions to illustrate the validity of our theory and delineate the errors obtained by rigorous asymptotics. Information theory estimates are employed for the first time to provide rigorous error estimates between the solutions of microscopic MC and CGMC, describing the loss of information during the coarse-graining process. Simulations under periodic boundary conditions are used to verify the information theory error estimates. It is shown that coarse-graining in space leads also to coarse-graining in time by q2, where q is the level of coarse-graining, and overcomes in part the hydrodynamic slowdown. Operation counting and CGMC simulations demonstrate significant CPU savings in continuous time MC simulations that vary from q3 for short potentials to q4 for long potentials. Finally, connections of the new coarse-grained stochastic processes to stochastic mesoscopic and Cahn-Hilliard-Cook models are made.

  18. Objective characterization of bruise evolution using photothermal depth profiling and Monte Carlo modeling

    NASA Astrophysics Data System (ADS)

    Vidovič, Luka; Milanič, Matija; Majaron, Boris

    2015-01-01

    Pulsed photothermal radiometry (PPTR) allows noninvasive determination of laser-induced temperature depth profiles in optically scattering layered structures. The obtained profiles provide information on spatial distribution of selected chromophores such as melanin and hemoglobin in human skin. We apply the described approach to study time evolution of incidental bruises (hematomas) in human subjects. By combining numerical simulations of laser energy deposition in bruised skin with objective fitting of the predicted and measured PPTR signals, we can quantitatively characterize the key processes involved in bruise evolution (i.e., hemoglobin mass diffusion and biochemical decomposition). Simultaneous analysis of PPTR signals obtained at various times post injury provides an insight into the variations of these parameters during the bruise healing process. The presented methodology and results advance our understanding of the bruise evolution and represent an important step toward development of an objective technique for age determination of traumatic bruises in forensic medicine.

  19. New Approaches and Applications for Monte Carlo Perturbation Theory

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

    Aufiero, Manuele; Bidaud, Adrien; Kotlyar, Dan

    2017-02-01

    This paper presents some of the recent and new advancements in the extension of Monte Carlo Perturbation Theory methodologies and application. In particular, the discussed problems involve Brunup calculation, perturbation calculation based on continuous energy functions, and Monte Carlo Perturbation Theory in loosely coupled systems.

  20. Fundamental electrode kinetics

    NASA Technical Reports Server (NTRS)

    Elder, J. P.

    1968-01-01

    Report presents the fundamentals of electrode kinetics and the methods used in evaluating the characteristic parameters of rapid-charge transfer processes at electrode-electrolyte interfaces. The concept of electrode kinetics is outlined, followed by the principles underlying the experimental techniques for the investigation of electrode kinetics.

  1. A Monte Carlo studies of the entrance foil material in a target assembly for FDG production

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

    Merouani, A.; El Khayati, N.; EL Ghayour, A.

    2015-07-01

    In this work, a Monte Carlo simulation was performed for different entrance foil Materials in the target assembly for [{sup 18}F] FDG production, to investigate the neutron generations in the entrance foil. However, the objective is to study a materials that has the more or less similar mechanical properties as the Havar{sup R} foil with less generation of secondary particles and without affecting, the yield of FDG production. (authors)

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

    PubMed

    Kapfer, Sebastian C; Krauth, Werner

    2016-09-01

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

  3. Recommender engine for continuous-time quantum Monte Carlo methods

    NASA Astrophysics Data System (ADS)

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

    2017-03-01

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

  4. Nuclide Depletion Capabilities in the Shift Monte Carlo Code

    DOE PAGES

    Davidson, Gregory G.; Pandya, Tara M.; Johnson, Seth R.; ...

    2017-12-21

    A new depletion capability has been developed in the Exnihilo radiation transport code suite. This capability enables massively parallel domain-decomposed coupling between the Shift continuous-energy Monte Carlo solver and the nuclide depletion solvers in ORIGEN to perform high-performance Monte Carlo depletion calculations. This paper describes this new depletion capability and discusses its various features, including a multi-level parallel decomposition, high-order transport-depletion coupling, and energy-integrated power renormalization. Several test problems are presented to validate the new capability against other Monte Carlo depletion codes, and the parallel performance of the new capability is analyzed.

  5. Rapid Monte Carlo Simulation of Gravitational Wave Galaxies

    NASA Astrophysics Data System (ADS)

    Breivik, Katelyn; Larson, Shane L.

    2015-01-01

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

  6. Effect of chemical kinetics uncertainties on calculated constituents in a tropospheric photochemical model

    NASA Technical Reports Server (NTRS)

    Thompson, Anne M.; Stewart, Richard W.

    1991-01-01

    Random photochemical reaction rates are employed in a 1D photochemical model to examine uncertainties in tropospheric concentrations and thereby determine critical kinetic processes and significant correlations. Monte Carlo computations are used to simulate different chemical environments and their related imprecisions. The most critical processes are the primary photodissociation of O3 (which initiates ozone destruction) and NO2 (which initiates ozone formation), and the OH/methane reaction is significant. Several correlations and anticorrelations between species are discussed, and the ozone/transient OH correlation is examined in detail. One important result of the modeling is that estimates of global OH are generally about 25 percent uncertain, limiting the precision of photochemical models. Techniques for reducing the imprecision are discussed which emphasize the use of species and radical species measurements.

  7. French Alps, Mont Blanc, French/Italian Border

    NASA Image and Video Library

    1992-04-02

    In this southeast looking view, Mont Blanc, on the French/Italian border, (48.0N, 4.5E) the highest mountain peak in all of Europe, is just below and right of center (below the end of the prominent valley of the Aosta River, in the center of the photo. The rivers flow out of the Alps into Italy toward Turin. Chamonix, the famous resort town and center of Alpine mountain climbing, lies in the valley just below Mont Blanc.

  8. Numerical integration of detector response functions via Monte Carlo simulations

    NASA Astrophysics Data System (ADS)

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

    2017-09-01

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

  9. Numerical integration of detector response functions via Monte Carlo simulations

    DOE PAGES

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

    2017-06-13

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

  10. Numerical integration of detector response functions via Monte Carlo simulations

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

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

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

  11. Malariotherapy at Mont Park: the earliest surviving movie of psychiatric treatment in Australia.

    PubMed

    Kaplan, Robert M

    2013-02-01

    A movie on malariotherapy for neurosyphilis made at Mont Park and filmed by Reg Ellery in 1926 is believed to be the oldest surviving movie of psychiatric treatment in Australia. The objective is to review the movie and discuss the background and context of the film, which shows the conditions of patients in a psychiatric hospital in the 1920s. Movie film is a guide to a psychiatric past that is rapidly being forgotten. The Ellery movie is an incentive to collect surviving footage before it is too late.

  12. Monte Carlo capabilities of the SCALE code system

    DOE PAGES

    Rearden, Bradley T.; Petrie, Jr., Lester M.; Peplow, Douglas E.; ...

    2014-09-12

    SCALE is a broadly used suite of tools for nuclear systems modeling and simulation that provides comprehensive, verified and validated, user-friendly capabilities for criticality safety, reactor physics, radiation shielding, and sensitivity and uncertainty analysis. For more than 30 years, regulators, licensees, and research institutions around the world have used SCALE for nuclear safety analysis and design. SCALE provides a “plug-and-play” framework that includes three deterministic and three Monte Carlo radiation transport solvers that can be selected based on the desired solution, including hybrid deterministic/Monte Carlo simulations. SCALE includes the latest nuclear data libraries for continuous-energy and multigroup radiation transport asmore » well as activation, depletion, and decay calculations. SCALE’s graphical user interfaces assist with accurate system modeling, visualization, and convenient access to desired results. SCALE 6.2 will provide several new capabilities and significant improvements in many existing features, especially with expanded continuous-energy Monte Carlo capabilities for criticality safety, shielding, depletion, and sensitivity and uncertainty analysis. Finally, an overview of the Monte Carlo capabilities of SCALE is provided here, with emphasis on new features for SCALE 6.2.« less

  13. 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.

  14. Kinetic effects on turbulence driven by the magnetorotational instability in black hole accretion

    NASA Astrophysics Data System (ADS)

    Sharma, Prateek

    Many astrophysical objects (e.g., spiral galaxies, the solar system, Saturn's rings, and luminous disks around compact objects) occur in the form of a disk. One of the important astrophysical problems is to understand how rotationally supported disks lose angular momentum, and accrete towards the bottom of the gravitational potential, converting gravitational energy into thermal (and radiation) energy. The magnetorotational instability (MRI), an instability causing turbulent transport in ionized accretion disks, is studied in the kinetic regime. Kinetic effects are important because radiatively inefficient accretion flows (RIAFs), like the one around the supermassive black hole in the center of our Galaxy, are collisionless. The ion Larmor radius is tiny compared to the scale of MHD turbulence so that the drift kinetic equation (DKE), obtained by averaging the Vlasov equation over the fast gyromotion, is appropriate for evolving the distribution function. The kinetic MHD formalism, based on the moments of the DKE, is used for linear and nonlinear studies. A Landau fluid closure for parallel heat flux, which models kinetic effects like collisionless damping, is used to close the moment hierarchy. We show, that the kinetic MHD and drift kinetic formalisms give the same set of linear modes for a Keplerian disk. The BGK collision operator is used to study the transition of the MRI from kinetic to the MHD regime. The ZEUS MHD code is modified to include the key kinetic MHD terms: anisotropy, pressure tensor and anisotropic thermal conduction. The modified code is used to simulate the collisionless MRI in a local shearing box. As magnetic field is amplified by the MRI, pressure anisotropy ( p [perpendicular] > p || ) is created because of the adiabatic invariance (m 0( p [perpendicular] / B ). Larmor radius scale instabilities---mirror, ion-cyclotron, and firehose---are excited even at small pressure anisotropies (D p/p ~ 1/b). Pressure isotropization due to pitch angle

  15. Performance bounds for matched field processing in subsurface object detection applications

    NASA Astrophysics Data System (ADS)

    Sahin, Adnan; Miller, Eric L.

