WorldWideScience

Sample records for monte-carlo uncertainty analysis

  1. Uncertainty analysis in Monte Carlo criticality computations

    International Nuclear Information System (INIS)

    Qi Ao

    2011-01-01

    Highlights: ► Two types of uncertainty methods for k eff Monte Carlo computations are examined. ► Sampling method has the least restrictions on perturbation but computing resources. ► Analytical method is limited to small perturbation on material properties. ► Practicality relies on efficiency, multiparameter applicability and data availability. - Abstract: Uncertainty analysis is imperative for nuclear criticality risk assessments when using Monte Carlo neutron transport methods to predict the effective neutron multiplication factor (k eff ) for fissionable material systems. For the validation of Monte Carlo codes for criticality computations against benchmark experiments, code accuracy and precision are measured by both the computational bias and uncertainty in the bias. The uncertainty in the bias accounts for known or quantified experimental, computational and model uncertainties. For the application of Monte Carlo codes for criticality analysis of fissionable material systems, an administrative margin of subcriticality must be imposed to provide additional assurance of subcriticality for any unknown or unquantified uncertainties. Because of a substantial impact of the administrative margin of subcriticality on economics and safety of nuclear fuel cycle operations, recently increasing interests in reducing the administrative margin of subcriticality make the uncertainty analysis in criticality safety computations more risk-significant. This paper provides an overview of two most popular k eff uncertainty analysis methods for Monte Carlo criticality computations: (1) sampling-based methods, and (2) analytical methods. Examples are given to demonstrate their usage in the k eff uncertainty analysis due to uncertainties in both neutronic and non-neutronic parameters of fissionable material systems.

  2. Uncertainty Propagation in Monte Carlo Depletion Analysis

    International Nuclear Information System (INIS)

    Shim, Hyung Jin; Kim, Yeong-il; Park, Ho Jin; Joo, Han Gyu; Kim, Chang Hyo

    2008-01-01

    A new formulation aimed at quantifying uncertainties of Monte Carlo (MC) tallies such as k eff and the microscopic reaction rates of nuclides and nuclide number densities in MC depletion analysis and examining their propagation behaviour as a function of depletion time step (DTS) is presented. It is shown that the variance of a given MC tally used as a measure of its uncertainty in this formulation arises from four sources; the statistical uncertainty of the MC tally, uncertainties of microscopic cross sections and nuclide number densities, and the cross correlations between them and the contribution of the latter three sources can be determined by computing the correlation coefficients between the uncertain variables. It is also shown that the variance of any given nuclide number density at the end of each DTS stems from uncertainties of the nuclide number densities (NND) and microscopic reaction rates (MRR) of nuclides at the beginning of each DTS and they are determined by computing correlation coefficients between these two uncertain variables. To test the viability of the formulation, we conducted MC depletion analysis for two sample depletion problems involving a simplified 7x7 fuel assembly (FA) and a 17x17 PWR FA, determined number densities of uranium and plutonium isotopes and their variances as well as k ∞ and its variance as a function of DTS, and demonstrated the applicability of the new formulation for uncertainty propagation analysis that need be followed in MC depletion computations. (authors)

  3. Improved Monte Carlo Method for PSA Uncertainty Analysis

    International Nuclear Information System (INIS)

    Choi, Jongsoo

    2016-01-01

    The treatment of uncertainty is an important issue for regulatory decisions. Uncertainties exist from knowledge limitations. A probabilistic approach has exposed some of these limitations and provided a framework to assess their significance and assist in developing a strategy to accommodate them in the regulatory process. The uncertainty analysis (UA) is usually based on the Monte Carlo method. This paper proposes a Monte Carlo UA approach to calculate the mean risk metrics accounting for the SOKC between basic events (including CCFs) using efficient random number generators and to meet Capability Category III of the ASME/ANS PRA standard. Audit calculation is needed in PSA regulatory reviews of uncertainty analysis results submitted for licensing. The proposed Monte Carlo UA approach provides a high degree of confidence in PSA reviews. All PSA needs accounting for the SOKC between event probabilities to meet the ASME/ANS PRA standard

  4. Improved Monte Carlo Method for PSA Uncertainty Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Choi, Jongsoo [Korea Institute of Nuclear Safety, Daejeon (Korea, Republic of)

    2016-10-15

    The treatment of uncertainty is an important issue for regulatory decisions. Uncertainties exist from knowledge limitations. A probabilistic approach has exposed some of these limitations and provided a framework to assess their significance and assist in developing a strategy to accommodate them in the regulatory process. The uncertainty analysis (UA) is usually based on the Monte Carlo method. This paper proposes a Monte Carlo UA approach to calculate the mean risk metrics accounting for the SOKC between basic events (including CCFs) using efficient random number generators and to meet Capability Category III of the ASME/ANS PRA standard. Audit calculation is needed in PSA regulatory reviews of uncertainty analysis results submitted for licensing. The proposed Monte Carlo UA approach provides a high degree of confidence in PSA reviews. All PSA needs accounting for the SOKC between event probabilities to meet the ASME/ANS PRA standard.

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

    Science.gov (United States)

    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.

  6. Uncertainty Analysis of Power Grid Investment Capacity Based on Monte Carlo

    Science.gov (United States)

    Qin, Junsong; Liu, Bingyi; Niu, Dongxiao

    By analyzing the influence factors of the investment capacity of power grid, to depreciation cost, sales price and sales quantity, net profit, financing and GDP of the second industry as the dependent variable to build the investment capacity analysis model. After carrying out Kolmogorov-Smirnov test, get the probability distribution of each influence factor. Finally, obtained the grid investment capacity uncertainty of analysis results by Monte Carlo simulation.

  7. Parameter sensitivity and uncertainty of the forest carbon flux model FORUG : a Monte Carlo analysis

    Energy Technology Data Exchange (ETDEWEB)

    Verbeeck, H.; Samson, R.; Lemeur, R. [Ghent Univ., Ghent (Belgium). Laboratory of Plant Ecology; Verdonck, F. [Ghent Univ., Ghent (Belgium). Dept. of Applied Mathematics, Biometrics and Process Control

    2006-06-15

    The FORUG model is a multi-layer process-based model that simulates carbon dioxide (CO{sub 2}) and water exchange between forest stands and the atmosphere. The main model outputs are net ecosystem exchange (NEE), total ecosystem respiration (TER), gross primary production (GPP) and evapotranspiration. This study used a sensitivity analysis to identify the parameters contributing to NEE uncertainty in the FORUG model. The aim was to determine if it is necessary to estimate the uncertainty of all parameters of a model to determine overall output uncertainty. Data used in the study were the meteorological and flux data of beech trees in Hesse. The Monte Carlo method was used to rank sensitivity and uncertainty parameters in combination with a multiple linear regression. Simulations were run in which parameters were assigned probability distributions and the effect of variance in the parameters on the output distribution was assessed. The uncertainty of the output for NEE was estimated. Based on the arbitrary uncertainty of 10 key parameters, a standard deviation of 0.88 Mg C per year per NEE was found, which was equal to 24 per cent of the mean value of NEE. The sensitivity analysis showed that the overall output uncertainty of the FORUG model could be determined by accounting for only a few key parameters, which were identified as corresponding to critical parameters in the literature. It was concluded that the 10 most important parameters determined more than 90 per cent of the output uncertainty. High ranking parameters included soil respiration; photosynthesis; and crown architecture. It was concluded that the Monte Carlo technique is a useful tool for ranking the uncertainty of parameters of process-based forest flux models. 48 refs., 2 tabs., 2 figs.

  8. Stand-alone core sensitivity and uncertainty analysis of ALFRED from Monte Carlo simulations

    International Nuclear Information System (INIS)

    Pérez-Valseca, A.-D.; Espinosa-Paredes, G.; François, J.L.; Vázquez Rodríguez, A.; Martín-del-Campo, C.

    2017-01-01

    Highlights: • Methodology based on Monte Carlo simulation. • Sensitivity analysis of Lead Fast Reactor (LFR). • Uncertainty and regression analysis of LFR. • 10% change in the core inlet flow, the response in thermal power change is 0.58%. • 2.5% change in the inlet lead temperature the response is 1.87% in power. - Abstract: The aim of this paper is the sensitivity and uncertainty analysis of a Lead-Cooled Fast Reactor (LFR) based on Monte Carlo simulation of sizes up to 2000. The methodology developed in this work considers the uncertainty of sensitivities and uncertainty of output variables due to a single-input-variable variation. The Advanced Lead fast Reactor European Demonstrator (ALFRED) is analyzed to determine the behavior of the essential parameters due to effects of mass flow and temperature of liquid lead. The ALFRED core mathematical model developed in this work is fully transient, which takes into account the heat transfer in an annular fuel pellet design, the thermo-fluid in the core, and the neutronic processes, which are modeled with point kinetic with feedback fuel temperature and expansion effects. The sensitivity evaluated in terms of the relative standard deviation (RSD) showed that for 10% change in the core inlet flow, the response in thermal power change is 0.58%, and for 2.5% change in the inlet lead temperature is 1.87%. The regression analysis with mass flow rate as the predictor variable showed statistically valid cubic correlations for neutron flux and linear relationship neutron flux as a function of the lead temperature. No statistically valid correlation was observed for the reactivity as a function of the mass flow rate and for the lead temperature. These correlations are useful for the study, analysis, and design of any LFR.

  9. Uncertainty analysis using Monte Carlo method in the measurement of phase by ESPI

    International Nuclear Information System (INIS)

    Anguiano Morales, Marcelino; Martinez, Amalia; Rayas, J. A.; Cordero, Raul R.

    2008-01-01

    A method for simultaneously measuring whole field in-plane displacements by using optical fiber and based on the dual-beam illumination principle electronic speckle pattern interferometry (ESPI) is presented in this paper. A set of single mode optical fibers and beamsplitter are employed to split the laser beam into four beams of equal intensity.One pair of fibers is utilized to illuminate the sample in the horizontal plane so it is sensitive only to horizontal in-plane displacement. Another pair of optical fibers is set to be sensitive only to vertical in-plane displacement. Each pair of optical fibers differs in longitude to avoid unwanted interference. By means of a Fourier-transform method of fringe-pattern analysis (Takeda method), we can obtain the quantitative data of whole field displacements. We found the uncertainty associated with the phases by mean of Monte Carlo-based technique

  10. A smart Monte Carlo procedure for production costing and uncertainty analysis

    International Nuclear Information System (INIS)

    Parker, C.; Stremel, J.

    1996-01-01

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

  11. Uncertainty analysis in the simulation of an HPGe detector using the Monte Carlo Code MCNP5

    International Nuclear Information System (INIS)

    Gallardo, Sergio; Pozuelo, Fausto; Querol, Andrea; Verdu, Gumersindo; Rodenas, Jose; Ortiz, J.; Pereira, Claubia

    2013-01-01

    A gamma spectrometer including an HPGe detector is commonly used for environmental radioactivity measurements. Many works have been focused on the simulation of the HPGe detector using Monte Carlo codes such as MCNP5. However, the simulation of this kind of detectors presents important difficulties due to the lack of information from manufacturers and due to loss of intrinsic properties in aging detectors. Some parameters such as the active volume or the Ge dead layer thickness are many times unknown and are estimated during simulations. In this work, a detailed model of an HPGe detector and a petri dish containing a certified gamma source has been done. The certified gamma source contains nuclides to cover the energy range between 50 and 1800 keV. As a result of the simulation, the Pulse Height Distribution (PHD) is obtained and the efficiency curve can be calculated from net peak areas and taking into account the certified activity of the source. In order to avoid errors due to the net area calculation, the simulated PHD is treated using the GammaVision software. On the other hand, it is proposed to use the Noether-Wilks formula to do an uncertainty analysis of model with the main goal of determining the efficiency curve of this detector and its associated uncertainty. The uncertainty analysis has been focused on dead layer thickness at different positions of the crystal. Results confirm the important role of the dead layer thickness in the low energy range of the efficiency curve. In the high energy range (from 300 to 1800 keV) the main contribution to the absolute uncertainty is due to variations in the active volume. (author)

  12. Uncertainty analysis in the simulation of an HPGe detector using the Monte Carlo Code MCNP5

    Energy Technology Data Exchange (ETDEWEB)

    Gallardo, Sergio; Pozuelo, Fausto; Querol, Andrea; Verdu, Gumersindo; Rodenas, Jose, E-mail: sergalbe@upv.es [Universitat Politecnica de Valencia, Valencia, (Spain). Instituto de Seguridad Industrial, Radiofisica y Medioambiental (ISIRYM); Ortiz, J. [Universitat Politecnica de Valencia, Valencia, (Spain). Servicio de Radiaciones. Lab. de Radiactividad Ambiental; Pereira, Claubia [Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, MG (Brazil). Departamento de Engenharia Nuclear

    2013-07-01

    A gamma spectrometer including an HPGe detector is commonly used for environmental radioactivity measurements. Many works have been focused on the simulation of the HPGe detector using Monte Carlo codes such as MCNP5. However, the simulation of this kind of detectors presents important difficulties due to the lack of information from manufacturers and due to loss of intrinsic properties in aging detectors. Some parameters such as the active volume or the Ge dead layer thickness are many times unknown and are estimated during simulations. In this work, a detailed model of an HPGe detector and a petri dish containing a certified gamma source has been done. The certified gamma source contains nuclides to cover the energy range between 50 and 1800 keV. As a result of the simulation, the Pulse Height Distribution (PHD) is obtained and the efficiency curve can be calculated from net peak areas and taking into account the certified activity of the source. In order to avoid errors due to the net area calculation, the simulated PHD is treated using the GammaVision software. On the other hand, it is proposed to use the Noether-Wilks formula to do an uncertainty analysis of model with the main goal of determining the efficiency curve of this detector and its associated uncertainty. The uncertainty analysis has been focused on dead layer thickness at different positions of the crystal. Results confirm the important role of the dead layer thickness in the low energy range of the efficiency curve. In the high energy range (from 300 to 1800 keV) the main contribution to the absolute uncertainty is due to variations in the active volume. (author)

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

    Science.gov (United States)

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

    2018-03-01

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

  14. Uncertainty Propagation Analysis for the Monte Carlo Time-Dependent Simulations

    International Nuclear Information System (INIS)

    Shaukata, Nadeem; Shim, Hyung Jin

    2015-01-01

    In this paper, a conventional method to control the neutron population for super-critical systems is implemented. Instead of considering the cycles, the simulation is divided in time intervals. At the end of each time interval, neutron population control is applied on the banked neutrons. Randomly selected neutrons are discarded, until the size of neutron population matches the initial neutron histories at the beginning of time simulation. A time-dependent simulation mode has also been implemented in the development version of SERPENT 2 Monte Carlo code. In this mode, sequential population control mechanism has been proposed for modeling of prompt super-critical systems. A Monte Carlo method has been properly used in TART code for dynamic criticality calculations. For super-critical systems, the neutron population is allowed to grow over a period of time. The neutron population is uniformly combed to return it to the neutron population started with at the beginning of time boundary. In this study, conventional time-dependent Monte Carlo (TDMC) algorithm is implemented. There is an exponential growth of neutron population in estimation of neutron density tally for super-critical systems and the number of neutrons being tracked exceed the memory of the computer. In order to control this exponential growth at the end of each time boundary, a conventional time cut-off controlling population strategy is included in TDMC. A scale factor is introduced to tally the desired neutron density at the end of each time boundary. The main purpose of this paper is the quantification of uncertainty propagation in neutron densities at the end of each time boundary for super-critical systems. This uncertainty is caused by the uncertainty resulting from the introduction of scale factor. The effectiveness of TDMC is examined for one-group infinite homogeneous problem (the rod model) and two-group infinite homogeneous problem. The desired neutron density is tallied by the introduction of

  15. Uncertainty Propagation Analysis for the Monte Carlo Time-Dependent Simulations

    Energy Technology Data Exchange (ETDEWEB)

    Shaukata, Nadeem; Shim, Hyung Jin [Seoul National University, Seoul (Korea, Republic of)

    2015-10-15

    In this paper, a conventional method to control the neutron population for super-critical systems is implemented. Instead of considering the cycles, the simulation is divided in time intervals. At the end of each time interval, neutron population control is applied on the banked neutrons. Randomly selected neutrons are discarded, until the size of neutron population matches the initial neutron histories at the beginning of time simulation. A time-dependent simulation mode has also been implemented in the development version of SERPENT 2 Monte Carlo code. In this mode, sequential population control mechanism has been proposed for modeling of prompt super-critical systems. A Monte Carlo method has been properly used in TART code for dynamic criticality calculations. For super-critical systems, the neutron population is allowed to grow over a period of time. The neutron population is uniformly combed to return it to the neutron population started with at the beginning of time boundary. In this study, conventional time-dependent Monte Carlo (TDMC) algorithm is implemented. There is an exponential growth of neutron population in estimation of neutron density tally for super-critical systems and the number of neutrons being tracked exceed the memory of the computer. In order to control this exponential growth at the end of each time boundary, a conventional time cut-off controlling population strategy is included in TDMC. A scale factor is introduced to tally the desired neutron density at the end of each time boundary. The main purpose of this paper is the quantification of uncertainty propagation in neutron densities at the end of each time boundary for super-critical systems. This uncertainty is caused by the uncertainty resulting from the introduction of scale factor. The effectiveness of TDMC is examined for one-group infinite homogeneous problem (the rod model) and two-group infinite homogeneous problem. The desired neutron density is tallied by the introduction of

  16. Uncertainty Analysis Based on Sparse Grid Collocation and Quasi-Monte Carlo Sampling with Application in Groundwater Modeling

    Science.gov (United States)

    Zhang, G.; Lu, D.; Ye, M.; Gunzburger, M.

    2011-12-01

    Markov Chain Monte Carlo (MCMC) methods have been widely used in many fields of uncertainty analysis to estimate the posterior distributions of parameters and credible intervals of predictions in the Bayesian framework. However, in practice, MCMC may be computationally unaffordable due to slow convergence and the excessive number of forward model executions required, especially when the forward model is expensive to compute. Both disadvantages arise from the curse of dimensionality, i.e., the posterior distribution is usually a multivariate function of parameters. Recently, sparse grid method has been demonstrated to be an effective technique for coping with high-dimensional interpolation or integration problems. Thus, in order to accelerate the forward model and avoid the slow convergence of MCMC, we propose a new method for uncertainty analysis based on sparse grid interpolation and quasi-Monte Carlo sampling. First, we construct a polynomial approximation of the forward model in the parameter space by using the sparse grid interpolation. This approximation then defines an accurate surrogate posterior distribution that can be evaluated repeatedly at minimal computational cost. Second, instead of using MCMC, a quasi-Monte Carlo method is applied to draw samples in the parameter space. Then, the desired probability density function of each prediction is approximated by accumulating the posterior density values of all the samples according to the prediction values. Our method has the following advantages: (1) the polynomial approximation of the forward model on the sparse grid provides a very efficient evaluation of the surrogate posterior distribution; (2) the quasi-Monte Carlo method retains the same accuracy in approximating the PDF of predictions but avoids all disadvantages of MCMC. The proposed method is applied to a controlled numerical experiment of groundwater flow modeling. The results show that our method attains the same accuracy much more efficiently

  17. Application of Monte Carlo Methods to Perform Uncertainty and Sensitivity Analysis on Inverse Water-Rock Reactions with NETPATH

    Energy Technology Data Exchange (ETDEWEB)

    McGraw, David [Desert Research Inst. (DRI), Reno, NV (United States); Hershey, Ronald L. [Desert Research Inst. (DRI), Reno, NV (United States)

    2016-06-01

    Methods were developed to quantify uncertainty and sensitivity for NETPATH inverse water-rock reaction models and to calculate dissolved inorganic carbon, carbon-14 groundwater travel times. The NETPATH models calculate upgradient groundwater mixing fractions that produce the downgradient target water chemistry along with amounts of mineral phases that are either precipitated or dissolved. Carbon-14 groundwater travel times are calculated based on the upgradient source-water fractions, carbonate mineral phase changes, and isotopic fractionation. Custom scripts and statistical code were developed for this study to facilitate modifying input parameters, running the NETPATH simulations, extracting relevant output, postprocessing the results, and producing graphs and summaries. The scripts read userspecified values for each constituent’s coefficient of variation, distribution, sensitivity parameter, maximum dissolution or precipitation amounts, and number of Monte Carlo simulations. Monte Carlo methods for analysis of parametric uncertainty assign a distribution to each uncertain variable, sample from those distributions, and evaluate the ensemble output. The uncertainty in input affected the variability of outputs, namely source-water mixing, phase dissolution and precipitation amounts, and carbon-14 travel time. Although NETPATH may provide models that satisfy the constraints, it is up to the geochemist to determine whether the results are geochemically reasonable. Two example water-rock reaction models from previous geochemical reports were considered in this study. Sensitivity analysis was also conducted to evaluate the change in output caused by a small change in input, one constituent at a time. Results were standardized to allow for sensitivity comparisons across all inputs, which results in a representative value for each scenario. The approach yielded insight into the uncertainty in water-rock reactions and travel times. For example, there was little

  18. Monte Carlo eigenfunction strategies and uncertainties

    International Nuclear Information System (INIS)

    Gast, R.C.; Candelore, N.R.

    1974-01-01

    Comparisons of convergence rates for several possible eigenfunction source strategies led to the selection of the ''straight'' analog of the analytic power method as the source strategy for Monte Carlo eigenfunction calculations. To insure a fair game strategy, the number of histories per iteration increases with increasing iteration number. The estimate of eigenfunction uncertainty is obtained from a modification of a proposal by D. B. MacMillan and involves only estimates of the usual purely statistical component of uncertainty and a serial correlation coefficient of lag one. 14 references. (U.S.)

  19. Propagating Mixed Uncertainties in Cyber Attacker Payoffs: Exploration of Two-Phase Monte Carlo Sampling and Probability Bounds Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Chatterjee, Samrat; Tipireddy, Ramakrishna; Oster, Matthew R.; Halappanavar, Mahantesh

    2016-09-16

    Securing cyber-systems on a continual basis against a multitude of adverse events is a challenging undertaking. Game-theoretic approaches, that model actions of strategic decision-makers, are increasingly being applied to address cybersecurity resource allocation challenges. Such game-based models account for multiple player actions and represent cyber attacker payoffs mostly as point utility estimates. Since a cyber-attacker’s payoff generation mechanism is largely unknown, appropriate representation and propagation of uncertainty is a critical task. In this paper we expand on prior work and focus on operationalizing the probabilistic uncertainty quantification framework, for a notional cyber system, through: 1) representation of uncertain attacker and system-related modeling variables as probability distributions and mathematical intervals, and 2) exploration of uncertainty propagation techniques including two-phase Monte Carlo sampling and probability bounds analysis.

  20. APPLICATION OF BAYESIAN MONTE CARLO ANALYSIS TO A LAGRANGIAN PHOTOCHEMICAL AIR QUALITY MODEL. (R824792)

    Science.gov (United States)

    Uncertainties in ozone concentrations predicted with a Lagrangian photochemical air quality model have been estimated using Bayesian Monte Carlo (BMC) analysis. Bayesian Monte Carlo analysis provides a means of combining subjective "prior" uncertainty estimates developed ...

  1. Uncertainties in models of tropospheric ozone based on Monte Carlo analysis: Tropospheric ozone burdens, atmospheric lifetimes and surface distributions

    Science.gov (United States)

    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

  2. Predictive uncertainty analysis of a saltwater intrusion model using null-space Monte Carlo

    DEFF Research Database (Denmark)

    Herckenrath, Daan; Langevin, Christian D.; Doherty, John

    2011-01-01

    variability did not make a noticeable difference to the uncertainty of the prediction. With this higher level of heterogeneity, however, the computational burden of generating calibration-constrained parameter fields approximately doubled. Predictive uncertainty variance computed through the NSMC method...

  3. Uncertainty in return period analysis of combined sewer overflow effects using embedded Monte Carlo simulations

    NARCIS (Netherlands)

    Grum, M.; Aalderink, R.H.

    1999-01-01

    The rerun periods of detrimental effects ate often used as design criteria in urban storm water management. Considerable uncertainty is associated with the models used. This is either ignored or pooled with the inherent event to event variation such as rainfall depth It is here argued that

  4. Design and analysis of Monte Carlo experiments

    NARCIS (Netherlands)

    Kleijnen, Jack P.C.; Gentle, J.E.; Haerdle, W.; Mori, Y.

    2012-01-01

    By definition, computer simulation or Monte Carlo models are not solved by mathematical analysis (such as differential calculus), but are used for numerical experimentation. The goal of these experiments is to answer questions about the real world; i.e., the experimenters may use their models to

  5. Efficiency enhancement of optimized Latin hypercube sampling strategies: Application to Monte Carlo uncertainty analysis and meta-modeling

    Science.gov (United States)

    Rajabi, Mohammad Mahdi; Ataie-Ashtiani, Behzad; Janssen, Hans

    2015-02-01

    The majority of literature regarding optimized Latin hypercube sampling (OLHS) is devoted to increasing the efficiency of these sampling strategies through the development of new algorithms based on the combination of innovative space-filling criteria and specialized optimization schemes. However, little attention has been given to the impact of the initial design that is fed into the optimization algorithm, on the efficiency of OLHS strategies. Previous studies, as well as codes developed for OLHS, have relied on one of the following two approaches for the selection of the initial design in OLHS: (1) the use of random points in the hypercube intervals (random LHS), and (2) the use of midpoints in the hypercube intervals (midpoint LHS). Both approaches have been extensively used, but no attempt has been previously made to compare the efficiency and robustness of their resulting sample designs. In this study we compare the two approaches and show that the space-filling characteristics of OLHS designs are sensitive to the initial design that is fed into the optimization algorithm. It is also illustrated that the space-filling characteristics of OLHS designs based on midpoint LHS are significantly better those based on random LHS. The two approaches are compared by incorporating their resulting sample designs in Monte Carlo simulation (MCS) for uncertainty propagation analysis, and then, by employing the sample designs in the selection of the training set for constructing non-intrusive polynomial chaos expansion (NIPCE) meta-models which subsequently replace the original full model in MCSs. The analysis is based on two case studies involving numerical simulation of density dependent flow and solute transport in porous media within the context of seawater intrusion in coastal aquifers. We show that the use of midpoint LHS as the initial design increases the efficiency and robustness of the resulting MCSs and NIPCE meta-models. The study also illustrates that this

  6. Bayesian phylogeny analysis via stochastic approximation Monte Carlo

    KAUST Repository

    Cheon, Sooyoung; Liang, Faming

    2009-01-01

    in simulating from the posterior distribution of phylogenetic trees, rendering the inference ineffective. In this paper, we apply an advanced Monte Carlo algorithm, the stochastic approximation Monte Carlo algorithm, to Bayesian phylogeny analysis. Our method

  7. Uncertainty Analysis and Overtopping Risk Evaluation of Maroon Dam withMonte Carlo and Latin Hypercube Methods

    Directory of Open Access Journals (Sweden)

    J. M. Vali Samani

    2016-02-01

    Full Text Available Introduction: The greatest part of constructed dams belongs to embankment dams and there are many examples of their failures throughout history. About one-third of the world’s dam failures have been caused by flood overtopping, which indicates that flood overtopping is an important factor affecting reservoir projects’ safety. Moreover, because of a poor understanding of the randomness of floods, reservoir water levels during flood seasons are often lowered artificially in order to avoid overtopping and protect the lives and property of downstream residents. So, estimation of dam overtopping risk with regard to uncertainties is more important than achieving the dam’s safety. This study presents the procedure for risk evaluation of dam overtopping due to various uncertaintiess in inflows and reservoir initial condition. Materials and Methods: This study aims to present a practical approach and compare the different uncertainty analysis methods in the evaluation of dam overtopping risk due to flood. For this purpose, Monte Carlo simulation and Latin hypercube sampling methods were used to calculate the overtopping risk, evaluate the uncertainty, and calculate the highest water level during different flood events. To assess these methods from a practical point of view, the Maroon dam was chosen for the case study. Figure. 1 indicates the work procedure, including three parts: 1 Identification and evaluation of effective factors on flood routing and dam overtopping, 2 Data collection and analysis for reservoir routing and uncertainty analysis, 3 Uncertainty and risk analysis. Figure 1- Diagram of dam overtopping risk evaluation Results and Discussion: Figure 2 shows the results of the computed overtopping risks for the Maroon Dam without considering the wind effect, for the initial water level of 504 m as an example. As it is shown in Figure. 2, the trends of the risk curves computed by the different uncertainty analysis methods are similar

  8. The use of Monte-Carlo simulation and order statistics for uncertainty analysis of a LBLOCA transient (LOFT-L2-5)

    International Nuclear Information System (INIS)

    Chojnacki, E.; Benoit, J.P.

    2007-01-01

    Best estimate computer codes are increasingly used in nuclear industry for the accident management procedures and have been planned to be used for the licensing procedures. Contrary to conservative codes which are supposed to give penalizing results, best estimate codes attempt to calculate accidental transients in a realistic way. It becomes therefore of prime importance, in particular for technical organization as IRSN in charge of safety assessment, to know the uncertainty on the results of such codes. Thus, CSNI has sponsored few years ago (published in 1998) the Uncertainty Methods Study (UMS) program on uncertainty methodologies used for a SBLOCA transient (LSTF-CL-18) and is now supporting the BEMUSE program for a LBLOCA transient (LOFT-L2-5). The large majority of BEMUSE participants (9 out of 10) use uncertainty methodologies based on a probabilistic modelling and all of them use Monte-Carlo simulations to propagate the uncertainties through their computer codes. Also, all of 'probabilistic participants' intend to use order statistics to determine the sampling size of the Monte-Carlo simulation and to derive the uncertainty ranges associated to their computer calculations. The first aim of this paper is to remind the advantages and also the assumptions of the probabilistic modelling and more specifically of order statistics (as Wilks' formula) in uncertainty methodologies. Indeed Monte-Carlo methods provide flexible and extremely powerful techniques for solving many of the uncertainty propagation problems encountered in nuclear safety analysis. However it is important to keep in mind that probabilistic methods are data intensive. That means, probabilistic methods cannot produce robust results unless a considerable body of information has been collected. A main interest of the use of order statistics results is to allow to take into account an unlimited number of uncertain parameters and, from a restricted number of code calculations to provide statistical

  9. Systematic uncertainties on Monte Carlo simulation of lead based ADS

    International Nuclear Information System (INIS)

    Embid, M.; Fernandez, R.; Garcia-Sanz, J.M.; Gonzalez, E.

    1999-01-01

    Computer simulations of the neutronic behaviour of ADS systems foreseen for actinide and fission product transmutation are affected by many sources of systematic uncertainties, both from the nuclear data and by the methodology selected when applying the codes. Several actual ADS Monte Carlo simulations are presented, comparing different options both for the data and for the methodology, evaluating the relevance of the different uncertainties. (author)

  10. Monte Carlo parameter studies and uncertainty analyses with MCNP5

    International Nuclear Information System (INIS)

    Brown, F. B.; Sweezy, J. E.; Hayes, R.

    2004-01-01

    A software tool called mcnp p study has been developed to automate the setup, execution, and collection of results from a series of MCNP5 Monte Carlo calculations. This tool provides a convenient means of performing parameter studies, total uncertainty analyses, parallel job execution on clusters, stochastic geometry modeling, and other types of calculations where a series of MCNP5 jobs must be performed with varying problem input specifications. (authors)

  11. Monte Carlo criticality analysis for dissolvers with neutron poison

    International Nuclear Information System (INIS)

    Yu, Deshun; Dong, Xiufang; Pu, Fuxiang.

    1987-01-01

    Criticality analysis for dissolvers with neutron poison is given on the basis of Monte Carlo method. In Monte Carlo calculations of thermal neutron group parameters for fuel pieces, neutron transport length is determined in terms of maximum cross section approach. A set of related effective multiplication factors (K eff ) are calculated by Monte Carlo method for the three cases. Related numerical results are quite useful for the design and operation of this kind of dissolver in the criticality safety analysis. (author)

  12. Latent uncertainties of the precalculated track Monte Carlo method

    International Nuclear Information System (INIS)

    Renaud, Marc-André; Seuntjens, Jan; Roberge, David

    2015-01-01

    Purpose: While significant progress has been made in speeding up Monte Carlo (MC) dose calculation methods, they remain too time-consuming for the purpose of inverse planning. To achieve clinically usable calculation speeds, a precalculated Monte Carlo (PMC) algorithm for proton and electron transport was developed to run on graphics processing units (GPUs). The algorithm utilizes pregenerated particle track data from conventional MC codes for different materials such as water, bone, and lung to produce dose distributions in voxelized phantoms. While PMC methods have been described in the past, an explicit quantification of the latent uncertainty arising from the limited number of unique tracks in the pregenerated track bank is missing from the paper. With a proper uncertainty analysis, an optimal number of tracks in the pregenerated track bank can be selected for a desired dose calculation uncertainty. Methods: Particle tracks were pregenerated for electrons and protons using EGSnrc and GEANT4 and saved in a database. The PMC algorithm for track selection, rotation, and transport was implemented on the Compute Unified Device Architecture (CUDA) 4.0 programming framework. PMC dose distributions were calculated in a variety of media and compared to benchmark dose distributions simulated from the corresponding general-purpose MC codes in the same conditions. A latent uncertainty metric was defined and analysis was performed by varying the pregenerated track bank size and the number of simulated primary particle histories and comparing dose values to a “ground truth” benchmark dose distribution calculated to 0.04% average uncertainty in voxels with dose greater than 20% of D max . Efficiency metrics were calculated against benchmark MC codes on a single CPU core with no variance reduction. Results: Dose distributions generated using PMC and benchmark MC codes were compared and found to be within 2% of each other in voxels with dose values greater than 20% of the

  13. Latent uncertainties of the precalculated track Monte Carlo method

    Energy Technology Data Exchange (ETDEWEB)

    Renaud, Marc-André; Seuntjens, Jan [Medical Physics Unit, McGill University, Montreal, Quebec H3G 1A4 (Canada); Roberge, David [Département de radio-oncologie, Centre Hospitalier de l’Université de Montréal, Montreal, Quebec H2L 4M1 (Canada)

    2015-01-15

    Purpose: While significant progress has been made in speeding up Monte Carlo (MC) dose calculation methods, they remain too time-consuming for the purpose of inverse planning. To achieve clinically usable calculation speeds, a precalculated Monte Carlo (PMC) algorithm for proton and electron transport was developed to run on graphics processing units (GPUs). The algorithm utilizes pregenerated particle track data from conventional MC codes for different materials such as water, bone, and lung to produce dose distributions in voxelized phantoms. While PMC methods have been described in the past, an explicit quantification of the latent uncertainty arising from the limited number of unique tracks in the pregenerated track bank is missing from the paper. With a proper uncertainty analysis, an optimal number of tracks in the pregenerated track bank can be selected for a desired dose calculation uncertainty. Methods: Particle tracks were pregenerated for electrons and protons using EGSnrc and GEANT4 and saved in a database. The PMC algorithm for track selection, rotation, and transport was implemented on the Compute Unified Device Architecture (CUDA) 4.0 programming framework. PMC dose distributions were calculated in a variety of media and compared to benchmark dose distributions simulated from the corresponding general-purpose MC codes in the same conditions. A latent uncertainty metric was defined and analysis was performed by varying the pregenerated track bank size and the number of simulated primary particle histories and comparing dose values to a “ground truth” benchmark dose distribution calculated to 0.04% average uncertainty in voxels with dose greater than 20% of D{sub max}. Efficiency metrics were calculated against benchmark MC codes on a single CPU core with no variance reduction. Results: Dose distributions generated using PMC and benchmark MC codes were compared and found to be within 2% of each other in voxels with dose values greater than 20% of

  14. Uncertainty of the Soil–Water Characteristic Curve and Its Effects on Slope Seepage and Stability Analysis under Conditions of Rainfall Using the Markov Chain Monte Carlo Method

    Directory of Open Access Journals (Sweden)

    Weiping Liu

    2017-10-01

    Full Text Available It is important to determine the soil–water characteristic curve (SWCC for analyzing slope seepage and stability under the conditions of rainfall. However, SWCCs exhibit high uncertainty because of complex influencing factors, which has not been previously considered in slope seepage and stability analysis under conditions of rainfall. This study aimed to evaluate the uncertainty of the SWCC and its effects on the seepage and stability analysis of an unsaturated soil slope under conditions of rainfall. The SWCC model parameters were treated as random variables. An uncertainty evaluation of the parameters was conducted based on the Bayesian approach and the Markov chain Monte Carlo (MCMC method. Observed data from granite residual soil were used to test the uncertainty of the SWCC. Then, different confidence intervals for the model parameters of the SWCC were constructed. The slope seepage and stability analysis under conditions of rainfall with the SWCC of different confidence intervals was investigated using finite element software (SEEP/W and SLOPE/W. The results demonstrated that SWCC uncertainty had significant effects on slope seepage and stability. In general, the larger the percentile value, the greater the reduction of negative pore-water pressure in the soil layer and the lower the safety factor of the slope. Uncertainties in the model parameters of the SWCC can lead to obvious errors in predicted pore-water pressure profiles and the estimated safety factor of the slope under conditions of rainfall.

  15. Pore-scale uncertainty quantification with multilevel Monte Carlo

    KAUST Repository

    Icardi, Matteo; Hoel, Haakon; Long, Quan; Tempone, Raul

    2014-01-01

    . Since there are no generic ways to parametrize the randomness in the porescale structures, Monte Carlo techniques are the most accessible to compute statistics. We propose a multilevel Monte Carlo (MLMC) technique to reduce the computational cost

  16. Eigenvalue sensitivity analysis and uncertainty quantification in SCALE6.2.1 using continuous-energy Monte Carlo Method

    Energy Technology Data Exchange (ETDEWEB)

    Labarile, A.; Barrachina, T.; Miró, R.; Verdú, G., E-mail: alabarile@iqn.upv.es, E-mail: tbarrachina@iqn.upv.es, E-mail: rmiro@iqn.upv.es, E-mail: gverdu@iqn.upv.es [Institute for Industrial, Radiophysical and Environmental Safety - ISIRYM, Valencia (Spain); Pereira, C., E-mail: claubia@nuclear.ufmg.br [Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, MG (Brazil). Departamento de Engenharia Nuclear

    2017-07-01

    The use of Best-Estimate computer codes is one of the greatest concerns in the nuclear industry especially for licensing analysis. Of paramount importance is the estimation of the uncertainties of the whole system to establish the safety margins based on highly reliable results. The estimation of these uncertainties should be performed by applying a methodology to propagate the uncertainties from the input parameters and the models implemented in the code to the output parameters. This study employs two different approaches for the Sensitivity Analysis (SA) and Uncertainty Quantification (UQ), the adjoint-based perturbation theory of TSUNAMI-3D, and the stochastic sampling technique of SAMPLER/KENO. The cases studied are two models of Light Water Reactors in the framework of the OECD/NEA UAM-LWR benchmark, a Boiling Water Reactor (BWR) and a Pressurized Water Reactor (PWR). Both of them at Hot Full Power (HFP) and Hot Zero Power (HZP) conditions, with and without control rod. This work presents the results of k{sub eff} from different simulation, and discuss the comparison of the two methods employed. In particular, a list of the major contributors to the uncertainty of k{sub eff} in terms of microscopic cross sections; their sensitivity coefficients; a comparison between the results of the two modules and with reference values; statistical information from the stochastic approach, and the probability and statistical confidence reached in the simulations. The reader will find all these information discussed in this paper. (author)

  17. Pore-scale uncertainty quantification with multilevel Monte Carlo

    KAUST Repository

    Icardi, Matteo

    2014-01-06

    Computational fluid dynamics (CFD) simulations of pore-scale transport processes in porous media have recently gained large popularity. However the geometrical details of the pore structures can be known only in a very low number of samples and the detailed flow computations can be carried out only on a limited number of cases. The explicit introduction of randomness in the geometry and in other setup parameters can be crucial for the optimization of pore-scale investigations for random homogenization. Since there are no generic ways to parametrize the randomness in the porescale structures, Monte Carlo techniques are the most accessible to compute statistics. We propose a multilevel Monte Carlo (MLMC) technique to reduce the computational cost of estimating quantities of interest within a prescribed accuracy constraint. Random samples of pore geometries with a hierarchy of geometrical complexities and grid refinements, are synthetically generated and used to propagate the uncertainties in the flow simulations and compute statistics of macro-scale effective parameters.