    1998-09-01

    In recent years there has been considerable interest in the use of ground penetrating radar (GPR) for the non-invasive detection and localization of buried objects. In a previous work, we have considered the use of high resolution array processing methods for solving these problems for measurement geometries in which an array of electromagnetic receivers observes the fields scattered by the subsurface targets in response to a plane wave illumination. Our approach uses the MUSIC algorithm in a matched field processing (MFP) scheme to determine both the range and the bearing of the objects. In this paper we derive the Cramer-Rao bounds (CRB) for this MUSIC-based approach analytically. Analysis of the theoretical CRB has shown that there exists an optimum inter-element spacing of array elements for which the CRB is minimum. Furthermore, the optimum inter-element spacing minimizing CRB is smaller than the conventional half wavelength criterion. The theoretical bounds are then verified for two estimators using Monte-Carlo simulations. The first estimator is the MUSIC-based MFP and the second one is the maximum likelihood based MFP. The two approaches differ in the cost functions they optimize. We observe that Monte-Carlo simulated error variances always lie above the values established by CRB. Finally, we evaluate the performance of our MUSIC-based algorithm in the presence of model mismatches. Since the detection algorithm strongly depends on the model used, we have tested the performance of the algorithm when the object radius used in the model is different from the true radius. This analysis reveals that the algorithm is still capable of localizing the objects with a bias depending on the degree of mismatch.

  16. Geodesic Monte Carlo on Embedded Manifolds

    PubMed Central

    Byrne, Simon; Girolami, Mark

    2013-01-01

    Markov chain Monte Carlo methods explicitly defined on the manifold of probability distributions have recently been established. These methods are constructed from diffusions across the manifold and the solution of the equations describing geodesic flows in the Hamilton–Jacobi representation. This paper takes the differential geometric basis of Markov chain Monte Carlo further by considering methods to simulate from probability distributions that themselves are defined on a manifold, with common examples being classes of distributions describing directional statistics. Proposal mechanisms are developed based on the geodesic flows over the manifolds of support for the distributions, and illustrative examples are provided for the hypersphere and Stiefel manifold of orthonormal matrices. PMID:25309024

  17. The Rational Hybrid Monte Carlo algorithm

    NASA Astrophysics Data System (ADS)

    Clark, Michael

    2006-12-01

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

  18. Optimum angle-cut of collimator for dense objects in high-energy proton radiography

    NASA Astrophysics Data System (ADS)

    Xu, Hai-Bo; Zheng, Na

    2016-02-01

    The use of minus identity lenses with an angle-cut collimator can achieve high contrast images in high-energy proton radiography. This article presents the principles of choosing the angle-cut aperture of the collimator for different energies and objects. Numerical simulation using the Monte Carlo code Geant4 has been implemented to investigate the entire radiography for the French test object. The optimum angle-cut apertures of the collimators are also obtained for different energies. Supported by NSAF (11176001) and Science and Technology Developing Foundation of China Academy of Engineering Physics (2012A0202006)

  19. MONTE CARLO SIMULATIONS OF PERIODIC PULSED REACTOR WITH MOVING GEOMETRY PARTS

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

    Cao, Yan; Gohar, Yousry

    2015-11-01

    In a periodic pulsed reactor, the reactor state varies periodically from slightly subcritical to slightly prompt supercritical for producing periodic power pulses. Such periodic state change is accomplished by a periodic movement of specific reactor parts, such as control rods or reflector sections. The analysis of such reactor is difficult to perform with the current reactor physics computer programs. Based on past experience, the utilization of the point kinetics approximations gives considerable errors in predicting the magnitude and the shape of the power pulse if the reactor has significantly different neutron life times in different zones. To accurately simulate themore » dynamics of this type of reactor, a Monte Carlo procedure using the transfer function TRCL/TR of the MCNP/MCNPX computer programs is utilized to model the movable reactor parts. In this paper, two algorithms simulating the geometry part movements during a neutron history tracking have been developed. Several test cases have been developed to evaluate these procedures. The numerical test cases have shown that the developed algorithms can be utilized to simulate the reactor dynamics with movable geometry parts.« less

  20. MONTE: the next generation of mission design and navigation software

    NASA Astrophysics Data System (ADS)

    Evans, Scott; Taber, William; Drain, Theodore; Smith, Jonathon; Wu, Hsi-Cheng; Guevara, Michelle; Sunseri, Richard; Evans, James

    2018-03-01

    The Mission analysis, Operations and Navigation Toolkit Environment (MONTE) (Sunseri et al. in NASA Tech Briefs 36(9), 2012) is an astrodynamic toolkit produced by the Mission Design and Navigation Software Group at the Jet Propulsion Laboratory. It provides a single integrated environment for all phases of deep space and Earth orbiting missions. Capabilities include: trajectory optimization and analysis, operational orbit determination, flight path control, and 2D/3D visualization. MONTE is presented to the user as an importable Python language module. This allows a simple but powerful user interface via CLUI or script. In addition, the Python interface allows MONTE to be used seamlessly with other canonical scientific programming tools such as SciPy, NumPy, and Matplotlib. MONTE is the prime operational orbit determination software for all JPL navigated missions.

  1. Kinetic Atom.

    ERIC Educational Resources Information Center

    Wilson, David B.

    1981-01-01

    Surveys the research of scientists like Joule, Kelvin, Maxwell, Clausius, and Boltzmann as it comments on the basic conceptual issues involved in the development of a more precise kinetic theory and the idea of a kinetic atom. (Author/SK)

  2. Atomic kinetic energy, momentum distribution, and structure of solid neon at zero temperature

    NASA Astrophysics Data System (ADS)

    Cazorla, C.; Boronat, J.

    2008-01-01

    We report on the calculation of the ground-state atomic kinetic energy Ek and momentum distribution of solid Ne by means of the diffusion Monte Carlo method and Aziz HFD-B pair potential. This approach is shown to perform notably for this crystal since we obtain very good agreement with respect to experimental thermodynamic data. Additionally, we study the structural properties of solid Ne at densities near the equilibrium by estimating the radial pair-distribution function, Lindemann’s ratio, and atomic density profile around the positions of the perfect crystalline lattice. Our value for Ek at the equilibrium density is 41.51(6)K , which agrees perfectly with the recent prediction made by Timms , 41(2)K , based on their deep-inelastic neutron scattering experiments carried out over the temperature range 4-20K , and also with previous path integral Monte Carlo results obtained with the Lennard-Jones and Aziz HFD-C2 atomic pairwise interactions. The one-body density function of solid Ne is calculated accurately and found to fit perfectly, within statistical uncertainty, to a Gaussian curve. Furthermore, we analyze the degree of anharmonicity of solid Ne by calculating some of its microscopic ground-state properties within traditional harmonic approaches. We provide insightful comparison to solid He4 in terms of the Debye model in order to assess the relevance of anharmonic effects in Ne.

  3. PyMercury: Interactive Python for the Mercury Monte Carlo Particle Transport Code

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

    Iandola, F N; O'Brien, M J; Procassini, R J

    2010-11-29

    Monte Carlo particle transport applications are often written in low-level languages (C/C++) for optimal performance on clusters and supercomputers. However, this development approach often sacrifices straightforward usability and testing in the interest of fast application performance. To improve usability, some high-performance computing applications employ mixed-language programming with high-level and low-level languages. In this study, we consider the benefits of incorporating an interactive Python interface into a Monte Carlo application. With PyMercury, a new Python extension to the Mercury general-purpose Monte Carlo particle transport code, we improve application usability without diminishing performance. In two case studies, we illustrate how PyMercury improvesmore » usability and simplifies testing and validation in a Monte Carlo application. In short, PyMercury demonstrates the value of interactive Python for Monte Carlo particle transport applications. In the future, we expect interactive Python to play an increasingly significant role in Monte Carlo usage and testing.« less

  4. Mathematical modeling and growth kinetics of Clostridium sporogenes in cooked beef

    USDA-ARS?s Scientific Manuscript database

    Clostridium sporogenes PA 3679 is a common surrogate for proteolytic Clostridium botulinum for thermal process development and validation. However, little information is available concerning the growth kinetics of C. sporogenes in food. Therefore, the objective of this study was to investigate the...

  5. Kinetic Parameter Measurements in the MINERVE Reactor

    NASA Astrophysics Data System (ADS)

    Perret, Grégory; Geslot, Benoit; Gruel, Adrien; Blaise, Patrick; Di-Salvo, Jacques; De Izarra, Grégoire; Jammes, Christian; Hursin, Mathieu; Pautz, Andréas

    2017-01-01

    In the framework of an international collaboration, teams of the PSI and CEA research institutes measure the critical decay constant (α0 = β/A), delayed neutron fraction (β) and generation time (A) of the Minerve reactor using the Feynman-α, Power Spectral Density and Rossi-α neutron noise measurement techniques. These measurements contribute to the experimental database of kinetic parameters used to improve nuclear data files and validate modern methods in Monte Carlo codes. Minerve is a zero-power pool reactor composed of a central experimental test lattice surrounded by a large aluminum buffer and four high-enriched driver regions. Measurements are performed in three slightly subcritical configurations (-2 cents to -30 cents) using two high-efficiency 235U fission chambers in the driver regions. Measurement of α0 and β obtained by the two institutes and with the different techniques are consistent for the configurations envisaged. Slight increases of the β values are observed with the subcriticality level. Best estimate values are obtained with the Cross-Power Spectral Density technique at -2 cents, and are worth: β = 716.9±9.0 pcm, α0 = 79.0±0.6 s-1 and A = 90.7±1.4 μs. The kinetic parameters are predicted with MCNP5-v1.6 and TRIPOLI4.9 and the JEFF-3.1/3.1.1 and ENDF/B-VII.1 nuclear data libraries. The predictions for β and α0 overestimate the experimental results by 3-5% and 10-12%, respectively; that for A underestimate the experimental result by 6-7%. The discrepancies are suspected to come from the driven system nature of Minerve and the location of the detectors in the driver regions, which prevent accounting for the full reactor.

  6. Monte Carlo Simulations for the Detection of Buried Objects Using Single Sided Backscattered Radiation.

    PubMed

    Yip, Mary; Saripan, M Iqbal; Wells, Kevin; Bradley, David A

    2015-01-01

    Detection of buried improvised explosive devices (IEDs) is a delicate task, leading to a need to develop sensitive stand-off detection technology. The shape, composition and size of the IEDs can be expected to be revised over time in an effort to overcome increasingly sophisticated detection methods. As an example, for the most part, landmines are found through metal detection which has led to increasing use of non-ferrous materials such as wood or plastic containers for chemical based explosives being developed. Monte Carlo simulations have been undertaken considering three different commercially available detector materials (hyperpure-Ge (HPGe), lanthanum(III) bromide (LaBr) and thallium activated sodium iodide (NaI(Tl)), applied at a stand-off distance of 50 cm from the surface and burial depths of 0, 5 and 10 cm, with sand as the obfuscating medium. Target materials representing medium density wood and mild steel have been considered. Each detector has been modelled as a 10 cm thick cylinder with a 20 cm diameter. It appears that HPGe represents the most promising detector for this application. Although it was not the highest density material studied, its excellent energy resolving capability leads to the highest quality spectra from which detection decisions can be inferred. The simulation work undertaken here suggests that a vehicle-born threat detection system could be envisaged using a single betatron and a series of detectors operating in parallel observing the space directly in front of the vehicle path. Furthermore, results show that non-ferrous materials such as wood can be effectively discerned in such remote-operated detection system, with the potential to apply a signature analysis template matching technique for real-time analysis of such data.