  18. Propagation of nuclear data uncertainties in fuel cycle calculations using Monte-Carlo technique

    International Nuclear Information System (INIS)

    Diez, C.J.; Cabellos, O.; Martinez, J.S.

    2011-01-01

    Nowadays, the knowledge of uncertainty propagation in depletion calculations is a critical issue because of the safety and economical performance of fuel cycles. Response magnitudes such as decay heat, radiotoxicity and isotopic inventory and their uncertainties should be known to handle spent fuel in present fuel cycles (e.g. high burnup fuel programme) and furthermore in new fuel cycles designs (e.g. fast breeder reactors and ADS). To deal with this task, there are different error propagation techniques, deterministic (adjoint/forward sensitivity analysis) and stochastic (Monte-Carlo technique) to evaluate the error in response magnitudes due to nuclear data uncertainties. In our previous works, cross-section uncertainties were propagated using a Monte-Carlo technique to calculate the uncertainty of response magnitudes such as decay heat and neutron emission. Also, the propagation of decay data, fission yield and cross-section uncertainties was performed, but only isotopic composition was the response magnitude calculated. Following the previous technique, the nuclear data uncertainties are taken into account and propagated to response magnitudes, decay heat and radiotoxicity. These uncertainties are assessed during cooling time. To evaluate this Monte-Carlo technique, two different applications are performed. First, a fission pulse decay heat calculation is carried out to check the Monte-Carlo technique, using decay data and fission yields uncertainties. Then, the results, experimental data and reference calculation (JEFF Report20), are compared. Second, we assess the impact of basic nuclear data (activation cross-section, decay data and fission yields) uncertainties on relevant fuel cycle parameters (decay heat and radiotoxicity) for a conceptual design of a modular European Facility for Industrial Transmutation (EFIT) fuel cycle. After identifying which time steps have higher uncertainties, an assessment of which uncertainties have more relevance is performed

  19. Monte Carlo method in neutron activation analysis

    International Nuclear Information System (INIS)

    Majerle, M.; Krasa, A.; Svoboda, O.; Wagner, V.; Adam, J.; Peetermans, S.; Slama, O.; Stegajlov, V.I.; Tsupko-Sitnikov, V.M.

    2009-01-01

    Neutron activation detectors are a useful technique for the neutron flux measurements in spallation experiments. The study of the usefulness and the accuracy of this method at similar experiments was performed with the help of Monte Carlo codes MCNPX and FLUKA

  20. Comparative and Predictive Multimedia Assessments Using Monte Carlo Uncertainty Analyses

    Science.gov (United States)

    Whelan, G.

    2002-05-01

    Multiple-pathway frameworks (sometimes referred to as multimedia models) provide a platform for combining medium-specific environmental models and databases, such that they can be utilized in a more holistic assessment of contaminant fate and transport in the environment. These frameworks provide a relatively seamless transfer of information from one model to the next and from databases to models. Within these frameworks, multiple models are linked, resulting in models that consume information from upstream models and produce information to be consumed by downstream models. The Framework for Risk Analysis in Multimedia Environmental Systems (FRAMES) is an example, which allows users to link their models to other models and databases. FRAMES is an icon-driven, site-layout platform that is an open-architecture, object-oriented system that interacts with environmental databases; helps the user construct a Conceptual Site Model that is real-world based; allows the user to choose the most appropriate models to solve simulation requirements; solves the standard risk paradigm of release transport and fate; and exposure/risk assessments to people and ecology; and presents graphical packages for analyzing results. FRAMES is specifically designed allow users to link their own models into a system, which contains models developed by others. This paper will present the use of FRAMES to evaluate potential human health exposures using real site data and realistic assumptions from sources, through the vadose and saturated zones, to exposure and risk assessment at three real-world sites, using the Multimedia Environmental Pollutant Assessment System (MEPAS), which is a multimedia model contained within FRAMES. These real-world examples use predictive and comparative approaches coupled with a Monte Carlo analysis. A predictive analysis is where models are calibrated to monitored site data, prior to the assessment, and a comparative analysis is where models are not calibrated but

  1. Modern analysis of ion channeling data by Monte Carlo simulations

    Energy Technology Data Exchange (ETDEWEB)

    Nowicki, Lech [Andrzej SoItan Institute for Nuclear Studies, ul. Hoza 69, 00-681 Warsaw (Poland)]. E-mail: lech.nowicki@fuw.edu.pl; Turos, Andrzej [Institute of Electronic Materials Technology, Wolczynska 133, 01-919 Warsaw (Poland); Ratajczak, Renata [Andrzej SoItan Institute for Nuclear Studies, ul. Hoza 69, 00-681 Warsaw (Poland); Stonert, Anna [Andrzej SoItan Institute for Nuclear Studies, ul. Hoza 69, 00-681 Warsaw (Poland); Garrido, Frederico [Centre de Spectrometrie Nucleaire et Spectrometrie de Masse, CNRS-IN2P3-Universite Paris-Sud, 91405 Orsay (France)

    2005-10-15

    Basic scheme of ion channeling spectra Monte Carlo simulation is reformulated in terms of statistical sampling. The McChasy simulation code is described and two examples of the code applications are presented. These are: calculation of projectile flux in uranium dioxide crystal and defect analysis for ion implanted InGaAsP/InP superlattice. Virtues and pitfalls of defect analysis using Monte Carlo simulations are discussed.

  2. Bayesian phylogeny analysis via stochastic approximation Monte Carlo

    KAUST Repository

    Cheon, Sooyoung

    2009-11-01

    Monte Carlo methods have received much attention in the recent literature of phylogeny analysis. However, the conventional Markov chain Monte Carlo algorithms, such as the Metropolis-Hastings algorithm, tend to get trapped in a local mode in simulating from the posterior distribution of phylogenetic trees, rendering the inference ineffective. In this paper, we apply an advanced Monte Carlo algorithm, the stochastic approximation Monte Carlo algorithm, to Bayesian phylogeny analysis. Our method is compared with two popular Bayesian phylogeny software, BAMBE and MrBayes, on simulated and real datasets. The numerical results indicate that our method outperforms BAMBE and MrBayes. Among the three methods, SAMC produces the consensus trees which have the highest similarity to the true trees, and the model parameter estimates which have the smallest mean square errors, but costs the least CPU time. © 2009 Elsevier Inc. All rights reserved.

  3. Improvement and comparison of likelihood functions for model calibration and parameter uncertainty analysis within a Markov chain Monte Carlo scheme

    Science.gov (United States)

    Cheng, Qin-Bo; Chen, Xi; Xu, Chong-Yu; Reinhardt-Imjela, Christian; Schulte, Achim

    2014-11-01

    In this study, the likelihood functions for uncertainty analysis of hydrological models are compared and improved through the following steps: (1) the equivalent relationship between the Nash-Sutcliffe Efficiency coefficient (NSE) and the likelihood function with Gaussian independent and identically distributed residuals is proved; (2) a new estimation method of the Box-Cox transformation (BC) parameter is developed to improve the effective elimination of the heteroscedasticity of model residuals; and (3) three likelihood functions-NSE, Generalized Error Distribution with BC (BC-GED) and Skew Generalized Error Distribution with BC (BC-SGED)-are applied for SWAT-WB-VSA (Soil and Water Assessment Tool - Water Balance - Variable Source Area) model calibration in the Baocun watershed, Eastern China. Performances of calibrated models are compared using the observed river discharges and groundwater levels. The result shows that the minimum variance constraint can effectively estimate the BC parameter. The form of the likelihood function significantly impacts on the calibrated parameters and the simulated results of high and low flow components. SWAT-WB-VSA with the NSE approach simulates flood well, but baseflow badly owing to the assumption of Gaussian error distribution, where the probability of the large error is low, but the small error around zero approximates equiprobability. By contrast, SWAT-WB-VSA with the BC-GED or BC-SGED approach mimics baseflow well, which is proved in the groundwater level simulation. The assumption of skewness of the error distribution may be unnecessary, because all the results of the BC-SGED approach are nearly the same as those of the BC-GED approach.

  4. Study of Monte Carlo approach to experimental uncertainty propagation with MSTW 2008 PDFs

    CERN Document Server

    Watt, G.

    2012-01-01

    We investigate the Monte Carlo approach to propagation of experimental uncertainties within the context of the established 'MSTW 2008' global analysis of parton distribution functions (PDFs) of the proton at next-to-leading order in the strong coupling. We show that the Monte Carlo approach using replicas of the original data gives PDF uncertainties in good agreement with the usual Hessian approach using the standard Delta(chi^2) = 1 criterion, then we explore potential parameterisation bias by increasing the number of free parameters, concluding that any parameterisation bias is likely to be small, with the exception of the valence-quark distributions at low momentum fractions x. We motivate the need for a larger tolerance, Delta(chi^2) > 1, by making fits to restricted data sets and idealised consistent or inconsistent pseudodata. Instead of using data replicas, we alternatively produce PDF sets randomly distributed according to the covariance matrix of fit parameters including appropriate tolerance values,...

  5. Monte Carlo analysis of Musashi TRIGA mark II reactor core

    International Nuclear Information System (INIS)

    Matsumoto, Tetsuo

    1999-01-01

    The analysis of the TRIGA-II core at the Musashi Institute of Technology Research Reactor (Musashi reactor, 100 kW) was performed by the three-dimensional continuous-energy Monte Carlo code (MCNP4A). Effective multiplication factors (k eff ) for the several fuel-loading patterns including the initial core criticality experiment, the fuel element and control rod reactivity worth as well as the neutron flux measurements were used in the validation process of the physical model and neutron cross section data from the ENDF/B-V evaluation. The calculated k eff overestimated the experimental data by about 1.0%Δk/k for both the initial core and the several fuel-loading arrangements. The calculated reactivity worths of control rod and fuel element agree well the measured ones within the uncertainties. The comparison of neutron flux distribution was consistent with the experimental ones which were measured by activation methods at the sample irradiation tubes. All in all, the agreement between the MCNP predictions and the experimentally determined values is good, which indicated that the Monte Carlo model is enough to simulate the Musashi TRIGA-II reactor core. (author)

  6. An analysis of Monte Carlo tree search

    CSIR Research Space (South Africa)

    James, S

    2017-02-01

    Full Text Available Tree Search Steven James∗, George Konidaris† & Benjamin Rosman∗‡ ∗University of the Witwatersrand, Johannesburg, South Africa †Brown University, Providence RI 02912, USA ‡Council for Scientific and Industrial Research, Pretoria, South Africa steven....james@students.wits.ac.za, gdk@cs.brown.edu, brosman@csir.co.za Abstract Monte Carlo Tree Search (MCTS) is a family of directed search algorithms that has gained widespread attention in re- cent years. Despite the vast amount of research into MCTS, the effect of modifications...

  7. Monte Carlo methods for the reliability analysis of Markov systems

    International Nuclear Information System (INIS)

    Buslik, A.J.

    1985-01-01

    This paper presents Monte Carlo methods for the reliability analysis of Markov systems. Markov models are useful in treating dependencies between components. The present paper shows how the adjoint Monte Carlo method for the continuous time Markov process can be derived from the method for the discrete-time Markov process by a limiting process. The straightforward extensions to the treatment of mean unavailability (over a time interval) are given. System unavailabilities can also be estimated; this is done by making the system failed states absorbing, and not permitting repair from them. A forward Monte Carlo method is presented in which the weighting functions are related to the adjoint function. In particular, if the exact adjoint function is known then weighting factors can be constructed such that the exact answer can be obtained with a single Monte Carlo trial. Of course, if the exact adjoint function is known, there is no need to perform the Monte Carlo calculation. However, the formulation is useful since it gives insight into choices of the weight factors which will reduce the variance of the estimator

  8. Characterization of decommissioned reactor internals: Monte Carlo analysis technique

    International Nuclear Information System (INIS)

    Reid, B.D.; Love, E.F.; Luksic, A.T.

    1993-03-01

    This study discusses computer analysis techniques for determining activation levels of irradiated reactor component hardware to yield data for the Department of Energy's Greater-Than-Class C Low-Level Radioactive Waste Program. The study recommends the Monte Carlo Neutron/Photon (MCNP) computer code as the best analysis tool for this application and compares the technique to direct sampling methodology. To implement the MCNP analysis, a computer model would be developed to reflect the geometry, material composition, and power history of an existing shutdown reactor. MCNP analysis would then be performed using the computer model, and the results would be validated by comparison to laboratory analysis results from samples taken from the shutdown reactor. The report estimates uncertainties for each step of the computational and laboratory analyses; the overall uncertainty of the MCNP results is projected to be ±35%. The primary source of uncertainty is identified as the material composition of the components, and research is suggested to address that uncertainty

  9. Use of the Monte Carlo uncertainty combination method in nuclear reactor setpoint evaluation

    International Nuclear Information System (INIS)

    Berte, Frank J.

    2004-01-01

    This paper provides an overview of an alternate method for the performance of instrument uncertainty calculation and instrument setpoint determination, when a setpoint analysis requires application of techniques beyond that provided by the widely used 'Root Sum Squares' approach. The paper will address, when the application of the Monte Carlo (MC) method should be considered, application of the MC method when independent and/or dependent uncertainties are involved, and finally interpretation of results obtained. Both single module as well as instrument string sample applications will be presented. (author)

  10. Estimation of balance uncertainty using Direct Monte Carlo Simulation (DSMC) on a CPU-GPU architecture

    CSIR Research Space (South Africa)

    Bidgood, Peter M

    2017-01-01

    Full Text Available The estimation of balance uncertainty using conventional statistical and error propagation methods has been found to be both approximate and laborious to the point of being untenable. Direct Simulation by Monte Carlo (DSMC) has been shown...

  11. On Monte Carlo Simulation and Analysis of Electricity Markets

    International Nuclear Information System (INIS)

    Amelin, Mikael

    2004-07-01

    This dissertation is about how Monte Carlo simulation can be used to analyse electricity markets. There are a wide range of applications for simulation; for example, players in the electricity market can use simulation to decide whether or not an investment can be expected to be profitable, and authorities can by means of simulation find out which consequences a certain market design can be expected to have on electricity prices, environmental impact, etc. In the first part of the dissertation, the focus is which electricity market models are suitable for Monte Carlo simulation. The starting point is a definition of an ideal electricity market. Such an electricity market is partly practical from a mathematical point of view (it is simple to formulate and does not require too complex calculations) and partly it is a representation of the best possible resource utilisation. The definition of the ideal electricity market is followed by analysis how the reality differs from the ideal model, what consequences the differences have on the rules of the electricity market and the strategies of the players, as well as how non-ideal properties can be included in a mathematical model. Particularly, questions about environmental impact, forecast uncertainty and grid costs are studied. The second part of the dissertation treats the Monte Carlo technique itself. To reduce the number of samples necessary to obtain accurate results, variance reduction techniques can be used. Here, six different variance reduction techniques are studied and possible applications are pointed out. The conclusions of these studies are turned into a method for efficient simulation of basic electricity markets. The method is applied to some test systems and the results show that the chosen variance reduction techniques can produce equal or better results using 99% fewer samples compared to when the same system is simulated without any variance reduction technique. More complex electricity market models

  12. Sensitivity analysis for oblique incidence reflectometry using Monte Carlo simulations

    DEFF Research Database (Denmark)

    Kamran, Faisal; Andersen, Peter E.

    2015-01-01

    profiles. This article presents a sensitivity analysis of the technique in turbid media. Monte Carlo simulations are used to investigate the technique and its potential to distinguish the small changes between different levels of scattering. We present various regions of the dynamic range of optical...

  13. Monte Carlo Simulation of Influence of Input Parameters Uncertainty on Output Data

    International Nuclear Information System (INIS)

    Sobek, Lukas

    2010-01-01

    Input parameters of a complex system in the probabilistic simulation are treated by means of probability density function (PDF). The result of the simulation have also probabilistic character. Monte Carlo simulation is widely used to obtain predictions concerning the probability of the risk. The Monte Carlo method was performed to calculate histograms of PDF for release rate given by uncertainty in distribution coefficient of radionuclides 135 Cs and 235 U.

  14. Monte-Carlo-based uncertainty propagation with hierarchical models—a case study in dynamic torque

    Science.gov (United States)

    Klaus, Leonard; Eichstädt, Sascha

    2018-04-01

    For a dynamic calibration, a torque transducer is described by a mechanical model, and the corresponding model parameters are to be identified from measurement data. A measuring device for the primary calibration of dynamic torque, and a corresponding model-based calibration approach, have recently been developed at PTB. The complete mechanical model of the calibration set-up is very complex, and involves several calibration steps—making a straightforward implementation of a Monte Carlo uncertainty evaluation tedious. With this in mind, we here propose to separate the complete model into sub-models, with each sub-model being treated with individual experiments and analysis. The uncertainty evaluation for the overall model then has to combine the information from the sub-models in line with Supplement 2 of the Guide to the Expression of Uncertainty in Measurement. In this contribution, we demonstrate how to carry this out using the Monte Carlo method. The uncertainty evaluation involves various input quantities of different origin and the solution of a numerical optimisation problem.

  15. Range uncertainties in proton therapy and the role of Monte Carlo simulations

    International Nuclear Information System (INIS)

    Paganetti, Harald

    2012-01-01

    The main advantages of proton therapy are the reduced total energy deposited in the patient as compared to photon techniques and the finite range of the proton beam. The latter adds an additional degree of freedom to treatment planning. The range in tissue is associated with considerable uncertainties caused by imaging, patient setup, beam delivery and dose calculation. Reducing the uncertainties would allow a reduction of the treatment volume and thus allow a better utilization of the advantages of protons. This paper summarizes the role of Monte Carlo simulations when aiming at a reduction of range uncertainties in proton therapy. Differences in dose calculation when comparing Monte Carlo with analytical algorithms are analyzed as well as range uncertainties due to material constants and CT conversion. Range uncertainties due to biological effects and the role of Monte Carlo for in vivo range verification are discussed. Furthermore, the current range uncertainty recipes used at several proton therapy facilities are revisited. We conclude that a significant impact of Monte Carlo dose calculation can be expected in complex geometries where local range uncertainties due to multiple Coulomb scattering will reduce the accuracy of analytical algorithms. In these cases Monte Carlo techniques might reduce the range uncertainty by several mm. (topical review)

  16. Quasi-random Monte Carlo application in CGE systematic sensitivity analysis

    NARCIS (Netherlands)

    Chatzivasileiadis, T.

    2017-01-01

    The uncertainty and robustness of Computable General Equilibrium models can be assessed by conducting a Systematic Sensitivity Analysis. Different methods have been used in the literature for SSA of CGE models such as Gaussian Quadrature and Monte Carlo methods. This paper explores the use of

  17. Advanced Mesh-Enabled Monte carlo capability for Multi-Physics Reactor Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Wilson, Paul; Evans, Thomas; Tautges, Tim

    2012-12-24

    This project will accumulate high-precision fluxes throughout reactor geometry on a non- orthogonal grid of cells to support multi-physics coupling, in order to more accurately calculate parameters such as reactivity coefficients and to generate multi-group cross sections. This work will be based upon recent developments to incorporate advanced geometry and mesh capability in a modular Monte Carlo toolkit with computational science technology that is in use in related reactor simulation software development. Coupling this capability with production-scale Monte Carlo radiation transport codes can provide advanced and extensible test-beds for these developments. Continuous energy Monte Carlo methods are generally considered to be the most accurate computational tool for simulating radiation transport in complex geometries, particularly neutron transport in reactors. Nevertheless, there are several limitations for their use in reactor analysis. Most significantly, there is a trade-off between the fidelity of results in phase space, statistical accuracy, and the amount of computer time required for simulation. Consequently, to achieve an acceptable level of statistical convergence in high-fidelity results required for modern coupled multi-physics analysis, the required computer time makes Monte Carlo methods prohibitive for design iterations and detailed whole-core analysis. More subtly, the statistical uncertainty is typically not uniform throughout the domain, and the simulation quality is limited by the regions with the largest statistical uncertainty. In addition, the formulation of neutron scattering laws in continuous energy Monte Carlo methods makes it difficult to calculate adjoint neutron fluxes required to properly determine important reactivity parameters. Finally, most Monte Carlo codes available for reactor analysis have relied on orthogonal hexahedral grids for tallies that do not conform to the geometric boundaries and are thus generally not well

  18. The impact of Monte Carlo simulation: a scientometric analysis of scholarly literature

    CERN Document Server

    Pia, Maria Grazia; Bell, Zane W; Dressendorfer, Paul V

    2010-01-01

    A scientometric analysis of Monte Carlo simulation and Monte Carlo codes has been performed over a set of representative scholarly journals related to radiation physics. The results of this study are reported and discussed. They document and quantitatively appraise the role of Monte Carlo methods and codes in scientific research and engineering applications.

  19. Uncertainties in personal dosimetry for external radiation: A Monte Carlo approach

    International Nuclear Information System (INIS)

    Van Dijk, J. W. E.

    2006-01-01

    This paper explores the possibilities of numerical methods for uncertainty analysis of personal dosimetry systems. Using a numerical method based on Monte Carlo sampling the probability density function (PDF) of the dose measured using a personal dosemeter can be calculated using type-test measurements. From this PDF the combined standard uncertainty in the measurements with the dosemeter and the confidence interval can be calculated. The method calculates the output PDF directly from the PDFs of the inputs of the system such as the spectral distribution of the radiation and distributions of detector parameters like sensitivity and zero signal. The method can be used not only in its own right but also for validating other methods because it is not limited by restrictions that apply to using the Law of Propagation of Uncertainty and the Central Limit Theorem. The use of the method is demonstrated using the type-test data of the NRG-TLD. (authors)

  20. Exploring uncertainty in glacier mass balance modelling with Monte Carlo simulation

    NARCIS (Netherlands)

    Machguth, H.; Purves, R.S.; Oerlemans, J.; Hoelzle, M.; Paul, F.

    2008-01-01

    By means of Monte Carlo simulations we calculated uncertainty in modelled cumulative mass balance over 400 days at one particular point on the tongue of Morteratsch Glacier, Switzerland, using a glacier energy balance model of intermediate complexity. Before uncertainty assessment, the model was

  1. Propagation of Nuclear Data Uncertainties in Integral Measurements by Monte-Carlo Calculations

    Energy Technology Data Exchange (ETDEWEB)

    Noguere, G.; Bernard, D.; De Saint-Jean, C. [CEA Cadarache, 13 - Saint Paul lez Durance (France)

    2006-07-01

    Full text of the publication follows: The generation of Multi-group cross sections together with relevant uncertainties is fundamental to assess the quality of integral data. The key information that are needed to propagate the microscopic experimental uncertainties to macroscopic reactor calculations are (1) the experimental covariance matrices, (2) the correlations between the parameters of the model and (3) the covariance matrices for the multi-group cross sections. The propagation of microscopic errors by Monte-Carlo technique was applied to determine the accuracy of the integral trends provided by the OSMOSE experiment carried out in the MINERVE reactor of the CEA Cadarache. The technique consists in coupling resonance shape analysis and deterministic codes. The integral trend and its accuracy obtained on the {sup 237}Np(n,{gamma}) reaction will be presented. (author)

  2. Uncertainties associated with the use of the KENO Monte Carlo criticality codes

    International Nuclear Information System (INIS)

    Landers, N.F.; Petrie, L.M.

    1989-01-01

    The KENO multi-group Monte Carlo criticality codes have earned the reputation of being efficient, user friendly tools especially suited for the analysis of situations commonly encountered in the storage and transportation of fissile materials. Throughout their twenty years of service, a continuing effort has been made to maintain and improve these codes to meet the needs of the nuclear criticality safety community. Foremost among these needs is the knowledge of how to utilize the results safely and effectively. Therefore it is important that code users be aware of uncertainties that may affect their results. These uncertainties originate from approximations in the problem data, methods used to process cross sections, and assumptions, limitations and approximations within the criticality computer code itself. 6 refs., 8 figs., 1 tab

  3. Comparison of first order analysis and Monte Carlo methods in evaluating groundwater model uncertainty: a case study from an iron ore mine in the Pilbara Region of Western Australia

    Science.gov (United States)

    Firmani, G.; Matta, J.

    2012-04-01

    The expansion of mining in the Pilbara region of Western Australia is resulting in the need to develop better water strategies to make below water table resources accessible, manage surplus water and deal with water demands for processing ore and construction. In all these instances, understanding the local and regional hydrogeology is fundamental to allow sustainable mining; minimising the impacts to the environment. An understanding of the uncertainties of the hydrogeology is necessary to quantify the risks and make objective decisions rather than relying on subjective judgements. The aim of this paper is to review some of the methods proposed by the published literature and find approaches that can be practically implemented in an attempt to estimate model uncertainties. In particular, this paper adopts two general probabilistic approaches that address the parametric uncertainty estimation and its propagation in predictive scenarios: the first order analysis and Monte Carlo simulations. A case example application of the two techniques is also presented for the dewatering strategy of a large below water table open cut iron ore mine in the Pilbara region of Western Australia. This study demonstrates the weakness of the deterministic approach, as the coefficients of variation of some model parameters were greater than 1.0; and suggests a review of the model calibration method and conceptualisation. The uncertainty propagation into predictive scenarios was calculated assuming the parameters with a coefficient of variation higher than 0.25 as deterministic, due to computational difficulties to achieve an accurate result with the Monte Carlo method. The conclusion of this case study was that the first order analysis appears to be a successful and simple tool when the coefficients of variation of calibrated parameters are less than 0.25.

  4. Monte carlo depletion analysis of SMART core by MCNAP code

    International Nuclear Information System (INIS)

    Jung, Jong Sung; Sim, Hyung Jin; Kim, Chang Hyo; Lee, Jung Chan; Ji, Sung Kyun

    2001-01-01

    Depletion an analysis of SMART, a small-sized advanced integral PWR under development by KAERI, is conducted using the Monte Carlo (MC) depletion analysis program, MCNAP. The results are compared with those of the CASMO-3/ MASTER nuclear analysis. The difference between MASTER and MCNAP on k eff prediction is observed about 600pcm at BOC, and becomes smaller as the core burnup increases. The maximum difference bet ween two predict ions on fuel assembly (FA) normalized power distribution is about 6.6% radially , and 14.5% axially but the differences are observed to lie within standard deviation of MC estimations

  5. Reducing uncertainty of Monte Carlo estimated fatigue damage in offshore wind turbines using FORM

    DEFF Research Database (Denmark)

    H. Horn, Jan-Tore; Jensen, Jørgen Juncher

    2016-01-01

    Uncertainties related to fatigue damage estimation of non-linear systems are highly dependent on the tail behaviour and extreme values of the stress range distribution. By using a combination of the First Order Reliability Method (FORM) and Monte Carlo simulations (MCS), the accuracy of the fatigue...

  6. Asymptotic analysis of spatial discretizations in implicit Monte Carlo

    International Nuclear Information System (INIS)

    Densmore, Jeffery D.

    2009-01-01

    We perform an asymptotic analysis of spatial discretizations in Implicit Monte Carlo (IMC). We consider two asymptotic scalings: one that represents a time step that resolves the mean-free time, and one that corresponds to a fixed, optically large time step. We show that only the latter scaling results in a valid spatial discretization of the proper diffusion equation, and thus we conclude that IMC only yields accurate solutions when using optically large spatial cells if time steps are also optically large. We demonstrate the validity of our analysis with a set of numerical examples.

  7. Data Analysis Recipes: Using Markov Chain Monte Carlo

    Science.gov (United States)

    Hogg, David W.; Foreman-Mackey, Daniel

    2018-05-01

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

  8. Reliability analysis of neutron transport simulation using Monte Carlo method

    International Nuclear Information System (INIS)

    Souza, Bismarck A. de; Borges, Jose C.

    1995-01-01

    This work presents a statistical and reliability analysis covering data obtained by computer simulation of neutron transport process, using the Monte Carlo method. A general description of the method and its applications is presented. Several simulations, corresponding to slowing down and shielding problems have been accomplished. The influence of the physical dimensions of the materials and of the sample size on the reliability level of results was investigated. The objective was to optimize the sample size, in order to obtain reliable results, optimizing computation time. (author). 5 refs, 8 figs

  9. Propagation of statistical and nuclear data uncertainties in Monte Carlo burn-up calculations

    International Nuclear Information System (INIS)

    Garcia-Herranz, Nuria; Cabellos, Oscar; Sanz, Javier; Juan, Jesus; Kuijper, Jim C.

    2008-01-01

    Two methodologies to propagate the uncertainties on the nuclide inventory in combined Monte Carlo-spectrum and burn-up calculations are presented, based on sensitivity/uncertainty and random sampling techniques (uncertainty Monte Carlo method). Both enable the assessment of the impact of uncertainties in the nuclear data as well as uncertainties due to the statistical nature of the Monte Carlo neutron transport calculation. The methodologies are implemented in our MCNP-ACAB system, which combines the neutron transport code MCNP-4C and the inventory code ACAB. A high burn-up benchmark problem is used to test the MCNP-ACAB performance in inventory predictions, with no uncertainties. A good agreement is found with the results of other participants. This benchmark problem is also used to assess the impact of nuclear data uncertainties and statistical flux errors in high burn-up applications. A detailed calculation is performed to evaluate the effect of cross-section uncertainties in the inventory prediction, taking into account the temporal evolution of the neutron flux level and spectrum. Very large uncertainties are found at the unusually high burn-up of this exercise (800 MWd/kgHM). To compare the impact of the statistical errors in the calculated flux with respect to the cross uncertainties, a simplified problem is considered, taking a constant neutron flux level and spectrum. It is shown that, provided that the flux statistical deviations in the Monte Carlo transport calculation do not exceed a given value, the effect of the flux errors in the calculated isotopic inventory are negligible (even at very high burn-up) compared to the effect of the large cross-section uncertainties available at present in the data files

  10. Propagation of statistical and nuclear data uncertainties in Monte Carlo burn-up calculations

    Energy Technology Data Exchange (ETDEWEB)

    Garcia-Herranz, Nuria [Departamento de Ingenieria Nuclear, Universidad Politecnica de Madrid, UPM (Spain)], E-mail: nuria@din.upm.es; Cabellos, Oscar [Departamento de Ingenieria Nuclear, Universidad Politecnica de Madrid, UPM (Spain); Sanz, Javier [Departamento de Ingenieria Energetica, Universidad Nacional de Educacion a Distancia, UNED (Spain); Juan, Jesus [Laboratorio de Estadistica, Universidad Politecnica de Madrid, UPM (Spain); Kuijper, Jim C. [NRG - Fuels, Actinides and Isotopes Group, Petten (Netherlands)

    2008-04-15

    Two methodologies to propagate the uncertainties on the nuclide inventory in combined Monte Carlo-spectrum and burn-up calculations are presented, based on sensitivity/uncertainty and random sampling techniques (uncertainty Monte Carlo method). Both enable the assessment of the impact of uncertainties in the nuclear data as well as uncertainties due to the statistical nature of the Monte Carlo neutron transport calculation. The methodologies are implemented in our MCNP-ACAB system, which combines the neutron transport code MCNP-4C and the inventory code ACAB. A high burn-up benchmark problem is used to test the MCNP-ACAB performance in inventory predictions, with no uncertainties. A good agreement is found with the results of other participants. This benchmark problem is also used to assess the impact of nuclear data uncertainties and statistical flux errors in high burn-up applications. A detailed calculation is performed to evaluate the effect of cross-section uncertainties in the inventory prediction, taking into account the temporal evolution of the neutron flux level and spectrum. Very large uncertainties are found at the unusually high burn-up of this exercise (800 MWd/kgHM). To compare the impact of the statistical errors in the calculated flux with respect to the cross uncertainties, a simplified problem is considered, taking a constant neutron flux level and spectrum. It is shown that, provided that the flux statistical deviations in the Monte Carlo transport calculation do not exceed a given value, the effect of the flux errors in the calculated isotopic inventory are negligible (even at very high burn-up) compared to the effect of the large cross-section uncertainties available at present in the data files.

  11. Uncertainty assessment in geodetic network adjustment by combining GUM and Monte-Carlo-simulations

    Science.gov (United States)

    Niemeier, Wolfgang; Tengen, Dieter

    2017-06-01

    In this article first ideas are presented to extend the classical concept of geodetic network adjustment by introducing a new method for uncertainty assessment as two-step analysis. In the first step the raw data and possible influencing factors are analyzed using uncertainty modeling according to GUM (Guidelines to the Expression of Uncertainty in Measurements). This approach is well established in metrology, but rarely adapted within Geodesy. The second step consists of Monte-Carlo-Simulations (MC-simulations) for the complete processing chain from raw input data and pre-processing to adjustment computations and quality assessment. To perform these simulations, possible realizations of raw data and the influencing factors are generated, using probability distributions for all variables and the established concept of pseudo-random number generators. Final result is a point cloud which represents the uncertainty of the estimated coordinates; a confidence region can be assigned to these point clouds, as well. This concept may replace the common concept of variance propagation and the quality assessment of adjustment parameters by using their covariance matrix. It allows a new way for uncertainty assessment in accordance with the GUM concept for uncertainty modelling and propagation. As practical example the local tie network in "Metsähovi Fundamental Station", Finland is used, where classical geodetic observations are combined with GNSS data.

  12. Monte Carlo approaches for uncertainty quantification of criticality for system dimensions

    International Nuclear Information System (INIS)

    Kiedrowski, B.C.; Brown, F.B.

    2013-01-01

    One of the current challenges in nuclear engineering computations is the issue of performing uncertainty analysis for either calculations or experimental measurements. This paper specifically focuses on the issue of estimating the uncertainties arising from geometric tolerances. For this paper, two techniques for uncertainty quantification are studied. The first is the forward propagation technique, which can be thought of as a 'brute force' approach; uncertain system parameters are randomly sampled, the calculation is run, and uncertainties are found from the empirically obtained distribution of results. This approach need make no approximations in principle, but is very computationally expensive. The other approach investigated is the adjoint-based approach; system sensitivities are computed via a single Monte Carlo calculation and those are used with a covariance matrix to provide a linear estimate of the uncertainty. Demonstration calculations are performed with the MCNP6 code for both techniques. The 2 techniques are tested on 2 cases: the first case is a solid, bare cylinder of Pu-metal while the second case is a can of plutonium nitrate solution. The results show that the forward and adjoint approaches appear to agree in some cases where the responses are not non-linearly correlated. In other cases, the uncertainties in the effective multiplication k disagree for reasons not yet known

  13. Comparative Criticality Analysis of Two Monte Carlo Codes on Centrifugal Atomizer: MCNPS and SCALE

    International Nuclear Information System (INIS)

    Kang, H-S; Jang, M-S; Kim, S-R; Park, J-M; Kim, K-N

    2015-01-01

    There are two well-known Monte Carlo codes for criticality analysis, MCNP5 and SCALE. MCNP5 is a general-purpose Monte Carlo N-Particle code that can be used for neutron, photon, electron or coupled neutron / photon / electron transport, including the capability to calculate eigenvalues for critical system as a main analysis code. SCALE provides a comprehensive, verified and validated, user-friendly tool set for criticality safety, reactor physics, radiation shielding, radioactive source term characterization, and sensitivity and uncertainty analysis. SCALE was conceived and funded by US NRC to perform standardized computer analysis for licensing evaluation and is used widely in the world. We performed a validation test of MCNP5 and a comparative analysis of Monte Carlo codes, MCNP5 and SCALE, in terms of the critical analysis of centrifugal atomizer. In the criticality analysis using MCNP5 code, we obtained the statistically reliable results by using a large number of source histories per cycle and performing of uncertainty analysis

  14. Comparative Criticality Analysis of Two Monte Carlo Codes on Centrifugal Atomizer: MCNPS and SCALE

    Energy Technology Data Exchange (ETDEWEB)

    Kang, H-S; Jang, M-S; Kim, S-R [NESS, Daejeon (Korea, Republic of); Park, J-M; Kim, K-N [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2015-10-15

    There are two well-known Monte Carlo codes for criticality analysis, MCNP5 and SCALE. MCNP5 is a general-purpose Monte Carlo N-Particle code that can be used for neutron, photon, electron or coupled neutron / photon / electron transport, including the capability to calculate eigenvalues for critical system as a main analysis code. SCALE provides a comprehensive, verified and validated, user-friendly tool set for criticality safety, reactor physics, radiation shielding, radioactive source term characterization, and sensitivity and uncertainty analysis. SCALE was conceived and funded by US NRC to perform standardized computer analysis for licensing evaluation and is used widely in the world. We performed a validation test of MCNP5 and a comparative analysis of Monte Carlo codes, MCNP5 and SCALE, in terms of the critical analysis of centrifugal atomizer. In the criticality analysis using MCNP5 code, we obtained the statistically reliable results by using a large number of source histories per cycle and performing of uncertainty analysis.

  15. Stratified source-sampling techniques for Monte Carlo eigenvalue analysis

    International Nuclear Information System (INIS)

    Mohamed, A.