  7. Multiscale modelling of precipitation in concentrated alloys: from atomistic Monte Carlo simulations to cluster dynamics I thermodynamics

    NASA Astrophysics Data System (ADS)

    Lépinoux, J.; Sigli, C.

    2018-01-01

    In a recent paper, the authors showed how the clusters free energies are constrained by the coagulation probability, and explained various anomalies observed during the precipitation kinetics in concentrated alloys. This coagulation probability appeared to be a too complex function to be accurately predicted knowing only the cluster distribution in Cluster Dynamics (CD). Using atomistic Monte Carlo (MC) simulations, it is shown that during a transformation at constant temperature, after a short transient regime, the transformation occurs at quasi-equilibrium. It is proposed to use MC simulations until the system quasi-equilibrates then to switch to CD which is mean field but not limited by a box size like MC. In this paper, we explain how to take into account the information available before the quasi-equilibrium state to establish guidelines to safely predict the cluster free energies.

  8. A plausible energy source and structure for quasi-stellar objects

    NASA Technical Reports Server (NTRS)

    Daltabuit, E.; Cox, D.

    1972-01-01

    If a collision of two large, massive, fast gas clouds occurs, their kinetic energy is converted to radiation in a pair of shock fronts at their interface. The resulting structure is described, and the relevance of this as a radiation source for quasi-stellar objects is considered.

  9. Effect of an isoenergetic traditional Mediterranean diet on apolipoprotein A-I kinetic in men with metabolic syndrome

    USDA-ARS?s Scientific Manuscript database

    The impact of the Mediterranean diet (MedDiet) on high-density lipoprotein (HDL) kinetics has not been studied to date. The objective of this study was therefore to investigate the effect of the MedDiet in the absence of changes in body weight on apolipoprotein (apo) A-I kinetic in men with metaboli...

  10. Kinetics and mechanism of soot formation in hydrocarbon combustion

    NASA Technical Reports Server (NTRS)

    Frenklach, Michael

    1990-01-01

    The focus of this work was on kinetic modeling. The specific objectives were: detailed modeling of soot formation in premixed flames, elucidation of the effects of fuel structure on the pathway to soot, and the development of a numerical technique for accurate modeling of soot particle coagulation and surface growth. Those tasks were successfully completed and are briefly summarized.

  11. Monte Carlo algorithms for Brownian phylogenetic models.

    PubMed

    Horvilleur, Benjamin; Lartillot, Nicolas

    2014-11-01

    Brownian models have been introduced in phylogenetics for describing variation in substitution rates through time, with applications to molecular dating or to the comparative analysis of variation in substitution patterns among lineages. Thus far, however, the Monte Carlo implementations of these models have relied on crude approximations, in which the Brownian process is sampled only at the internal nodes of the phylogeny or at the midpoints along each branch, and the unknown trajectory between these sampled points is summarized by simple branchwise average substitution rates. A more accurate Monte Carlo approach is introduced, explicitly sampling a fine-grained discretization of the trajectory of the (potentially multivariate) Brownian process along the phylogeny. Generic Monte Carlo resampling algorithms are proposed for updating the Brownian paths along and across branches. Specific computational strategies are developed for efficient integration of the finite-time substitution probabilities across branches induced by the Brownian trajectory. The mixing properties and the computational complexity of the resulting Markov chain Monte Carlo sampler scale reasonably with the discretization level, allowing practical applications with up to a few hundred discretization points along the entire depth of the tree. The method can be generalized to other Markovian stochastic processes, making it possible to implement a wide range of time-dependent substitution models with well-controlled computational precision. The program is freely available at www.phylobayes.org. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  12. High-efficiency wavefunction updates for large scale Quantum Monte Carlo

    NASA Astrophysics Data System (ADS)

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

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

  13. A modified Monte Carlo model for the ionospheric heating rates

    NASA Technical Reports Server (NTRS)

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

    1972-01-01

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

  14. Implementation of Monte Carlo Dose calculation for CyberKnife treatment planning

    NASA Astrophysics Data System (ADS)

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

    2008-02-01

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

  15. Decay Kinetics of UV-Sensitive Materials: An Introductory Chemistry Experiment

    ERIC Educational Resources Information Center

    Via, Garrhett; Williams, Chelsey; Dudek, Raymond; Dudek, John

    2015-01-01

    First-order kinetic decay rates can be obtained by measuring the time-dependent reflection spectra of ultraviolet-sensitive objects as they returned from their excited, colored state back to the ground, colorless state. In this paper, a procedure is described which provides an innovative and unique twist on standard, undergraduate, kinetics…

  16. Monte Carlo Perturbation Theory Estimates of Sensitivities to System Dimensions

    DOE PAGES

    Burke, Timothy P.; Kiedrowski, Brian C.

    2017-12-11

    Here, Monte Carlo methods are developed using adjoint-based perturbation theory and the differential operator method to compute the sensitivities of the k-eigenvalue, linear functions of the flux (reaction rates), and bilinear functions of the forward and adjoint flux (kinetics parameters) to system dimensions for uniform expansions or contractions. The calculation of sensitivities to system dimensions requires computing scattering and fission sources at material interfaces using collisions occurring at the interface—which is a set of events with infinitesimal probability. Kernel density estimators are used to estimate the source at interfaces using collisions occurring near the interface. The methods for computing sensitivitiesmore » of linear and bilinear ratios are derived using the differential operator method and adjoint-based perturbation theory and are shown to be equivalent to methods previously developed using a collision history–based approach. The methods for determining sensitivities to system dimensions are tested on a series of fast, intermediate, and thermal critical benchmarks as well as a pressurized water reactor benchmark problem with iterated fission probability used for adjoint-weighting. The estimators are shown to agree within 5% and 3σ of reference solutions obtained using direct perturbations with central differences for the majority of test problems.« less

  17. Calculating Potential Energy Curves with Quantum Monte Carlo

    NASA Astrophysics Data System (ADS)

    Powell, Andrew D.; Dawes, Richard

    2014-06-01

    Quantum Monte Carlo (QMC) is a computational technique that can be applied to the electronic Schrödinger equation for molecules. QMC methods such as Variational Monte Carlo (VMC) and Diffusion Monte Carlo (DMC) have demonstrated the capability of capturing large fractions of the correlation energy, thus suggesting their possible use for high-accuracy quantum chemistry calculations. QMC methods scale particularly well with respect to parallelization making them an attractive consideration in anticipation of next-generation computing architectures which will involve massive parallelization with millions of cores. Due to the statistical nature of the approach, in contrast to standard quantum chemistry methods, uncertainties (error-bars) are associated with each calculated energy. This study focuses on the cost, feasibility and practical application of calculating potential energy curves for small molecules with QMC methods. Trial wave functions were constructed with the multi-configurational self-consistent field (MCSCF) method from GAMESS-US.[1] The CASINO Monte Carlo quantum chemistry package [2] was used for all of the DMC calculations. An overview of our progress in this direction will be given. References: M. W. Schmidt et al. J. Comput. Chem. 14, 1347 (1993). R. J. Needs et al. J. Phys.: Condensed Matter 22, 023201 (2010).

  18. Monte Carlo verification of radiotherapy treatments with CloudMC.

    PubMed

    Miras, Hector; Jiménez, Rubén; Perales, Álvaro; Terrón, José Antonio; Bertolet, Alejandro; Ortiz, Antonio; Macías, José

    2018-06-27

    A new implementation has been made on CloudMC, a cloud-based platform presented in a previous work, in order to provide services for radiotherapy treatment verification by means of Monte Carlo in a fast, easy and economical way. A description of the architecture of the application and the new developments implemented is presented together with the results of the tests carried out to validate its performance. CloudMC has been developed over Microsoft Azure cloud. It is based on a map/reduce implementation for Monte Carlo calculations distribution over a dynamic cluster of virtual machines in order to reduce calculation time. CloudMC has been updated with new methods to read and process the information related to radiotherapy treatment verification: CT image set, treatment plan, structures and dose distribution files in DICOM format. Some tests have been designed in order to determine, for the different tasks, the most suitable type of virtual machines from those available in Azure. Finally, the performance of Monte Carlo verification in CloudMC is studied through three real cases that involve different treatment techniques, linac models and Monte Carlo codes. Considering computational and economic factors, D1_v2 and G1 virtual machines were selected as the default type for the Worker Roles and the Reducer Role respectively. Calculation times up to 33 min and costs of 16 € were achieved for the verification cases presented when a statistical uncertainty below 2% (2σ) was required. The costs were reduced to 3-6 € when uncertainty requirements are relaxed to 4%. Advantages like high computational power, scalability, easy access and pay-per-usage model, make Monte Carlo cloud-based solutions, like the one presented in this work, an important step forward to solve the long-lived problem of truly introducing the Monte Carlo algorithms in the daily routine of the radiotherapy planning process.

  19. Monte Carlo study of the hetero-polytypical growth of cubic on hexagonal silicon carbide polytypes

    NASA Astrophysics Data System (ADS)

    Camarda, Massimo

    2012-08-01

    In this article we use three dimensional kinetic Monte Carlo simulations on super-lattices to study the hetero-polytypical growth of cubic silicon carbide polytype (3C-SiC) on misoriented hexagonal (4H and 6H) substrates. We analyze the quality of the 3C-SiC film varying the polytype, the miscut angle and the initial surface morphology of the substrate. We find that the use of 6H misoriented (4°-10° off) substrates, with step bunched surfaces, can strongly improve the quality of the cubic epitaxial film whereas the 3C/4H growth is affected by the generation of dislocations, due to the incommensurable periodicity of the 3C (3) and the 4H (4) polytypes. For these reasons, a proper pre-growth treatment of 6H misoriented substrates can be the key for the growth of high quality, twin free, 3C-SiC films.

  20. Libya Montes

    NASA Image and Video Library

    2002-11-23

    This image by NASA Mars Odyssey spacecraft shows the rugged cratered highland region of Libya Montes, which forms part of the rim of an ancient impact basin called Isidis. This region of the highlands is fairly dissected with valley networks. There is still debate within the scientific community as to how valley networks themselves form: surface runoff (rainfall/snowmelt) or headward erosion via groundwater sapping. The degree of dissection here in this region suggests surface runoff rather than groundwater sapping. Small dunes are also visible on the floors of some of these channels. http://photojournal.jpl.nasa.gov/catalog/PIA04008

  1. Exploring cluster Monte Carlo updates with Boltzmann machines

    NASA Astrophysics Data System (ADS)

    Wang, Lei

    2017-11-01

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

  2. A model based on feature objects aided strategy to evaluate the methane generation from food waste by anaerobic digestion.

    PubMed

    Yu, Meijuan; Zhao, Mingxing; Huang, Zhenxing; Xi, Kezhong; Shi, Wansheng; Ruan, Wenquan

    2018-02-01

    A model based on feature objects (FOs) aided strategy was used to evaluate the methane generation from food waste by anaerobic digestion. The kinetics of feature objects was tested by the modified Gompertz model and the first-order kinetic model, and the first-order kinetic hydrolysis constants were used to estimate the reaction rate of homemade and actual food waste. The results showed that the methane yields of four feature objects were significantly different. The anaerobic digestion of homemade food waste and actual food waste had various methane yields and kinetic constants due to the different contents of FOs in food waste. Combining the kinetic equations with the multiple linear regression equation could well express the methane yield of food waste, as the R 2 of food waste was more than 0.9. The predictive methane yields of the two actual food waste were 528.22 mL g -1  TS and 545.29 mL g -1  TS with the model, while the experimental values were 527.47 mL g -1  TS and 522.1 mL g -1  TS, respectively. The relative error between the experimental cumulative methane yields and the predicted cumulative methane yields were both less than 5%. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. Sensitivity of tropospheric ozone to chemical kinetic uncertainties in air masses influenced by anthropogenic and biomass burning emissions

    NASA Astrophysics Data System (ADS)

    Ridley, D. A.; Cain, M.; Methven, J.; Arnold, S. R.

    2017-07-01

    We use a Lagrangian chemical transport model with a Monte Carlo approach to determine impacts of kinetic rate uncertainties on simulated concentrations of ozone, NOy and OH in a high-altitude biomass burning plume and a low-level industrial pollution plume undergoing long-range transport. Uncertainties in kinetic rate constants yield 10-12 ppbv (5th to 95th percentile) uncertainty in the ozone concentration, dominated by reactions that cycle NO and NO2, control NOx conversion to NOy reservoir species, and key reactions contributing to O3 loss (O(1D) + H2O, HO2 + O3). Our results imply that better understanding of the peroxyacetylnitrate (PAN) thermal decomposition constant is key to predicting large-scale O3 production from fire emissions and uncertainty in the reaction of NO + O3 at low temperatures is particularly important for both the anthropogenic and biomass burning plumes. The highlighted reactions serve as a useful template for targeting new laboratory experiments aimed at reducing uncertainties in our understanding of tropospheric O3 photochemistry.

  4. Phase-plane analysis of the totally asymmetric simple exclusion process with binding kinetics and switching between antiparallel lanes

    PubMed Central

    Kuan, Hui-Shun; Betterton, Meredith D.

    2016-01-01

    Motor protein motion on biopolymers can be described by models related to the totally asymmetric simple exclusion process (TASEP). Inspired by experiments on the motion of kinesin-4 motors on antiparallel microtubule overlaps, we analyze a model incorporating the TASEP on two antiparallel lanes with binding kinetics and lane switching. We determine the steady-state motor density profiles using phase-plane analysis of the steady-state mean field equations and kinetic Monte Carlo simulations. We focus on the density-density phase plane, where we find an analytic solution to the mean field model. By studying the phase-space flows, we determine the model’s fixed points and their changes with parameters. Phases previously identified for the single-lane model occur for low switching rate between lanes. We predict a multiple coexistence phase due to additional fixed points that appear as the switching rate increases: switching moves motors from the higher-density to the lower-density lane, causing local jamming and creating multiple domain walls. We determine the phase diagram of the model for both symmetric and general boundary conditions. PMID:27627345

  5. Monte Carlo Optimization of Crystal Configuration for Pixelated Molecular SPECT Scanners

    NASA Astrophysics Data System (ADS)

    Mahani, Hojjat; Raisali, Gholamreza; Kamali-Asl, Alireza; Ay, Mohammad Reza

    2017-02-01

    Resolution-sensitivity-PDA tradeoff is the most challenging problem in design and optimization of pixelated preclinical SPECT scanners. In this work, we addressed such a challenge from a crystal point-of-view by looking for an optimal pixelated scintillator using GATE Monte Carlo simulation. Various crystal configurations have been investigated and the influence of different pixel sizes, pixel gaps, and three scintillators on tomographic resolution, sensitivity, and PDA of the camera were evaluated. The crystal configuration was then optimized using two objective functions: the weighted-sum and the figure-of-merit methods. The CsI(Na) reveals the highest sensitivity of the order of 43.47 cps/MBq in comparison to the NaI(Tl) and the YAP(Ce), for a 1.5×1.5 mm2 pixel size and 0.1 mm gap. The results show that the spatial resolution, in terms of FWHM, improves from 3.38 to 2.21 mm while the sensitivity simultaneously deteriorates from 42.39 cps/MBq to 27.81 cps/MBq when pixel size varies from 2×2 mm2 to 0.5×0.5 mm2 for a 0.2 mm gap, respectively. The PDA worsens from 0.91 to 0.42 when pixel size decreases from 0.5×0.5 mm2 to 1×1 mm2 for a 0.2 mm gap at 15° incident-angle. The two objective functions agree that the 1.5×1.5 mm2 pixel size and 0.1 mm Epoxy gap CsI(Na) configuration provides the best compromise for small-animal imaging, using the HiReSPECT scanner. Our study highlights that crystal configuration can significantly affect the performance of the camera, and thereby Monte Carlo optimization of pixelated detectors is mandatory in order to achieve an optimal quality tomogram.

  6. Four decades of implicit Monte Carlo

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

    Wollaber, Allan B.

    In 1971, Fleck and Cummings derived a system of equations to enable robust Monte Carlo simulations of time-dependent, thermal radiative transfer problems. Denoted the “Implicit Monte Carlo” (IMC) equations, their solution remains the de facto standard of high-fidelity radiative transfer simulations. Over the course of 44 years, their numerical properties have become better understood, and accuracy enhancements, novel acceleration methods, and variance reduction techniques have been suggested. In this review, we rederive the IMC equations—explicitly highlighting assumptions as they are made—and outfit the equations with a Monte Carlo interpretation. We put the IMC equations in context with other approximate formsmore » of the radiative transfer equations and present a new demonstration of their equivalence to another well-used linearization solved with deterministic transport methods for frequency-independent problems. We discuss physical and numerical limitations of the IMC equations for asymptotically small time steps, stability characteristics and the potential of maximum principle violations for large time steps, and solution behaviors in an asymptotically thick diffusive limit. We provide a new stability analysis for opacities with general monomial dependence on temperature. Here, we consider spatial accuracy limitations of the IMC equations and discussion acceleration and variance reduction techniques.« less

  7. jTracker and Monte Carlo Comparison

    NASA Astrophysics Data System (ADS)

    Selensky, Lauren; SeaQuest/E906 Collaboration

    2015-10-01

    SeaQuest is designed to observe the characteristics and behavior of `sea-quarks' in a proton by reconstructing them from the subatomic particles produced in a collision. The 120 GeV beam from the main injector collides with a fixed target and then passes through a series of detectors which records information about the particles produced in the collision. However, this data becomes meaningful only after it has been processed, stored, analyzed, and interpreted. Several programs are involved in this process. jTracker (sqerp) reads wire or hodoscope hits and reconstructs the tracks of potential dimuon pairs from a run, and Geant4 Monte Carlo simulates dimuon production and background noise from the beam. During track reconstruction, an event must meet the criteria set by the tracker to be considered a viable dimuon pair; this ensures that relevant data is retained. As a check, a comparison between a new version of jTracker and Monte Carlo was made in order to see how accurately jTracker could reconstruct the events created by Monte Carlo. In this presentation, the results of the inquest and their potential effects on the programming will be shown. This work is supported by U.S. DOE MENP Grant DE-FG02-03ER41243.

  8. Four decades of implicit Monte Carlo

    DOE PAGES

    Wollaber, Allan B.

    2016-02-23

    In 1971, Fleck and Cummings derived a system of equations to enable robust Monte Carlo simulations of time-dependent, thermal radiative transfer problems. Denoted the “Implicit Monte Carlo” (IMC) equations, their solution remains the de facto standard of high-fidelity radiative transfer simulations. Over the course of 44 years, their numerical properties have become better understood, and accuracy enhancements, novel acceleration methods, and variance reduction techniques have been suggested. In this review, we rederive the IMC equations—explicitly highlighting assumptions as they are made—and outfit the equations with a Monte Carlo interpretation. We put the IMC equations in context with other approximate formsmore » of the radiative transfer equations and present a new demonstration of their equivalence to another well-used linearization solved with deterministic transport methods for frequency-independent problems. We discuss physical and numerical limitations of the IMC equations for asymptotically small time steps, stability characteristics and the potential of maximum principle violations for large time steps, and solution behaviors in an asymptotically thick diffusive limit. We provide a new stability analysis for opacities with general monomial dependence on temperature. Here, we consider spatial accuracy limitations of the IMC equations and discussion acceleration and variance reduction techniques.« less

  9. Reciprocal Sliding Friction Model for an Electro-Deposited Coating and Its Parameter Estimation Using Markov Chain Monte Carlo Method

    PubMed Central

    Kim, Kyungmok; Lee, Jaewook

    2016-01-01

    This paper describes a sliding friction model for an electro-deposited coating. Reciprocating sliding tests using ball-on-flat plate test apparatus are performed to determine an evolution of the kinetic friction coefficient. The evolution of the friction coefficient is classified into the initial running-in period, steady-state sliding, and transition to higher friction. The friction coefficient during the initial running-in period and steady-state sliding is expressed as a simple linear function. The friction coefficient in the transition to higher friction is described with a mathematical model derived from Kachanov-type damage law. The model parameters are then estimated using the Markov Chain Monte Carlo (MCMC) approach. It is identified that estimated friction coefficients obtained by MCMC approach are in good agreement with measured ones. PMID:28773359

  10. Benchmark of Atucha-2 PHWR RELAP5-3D control rod model by Monte Carlo MCNP5 core calculation

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

    Pecchia, M.; D'Auria, F.; Mazzantini, O.