    1998-01-01

    In 1995, at a conference on criticality safety, a special session was devoted to the Monte Carlo ''Eigenvalue of the World'' problem. Argonne presented a paper, at that session, in which the anomalies originally observed in that problem were reproduced in a much simplified model-problem configuration, and removed by a version of stratified source-sampling. In this paper, stratified source-sampling techniques are generalized and applied to three different Eigenvalue of the World configurations which take into account real-world statistical noise sources not included in the model problem, but which differ in the amount of neutronic coupling among the constituents of each configuration. It is concluded that, in Monte Carlo eigenvalue analysis of loosely-coupled arrays, the use of stratified source-sampling reduces the probability of encountering an anomalous result over that if conventional source-sampling methods are used. However, this gain in reliability is substantially less than that observed in the model-problem results

  16. Parameter uncertainty and model predictions: a review of Monte Carlo results

    International Nuclear Information System (INIS)

    Gardner, R.H.; O'Neill, R.V.

    1979-01-01

    Studies of parameter variability by Monte Carlo analysis are reviewed using repeated simulations of the model with randomly selected parameter values. At the beginning of each simulation, parameter values are chosen from specific frequency distributions. This process is continued for a number of iterations sufficient to converge on an estimate of the frequency distribution of the output variables. The purpose was to explore the general properties of error propagaton in models. Testing the implicit assumptions of analytical methods and pointing out counter-intuitive results produced by the Monte Carlo approach are additional points covered

  17. Crop canopy BRDF simulation and analysis using Monte Carlo method

    NARCIS (Netherlands)

    Huang, J.; Wu, B.; Tian, Y.; Zeng, Y.

    2006-01-01

    This author designs the random process between photons and crop canopy. A Monte Carlo model has been developed to simulate the Bi-directional Reflectance Distribution Function (BRDF) of crop canopy. Comparing Monte Carlo model to MCRM model, this paper analyzes the variations of different LAD and

  18. A Monte-Carlo game theoretic approach for Multi-Criteria Decision Making under uncertainty

    Science.gov (United States)

    Madani, Kaveh; Lund, Jay R.

    2011-05-01

    Game theory provides a useful framework for studying Multi-Criteria Decision Making problems. This paper suggests modeling Multi-Criteria Decision Making problems as strategic games and solving them using non-cooperative game theory concepts. The suggested method can be used to prescribe non-dominated solutions and also can be used as a method to predict the outcome of a decision making problem. Non-cooperative stability definitions for solving the games allow consideration of non-cooperative behaviors, often neglected by other methods which assume perfect cooperation among decision makers. To deal with the uncertainty in input variables a Monte-Carlo Game Theory (MCGT) approach is suggested which maps the stochastic problem into many deterministic strategic games. The games are solved using non-cooperative stability definitions and the results include possible effects of uncertainty in input variables on outcomes. The method can handle multi-criteria multi-decision-maker problems with uncertainty. The suggested method does not require criteria weighting, developing a compound decision objective, and accurate quantitative (cardinal) information as it simplifies the decision analysis by solving problems based on qualitative (ordinal) information, reducing the computational burden substantially. The MCGT method is applied to analyze California's Sacramento-San Joaquin Delta problem. The suggested method provides insights, identifies non-dominated alternatives, and predicts likely decision outcomes.

  19. Monte Carlo Uncertainty Quantification Using Quasi-1D SRM Ballistic Model

    Directory of Open Access Journals (Sweden)

    Davide Viganò

    2016-01-01

    Full Text Available Compactness, reliability, readiness, and construction simplicity of solid rocket motors make them very appealing for commercial launcher missions and embarked systems. Solid propulsion grants high thrust-to-weight ratio, high volumetric specific impulse, and a Technology Readiness Level of 9. However, solid rocket systems are missing any throttling capability at run-time, since pressure-time evolution is defined at the design phase. This lack of mission flexibility makes their missions sensitive to deviations of performance from nominal behavior. For this reason, the reliability of predictions and reproducibility of performances represent a primary goal in this field. This paper presents an analysis of SRM performance uncertainties throughout the implementation of a quasi-1D numerical model of motor internal ballistics based on Shapiro’s equations. The code is coupled with a Monte Carlo algorithm to evaluate statistics and propagation of some peculiar uncertainties from design data to rocker performance parameters. The model has been set for the reproduction of a small-scale rocket motor, discussing a set of parametric investigations on uncertainty propagation across the ballistic model.

  20. Monte Carlo based diffusion coefficients for LMFBR analysis

    International Nuclear Information System (INIS)

    Van Rooijen, Willem F.G.; Takeda, Toshikazu; Hazama, Taira

    2010-01-01

    A method based on Monte Carlo calculations is developed to estimate the diffusion coefficient of unit cells. The method uses a geometrical model similar to that used in lattice theory, but does not use the assumption of a separable fundamental mode used in lattice theory. The method uses standard Monte Carlo flux and current tallies, and the continuous energy Monte Carlo code MVP was used without modifications. Four models are presented to derive the diffusion coefficient from tally results of flux and partial currents. In this paper the method is applied to the calculation of a plate cell of the fast-spectrum critical facility ZEBRA. Conventional calculations of the diffusion coefficient diverge in the presence of planar voids in the lattice, but our Monte Carlo method can treat this situation without any problem. The Monte Carlo method was used to investigate the influence of geometrical modeling as well as the directional dependence of the diffusion coefficient. The method can be used to estimate the diffusion coefficient of complicated unit cells, the limitation being the capabilities of the Monte Carlo code. The method will be used in the future to confirm results for the diffusion coefficient obtained of the Monte Carlo code. The method will be used in the future to confirm results for the diffusion coefficient obtained with deterministic codes. (author)

  1. Multilevel and quasi-Monte Carlo methods for uncertainty quantification in particle travel times through random heterogeneous porous media

    Science.gov (United States)

    Crevillén-García, D.; Power, H.

    2017-08-01

    In this study, we apply four Monte Carlo simulation methods, namely, Monte Carlo, quasi-Monte Carlo, multilevel Monte Carlo and multilevel quasi-Monte Carlo to the problem of uncertainty quantification in the estimation of the average travel time during the transport of particles through random heterogeneous porous media. We apply the four methodologies to a model problem where the only input parameter, the hydraulic conductivity, is modelled as a log-Gaussian random field by using direct Karhunen-Loéve decompositions. The random terms in such expansions represent the coefficients in the equations. Numerical calculations demonstrating the effectiveness of each of the methods are presented. A comparison of the computational cost incurred by each of the methods for three different tolerances is provided. The accuracy of the approaches is quantified via the mean square error.

  2. Multilevel and quasi-Monte Carlo methods for uncertainty quantification in particle travel times through random heterogeneous porous media.

    Science.gov (United States)

    Crevillén-García, D; Power, H

    2017-08-01

    In this study, we apply four Monte Carlo simulation methods, namely, Monte Carlo, quasi-Monte Carlo, multilevel Monte Carlo and multilevel quasi-Monte Carlo to the problem of uncertainty quantification in the estimation of the average travel time during the transport of particles through random heterogeneous porous media. We apply the four methodologies to a model problem where the only input parameter, the hydraulic conductivity, is modelled as a log-Gaussian random field by using direct Karhunen-Loéve decompositions. The random terms in such expansions represent the coefficients in the equations. Numerical calculations demonstrating the effectiveness of each of the methods are presented. A comparison of the computational cost incurred by each of the methods for three different tolerances is provided. The accuracy of the approaches is quantified via the mean square error.

  3. Implementation and analysis of an adaptive multilevel Monte Carlo algorithm

    KAUST Repository

    Hoel, Hakon; Von Schwerin, Erik; Szepessy, Anders; Tempone, Raul

    2014-01-01

    We present an adaptive multilevel Monte Carlo (MLMC) method for weak approximations of solutions to Itô stochastic dierential equations (SDE). The work [11] proposed and analyzed an MLMC method based on a hierarchy of uniform time discretizations and control variates to reduce the computational effort required by a single level Euler-Maruyama Monte Carlo method from O(TOL-3) to O(TOL-2 log(TOL-1)2) for a mean square error of O(TOL2). Later, the work [17] presented an MLMC method using a hierarchy of adaptively re ned, non-uniform time discretizations, and, as such, it may be considered a generalization of the uniform time discretizationMLMC method. This work improves the adaptiveMLMC algorithms presented in [17] and it also provides mathematical analysis of the improved algorithms. In particular, we show that under some assumptions our adaptive MLMC algorithms are asymptotically accurate and essentially have the correct complexity but with improved control of the complexity constant factor in the asymptotic analysis. Numerical tests include one case with singular drift and one with stopped diusion, where the complexity of a uniform single level method is O(TOL-4). For both these cases the results con rm the theory, exhibiting savings in the computational cost for achieving the accuracy O(TOL) from O(TOL-3) for the adaptive single level algorithm to essentially O(TOL-2 log(TOL-1)2) for the adaptive MLMC algorithm. © 2014 by Walter de Gruyter Berlin/Boston 2014.

  4. Bayesian Monte Carlo and Maximum Likelihood Approach for Uncertainty Estimation and Risk Management: Application to Lake Oxygen Recovery Model

    Science.gov (United States)

    Model uncertainty estimation and risk assessment is essential to environmental management and informed decision making on pollution mitigation strategies. In this study, we apply a probabilistic methodology, which combines Bayesian Monte Carlo simulation and Maximum Likelihood e...

  5. Validation of uncertainty of weighing in the preparation of radionuclide standards by Monte Carlo Method

    International Nuclear Information System (INIS)

    Cacais, F.L.; Delgado, J.U.; Loayza, V.M.

    2016-01-01

    In preparing solutions for the production of radionuclide metrology standards is necessary measuring the quantity Activity by mass. The gravimetric method by elimination is applied to perform weighing with smaller uncertainties. At this work is carried out the validation, by the Monte Carlo method, of the uncertainty calculation approach implemented by Lourenco and Bobin according to ISO GUM for the method by elimination. The results obtained by both uncertainty calculation methods were consistent indicating that were fulfilled the conditions for the application of ISO GUM in the preparation of radioactive standards. (author)

  6. Uncertainty versus variability in Monte Carlo simulations of human exposure through food pathways

    International Nuclear Information System (INIS)

    McKone, T.E.

    1994-01-01

    An important issue in both the risk characterization and subsequent risk management of contaminated soil is how precisely we can characterize the distribution among individuals of potential doses associated with chemical contaminants in soil and whether this level of precision favors the use of population distributions of exposure over the use of single scenario representations. For lipophilic contaminants, such as dioxins, furans, polychlorinated biphenyls, pesticides, and for metals such as lead and mercury, exposures through food have been demonstrated to be dominant contributors to total dose within non-occupationally exposed populations. However, overall uncertainties in estimating potential doses through food chains are much larger than uncertainties associated with other exposure pathways. A general model is described here for estimating the ratio of potential dose to contaminant concentration in soil for homegrown foods contaminated by lipophilic, nonionic organic chemicals. This model includes parameters describing homegrown food consumption rates, exposure duration, biotransfer factors, and partition factors. For the parameters needed in this model, the mean and variance are often the only moments of the parameter distribution available. Parameters are divided into three categories, uncertain parameters, variable parameters, and mixed uncertain/variable parameters. Using soils contaminated by hexachlorbenzene (HCB) and benzo(a)pyrene (BaP) as cases studies, a stepwise Monte Carlo analysis is used to develop a histogram that apportions variance in the outcome (ratio of potential dose by food pathways to soil concentration) to variance in each of the three input categories. The results represent potential doses in households consuming homegrown foods

  7. The Monte Carlo Simulation Method for System Reliability and Risk Analysis

    CERN Document Server

    Zio, Enrico

    2013-01-01

    Monte Carlo simulation is one of the best tools for performing realistic analysis of complex systems as it allows most of the limiting assumptions on system behavior to be relaxed. The Monte Carlo Simulation Method for System Reliability and Risk Analysis comprehensively illustrates the Monte Carlo simulation method and its application to reliability and system engineering. Readers are given a sound understanding of the fundamentals of Monte Carlo sampling and simulation and its application for realistic system modeling.   Whilst many of the topics rely on a high-level understanding of calculus, probability and statistics, simple academic examples will be provided in support to the explanation of the theoretical foundations to facilitate comprehension of the subject matter. Case studies will be introduced to provide the practical value of the most advanced techniques.   This detailed approach makes The Monte Carlo Simulation Method for System Reliability and Risk Analysis a key reference for senior undergra...

  8. Monte Carlo Calculation of Thermal Neutron Inelastic Scattering Cross Section Uncertainties by Sampling Perturbed Phonon Spectra

    Science.gov (United States)

    Holmes, Jesse Curtis

    established that depends on uncertainties in the physics models and methodology employed to produce the DOS. Through Monte Carlo sampling of perturbations from the reference phonon spectrum, an S(alpha, beta) covariance matrix may be generated. In this work, density functional theory and lattice dynamics in the harmonic approximation are used to calculate the phonon DOS for hexagonal crystalline graphite. This form of graphite is used as an example material for the purpose of demonstrating procedures for analyzing, calculating and processing thermal neutron inelastic scattering uncertainty information. Several sources of uncertainty in thermal neutron inelastic scattering calculations are examined, including sources which cannot be directly characterized through a description of the phonon DOS uncertainty, and their impacts are evaluated. Covariances for hexagonal crystalline graphite S(alpha, beta) data are quantified by coupling the standard methodology of LEAPR with a Monte Carlo sampling process. The mechanics of efficiently representing and processing this covariance information is also examined. Finally, with appropriate sensitivity information, it is shown that an S(alpha, beta) covariance matrix can be propagated to generate covariance data for integrated cross sections, secondary energy distributions, and coupled energy-angle distributions. This approach enables a complete description of thermal neutron inelastic scattering cross section uncertainties which may be employed to improve the simulation of nuclear systems.

  9. An Application of Monte-Carlo-Based Sensitivity Analysis on the Overlap in Discriminant Analysis

    Directory of Open Access Journals (Sweden)

    S. Razmyan

    2012-01-01

    Full Text Available Discriminant analysis (DA is used for the measurement of estimates of a discriminant function by minimizing their group misclassifications to predict group membership of newly sampled data. A major source of misclassification in DA is due to the overlapping of groups. The uncertainty in the input variables and model parameters needs to be properly characterized in decision making. This study combines DEA-DA with a sensitivity analysis approach to an assessment of the influence of banks’ variables on the overall variance in overlap in a DA in order to determine which variables are most significant. A Monte-Carlo-based sensitivity analysis is considered for computing the set of first-order sensitivity indices of the variables to estimate the contribution of each uncertain variable. The results show that the uncertainties in the loans granted and different deposit variables are more significant than uncertainties in other banks’ variables in decision making.

  10. Coupling of system thermal–hydraulics and Monte-Carlo code: Convergence criteria and quantification of correlation between statistical uncertainty and coupled error

    International Nuclear Information System (INIS)

    Wu, Xu; Kozlowski, Tomasz

    2015-01-01

    Highlights: • Coupling of Monte Carlo code Serpent and thermal–hydraulics code RELAP5. • A convergence criterion is developed based on the statistical uncertainty of power. • Correlation between MC statistical uncertainty and coupled error is quantified. • Both UO 2 and MOX single assembly models are used in the coupled simulation. • Validation of coupling results with a multi-group transport code DeCART. - Abstract: Coupled multi-physics approach plays an important role in improving computational accuracy. Compared with deterministic neutronics codes, Monte Carlo codes have the advantage of a higher resolution level. In the present paper, a three-dimensional continuous-energy Monte Carlo reactor physics burnup calculation code, Serpent, is coupled with a thermal–hydraulics safety analysis code, RELAP5. The coupled Serpent/RELAP5 code capability is demonstrated by the improved axial power distribution of UO 2 and MOX single assembly models, based on the OECD-NEA/NRC PWR MOX/UO 2 Core Transient Benchmark. Comparisons of calculation results using the coupled code with those from the deterministic methods, specifically heterogeneous multi-group transport code DeCART, show that the coupling produces more precise results. A new convergence criterion for the coupled simulation is developed based on the statistical uncertainty in power distribution in the Monte Carlo code, rather than ad-hoc criteria used in previous research. The new convergence criterion is shown to be more rigorous, equally convenient to use but requiring a few more coupling steps to converge. Finally, the influence of Monte Carlo statistical uncertainty on the coupled error of power and thermal–hydraulics parameters is quantified. The results are presented such that they can be used to find the statistical uncertainty to use in Monte Carlo in order to achieve a desired precision in coupled simulation

  11. Sampling-based nuclear data uncertainty quantification for continuous energy Monte-Carlo codes

    International Nuclear Information System (INIS)

    Zhu, T.

    2015-01-01

    Research on the uncertainty of nuclear data is motivated by practical necessity. Nuclear data uncertainties can propagate through nuclear system simulations into operation and safety related parameters. The tolerance for uncertainties in nuclear reactor design and operation can affect the economic efficiency of nuclear power, and essentially its sustainability. The goal of the present PhD research is to establish a methodology of nuclear data uncertainty quantification (NDUQ) for MCNPX, the continuous-energy Monte-Carlo (M-C) code. The high fidelity (continuous-energy treatment and flexible geometry modelling) of MCNPX makes it the choice of routine criticality safety calculations at PSI/LRS, but also raises challenges for NDUQ by conventional sensitivity/uncertainty (S/U) methods. For example, only recently in 2011, the capability of calculating continuous energy κ_e_f_f sensitivity to nuclear data was demonstrated in certain M-C codes by using the method of iterated fission probability. The methodology developed during this PhD research is fundamentally different from the conventional S/U approach: nuclear data are treated as random variables and sampled in accordance to presumed probability distributions. When sampled nuclear data are used in repeated model calculations, the output variance is attributed to the collective uncertainties of nuclear data. The NUSS (Nuclear data Uncertainty Stochastic Sampling) tool is based on this sampling approach and implemented to work with MCNPX’s ACE format of nuclear data, which also gives NUSS compatibility with MCNP and SERPENT M-C codes. In contrast, multigroup uncertainties are used for the sampling of ACE-formatted pointwise-energy nuclear data in a groupwise manner due to the more limited quantity and quality of nuclear data uncertainties. Conveniently, the usage of multigroup nuclear data uncertainties allows consistent comparison between NUSS and other methods (both S/U and sampling-based) that employ the same

  12. Sampling-based nuclear data uncertainty quantification for continuous energy Monte-Carlo codes

    Energy Technology Data Exchange (ETDEWEB)

    Zhu, T.

    2015-07-01

    Research on the uncertainty of nuclear data is motivated by practical necessity. Nuclear data uncertainties can propagate through nuclear system simulations into operation and safety related parameters. The tolerance for uncertainties in nuclear reactor design and operation can affect the economic efficiency of nuclear power, and essentially its sustainability. The goal of the present PhD research is to establish a methodology of nuclear data uncertainty quantification (NDUQ) for MCNPX, the continuous-energy Monte-Carlo (M-C) code. The high fidelity (continuous-energy treatment and flexible geometry modelling) of MCNPX makes it the choice of routine criticality safety calculations at PSI/LRS, but also raises challenges for NDUQ by conventional sensitivity/uncertainty (S/U) methods. For example, only recently in 2011, the capability of calculating continuous energy κ{sub eff} sensitivity to nuclear data was demonstrated in certain M-C codes by using the method of iterated fission probability. The methodology developed during this PhD research is fundamentally different from the conventional S/U approach: nuclear data are treated as random variables and sampled in accordance to presumed probability distributions. When sampled nuclear data are used in repeated model calculations, the output variance is attributed to the collective uncertainties of nuclear data. The NUSS (Nuclear data Uncertainty Stochastic Sampling) tool is based on this sampling approach and implemented to work with MCNPX’s ACE format of nuclear data, which also gives NUSS compatibility with MCNP and SERPENT M-C codes. In contrast, multigroup uncertainties are used for the sampling of ACE-formatted pointwise-energy nuclear data in a groupwise manner due to the more limited quantity and quality of nuclear data uncertainties. Conveniently, the usage of multigroup nuclear data uncertainties allows consistent comparison between NUSS and other methods (both S/U and sampling-based) that employ the same

  13. LISA data analysis using Markov chain Monte Carlo methods

    International Nuclear Information System (INIS)

    Cornish, Neil J.; Crowder, Jeff

    2005-01-01

    The Laser Interferometer Space Antenna (LISA) is expected to simultaneously detect many thousands of low-frequency gravitational wave signals. This presents a data analysis challenge that is very different to the one encountered in ground based gravitational wave astronomy. LISA data analysis requires the identification of individual signals from a data stream containing an unknown number of overlapping signals. Because of the signal overlaps, a global fit to all the signals has to be performed in order to avoid biasing the solution. However, performing such a global fit requires the exploration of an enormous parameter space with a dimension upwards of 50 000. Markov Chain Monte Carlo (MCMC) methods offer a very promising solution to the LISA data analysis problem. MCMC algorithms are able to efficiently explore large parameter spaces, simultaneously providing parameter estimates, error analysis, and even model selection. Here we present the first application of MCMC methods to simulated LISA data and demonstrate the great potential of the MCMC approach. Our implementation uses a generalized F-statistic to evaluate the likelihoods, and simulated annealing to speed convergence of the Markov chains. As a final step we supercool the chains to extract maximum likelihood estimates, and estimates of the Bayes factors for competing models. We find that the MCMC approach is able to correctly identify the number of signals present, extract the source parameters, and return error estimates consistent with Fisher information matrix predictions

  14. Data analytics using canonical correlation analysis and Monte Carlo simulation

    Science.gov (United States)

    Rickman, Jeffrey M.; Wang, Yan; Rollett, Anthony D.; Harmer, Martin P.; Compson, Charles

    2017-07-01

    A canonical correlation analysis is a generic parametric model used in the statistical analysis of data involving interrelated or interdependent input and output variables. It is especially useful in data analytics as a dimensional reduction strategy that simplifies a complex, multidimensional parameter space by identifying a relatively few combinations of variables that are maximally correlated. One shortcoming of the canonical correlation analysis, however, is that it provides only a linear combination of variables that maximizes these correlations. With this in mind, we describe here a versatile, Monte-Carlo based methodology that is useful in identifying non-linear functions of the variables that lead to strong input/output correlations. We demonstrate that our approach leads to a substantial enhancement of correlations, as illustrated by two experimental applications of substantial interest to the materials science community, namely: (1) determining the interdependence of processing and microstructural variables associated with doped polycrystalline aluminas, and (2) relating microstructural decriptors to the electrical and optoelectronic properties of thin-film solar cells based on CuInSe2 absorbers. Finally, we describe how this approach facilitates experimental planning and process control.

  15. Analysis of error in Monte Carlo transport calculations

    International Nuclear Information System (INIS)

    Booth, T.E.

    1979-01-01

    The Monte Carlo method for neutron transport calculations suffers, in part, because of the inherent statistical errors associated with the method. Without an estimate of these errors in advance of the calculation, it is difficult to decide what estimator and biasing scheme to use. Recently, integral equations have been derived that, when solved, predicted errors in Monte Carlo calculations in nonmultiplying media. The present work allows error prediction in nonanalog Monte Carlo calculations of multiplying systems, even when supercritical. Nonanalog techniques such as biased kernels, particle splitting, and Russian Roulette are incorporated. Equations derived here allow prediction of how much a specific variance reduction technique reduces the number of histories required, to be weighed against the change in time required for calculation of each history. 1 figure, 1 table

  16. A Multivariate Time Series Method for Monte Carlo Reactor Analysis

    International Nuclear Information System (INIS)

    Taro Ueki

    2008-01-01

    A robust multivariate time series method has been established for the Monte Carlo calculation of neutron multiplication problems. The method is termed Coarse Mesh Projection Method (CMPM) and can be implemented using the coarse statistical bins for acquisition of nuclear fission source data. A novel aspect of CMPM is the combination of the general technical principle of projection pursuit in the signal processing discipline and the neutron multiplication eigenvalue problem in the nuclear engineering discipline. CMPM enables reactor physicists to accurately evaluate major eigenvalue separations of nuclear reactors with continuous energy Monte Carlo calculation. CMPM was incorporated in the MCNP Monte Carlo particle transport code of Los Alamos National Laboratory. The great advantage of CMPM over the traditional Fission Matrix method is demonstrated for the three space-dimensional modeling of the initial core of a pressurized water reactor

  17. Proton therapy analysis using the Monte Carlo method

    Energy Technology Data Exchange (ETDEWEB)

    Noshad, Houshyar [Center for Theoretical Physics and Mathematics, AEOI, P.O. Box 14155-1339, Tehran (Iran, Islamic Republic of)]. E-mail: hnoshad@aeoi.org.ir; Givechi, Nasim [Islamic Azad University, Science and Research Branch, Tehran (Iran, Islamic Republic of)

    2005-10-01

    The range and straggling data obtained from the transport of ions in matter (TRIM) computer program were used to determine the trajectories of monoenergetic 60 MeV protons in muscle tissue by using the Monte Carlo technique. The appropriate profile for the shape of a proton pencil beam in proton therapy as well as the dose deposited in the tissue were computed. The good agreements between our results as compared with the corresponding experimental values are presented here to show the reliability of our Monte Carlo method.

  18. Fast Monte Carlo for ion beam analysis simulations

    International Nuclear Information System (INIS)

    Schiettekatte, Francois

    2008-01-01

    A Monte Carlo program for the simulation of ion beam analysis data is presented. It combines mainly four features: (i) ion slowdown is computed separately from the main scattering/recoil event, which is directed towards the detector. (ii) A virtual detector, that is, a detector larger than the actual one can be used, followed by trajectory correction. (iii) For each collision during ion slowdown, scattering angle components are extracted form tables. (iv) Tables of scattering angle components, stopping power and energy straggling are indexed using the binary representation of floating point numbers, which allows logarithmic distribution of these tables without the computation of logarithms to access them. Tables are sufficiently fine-grained that interpolation is not necessary. Ion slowdown computation thus avoids trigonometric, inverse and transcendental function calls and, as much as possible, divisions. All these improvements make possible the computation of 10 7 collisions/s on current PCs. Results for transmitted ions of several masses in various substrates are well comparable to those obtained using SRIM-2006 in terms of both angular and energy distributions, as long as a sufficiently large number of collisions is considered for each ion. Examples of simulated spectrum show good agreement with experimental data, although a large detector rather than the virtual detector has to be used to properly simulate background signals that are due to plural collisions. The program, written in standard C, is open-source and distributed under the terms of the GNU General Public License

  19. Application to risk analysis of Monte Carlo method

    International Nuclear Information System (INIS)

    Mihara, Takashi

    2001-01-01

    Phased mission analysis code, PHAMMON by means of monte carlo method is developed for reliability assessment of decay heat removal system in LMFBR. Success criteria and grace periods of the decay heat removal system which has long mission times (∼1 week or ∼1 month) change as a function of time. It is necessary to divide mission time into some phases. In probability safety assessment (PSA) of real systems, it usually happens that the mean time to component failure (MTTF) is considerably long (1000-10 6 hours) and the mean time to component repair (MTTR) is short (∼10 hours). The failure probability of the systems, therefore, is extremely small (10 -6 -10 -9 ). Suitable variance reduction techniques are needed. The PHAMMON code involved two kinds of variance reduction techniques: (1) forced time transitions, and (2) failure biasing. For further reducing the variance of the result from the PHAMMON code execution, a biasing method of the transitions towards the closest cut set incorporating a new distance concept is introduced to the PHAMMON code. Failure probability and it's fractional standard deviation for the decay heat removal system are calculated by the PHAMMON code under the conditions of various success criteria over 168hrs after reactor shutdown. The biasing of the transition towards the closet cut set is an effective means of reducing the variance. (M. Suetake)

  20. Monte Carlo analysis of radiative transport in oceanographic lidar measurements

    Energy Technology Data Exchange (ETDEWEB)

    Cupini, E.; Ferro, G. [ENEA, Divisione Fisica Applicata, Centro Ricerche Ezio Clementel, Bologna (Italy); Ferrari, N. [Bologna Univ., Bologna (Italy). Dipt. Ingegneria Energetica, Nucleare e del Controllo Ambientale

    2001-07-01

    The analysis of oceanographic lidar systems measurements is often carried out with semi-empirical methods, since there is only a rough understanding of the effects of many environmental variables. The development of techniques for interpreting the accuracy of lidar measurements is needed to evaluate the effects of various environmental situations, as well as of different experimental geometric configurations and boundary conditions. A Monte Carlo simulation model represents a tool that is particularly well suited for answering these important questions. The PREMAR-2F Monte Carlo code has been developed taking into account the main molecular and non-molecular components of the marine environment. The laser radiation interaction processes of diffusion, re-emission, refraction and absorption are treated. In particular are considered: the Rayleigh elastic scattering, produced by atoms and molecules with small dimensions with respect to the laser emission wavelength (i.e. water molecules), the Mie elastic scattering, arising from atoms or molecules with dimensions comparable to the laser wavelength (hydrosols), the Raman inelastic scattering, typical of water, the absorption of water, inorganic (sediments) and organic (phytoplankton and CDOM) hydrosols, the fluorescence re-emission of chlorophyll and yellow substances. PREMAR-2F is an extension of a code for the simulation of the radiative transport in atmospheric environments (PREMAR-2). The approach followed in PREMAR-2 was to combine conventional Monte Carlo techniques with analytical estimates of the probability of the receiver to have a contribution from photons coming back after an interaction in the field of view of the lidar fluorosensor collecting apparatus. This offers an effective mean for modelling a lidar system with realistic geometric constraints. The retrieved semianalytic Monte Carlo radiative transfer model has been developed in the frame of the Italian Research Program for Antarctica (PNRA) and it is

  1. Monte Carlo analysis of highly compressed fissile assemblies. Pt. 1

    International Nuclear Information System (INIS)

    Raspet, R.; Baird, G.E.

    1978-01-01

    Laserinduced fission of highly compressed bare fissionable spheres is analyzed using Monte Carlo techniques. The critical mass and critical radius as a function of density are calculated and the fission energy yield is calculated and compared with the input laser energy necessary to achieve compression to criticality. (orig.) [de

  2. Monte Carlo simulation for slip rate sensitivity analysis in Cimandiri fault area

    Energy Technology Data Exchange (ETDEWEB)

    Pratama, Cecep, E-mail: great.pratama@gmail.com [Graduate Program of Earth Science, Faculty of Earth Science and Technology, ITB, JalanGanesa no. 10, Bandung 40132 (Indonesia); Meilano, Irwan [Geodesy Research Division, Faculty of Earth Science and Technology, ITB, JalanGanesa no. 10, Bandung 40132 (Indonesia); Nugraha, Andri Dian [Global Geophysical Group, Faculty of Mining and Petroleum Engineering, ITB, JalanGanesa no. 10, Bandung 40132 (Indonesia)

    2015-04-24

    Slip rate is used to estimate earthquake recurrence relationship which is the most influence for hazard level. We examine slip rate contribution of Peak Ground Acceleration (PGA), in probabilistic seismic hazard maps (10% probability of exceedance in 50 years or 500 years return period). Hazard curve of PGA have been investigated for Sukabumi using a PSHA (Probabilistic Seismic Hazard Analysis). We observe that the most influence in the hazard estimate is crustal fault. Monte Carlo approach has been developed to assess the sensitivity. Then, Monte Carlo simulations properties have been assessed. Uncertainty and coefficient of variation from slip rate for Cimandiri Fault area has been calculated. We observe that seismic hazard estimates is sensitive to fault slip rate with seismic hazard uncertainty result about 0.25 g. For specific site, we found seismic hazard estimate for Sukabumi is between 0.4904 – 0.8465 g with uncertainty between 0.0847 – 0.2389 g and COV between 17.7% – 29.8%.

  3. Monte-Carlo Application for Nondestructive Nuclear Waste Analysis

    Science.gov (United States)

    Carasco, C.; Engels, R.; Frank, M.; Furletov, S.; Furletova, J.; Genreith, C.; Havenith, A.; Kemmerling, G.; Kettler, J.; Krings, T.; Ma, J.-L.; Mauerhofer, E.; Neike, D.; Payan, E.; Perot, B.; Rossbach, M.; Schitthelm, O.; Schumann, M.; Vasquez, R.

    2014-06-01

    Radioactive waste has to undergo a process of quality checking in order to check its conformance with national regulations prior to its transport, intermediate storage and final disposal. Within the quality checking of radioactive waste packages non-destructive assays are required to characterize their radio-toxic and chemo-toxic contents. The Institute of Energy and Climate Research - Nuclear Waste Management and Reactor Safety of the Forschungszentrum Jülich develops in the framework of cooperation nondestructive analytical techniques for the routine characterization of radioactive waste packages at industrial-scale. During the phase of research and development Monte Carlo techniques are used to simulate the transport of particle, especially photons, electrons and neutrons, through matter and to obtain the response of detection systems. The radiological characterization of low and intermediate level radioactive waste drums is performed by segmented γ-scanning (SGS). To precisely and accurately reconstruct the isotope specific activity content in waste drums by SGS measurement, an innovative method called SGSreco was developed. The Geant4 code was used to simulate the response of the collimated detection system for waste drums with different activity and matrix configurations. These simulations allow a far more detailed optimization, validation and benchmark of SGSreco, since the construction of test drums covering a broad range of activity and matrix properties is time consuming and cost intensive. The MEDINA (Multi Element Detection based on Instrumental Neutron Activation) test facility was developed to identify and quantify non-radioactive elements and substances in radioactive waste drums. MEDINA is based on prompt and delayed gamma neutron activation analysis (P&DGNAA) using a 14 MeV neutron generator. MCNP simulations were carried out to study the response of the MEDINA facility in terms of gamma spectra, time dependence of the neutron energy spectrum

  4. Markov Chain Monte Carlo Methods for Bayesian Data Analysis in Astronomy

    Science.gov (United States)

    Sharma, Sanjib

    2017-08-01

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

  5. Hydrogen analysis depth calibration by CORTEO Monte-Carlo simulation

    Energy Technology Data Exchange (ETDEWEB)

    Moser, M., E-mail: marcus.moser@unibw.de [Universität der Bundeswehr München, Institut für Angewandte Physik und Messtechnik LRT2, Fakultät für Luft- und Raumfahrttechnik, 85577 Neubiberg (Germany); Reichart, P.; Bergmaier, A.; Greubel, C. [Universität der Bundeswehr München, Institut für Angewandte Physik und Messtechnik LRT2, Fakultät für Luft- und Raumfahrttechnik, 85577 Neubiberg (Germany); Schiettekatte, F. [Université de Montréal, Département de Physique, Montréal, QC H3C 3J7 (Canada); Dollinger, G., E-mail: guenther.dollinger@unibw.de [Universität der Bundeswehr München, Institut für Angewandte Physik und Messtechnik LRT2, Fakultät für Luft- und Raumfahrttechnik, 85577 Neubiberg (Germany)

    2016-03-15

    Hydrogen imaging with sub-μm lateral resolution and sub-ppm sensitivity has become possible with coincident proton–proton (pp) scattering analysis (Reichart et al., 2004). Depth information is evaluated from the energy sum signal with respect to energy loss of both protons on their path through the sample. In first order, there is no angular dependence due to elastic scattering. In second order, a path length effect due to different energy loss on the paths of the protons causes an angular dependence of the energy sum. Therefore, the energy sum signal has to be de-convoluted depending on the matrix composition, i.e. mainly the atomic number Z, in order to get a depth calibrated hydrogen profile. Although the path effect can be calculated analytically in first order, multiple scattering effects lead to significant deviations in the depth profile. Hence, in our new approach, we use the CORTEO Monte-Carlo code (Schiettekatte, 2008) in order to calculate the depth of a coincidence event depending on the scattering angle. The code takes individual detector geometry into account. In this paper we show, that the code correctly reproduces measured pp-scattering energy spectra with roughness effects considered. With more than 100 μm thick Mylar-sandwich targets (Si, Fe, Ge) we demonstrate the deconvolution of the energy spectra on our current multistrip detector at the microprobe SNAKE at the Munich tandem accelerator lab. As a result, hydrogen profiles can be evaluated with an accuracy in depth of about 1% of the sample thickness.

  6. Uncertainty assessment of integrated distributed hydrological models using GLUE with Markov chain Monte Carlo sampling

    DEFF Research Database (Denmark)

    Blasone, Roberta-Serena; Madsen, Henrik; Rosbjerg, Dan

    2008-01-01

    uncertainty estimation (GLUE) procedure based on Markov chain Monte Carlo sampling is applied in order to improve the performance of the methodology in estimating parameters and posterior output distributions. The description of the spatial variations of the hydrological processes is accounted for by defining......In recent years, there has been an increase in the application of distributed, physically-based and integrated hydrological models. Many questions regarding how to properly calibrate and validate distributed models and assess the uncertainty of the estimated parameters and the spatially......-site validation must complement the usual time validation. In this study, we develop, through an application, a comprehensive framework for multi-criteria calibration and uncertainty assessment of distributed physically-based, integrated hydrological models. A revised version of the generalized likelihood...

  7. POWER ANALYSIS FOR COMPLEX MEDIATIONAL DESIGNS USING MONTE CARLO METHODS

    OpenAIRE

    Thoemmes, Felix; MacKinnon, David P.; Reiser, Mark R.

    2010-01-01

    Applied researchers often include mediation effects in applications of advanced methods such as latent variable models and linear growth curve models. Guidance on how to estimate statistical power to detect mediation for these models has not yet been addressed in the literature. We describe a general framework for power analyses for complex mediational models. The approach is based on the well known technique of generating a large number of samples in a Monte Carlo study, and estimating power...

  8. A Monte Carlo error simulation applied to calibration-free X-ray diffraction phase analysis

    International Nuclear Information System (INIS)

    Braun, G.E.

    1986-01-01

    Quantitative phase analysis of a system of n phases can be effected without the need for calibration standards provided at least n different mixtures of these phases are available. A series of linear equations relating diffracted X-ray intensities, weight fractions and quantitation factors coupled with mass balance relationships can be solved for the unknown weight fractions and factors. Uncertainties associated with the measured X-ray intensities, owing to counting of random X-ray quanta, are used to estimate the errors in the calculated parameters utilizing a Monte Carlo simulation. The Monte Carlo approach can be generalized and applied to any quantitative X-ray diffraction phase analysis method. Two examples utilizing mixtures of CaCO 3 , Fe 2 O 3 and CaF 2 with an α-SiO 2 (quartz) internal standard illustrate the quantitative method and corresponding error analysis. One example is well conditioned; the other is poorly conditioned and, therefore, very sensitive to errors in the measured intensities. (orig.)

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

    Science.gov (United States)

    Karakoylu, E.; Franz, B.

    2016-01-01

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

  10. Measurement uncertainty of dissolution test of acetaminophen immediate release tablets using Monte Carlo simulations

    Directory of Open Access Journals (Sweden)

    Daniel Cancelli Romero

    2017-10-01

    Full Text Available ABSTRACT Analytical results are widely used to assess batch-by-batch conformity, pharmaceutical equivalence, as well as in the development of drug products. Despite this, few papers describing the measurement uncertainty estimation associated with these results were found in the literature. Here, we described a simple procedure used for estimating measurement uncertainty associated with the dissolution test of acetaminophen tablets. A fractionate factorial design was used to define a mathematical model that explains the amount of acetaminophen dissolved (% as a function of time of dissolution (from 20 to 40 minutes, volume of dissolution media (from 800 to 1000 mL, pH of dissolution media (from 2.0 to 6.8, and rotation speed (from 40 to 60 rpm. Using Monte Carlo simulations, we estimated measurement uncertainty for dissolution test of acetaminophen tablets (95.2 ± 1.0%, with a 95% confidence level. Rotation speed was the most important source of uncertainty, contributing about 96.2% of overall uncertainty. Finally, it is important to note that the uncertainty calculated in this paper reflects the expected uncertainty to the dissolution test, and does not consider variations in the content of acetaminophen.

  11. Uncertainties in s-process nucleosynthesis in massive stars determined by Monte Carlo variations

    Science.gov (United States)

    Nishimura, N.; Hirschi, R.; Rauscher, T.; St. J. Murphy, A.; Cescutti, G.

    2017-08-01

    The s-process in massive stars produces the weak component of the s-process (nuclei up to A ˜ 90), in amounts that match solar abundances. For heavier isotopes, such as barium, production through neutron capture is significantly enhanced in very metal-poor stars with fast rotation. However, detailed theoretical predictions for the resulting final s-process abundances have important uncertainties caused both by the underlying uncertainties in the nuclear physics (principally neutron-capture reaction and β-decay rates) as well as by the stellar evolution modelling. In this work, we investigated the impact of nuclear-physics uncertainties relevant to the s-process in massive stars. Using a Monte Carlo based approach, we performed extensive nuclear reaction network calculations that include newly evaluated upper and lower limits for the individual temperature-dependent reaction rates. We found that most of the uncertainty in the final abundances is caused by uncertainties in the neutron-capture rates, while β-decay rate uncertainties affect only a few nuclei near s-process branchings. The s-process in rotating metal-poor stars shows quantitatively different uncertainties and key reactions, although the qualitative characteristics are similar. We confirmed that our results do not significantly change at different metallicities for fast rotating massive stars in the very low metallicity regime. We highlight which of the identified key reactions are realistic candidates for improved measurement by future experiments.

  12. Active neutron multiplicity analysis and Monte Carlo calculations

    International Nuclear Information System (INIS)

    Krick, M.S.; Ensslin, N.; Langner, D.G.; Miller, M.C.; Siebelist, R.; Stewart, J.E.; Ceo, R.N.; May, P.K.; Collins, L.L. Jr

    1994-01-01

    Active neutron multiplicity measurements of high-enrichment uranium metal and oxide samples have been made at Los Alamos and Y-12. The data from the measurements of standards at Los Alamos were analyzed to obtain values for neutron multiplication and source-sample coupling. These results are compared to equivalent results obtained from Monte Carlo calculations. An approximate relationship between coupling and multiplication is derived and used to correct doubles rates for multiplication and coupling. The utility of singles counting for uranium samples is also examined

  13. An Advanced Neutronic Analysis Toolkit with Inline Monte Carlo capability for BHTR Analysis

    Energy Technology Data Exchange (ETDEWEB)

    William R. Martin; John C. Lee

    2009-12-30

    Monte Carlo capability has been combined with a production LWR lattice physics code to allow analysis of high temperature gas reactor configurations, accounting for the double heterogeneity due to the TRISO fuel. The Monte Carlo code MCNP5 has been used in conjunction with CPM3, which was the testbench lattice physics code for this project. MCNP5 is used to perform two calculations for the geometry of interest, one with homogenized fuel compacts and the other with heterogeneous fuel compacts, where the TRISO fuel kernels are resolved by MCNP5.

  14. An Advanced Neutronic Analysis Toolkit with Inline Monte Carlo capability for VHTR Analysis

    International Nuclear Information System (INIS)

    Martin, William R.; Lee, John C.

    2009-01-01

    Monte Carlo capability has been combined with a production LWR lattice physics code to allow analysis of high temperature gas reactor configurations, accounting for the double heterogeneity due to the TRISO fuel. The Monte Carlo code MCNP5 has been used in conjunction with CPM3, which was the testbench lattice physics code for this project. MCNP5 is used to perform two calculations for the geometry of interest, one with homogenized fuel compacts and the other with heterogeneous fuel compacts, where the TRISO fuel kernels are resolved by MCNP5.

  15. Propagation of cross section uncertainties in combined Monte Carlo neutronics and burnup calculations

    Energy Technology Data Exchange (ETDEWEB)

    Kuijper, J.C.; Oppe, J.; Klein Meulekamp, R.; Koning, H. [NRG - Fuels, Actinides and Isotopes group, Petten (Netherlands)

    2005-07-01

    Some years ago a methodology was developed at NRG for the calculation of 'density-to-density' and 'one-group cross section-to-density' sensitivity matrices and covariance matrices for final nuclide densities for burnup schemes consisting of multiple sets of flux/spectrum and burnup calculations. The applicability of the methodology was then demonstrated by calculations of BR3 MOX pin irradiation experiments employing multi-group cross section uncertainty data from the EAF4 data library. A recent development is the extension of this methodology to enable its application in combination with the OCTOPUS-MCNP-FISPACT/ORIGEN Monte Carlo burnup scheme. This required some extensions to the sensitivity matrix calculation tool CASEMATE. The extended methodology was applied on the 'HTR Plutonium Cell Burnup Benchmark' to calculate the uncertainties (covariances) in the final densities, as far as these uncertainties are caused by uncertainties in cross sections. Up to 600 MWd/kg these uncertainties are larger than the differences between the code systems. However, it should be kept in mind that the calculated uncertainties are based on EAF4 uncertainty data. It is not exactly clear on beforehand what a proper set of associated (MCNP) cross sections and covariances would yield in terms of final uncertainties in calculated densities. This will be investigated, by the same formalism, once these data becomes available. It should be noted that the studies performed up till the present date are mainly concerned with the influence of uncertainties in cross sections. The influence of uncertainties in the decay constants, although included in the formalism, is not considered further. Also the influence of other uncertainties (such as -geometrical- modelling approximations) has been left out of consideration for the time being. (authors)

  16. Propagation of cross section uncertainties in combined Monte Carlo neutronics and burnup calculations

    International Nuclear Information System (INIS)

    Kuijper, J.C.; Oppe, J.; Klein Meulekamp, R.; Koning, H.

    2005-01-01

    Some years ago a methodology was developed at NRG for the calculation of 'density-to-density' and 'one-group cross section-to-density' sensitivity matrices and covariance matrices for final nuclide densities for burnup schemes consisting of multiple sets of flux/spectrum and burnup calculations. The applicability of the methodology was then demonstrated by calculations of BR3 MOX pin irradiation experiments employing multi-group cross section uncertainty data from the EAF4 data library. A recent development is the extension of this methodology to enable its application in combination with the OCTOPUS-MCNP-FISPACT/ORIGEN Monte Carlo burnup scheme. This required some extensions to the sensitivity matrix calculation tool CASEMATE. The extended methodology was applied on the 'HTR Plutonium Cell Burnup Benchmark' to calculate the uncertainties (covariances) in the final densities, as far as these uncertainties are caused by uncertainties in cross sections. Up to 600 MWd/kg these uncertainties are larger than the differences between the code systems. However, it should be kept in mind that the calculated uncertainties are based on EAF4 uncertainty data. It is not exactly clear on beforehand what a proper set of associated (MCNP) cross sections and covariances would yield in terms of final uncertainties in calculated densities. This will be investigated, by the same formalism, once these data becomes available. It should be noted that the studies performed up till the present date are mainly concerned with the influence of uncertainties in cross sections. The influence of uncertainties in the decay constants, although included in the formalism, is not considered further. Also the influence of other uncertainties (such as -geometrical- modelling approximations) has been left out of consideration for the time being. (authors)

  17. Comparison of ISO-GUM and Monte Carlo Method for Evaluation of Measurement Uncertainty

    Energy Technology Data Exchange (ETDEWEB)

    Ha, Young-Cheol; Her, Jae-Young; Lee, Seung-Jun; Lee, Kang-Jin [Korea Gas Corporation, Daegu (Korea, Republic of)

    2014-07-15

    To supplement the ISO-GUM method for the evaluation of measurement uncertainty, a simulation program using the Monte Carlo method (MCM) was developed, and the MCM and GUM methods were compared. The results are as follows: (1) Even under a non-normal probability distribution of the measurement, MCM provides an accurate coverage interval; (2) Even if a probability distribution that emerged from combining a few non-normal distributions looks as normal, there are cases in which the actual distribution is not normal and the non-normality can be determined by the probability distribution of the combined variance; and (3) If type-A standard uncertainties are involved in the evaluation of measurement uncertainty, GUM generally offers an under-valued coverage interval. However, this problem can be solved by the Bayesian evaluation of type-A standard uncertainty. In this case, the effective degree of freedom for the combined variance is not required in the evaluation of expanded uncertainty, and the appropriate coverage factor for 95% level of confidence was determined to be 1.96.

  18. Markov chain Monte Carlo methods for statistical analysis of RF photonic devices

    DEFF Research Database (Denmark)

    Piels, Molly; Zibar, Darko

    2016-01-01

    uncertainty is shown to give unsatisfactory and incorrect results due to the nonlinear relationship between the circuit parameters and the measured data. Markov chain Monte Carlo methods are shown to provide superior results, both for individual devices and for assessing within-die variation...

  19. Reporting and analyzing statistical uncertainties in Monte Carlo-based treatment planning

    International Nuclear Information System (INIS)

    Chetty, Indrin J.; Rosu, Mihaela; Kessler, Marc L.; Fraass, Benedick A.; Haken, Randall K. ten; Kong, Feng-Ming; McShan, Daniel L.

    2006-01-01

    Purpose: To investigate methods of reporting and analyzing statistical uncertainties in doses to targets and normal tissues in Monte Carlo (MC)-based treatment planning. Methods and Materials: Methods for quantifying statistical uncertainties in dose, such as uncertainty specification to specific dose points, or to volume-based regions, were analyzed in MC-based treatment planning for 5 lung cancer patients. The effect of statistical uncertainties on target and normal tissue dose indices was evaluated. The concept of uncertainty volume histograms for targets and organs at risk was examined, along with its utility, in conjunction with dose volume histograms, in assessing the acceptability of the statistical precision in dose distributions. The uncertainty evaluation tools were extended to four-dimensional planning for application on multiple instances of the patient geometry. All calculations were performed using the Dose Planning Method MC code. Results: For targets, generalized equivalent uniform doses and mean target doses converged at 150 million simulated histories, corresponding to relative uncertainties of less than 2% in the mean target doses. For the normal lung tissue (a volume-effect organ), mean lung dose and normal tissue complication probability converged at 150 million histories despite the large range in the relative organ uncertainty volume histograms. For 'serial' normal tissues such as the spinal cord, large fluctuations exist in point dose relative uncertainties. Conclusions: The tools presented here provide useful means for evaluating statistical precision in MC-based dose distributions. Tradeoffs between uncertainties in doses to targets, volume-effect organs, and 'serial' normal tissues must be considered carefully in determining acceptable levels of statistical precision in MC-computed dose distributions

  20. New Monte Carlo-based method to evaluate fission fraction uncertainties for the reactor antineutrino experiment

    Energy Technology Data Exchange (ETDEWEB)

    Ma, X.B., E-mail: maxb@ncepu.edu.cn; Qiu, R.M.; Chen, Y.X.

    2017-02-15

    Uncertainties regarding fission fractions are essential in understanding antineutrino flux predictions in reactor antineutrino experiments. A new Monte Carlo-based method to evaluate the covariance coefficients between isotopes is proposed. The covariance coefficients are found to vary with reactor burnup and may change from positive to negative because of balance effects in fissioning. For example, between {sup 235}U and {sup 239}Pu, the covariance coefficient changes from 0.15 to −0.13. Using the equation relating fission fraction and atomic density, consistent uncertainties in the fission fraction and covariance matrix were obtained. The antineutrino flux uncertainty is 0.55%, which does not vary with reactor burnup. The new value is about 8.3% smaller. - Highlights: • The covariance coefficients between isotopes vs reactor burnup may change its sign because of two opposite effects. • The relation between fission fraction uncertainty and atomic density are first studied. • A new MC-based method of evaluating the covariance coefficients between isotopes was proposed.

  1. Application analysis of Monte Carlo to estimate the capacity of geothermal resources in Lawu Mount

    Energy Technology Data Exchange (ETDEWEB)

    Supriyadi, E-mail: supriyadi-uno@yahoo.co.nz [Physics, Faculty of Mathematics and Natural Sciences, University of Jember, Jl. Kalimantan Kampus Bumi Tegal Boto, Jember 68181 (Indonesia); Srigutomo, Wahyu [Complex system and earth physics, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung, Jl. Ganesha 10, Bandung 40132 (Indonesia); Munandar, Arif [Kelompok Program Penelitian Panas Bumi, PSDG, Badan Geologi, Kementrian ESDM, Jl. Soekarno Hatta No. 444 Bandung 40254 (Indonesia)

    2014-03-24

    Monte Carlo analysis has been applied in calculation of geothermal resource capacity based on volumetric method issued by Standar Nasional Indonesia (SNI). A deterministic formula is converted into a stochastic formula to take into account the nature of uncertainties in input parameters. The method yields a range of potential power probability stored beneath Lawu Mount geothermal area. For 10,000 iterations, the capacity of geothermal resources is in the range of 139.30-218.24 MWe with the most likely value is 177.77 MWe. The risk of resource capacity above 196.19 MWe is less than 10%. The power density of the prospect area covering 17 km{sup 2} is 9.41 MWe/km{sup 2} with probability 80%.

  2. Uncertainties in the production of p nuclides in thermonuclear supernovae determined by Monte Carlo variations

    Science.gov (United States)

    Nishimura, N.; Rauscher, T.; Hirschi, R.; Murphy, A. St J.; Cescutti, G.; Travaglio, C.

    2018-03-01

    Thermonuclear supernovae originating from the explosion of a white dwarf accreting mass from a companion star have been suggested as a site for the production of p nuclides. Such nuclei are produced during the explosion, in layers enriched with seed nuclei coming from prior strong s processing. These seeds are transformed into proton-richer isotopes mainly by photodisintegration reactions. Several thousand trajectories from a 2D explosion model were used in a Monte Carlo approach. Temperature-dependent uncertainties were assigned individually to thousands of rates varied simultaneously in post-processing in an extended nuclear reaction network. The uncertainties in the final nuclear abundances originating from uncertainties in the astrophysical reaction rates were determined. In addition to the 35 classical p nuclides, abundance uncertainties were also determined for the radioactive nuclides 92Nb, 97, 98Tc, 146Sm, and for the abundance ratios Y(92Mo)/Y(94Mo), Y(92Nb)/Y(92Mo), Y(97Tc)/Y(98Ru), Y(98Tc)/Y(98Ru), and Y(146Sm)/Y(144Sm), important for Galactic Chemical Evolution studies. Uncertainties found were generally lower than a factor of 2, although most nucleosynthesis flows mainly involve predicted rates with larger uncertainties. The main contribution to the total uncertainties comes from a group of trajectories with high peak density originating from the interior of the exploding white dwarf. The distinction between low-density and high-density trajectories allows more general conclusions to be drawn, also applicable to other simulations of white dwarf explosions.

  3. General purpose dynamic Monte Carlo with continuous energy for transient analysis

    Energy Technology Data Exchange (ETDEWEB)

    Sjenitzer, B. L.; Hoogenboom, J. E. [Delft Univ. of Technology, Dept. of Radiation, Radionuclide and Reactors, Mekelweg 15, 2629JB Delft (Netherlands)

    2012-07-01

    For safety assessments transient analysis is an important tool. It can predict maximum temperatures during regular reactor operation or during an accident scenario. Despite the fact that this kind of analysis is very important, the state of the art still uses rather crude methods, like diffusion theory and point-kinetics. For reference calculations it is preferable to use the Monte Carlo method. In this paper the dynamic Monte Carlo method is implemented in the general purpose Monte Carlo code Tripoli4. Also, the method is extended for use with continuous energy. The first results of Dynamic Tripoli demonstrate that this kind of calculation is indeed accurate and the results are achieved in a reasonable amount of time. With the method implemented in Tripoli it is now possible to do an exact transient calculation in arbitrary geometry. (authors)

  4. Developing and investigating a pure Monte-Carlo module for transient neutron transport analysis

    International Nuclear Information System (INIS)

    Mylonakis, Antonios G.; Varvayanni, M.; Grigoriadis, D.G.E.; Catsaros, N.

    2017-01-01

    Highlights: • Development and investigation of a Monte-Carlo module for transient neutronic analysis. • A transient module developed on the open-source Monte-Carlo static code OpenMC. • Treatment of delayed neutrons is inserted. • Simulation of precursors’ decay process is performed. • Transient analysis of simplified test-cases. - Abstract: In the field of computational reactor physics, Monte-Carlo methodology is extensively used in the analysis of static problems while the transient behavior of the reactor core is mostly analyzed using deterministic algorithms. However, deterministic algorithms make use of various approximations mainly in the geometric and energetic domain that may induce inaccuracy. Therefore, Monte-Carlo methodology which generally does not require significant approximations seems to be an attractive candidate tool for the analysis of transient phenomena. One of the most important constraints towards this direction is the significant computational cost; however since nowadays the available computational resources are continuously increasing, the potential use of the Monte-Carlo methodology in the field of reactor core transient analysis seems feasible. So far, very few attempts to employ Monte-Carlo methodology to transient analysis have been reported. Even more, most of those few attempts make use of several approximations, showing the existence of an “open” research field of great interest. It is obvious that comparing to static Monte-Carlo, a straight-forward physical treatment of a transient problem requires the temporal evolution of the simulated neutrons; but this is not adequate. In order to be able to properly analyze transient reactor core phenomena, the proper simulation of delayed neutrons together with other essential extensions and modifications is necessary. This work is actually the first step towards the development of a tool that could serve as a platform for research and development on this interesting but also

  5. Monte Carlo simulations to advance characterisation of landmines by pulsed fast/thermal neutron analysis

    NARCIS (Netherlands)

    Maucec, M.; Rigollet, C.

    The performance of a detection system based on the pulsed fast/thermal neutron analysis technique was assessed using Monte Carlo simulations. The aim was to develop and implement simulation methods, to support and advance the data analysis techniques of the characteristic gamma-ray spectra,

  6. A Markov Chain Monte Carlo Approach to Confirmatory Item Factor Analysis

    Science.gov (United States)

    Edwards, Michael C.

    2010-01-01

    Item factor analysis has a rich tradition in both the structural equation modeling and item response theory frameworks. The goal of this paper is to demonstrate a novel combination of various Markov chain Monte Carlo (MCMC) estimation routines to estimate parameters of a wide variety of confirmatory item factor analysis models. Further, I show…

  7. Construction of the quantitative analysis environment using Monte Carlo simulation

    International Nuclear Information System (INIS)

    Shirakawa, Seiji; Ushiroda, Tomoya; Hashimoto, Hiroshi; Tadokoro, Masanori; Uno, Masaki; Tsujimoto, Masakazu; Ishiguro, Masanobu; Toyama, Hiroshi

    2013-01-01

    The thoracic phantom image was acquisitioned of the axial section to construct maps of the source and density with Monte Carlo (MC) simulation. The phantom was Heart/Liver Type HL (Kyoto Kagaku Co., Ltd.) single photon emission CT (SPECT)/CT machine was Symbia T6 (Siemence) with the collimator LMEGP (low-medium energy general purpose). Maps were constructed from CT images with an in-house software using Visual studio C Sharp (Microsoft). The code simulation of imaging nuclear detectors (SIMIND) was used for MC simulation, Prominence processor (Nihon Medi-Physics) for filter processing and image reconstruction, and the environment DELL Precision T7400 for all image processes. For the actual experiment, the phantom was given 15 MBq of 99m Tc assuming the uptake 2% at the dose of 740 MBq in its myocardial portion and SPECT image was acquisitioned and reconstructed with Butter-worth filter and filter back projection method. CT images were similarly obtained in 0.3 mm thick slices, which were filed in one formatted with digital imaging and communication in medicine (DICOM), and then processed for application to SIMIND for mapping the source and density. Physical and mensuration factors were examined in ideal images by sequential exclusion and simulation of those factors as attenuation, scattering, spatial resolution deterioration and statistical fluctuation. Gamma energy spectrum, SPECT projection and reconstructed images given by the simulation were found to well agree with the actual data, and the precision of MC simulation was confirmed. Physical and mensuration factors were found to be evaluable individually, suggesting the usefulness of the simulation for assessing the precision of their correction. (T.T.)

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

    Science.gov (United States)

    Xin, Cao; Chongshi, Gu

    2016-01-01

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

  9. A Monte Carlo approach to constraining uncertainties in modelled downhole gravity gradiometry applications

    Science.gov (United States)

    Matthews, Samuel J.; O'Neill, Craig; Lackie, Mark A.

    2017-06-01

    Gravity gradiometry has a long legacy, with airborne/marine applications as well as surface applications receiving renewed recent interest. Recent instrumental advances has led to the emergence of downhole gravity gradiometry applications that have the potential for greater resolving power than borehole gravity alone. This has promise in both the petroleum and geosequestration industries; however, the effect of inherent uncertainties in the ability of downhole gravity gradiometry to resolve a subsurface signal is unknown. Here, we utilise the open source modelling package, Fatiando a Terra, to model both the gravity and gravity gradiometry responses of a subsurface body. We use a Monte Carlo approach to vary the geological structure and reference densities of the model within preset distributions. We then perform 100 000 simulations to constrain the mean response of the buried body as well as uncertainties in these results. We varied our modelled borehole to be either centred on the anomaly, adjacent to the anomaly (in the x-direction), and 2500 m distant to the anomaly (also in the x-direction). We demonstrate that gravity gradiometry is able to resolve a reservoir-scale modelled subsurface density variation up to 2500 m away, and that certain gravity gradient components (Gzz, Gxz, and Gxx) are particularly sensitive to this variation in gravity/gradiometry above the level of uncertainty in the model. The responses provided by downhole gravity gradiometry modelling clearly demonstrate a technique that can be utilised in determining a buried density contrast, which will be of particular use in the emerging industry of CO2 geosequestration. The results also provide a strong benchmark for the development of newly emerging prototype downhole gravity gradiometers.

  10. Asymptotic equilibrium diffusion analysis of time-dependent Monte Carlo methods for grey radiative transfer

    International Nuclear Information System (INIS)

    Densmore, Jeffery D.; Larsen, Edward W.

    2004-01-01

    The equations of nonlinear, time-dependent radiative transfer are known to yield the equilibrium diffusion equation as the leading-order solution of an asymptotic analysis when the mean-free path and mean-free time of a photon become small. We apply this same analysis to the Fleck-Cummings, Carter-Forest, and N'kaoua Monte Carlo approximations for grey (frequency-independent) radiative transfer. Although Monte Carlo simulation usually does not require the discretizations found in deterministic transport techniques, Monte Carlo methods for radiative transfer require a time discretization due to the nonlinearities of the problem. If an asymptotic analysis of the equations used by a particular Monte Carlo method yields an accurate time-discretized version of the equilibrium diffusion equation, the method should generate accurate solutions if a time discretization is chosen that resolves temperature changes, even if the time steps are much larger than the mean-free time of a photon. This analysis is of interest because in many radiative transfer problems, it is a practical necessity to use time steps that are large compared to a mean-free time. Our asymptotic analysis shows that: (i) the N'kaoua method has the equilibrium diffusion limit, (ii) the Carter-Forest method has the equilibrium diffusion limit if the material temperature change during a time step is small, and (iii) the Fleck-Cummings method does not have the equilibrium diffusion limit. We include numerical results that verify our theoretical predictions

  11. Research on reactor physics analysis method based on Monte Carlo homogenization

    International Nuclear Information System (INIS)

    Ye Zhimin; Zhang Peng

    2014-01-01

    In order to meet the demand of nuclear energy market in the future, many new concepts of nuclear energy systems has been put forward. The traditional deterministic neutronics analysis method has been challenged in two aspects: one is the ability of generic geometry processing; the other is the multi-spectrum applicability of the multigroup cross section libraries. Due to its strong geometry modeling capability and the application of continuous energy cross section libraries, the Monte Carlo method has been widely used in reactor physics calculations, and more and more researches on Monte Carlo method has been carried out. Neutronics-thermal hydraulics coupling analysis based on Monte Carlo method has been realized. However, it still faces the problems of long computation time and slow convergence which make it not applicable to the reactor core fuel management simulations. Drawn from the deterministic core analysis method, a new two-step core analysis scheme is proposed in this work. Firstly, Monte Carlo simulations are performed for assembly, and the assembly homogenized multi-group cross sections are tallied at the same time. Secondly, the core diffusion calculations can be done with these multigroup cross sections. The new scheme can achieve high efficiency while maintain acceptable precision, so it can be used as an effective tool for the design and analysis of innovative nuclear energy systems. Numeric tests have been done in this work to verify the new scheme. (authors)

  12. Failure Bounding And Sensitivity Analysis Applied To Monte Carlo Entry, Descent, And Landing Simulations

    Science.gov (United States)

    Gaebler, John A.; Tolson, Robert H.

    2010-01-01

    In the study of entry, descent, and landing, Monte Carlo sampling methods are often employed to study the uncertainty in the designed trajectory. The large number of uncertain inputs and outputs, coupled with complicated non-linear models, can make interpretation of the results difficult. Three methods that provide statistical insights are applied to an entry, descent, and landing simulation. The advantages and disadvantages of each method are discussed in terms of the insights gained versus the computational cost. The first method investigated was failure domain bounding which aims to reduce the computational cost of assessing the failure probability. Next a variance-based sensitivity analysis was studied for the ability to identify which input variable uncertainty has the greatest impact on the uncertainty of an output. Finally, probabilistic sensitivity analysis is used to calculate certain sensitivities at a reduced computational cost. These methods produce valuable information that identifies critical mission parameters and needs for new technology, but generally at a significant computational cost.

  13. Monte Carlo sensitivity analysis of an Eulerian large-scale air pollution model

    International Nuclear Information System (INIS)

    Dimov, I.; Georgieva, R.; Ostromsky, Tz.

    2012-01-01

    Variance-based approaches for global sensitivity analysis have been applied and analyzed to study the sensitivity of air pollutant concentrations according to variations of rates of chemical reactions. The Unified Danish Eulerian Model has been used as a mathematical model simulating a remote transport of air pollutants. Various Monte Carlo algorithms for numerical integration have been applied to compute Sobol's global sensitivity indices. A newly developed Monte Carlo algorithm based on Sobol's quasi-random points MCA-MSS has been applied for numerical integration. It has been compared with some existing approaches, namely Sobol's ΛΠ τ sequences, an adaptive Monte Carlo algorithm, the plain Monte Carlo algorithm, as well as, eFAST and Sobol's sensitivity approaches both implemented in SIMLAB software. The analysis and numerical results show advantages of MCA-MSS for relatively small sensitivity indices in terms of accuracy and efficiency. Practical guidelines on the estimation of Sobol's global sensitivity indices in the presence of computational difficulties have been provided. - Highlights: ► Variance-based global sensitivity analysis is performed for the air pollution model UNI-DEM. ► The main effect of input parameters dominates over higher-order interactions. ► Ozone concentrations are influenced mostly by variability of three chemical reactions rates. ► The newly developed MCA-MSS for multidimensional integration is compared with other approaches. ► More precise approaches like MCA-MSS should be applied when the needed accuracy has not been achieved.

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

    Science.gov (United States)

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

    2012-01-01

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

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

    Czech Academy of Sciences Publication Activity Database

    Mukhopadhyay, N. D.; Sampson, A. J.; Deniz, D.; Carlsson, G. A.; Williamson, J.; Malušek, Alexandr

    2012-01-01

    Roč. 70, č. 1 (2012), s. 315-323 ISSN 0969-8043 Institutional research plan: CEZ:AV0Z10480505 Keywords : Monte Carlo * correlated sampling * efficiency * uncertainty * bootstrap Subject RIV: BG - Nuclear, Atomic and Molecular Physics, Colliders Impact factor: 1.179, year: 2012 http://www.sciencedirect.com/science/article/pii/S0969804311004775

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

    Science.gov (United States)

    Hoogenboom, J. Eduard; Sjenitzer, Bart L.

    2014-06-01

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

  17. Accelerated Monte Carlo system reliability analysis through machine-learning-based surrogate models of network connectivity

    International Nuclear Information System (INIS)

    Stern, R.E.; Song, J.; Work, D.B.

    2017-01-01

    The two-terminal reliability problem in system reliability analysis is known to be computationally intractable for large infrastructure graphs. Monte Carlo techniques can estimate the probability of a disconnection between two points in a network by selecting a representative sample of network component failure realizations and determining the source-terminal connectivity of each realization. To reduce the runtime required for the Monte Carlo approximation, this article proposes an approximate framework in which the connectivity check of each sample is estimated using a machine-learning-based classifier. The framework is implemented using both a support vector machine (SVM) and a logistic regression based surrogate model. Numerical experiments are performed on the California gas distribution network using the epicenter and magnitude of the 1989 Loma Prieta earthquake as well as randomly-generated earthquakes. It is shown that the SVM and logistic regression surrogate models are able to predict network connectivity with accuracies of 99% for both methods, and are 1–2 orders of magnitude faster than using a Monte Carlo method with an exact connectivity check. - Highlights: • Surrogate models of network connectivity are developed by machine-learning algorithms. • Developed surrogate models can reduce the runtime required for Monte Carlo simulations. • Support vector machine and logistic regressions are employed to develop surrogate models. • Numerical example of California gas distribution network demonstrate the proposed approach. • The developed models have accuracies 99%, and are 1–2 orders of magnitude faster than MCS.

  18. An alternative approach to probabilistic seismic hazard analysis in the Aegean region using Monte Carlo simulation

    Science.gov (United States)

    Weatherill, Graeme; Burton, Paul W.

    2010-09-01

    The Aegean is the most seismically active and tectonically complex region in Europe. Damaging earthquakes have occurred here throughout recorded history, often resulting in considerable loss of life. The Monte Carlo method of probabilistic seismic hazard analysis (PSHA) is used to determine the level of ground motion likely to be exceeded in a given time period. Multiple random simulations of seismicity are generated to calculate, directly, the ground motion for a given site. Within the seismic hazard analysis we explore the impact of different seismic source models, incorporating both uniform zones and distributed seismicity. A new, simplified, seismic source model, derived from seismotectonic interpretation, is presented for the Aegean region. This is combined into the epistemic uncertainty analysis alongside existing source models for the region, and models derived by a K-means cluster analysis approach. Seismic source models derived using the K-means approach offer a degree of objectivity and reproducibility into the otherwise subjective approach of delineating seismic sources using expert judgment. Similar review and analysis is undertaken for the selection of peak ground acceleration (PGA) attenuation models, incorporating into the epistemic analysis Greek-specific models, European models and a Next Generation Attenuation model. Hazard maps for PGA on a "rock" site with a 10% probability of being exceeded in 50 years are produced and different source and attenuation models are compared. These indicate that Greek-specific attenuation models, with their smaller aleatory variability terms, produce lower PGA hazard, whilst recent European models and Next Generation Attenuation (NGA) model produce similar results. The Monte Carlo method is extended further to assimilate epistemic uncertainty into the hazard calculation, thus integrating across several appropriate source and PGA attenuation models. Site condition and fault-type are also integrated into the hazard

  19. Integrating uncertainties to the combined environmental and economic assessment of algal biorefineries: A Monte Carlo approach.

    Science.gov (United States)

    Pérez-López, Paula; Montazeri, Mahdokht; Feijoo, Gumersindo; Moreira, María Teresa; Eckelman, Matthew J

    2018-06-01

    The economic and environmental performance of microalgal processes has been widely analyzed in recent years. However, few studies propose an integrated process-based approach to evaluate economic and environmental indicators simultaneously. Biodiesel is usually the single product and the effect of environmental benefits of co-products obtained in the process is rarely discussed. In addition, there is wide variation of the results due to inherent variability of some parameters as well as different assumptions in the models and limited knowledge about the processes. In this study, two standardized models were combined to provide an integrated simulation tool allowing the simultaneous estimation of economic and environmental indicators from a unique set of input parameters. First, a harmonized scenario was assessed to validate the joint environmental and techno-economic model. The findings were consistent with previous assessments. In a second stage, a Monte Carlo simulation was applied to evaluate the influence of variable and uncertain parameters in the model output, as well as the correlations between the different outputs. The simulation showed a high probability of achieving favorable environmental performance for the evaluated categories and a minimum selling price ranging from $11gal -1 to $106gal -1 . Greenhouse gas emissions and minimum selling price were found to have the strongest positive linear relationship, whereas eutrophication showed weak correlations with the other indicators (namely greenhouse gas emissions, cumulative energy demand and minimum selling price). Process parameters (especially biomass productivity and lipid content) were the main source of variation, whereas uncertainties linked to the characterization methods and economic parameters had limited effect on the results. Copyright © 2018 Elsevier B.V. All rights reserved.

  20. Systematic uncertainties in the Monte Carlo calculation of ion chamber replacement correction factors

    Energy Technology Data Exchange (ETDEWEB)

    Wang, L. L. W.; La Russa, D. J.; Rogers, D. W. O. [Ottawa Carleton Institute of Physics, Carleton University, Campus Ottawa, Ottawa, Ontario KIS 5B6 (Canada)

    2009-05-15

    In a previous study [Med. Phys. 35, 1747-1755 (2008)], the authors proposed two direct methods of calculating the replacement correction factors (P{sub repl} or p{sub cav}p{sub dis}) for ion chambers by Monte Carlo calculation. By ''direct'' we meant the stopping-power ratio evaluation is not necessary. The two methods were named as the high-density air (HDA) and low-density water (LDW) methods. Although the accuracy of these methods was briefly discussed, it turns out that the assumption made regarding the dose in an HDA slab as a function of slab thickness is not correct. This issue is reinvestigated in the current study, and the accuracy of the LDW method applied to ion chambers in a {sup 60}Co photon beam is also studied. It is found that the two direct methods are in fact not completely independent of the stopping-power ratio of the two materials involved. There is an implicit dependence of the calculated P{sub repl} values upon the stopping-power ratio evaluation through the choice of an appropriate energy cutoff {Delta}, which characterizes a cavity size in the Spencer-Attix cavity theory. Since the {Delta} value is not accurately defined in the theory, this dependence on the stopping-power ratio results in a systematic uncertainty on the calculated P{sub repl} values. For phantom materials of similar effective atomic number to air, such as water and graphite, this systematic uncertainty is at most 0.2% for most commonly used chambers for either electron or photon beams. This uncertainty level is good enough for current ion chamber dosimetry, and the merits of the two direct methods of calculating P{sub repl} values are maintained, i.e., there is no need to do a separate stopping-power ratio calculation. For high-Z materials, the inherent uncertainty would make it practically impossible to calculate reliable P{sub repl} values using the two direct methods.

  1. Perturbation analysis for Monte Carlo continuous cross section models

    International Nuclear Information System (INIS)

    Kennedy, Chris B.; Abdel-Khalik, Hany S.

    2011-01-01

    Sensitivity analysis, including both its forward and adjoint applications, collectively referred to hereinafter as Perturbation Analysis (PA), is an essential tool to complete Uncertainty Quantification (UQ) and Data Assimilation (DA). PA-assisted UQ and DA have traditionally been carried out for reactor analysis problems using deterministic as opposed to stochastic models for radiation transport. This is because PA requires many model executions to quantify how variations in input data, primarily cross sections, affect variations in model's responses, e.g. detectors readings, flux distribution, multiplication factor, etc. Although stochastic models are often sought for their higher accuracy, their repeated execution is at best computationally expensive and in reality intractable for typical reactor analysis problems involving many input data and output responses. Deterministic methods however achieve computational efficiency needed to carry out the PA analysis by reducing problem dimensionality via various spatial and energy homogenization assumptions. This however introduces modeling error components into the PA results which propagate to the following UQ and DA analyses. The introduced errors are problem specific and therefore are expected to limit the applicability of UQ and DA analyses to reactor systems that satisfy the introduced assumptions. This manuscript introduces a new method to complete PA employing a continuous cross section stochastic model and performed in a computationally efficient manner. If successful, the modeling error components introduced by deterministic methods could be eliminated, thereby allowing for wider applicability of DA and UQ results. Two MCNP models demonstrate the application of the new method - a Critical Pu Sphere (Jezebel), a Pu Fast Metal Array (Russian BR-1). The PA is completed for reaction rate densities, reaction rate ratios, and the multiplication factor. (author)

  2. Monte carlo analysis of multicolour LED light engine

    DEFF Research Database (Denmark)

    Chakrabarti, Maumita; Thorseth, Anders; Jepsen, Jørgen

    2015-01-01

    light engine designed for white tuneable studio lighting. The measured sensitivities to the various factors influencing the colour uncertainty for similar system are incorporated. The method aims to provide uncertainties in the achievable chromaticity coordinates as output over the tuneable range, e...

  3. Confronting uncertainty in model-based geostatistics using Markov Chain Monte Carlo simulation

    NARCIS (Netherlands)

    Minasny, B.; Vrugt, J.A.; McBratney, A.B.

    2011-01-01

    This paper demonstrates for the first time the use of Markov Chain Monte Carlo (MCMC) simulation for parameter inference in model-based soil geostatistics. We implemented the recently developed DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm to jointly summarize the posterior

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

    NARCIS (Netherlands)

    Vrugt, J.A.; Braak, ter C.J.F.; Clark, M.P.; Hyman, J.M.; Robinson, B.A.