    2012-07-01

    Atucha-2 is a Siemens-designed PHWR reactor under construction in the Republic of Argentina. Its geometrical complexity and peculiarities require the adoption of advanced Monte Carlo codes for performing realistic neutronic simulations. Therefore core models of Atucha-2 PHWR were developed using MCNP5. In this work a methodology was set up to collect the flux in the hexagonal mesh by which the Atucha-2 core is represented. The scope of this activity is to evaluate the effect of obliquely inserted control rod on neutron flux in order to validate the RELAP5-3D{sup C}/NESTLE three dimensional neutron kinetic coupled thermal-hydraulic model, applied by GRNSPG/UNIPI formore » performing selected transients of Chapter 15 FSAR of Atucha-2. (authors)« less

  11. Fully kinetic particle simulations of high pressure streamer propagation

    NASA Astrophysics Data System (ADS)

    Rose, David; Welch, Dale; Thoma, Carsten; Clark, Robert

    2012-10-01

    Streamer and leader formation in high pressure devices is a dynamic process involving a hierarchy of physical phenomena. These include elastic and inelastic particle collisions in the gas, radiation generation, transport and absorption, and electrode interactions. We have performed 2D and 3D fully EM implicit particle-in-cell simulation model of gas breakdown leading to streamer formation under DC and RF fields. The model uses a Monte Carlo treatment for all particle interactions and includes discrete photon generation, transport, and absorption for ultra-violet and soft x-ray radiation. Central to the realization of this fully kinetic particle treatment is an algorithm [D. R. Welch, et al., J. Comp. Phys. 227, 143 (2007)] that manages the total particle count by species while preserving the local momentum distribution functions and conserving charge. These models are being applied to the analysis of high-pressure gas switches [D. V. Rose, et al., Phys. Plasmas 18, 093501 (2011)] and gas-filled RF accelerator cavities [D. V. Rose, et al. Proc. IPAC12, to appear].

  12. A BAYESIAN METHOD OF ESTIMATING KINETIC PARAMETERS FOR THE INACTIVATION OF CRYPTOSPORIDIUM PARVUM OOCYSTS WITH CHLORINE DIOXIDE AND OZONE

    EPA Science Inventory

    The main objective of this paper is to use Bayesian methods to estimate the kinetic parameters for the inactivation kinetics of Cryptosporidium parvum oocysts with chlorine dioxide or ozone which are characterized by the delayed Chick-Watson model, i.e., a lag phase or shoulder f...

  13. Noninvasive in situ observation of the crystallization kinetics of biological macromolecules by confocal laser scanning microscopy.

    PubMed

    Mühlig, P; Klupsch, Th; Kaulmann, U; Hilgenfeld, R

    2003-04-01

    High-resolution confocal laser scanning microscopy (CLSM) is a powerful tool for in situ observation and analysis of protein crystal growth kinetics. Because the resolution of CLSM is not diffraction-limited by the object, it is possible to visualize, under certain conditions, objects in molecular dimensions. A modified batch technique is applied which allows the growth kinetics of sufficiently small crystallites fixed at the lower side of a cover glass, within a hanging drop, to be studied in reflected light near the total reflection angle. A gap, or cavity, filled with solution is formed between the cover glass and the upper crystal face, which acts to fix small crystallites by hydrodynamic friction forces. The cavity height enables the propagation of molecular steps across the upper crystal face without constraint, so that the propagation velocity and geometrical parameters can be measured by CLSM. The layer growth kinetics of monoclinic crystallites of a long-acting insulin derivative (Insulin Glargine) is investigated. For a twofold supersaturation of the solution, the growth is governed by 2D nucleation at the edges of the crystallites followed by a spreading of molecular steps. The layer growth kinetics are well fitted by the simple cubic kinetic lattice model. We find that only about one of a thousand solute (protein) molecules which push a kink place due to their Brownian motion becomes really incorporated into the growing crystal.

  14. Monte Carlo Particle Lists: MCPL

    NASA Astrophysics Data System (ADS)

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

    2017-09-01

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

  15. Estimating the kinetic parameters of activated sludge storage using weighted non-linear least-squares and accelerating genetic algorithm.

    PubMed

    Fang, Fang; Ni, Bing-Jie; Yu, Han-Qing

    2009-06-01

    In this study, weighted non-linear least-squares analysis and accelerating genetic algorithm are integrated to estimate the kinetic parameters of substrate consumption and storage product formation of activated sludge. A storage product formation equation is developed and used to construct the objective function for the determination of its production kinetics. The weighted least-squares analysis is employed to calculate the differences in the storage product concentration between the model predictions and the experimental data as the sum of squared weighted errors. The kinetic parameters for the substrate consumption and the storage product formation are estimated to be the maximum heterotrophic growth rate of 0.121/h, the yield coefficient of 0.44 mg CODX/mg CODS (COD, chemical oxygen demand) and the substrate half saturation constant of 16.9 mg/L, respectively, by minimizing the objective function using a real-coding-based accelerating genetic algorithm. Also, the fraction of substrate electrons diverted to the storage product formation is estimated to be 0.43 mg CODSTO/mg CODS. The validity of our approach is confirmed by the results of independent tests and the kinetic parameter values reported in literature, suggesting that this approach could be useful to evaluate the product formation kinetics of mixed cultures like activated sludge. More importantly, as this integrated approach could estimate the kinetic parameters rapidly and accurately, it could be applied to other biological processes.

  16. Chemical Kinetics Database

    National Institute of Standards and Technology Data Gateway

    SRD 17 NIST Chemical Kinetics Database (Web, free access)   The NIST Chemical Kinetics Database includes essentially all reported kinetics results for thermal gas-phase chemical reactions. The database is designed to be searched for kinetics data based on the specific reactants involved, for reactions resulting in specified products, for all the reactions of a particular species, or for various combinations of these. In addition, the bibliography can be searched by author name or combination of names. The database contains in excess of 38,000 separate reaction records for over 11,700 distinct reactant pairs. These data have been abstracted from over 12,000 papers with literature coverage through early 2000.

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

    NASA Astrophysics Data System (ADS)

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

    2004-12-01

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

  18. Monte Carlo Calculations of Polarized Microwave Radiation Emerging from Cloud Structures

    NASA Technical Reports Server (NTRS)

    Kummerow, Christian; Roberti, Laura

    1998-01-01

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

  19. Many-body kinetics of dynamic nuclear polarization by the cross effect

    NASA Astrophysics Data System (ADS)

    Karabanov, A.; Wiśniewski, D.; Raimondi, F.; Lesanovsky, I.; Köckenberger, W.

    2018-03-01

    Dynamic nuclear polarization (DNP) is an out-of-equilibrium method for generating nonthermal spin polarization which provides large signal enhancements in modern diagnostic methods based on nuclear magnetic resonance. A particular instance is cross-effect DNP, which involves the interaction of two coupled electrons with the nuclear spin ensemble. Here we develop a theory for this important DNP mechanism and show that the nonequilibrium nuclear polarization buildup is effectively driven by three-body incoherent Markovian dissipative processes involving simultaneous state changes of two electrons and one nucleus. We identify different parameter regimes for effective polarization transfer and discuss under which conditions the polarization dynamics can be simulated by classical kinetic Monte Carlo methods. Our theoretical approach allows simulations of the polarization dynamics on an individual spin level for ensembles consisting of hundreds of nuclear spins. The insight obtained by these simulations can be used to find optimal experimental conditions for cross-effect DNP and to design tailored radical systems that provide optimal DNP efficiency.

  20. Enzyme Kinetics Experiment with the Multienzyme Complex Viscozyme L and Two Substrates for the Accurate Determination of Michaelian Parameters

    ERIC Educational Resources Information Center

    Guerra, Nelson Pérez

    2017-01-01

    A laboratory experiment in which students study the kinetics of the Viscozyme-L-catalyzed hydrolysis of cellulose and starch comparatively was designed for an upper-division biochemistry laboratory. The main objective of this experiment was to provide an opportunity to perform enhanced enzyme kinetics data analysis using appropriate informatics…

  1. Kinetic simulations of scrape-off layer physics in the DIII-D tokamak

    DOE PAGES

    Churchill, Randy M.; Canik, John M.; Chang, C. S.; ...

    2016-12-27

    Simulations using the fully kinetic code XGCa were undertaken to explore the impact of kinetic effects on scrape-off layer (SOL) physics in DIII-D H-mode plasmas. XGCa is a total- f, gyrokinetic code which self-consistently calculates the axisymmetric electrostatic potential and plasma dynamics, and includes modules for Monte Carlo neutral transport. Fluid simulations are normally used to simulate the SOL, due to its high collisionality. However, depending on plasma conditions, a number of discrepancies have been observed between experiment and leading SOL fluid codes (e.g. SOLPS), including underestimating outer target temperatures, radial electric field in the SOL, parallel ion SOL flowsmore » at the low field side, and impurity radiation. Many of these discrepancies may be linked to the fluid treatment, and might be resolved by including kinetic effects in SOL simulations. The XGCa simulation of the DIII-D tokamak in a nominally sheath-limited regime show many noteworthy features in the SOL. The density and ion temperature are higher at the low-field side, indicative of ion orbit loss. The SOL ion Mach flows are at experimentally relevant levels ( Mi ~0.5), with similar shapes and poloidal variation as observed in various tokamaks. Surprisingly, the ion Mach flows close to the sheath edge remain subsonic, in contrast to the typical fluid Bohm criterion requiring ion flows to be above sonic at the sheath edge. Related to this are the presence of elevated sheath potentials, eΔΦ/T e ~ 3–4, over most of the SOL, with regions in the near-SOL close to the separatrix having eΔΦ/Te > 4. Finally, these two results at the sheath edge are a consequence of non-Maxwellian features in the ions and electrons there.« less

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

    PubMed

    Beentjes, Casper H L; Baker, Ruth E

    2018-05-25

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

  3. A kinetic equation with kinetic entropy functions for scalar conservation laws

    NASA Technical Reports Server (NTRS)

    Perthame, Benoit; Tadmor, Eitan

    1990-01-01

    A nonlinear kinetic equation is constructed and proved to be well-adapted to describe general multidimensional scalar conservation laws. In particular, it is proved to be well-posed uniformly in epsilon - the microscopic scale. It is also shown that the proposed kinetic equation is equipped with a family of kinetic entropy functions - analogous to Boltzmann's microscopic H-function, such that they recover Krushkov-type entropy inequality on the macroscopic scale. Finally, it is proved by both - BV compactness arguments in the one-dimensional case, that the local density of kinetic particles admits a continuum limit, as it converges strongly with epsilon below 0 to the unique entropy solution of the corresponding conservation law.