    2008-01-01

    There is increasing consensus in the hydrologic literature that an appropriate framework for streamflow forecasting and simulation should include explicit recognition of forcing and parameter and model structural error. This paper presents a novel Markov chain Monte Carlo (MCMC) sampler, entitled

  5. On the predictivity of pore-scale simulations: estimating uncertainties with multilevel Monte Carlo

    KAUST Repository

    Icardi, Matteo

    2016-02-08

    A fast method with tunable accuracy is proposed to estimate errors and uncertainties in pore-scale and Digital Rock Physics (DRP) problems. The overall predictivity of these studies can be, in fact, hindered by many factors including sample heterogeneity, computational and imaging limitations, model inadequacy and not perfectly known physical parameters. The typical objective of pore-scale studies is the estimation of macroscopic effective parameters such as permeability, effective diffusivity and hydrodynamic dispersion. However, these are often non-deterministic quantities (i.e., results obtained for specific pore-scale sample and setup are not totally reproducible by another “equivalent” sample and setup). The stochastic nature can arise due to the multi-scale heterogeneity, the computational and experimental limitations in considering large samples, and the complexity of the physical models. These approximations, in fact, introduce an error that, being dependent on a large number of complex factors, can be modeled as random. We propose a general simulation tool, based on multilevel Monte Carlo, that can reduce drastically the computational cost needed for computing accurate statistics of effective parameters and other quantities of interest, under any of these random errors. This is, to our knowledge, the first attempt to include Uncertainty Quantification (UQ) in pore-scale physics and simulation. The method can also provide estimates of the discretization error and it is tested on three-dimensional transport problems in heterogeneous materials, where the sampling procedure is done by generation algorithms able to reproduce realistic consolidated and unconsolidated random sphere and ellipsoid packings and arrangements. A totally automatic workflow is developed in an open-source code [2015. https://bitbucket.org/micardi/porescalemc.], that include rigid body physics and random packing algorithms, unstructured mesh discretization, finite volume solvers

  6. Propagation of uncertainty by Monte Carlo simulations in case of basic geodetic computations

    Directory of Open Access Journals (Sweden)

    Wyszkowska Patrycja

    2017-12-01

    Full Text Available The determination of the accuracy of functions of measured or adjusted values may be a problem in geodetic computations. The general law of covariance propagation or in case of the uncorrelated observations the propagation of variance (or the Gaussian formula are commonly used for that purpose. That approach is theoretically justified for the linear functions. In case of the non-linear functions, the first-order Taylor series expansion is usually used but that solution is affected by the expansion error. The aim of the study is to determine the applicability of the general variance propagation law in case of the non-linear functions used in basic geodetic computations. The paper presents errors which are a result of negligence of the higher-order expressions and it determines the range of such simplification. The basis of that analysis is the comparison of the results obtained by the law of propagation of variance and the probabilistic approach, namely Monte Carlo simulations. Both methods are used to determine the accuracy of the following geodetic computations: the Cartesian coordinates of unknown point in the three-point resection problem, azimuths and distances of the Cartesian coordinates, height differences in the trigonometric and the geometric levelling. These simulations and the analysis of the results confirm the possibility of applying the general law of variance propagation in basic geodetic computations even if the functions are non-linear. The only condition is the accuracy of observations, which cannot be too low. Generally, this is not a problem with using present geodetic instruments.

  7. Propagation of uncertainty by Monte Carlo simulations in case of basic geodetic computations

    Science.gov (United States)

    Wyszkowska, Patrycja

    2017-12-01

    The determination of the accuracy of functions of measured or adjusted values may be a problem in geodetic computations. The general law of covariance propagation or in case of the uncorrelated observations the propagation of variance (or the Gaussian formula) are commonly used for that purpose. That approach is theoretically justified for the linear functions. In case of the non-linear functions, the first-order Taylor series expansion is usually used but that solution is affected by the expansion error. The aim of the study is to determine the applicability of the general variance propagation law in case of the non-linear functions used in basic geodetic computations. The paper presents errors which are a result of negligence of the higher-order expressions and it determines the range of such simplification. The basis of that analysis is the comparison of the results obtained by the law of propagation of variance and the probabilistic approach, namely Monte Carlo simulations. Both methods are used to determine the accuracy of the following geodetic computations: the Cartesian coordinates of unknown point in the three-point resection problem, azimuths and distances of the Cartesian coordinates, height differences in the trigonometric and the geometric levelling. These simulations and the analysis of the results confirm the possibility of applying the general law of variance propagation in basic geodetic computations even if the functions are non-linear. The only condition is the accuracy of observations, which cannot be too low. Generally, this is not a problem with using present geodetic instruments.

  8. A comparison of Bayesian and Monte Carlo sensitivity analysis for unmeasured confounding.

    Science.gov (United States)

    McCandless, Lawrence C; Gustafson, Paul

    2017-08-15

    Bias from unmeasured confounding is a persistent concern in observational studies, and sensitivity analysis has been proposed as a solution. In the recent years, probabilistic sensitivity analysis using either Monte Carlo sensitivity analysis (MCSA) or Bayesian sensitivity analysis (BSA) has emerged as a practical analytic strategy when there are multiple bias parameters inputs. BSA uses Bayes theorem to formally combine evidence from the prior distribution and the data. In contrast, MCSA samples bias parameters directly from the prior distribution. Intuitively, one would think that BSA and MCSA ought to give similar results. Both methods use similar models and the same (prior) probability distributions for the bias parameters. In this paper, we illustrate the surprising finding that BSA and MCSA can give very different results. Specifically, we demonstrate that MCSA can give inaccurate uncertainty assessments (e.g. 95% intervals) that do not reflect the data's influence on uncertainty about unmeasured confounding. Using a data example from epidemiology and simulation studies, we show that certain combinations of data and prior distributions can result in dramatic prior-to-posterior changes in uncertainty about the bias parameters. This occurs because the application of Bayes theorem in a non-identifiable model can sometimes rule out certain patterns of unmeasured confounding that are not compatible with the data. Consequently, the MCSA approach may give 95% intervals that are either too wide or too narrow and that do not have 95% frequentist coverage probability. Based on our findings, we recommend that analysts use BSA for probabilistic sensitivity analysis. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  9. Statistical analysis and Monte Carlo simulation of growing self-avoiding walks on percolation

    Energy Technology Data Exchange (ETDEWEB)

    Zhang Yuxia [Department of Physics, Wuhan University, Wuhan 430072 (China); Sang Jianping [Department of Physics, Wuhan University, Wuhan 430072 (China); Department of Physics, Jianghan University, Wuhan 430056 (China); Zou Xianwu [Department of Physics, Wuhan University, Wuhan 430072 (China)]. E-mail: xwzou@whu.edu.cn; Jin Zhunzhi [Department of Physics, Wuhan University, Wuhan 430072 (China)

    2005-09-26

    The two-dimensional growing self-avoiding walk on percolation was investigated by statistical analysis and Monte Carlo simulation. We obtained the expression of the mean square displacement and effective exponent as functions of time and percolation probability by statistical analysis and made a comparison with simulations. We got a reduced time to scale the motion of walkers in growing self-avoiding walks on regular and percolation lattices.

  10. Mixed oxidizer hybrid propulsion system optimization under uncertainty using applied response surface methodology and Monte Carlo simulation

    Science.gov (United States)

    Whitehead, James Joshua

    The analysis documented herein provides an integrated approach for the conduct of optimization under uncertainty (OUU) using Monte Carlo Simulation (MCS) techniques coupled with response surface-based methods for characterization of mixture-dependent variables. This novel methodology provides an innovative means of conducting optimization studies under uncertainty in propulsion system design. Analytic inputs are based upon empirical regression rate information obtained from design of experiments (DOE) mixture studies utilizing a mixed oxidizer hybrid rocket concept. Hybrid fuel regression rate was selected as the target response variable for optimization under uncertainty, with maximization of regression rate chosen as the driving objective. Characteristic operational conditions and propellant mixture compositions from experimental efforts conducted during previous foundational work were combined with elemental uncertainty estimates as input variables. Response surfaces for mixture-dependent variables and their associated uncertainty levels were developed using quadratic response equations incorporating single and two-factor interactions. These analysis inputs, response surface equations and associated uncertainty contributions were applied to a probabilistic MCS to develop dispersed regression rates as a function of operational and mixture input conditions within design space. Illustrative case scenarios were developed and assessed using this analytic approach including fully and partially constrained operational condition sets over all of design mixture space. In addition, optimization sets were performed across an operationally representative region in operational space and across all investigated mixture combinations. These scenarios were selected as representative examples relevant to propulsion system optimization, particularly for hybrid and solid rocket platforms. Ternary diagrams, including contour and surface plots, were developed and utilized to aid in

  11. Benchmarking the MCNP code for Monte Carlo modelling of an in vivo neutron activation analysis system.

    Science.gov (United States)

    Natto, S A; Lewis, D G; Ryde, S J

    1998-01-01

    The Monte Carlo computer code MCNP (version 4A) has been used to develop a personal computer-based model of the Swansea in vivo neutron activation analysis (IVNAA) system. The model included specification of the neutron source (252Cf), collimators, reflectors and shielding. The MCNP model was 'benchmarked' against fast neutron and thermal neutron fluence data obtained experimentally from the IVNAA system. The Swansea system allows two irradiation geometries using 'short' and 'long' collimators, which provide alternative dose rates for IVNAA. The data presented here relate to the short collimator, although results of similar accuracy were obtained using the long collimator. The fast neutron fluence was measured in air at a series of depths inside the collimator. The measurements agreed with the MCNP simulation within the statistical uncertainty (5-10%) of the calculations. The thermal neutron fluence was measured and calculated inside the cuboidal water phantom. The depth of maximum thermal fluence was 3.2 cm (measured) and 3.0 cm (calculated). The width of the 50% thermal fluence level across the phantom at its mid-depth was found to be the same by both MCNP and experiment. This benchmarking exercise has given us a high degree of confidence in MCNP as a tool for the design of IVNAA systems.

  12. Present status of Monte Carlo seminar for sub-criticality safety analysis in Japan

    International Nuclear Information System (INIS)

    Sakurai, Kiyoshi

    2003-01-01

    This paper provides overview of the methods and results of a series of sub-criticality safety analysis seminars for nuclear fuel cycle facility with the Monte Carlo method held in Japan from July 2000 to July 2003. In these seminars, MCNP-4C2 system (MS-DOS version) was installed in note-type personal computers for participants. Fundamental theory of reactor physics and Monte Carlo simulation as well as the contents of the MCNP manual were lectured. Effective neutron multiplication factors and neutron spectra were calculated for some examples such as JCO deposit tank, JNC uranium solution storage tank, JNC plutonium solution storage tank and JAERI TCA core. Management for safety of nuclear fuel cycle facilities was discussed in order to prevent criticality accidents in some of the seminars. (author)

  13. Stability analysis and time-step limits for a Monte Carlo Compton-scattering method

    International Nuclear Information System (INIS)

    Densmore, Jeffery D.; Warsa, James S.; Lowrie, Robert B.

    2010-01-01

    A Monte Carlo method for simulating Compton scattering in high energy density applications has been presented that models the photon-electron collision kinematics exactly [E. Canfield, W.M. Howard, E.P. Liang, Inverse Comptonization by one-dimensional relativistic electrons, Astrophys. J. 323 (1987) 565]. However, implementing this technique typically requires an explicit evaluation of the material temperature, which can lead to unstable and oscillatory solutions. In this paper, we perform a stability analysis of this Monte Carlo method and develop two time-step limits that avoid undesirable behavior. The first time-step limit prevents instabilities, while the second, more restrictive time-step limit avoids both instabilities and nonphysical oscillations. With a set of numerical examples, we demonstrate the efficacy of these time-step limits.

  14. Canonical Least-Squares Monte Carlo Valuation of American Options: Convergence and Empirical Pricing Analysis

    Directory of Open Access Journals (Sweden)

    Xisheng Yu

    2014-01-01

    Full Text Available The paper by Liu (2010 introduces a method termed the canonical least-squares Monte Carlo (CLM which combines a martingale-constrained entropy model and a least-squares Monte Carlo algorithm to price American options. In this paper, we first provide the convergence results of CLM and numerically examine the convergence properties. Then, the comparative analysis is empirically conducted using a large sample of the S&P 100 Index (OEX puts and IBM puts. The results on the convergence show that choosing the shifted Legendre polynomials with four regressors is more appropriate considering the pricing accuracy and the computational cost. With this choice, CLM method is empirically demonstrated to be superior to the benchmark methods of binominal tree and finite difference with historical volatilities.

  15. Approximation of the Monte Carlo Sampling Method for Reliability Analysis of Structures

    Directory of Open Access Journals (Sweden)

    Mahdi Shadab Far

    2016-01-01

    Full Text Available Structural load types, on the one hand, and structural capacity to withstand these loads, on the other hand, are of a probabilistic nature as they cannot be calculated and presented in a fully deterministic way. As such, the past few decades have witnessed the development of numerous probabilistic approaches towards the analysis and design of structures. Among the conventional methods used to assess structural reliability, the Monte Carlo sampling method has proved to be very convenient and efficient. However, it does suffer from certain disadvantages, the biggest one being the requirement of a very large number of samples to handle small probabilities, leading to a high computational cost. In this paper, a simple algorithm was proposed to estimate low failure probabilities using a small number of samples in conjunction with the Monte Carlo method. This revised approach was then presented in a step-by-step flowchart, for the purpose of easy programming and implementation.

  16. Monte Carlo Analysis as a Trajectory Design Driver for the TESS Mission

    Science.gov (United States)

    Nickel, Craig; Lebois, Ryan; Lutz, Stephen; Dichmann, Donald; Parker, Joel

    2016-01-01

    The Transiting Exoplanet Survey Satellite (TESS) will be injected into a highly eccentric Earth orbit and fly 3.5 phasing loops followed by a lunar flyby to enter a mission orbit with lunar 2:1 resonance. Through the phasing loops and mission orbit, the trajectory is significantly affected by lunar and solar gravity. We have developed a trajectory design to achieve the mission orbit and meet mission constraints, including eclipse avoidance and a 30-year geostationary orbit avoidance requirement. A parallelized Monte Carlo simulation was performed to validate the trajectory after injecting common perturbations, including launch dispersions, orbit determination errors, and maneuver execution errors. The Monte Carlo analysis helped identify mission risks and is used in the trajectory selection process.

  17. Monte Carlo Analysis as a Trajectory Design Driver for the Transiting Exoplanet Survey Satellite (TESS) Mission

    Science.gov (United States)

    Nickel, Craig; Parker, Joel; Dichmann, Don; Lebois, Ryan; Lutz, Stephen

    2016-01-01

    The Transiting Exoplanet Survey Satellite (TESS) will be injected into a highly eccentric Earth orbit and fly 3.5 phasing loops followed by a lunar flyby to enter a mission orbit with lunar 2:1 resonance. Through the phasing loops and mission orbit, the trajectory is significantly affected by lunar and solar gravity. We have developed a trajectory design to achieve the mission orbit and meet mission constraints, including eclipse avoidance and a 30-year geostationary orbit avoidance requirement. A parallelized Monte Carlo simulation was performed to validate the trajectory after injecting common perturbations, including launch dispersions, orbit determination errors, and maneuver execution errors. The Monte Carlo analysis helped identify mission risks and is used in the trajectory selection process.

  18. Vectorized Monte Carlo

    International Nuclear Information System (INIS)

    Brown, F.B.

    1981-01-01

    Examination of the global algorithms and local kernels of conventional general-purpose Monte Carlo codes shows that multigroup Monte Carlo methods have sufficient structure to permit efficient vectorization. A structured multigroup Monte Carlo algorithm for vector computers is developed in which many particle events are treated at once on a cell-by-cell basis. Vectorization of kernels for tracking and variance reduction is described, and a new method for discrete sampling is developed to facilitate the vectorization of collision analysis. To demonstrate the potential of the new method, a vectorized Monte Carlo code for multigroup radiation transport analysis was developed. This code incorporates many features of conventional general-purpose production codes, including general geometry, splitting and Russian roulette, survival biasing, variance estimation via batching, a number of cutoffs, and generalized tallies of collision, tracklength, and surface crossing estimators with response functions. Predictions of vectorized performance characteristics for the CYBER-205 were made using emulated coding and a dynamic model of vector instruction timing. Computation rates were examined for a variety of test problems to determine sensitivities to batch size and vector lengths. Significant speedups are predicted for even a few hundred particles per batch, and asymptotic speedups by about 40 over equivalent Amdahl 470V/8 scalar codes arepredicted for a few thousand particles per batch. The principal conclusion is that vectorization of a general-purpose multigroup Monte Carlo code is well worth the significant effort required for stylized coding and major algorithmic changes

  19. Monte-Carlo error analysis in x-ray spectral deconvolution

    International Nuclear Information System (INIS)

    Shirk, D.G.; Hoffman, N.M.

    1985-01-01

    The deconvolution of spectral information from sparse x-ray data is a widely encountered problem in data analysis. An often-neglected aspect of this problem is the propagation of random error in the deconvolution process. We have developed a Monte-Carlo approach that enables us to attach error bars to unfolded x-ray spectra. Our Monte-Carlo error analysis has been incorporated into two specific deconvolution techniques: the first is an iterative convergent weight method; the second is a singular-value-decomposition (SVD) method. These two methods were applied to an x-ray spectral deconvolution problem having m channels of observations with n points in energy space. When m is less than n, this problem has no unique solution. We discuss the systematics of nonunique solutions and energy-dependent error bars for both methods. The Monte-Carlo approach has a particular benefit in relation to the SVD method: It allows us to apply the constraint of spectral nonnegativity after the SVD deconvolution rather than before. Consequently, we can identify inconsistencies between different detector channels

  20. Time Series Analysis of Monte Carlo Fission Sources - I: Dominance Ratio Computation

    International Nuclear Information System (INIS)

    Ueki, Taro; Brown, Forrest B.; Parsons, D. Kent; Warsa, James S.

    2004-01-01

    In the nuclear engineering community, the error propagation of the Monte Carlo fission source distribution through cycles is known to be a linear Markov process when the number of histories per cycle is sufficiently large. In the statistics community, linear Markov processes with linear observation functions are known to have an autoregressive moving average (ARMA) representation of orders p and p - 1. Therefore, one can perform ARMA fitting of the binned Monte Carlo fission source in order to compute physical and statistical quantities relevant to nuclear criticality analysis. In this work, the ARMA fitting of a binary Monte Carlo fission source has been successfully developed as a method to compute the dominance ratio, i.e., the ratio of the second-largest to the largest eigenvalues. The method is free of binning mesh refinement and does not require the alteration of the basic source iteration cycle algorithm. Numerical results are presented for problems with one-group isotropic, two-group linearly anisotropic, and continuous-energy cross sections. Also, a strategy for the analysis of eigenmodes higher than the second-largest eigenvalue is demonstrated numerically

  1. Progress on RMC: a Monte Carlo neutron transport code for reactor analysis

    International Nuclear Information System (INIS)

    Wang, Kan; Li, Zeguang; She, Ding; Liu, Yuxuan; Xu, Qi; Shen, Huayun; Yu, Ganglin

    2011-01-01

    This paper presents a new 3-D Monte Carlo neutron transport code named RMC (Reactor Monte Carlo code), specifically intended for reactor physics analysis. This code is being developed by Department of Engineering Physics in Tsinghua University and written in C++ and Fortran 90 language with the latest version of RMC 2.5.0. The RMC code uses the method known as the delta-tracking method to simulate neutron transport, the advantages of which include fast simulation in complex geometries and relatively simple handling of complicated geometrical objects. Some other techniques such as computational-expense oriented method and hash-table method have been developed and implemented in RMC to speedup the calculation. To meet the requirements of reactor analysis, the RMC code has the calculational functions including criticality calculation, burnup calculation and also kinetics simulation. In this paper, comparison calculations of criticality problems, burnup problems and transient problems are carried out using RMC code and other Monte Carlo codes, and the results show that RMC performs quite well in these kinds of problems. Based on MPI, RMC succeeds in parallel computation and represents a high speed-up. This code is still under intensive development and the further work directions are mentioned at the end of this paper. (author)

  2. Sensitivity of low energy brachytherapy Monte Carlo dose calculations to uncertainties in human tissue composition

    Energy Technology Data Exchange (ETDEWEB)

    Landry, Guillaume; Reniers, Brigitte; Murrer, Lars; Lutgens, Ludy; Bloemen-Van Gurp, Esther; Pignol, Jean-Philippe; Keller, Brian; Beaulieu, Luc; Verhaegen, Frank [Department of Radiation Oncology (MAASTRO), GROW-School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht 6201 BN (Netherlands); Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario M4N 3M5 (Canada); Departement de Radio-Oncologie et Centre de Recherche en Cancerologie, de l' Universite Laval, CHUQ, Pavillon L' Hotel-Dieu de Quebec, Quebec G1R 2J6 (Canada) and Departement de Physique, de Genie Physique et d' Optique, Universite Laval, Quebec G1K 7P4 (Canada); Department of Radiation Oncology (MAASTRO), GROW-School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht 6201 BN (Netherlands) and Medical Physics Unit, McGill University, Montreal General Hospital, Montreal, Quebec H3G 1A4 (Canada)

    2010-10-15

    Purpose: The objective of this work is to assess the sensitivity of Monte Carlo (MC) dose calculations to uncertainties in human tissue composition for a range of low photon energy brachytherapy sources: {sup 125}I, {sup 103}Pd, {sup 131}Cs, and an electronic brachytherapy source (EBS). The low energy photons emitted by these sources make the dosimetry sensitive to variations in tissue atomic number due to the dominance of the photoelectric effect. This work reports dose to a small mass of water in medium D{sub w,m} as opposed to dose to a small mass of medium in medium D{sub m,m}. Methods: Mean adipose, mammary gland, and breast tissues (as uniform mixture of the aforementioned tissues) are investigated as well as compositions corresponding to one standard deviation from the mean. Prostate mean compositions from three different literature sources are also investigated. Three sets of MC simulations are performed with the GEANT4 code: (1) Dose calculations for idealized TG-43-like spherical geometries using point sources. Radial dose profiles obtained in different media are compared to assess the influence of compositional uncertainties. (2) Dose calculations for four clinical prostate LDR brachytherapy permanent seed implants using {sup 125}I seeds (Model 2301, Best Medical, Springfield, VA). The effect of varying the prostate composition in the planning target volume (PTV) is investigated by comparing PTV D{sub 90} values. (3) Dose calculations for four clinical breast LDR brachytherapy permanent seed implants using {sup 103}Pd seeds (Model 2335, Best Medical). The effects of varying the adipose/gland ratio in the PTV and of varying the elemental composition of adipose and gland within one standard deviation of the assumed mean composition are investigated by comparing PTV D{sub 90} values. For (2) and (3), the influence of using the mass density from CT scans instead of unit mass density is also assessed. Results: Results from simulation (1) show that variations

  3. Extensions of the MCNP5 and TRIPOLI4 Monte Carlo codes for transient reactor analysis

    International Nuclear Information System (INIS)

    Hoogenboom, J.E.

    2013-01-01

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

  4. Analysis of subgrid scale mixing using a hybrid LES-Monte-Carlo PDF method

    International Nuclear Information System (INIS)

    Olbricht, C.; Hahn, F.; Sadiki, A.; Janicka, J.

    2007-01-01

    This contribution introduces a hybrid LES-Monte-Carlo method for a coupled solution of the flow and the multi-dimensional scalar joint pdf in two complex mixing devices. For this purpose an Eulerian Monte-Carlo method is used. First, a complex mixing device (jet-in-crossflow, JIC) is presented in which the stochastic convergence and the coherency between the scalar field solution obtained via finite-volume methods and that from the stochastic solution of the pdf for the hybrid method are evaluated. Results are compared to experimental data. Secondly, an extensive investigation of the micromixing on the basis of assumed shape and transported SGS-pdfs in a configuration with practical relevance is carried out. This consists of a mixing chamber with two opposite rows of jets penetrating a crossflow (multi-jet-in-crossflow, MJIC). Some numerical results are compared to available experimental data and to RANS based results. It turns out that the hybrid LES-Monte-Carlo method could achieve a detailed analysis of the mixing at the subgrid level

  5. Reliability analysis of PWR thermohydraulic design by the Monte Carlo method

    International Nuclear Information System (INIS)

    Silva Junior, H.C. da; Berthoud, J.S.; Carajilescov, P.

    1977-01-01

    The operating power level of a PWR is limited by the occurence of DNB. Without affecting the safety and performance of the reactor, it is possible to admit failure of a certain number of core channels. The thermohydraulic design, however, is affect by a great number of uncertainties of deterministic or statistical nature. In the present work, the Monte Carlo method is applied to yield the probability that a number F of channels submitted to boiling crises will not exceed a number F* previously given. This probability is obtained as function of the reactor power level. (Author) [pt

  6. Research on perturbation based Monte Carlo reactor criticality search

    International Nuclear Information System (INIS)

    Li Zeguang; Wang Kan; Li Yangliu; Deng Jingkang

    2013-01-01

    Criticality search is a very important aspect in reactor physics analysis. Due to the advantages of Monte Carlo method and the development of computer technologies, Monte Carlo criticality search is becoming more and more necessary and feasible. Traditional Monte Carlo criticality search method is suffered from large amount of individual criticality runs and uncertainty and fluctuation of Monte Carlo results. A new Monte Carlo criticality search method based on perturbation calculation is put forward in this paper to overcome the disadvantages of traditional method. By using only one criticality run to get initial k_e_f_f and differential coefficients of concerned parameter, the polynomial estimator of k_e_f_f changing function is solved to get the critical value of concerned parameter. The feasibility of this method was tested. The results show that the accuracy and efficiency of perturbation based criticality search method are quite inspiring and the method overcomes the disadvantages of traditional one. (authors)

  7. Application of Monte Carlo Method for Evaluation of Uncertainties of ITS-90 by Standard Platinum Resistance Thermometer

    Science.gov (United States)

    Palenčár, Rudolf; Sopkuliak, Peter; Palenčár, Jakub; Ďuriš, Stanislav; Suroviak, Emil; Halaj, Martin

    2017-06-01

    Evaluation of uncertainties of the temperature measurement by standard platinum resistance thermometer calibrated at the defining fixed points according to ITS-90 is a problem that can be solved in different ways. The paper presents a procedure based on the propagation of distributions using the Monte Carlo method. The procedure employs generation of pseudo-random numbers for the input variables of resistances at the defining fixed points, supposing the multivariate Gaussian distribution for input quantities. This allows taking into account the correlations among resistances at the defining fixed points. Assumption of Gaussian probability density function is acceptable, with respect to the several sources of uncertainties of resistances. In the case of uncorrelated resistances at the defining fixed points, the method is applicable to any probability density function. Validation of the law of propagation of uncertainty using the Monte Carlo method is presented on the example of specific data for 25 Ω standard platinum resistance thermometer in the temperature range from 0 to 660 °C. Using this example, we demonstrate suitability of the method by validation of its results.

  8. A Monte Carlo based spent fuel analysis safeguards strategy assessment

    International Nuclear Information System (INIS)

    Fensin, Michael L.; Tobin, Stephen J.; Swinhoe, Martyn T.; Menlove, Howard O.; Sandoval, Nathan P.

    2009-01-01

    assessment process, the techniques employed to automate the coupled facets of the assessment process, and the standard burnup/enrichment/cooling time dependent spent fuel assembly library. We also clearly define the diversion scenarios that will be analyzed during the standardized assessments. Though this study is currently limited to generic PWR assemblies, it is expected that the results of the assessment will yield an adequate spent fuel analysis strategy knowledge that will help the down-select process for other reactor types

  9. A Monte Carlo Based Spent Fuel Analysis Safeguards Strategy Assessment

    Energy Technology Data Exchange (ETDEWEB)

    Fensin, Michael L.; Tobin, Stephen J.; Swinhoe, Martyn T.; Menlove, Howard O.; Sandoval, Nathan P. [Los Alamos National Laboratory, E540, Los Alamos, NM 87545 (United States)

    2009-06-15

    the generalized assessment process, the techniques employed to automate the coupled facets of the assessment process, and the standard burnup/enrichment/cooling time dependent spent fuel assembly library. We also clearly define the diversion scenarios that will be analyzed during the standardized assessments. Though this study is currently limited to generic PWR assemblies, it is expected that the results of the assessment will yield an adequate spent fuel analysis strategy knowledge that will help the down-select process for other reactor types. (authors)

  10. A Bayesian analysis of rare B decays with advanced Monte Carlo methods

    International Nuclear Information System (INIS)

    Beaujean, Frederik

    2012-01-01

    Searching for new physics in rare B meson decays governed by b → s transitions, we perform a model-independent global fit of the short-distance couplings C 7 , C 9 , and C 10 of the ΔB=1 effective field theory. We assume the standard-model set of b → sγ and b → sl + l - operators with real-valued C i . A total of 59 measurements by the experiments BaBar, Belle, CDF, CLEO, and LHCb of observables in B→K * γ, B→K (*) l + l - , and B s →μ + μ - decays are used in the fit. Our analysis is the first of its kind to harness the full power of the Bayesian approach to probability theory. All main sources of theory uncertainty explicitly enter the fit in the form of nuisance parameters. We make optimal use of the experimental information to simultaneously constrain theWilson coefficients as well as hadronic form factors - the dominant theory uncertainty. Generating samples from the posterior probability distribution to compute marginal distributions and predict observables by uncertainty propagation is a formidable numerical challenge for two reasons. First, the posterior has multiple well separated maxima and degeneracies. Second, the computation of the theory predictions is very time consuming. A single posterior evaluation requires O(1s), and a few million evaluations are needed. Population Monte Carlo (PMC) provides a solution to both issues; a mixture density is iteratively adapted to the posterior, and samples are drawn in a massively parallel way using importance sampling. The major shortcoming of PMC is the need for cogent knowledge of the posterior at the initial stage. In an effort towards a general black-box Monte Carlo sampling algorithm, we present a new method to extract the necessary information in a reliable and automatic manner from Markov chains with the help of hierarchical clustering. Exploiting the latest 2012 measurements, the fit reveals a flipped-sign solution in addition to a standard-model-like solution for the couplings C i . The

  11. A Bayesian analysis of rare B decays with advanced Monte Carlo methods

    Energy Technology Data Exchange (ETDEWEB)

    Beaujean, Frederik

    2012-11-12

    Searching for new physics in rare B meson decays governed by b {yields} s transitions, we perform a model-independent global fit of the short-distance couplings C{sub 7}, C{sub 9}, and C{sub 10} of the {Delta}B=1 effective field theory. We assume the standard-model set of b {yields} s{gamma} and b {yields} sl{sup +}l{sup -} operators with real-valued C{sub i}. A total of 59 measurements by the experiments BaBar, Belle, CDF, CLEO, and LHCb of observables in B{yields}K{sup *}{gamma}, B{yields}K{sup (*)}l{sup +}l{sup -}, and B{sub s}{yields}{mu}{sup +}{mu}{sup -} decays are used in the fit. Our analysis is the first of its kind to harness the full power of the Bayesian approach to probability theory. All main sources of theory uncertainty explicitly enter the fit in the form of nuisance parameters. We make optimal use of the experimental information to simultaneously constrain theWilson coefficients as well as hadronic form factors - the dominant theory uncertainty. Generating samples from the posterior probability distribution to compute marginal distributions and predict observables by uncertainty propagation is a formidable numerical challenge for two reasons. First, the posterior has multiple well separated maxima and degeneracies. Second, the computation of the theory predictions is very time consuming. A single posterior evaluation requires O(1s), and a few million evaluations are needed. Population Monte Carlo (PMC) provides a solution to both issues; a mixture density is iteratively adapted to the posterior, and samples are drawn in a massively parallel way using importance sampling. The major shortcoming of PMC is the need for cogent knowledge of the posterior at the initial stage. In an effort towards a general black-box Monte Carlo sampling algorithm, we present a new method to extract the necessary information in a reliable and automatic manner from Markov chains with the help of hierarchical clustering. Exploiting the latest 2012 measurements, the fit

  12. Validation of uncertainty of weighing in the preparation of radionuclide standards by Monte Carlo Method; Validacao da incerteza de pesagens no preparo de padroes de radionuclideos por Metodo de Monte Carlo

    Energy Technology Data Exchange (ETDEWEB)

    Cacais, F.L.; Delgado, J.U., E-mail: facacais@gmail.com [Instituto de Radioprotecao e Dosimetria (IRD/CNEN-RJ), Rio de Janeiro, RJ (Brazil); Loayza, V.M. [Instituto Nacional de Metrologia (INMETRO), Rio de Janeiro, RJ (Brazil). Qualidade e Tecnologia

    2016-07-01

    In preparing solutions for the production of radionuclide metrology standards is necessary measuring the quantity Activity by mass. The gravimetric method by elimination is applied to perform weighing with smaller uncertainties. At this work is carried out the validation, by the Monte Carlo method, of the uncertainty calculation approach implemented by Lourenco and Bobin according to ISO GUM for the method by elimination. The results obtained by both uncertainty calculation methods were consistent indicating that were fulfilled the conditions for the application of ISO GUM in the preparation of radioactive standards. (author)

  13. Application of a Monte Carlo framework with bootstrapping for quantification of uncertainty in baseline map of carbon emissions from deforestation in Tropical Regions

    Science.gov (United States)

    William Salas; Steve Hagen

    2013-01-01

    This presentation will provide an overview of an approach for quantifying uncertainty in spatial estimates of carbon emission from land use change. We generate uncertainty bounds around our final emissions estimate using a randomized, Monte Carlo (MC)-style sampling technique. This approach allows us to combine uncertainty from different sources without making...

  14. Monte Carlo Analysis of Reservoir Models Using Seismic Data and Geostatistical Models

    Science.gov (United States)

    Zunino, A.; Mosegaard, K.; Lange, K.; Melnikova, Y.; Hansen, T. M.

    2013-12-01

    We present a study on the analysis of petroleum reservoir models consistent with seismic data and geostatistical constraints performed on a synthetic reservoir model. Our aim is to invert directly for structure and rock bulk properties of the target reservoir zone. To infer the rock facies, porosity and oil saturation seismology alone is not sufficient but a rock physics model must be taken into account, which links the unknown properties to the elastic parameters. We then combine a rock physics model with a simple convolutional approach for seismic waves to invert the "measured" seismograms. To solve this inverse problem, we employ a Markov chain Monte Carlo (MCMC) method, because it offers the possibility to handle non-linearity, complex and multi-step forward models and provides realistic estimates of uncertainties. However, for large data sets the MCMC method may be impractical because of a very high computational demand. To face this challenge one strategy is to feed the algorithm with realistic models, hence relying on proper prior information. To address this problem, we utilize an algorithm drawn from geostatistics to generate geologically plausible models which represent samples of the prior distribution. The geostatistical algorithm learns the multiple-point statistics from prototype models (in the form of training images), then generates thousands of different models which are accepted or rejected by a Metropolis sampler. To further reduce the computation time we parallelize the software and run it on multi-core machines. The solution of the inverse problem is then represented by a collection of reservoir models in terms of facies, porosity and oil saturation, which constitute samples of the posterior distribution. We are finally able to produce probability maps of the properties we are interested in by performing statistical analysis on the collection of solutions.

  15. Monte Carlo simulation applied to order economic analysis Simulação de Monte Carlo aplicada à análise econômica de pedido

    Directory of Open Access Journals (Sweden)

    Abraão Freires Saraiva Júnior

    2011-03-01

    Full Text Available The use of mathematical and statistical methods can help managers to deal with decision-making difficulties in the business environment. Some of these decisions are related to productive capacity optimization in order to obtain greater economic gains for the company. Within this perspective, this study aims to present the establishment of metrics to support economic decisions related to process or not orders in a company whose products have great variability in variable direct costs per unit that generates accounting uncertainties. To achieve this objective, is proposed a five-step method built from the integration of Management Accounting and Operations Research techniques, emphasizing the Monte Carlo simulation. The method is applied from a didactic example which uses real data achieved through a field research carried out in a plastic products industry that employ recycled material. Finally, it is concluded that the Monte Carlo simulation is effective for treating variable direct costs per unit variability and that the proposed method is useful to support decision-making related to order acceptance.A utilização de métodos matemáticos e estatísticos pode auxiliar gestores a lidar com dificuldades do processo de tomada de decisão no ambiente de negócios. Algumas dessas decisões estão relacionadas à otimização da utilização da capacidade produtiva visando a obtenção de melhores resultados econômicos para a empresa. Dentro dessa perspectiva, o presente trabalho objetiva apresentar o estabelecimento de métricas que deem suporte à decisão econômica de atender ou não a pedidos em uma empresa cujos produtos têm grande variabilidade de custos variáveis diretos unitários que gera incertezas contábeis. Para cumprir esse objetivo, é proposto um método em cinco etapas, construído a partir da integração de técnicas provindas da contabilidade gerencial e da pesquisa operacional, com destaque à simulação de Monte Carlo. O m

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

    Science.gov (United States)

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

    2010-08-01

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

  17. Monte-Carlo Analysis of the Flavour Changing Neutral Current B \\to Gamma at Babar

    Energy Technology Data Exchange (ETDEWEB)

    Smith, D. [Imperial College, London (United Kingdom)

    2001-09-01

    The main theme of this thesis is a Monte-Carlo analysis of the rare Flavour Changing Neutral Current (FCNC) decay b→sγ. The analysis develops techniques that could be applied to real data, to discriminate between signal and background events in order to make a measurement of the branching ratio of this rare decay using the BaBar detector. Also included in this thesis is a description of the BaBar detector and the work I have undertaken in the development of the electronic data acquisition system for the Electromagnetic calorimeter (EMC), a subsystem of the BaBar detector.

  18. Analysis of communication costs for domain decomposed Monte Carlo methods in nuclear reactor analysis

    International Nuclear Information System (INIS)

    Siegel, A.; Smith, K.; Fischer, P.; Mahadevan, V.

    2012-01-01

    A domain decomposed Monte Carlo communication kernel is used to carry out performance tests to establish the feasibility of using Monte Carlo techniques for practical Light Water Reactor (LWR) core analyses. The results of the prototype code are interpreted in the context of simplified performance models which elucidate key scaling regimes of the parallel algorithm.

  19. Model Reduction via Principe Component Analysis and Markov Chain Monte Carlo (MCMC) Methods

    Science.gov (United States)

    Gong, R.; Chen, J.; Hoversten, M. G.; Luo, J.

    2011-12-01

    Geophysical and hydrogeological inverse problems often include a large number of unknown parameters, ranging from hundreds to millions, depending on parameterization and problems undertaking. This makes inverse estimation and uncertainty quantification very challenging, especially for those problems in two- or three-dimensional spatial domains. Model reduction technique has the potential of mitigating the curse of dimensionality by reducing total numbers of unknowns while describing the complex subsurface systems adequately. In this study, we explore the use of principal component analysis (PCA) and Markov chain Monte Carlo (MCMC) sampling methods for model reduction through the use of synthetic datasets. We compare the performances of three different but closely related model reduction approaches: (1) PCA methods with geometric sampling (referred to as 'Method 1'), (2) PCA methods with MCMC sampling (referred to as 'Method 2'), and (3) PCA methods with MCMC sampling and inclusion of random effects (referred to as 'Method 3'). We consider a simple convolution model with five unknown parameters as our goal is to understand and visualize the advantages and disadvantages of each method by comparing their inversion results with the corresponding analytical solutions. We generated synthetic data with noise added and invert them under two different situations: (1) the noised data and the covariance matrix for PCA analysis are consistent (referred to as the unbiased case), and (2) the noise data and the covariance matrix are inconsistent (referred to as biased case). In the unbiased case, comparison between the analytical solutions and the inversion results show that all three methods provide good estimates of the true values and Method 1 is computationally more efficient. In terms of uncertainty quantification, Method 1 performs poorly because of relatively small number of samples obtained, Method 2 performs best, and Method 3 overestimates uncertainty due to inclusion

  20. Binocular optical axis parallelism detection precision analysis based on Monte Carlo method

    Science.gov (United States)

    Ying, Jiaju; Liu, Bingqi

    2018-02-01

    According to the working principle of the binocular photoelectric instrument optical axis parallelism digital calibration instrument, and in view of all components of the instrument, the various factors affect the system precision is analyzed, and then precision analysis model is established. Based on the error distribution, Monte Carlo method is used to analyze the relationship between the comprehensive error and the change of the center coordinate of the circle target image. The method can further guide the error distribution, optimize control the factors which have greater influence on the comprehensive error, and improve the measurement accuracy of the optical axis parallelism digital calibration instrument.

  1. MKENO-DAR: a direct angular representation Monte Carlo code for criticality safety analysis

    International Nuclear Information System (INIS)

    Naito, Yoshitaka; Komuro, Yuichi; Tsunoo, Yukiyasu; Nakayama, Mitsuo.

    1984-03-01

    Improving the Monte Carlo code MULTI-KENO, the MKENO-DAR (Direct Angular Representation) code has been developed for criticality safety analysis in detail. A function was added to MULTI-KENO for representing anisotropic scattering strictly. With this function, the scattering angle of neutron is determined not by the average scattering angle μ-bar of the Pl Legendre polynomial but by the random work operation using probability distribution function produced with the higher order Legendre polynomials. This code is avilable for the FACOM-M380 computer. This report is a computer code manual for MKENO-DAR. (author)

  2. FTREE. Single-history Monte Carlo analysis for radiation detection and measurement

    International Nuclear Information System (INIS)

    Chin, M.P.W.

    2015-01-01

    This work introduces FTREE, which describes radiation cascades following impingement of a source particle on matter. The ensuing radiation field is characterised interaction by interaction, accounting for each generation of secondaries recursively. Each progeny is uniquely differentiated and catalogued into a family tree; the kinship is identified without ambiguity. This mode of observation, analysis and presentation goes beyond present-day detector technologies, beyond conventional Monte Carlo simulations and beyond standard pedagogy. It is able to observe rare events far out in the Gaussian tail which would have been lost in averaging-events less probable, but no less correct in physics. (author)

  3. Total Monte-Carlo method applied to the assessment of uncertainties in a reactivity-initiated accident

    Energy Technology Data Exchange (ETDEWEB)

    Cruz, D.F. da; Rochman, D.; Koning, A.J. [Nuclear Research and Consultancy Group NRG, Petten (Netherlands)

    2014-07-01

    The Total Monte-Carlo (TMC) method has been applied extensively since 2008 to propagate the uncertainties in nuclear data for reactor parameters and fuel inventory, and for several types of advanced nuclear systems. The analyses have been performed considering different levels of complexity, ranging from a single fuel rod to a full 3-D reactor core at steady-state. The current work applies the TMC method for a full 3-D pressurized water reactor core model under steady-state and transient conditions, considering thermal-hydraulic feedback. As a transient scenario the study focused on a reactivity-initiated accident, namely a control rod ejection accident initiated by a mechanical failure of the control rod drive mechanism. The uncertainties on the main reactor parameters due to variations in nuclear data for the isotopes {sup 235},{sup 238}U, {sup 239}Pu and thermal scattering data for {sup 1}H in water were quantified. (author)

  4. Application of Monte Carlo filtering method in regional sensitivity analysis of AASHTOWare Pavement ME design

    Directory of Open Access Journals (Sweden)

    Zhong Wu

    2017-04-01

    Full Text Available Since AASHTO released the Mechanistic-Empirical Pavement Design Guide (MEPDG for public review in 2004, many highway research agencies have performed sensitivity analyses using the prototype MEPDG design software. The information provided by the sensitivity analysis is essential for design engineers to better understand the MEPDG design models and to identify important input parameters for pavement design. In literature, different studies have been carried out based on either local or global sensitivity analysis methods, and sensitivity indices have been proposed for ranking the importance of the input parameters. In this paper, a regional sensitivity analysis method, Monte Carlo filtering (MCF, is presented. The MCF method maintains many advantages of the global sensitivity analysis, while focusing on the regional sensitivity of the MEPDG model near the design criteria rather than the entire problem domain. It is shown that the information obtained from the MCF method is more helpful and accurate in guiding design engineers in pavement design practices. To demonstrate the proposed regional sensitivity method, a typical three-layer flexible pavement structure was analyzed at input level 3. A detailed procedure to generate Monte Carlo runs using the AASHTOWare Pavement ME Design software was provided. The results in the example show that the sensitivity ranking of the input parameters in this study reasonably matches with that in a previous study under a global sensitivity analysis. Based on the analysis results, the strengths, practical issues, and applications of the MCF method were further discussed.

  5. The Cherenkov Telescope Array production system for Monte Carlo simulations and analysis

    Science.gov (United States)

    Arrabito, L.; Bernloehr, K.; Bregeon, J.; Cumani, P.; Hassan, T.; Haupt, A.; Maier, G.; Moralejo, A.; Neyroud, N.; pre="for the"> CTA Consortium, DIRAC Consortium,

    2017-10-01

    The Cherenkov Telescope Array (CTA), an array of many tens of Imaging Atmospheric Cherenkov Telescopes deployed on an unprecedented scale, is the next-generation instrument in the field of very high energy gamma-ray astronomy. An average data stream of about 0.9 GB/s for about 1300 hours of observation per year is expected, therefore resulting in 4 PB of raw data per year and a total of 27 PB/year, including archive and data processing. The start of CTA operation is foreseen in 2018 and it will last about 30 years. The installation of the first telescopes in the two selected locations (Paranal, Chile and La Palma, Spain) will start in 2017. In order to select the best site candidate to host CTA telescopes (in the Northern and in the Southern hemispheres), massive Monte Carlo simulations have been performed since 2012. Once the two sites have been selected, we have started new Monte Carlo simulations to determine the optimal array layout with respect to the obtained sensitivity. Taking into account that CTA may be finally composed of 7 different telescope types coming in 3 different sizes, many different combinations of telescope position and multiplicity as a function of the telescope type have been proposed. This last Monte Carlo campaign represented a huge computational effort, since several hundreds of telescope positions have been simulated, while for future instrument response function simulations, only the operating telescopes will be considered. In particular, during the last 18 months, about 2 PB of Monte Carlo data have been produced and processed with different analysis chains, with a corresponding overall CPU consumption of about 125 M HS06 hours. In these proceedings, we describe the employed computing model, based on the use of grid resources, as well as the production system setup, which relies on the DIRAC interware. Finally, we present the envisaged evolutions of the CTA production system for the off-line data processing during CTA operations and

  6. Assessment of bioethanol yield by S. cerevisiae grown on oil palm residues: Monte Carlo simulation and sensitivity analysis.

    Science.gov (United States)

    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. Neutronic Analysis of the 3 MW TRIGA MARK II Research Reactor, Part I: Monte Carlo Simulation

    International Nuclear Information System (INIS)

    Huda, M.Q.; Chakrobortty, T.K.; Rahman, M.; Sarker, M.M.; Mahmood, M.S.

    2003-05-01

    This study deals with the neutronic analysis of the current core configuration of a 3 MW TRIGA MARK II research reactor at Atomic Energy Research Establishment (AERE), Savar, Dhaka, Bangladesh and validation of the results by benchmarking with the experimental, operational and available Final Safety Analysis Report (FSAR) values. The three-dimensional continuous-energy Monte Carlo code MCNP4C was used to develop a versatile and accurate full-core model of the TRIGA core. The model represents in detail all components of the core with literally no physical approximation. All fresh fuel and control elements as well as the vicinity of the core were precisely described. Continuous energy cross-section data from ENDF/B-VI and S(α, β) scattering functions from the ENDF/B-V library were used. The validation of the model against benchmark experimental results is presented. The MCNP predictions and the experimentally determined values are found to be in very good agreement, which indicates that the Monte Carlo model is correctly simulating the TRIGA reactor. (author)

  8. Implementation of the dynamic Monte Carlo method for transient analysis in the general purpose code Tripoli

    Energy Technology Data Exchange (ETDEWEB)

    Sjenitzer, Bart L.; Hoogenboom, J. Eduard, E-mail: B.L.Sjenitzer@TUDelft.nl, E-mail: J.E.Hoogenboom@TUDelft.nl [Delft University of Technology (Netherlands)

    2011-07-01

    A new Dynamic Monte Carlo method is implemented in the general purpose Monte Carlo code Tripoli 4.6.1. With this new method incorporated, a general purpose code can be used for safety transient analysis, such as the movement of a control rod or in an accident scenario. To make the Tripoli code ready for calculating on dynamic systems, the Tripoli scheme had to be altered to incorporate time steps, to include the simulation of delayed neutron precursors and to simulate prompt neutron chains. The modified Tripoli code is tested on two sample cases, a steady-state system and a subcritical system and the resulting neutron fluxes behave just as expected. The steady-state calculation has a constant neutron flux over time and this result shows the stability of the calculation. The neutron flux stays constant with acceptable variance. This also shows that the starting conditions are determined correctly. The sub-critical case shows that the code can also handle dynamic systems with a varying neutron flux. (author)

  9. Implementation of the dynamic Monte Carlo method for transient analysis in the general purpose code Tripoli

    International Nuclear Information System (INIS)

    Sjenitzer, Bart L.; Hoogenboom, J. Eduard

    2011-01-01

    A new Dynamic Monte Carlo method is implemented in the general purpose Monte Carlo code Tripoli 4.6.1. With this new method incorporated, a general purpose code can be used for safety transient analysis, such as the movement of a control rod or in an accident scenario. To make the Tripoli code ready for calculating on dynamic systems, the Tripoli scheme had to be altered to incorporate time steps, to include the simulation of delayed neutron precursors and to simulate prompt neutron chains. The modified Tripoli code is tested on two sample cases, a steady-state system and a subcritical system and the resulting neutron fluxes behave just as expected. The steady-state calculation has a constant neutron flux over time and this result shows the stability of the calculation. The neutron flux stays constant with acceptable variance. This also shows that the starting conditions are determined correctly. The sub-critical case shows that the code can also handle dynamic systems with a varying neutron flux. (author)

  10. Current and future applications of Monte Carlo

    International Nuclear Information System (INIS)

    Zaidi, H.

    2003-01-01

    Full text: The use of radionuclides in medicine has a long history and encompasses a large area of applications including diagnosis and radiation treatment of cancer patients using either external or radionuclide radiotherapy. The 'Monte Carlo method'describes a very broad area of science, in which many processes, physical systems, and phenomena are simulated by statistical methods employing random numbers. The general idea of Monte Carlo analysis is to create a model, which is as similar as possible to the real physical system of interest, and to create interactions within that system based on known probabilities of occurrence, with random sampling of the probability density functions (pdfs). As the number of individual events (called 'histories') is increased, the quality of the reported average behavior of the system improves, meaning that the statistical uncertainty decreases. The use of the Monte Carlo method to simulate radiation transport has become the most accurate means of predicting absorbed dose distributions and other quantities of interest in the radiation treatment of cancer patients using either external or radionuclide radiotherapy. The same trend has occurred for the estimation of the absorbed dose in diagnostic procedures using radionuclides as well as the assessment of image quality and quantitative accuracy of radionuclide imaging. As a consequence of this generalized use, many questions are being raised primarily about the need and potential of Monte Carlo techniques, but also about how accurate it really is, what would it take to apply it clinically and make it available widely to the nuclear medicine community at large. Many of these questions will be answered when Monte Carlo techniques are implemented and used for more routine calculations and for in-depth investigations. In this paper, the conceptual role of the Monte Carlo method is briefly introduced and followed by a survey of its different applications in diagnostic and therapeutic

  11. Comparison of the GUM and Monte Carlo methods on the flatness uncertainty estimation in coordinate measuring machine

    Directory of Open Access Journals (Sweden)

    Jalid Abdelilah

    2016-01-01

    Full Text Available In engineering industry, control of manufactured parts is usually done on a coordinate measuring machine (CMM, a sensor mounted at the end of the machine probes a set of points on the surface to be inspected. Data processing is performed subsequently using software, and the result of this measurement process either validates or not the conformity of the part. Measurement uncertainty is a crucial parameter for making the right decisions, and not taking into account this parameter can, therefore, sometimes lead to aberrant decisions. The determination of the uncertainty measurement on CMM is a complex task for the variety of influencing factors. Through this study, we aim to check if the uncertainty propagation model developed according to the guide to the expression of uncertainty in measurement (GUM approach is valid, we present here a comparison of the GUM and Monte Carlo methods. This comparison is made to estimate a flatness deviation of a surface belonging to an industrial part and the uncertainty associated to the measurement result.

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

    Science.gov (United States)

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

    2017-01-01

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

  13. Monte Carlo analysis of an ODE Model of the Sea Urchin Endomesoderm Network

    Directory of Open Access Journals (Sweden)

    Klipp Edda

    2009-08-01

    Full Text Available Abstract Background Gene Regulatory Networks (GRNs control the differentiation, specification and function of cells at the genomic level. The levels of interactions within large GRNs are of enormous depth and complexity. Details about many GRNs are emerging, but in most cases it is unknown to what extent they control a given process, i.e. the grade of completeness is uncertain. This uncertainty stems from limited experimental data, which is the main bottleneck for creating detailed dynamical models of cellular processes. Parameter estimation for each node is often infeasible for very large GRNs. We propose a method, based on random parameter estimations through Monte-Carlo simulations to measure completeness grades of GRNs. Results We developed a heuristic to assess the completeness of large GRNs, using ODE simulations under different conditions and randomly sampled parameter sets to detect parameter-invariant effects of perturbations. To test this heuristic, we constructed the first ODE model of the whole sea urchin endomesoderm GRN, one of the best studied large GRNs. We find that nearly 48% of the parameter-invariant effects correspond with experimental data, which is 65% of the expected optimal agreement obtained from a submodel for which kinetic parameters were estimated and used for simulations. Randomized versions of the model reproduce only 23.5% of the experimental data. Conclusion The method described in this paper enables an evaluation of network topologies of GRNs without requiring any parameter values. The benefit of this method is exemplified in the first mathematical analysis of the complete Endomesoderm Network Model. The predictions we provide deliver candidate nodes in the network that are likely to be erroneous or miss unknown connections, which may need additional experiments to improve the network topology. This mathematical model can serve as a scaffold for detailed and more realistic models. We propose that our method can

  14. Monte Carlo based statistical power analysis for mediation models: methods and software.

    Science.gov (United States)

    Zhang, Zhiyong

    2014-12-01

    The existing literature on statistical power analysis for mediation models often assumes data normality and is based on a less powerful Sobel test instead of the more powerful bootstrap test. This study proposes to estimate statistical power to detect mediation effects on the basis of the bootstrap method through Monte Carlo simulation. Nonnormal data with excessive skewness and kurtosis are allowed in the proposed method. A free R package called bmem is developed to conduct the power analysis discussed in this study. Four examples, including a simple mediation model, a multiple-mediator model with a latent mediator, a multiple-group mediation model, and a longitudinal mediation model, are provided to illustrate the proposed method.

  15. A bottom collider vertex detector design, Monte-Carlo simulation and analysis package

    International Nuclear Information System (INIS)

    Lebrun, P.

    1990-01-01

    A detailed simulation of the BCD vertex detector is underway. Specifications and global design issues are briefly reviewed. The BCD design based on double sided strip detector is described in more detail. The GEANT3-based Monte-Carlo program and the analysis package used to estimate detector performance are discussed in detail. The current status of the expected resolution and signal to noise ratio for the ''golden'' CP violating mode B d → π + π - is presented. These calculations have been done at FNAL energy (√s = 2.0 TeV). Emphasis is placed on design issues, analysis techniques and related software rather than physics potentials. 20 refs., 46 figs

  16. Noninvasive spectral imaging of skin chromophores based on multiple regression analysis aided by Monte Carlo simulation

    Science.gov (United States)

    Nishidate, Izumi; Wiswadarma, Aditya; Hase, Yota; Tanaka, Noriyuki; Maeda, Takaaki; Niizeki, Kyuichi; Aizu, Yoshihisa

    2011-08-01

    In order to visualize melanin and blood concentrations and oxygen saturation in human skin tissue, a simple imaging technique based on multispectral diffuse reflectance images acquired at six wavelengths (500, 520, 540, 560, 580 and 600nm) was developed. The technique utilizes multiple regression analysis aided by Monte Carlo simulation for diffuse reflectance spectra. Using the absorbance spectrum as a response variable and the extinction coefficients of melanin, oxygenated hemoglobin, and deoxygenated hemoglobin as predictor variables, multiple regression analysis provides regression coefficients. Concentrations of melanin and total blood are then determined from the regression coefficients using conversion vectors that are deduced numerically in advance, while oxygen saturation is obtained directly from the regression coefficients. Experiments with a tissue-like agar gel phantom validated the method. In vivo experiments with human skin of the human hand during upper limb occlusion and of the inner forearm exposed to UV irradiation demonstrated the ability of the method to evaluate physiological reactions of human skin tissue.

  17. Usefulness of the Monte Carlo method in reliability calculations

    International Nuclear Information System (INIS)

    Lanore, J.M.; Kalli, H.

    1977-01-01

    Three examples of reliability Monte Carlo programs developed in the LEP (Laboratory for Radiation Shielding Studies in the Nuclear Research Center at Saclay) are presented. First, an uncertainty analysis is given for a simplified spray system; a Monte Carlo program PATREC-MC has been written to solve the problem with the system components given in the fault tree representation. The second program MONARC 2 has been written to solve the problem of complex systems reliability by the Monte Carlo simulation, here again the system (a residual heat removal system) is in the fault tree representation. Third, the Monte Carlo program MONARC was used instead of the Markov diagram to solve the simulation problem of an electric power supply including two nets and two stand-by diesels

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

    Science.gov (United States)

    Arampatzis, Georgios; Katsoulakis, Markos A

    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 the new coupled process depends on the targeted observables, e.g., coverage, Hamiltonian, spatial correlations, surface roughness, etc., hence we refer to the proposed method as goal-oriented sensitivity analysis. In particular, the rates of the coupled Continuous Time Markov Chain are obtained as solutions to a goal-oriented optimization problem, depending on the observable of interest, by considering the minimization functional of the corresponding variance. We show that this functional can be used as a diagnostic tool for the design and evaluation of different classes of couplings. Furthermore, the resulting KMC sensitivity algorithm has an easy implementation that is based on the Bortz-Kalos-Lebowitz algorithm's philosophy, where events are divided in classes depending on level sets of the observable of interest. Finally, we demonstrate in several examples including adsorption, desorption, and diffusion Kinetic Monte Carlo that for the same confidence interval and observable, the proposed goal-oriented algorithm can be two orders of magnitude faster than existing coupling algorithms for spatial KMC such as the Common Random Number approach. We also provide a complete implementation of the proposed sensitivity analysis algorithms, including various spatial KMC examples, in a supplementary MATLAB

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

    International Nuclear Information System (INIS)

    Arampatzis, Georgios; Katsoulakis, Markos A.

    2014-01-01

    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 the new coupled process depends on the targeted observables, e.g., coverage, Hamiltonian, spatial correlations, surface roughness, etc., hence we refer to the proposed method as goal-oriented sensitivity analysis. In particular, the rates of the coupled Continuous Time Markov Chain are obtained as solutions to a goal-oriented optimization problem, depending on the observable of interest, by considering the minimization functional of the corresponding variance. We show that this functional can be used as a diagnostic tool for the design and evaluation of different classes of couplings. Furthermore, the resulting KMC sensitivity algorithm has an easy implementation that is based on the Bortz–Kalos–Lebowitz algorithm's philosophy, where events are divided in classes depending on level sets of the observable of interest. Finally, we demonstrate in several examples including adsorption, desorption, and diffusion Kinetic Monte Carlo that for the same confidence interval and observable, the proposed goal-oriented algorithm can be two orders of magnitude faster than existing coupling algorithms for spatial KMC such as the Common Random Number approach. We also provide a complete implementation of the proposed sensitivity analysis algorithms, including various spatial KMC examples, in a supplementary

  20. Analysis of the design of an X-ray tube using Monte Carlo; Analisis del diseno de un tubo de rayos X mediante Monte Carlo

    Energy Technology Data Exchange (ETDEWEB)

    Pena V, J. D.; Sosa A, M. A.; Ceron, P. V.; Vallejo, M. A. [Universidad de Guanajuato, Division de Ciencias e Ingenierias, Loma del Bosque No. 103, Lomas del Campestre, 37150 Leon, Guanajuato (Mexico); Vega C, H. R., E-mail: jd.penavidal@ugto.mx [Universidad Autonoma de Zacatecas, Unidad Academica de Estudios Nucleares, Cipres No. 10, Fracc. La Penuela, 98060 Zacatecas, Zac. (Mexico)

    2017-10-15

    In this paper we present the Monte Carlo analysis of the X-rays produced by a rotating X-ray tube of the Siemens brand that is used in tomographs for clinical use. The work was done with the MCNP6 code with which the tube was modeled and the primary X-ray spectra produced during the interaction of monoenergetic electrons of 130 keV were calculated. The X-ray spectra were obtained by varying some parameters such as: the angle of the anode (15 to 20 degrees), the type of target (Tungsten, Molybdenum and Rhodium) and the thickness of the filter (3, 5, 10 and 15 mm). In order to have a good statistic 10{sup 7} stories were used. Though the estimators f2 and f5 the X-ray spectra and the total fluencies were estimated. This information will be used to calculate the dose absorbed in the lens and the thyroid gland in patients undergoing radio diagnosis procedures. (Author)

  1. Statistical implications in Monte Carlo depletions - 051

    International Nuclear Information System (INIS)

    Zhiwen, Xu; Rhodes, J.; Smith, K.

    2010-01-01

    As a result of steady advances of computer power, continuous-energy Monte Carlo depletion analysis is attracting considerable attention for reactor burnup calculations. The typical Monte Carlo analysis is set up as a combination of a Monte Carlo neutron transport solver and a fuel burnup solver. Note that the burnup solver is a deterministic module. The statistical errors in Monte Carlo solutions are introduced into nuclide number densities and propagated along fuel burnup. This paper is towards the understanding of the statistical implications in Monte Carlo depletions, including both statistical bias and statistical variations in depleted fuel number densities. The deterministic Studsvik lattice physics code, CASMO-5, is modified to model the Monte Carlo depletion. The statistical bias in depleted number densities is found to be negligible compared to its statistical variations, which, in turn, demonstrates the correctness of the Monte Carlo depletion method. Meanwhile, the statistical variation in number densities generally increases with burnup. Several possible ways of reducing the statistical errors are discussed: 1) to increase the number of individual Monte Carlo histories; 2) to increase the number of time steps; 3) to run additional independent Monte Carlo depletion cases. Finally, a new Monte Carlo depletion methodology, called the batch depletion method, is proposed, which consists of performing a set of independent Monte Carlo depletions and is thus capable of estimating the overall statistical errors including both the local statistical error and the propagated statistical error. (authors)

  2. Monte Carlo Simulation of Complete X-Ray Spectra for Use in Scanning Electron Microscopy Analysis

    International Nuclear Information System (INIS)

    Roet, David; Van Espen, Piet

    2003-01-01

    Full Text: The interactions of keV electrons and photons with matter can be simulated accurately with the aid of the Monte Carlo (MC) technique. In scanning electron microscopy x-ray analysis (SEM-EDX) such simulations can be used to perform quantitative analysis using a Reverse Monte Carlo method even if the samples have irregular geometry. Alternatively the MC technique can generate spectra of standards for use in quantization with partial least squares regression. The feasibility of these alternatives to the more classical ZAF or phi-rho-Z quantification methods has been proven already. In order to be applicable for these purposes the MC-code needs to generate accurately only the characteristic K and L x-ray lines, but also the Bremsstrahlung continuum, i.e. the complete x-ray spectrum need to be simulated. Currently two types of MC simulation codes are available. Programs like Electron Flight Simulator and CASINO simulate characteristic x-rays due to electron interaction in a fast and efficient way but lack provision for the simulation of the continuum. On the other hand, programs like EGS4, MCNP4 and PENELOPE, originally developed for high energy (MeV- GeV) applications, are more complete but difficult to use and still slow, even on todays fastest computers. We therefore started the development of a dedicated MC simulation code for use in quantitative SEM-EDX work. The selection of the most appropriate cross section for the different interactions will be discussed and the results obtained will be compared with those obtained with existing MC programs. Examples of the application of MC simulations for quantitative analysis of samples with various composition will be given

  3. Converting boundary representation solid models to half-space representation models for Monte Carlo analysis

    International Nuclear Information System (INIS)

    Davis, J. E.; Eddy, M. J.; Sutton, T. M.; Altomari, T. J.

    2007-01-01

    Solid modeling computer software systems provide for the design of three-dimensional solid models used in the design and analysis of physical components. The current state-of-the-art in solid modeling representation uses a boundary representation format in which geometry and topology are used to form three-dimensional boundaries of the solid. The geometry representation used in these systems is cubic B-spline curves and surfaces - a network of cubic B-spline functions in three-dimensional Cartesian coordinate space. Many Monte Carlo codes, however, use a geometry representation in which geometry units are specified by intersections and unions of half-spaces. This paper describes an algorithm for converting from a boundary representation to a half-space representation. (authors)

  4. A spectral analysis of the domain decomposed Monte Carlo method for linear systems

    Energy Technology Data Exchange (ETDEWEB)

    Slattery, S. R.; Wilson, P. P. H. [Engineering Physics Department, University of Wisconsin - Madison, 1500 Engineering Dr., Madison, WI 53706 (United States); Evans, T. M. [Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, TN 37830 (United States)

    2013-07-01

    The domain decomposed behavior of the adjoint Neumann-Ulam Monte Carlo method for solving linear systems is analyzed using the spectral properties of the linear operator. Relationships for the average length of the adjoint random walks, a measure of convergence speed and serial performance, are made with respect to the eigenvalues of the linear operator. In addition, relationships for the effective optical thickness of a domain in the decomposition are presented based on the spectral analysis and diffusion theory. Using the effective optical thickness, the Wigner rational approximation and the mean chord approximation are applied to estimate the leakage fraction of stochastic histories from a domain in the decomposition as a measure of parallel performance and potential communication costs. The one-speed, two-dimensional neutron diffusion equation is used as a model problem to test the models for symmetric operators. In general, the derived approximations show good agreement with measured computational results. (authors)

  5. A spectral analysis of the domain decomposed Monte Carlo method for linear systems

    International Nuclear Information System (INIS)

    Slattery, S. R.; Wilson, P. P. H.; Evans, T. M.

    2013-01-01

    The domain decomposed behavior of the adjoint Neumann-Ulam Monte Carlo method for solving linear systems is analyzed using the spectral properties of the linear operator. Relationships for the average length of the adjoint random walks, a measure of convergence speed and serial performance, are made with respect to the eigenvalues of the linear operator. In addition, relationships for the effective optical thickness of a domain in the decomposition are presented based on the spectral analysis and diffusion theory. Using the effective optical thickness, the Wigner rational approximation and the mean chord approximation are applied to estimate the leakage fraction of stochastic histories from a domain in the decomposition as a measure of parallel performance and potential communication costs. The one-speed, two-dimensional neutron diffusion equation is used as a model problem to test the models for symmetric operators. In general, the derived approximations show good agreement with measured computational results. (authors)

  6. Contrast to Noise Ratio and Contrast Detail Analysis in Mammography:A Monte Carlo Study

    International Nuclear Information System (INIS)

    Metaxas, V; Delis, H; Panayiotakis, G; Kalogeropoulou, C; Zampakis, P

    2015-01-01

    The mammographic spectrum is one of the major factors affecting image quality in mammography. In this study, a Monte Carlo (MC) simulation model was used to evaluate image quality characteristics of various mammographic spectra. The anode/filter combinations evaluated, were those traditionally used in mammography, for tube voltages between 26 and 30 kVp. The imaging performance was investigated in terms of Contrast to Noise Ratio (CNR) and Contrast Detail (CD) analysis, by involving human observers, utilizing a mathematical CD phantom. Soft spectra provided the best characteristics in terms of both CNR and CD scores, while tube voltage had a limited effect. W-anode spectra filtered with k-edge filters demonstrated an improved performance, that sometimes was better compared to softer x-ray spectra, produced by Mo or Rh anode. Regarding the filter material, k-edge filters showed superior performance compared to Al filters. (paper)

  7. First Monte Carlo Global Analysis of Nucleon Transversity with Lattice QCD Constraints

    Science.gov (United States)

    Lin, H.-W.; Melnitchouk, W.; Prokudin, A.; Sato, N.; Shows, H.; Jefferson Lab Angular Momentum JAM Collaboration

    2018-04-01

    We report on the first global QCD analysis of the quark transversity distributions in the nucleon from semi-inclusive deep-inelastic scattering (SIDIS), using a new Monte Carlo method based on nested sampling and constraints on the isovector tensor charge gT from lattice QCD. A simultaneous fit to the available SIDIS Collins asymmetry data is compatible with gT values extracted from a comprehensive reanalysis of existing lattice simulations, in contrast to previous analyses, which found significantly smaller gT values. The contributions to the nucleon tensor charge from u and d quarks are found to be δ u =0.3 (2 ) and δ d =-0.7 (2 ) at a scale Q2=2 GeV2.

  8. Generalized likelihood uncertainty estimation (GLUE) using adaptive Markov chain Monte Carlo sampling

    DEFF Research Database (Denmark)

    Blasone, Roberta-Serena; Vrugt, Jasper A.; Madsen, Henrik

    2008-01-01

    propose an alternative strategy to determine the value of the cutoff threshold based on the appropriate coverage of the resulting uncertainty bounds. We demonstrate the superiority of this revised GLUE method with three different conceptual watershed models of increasing complexity, using both synthetic......In the last few decades hydrologists have made tremendous progress in using dynamic simulation models for the analysis and understanding of hydrologic systems. However, predictions with these models are often deterministic and as such they focus on the most probable forecast, without an explicit...... of applications. However, the MC based sampling strategy of the prior parameter space typically utilized in GLUE is not particularly efficient in finding behavioral simulations. This becomes especially problematic for high-dimensional parameter estimation problems, and in the case of complex simulation models...

  9. Analysis of the KANT experiment on beryllium using TRIPOLI-4 Monte Carlo code

    International Nuclear Information System (INIS)

    Lee, Yi-Kang

    2011-01-01

    Beryllium is an important material in fusion technology for multiplying neutrons in blankets. However, beryllium nuclear data are differently presented in modern nuclear data evaluations. Recent investigations with the TRIPOLI-4 Monte Carlo simulation of the tritium breeding ratio (TBR) demonstrated that beryllium reaction data are the main source of the calculation uncertainties between ENDF/B-VII.0 and JEFF-3.1. To clarify the calculation uncertainties from data libraries on beryllium, in this study TRIPOLI-4 calculations of the Karlsruhe Neutron Transmission (KANT) experiment have been performed by using ENDF/B-VII.0 and new JEFF-3.1.1 data libraries. The KANT Experiment on beryllium has been used to validate neutron transport codes and nuclear data libraries. An elaborated KANT experiment benchmark has been compiled and published in the NEA/SINBAD database and it has been used as reference in the present work. The neutron multiplication in bulk beryllium assemblies was considered with a central D-T neutron source. Neutron leakage spectra through the 5, 10, and 17 cm thick spherical beryllium shells were calculated and five-group partial leakage multiplications were reported and discussed. In general, improved C/E ratios on neutron leakage multiplications have been obtained. Both ENDF/B-VII.0 and JEFF-3.1.1 beryllium data libraries of TRIPOLI-4 are acceptable now for fusion neutronics calculations.

  10. Bayesian uncertainty quantification for flows in heterogeneous porous media using reversible jump Markov chain Monte Carlo methods

    KAUST Repository

    Mondal, A.

    2010-03-01

    In this paper, we study the uncertainty quantification in inverse problems for flows in heterogeneous porous media. Reversible jump Markov chain Monte Carlo algorithms (MCMC) are used for hierarchical modeling of channelized permeability fields. Within each channel, the permeability is assumed to have a lognormal distribution. Uncertainty quantification in history matching is carried out hierarchically by constructing geologic facies boundaries as well as permeability fields within each facies using dynamic data such as production data. The search with Metropolis-Hastings algorithm results in very low acceptance rate, and consequently, the computations are CPU demanding. To speed-up the computations, we use a two-stage MCMC that utilizes upscaled models to screen the proposals. In our numerical results, we assume that the channels intersect the wells and the intersection locations are known. Our results show that the proposed algorithms are capable of capturing the channel boundaries and describe the permeability variations within the channels using dynamic production history at the wells. © 2009 Elsevier Ltd. All rights reserved.

  11. Energy planning of a hospital using Mathematical Programming and Monte Carlo simulation for dealing with uncertainty in the economic parameters

    International Nuclear Information System (INIS)

    Mavrotas, George; Florios, Kostas; Vlachou, Dimitra

    2010-01-01

    For more than 40 years, Mathematical Programming is the traditional tool for energy planning at the national or regional level aiming at cost minimization subject to specific technological, political and demand satisfaction constraints. The liberalization of the energy market along with the ongoing technical progress increased the level of competition and forced energy consumers, even at the unit level, to make their choices among a large number of alternative or complementary energy technologies, fuels and/or suppliers. In the present work we develop a modelling framework for energy planning in units of the tertiary sector giving special emphasis to model reduction and to the uncertainty of the economic parameters. In the given case study, the energy rehabilitation of a hospital in Athens is examined and the installation of a cogeneration, absorption and compression unit is examined for the supply of the electricity, heating and cooling load. The basic innovation of the given energy model lies in the uncertainty modelling through the combined use of Mathematical Programming (namely, Mixed Integer Linear Programming, MILP) and Monte Carlo simulation that permits the risk management for the most volatile parameters of the objective function such as the fuel costs and the interest rate. The results come in the form of probability distributions that provide fruitful information to the decision maker. The effect of model reduction through appropriate data compression of the load data is also addressed.

  12. Distribution network design under demand uncertainty using genetic algorithm and Monte Carlo simulation approach: a case study in pharmaceutical industry

    Science.gov (United States)

    Izadi, Arman; Kimiagari, Ali Mohammad

    2014-05-01

    Distribution network design as a strategic decision has long-term effect on tactical and operational supply chain management. In this research, the location-allocation problem is studied under demand uncertainty. The purposes of this study were to specify the optimal number and location of distribution centers and to determine the allocation of customer demands to distribution centers. The main feature of this research is solving the model with unknown demand function which is suitable with the real-world problems. To consider the uncertainty, a set of possible scenarios for customer demands is created based on the Monte Carlo simulation. The coefficient of variation of costs is mentioned as a measure of risk and the most stable structure for firm's distribution network is defined based on the concept of robust optimization. The best structure is identified using genetic algorithms and 14 % reduction in total supply chain costs is the outcome. Moreover, it imposes the least cost variation created by fluctuation in customer demands (such as epidemic diseases outbreak in some areas of the country) to the logistical system. It is noteworthy that this research is done in one of the largest pharmaceutical distribution firms in Iran.

  13. The effect of load imbalances on the performance of Monte Carlo algorithms in LWR analysis

    International Nuclear Information System (INIS)

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

    2013-01-01

    A model is developed to predict the impact of particle load imbalances on the performance of domain-decomposed Monte Carlo neutron transport algorithms. Expressions for upper bound performance “penalties” are derived in terms of simple machine characteristics, material characterizations and initial particle distributions. The hope is that these relations can be used to evaluate tradeoffs among different memory decomposition strategies in next generation Monte Carlo codes, and perhaps as a metric for triggering particle redistribution in production codes

  14. Study of the quantitative analysis approach of maintenance by the Monte Carlo simulation method

    International Nuclear Information System (INIS)

    Shimizu, Takashi

    2007-01-01

    This study is examination of the quantitative valuation by Monte Carlo simulation method of maintenance activities of a nuclear power plant. Therefore, the concept of the quantitative valuation of maintenance that examination was advanced in the Japan Society of Maintenology and International Institute of Universality (IUU) was arranged. Basis examination for quantitative valuation of maintenance was carried out at simple feed water system, by Monte Carlo simulation method. (author)

  15. Uncertainty evaluation of the kerma in the air, related to the active volume in the ionization chamber of concentric cylinders, by Monte Carlo simulation

    International Nuclear Information System (INIS)

    Lo Bianco, A.S.; Oliveira, H.P.S.; Peixoto, J.G.P.

    2009-01-01

    To implant the primary standard of the magnitude kerma in the air for X-ray between 10 - 50 keV, the National Metrology Laboratory of Ionizing Radiations (LNMRI) must evaluate all the uncertainties of measurement related with Victtoren chamber. So, it was evaluated the uncertainty of the kerma in the air consequent of the inaccuracy in the active volume of the chamber using the calculation of Monte Carlo as a tool through the Penelope software

  16. Adjoint electron Monte Carlo calculations

    International Nuclear Information System (INIS)

    Jordan, T.M.

    1986-01-01

    Adjoint Monte Carlo is the most efficient method for accurate analysis of space systems exposed to natural and artificially enhanced electron environments. Recent adjoint calculations for isotropic electron environments include: comparative data for experimental measurements on electronics boxes; benchmark problem solutions for comparing total dose prediction methodologies; preliminary assessment of sectoring methods used during space system design; and total dose predictions on an electronics package. Adjoint Monte Carlo, forward Monte Carlo, and experiment are in excellent agreement for electron sources that simulate space environments. For electron space environments, adjoint Monte Carlo is clearly superior to forward Monte Carlo, requiring one to two orders of magnitude less computer time for relatively simple geometries. The solid-angle sectoring approximations used for routine design calculations can err by more than a factor of 2 on dose in simple shield geometries. For critical space systems exposed to severe electron environments, these potential sectoring errors demand the establishment of large design margins and/or verification of shield design by adjoint Monte Carlo/experiment

  17. Analysis of possibility to apply new mathematical methods (R-function theory) in Monte Carlo simulation of complex geometry

    International Nuclear Information System (INIS)

    Altiparmakov, D.