  4. A Well-Posed, Objective and Dynamic Two-Fluid Model

    NASA Astrophysics Data System (ADS)

    Chetty, Krishna; Vaidheeswaran, Avinash; Sharma, Subash; Clausse, Alejandro; Lopez de Bertodano, Martin

    The transition from dispersed to clustered bubbly flows due to wake entrainment is analyzed with a well-posed and objective one-dimensional (1-D) Two-Fluid Model, derived from variational principles. Modeling the wake entrainment force using the variational technique requires formulation of the inertial coupling coefficient, which defines the kinetic coupling between the phases. The kinetic coupling between a pair of bubbles and the liquid is obtained from potential flow over two-spheres and the results are validated by comparing the virtual mass coefficients with existing literature. The two-body interaction kinetic coupling is then extended to a lumped parameter model for viscous flow over two cylindrical bubbles, to get the Two-Fluid Model for wake entrainment. Linear stability analyses comprising the characteristics and the dispersion relation and non-linear numerical simulations are performed with the 1-D variational Two-Fluid Model to demonstrate the wake entrainment instability leading to clustering of bubbles. Finally, the wavelengths, amplitudes and propagation velocities of the void waves from non-linear simulations are compared with the experimental data.

  5. NUEN-618 Class Project: Actually Implicit Monte Carlo

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

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

    2017-12-14

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

  6. Thermal hysteresis kinetic effects of spin crossover nanoparticulated systems studied by FORC diagram method on an Ising-like model

    NASA Astrophysics Data System (ADS)

    Atitoaie, Alexandru; Stoleriu, Laurentiu; Tanasa, Radu; Stancu, Alexandru; Enachescu, Cristian

    2016-04-01

    The scientific community is manifesting a high research interest on spin crossover compounds and their recently synthesized nanoparticles, due to their various appealing properties, such as the bistability between a diamagnetic low spin state and a paramagnetic high spin state (HS), inter-switchable by temperature or pressure changes, light irradiation or magnetic field. The utility of these compounds showing hysteresis covers a broad area of applications, from the development of more efficient designs of temperature and pressure sensors to automotive and aeronautic industries and even a new type of molecular actuators. We are proposing in this work a study regarding the kinetic effects and the distribution of reversible and irreversible components on the thermal hysteresis of spin crossover nanoparticulated systems. We are considering here tridimensional systems with different sizes and also systems of nanoparticles with a Gaussian size distribution. The correlations between the kinetics of the thermal hysteresis, the distributions of sizes and intermolecular interactions and the transition temperature distributions were established by using the FORC (First Order Reversal Curves) method using a Monte Carlo technique within an Ising-like system.

  7. Fully kinetic simulations of magnetic reconnction in semi-collisional plasmas

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

    Daughton, William S; Roytershteyn, Vadim S; Albright, Brian J

    2009-01-01

    The influence of Coulomb collisions on the dynamics of magnetic reconnection is examined using fully kinetic simulations with a Monte-Carlo treatment of the Fokker-Planck collision operator. This powerful first-principles approach offers a bridge between kinetic and fluid regimes, which may prove useful for understanding the applicability of various fluid models. In order to lay the necessary groundwork, the collision algorithm is first carefully bench marked for a homogeneous plasma against theoretical predictions for beam-plasma interactions and electrical resistivity. Next, the collisional decay of a current layer is examined as a function of guide field, allowing direct comparisons with transport theorymore » for the parallel and perpendicular resistivity as well as the thermoelectric force. Finally, the transition between collisional and collision less reconnection is examined in neutral sheet geometry. For modest Lundquist numbers S {approx}< 1000, a distinct transition is observed when the thickness of the Sweet-Parker layers falls below the ion inertia length {delta}{sub sp} {approx}< d,. At higher Lundquist number, deviations from the Sweet-Parker scaling are observed due to the growth of plasmoids (secondary-islands) within the elongated resistive layer. In certain cases, this instability leads to the onset of fast reconnection sooner than expected from {delta}{sub sp} {approx} d, condition. After the transition to fast reconnection, elongated electron current layers are formed which are unstable to the formation of new plasmoids. The structure and time-dependence of the electron diffusion region in these semi-collisional regimes is profoundly different than reported in two-fluid simulations.« less

  8. Non-Isothermal Kinetics.

    ERIC Educational Resources Information Center

    Brown, M. E.; Phillpotts, C. A. R.

    1978-01-01

    Discusses the principle of nonisothermal kinetics and some of the factors involved in such reactions, especially when considering the reliability of the kinetic parameters, compared to those of isothermal conditions. (GA)

  9. Geometry and Dynamics for Markov Chain Monte Carlo

    NASA Astrophysics Data System (ADS)

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

    2018-03-01

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

  10. Tool for Rapid Analysis of Monte Carlo Simulations

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

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

  11. Monte Carlo tests of the ELIPGRID-PC algorithm

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

    Davidson, J.R.

    1995-04-01

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

  12. Two proposed convergence criteria for Monte Carlo solutions

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

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

    1992-01-01

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

  13. Kinetics of thermophilic anaerobes in fixed-bed reactors.

    PubMed

    Perez, M; Romero, L I; Sales, D

    2001-08-01

    The main objective of this study is to estimate growth kinetic constants and the concentration of "active" attached biomass in two anaerobic thermophilic reactors which contain different initial sizes of immobilized anaerobic mixed cultures and decompose distillery wastewater. This paper studies the substrate decomposition in two lab-scale fixed-bed reactors operating at batch conditions with corrugated tubes as support media. It can be demonstrated that high micro-organisms-substrate ratios favor the degradation activity of the different anaerobic cultures, allowing the stable operation without lag-phases and giving better quality in effluent. The kinetic parameters obtained--maximum specific growth rates (mu(max)), non-biodegradable substrate (S(NB)) and "active or viable biomass" concentrations (X(V0))--were obtained by applying the Romero kinetic model [L.I. Romero, 1991. Desarrollo de un modelo matemático general para los procesos fermentativos, Cinética de la degradación anaerobia, Ph.D. Thesis, University of Cádiz (Spain), Serv. Pub. Univ. Cádiz], with COD as substrate and methane (CH4) as the main product of the anaerobic process. This method is suitable to calculate and to differentiate the main kinetic parameters of both the total anaerobic mixed culture and the methanogenic population. Comparison of experimental measured concentration of volatile attached solids (VS(att)) in both reactors with the estimated "active" biomass concentrations obtained by applying Romero kinetic model [L.I. Romero, 1991. Desarrollo de un modelo matemático general para los procesos fermentativos, Cinética de la degradación anaerobia, Ph.D. Thesis, University of Cádiz (Spain), Serv. Pub. Univ. Cádiz] shows that a large amount of inert matter is present in the fixed-bed reactor.

  14. Chemical Kinetic Influences of Alkyl Chain Structure on the High Pressure and Temperature Oxidation of a Representative Unsaturated Biodiesel: Methyl Nonenoate.

    PubMed

    Fridlyand, Aleksandr; Goldsborough, S Scott; Brezinsky, Kenneth

    2015-07-16

    The high pressure and temperature oxidation of methyl trans-2-nonenoate, methyl trans-3-nonenoate, 1-octene, and trans-2-octene are investigated experimentally to probe the influence of the double bond position on the chemical kinetics of long esters and alkenes. Single pulse shock tube experiments are performed in the ranges p = 3.8-6.2 MPa and T = 850-1500 K, with an average reaction time of 2 ms. Gas chromatographic measurements indicate increased reactivity for trans-2-octene compared to 1-octene, whereas both methyl nonenoate isomers have reactivities similar to that of 1-octene. A difference in the yield of stable intermediates is observed for the octenes when compared to the methyl nonenoates. Chemical kinetic models are developed with the aid of the Reaction Mechanism Generator to interpret the experimental results. The models are created using two different base chemistry submodels to investigate the influence of the foundational chemistry (i.e., C0-C4), whereas Monte Carlo simulations are performed to examine the quality of agreement with the experimental results. Significant uncertainties are found in the chemistry of unsaturated esters with the double bonds located close to the ester groups. This work highlights the importance of the foundational chemistry in predictive chemical kinetics of biodiesel combustion at engine relevant conditions.

  15. Venus - Lakshmi Planum and Maxwell Montes

    NASA Image and Video Library

    1996-03-07

    This full resolution radar image from NASA Magellan spacecraft is centered along the eastern edge of Lakshmi Planum and the western edge of Maxwell Montes. http://photojournal.jpl.nasa.gov/catalog/PIA00241

  16. Perception of Elasticity in the Kinetic Illusory Object with Phase Differences in Inducer Motion

    PubMed Central

    Masuda, Tomohiro; Sato, Kazuki; Murakoshi, Takuma; Utsumi, Ken; Kimura, Atsushi; Shirai, Nobu; Kanazawa, So; Yamaguchi, Masami K.; Wada, Yuji

    2013-01-01

    Background It is known that subjective contours are perceived even when a figure involves motion. However, whether this includes the perception of rigidity or deformation of an illusory surface remains unknown. In particular, since most visual stimuli used in previous studies were generated in order to induce illusory rigid objects, the potential perception of material properties such as rigidity or elasticity in these illusory surfaces has not been examined. Here, we elucidate whether the magnitude of phase difference in oscillation influences the visual impressions of an object's elasticity (Experiment 1) and identify whether such elasticity perceptions are accompanied by the shape of the subjective contours, which can be assumed to be strongly correlated with the perception of rigidity (Experiment 2). Methodology/Principal Findings In Experiment 1, the phase differences in the oscillating motion of inducers were controlled to investigate whether they influenced the visual impression of an illusory object's elasticity. The results demonstrated that the impression of the elasticity of an illusory surface with subjective contours was systematically flipped with the degree of phase difference. In Experiment 2, we examined whether the subjective contours of a perceived object appeared linear or curved using multi-dimensional scaling analysis. The results indicated that the contours of a moving illusory object were perceived as more curved than linear in all phase-difference conditions. Conclusions/Significance These findings suggest that the phase difference in an object's motion is a significant factor in the material perception of motion-related elasticity. PMID:24205281

  17. Fixed forced detection for fast SPECT Monte-Carlo simulation

    NASA Astrophysics Data System (ADS)

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

    2018-03-01

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

  18. Fixed forced detection for fast SPECT Monte-Carlo simulation.

    PubMed

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

    2018-03-02

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

  19. Accurate Monte Carlo simulations for nozzle design, commissioning and quality assurance for a proton radiation therapy facility.