    1988-12-01

    This analysis is part of the report on ' Implementation of geometry module of 05R code in another Monte Carlo code', chapter 6.0: establishment of future activity related to geometry in Monte Carlo method. The introduction points out some problems in solving complex three-dimensional models which induce the need for developing more efficient geometry modules in Monte Carlo calculations. Second part include formulation of the problem and geometry module. Two fundamental questions to be solved are defined: (1) for a given point, it is necessary to determine material region or boundary where it belongs, and (2) for a given direction, all cross section points with material regions should be determined. Third part deals with possible connection with Monte Carlo calculations for computer simulation of geometry objects. R-function theory enables creation of geometry module base on the same logic (complex regions are constructed by elementary regions sets operations) as well as construction geometry codes. R-functions can efficiently replace functions of three-value logic in all significant models. They are even more appropriate for application since three-value logic is not typical for digital computers which operate in two-value logic. This shows that there is a need for work in this field. It is shown that there is a possibility to develop interactive code for computer modeling of geometry objects in parallel with development of geometry module [sr

  18. Uncertainty in Measurement: A Review of Monte Carlo Simulation Using Microsoft Excel for the Calculation of Uncertainties Through Functional Relationships, Including Uncertainties in Empirically Derived Constants

    Science.gov (United States)

    Farrance, Ian; Frenkel, Robert

    2014-01-01

    The Guide to the Expression of Uncertainty in Measurement (usually referred to as the GUM) provides the basic framework for evaluating uncertainty in measurement. The GUM however does not always provide clearly identifiable procedures suitable for medical laboratory applications, particularly when internal quality control (IQC) is used to derive most of the uncertainty estimates. The GUM modelling approach requires advanced mathematical skills for many of its procedures, but Monte Carlo simulation (MCS) can be used as an alternative for many medical laboratory applications. In particular, calculations for determining how uncertainties in the input quantities to a functional relationship propagate through to the output can be accomplished using a readily available spreadsheet such as Microsoft Excel. The MCS procedure uses algorithmically generated pseudo-random numbers which are then forced to follow a prescribed probability distribution. When IQC data provide the uncertainty estimates the normal (Gaussian) distribution is generally considered appropriate, but MCS is by no means restricted to this particular case. With input variations simulated by random numbers, the functional relationship then provides the corresponding variations in the output in a manner which also provides its probability distribution. The MCS procedure thus provides output uncertainty estimates without the need for the differential equations associated with GUM modelling. The aim of this article is to demonstrate the ease with which Microsoft Excel (or a similar spreadsheet) can be used to provide an uncertainty estimate for measurands derived through a functional relationship. In addition, we also consider the relatively common situation where an empirically derived formula includes one or more ‘constants’, each of which has an empirically derived numerical value. Such empirically derived ‘constants’ must also have associated uncertainties which propagate through the functional

  19. Uncertainty in measurement: a review of monte carlo simulation using microsoft excel for the calculation of uncertainties through functional relationships, including uncertainties in empirically derived constants.

    Science.gov (United States)

    Farrance, Ian; Frenkel, Robert

    2014-02-01

    The Guide to the Expression of Uncertainty in Measurement (usually referred to as the GUM) provides the basic framework for evaluating uncertainty in measurement. The GUM however does not always provide clearly identifiable procedures suitable for medical laboratory applications, particularly when internal quality control (IQC) is used to derive most of the uncertainty estimates. The GUM modelling approach requires advanced mathematical skills for many of its procedures, but Monte Carlo simulation (MCS) can be used as an alternative for many medical laboratory applications. In particular, calculations for determining how uncertainties in the input quantities to a functional relationship propagate through to the output can be accomplished using a readily available spreadsheet such as Microsoft Excel. The MCS procedure uses algorithmically generated pseudo-random numbers which are then forced to follow a prescribed probability distribution. When IQC data provide the uncertainty estimates the normal (Gaussian) distribution is generally considered appropriate, but MCS is by no means restricted to this particular case. With input variations simulated by random numbers, the functional relationship then provides the corresponding variations in the output in a manner which also provides its probability distribution. The MCS procedure thus provides output uncertainty estimates without the need for the differential equations associated with GUM modelling. The aim of this article is to demonstrate the ease with which Microsoft Excel (or a similar spreadsheet) can be used to provide an uncertainty estimate for measurands derived through a functional relationship. In addition, we also consider the relatively common situation where an empirically derived formula includes one or more 'constants', each of which has an empirically derived numerical value. Such empirically derived 'constants' must also have associated uncertainties which propagate through the functional relationship

  20. A Monte-Carlo investigation of the uncertainty of acoustic decay measurements

    DEFF Research Database (Denmark)

    Cabo, David Pérez; Seoane, Manuel A. Sobreira; Jacobsen, Finn

    2012-01-01

    Measurement of acoustic decays can be problematic at low frequencies: short decays cannot be evaluated accurately. Several effects influencing the evaluation will be reviewed in this paper. As new contribution, the measurement uncertainty due to one-third octave band pass filters will be analysed...

  1. New strategies of sensitivity analysis capabilities in continuous-energy Monte Carlo code RMC

    International Nuclear Information System (INIS)

    Qiu, Yishu; Liang, Jingang; Wang, Kan; Yu, Jiankai

    2015-01-01

    Highlights: • Data decomposition techniques are proposed for memory reduction. • New strategies are put forward and implemented in RMC code to improve efficiency and accuracy for sensitivity calculations. • A capability to compute region-specific sensitivity coefficients is developed in RMC code. - Abstract: The iterated fission probability (IFP) method has been demonstrated to be an accurate alternative for estimating the adjoint-weighted parameters in continuous-energy Monte Carlo forward calculations. However, the memory requirements of this method are huge especially when a large number of sensitivity coefficients are desired. Therefore, data decomposition techniques are proposed in this work. Two parallel strategies based on the neutron production rate (NPR) estimator and the fission neutron population (FNP) estimator for adjoint fluxes, as well as a more efficient algorithm which has multiple overlapping blocks (MOB) in a cycle, are investigated and implemented in the continuous-energy Reactor Monte Carlo code RMC for sensitivity analysis. Furthermore, a region-specific sensitivity analysis capability is developed in RMC. These new strategies, algorithms and capabilities are verified against analytic solutions of a multi-group infinite-medium problem and against results from other software packages including MCNP6, TSUANAMI-1D and multi-group TSUNAMI-3D. While the results generated by the NPR and FNP strategies agree within 0.1% of the analytic sensitivity coefficients, the MOB strategy surprisingly produces sensitivity coefficients exactly equal to the analytic ones. Meanwhile, the results generated by the three strategies in RMC are in agreement with those produced by other codes within a few percent. Moreover, the MOB strategy performs the most efficient sensitivity coefficient calculations (offering as much as an order of magnitude gain in FoMs over MCNP6), followed by the NPR and FNP strategies, and then MCNP6. The results also reveal that these

  2. Steady state likelihood ratio sensitivity analysis for stiff kinetic Monte Carlo simulations.

    Science.gov (United States)

    Núñez, M; Vlachos, D G

    2015-01-28

    Kinetic Monte Carlo simulation is an integral tool in the study of complex physical phenomena present in applications ranging from heterogeneous catalysis to biological systems to crystal growth and atmospheric sciences. Sensitivity analysis is useful for identifying important parameters and rate-determining steps, but the finite-difference application of sensitivity analysis is computationally demanding. Techniques based on the likelihood ratio method reduce the computational cost of sensitivity analysis by obtaining all gradient information in a single run. However, we show that disparity in time scales of microscopic events, which is ubiquitous in real systems, introduces drastic statistical noise into derivative estimates for parameters affecting the fast events. In this work, the steady-state likelihood ratio sensitivity analysis is extended to singularly perturbed systems by invoking partial equilibration for fast reactions, that is, by working on the fast and slow manifolds of the chemistry. Derivatives on each time scale are computed independently and combined to the desired sensitivity coefficients to considerably reduce the noise in derivative estimates for stiff systems. The approach is demonstrated in an analytically solvable linear system.

  3. Feasibility of a Monte Carlo-deterministic hybrid method for fast reactor analysis

    Energy Technology Data Exchange (ETDEWEB)

    Heo, W.; Kim, W.; Kim, Y. [Korea Advanced Institute of Science and Technology - KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon, 305-701 (Korea, Republic of); Yun, S. [Korea Atomic Energy Research Institute - KAERI, 989-111 Daedeok-daero, Yuseong-gu, Daejeon, 305-353 (Korea, Republic of)

    2013-07-01

    A Monte Carlo and deterministic hybrid method is investigated for the analysis of fast reactors in this paper. Effective multi-group cross sections data are generated using a collision estimator in the MCNP5. A high order Legendre scattering cross section data generation module was added into the MCNP5 code. Both cross section data generated from MCNP5 and TRANSX/TWODANT using the homogeneous core model were compared, and were applied to DIF3D code for fast reactor core analysis of a 300 MWe SFR TRU burner core. For this analysis, 9 groups macroscopic-wise data was used. In this paper, a hybrid calculation MCNP5/DIF3D was used to analyze the core model. The cross section data was generated using MCNP5. The k{sub eff} and core power distribution were calculated using the 54 triangle FDM code DIF3D. A whole core calculation of the heterogeneous core model using the MCNP5 was selected as a reference. In terms of the k{sub eff}, 9-group MCNP5/DIF3D has a discrepancy of -154 pcm from the reference solution, 9-group TRANSX/TWODANT/DIF3D analysis gives -1070 pcm discrepancy. (authors)

  4. Modelling of the X , Y , Z positioning errors and uncertainty evaluation for the LNE’s mAFM using the Monte Carlo method

    International Nuclear Information System (INIS)

    Ceria, Paul; Ducourtieux, Sebastien; Boukellal, Younes; Feltin, Nicolas; Allard, Alexandre; Fischer, Nicolas

    2017-01-01

    In order to evaluate the uncertainty budget of the LNE’s mAFM, a reference instrument dedicated to the calibration of nanoscale dimensional standards, a numerical model has been developed to evaluate the measurement uncertainty of the metrology loop involved in the XYZ positioning of the tip relative to the sample. The objective of this model is to overcome difficulties experienced when trying to evaluate some uncertainty components which cannot be experimentally determined and more specifically, the one linked to the geometry of the metrology loop. The model is based on object-oriented programming and developed under Matlab. It integrates one hundred parameters that allow the control of the geometry of the metrology loop without using analytical formulae. The created objects, mainly the reference and the mobile prism and their mirrors, the interferometers and their laser beams, can be moved and deformed freely to take into account several error sources. The Monte Carlo method is then used to determine the positioning uncertainty of the instrument by randomly drawing the parameters according to their associated tolerances and their probability density functions (PDFs). The whole process follows Supplement 2 to ‘The Guide to the Expression of the Uncertainty in Measurement’ (GUM). Some advanced statistical tools like Morris design and Sobol indices are also used to provide a sensitivity analysis by identifying the most influential parameters and quantifying their contribution to the XYZ positioning uncertainty. The approach validated in the paper shows that the actual positioning uncertainty is about 6 nm. As the final objective is to reach 1 nm, we engage in a discussion to estimate the most effective way to reduce the uncertainty. (paper)

  5. Modelling of the X,Y,Z positioning errors and uncertainty evaluation for the LNE’s mAFM using the Monte Carlo method

    Science.gov (United States)

    Ceria, Paul; Ducourtieux, Sebastien; Boukellal, Younes; Allard, Alexandre; Fischer, Nicolas; Feltin, Nicolas

    2017-03-01

    In order to evaluate the uncertainty budget of the LNE’s mAFM, a reference instrument dedicated to the calibration of nanoscale dimensional standards, a numerical model has been developed to evaluate the measurement uncertainty of the metrology loop involved in the XYZ positioning of the tip relative to the sample. The objective of this model is to overcome difficulties experienced when trying to evaluate some uncertainty components which cannot be experimentally determined and more specifically, the one linked to the geometry of the metrology loop. The model is based on object-oriented programming and developed under Matlab. It integrates one hundred parameters that allow the control of the geometry of the metrology loop without using analytical formulae. The created objects, mainly the reference and the mobile prism and their mirrors, the interferometers and their laser beams, can be moved and deformed freely to take into account several error sources. The Monte Carlo method is then used to determine the positioning uncertainty of the instrument by randomly drawing the parameters according to their associated tolerances and their probability density functions (PDFs). The whole process follows Supplement 2 to ‘The Guide to the Expression of the Uncertainty in Measurement’ (GUM). Some advanced statistical tools like Morris design and Sobol indices are also used to provide a sensitivity analysis by identifying the most influential parameters and quantifying their contribution to the XYZ positioning uncertainty. The approach validated in the paper shows that the actual positioning uncertainty is about 6 nm. As the final objective is to reach 1 nm, we engage in a discussion to estimate the most effective way to reduce the uncertainty.

  6. Monte Carlo Analysis of the Battery-Type High Temperature Gas Cooled Reactor

    Science.gov (United States)

    Grodzki, Marcin; Darnowski, Piotr; Niewiński, Grzegorz

    2017-12-01

    The paper presents a neutronic analysis of the battery-type 20 MWth high-temperature gas cooled reactor. The developed reactor model is based on the publicly available data being an `early design' variant of the U-battery. The investigated core is a battery type small modular reactor, graphite moderated, uranium fueled, prismatic, helium cooled high-temperature gas cooled reactor with graphite reflector. The two core alternative designs were investigated. The first has a central reflector and 30×4 prismatic fuel blocks and the second has no central reflector and 37×4 blocks. The SERPENT Monte Carlo reactor physics computer code, with ENDF and JEFF nuclear data libraries, was applied. Several nuclear design static criticality calculations were performed and compared with available reference results. The analysis covered the single assembly models and full core simulations for two geometry models: homogenous and heterogenous (explicit). A sensitivity analysis of the reflector graphite density was performed. An acceptable agreement between calculations and reference design was obtained. All calculations were performed for the fresh core state.

  7. Monte Carlo Analysis of the Battery-Type High Temperature Gas Cooled Reactor

    Directory of Open Access Journals (Sweden)

    Grodzki Marcin

    2017-12-01

    Full Text Available The paper presents a neutronic analysis of the battery-type 20 MWth high-temperature gas cooled reactor. The developed reactor model is based on the publicly available data being an ‘early design’ variant of the U-battery. The investigated core is a battery type small modular reactor, graphite moderated, uranium fueled, prismatic, helium cooled high-temperature gas cooled reactor with graphite reflector. The two core alternative designs were investigated. The first has a central reflector and 30×4 prismatic fuel blocks and the second has no central reflector and 37×4 blocks. The SERPENT Monte Carlo reactor physics computer code, with ENDF and JEFF nuclear data libraries, was applied. Several nuclear design static criticality calculations were performed and compared with available reference results. The analysis covered the single assembly models and full core simulations for two geometry models: homogenous and heterogenous (explicit. A sensitivity analysis of the reflector graphite density was performed. An acceptable agreement between calculations and reference design was obtained. All calculations were performed for the fresh core state.

  8. A user's guide to MICAP: A Monte Carlo Ionization Chamber Analysis Package

    Energy Technology Data Exchange (ETDEWEB)

    Johnson, J.O.; Gabriel, T.A.

    1988-01-01

    A collection of computer codes entitled MICAP - A Monte Carlo Ionization Chamber Analysis Package has been developed to determine the response of a gas-filled cavity ionization chamber in a mixed neutron and photon radiation environment. In particular, MICAP determines the neutron, photon, and total response of the ionization chamber. The applicability of MICAP encompasses all aspects of mixed field dosimetry analysis including detector design, preexperimental planning and post-experimental analysis. The MICAP codes include: RDNDF for reading and processing ENDF/B-formatted cross section files, MICRO for manipulating microscopic cross section data sets, MACRO for creating macroscopic cross section data sets, NEUTRON for transporting neutrons, RECOMB for calculating correction data due to ionization chamber saturation effects, HEAVY for transporting recoil heavy ions and charged particles, PECSP for generating photon and electron cross section and material data sets, PHOTPREP for generating photon source input tapes, and PHOTON for transporting photons and electrons. The codes are generally tailored to provide numerous input options, but whenever possible, default values are supplied which yield adequate results. All of the MICAP codes function independently, and are operational on the ORNL IBM 3033 computer system. 14 refs., 27 figs., 49 tabs.

  9. Monte Carlo analysis of a control technique for a tunable white lighting system

    DEFF Research Database (Denmark)

    Chakrabarti, Maumita; Thorseth, Anders; Jepsen, Jørgen

    2017-01-01

    A simulated colour control mechanism for a multi-coloured LED lighting system is presented. The system achieves adjustable and stable white light output and allows for system-to-system reproducibility after application of the control mechanism. The control unit works using a pre-calibrated lookup...... table for an experimentally realized system, with a calibrated tristimulus colour sensor. A Monte Carlo simulation is used to examine the system performance concerning the variation of luminous flux and chromaticity of the light output. The inputs to the Monte Carlo simulation, are variations of the LED...... peak wavelength, the LED rated luminous flux bin, the influence of the operating conditions, ambient temperature, driving current, and the spectral response of the colour sensor. The system performance is investigated by evaluating the outputs from the Monte Carlo simulation. The outputs show...

  10. Use of Monte Carlo Bootstrap Method in the Analysis of Sample Sufficiency for Radioecological Data

    International Nuclear Information System (INIS)

    Silva, A. N. C. da; Amaral, R. S.; Araujo Santos Jr, J.; Wilson Vieira, J.; Lima, F. R. de A.

    2015-01-01

    There are operational difficulties in obtaining samples for radioecological studies. Population data may no longer be available during the study and obtaining new samples may not be possible. These problems do the researcher sometimes work with a small number of data. Therefore, it is difficult to know whether the number of samples will be sufficient to estimate the desired parameter. Hence, it is critical do the analysis of sample sufficiency. It is not interesting uses the classical methods of statistic to analyze sample sufficiency in Radioecology, because naturally occurring radionuclides have a random distribution in soil, usually arise outliers and gaps with missing values. The present work was developed aiming to apply the Monte Carlo Bootstrap method in the analysis of sample sufficiency with quantitative estimation of a single variable such as specific activity of a natural radioisotope present in plants. The pseudo population was a small sample with 14 values of specific activity of 226 Ra in forage palm (Opuntia spp.). Using the R software was performed a computational procedure to calculate the number of the sample values. The re sampling process with replacement took the 14 values of original sample and produced 10,000 bootstrap samples for each round. Then was calculated the estimated average θ for samples with 2, 5, 8, 11 and 14 values randomly selected. The results showed that if the researcher work with only 11 sample values, the average parameter will be within a confidence interval with 90% probability . (Author)

  11. Criticality Analysis Of TCA Critical Lattices With MNCP-4C Monte Carlo Calculation

    International Nuclear Information System (INIS)

    Zuhair

    2002-01-01

    The use of uranium-plutonium mixed oxide (MOX) fuel in electric generation light water reactor (PWR, BWR) is being planned in Japan. Therefore, the accuracy evaluations of neutronic analysis code for MOX cores have been employed by many scientists and reactor physicists. Benchmark evaluations for TCA was done using various calculation methods. The Monte Carlo become the most reliable method to predict criticality of various reactor types. In this analysis, the MCNP-4C code was chosen because various superiorities the code has. All in all, the MCNP-4C calculation for TCA core with 38 MOX critical lattice configurations gave the results with high accuracy. The JENDL-3.2 library showed significantly closer results to the ENDF/B-V. The k eff values calculated with the ENDF/B-VI library gave underestimated results. The ENDF/B-V library gave the best estimation. It can be concluded that MCNP-4C calculation, especially with ENDF/B-V and JENDL-3.2 libraries, for MOX fuel utilized NPP design in reactor core is the best choice

  12. Monte Carlo analysis of thermochromatography as a fast separation method for nuclear forensics

    International Nuclear Information System (INIS)

    Garrison, J.R.; Hanson, D.E.; Hall, H.L.

    2012-01-01

    Nuclear forensic science has become increasingly important for global nuclear security, and enhancing the timeliness of forensic analysis has been established as an important objective in the field. New, faster techniques must be developed to meet this objective. Current approaches for the analysis of minor actinides, fission products, and fuel-specific materials require time-consuming chemical separation coupled with measurement through either nuclear counting or mass spectrometry. These very sensitive measurement techniques can be hindered by impurities or incomplete separation in even the most painstaking chemical separations. High-temperature gas-phase separation or thermochromatography has been used in the past for the rapid separations in the study of newly created elements and as a basis for chemical classification of that element. This work examines the potential for rapid separation of gaseous species to be applied in nuclear forensic investigations. Monte Carlo modeling has been used to evaluate the potential utility of the thermochromatographic separation method, albeit this assessment is necessarily limited due to the lack of available experimental data for validation. (author)

  13. Numerical experiment on variance biases and Monte Carlo neutronics analysis with thermal hydraulic feedback

    International Nuclear Information System (INIS)

    Hyung, Jin Shim; Beom, Seok Han; Chang, Hyo Kim

    2003-01-01

    Monte Carlo (MC) power method based on the fixed number of fission sites at the beginning of each cycle is known to cause biases in the variances of the k-eigenvalue (keff) and the fission reaction rate estimates. Because of the biases, the apparent variances of keff and the fission reaction rate estimates from a single MC run tend to be smaller or larger than the real variances of the corresponding quantities, depending on the degree of the inter-generational correlation of the sample. We demonstrate this through a numerical experiment involving 100 independent MC runs for the neutronics analysis of a 17 x 17 fuel assembly of a pressurized water reactor (PWR). We also demonstrate through the numerical experiment that Gelbard and Prael's batch method and Ueki et al's covariance estimation method enable one to estimate the approximate real variances of keff and the fission reaction rate estimates from a single MC run. We then show that the use of the approximate real variances from the two-bias predicting methods instead of the apparent variances provides an efficient MC power iteration scheme that is required in the MC neutronics analysis of a real system to determine the pin power distribution consistent with the thermal hydraulic (TH) conditions of individual pins of the system. (authors)

  14. A Monte Carlo study of Weibull reliability analysis for space shuttle main engine components

    Science.gov (United States)

    Abernethy, K.

    1986-01-01

    The incorporation of a number of additional capabilities into an existing Weibull analysis computer program and the results of Monte Carlo computer simulation study to evaluate the usefulness of the Weibull methods using samples with a very small number of failures and extensive censoring are discussed. Since the censoring mechanism inherent in the Space Shuttle Main Engine (SSME) data is hard to analyze, it was decided to use a random censoring model, generating censoring times from a uniform probability distribution. Some of the statistical techniques and computer programs that are used in the SSME Weibull analysis are described. The methods documented in were supplemented by adding computer calculations of approximate (using iteractive methods) confidence intervals for several parameters of interest. These calculations are based on a likelihood ratio statistic which is asymptotically a chisquared statistic with one degree of freedom. The assumptions built into the computer simulations are described. The simulation program and the techniques used in it are described there also. Simulation results are tabulated for various combinations of Weibull shape parameters and the numbers of failures in the samples.

  15. Monte Carlo analysis of thermochromatography as a fast separation method for nuclear forensics

    International Nuclear Information System (INIS)

    Hall, Howard L.

    2012-01-01

    Nuclear forensic science has become increasingly important for global nuclear security, and enhancing the timeliness of forensic analysis has been established as an important objective in the field. New, faster techniques must be developed to meet this objective. Current approaches for the analysis of minor actinides, fission products, and fuel-specific materials require time-consuming chemical separation coupled with measurement through either nuclear counting or mass spectrometry. These very sensitive measurement techniques can be hindered by impurities or incomplete separation in even the most painstaking chemical separations. High-temperature gas-phase separation or thermochromatography has been used in the past for the rapid separations in the study of newly created elements and as a basis for chemical classification of that element. This work examines the potential for rapid separation of gaseous species to be applied in nuclear forensic investigations. Monte Carlo modeling has been used to evaluate the potential utility of the thermochromatographic separation method, albeit this assessment is necessarily limited due to the lack of available experimental data for validation.

  16. Criticality qualification of a new Monte Carlo code for reactor core analysis

    International Nuclear Information System (INIS)

    Catsaros, N.; Gaveau, B.; Jaekel, M.; Maillard, J.; Maurel, G.; Savva, P.; Silva, J.; Varvayanni, M.; Zisis, Th.

    2009-01-01

    In order to accurately simulate Accelerator Driven Systems (ADS), the utilization of at least two computational tools is necessary (the thermal-hydraulic problem is not considered in the frame of this work), namely: (a) A High Energy Physics (HEP) code system dealing with the 'Accelerator part' of the installation, i.e. the computation of the spectrum, intensity and spatial distribution of the neutrons source created by (p, n) reactions of a proton beam on a target and (b) a neutronics code system, handling the 'Reactor part' of the installation, i.e. criticality calculations, neutron transport, fuel burn-up and fission products evolution. In the present work, a single computational tool, aiming to analyze an ADS in its integrity and also able to perform core analysis for a conventional fission reactor, is proposed. The code is based on the well qualified HEP code GEANT (version 3), transformed to perform criticality calculations. The performance of the code is tested against two qualified neutronics code systems, the diffusion/transport SCALE-CITATION code system and the Monte Carlo TRIPOLI code, in the case of a research reactor core analysis. A satisfactory agreement was exhibited by the three codes.

  17. Analysis of the design of an X-ray tube using Monte Carlo

    International Nuclear Information System (INIS)

    Pena V, J. D.; Sosa A, M. A.; Ceron, P. V.; Vallejo, M. A.; Vega C, H. R.

    2017-10-01

    In this paper we present the Monte Carlo analysis of the X-rays produced by a rotating X-ray tube of the Siemens brand that is used in tomographs for clinical use. The work was done with the MCNP6 code with which the tube was modeled and the primary X-ray spectra produced during the interaction of monoenergetic electrons of 130 keV were calculated. The X-ray spectra were obtained by varying some parameters such as: the angle of the anode (15 to 20 degrees), the type of target (Tungsten, Molybdenum and Rhodium) and the thickness of the filter (3, 5, 10 and 15 mm). In order to have a good statistic 10 7 stories were used. Though the estimators f2 and f5 the X-ray spectra and the total fluencies were estimated. This information will be used to calculate the dose absorbed in the lens and the thyroid gland in patients undergoing radio diagnosis procedures. (Author)

  18. Understanding product cost vs. performance through an in-depth system Monte Carlo analysis

    Science.gov (United States)

    Sanson, Mark C.

    2017-08-01

    The manner in which an optical system is toleranced and compensated greatly affects the cost to build it. By having a detailed understanding of different tolerance and compensation methods, the end user can decide on the balance of cost and performance. A detailed phased approach Monte Carlo analysis can be used to demonstrate the tradeoffs between cost and performance. In complex high performance optical systems, performance is fine-tuned by making adjustments to the optical systems after they are initially built. This process enables the overall best system performance, without the need for fabricating components to stringent tolerance levels that often can be outside of a fabricator's manufacturing capabilities. A good performance simulation of as built performance can interrogate different steps of the fabrication and build process. Such a simulation may aid the evaluation of whether the measured parameters are within the acceptable range of system performance at that stage of the build process. Finding errors before an optical system progresses further into the build process saves both time and money. Having the appropriate tolerances and compensation strategy tied to a specific performance level will optimize the overall product cost.

  19. Benchmark analysis of SPERT-IV reactor with Monte Carlo code MVP

    International Nuclear Information System (INIS)

    Motalab, M.A.; Mahmood, M.S.; Khan, M.J.H.; Badrun, N.H.; Lyric, Z.I.; Altaf, M.H.

    2014-01-01

    Highlights: • MVP was used for SPERT-IV core modeling. • Neutronics analysis of SPERT-IV reactor was performed. • Calculation performed to estimate critical rod height, excess reactivity. • Neutron flux, time integrated neutron flux and Cd-ratio also calculated. • Calculated values agree with experimental data. - Abstract: The benchmark experiment of the SPERT-IV D-12/25 reactor core has been analyzed with the Monte Carlo code MVP using the cross-section libraries based on JENDL-3.3. The MVP simulation was performed for the clean and cold core. The estimated values of K eff at the experimental critical rod height and the core excess reactivity were within 5% with the experimental data. Thermal neutron flux profiles at different vertical and horizontal positions of the core were also estimated. Cadmium Ratio at different point of the core was also estimated. All estimated results have been compared with the experimental results. Generally good agreement has been found between experimentally determined and the calculated results

  20. Markov chain Monte Carlo analysis to constrain dark matter properties with directional detection

    International Nuclear Information System (INIS)

    Billard, J.; Mayet, F.; Santos, D.

    2011-01-01

    Directional detection is a promising dark matter search strategy. Indeed, weakly interacting massive particle (WIMP)-induced recoils would present a direction dependence toward the Cygnus constellation, while background-induced recoils exhibit an isotropic distribution in the Galactic rest frame. Taking advantage of these characteristic features, and even in the presence of a sizeable background, it has recently been shown that data from forthcoming directional detectors could lead either to a competitive exclusion or to a conclusive discovery, depending on the value of the WIMP-nucleon cross section. However, it is possible to further exploit these upcoming data by using the strong dependence of the WIMP signal with: the WIMP mass and the local WIMP velocity distribution. Using a Markov chain Monte Carlo analysis of recoil events, we show for the first time the possibility to constrain the unknown WIMP parameters, both from particle physics (mass and cross section) and Galactic halo (velocity dispersion along the three axis), leading to an identification of non-baryonic dark matter.

  1. Application of Multi-Hypothesis Sequential Monte Carlo for Breakup Analysis

    Science.gov (United States)

    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.

  2. Markov chain Monte Carlo linkage analysis: effect of bin width on the probability of linkage.

    Science.gov (United States)

    Slager, S L; Juo, S H; Durner, M; Hodge, S E

    2001-01-01

    We analyzed part of the Genetic Analysis Workshop (GAW) 12 simulated data using Monte Carlo Markov chain (MCMC) methods that are implemented in the computer program Loki. The MCMC method reports the "probability of linkage" (PL) across the chromosomal regions of interest. The point of maximum PL can then be taken as a "location estimate" for the location of the quantitative trait locus (QTL). However, Loki does not provide a formal statistical test of linkage. In this paper, we explore how the bin width used in the calculations affects the max PL and the location estimate. We analyzed age at onset (AO) and quantitative trait number 5, Q5, from 26 replicates of the general simulated data in one region where we knew a major gene, MG5, is located. For each trait, we found the max PL and the corresponding location estimate, using four different bin widths. We found that bin width, as expected, does affect the max PL and the location estimate, and we recommend that users of Loki explore how their results vary with different bin widths.

  3. Monte Carlo Simulation for Particle Detectors

    CERN Document Server

    Pia, Maria Grazia

    2012-01-01

    Monte Carlo simulation is an essential component of experimental particle physics in all the phases of its life-cycle: the investigation of the physics reach of detector concepts, the design of facilities and detectors, the development and optimization of data reconstruction software, the data analysis for the production of physics results. This note briefly outlines some research topics related to Monte Carlo simulation, that are relevant to future experimental perspectives in particle physics. The focus is on physics aspects: conceptual progress beyond current particle transport schemes, the incorporation of materials science knowledge relevant to novel detection technologies, functionality to model radiation damage, the capability for multi-scale simulation, quantitative validation and uncertainty quantification to determine the predictive power of simulation. The R&D on simulation for future detectors would profit from cooperation within various components of the particle physics community, and synerg...

  4. Managing Groundwater Recharge and Pumping for Late Summer Streamflow Increases: Quantifying Uncertainty Using Null Space Monte Carlo

    Science.gov (United States)

    Tolley, D. G., III; Foglia, L.; Harter, T.

    2017-12-01

    Late summer and early fall streamflow decreases caused by climate change and agricultural pumping contribute to increased water temperatures and result in large disconnected sections during dry years in many semi-arid regions with Mediterranean climate. This negatively impacts aquatic habitat of fish species such as coho and fall-run Chinook salmon. In collaboration with local stakeholders, the Scott Valley Integrated Hydrologic Model (SVIHMv3) was developed to assess future water management scenarios with the goal of improving aquatic species habitat while maintaining agricultural production in the valley. The Null Space Monte Carlo (NSMC) method available in PEST was used to quantify the range of predicted streamflow changes for three conjunctive use scenarios: 1) managed aquifer recharge (MAR), 2) in lieu recharge (ILR, substituting surface-water irrigation for irrigation with groundwater while flows are available), and 3) MAR + ILR. Random parameter sets were generated using the calibrated covariance matrix of the model, which were then recalibrated if the sum of squared residuals was greater than 10% of the original sum of squared weighted residuals. These calibration-constrained stochastic parameter sets were then used to obtain a distribution of streamflow changes resulting from implementing the conjunctive use scenarios. Preliminary results show that while the range of streamflow increases using managed aquifer recharge is much narrower (i.e., greater degree of certainty) than in lieu recharge, there are potentially much greater benefits to streamflow by implementing in lieu recharge (although also greater costs). Combining the two scenarios provides the greatest benefit for increasing late summer and early fall streamflow, as most of the MAR streamflow increases are during the spring and early summer which ILR is able to take advantage of. Incorporation of uncertainty into model predictions is critical for establishing and maintaining stakeholder trust

  5. A Monte Carlo/response surface strategy for sensitivity analysis: application to a dynamic model of vegetative plant growth

    Science.gov (United States)

    Lim, J. T.; Gold, H. J.; Wilkerson, G. G.; Raper, C. D. Jr; Raper CD, J. r. (Principal Investigator)

    1989-01-01

    We describe the application of a strategy for conducting a sensitivity analysis for a complex dynamic model. The procedure involves preliminary screening of parameter sensitivities by numerical estimation of linear sensitivity coefficients, followed by generation of a response surface based on Monte Carlo simulation. Application is to a physiological model of the vegetative growth of soybean plants. The analysis provides insights as to the relative importance of certain physiological processes in controlling plant growth. Advantages and disadvantages of the strategy are discussed.

  6. SIMON. A computer program for reliability and statistical analysis using Monte Carlo simulation. Program description and manual

    International Nuclear Information System (INIS)

    Kongsoe, H.E.; Lauridsen, K.

    1993-09-01

    SIMON is a program for calculation of reliability and statistical analysis. The program is of the Monte Carlo type, and it is designed with high flexibility, and has a large potential for application to complex problems like reliability analyses of very large systems and of systems, where complex modelling or knowledge of special details are required. Examples of application of the program, including input and output, for reliability and statistical analysis are presented. (au) (3 tabs., 3 ills., 5 refs.)

  7. Exploring Monte Carlo methods

    CERN Document Server

    Dunn, William L

    2012-01-01

    Exploring Monte Carlo Methods is a basic text that describes the numerical methods that have come to be known as "Monte Carlo." The book treats the subject generically through the first eight chapters and, thus, should be of use to anyone who wants to learn to use Monte Carlo. The next two chapters focus on applications in nuclear engineering, which are illustrative of uses in other fields. Five appendices are included, which provide useful information on probability distributions, general-purpose Monte Carlo codes for radiation transport, and other matters. The famous "Buffon's needle proble

  8. Monte Carlo methods

    Directory of Open Access Journals (Sweden)

    Bardenet Rémi

    2013-07-01

    Full Text Available Bayesian inference often requires integrating some function with respect to a posterior distribution. Monte Carlo methods are sampling algorithms that allow to compute these integrals numerically when they are not analytically tractable. We review here the basic principles and the most common Monte Carlo algorithms, among which rejection sampling, importance sampling and Monte Carlo Markov chain (MCMC methods. We give intuition on the theoretical justification of the algorithms as well as practical advice, trying to relate both. We discuss the application of Monte Carlo in experimental physics, and point to landmarks in the literature for the curious reader.

  9. An Analysis on the Characteristic of Multi-response CADIS Method for the Monte Carlo Radiation Shielding Calculation

    International Nuclear Information System (INIS)

    Kim, Do Hyun; Shin, Chang Ho; Kim, Song Hyun

    2014-01-01

    It uses the deterministic method to calculate adjoint fluxes for the decision of the parameters used in the variance reductions. This is called as hybrid Monte Carlo method. The CADIS method, however, has a limitation to reduce the stochastic errors of all responses. The Forward Weighted CADIS (FW-CADIS) was introduced to solve this problem. To reduce the overall stochastic errors of the responses, the forward flux is used. In the previous study, the Multi-Response CADIS (MR-CAIDS) method was derived for minimizing sum of each squared relative error. In this study, the characteristic of the MR-CADIS method was evaluated and compared with the FW-CADIS method. In this study, how the CADIS, FW-CADIS, and MR-CADIS methods are applied to optimize and decide the parameters used in the variance reduction techniques was analyzed. The MR-CADIS Method uses a technique that the sum of squared relative error in each tally region was minimized to achieve uniform uncertainty. To compare the simulation efficiency of the methods, a simple shielding problem was evaluated. Using FW-CADIS method, it was evaluated that the average of the relative errors was minimized; however, MR-CADIS method gives a lowest variance of the relative errors. Analysis shows that, MR-CADIS method can efficiently and uniformly reduce the relative error of the plural response problem than FW-CADIS method

  10. A Monte Carlo evaluation of analytical multiple scattering corrections for unpolarised neutron scattering and polarisation analysis data

    International Nuclear Information System (INIS)

    Mayers, J.; Cywinski, R.

    1985-03-01

    Some of the approximations commonly used for the analytical estimation of multiple scattering corrections to thermal neutron elastic scattering data from cylindrical and plane slab samples have been tested using a Monte Carlo program. It is shown that the approximations are accurate for a wide range of sample geometries and scattering cross-sections. Neutron polarisation analysis provides the most stringent test of multiple scattering calculations as multiply scattered neutrons may be redistributed not only geometrically but also between the spin flip and non spin flip scattering channels. A very simple analytical technique for correcting for multiple scattering in neutron polarisation analysis has been tested using the Monte Carlo program and has been shown to work remarkably well in most circumstances. (author)

  11. Analysis of the distribution of X-ray characteristic production using the Monte Carlo methods

    International Nuclear Information System (INIS)

    Del Giorgio, Marcelo; Brizuela, Horacio; Riveros, J.A.

    1987-01-01

    The Monte Carlo method has been applied for the simulation of electron trajectories in a bulk sample, and therefore for the distribution of signals produced in an electron microprobe. Results for the function φ(ρz) are compared with experimental data. Some conclusions are drawn with respect to the parameters involved in the gaussian model. (Author) [es

  12. A study on Monte Carlo analysis of Pebble-type VHTR core for hydrogen production

    International Nuclear Information System (INIS)

    Kim, Hong Chul

    2005-02-01

    In order to pursue exact the core analysis for VHTR core which will be developed in future, a study on Monte Carol method was carried out. In Korea, pebble and prism type core are under investigation for VHTR core analysis. In this study, pebble-type core was investigated because it was known that it should not only maintain the nuclear fuel integrity but also have the advantage in economical efficiency and safety. The pebble-bed cores of HTR-PROTEUS critical facility in Swiss were selected for the benchmark model. After the detailed MCNP modeling of the whole facility, calculations of nuclear characteristics were performed. The two core configurations, Core 4.3 and Core 5 (reference state no. 3), among the 10 configurations of the HTR-PROTEUS cores were chosen to be analyzed in order to treat different fuel loading pattern and modeled. The former is a random packing core and the latter deterministic packing core. Based on the experimental data and the benchmark result of other research groups for the two different cores, some nuclear characteristics were calculated. Firstly, keff was calculated for these cores. The effect for TRIO homogeneity model was investigated. Control rod and shutdown rod worths also were calculated and the sensitivity analysis on cross-section library and reflector thickness was pursued. Lastly, neutron flux profiles were investigated in reflector regions. It is noted that Monte Carlo analysis of pebble-type VHTR core was firstly carried out in Korea. Also, this study should not only provide the basic data for pebble-type VHTR core analysis for hydrogen production but also be utilized as the verified data to validate a computer code for VHTR core analysis which will be developed in future

  13. Harnessing the theoretical foundations of the exponential and beta-Poisson dose-response models to quantify parameter uncertainty using Markov Chain Monte Carlo.