    PubMed

    Paganetti, H; Jiang, H; Lee, S Y; Kooy, H M

    2004-07-01

    Monte Carlo dosimetry calculations are essential methods in radiation therapy. To take full advantage of this tool, the beam delivery system has to be simulated in detail and the initial beam parameters have to be known accurately. The modeling of the beam delivery system itself opens various areas where Monte Carlo calculations prove extremely helpful, such as for design and commissioning of a therapy facility as well as for quality assurance verification. The gantry treatment nozzles at the Northeast Proton Therapy Center (NPTC) at Massachusetts General Hospital (MGH) were modeled in detail using the GEANT4.5.2 Monte Carlo code. For this purpose, various novel solutions for simulating irregular shaped objects in the beam path, like contoured scatterers, patient apertures or patient compensators, were found. The four-dimensional, in time and space, simulation of moving parts, such as the modulator wheel, was implemented. Further, the appropriate physics models and cross sections for proton therapy applications were defined. We present comparisons between measured data and simulations. These show that by modeling the treatment nozzle with millimeter accuracy, it is possible to reproduce measured dose distributions with an accuracy in range and modulation width, in the case of a spread-out Bragg peak (SOBP), of better than 1 mm. The excellent agreement demonstrates that the simulations can even be used to generate beam data for commissioning treatment planning systems. The Monte Carlo nozzle model was used to study mechanical optimization in terms of scattered radiation and secondary radiation in the design of the nozzles. We present simulations on the neutron background. Further, the Monte Carlo calculations supported commissioning efforts in understanding the sensitivity of beam characteristics and how these influence the dose delivered. We present the sensitivity of dose distributions in water with respect to various beam parameters and geometrical misalignments

  20. Fast quantum Monte Carlo on a GPU

    NASA Astrophysics Data System (ADS)

    Lutsyshyn, Y.

    2015-02-01

    We present a scheme for the parallelization of quantum Monte Carlo method on graphical processing units, focusing on variational Monte Carlo simulation of bosonic systems. We use asynchronous execution schemes with shared memory persistence, and obtain an excellent utilization of the accelerator. The CUDA code is provided along with a package that simulates liquid helium-4. The program was benchmarked on several models of Nvidia GPU, including Fermi GTX560 and M2090, and the Kepler architecture K20 GPU. Special optimization was developed for the Kepler cards, including placement of data structures in the register space of the Kepler GPUs. Kepler-specific optimization is discussed.

  1. Hyperspectral imaging simulation of object under sea-sky background

    NASA Astrophysics Data System (ADS)

    Wang, Biao; Lin, Jia-xuan; Gao, Wei; Yue, Hui

    2016-10-01

    Remote sensing image simulation plays an important role in spaceborne/airborne load demonstration and algorithm development. Hyperspectral imaging is valuable in marine monitoring, search and rescue. On the demand of spectral imaging of objects under the complex sea scene, physics based simulation method of spectral image of object under sea scene is proposed. On the development of an imaging simulation model considering object, background, atmosphere conditions, sensor, it is able to examine the influence of wind speed, atmosphere conditions and other environment factors change on spectral image quality under complex sea scene. Firstly, the sea scattering model is established based on the Philips sea spectral model, the rough surface scattering theory and the water volume scattering characteristics. The measured bi directional reflectance distribution function (BRDF) data of objects is fit to the statistical model. MODTRAN software is used to obtain solar illumination on the sea, sky brightness, the atmosphere transmittance from sea to sensor and atmosphere backscattered radiance, and Monte Carlo ray tracing method is used to calculate the sea surface object composite scattering and spectral image. Finally, the object spectrum is acquired by the space transformation, radiation degradation and adding the noise. The model connects the spectrum image with the environmental parameters, the object parameters, and the sensor parameters, which provide a tool for the load demonstration and algorithm development.

  2. Diagnosing Undersampling Biases in Monte Carlo Eigenvalue and Flux Tally Estimates

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

    Perfetti, Christopher M.; Rearden, Bradley T.; Marshall, William J.

    2017-02-08

    Here, this study focuses on understanding the phenomena in Monte Carlo simulations known as undersampling, in which Monte Carlo tally estimates may not encounter a sufficient number of particles during each generation to obtain unbiased tally estimates. Steady-state Monte Carlo simulations were performed using the KENO Monte Carlo tools within the SCALE code system for models of several burnup credit applications with varying degrees of spatial and isotopic complexities, and the incidence and impact of undersampling on eigenvalue and flux estimates were examined. Using an inadequate number of particle histories in each generation was found to produce a maximum bias of ~100 pcm in eigenvalue estimates and biases that exceeded 10% in fuel pin flux tally estimates. Having quantified the potential magnitude of undersampling biases in eigenvalue and flux tally estimates in these systems, this study then investigated whether Markov Chain Monte Carlo convergence metrics could be integrated into Monte Carlo simulations to predict the onset and magnitude of undersampling biases. Five potential metrics for identifying undersampling biases were implemented in the SCALE code system and evaluated for their ability to predict undersampling biases by comparing the test metric scores with the observed undersampling biases. Finally, of the five convergence metrics that were investigated, three (the Heidelberger-Welch relative half-width, the Gelman-Rubin more » $$\\hat{R}_c$$ diagnostic, and tally entropy) showed the potential to accurately predict the behavior of undersampling biases in the responses examined.« less

  3. Dunes in Nectaris Montes

    NASA Image and Video Library

    2018-05-14

    This image from NASA's Mars Reconnaissance Orbiter (MRO) shows some of these on the slopes of Nectaris Montes within Coprates Chasma. Sand dunes in Valles Marineris can be impressive in size, with steep slopes that seem to climb and descend. The brighter bedforms are inactive while the bigger dunes move over the landscape, burying and exhuming the surface. https://photojournal.jpl.nasa.gov/catalog/PIA22455

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

    PubMed

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

    2015-02-01

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

  5. A versatile multi-objective FLUKA optimization using Genetic Algorithms

    NASA Astrophysics Data System (ADS)

    Vlachoudis, Vasilis; Antoniucci, Guido Arnau; Mathot, Serge; Kozlowska, Wioletta Sandra; Vretenar, Maurizio

    2017-09-01

    Quite often Monte Carlo simulation studies require a multi phase-space optimization, a complicated task, heavily relying on the operator experience and judgment. Examples of such calculations are shielding calculations with stringent conditions in the cost, in residual dose, material properties and space available, or in the medical field optimizing the dose delivered to a patient under a hadron treatment. The present paper describes our implementation inside flair[1] the advanced user interface of FLUKA[2,3] of a multi-objective Genetic Algorithm[Erreur ! Source du renvoi introuvable.] to facilitate the search for the optimum solution.

  6. Monte Carlo simulation of electrothermal atomization on a desktop personal computer

    NASA Astrophysics Data System (ADS)

    Histen, Timothy E.; Güell, Oscar A.; Chavez, Iris A.; Holcombea, James A.

    1996-07-01

    Monte Carlo simulations have been applied to electrothermal atomization (ETA) using a tubular atomizer (e.g. graphite furnace) because of the complexity in the geometry, heating, molecular interactions, etc. The intense computational time needed to accurately model ETA often limited its effective implementation to the use of supercomputers. However, with the advent of more powerful desktop processors, this is no longer the case. A C-based program has been developed and can be used under Windows TM or DOS. With this program, basic parameters such as furnace dimensions, sample placement, furnace heating and kinetic parameters such as activation energies for desorption and adsorption can be varied to show the absorbance profile dependence on these parameters. Even data such as time-dependent spatial distribution of analyte inside the furnace can be collected. The DOS version also permits input of external temperaturetime data to permit comparison of simulated profiles with experimentally obtained absorbance data. The run-time versions are provided along with the source code. This article is an electronic publication in Spectrochimica Acta Electronica (SAE), the electronic section of Spectrochimica Acta Part B (SAB). The hardcopy text is accompanied by a diskette with a program (PC format), data files and text files.

  7. Electron kinetics at the plasma interface

    NASA Astrophysics Data System (ADS)

    Bronold, Franz Xaver; Fehske, Holger; Pamperin, Mathias; Thiessen, Elena

    2018-05-01

    The most fundamental response of an ionized gas to a macroscopic object is the formation of the plasma sheath. It is an electron depleted space charge region, adjacent to the object, which screens the object's negative charge arising from the accumulation of electrons from the plasma. The plasma sheath is thus the positively charged part of an electric double layer whose negatively charged part is inside the wall. In the course of the Transregional Collaborative Research Center SFB/TRR24 we investigated, from a microscopic point of view, the elementary charge transfer processes responsible for the electric double layer at a floating plasma-wall interface and made first steps towards a description of the negative part of the layer inside the wall. Below we review our work in a colloquial manner, describe possible extensions, and identify key issues which need to be resolved to make further progress in the understanding of the electron kinetics across plasma-wall interfaces. Contribution to the Topical Issue "Fundamentals of Complex Plasmas", edited by Jürgen Meichsner, Michael Bonitz, Holger Fehske, Alexander Piel.

  8. Analytical Applications of Monte Carlo Techniques.

    ERIC Educational Resources Information Center

    Guell, Oscar A.; Holcombe, James A.

    1990-01-01

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

  9. Kinetic Risk Factors of Running-Related Injuries in Female Recreational Runners.

    PubMed

    Napier, Christopher; MacLean, Christopher L; Maurer, Jessica; Taunton, Jack E; Hunt, Michael A

    2018-05-30

    Our objective was to prospectively investigate the association of kinetic variables with running-related injury (RRI) risk. Seventy-four healthy female recreational runners ran on an instrumented treadmill while 3D kinetic and kinematic data were collected. Kinetic outcomes were vertical impact transient, average vertical loading rate, instantaneous vertical loading rate, active peak, vertical impulse, and peak braking force (PBF). Participants followed a 15-week half-marathon training program. Exposure time (hours of running) was calculated from start of program until onset of injury, loss to follow-up, or end of program. After converting kinetic variables from continuous to ordinal variables based on tertiles, Cox proportional hazard models with competing risks were fit for each variable independently, before analysis in a forward stepwise multivariable model. Sixty-five participants were included in the final analysis, with a 33.8% injury rate. PBF was the only kinetic variable that was a significant predictor of RRI. Runners in the highest tertile (PBF <-0.27 BW) were injured at 5.08 times the rate of those in the middle tertile and 7.98 times the rate of those in the lowest tertile. When analyzed in the multivariable model, no kinetic variables made a significant contribution to predicting injury beyond what had already been accounted for by PBF alone. Findings from this study suggest PBF is associated with a significantly higher injury hazard ratio in female recreational runners and should be considered as a target for gait retraining interventions. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

  10. A prospectus on kinetic heliophysics

    NASA Astrophysics Data System (ADS)

    Howes, Gregory G.

    2017-05-01

    Under the low density and high temperature conditions typical of heliospheric plasmas, the macroscopic evolution of the heliosphere is strongly affected by the kinetic plasma physics governing fundamental microphysical mechanisms. Kinetic turbulence, collisionless magnetic reconnection, particle acceleration, and kinetic instabilities are four poorly understood, grand-challenge problems that lie at the new frontier of kinetic heliophysics. The increasing availability of high cadence and high phase-space resolution measurements of particle velocity distributions by current and upcoming spacecraft missions and of massively parallel nonlinear kinetic simulations of weakly collisional heliospheric plasmas provides the opportunity to transform our understanding of these kinetic mechanisms through the full utilization of the information contained in the particle velocity distributions. Several major considerations for future investigations of kinetic heliophysics are examined. Turbulent dissipation followed by particle heating is highlighted as an inherently two-step process in weakly collisional plasmas, distinct from the more familiar case in fluid theory. Concerted efforts must be made to tackle the big-data challenge of visualizing the high-dimensional (3D-3V) phase space of kinetic plasma theory through physics-based reductions. Furthermore, the development of innovative analysis methods that utilize full velocity-space measurements, such as the field-particle correlation technique, will enable us to gain deeper insight into these four grand-challenge problems of kinetic heliophysics. A systems approach to tackle the multi-scale problem of heliophysics through a rigorous connection between the kinetic physics at microscales and the self-consistent evolution of the heliosphere at macroscales will propel the field of kinetic heliophysics into the future.

  11. A prospectus on kinetic heliophysics

    PubMed Central

    2017-01-01

    Under the low density and high temperature conditions typical of heliospheric plasmas, the macroscopic evolution of the heliosphere is strongly affected by the kinetic plasma physics governing fundamental microphysical mechanisms. Kinetic turbulence, collisionless magnetic reconnection, particle acceleration, and kinetic instabilities are four poorly understood, grand-challenge problems that lie at the new frontier of kinetic heliophysics. The increasing availability of high cadence and high phase-space resolution measurements of particle velocity distributions by current and upcoming spacecraft missions and of massively parallel nonlinear kinetic simulations of weakly collisional heliospheric plasmas provides the opportunity to transform our understanding of these kinetic mechanisms through the full utilization of the information contained in the particle velocity distributions. Several major considerations for future investigations of kinetic heliophysics are examined. Turbulent dissipation followed by particle heating is highlighted as an inherently two-step process in weakly collisional plasmas, distinct from the more familiar case in fluid theory. Concerted efforts must be made to tackle the big-data challenge of visualizing the high-dimensional (3D-3V) phase space of kinetic plasma theory through physics-based reductions. Furthermore, the development of innovative analysis methods that utilize full velocity-space measurements, such as the field-particle correlation technique, will enable us to gain deeper insight into these four grand-challenge problems of kinetic heliophysics. A systems approach to tackle the multi-scale problem of heliophysics through a rigorous connection between the kinetic physics at microscales and the self-consistent evolution of the heliosphere at macroscales will propel the field of kinetic heliophysics into the future. PMID:29104421

  12. Simulation on reactor TRIGA Puspati core kinetics fueled with thorium (Th) based fuel element

    NASA Astrophysics Data System (ADS)

    Mohammed, Abdul Aziz; Pauzi, Anas Muhamad; Rahman, Shaik Mohmmed Haikhal Abdul; Zin, Muhamad Rawi Muhammad; Jamro, Rafhayudi; Idris, Faridah Mohamad

    2016-01-01

    In confronting global energy requirement and the search for better technologies, there is a real case for widening the range of potential variations in the design of nuclear power plants. Smaller and simpler reactors are attractive, provided they can meet safety and security standards and non-proliferation issues. On fuel cycle aspect, thorium fuel cycles produce much less plutonium and other radioactive transuranic elements than uranium fuel cycles. Although not fissile itself, Th-232 will absorb slow neutrons to produce uranium-233 (233U), which is fissile. By introducing Thorium, the numbers of highly enriched uranium fuel element can be reduced while maintaining the core neutronic performance. This paper describes the core kinetic of a small research reactor core like TRIGA fueled with a Th filled fuel element matrix using a general purpose Monte Carlo N-Particle (MCNP) code.

  13. Scattering properties of electromagnetic waves from metal object in the lower terahertz region

    NASA Astrophysics Data System (ADS)

    Chen, Gang; Dang, H. X.; Hu, T. Y.; Su, Xiang; Lv, R. C.; Li, Hao; Tan, X. M.; Cui, T. J.

    2018-01-01

    An efficient hybrid algorithm is proposed to analyze the electromagnetic scattering properties of metal objects in the lower terahertz (THz) frequency. The metal object can be viewed as perfectly electrical conducting object with a slightly rough surface in the lower THz region. Hence the THz scattered field from metal object can be divided into coherent and incoherent parts. The physical optics and truncated-wedge incremental-length diffraction coefficients methods are combined to compute the coherent part; while the small perturbation method is used for the incoherent part. With the MonteCarlo method, the radar cross section of the rough metal surface is computed by the multilevel fast multipole algorithm and the proposed hybrid algorithm, respectively. The numerical results show that the proposed algorithm has good accuracy to simulate the scattering properties rapidly in the lower THz region.

  14. Maximum proton kinetic energy and patient-generated neutron fluence considerations in proton beam arc delivery radiation therapy.

    PubMed

    Sengbusch, E; Pérez-Andújar, A; DeLuca, P M; Mackie, T R

    2009-02-01

    Several compact proton accelerator systems for use in proton therapy have recently been proposed. Of paramount importance to the development of such an accelerator system is the maximum kinetic energy of protons, immediately prior to entry into the patient, that must be reached by the treatment system. The commonly used value for the maximum kinetic energy required for a medical proton accelerator is 250 MeV, but it has not been demonstrated that this energy is indeed necessary to treat all or most patients eligible for proton therapy. This article quantifies the maximum kinetic energy of protons, immediately prior to entry into the patient, necessary to treat a given percentage of patients with rotational proton therapy, and examines the impact of this energy threshold on the cost and feasibility of a compact, gantry-mounted proton accelerator treatment system. One hundred randomized treatment plans from patients treated with IMRT were analyzed. The maximum radiological pathlength from the surface of the patient to the distal edge of the treatment volume was obtained for 180 degrees continuous arc proton therapy and for 180 degrees split arc proton therapy (two 90 degrees arcs) using CT# profiles from the Pinnacle (Philips Medical Systems, Madison, WI) treatment planning system. In each case, the maximum kinetic energy of protons, immediately prior to entry into the patient, that would be necessary to treat the patient was calculated using proton range tables for various media. In addition, Monte Carlo simulations were performed to quantify neutron production in a water phantom representing a patient as a function of the maximum proton kinetic energy achievable by a proton treatment system. Protons with a kinetic energy of 240 MeV, immediately prior to entry into the patient, were needed to treat 100% of patients in this study. However, it was shown that 90% of patients could be treated at 198 MeV, and 95% of patients could be treated at 207 MeV. Decreasing the

  15. Second-order Kinetics of DTPA and Plutonium in Rat Plasma

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

    Miller, Guthrie; Poudel, Deepesh; Klumpp, John Allan

    We report that in 2008, Serandour et al. reported on their in vitro experiment involving rat plasma samples obtained after an intravenous intake of plutonium citrate. Different amounts of DTPA were added to the plasma samples and the percentage of low-molecular-weight plutonium measured. Only when the DTPA dosage was three orders of magnitude greater than the recommended 30 μmol/kg was 100% of the plutonium apparently in the form of chelate. These data were modeled assuming three competing chemical reactions with other molecules that bind with plutonium. Here, time-dependent second-order kinetics of these reactions are calculated, intended eventually to become partmore » of a complete biokinetic model of DTPA action on actinides in laboratory animals or humans. The probability distribution of the ratio of stability constants for the reactants was calculated using Markov Chain Monte Carlo. In conclusion, these calculations substantiate that the inclusion of more reactions is needed in order to be in agreement with known stability constants.« less

  16. Second-order Kinetics of DTPA and Plutonium in Rat Plasma

    DOE PAGES

    Miller, Guthrie; Poudel, Deepesh; Klumpp, John Allan; ...

    2017-11-15

    We report that in 2008, Serandour et al. reported on their in vitro experiment involving rat plasma samples obtained after an intravenous intake of plutonium citrate. Different amounts of DTPA were added to the plasma samples and the percentage of low-molecular-weight plutonium measured. Only when the DTPA dosage was three orders of magnitude greater than the recommended 30 μmol/kg was 100% of the plutonium apparently in the form of chelate. These data were modeled assuming three competing chemical reactions with other molecules that bind with plutonium. Here, time-dependent second-order kinetics of these reactions are calculated, intended eventually to become partmore » of a complete biokinetic model of DTPA action on actinides in laboratory animals or humans. The probability distribution of the ratio of stability constants for the reactants was calculated using Markov Chain Monte Carlo. In conclusion, these calculations substantiate that the inclusion of more reactions is needed in order to be in agreement with known stability constants.« less

  17. Monte Carlo: in the beginning and some great expectations

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

    Metropolis, N.

    1985-01-01

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

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

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

    Enright, S; Asprinio, A; Lu, L

    2014-06-01

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

  19. A Monte Carlo analysis of the Viking lander dynamics at touchdown. [soft landing simulation

    NASA Technical Reports Server (NTRS)

    Muraca, R. J.; Campbell, J. W.; King, C. A.

    1975-01-01

    The performance of the Viking lander has been evaluated by using a Monte Carlo simulation, and all results are presented in statistical form. The primary objectives of this analysis were as follows: (1) to determine the three sigma design values of maximum rigid body accelerations and the minimum clearance of the lander body during landing; (2) to determine the probability of an unstable landing; and (3) to determine the probability of the lander body striking a rock. Two configurations were analyzed with the only difference being in the ability of the primary landing gear struts to carry tension loads.

  20. Grand canonical ensemble Monte Carlo simulation of the dCpG/proflavine crystal hydrate.

    PubMed

    Resat, H; Mezei, M

    1996-09-01

    The grand canonical ensemble Monte Carlo molecular simulation method is used to investigate hydration patterns in the crystal hydrate structure of the dCpG/proflavine intercalated complex. The objective of this study is to show by example that the recently advocated grand canonical ensemble simulation is a computationally efficient method for determining the positions of the hydrating water molecules in protein and nucleic acid structures. A detailed molecular simulation convergence analysis and an analogous comparison of the theoretical results with experiments clearly show that the grand ensemble simulations can be far more advantageous than the comparable canonical ensemble simulations.