    Science.gov (United States)

    Schmidt, Philip J; Pintar, Katarina D M; Fazil, Aamir M; Topp, Edward

    2013-09-01

    Dose-response models are the essential link between exposure assessment and computed risk values in quantitative microbial risk assessment, yet the uncertainty that is inherent to computed risks because the dose-response model parameters are estimated using limited epidemiological data is rarely quantified. Second-order risk characterization approaches incorporating uncertainty in dose-response model parameters can provide more complete information to decisionmakers by separating variability and uncertainty to quantify the uncertainty in computed risks. Therefore, the objective of this work is to develop procedures to sample from posterior distributions describing uncertainty in the parameters of exponential and beta-Poisson dose-response models using Bayes's theorem and Markov Chain Monte Carlo (in OpenBUGS). The theoretical origins of the beta-Poisson dose-response model are used to identify a decomposed version of the model that enables Bayesian analysis without the need to evaluate Kummer confluent hypergeometric functions. Herein, it is also established that the beta distribution in the beta-Poisson dose-response model cannot address variation among individual pathogens, criteria to validate use of the conventional approximation to the beta-Poisson model are proposed, and simple algorithms to evaluate actual beta-Poisson probabilities of infection are investigated. The developed MCMC procedures are applied to analysis of a case study data set, and it is demonstrated that an important region of the posterior distribution of the beta-Poisson dose-response model parameters is attributable to the absence of low-dose data. This region includes beta-Poisson models for which the conventional approximation is especially invalid and in which many beta distributions have an extreme shape with questionable plausibility. © Her Majesty the Queen in Right of Canada 2013. Reproduced with the permission of the Minister of the Public Health Agency of Canada.

  14. Status of software for PGNAA bulk analysis by the Monte Carlo - Library Least-Squares (MCLLS) approach

    International Nuclear Information System (INIS)

    Gardner, R.P.; Zhang, W.; Metwally, W.A.

    2005-01-01

    The Center for Engineering Applications of Radioisotopes (CEAR) has been working for about ten years on the Monte Carlo - Library Least-Squares (MCLLS) approach for treating the nonlinear inverse analysis problem for PGNAA bulk analysis. This approach consists essentially of using Monte Carlo simulation to generate the libraries of all the elements to be analyzed plus any other required libraries. These libraries are then used in the linear Library Least-Squares (LLS) approach with unknown sample spectra to analyze for all elements in the sample. The other libraries include all sources of background which includes: (1) gamma-rays emitted by the neutron source, (2) prompt gamma-rays produced in the analyzer construction materials, (3) natural gamma-rays from K-40 and the uranium and thorium decay chains, and (4) prompt and decay gamma-rays produced in the NaI detector by neutron activation. A number of unforeseen problems have arisen in pursuing this approach including: (1) the neutron activation of the most common detector (NaI) used in bulk analysis PGNAA systems, (2) the nonlinearity of this detector, and (3) difficulties in obtaining detector response functions for this (and other) detectors. These problems have been addressed by CEAR recently and have either been solved or are almost solved at the present time. Development of Monte Carlo simulation for all of the libraries has been finished except the prompt gamma-ray library from the activation of the NaI detector. Treatment for the coincidence schemes for Na and particularly I must be first determined to complete the Monte Carlo simulation of this last library. (author)

  15. Monte Carlo Techniques for Nuclear Systems - Theory Lectures

    International Nuclear Information System (INIS)

    Brown, Forrest B.; Univ. of New Mexico, Albuquerque, NM

    2016-01-01

    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. These lectures provide a balanced approach to the theory and practice of Monte Carlo simulation codes. The first lectures provide an overview of Monte Carlo simulation methods, covering the transport equation, random sampling, computational geometry, collision physics, and statistics. The next lectures focus on the state-of-the-art in Monte Carlo criticality simulations, covering the theory of eigenvalue calculations, convergence analysis, dominance ratio calculations, bias in Keff and tallies, bias in uncertainties, a case study of a realistic calculation, and Wielandt acceleration techniques. The remaining lectures cover advanced topics, including HTGR modeling and stochastic geometry, temperature dependence, fission energy deposition, depletion calculations, parallel calculations, and parameter studies. This portion of the class focuses on using MCNP to perform criticality calculations for reactor physics and criticality safety applications. It is an intermediate level class, intended for those with at least some familiarity with MCNP. Class examples provide hands-on experience at running the code, plotting both geometry and results, and understanding the code output. The class includes lectures & hands-on computer use for a variety of Monte Carlo calculations

  16. Monte Carlo Techniques for Nuclear Systems - Theory Lectures

    Energy Technology Data Exchange (ETDEWEB)

    Brown, Forrest B. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Monte Carlo Methods, Codes, and Applications Group; Univ. of New Mexico, Albuquerque, NM (United States). Nuclear Engineering Dept.

    2016-11-29

    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. These lectures provide a balanced approach to the theory and practice of Monte Carlo simulation codes. The first lectures provide an overview of Monte Carlo simulation methods, covering the transport equation, random sampling, computational geometry, collision physics, and statistics. The next lectures focus on the state-of-the-art in Monte Carlo criticality simulations, covering the theory of eigenvalue calculations, convergence analysis, dominance ratio calculations, bias in Keff and tallies, bias in uncertainties, a case study of a realistic calculation, and Wielandt acceleration techniques. The remaining lectures cover advanced topics, including HTGR modeling and stochastic geometry, temperature dependence, fission energy deposition, depletion calculations, parallel calculations, and parameter studies. This portion of the class focuses on using MCNP to perform criticality calculations for reactor physics and criticality safety applications. It is an intermediate level class, intended for those with at least some familiarity with MCNP. Class examples provide hands-on experience at running the code, plotting both geometry and results, and understanding the code output. The class includes lectures & hands-on computer use for a variety of Monte Carlo calculations

  17. MC21 Monte Carlo analysis of the Hoogenboom-Martin full-core PWR benchmark problem - 301

    International Nuclear Information System (INIS)

    Kelly, D.J.; Sutton, Th.M.; Trumbull, T.H.; Dobreff, P.S.

    2010-01-01

    At the 2009 American Nuclear Society Mathematics and Computation conference, Hoogenboom and Martin proposed a full-core PWR model to monitor the improvement of Monte Carlo codes to compute detailed power density distributions. This paper describes the application of the MC21 Monte Carlo code to the analysis of this benchmark model. With the MC21 code, we obtained detailed power distributions over the entire core. The model consisted of 214 assemblies, each made up of a 17x17 array of pins. Each pin was subdivided into 100 axial nodes, thus resulting in over seven million tally regions. Various cases were run to assess the statistical convergence of the model. This included runs of 10 billion and 40 billion neutron histories, as well as ten independent runs of 4 billion neutron histories each. The 40 billion neutron-history calculation resulted in 43% of all regions having a 95% confidence level of 2% or less implying a relative standard deviation of 1%. Furthermore, 99.7% of regions having a relative power density of 1.0 or greater have a similar confidence level. We present timing results that assess the MC21 performance relative to the number of tallies requested. Source convergence was monitored by analyzing plots of the Shannon entropy and eigenvalue versus active cycle. We also obtained an estimate of the dominance ratio. Additionally, we performed an analysis of the error in an attempt to ascertain the validity of the confidence intervals predicted by MC21. Finally, we look forward to the prospect of full core 3-D Monte Carlo depletion by scoping out the required problem size. This study provides an initial data point for the Hoogenboom-Martin benchmark model using a state-of-the-art Monte Carlo code. (authors)

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

    Science.gov (United States)

    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.

  19. Criticality analysis of thermal reactors for two energy groups applying Monte Carlo and neutron Albedo method

    International Nuclear Information System (INIS)

    Terra, Andre Miguel Barge Pontes Torres

    2005-01-01

    The Albedo method applied to criticality calculations to nuclear reactors is characterized by following the neutron currents, allowing to make detailed analyses of the physics phenomena about interactions of the neutrons with the core-reflector set, by the determination of the probabilities of reflection, absorption, and transmission. Then, allowing to make detailed appreciations of the variation of the effective neutron multiplication factor, keff. In the present work, motivated for excellent results presented in dissertations applied to thermal reactors and shieldings, was described the methodology to Albedo method for the analysis criticality of thermal reactors by using two energy groups admitting variable core coefficients to each re-entrant current. By using the Monte Carlo KENO IV code was analyzed relation between the total fraction of neutrons absorbed in the core reactor and the fraction of neutrons that never have stayed into the reflector but were absorbed into the core. As parameters of comparison and analysis of the results obtained by the Albedo method were used one dimensional deterministic code ANISN (ANIsotropic SN transport code) and Diffusion method. The keff results determined by the Albedo method, to the type of analyzed reactor, showed excellent agreement. Thus were obtained relative errors of keff values smaller than 0,78% between the Albedo method and code ANISN. In relation to the Diffusion method were obtained errors smaller than 0,35%, showing the effectiveness of the Albedo method applied to criticality analysis. The easiness of application, simplicity and clarity of the Albedo method constitute a valuable instrument to neutronic calculations applied to nonmultiplying and multiplying media. (author)

  20. Ascertainment correction for Markov chain Monte Carlo segregation and linkage analysis of a quantitative trait.

    Science.gov (United States)

    Ma, Jianzhong; Amos, Christopher I; Warwick Daw, E

    2007-09-01

    Although extended pedigrees are often sampled through probands with extreme levels of a quantitative trait, Markov chain Monte Carlo (MCMC) methods for segregation and linkage analysis have not been able to perform ascertainment corrections. Further, the extent to which ascertainment of pedigrees leads to biases in the estimation of segregation and linkage parameters has not been previously studied for MCMC procedures. In this paper, we studied these issues with a Bayesian MCMC approach for joint segregation and linkage analysis, as implemented in the package Loki. We first simulated pedigrees ascertained through individuals with extreme values of a quantitative trait in spirit of the sequential sampling theory of Cannings and Thompson [Cannings and Thompson [1977] Clin. Genet. 12:208-212]. Using our simulated data, we detected no bias in estimates of the trait locus location. However, in addition to allele frequencies, when the ascertainment threshold was higher than or close to the true value of the highest genotypic mean, bias was also found in the estimation of this parameter. When there were multiple trait loci, this bias destroyed the additivity of the effects of the trait loci, and caused biases in the estimation all genotypic means when a purely additive model was used for analyzing the data. To account for pedigree ascertainment with sequential sampling, we developed a Bayesian ascertainment approach and implemented Metropolis-Hastings updates in the MCMC samplers used in Loki. Ascertainment correction greatly reduced biases in parameter estimates. Our method is designed for multiple, but a fixed number of trait loci. Copyright (c) 2007 Wiley-Liss, Inc.

  1. Performance Analysis of Korean Liquid metal type TBM based on Monte Carlo code

    Energy Technology Data Exchange (ETDEWEB)

    Kim, C. H.; Han, B. S.; Park, H. J.; Park, D. K. [Seoul National Univ., Seoul (Korea, Republic of)

    2007-01-15

    The objective of this project is to analyze a nuclear performance of the Korean HCML(Helium Cooled Molten Lithium) TBM(Test Blanket Module) which will be installed in ITER(International Thermonuclear Experimental Reactor). This project is intended to analyze a neutronic design and nuclear performances of the Korean HCML ITER TBM through the transport calculation of MCCARD. In detail, we will conduct numerical experiments for analyzing the neutronic design of the Korean HCML TBM and the DEMO fusion blanket, and improving the nuclear performances. The results of the numerical experiments performed in this project will be utilized further for a design optimization of the Korean HCML TBM. In this project, Monte Carlo transport calculations for evaluating TBR (Tritium Breeding Ratio) and EMF (Energy Multiplication factor) were conducted to analyze a nuclear performance of the Korean HCML TBM. The activation characteristics and shielding performances for the Korean HCML TBM were analyzed using ORIGEN and MCCARD. We proposed the neutronic methodologies for analyzing the nuclear characteristics of the fusion blanket, which was applied to the blanket analysis of a DEMO fusion reactor. In the results, the TBR of the Korean HCML ITER TBM is 0.1352 and the EMF is 1.362. Taking into account a limitation for the Li amount in ITER TBM, it is expected that tritium self-sufficiency condition can be satisfied through a change of the Li quantity and enrichment. In the results of activation and shielding analysis, the activity drops to 1.5% of the initial value and the decay heat drops to 0.02% of the initial amount after 10 years from plasma shutdown.

  2. Monte Carlo: Basics

    OpenAIRE

    Murthy, K. P. N.

    2001-01-01

    An introduction to the basics of Monte Carlo is given. The topics covered include, sample space, events, probabilities, random variables, mean, variance, covariance, characteristic function, chebyshev inequality, law of large numbers, central limit theorem (stable distribution, Levy distribution), random numbers (generation and testing), random sampling techniques (inversion, rejection, sampling from a Gaussian, Metropolis sampling), analogue Monte Carlo and Importance sampling (exponential b...

  3. Development of CAD-Based Geometry Processing Module for a Monte Carlo Particle Transport Analysis Code

    International Nuclear Information System (INIS)

    Choi, Sung Hoon; Kwark, Min Su; Shim, Hyung Jin

    2012-01-01

    As The Monte Carlo (MC) particle transport analysis for a complex system such as research reactor, accelerator, and fusion facility may require accurate modeling of the complicated geometry. Its manual modeling by using the text interface of a MC code to define the geometrical objects is tedious, lengthy and error-prone. This problem can be overcome by taking advantage of modeling capability of the computer aided design (CAD) system. There have been two kinds of approaches to develop MC code systems utilizing the CAD data: the external format conversion and the CAD kernel imbedded MC simulation. The first approach includes several interfacing programs such as McCAD, MCAM, GEOMIT etc. which were developed to automatically convert the CAD data into the MCNP geometry input data. This approach makes the most of the existing MC codes without any modifications, but implies latent data inconsistency due to the difference of the geometry modeling system. In the second approach, a MC code utilizes the CAD data for the direct particle tracking or the conversion to an internal data structure of the constructive solid geometry (CSG) and/or boundary representation (B-rep) modeling with help of a CAD kernel. MCNP-BRL and OiNC have demonstrated their capabilities of the CAD-based MC simulations. Recently we have developed a CAD-based geometry processing module for the MC particle simulation by using the OpenCASCADE (OCC) library. In the developed module, CAD data can be used for the particle tracking through primitive CAD surfaces (hereafter the CAD-based tracking) or the internal conversion to the CSG data structure. In this paper, the performances of the text-based model, the CAD-based tracking, and the internal CSG conversion are compared by using an in-house MC code, McSIM, equipped with the developed CAD-based geometry processing module

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

    Science.gov (United States)

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

    2012-01-01

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

  5. TH-A-19A-04: Latent Uncertainties and Performance of a GPU-Implemented Pre-Calculated Track Monte Carlo Method

    International Nuclear Information System (INIS)

    Renaud, M; Seuntjens, J; Roberge, D

    2014-01-01

    Purpose: Assessing the performance and uncertainty of a pre-calculated Monte Carlo (PMC) algorithm for proton and electron transport running on graphics processing units (GPU). While PMC methods have been described in the past, an explicit quantification of the latent uncertainty arising from recycling a limited number of tracks in the pre-generated track bank is missing from the literature. With a proper uncertainty analysis, an optimal pre-generated track bank size can be selected for a desired dose calculation uncertainty. Methods: Particle tracks were pre-generated for electrons and protons using EGSnrc and GEANT4, respectively. The PMC algorithm for track transport was implemented on the CUDA programming framework. GPU-PMC dose distributions were compared to benchmark dose distributions simulated using general-purpose MC codes in the same conditions. A latent uncertainty analysis was performed by comparing GPUPMC dose values to a “ground truth” benchmark while varying the track bank size and primary particle histories. Results: GPU-PMC dose distributions and benchmark doses were within 1% of each other in voxels with dose greater than 50% of Dmax. In proton calculations, a submillimeter distance-to-agreement error was observed at the Bragg Peak. Latent uncertainty followed a Poisson distribution with the number of tracks per energy (TPE) and a track bank of 20,000 TPE produced a latent uncertainty of approximately 1%. Efficiency analysis showed a 937× and 508× gain over a single processor core running DOSXYZnrc for 16 MeV electrons in water and bone, respectively. Conclusion: The GPU-PMC method can calculate dose distributions for electrons and protons to a statistical uncertainty below 1%. The track bank size necessary to achieve an optimal efficiency can be tuned based on the desired uncertainty. Coupled with a model to calculate dose contributions from uncharged particles, GPU-PMC is a candidate for inverse planning of modulated electron radiotherapy

  6. Monte Carlo Analysis of the Accelerator-Driven System at Kyoto University Research Reactor Institute

    Directory of Open Access Journals (Sweden)

    Wonkyeong Kim

    2016-04-01

    Full Text Available An accelerator-driven system consists of a subcritical reactor and a controllable external neutron source. The reactor in an accelerator-driven system can sustain fission reactions in a subcritical state using an external neutron source, which is an intrinsic safety feature of the system. The system can provide efficient transmutations of nuclear wastes such as minor actinides and long-lived fission products and generate electricity. Recently at Kyoto University Research Reactor Institute (KURRI; Kyoto, Japan, a series of reactor physics experiments was conducted with the Kyoto University Critical Assembly and a Cockcroft–Walton type accelerator, which generates the external neutron source by deuterium–tritium reactions. In this paper, neutronic analyses of a series of experiments have been re-estimated by using the latest Monte Carlo code and nuclear data libraries. This feasibility study is presented through the comparison of Monte Carlo simulation results with measurements.

  7. Monte Carlo analysis of the accelerator-driven system at Kyoto University Research Reactor Institute

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Won Kyeong; Lee, Deok Jung [Nuclear Engineering Division, Ulsan National Institute of Science and Technology, Ulsan (Korea, Republic of); Lee, Hyun Chul [VHTR Technology Development Division, Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Pyeon, Cheol Ho [Nuclear Engineering Science Division, Kyoto University Research Reactor Institute, Osaka (Japan); Shin, Ho Cheol [Core and Fuel Analysis Group, Korea Hydro and Nuclear Power Central Research Institute, Daejeon (Korea, Republic of)

    2016-04-15

    An accelerator-driven system consists of a subcritical reactor and a controllable external neutron source. The reactor in an accelerator-driven system can sustain fission reactions in a subcritical state using an external neutron source, which is an intrinsic safety feature of the system. The system can provide efficient transmutations of nuclear wastes such as minor actinides and long-lived fission products and generate electricity. Recently at Kyoto University Research Reactor Institute (KURRI; Kyoto, Japan), a series of reactor physics experiments was conducted with the Kyoto University Critical Assembly and a Cockcroft-Walton type accelerator, which generates the external neutron source by deuterium-tritium reactions. In this paper, neutronic analyses of a series of experiments have been re-estimated by using the latest Monte Carlo code and nuclear data libraries. This feasibility study is presented through the comparison of Monte Carlo simulation results with measurements.

  8. Empirical Analysis of Stochastic Volatility Model by Hybrid Monte Carlo Algorithm

    International Nuclear Information System (INIS)

    Takaishi, Tetsuya

    2013-01-01

    The stochastic volatility model is one of volatility models which infer latent volatility of asset returns. The Bayesian inference of the stochastic volatility (SV) model is performed by the hybrid Monte Carlo (HMC) algorithm which is superior to other Markov Chain Monte Carlo methods in sampling volatility variables. We perform the HMC simulations of the SV model for two liquid stock returns traded on the Tokyo Stock Exchange and measure the volatilities of those stock returns. Then we calculate the accuracy of the volatility measurement using the realized volatility as a proxy of the true volatility and compare the SV model with the GARCH model which is one of other volatility models. Using the accuracy calculated with the realized volatility we find that empirically the SV model performs better than the GARCH model.

  9. Evaluation of CASMO-3 and HELIOS for Fuel Assembly Analysis from Monte Carlo Code

    Energy Technology Data Exchange (ETDEWEB)

    Shim, Hyung Jin; Song, Jae Seung; Lee, Chung Chan

    2007-05-15

    This report presents a study comparing deterministic lattice physics calculations with Monte Carlo calculations for LWR fuel pin and assembly problems. The study has focused on comparing results from the lattice physics code CASMO-3 and HELIOS against those from the continuous-energy Monte Carlo code McCARD. The comparisons include k{sub inf}, isotopic number densities, and pin power distributions. The CASMO-3 and HELIOS calculations for the k{sub inf}'s of the LWR fuel pin problems show good agreement with McCARD within 956pcm and 658pcm, respectively. For the assembly problems with Gadolinia burnable poison rods, the largest difference between the k{sub inf}'s is 1463pcm with CASMO-3 and 1141pcm with HELIOS. RMS errors for the pin power distributions of CASMO-3 and HELIOS are within 1.3% and 1.5%, respectively.

  10. A numerical analysis of antithetic variates in Monte Carlo radiation transport with geometrical surface splitting

    International Nuclear Information System (INIS)

    Sarkar, P.K.; Prasad, M.A.

    1989-01-01

    A numerical study for effective implementation of the antithetic variates technique with geometric splitting/Russian roulette in Monte Carlo radiation transport calculations is presented. The study is based on the theory of Monte Carlo errors where a set of coupled integral equations are solved for the first and second moments of the score and for the expected number of flights per particle history. Numerical results are obtained for particle transmission through an infinite homogeneous slab shield composed of an isotropically scattering medium. Two types of antithetic transformations are considered. The results indicate that the antithetic transformations always lead to reduction in variance and increase in efficiency provided optimal antithetic parameters are chosen. A substantial gain in efficiency is obtained by incorporating antithetic transformations in rule of thumb splitting. The advantage gained for thick slabs (∼20 mfp) with low scattering probability (0.1-0.5) is attractively large . (author). 27 refs., 9 tabs

  11. Summary - COG: A new point-wise Monte Carlo code for burnup credit analysis

    International Nuclear Information System (INIS)

    Alesso, H.P.

    1989-01-01

    COG, a new point-wise Monte Carlo code being developed and tested at Lawrence Livermore National Laboratory (LLNL) for the Cray-1, solves the Boltzmann equation for the transport of neutrons, photons, and (in future versions) other particles. Techniques included in the code for modifying the random walk of particles make COG most suitable for solving deep-penetration (shielding) problems and a wide variety of criticality problems. COG is similar to a number of other computer codes used in the shielding community. Each code is a little different in its geometry input and its random-walk modification options. COG is a Monte Carlo code specifically designed for the CRAY (in 1986) to be as precise as the current state of physics knowledge. It has been extensively benchmarked and used as a shielding code at LLNL since 1986, and has recently been extended to accomplish criticality calculations. It will make an excellent tool for future shipping cask studies

  12. Single pin BWR benchmark problem for coupled Monte Carlo - Thermal hydraulics analysis

    International Nuclear Information System (INIS)

    Ivanov, A.; Sanchez, V.; Hoogenboom, J. E.

    2012-01-01

    As part of the European NURISP research project, a single pin BWR benchmark problem was defined. The aim of this initiative is to test the coupling strategies between Monte Carlo and subchannel codes developed by different project participants. In this paper the results obtained by the Delft Univ. of Technology and Karlsruhe Inst. of Technology will be presented. The benchmark problem was simulated with the following coupled codes: TRIPOLI-SUBCHANFLOW, MCNP-FLICA, MCNP-SUBCHANFLOW, and KENO-SUBCHANFLOW. (authors)

  13. Single pin BWR benchmark problem for coupled Monte Carlo - Thermal hydraulics analysis

    Energy Technology Data Exchange (ETDEWEB)

    Ivanov, A.; Sanchez, V. [Karlsruhe Inst. of Technology, Inst. for Neutron Physics and Reactor Technology, Herman-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen (Germany); Hoogenboom, J. E. [Delft Univ. of Technology, Faculty of Applied Sciences, Mekelweg 15, 2629 JB Delft (Netherlands)

    2012-07-01

    As part of the European NURISP research project, a single pin BWR benchmark problem was defined. The aim of this initiative is to test the coupling strategies between Monte Carlo and subchannel codes developed by different project participants. In this paper the results obtained by the Delft Univ. of Technology and Karlsruhe Inst. of Technology will be presented. The benchmark problem was simulated with the following coupled codes: TRIPOLI-SUBCHANFLOW, MCNP-FLICA, MCNP-SUBCHANFLOW, and KENO-SUBCHANFLOW. (authors)

  14. Analysis of Monte Carlo methods for the simulation of photon transport

    International Nuclear Information System (INIS)

    Carlsson, G.A.; Kusoffsky, L.

    1975-01-01

    In connection with the transport of low-energy photons (30 - 140 keV) through layers of water of different thicknesses, various aspects of Monte Carlo methods are examined in order to improve their effectivity (to produce statistically more reliable results with shorter computer times) and to bridge the gap between more physical methods and more mathematical ones. The calculations are compared with results of experiments involving the simulation of photon transport, using direct methods and collision density ones (J.S.)

  15. Taylor-series and Monte-Carlo-method uncertainty estimation of the width of a probability distribution based on varying bias and random error

    International Nuclear Information System (INIS)

    Wilson, Brandon M; Smith, Barton L

    2013-01-01

    Uncertainties are typically assumed to be constant or a linear function of the measured value; however, this is generally not true. Particle image velocimetry (PIV) is one example of a measurement technique that has highly nonlinear, time varying local uncertainties. Traditional uncertainty methods are not adequate for the estimation of the uncertainty of measurement statistics (mean and variance) in the presence of nonlinear, time varying errors. Propagation of instantaneous uncertainty estimates into measured statistics is performed allowing accurate uncertainty quantification of time-mean and statistics of measurements such as PIV. It is shown that random errors will always elevate the measured variance, and thus turbulent statistics such as u'u'-bar. Within this paper, nonlinear, time varying errors are propagated from instantaneous measurements into the measured mean and variance using the Taylor-series method. With these results and knowledge of the systematic and random uncertainty of each measurement, the uncertainty of the time-mean, the variance and covariance can be found. Applicability of the Taylor-series uncertainty equations to time varying systematic and random errors and asymmetric error distributions are demonstrated with Monte-Carlo simulations. The Taylor-series uncertainty estimates are always accurate for uncertainties on the mean quantity. The Taylor-series variance uncertainty is similar to the Monte-Carlo results for cases in which asymmetric random errors exist or the magnitude of the instantaneous variations in the random and systematic errors is near the ‘true’ variance. However, the Taylor-series method overpredicts the uncertainty in the variance as the instantaneous variations of systematic errors are large or are on the same order of magnitude as the ‘true’ variance. (paper)

  16. Monte Carlo simulation for uncertainty estimation on structural data in implicit 3-D geological modeling, a guide for disturbance distribution selection and parameterization

    Science.gov (United States)

    Pakyuz-Charrier, Evren; Lindsay, Mark; Ogarko, Vitaliy; Giraud, Jeremie; Jessell, Mark

    2018-04-01

    Three-dimensional (3-D) geological structural modeling aims to determine geological information in a 3-D space using structural data (foliations and interfaces) and topological rules as inputs. This is necessary in any project in which the properties of the subsurface matters; they express our understanding of geometries in depth. For that reason, 3-D geological models have a wide range of practical applications including but not restricted to civil engineering, the oil and gas industry, the mining industry, and water management. These models, however, are fraught with uncertainties originating from the inherent flaws of the modeling engines (working hypotheses, interpolator's parameterization) and the inherent lack of knowledge in areas where there are no observations combined with input uncertainty (observational, conceptual and technical errors). Because 3-D geological models are often used for impactful decision-making it is critical that all 3-D geological models provide accurate estimates of uncertainty. This paper's focus is set on the effect of structural input data measurement uncertainty propagation in implicit 3-D geological modeling. This aim is achieved using Monte Carlo simulation for uncertainty estimation (MCUE), a stochastic method which samples from predefined disturbance probability distributions that represent the uncertainty of the original input data set. MCUE is used to produce hundreds to thousands of altered unique data sets. The altered data sets are used as inputs to produce a range of plausible 3-D models. The plausible models are then combined into a single probabilistic model as a means to propagate uncertainty from the input data to the final model. In this paper, several improved methods for MCUE are proposed. The methods pertain to distribution selection for input uncertainty, sample analysis and statistical consistency of the sampled distribution. Pole vector sampling is proposed as a more rigorous alternative than dip vector

  17. Monte Carlo simulation for uncertainty estimation on structural data in implicit 3-D geological modeling, a guide for disturbance distribution selection and parameterization

    Directory of Open Access Journals (Sweden)

    E. Pakyuz-Charrier

    2018-04-01

    Full Text Available Three-dimensional (3-D geological structural modeling aims to determine geological information in a 3-D space using structural data (foliations and interfaces and topological rules as inputs. This is necessary in any project in which the properties of the subsurface matters; they express our understanding of geometries in depth. For that reason, 3-D geological models have a wide range of practical applications including but not restricted to civil engineering, the oil and gas industry, the mining industry, and water management. These models, however, are fraught with uncertainties originating from the inherent flaws of the modeling engines (working hypotheses, interpolator's parameterization and the inherent lack of knowledge in areas where there are no observations combined with input uncertainty (observational, conceptual and technical errors. Because 3-D geological models are often used for impactful decision-making it is critical that all 3-D geological models provide accurate estimates of uncertainty. This paper's focus is set on the effect of structural input data measurement uncertainty propagation in implicit 3-D geological modeling. This aim is achieved using Monte Carlo simulation for uncertainty estimation (MCUE, a stochastic method which samples from predefined disturbance probability distributions that represent the uncertainty of the original input data set. MCUE is used to produce hundreds to thousands of altered unique data sets. The altered data sets are used as inputs to produce a range of plausible 3-D models. The plausible models are then combined into a single probabilistic model as a means to propagate uncertainty from the input data to the final model. In this paper, several improved methods for MCUE are proposed. The methods pertain to distribution selection for input uncertainty, sample analysis and statistical consistency of the sampled distribution. Pole vector sampling is proposed as a more rigorous alternative than

  18. Wavelet analysis of nonstationary fluctuations of Monte Carlo-simulated excitatory postsynaptic currents.

    Science.gov (United States)

    Aristizabal, F; Glavinovic, M I

    2003-10-01

    Tracking spectral changes of rapidly varying signals is a demanding task. In this study, we explore on Monte Carlo-simulated glutamate-activated AMPA patch and synaptic currents whether a wavelet analysis offers such a possibility. Unlike Fourier methods that determine only the frequency content of a signal, the wavelet analysis determines both the frequency and the time. This is owing to the nature of the basis functions, which are infinite for Fourier transforms (sines and cosines are infinite), but are finite for wavelet analysis (wavelets are localized waves). In agreement with previous reports, the frequency of the stationary patch current fluctuations is higher for larger currents, whereas the mean-variance plots are parabolic. The spectra of the current fluctuations and mean-variance plots are close to the theoretically predicted values. The median frequency of the synaptic and nonstationary patch currents is, however, time dependent, though at the peak of synaptic currents, the median frequency is insensitive to the number of glutamate molecules released. Such time dependence demonstrates that the "composite spectra" of the current fluctuations gathered over the whole duration of synaptic currents cannot be used to assess the mean open time or effective mean open time of AMPA channels. The current (patch or synaptic) versus median frequency plots show hysteresis. The median frequency is thus not a simple reflection of the overall receptor saturation levels and is greater during the rise phase for the same saturation level. The hysteresis is due to the higher occupancy of the doubly bound state during the rise phase and not due to the spatial spread of the saturation disk, which remains remarkably constant. Albeit time dependent, the variance of the synaptic and nonstationary patch currents can be accurately determined. Nevertheless the evaluation of the number of AMPA channels and their single current from the mean-variance plots of patch or synaptic

  19. Neutron dose rate analysis on HTGR-10 reactor using Monte Carlo code

    Science.gov (United States)

    Suwoto; Adrial, H.; Hamzah, A.; Zuhair; Bakhri, S.; Sunaryo, G. R.

    2018-02-01

    The HTGR-10 reactor is cylinder-shaped core fuelled with kernel TRISO coated fuel particles in the spherical pebble with helium cooling system. The outlet helium gas coolant temperature outputted from the reactor core is designed to 700 °C. One advantage HTGR type reactor is capable of co-generation, as an addition to generating electricity, the reactor was designed to produce heat at high temperature can be used for other processes. The spherical fuel pebble contains 8335 TRISO UO2 kernel coated particles with enrichment of 10% and 17% are dispersed in a graphite matrix. The main purpose of this study was to analysis the distribution of neutron dose rates generated from HTGR-10 reactors. The calculation and analysis result of neutron dose rate in the HTGR-10 reactor core was performed using Monte Carlo MCNP5v1.6 code. The problems of double heterogeneity in kernel fuel coated particles TRISO and spherical fuel pebble in the HTGR-10 core are modelled well with MCNP5v1.6 code. The neutron flux to dose conversion factors taken from the International Commission on Radiological Protection (ICRP-74) was used to determine the dose rate that passes through the active core, reflectors, core barrel, reactor pressure vessel (RPV) and a biological shield. The calculated results of neutron dose rate with MCNP5v1.6 code using a conversion factor of ICRP-74 (2009) for radiation workers in the radial direction on the outside of the RPV (radial position = 220 cm from the center of the patio HTGR-10) provides the respective value of 9.22E-4 μSv/h and 9.58E-4 μSv/h for enrichment 10% and 17%, respectively. The calculated values of neutron dose rates are compliant with BAPETEN Chairman’s Regulation Number 4 Year 2013 on Radiation Protection and Safety in Nuclear Energy Utilization which sets the limit value for the average effective dose for radiation workers 20 mSv/year or 10μSv/h. Thus the protection and safety for radiation workers to be safe from the radiation source has

  20. MORSE Monte Carlo code

    International Nuclear Information System (INIS)

    Cramer, S.N.

    1984-01-01

    The MORSE code is a large general-use multigroup Monte Carlo code system. Although no claims can be made regarding its superiority in either theoretical details or Monte Carlo techniques, MORSE has been, since its inception at ORNL in the late 1960s, the most widely used Monte Carlo radiation transport code. The principal reason for this popularity is that MORSE is relatively easy to use, independent of any installation or distribution center, and it can be easily customized to fit almost any specific need. Features of the MORSE code are described

  1. Use of Monte Carlo analysis in a risk-based prioritization of toxic constituents in house dust.

    Science.gov (United States)

    Ginsberg, Gary L; Belleggia, Giuliana

    2017-12-01

    Many chemicals have been detected in house dust with exposures to the general public and particularly young children of potential health concern. House dust is also an indicator of chemicals present in consumer products and the built environment that may constitute a health risk. The current analysis compiles a database of recent house dust concentrations from the United States and Canada, focusing upon semi-volatile constituents. Seven constituents from the phthalate and flame retardant categories were selected for risk-based screening and prioritization: diethylhexyl phthalate (DEHP), butyl benzyl phthalate (BBzP), diisononyl phthalate (DINP), a pentabrominated diphenyl ether congener (BDE-99), hexabromocyclododecane (HBCDD), tris(1,3-dichloro-2-propyl) phosphate (TDCIPP) and tris(2-chloroethyl) phosphate (TCEP). Monte Carlo analysis was used to represent the variability in house dust concentration as well as the uncertainty in the toxicology database in the estimation of children's exposure and risk. Constituents were prioritized based upon the percentage of the distribution of risk results for cancer and non-cancer endpoints that exceeded a hazard quotient (HQ) of 1. The greatest percent HQ exceedances were for DEHP (cancer and non-cancer), BDE-99 (non-cancer) and TDCIPP (cancer). Current uses and the potential for reducing levels of these constituents in house dust are discussed. Exposure and risk for other phthalates and flame retardants in house dust may increase if they are used to substitute for these prioritized constituents. Therefore, alternative assessment and green chemistry solutions are important elements in decreasing children's exposure to chemicals of concern in the indoor environment. Copyright © 2017 Elsevier Ltd. All rights reserved.

  2. ANALYSIS OF MONTE CARLO SIMULATION SAMPLING TECHNIQUES ON SMALL SIGNAL STABILITY OF WIND GENERATOR- CONNECTED POWER SYSTEM

    Directory of Open Access Journals (Sweden)

    TEMITOPE RAPHAEL AYODELE

    2016-04-01

    Full Text Available Monte Carlo simulation using Simple Random Sampling (SRS technique is popularly known for its ability to handle complex uncertainty problems. However, to produce a reasonable result, it requires huge sample size. This makes it to be computationally expensive, time consuming and unfit for online power system applications. In this article, the performance of Latin Hypercube Sampling (LHS technique is explored and compared with SRS in term of accuracy, robustness and speed for small signal stability application in a wind generator-connected power system. The analysis is performed using probabilistic techniques via eigenvalue analysis on two standard networks (Single Machine Infinite Bus and IEEE 16–machine 68 bus test system. The accuracy of the two sampling techniques is determined by comparing their different sample sizes with the IDEAL (conventional. The robustness is determined based on a significant variance reduction when the experiment is repeated 100 times with different sample sizes using the two sampling techniques in turn. Some of the results show that sample sizes generated from LHS for small signal stability application produces the same result as that of the IDEAL values starting from 100 sample size. This shows that about 100 sample size of random variable generated using LHS method is good enough to produce reasonable results for practical purpose in small signal stability application. It is also revealed that LHS has the least variance when the experiment is repeated 100 times compared to SRS techniques. This signifies the robustness of LHS over that of SRS techniques. 100 sample size of LHS produces the same result as that of the conventional method consisting of 50000 sample size. The reduced sample size required by LHS gives it computational speed advantage (about six times over the conventional method.

  3. Comparison of the uncertainties calculated for the results of radiochemical determinations using the law of propagation of uncertainty and a Monte Carlo simulation

    International Nuclear Information System (INIS)

    Berne, A.

    2001-01-01

    Quantitative determinations of many radioactive analytes in environmental samples are based on a process in which several independent measurements of different properties are taken. The final results that are calculated using the data have to be evaluated for accuracy and precision. The estimate of the standard deviation, s, also called the combined standard uncertainty (CSU) associated with the result of this combined measurement can be used to evaluate the precision of the result. The CSU can be calculated by applying the law of propagation of uncertainty, which is based on the Taylor series expansion of the equation used to calculate the analytical result. The estimate of s can also be obtained from a Monte Carlo simulation. The data used in this simulation includes the values resulting from the individual measurements, the estimate of the variance of each value, including the type of distribution, and the equation used to calculate the analytical result. A comparison is made between these two methods of estimating the uncertainty of the calculated result. (author)

  4. Analysis of the HTTR with Monte-Carlo and diffusion theory. An IRI-ECN intercomparison

    International Nuclear Information System (INIS)

    De Haas, J.B.M.; Wallerbos, E.J.M.

    2000-09-01

    In the framework of the IAEA Co-ordinated Research Program (CRP) 'Evaluation of HTGR Performance' for the start-up core physics benchmark of the High Temperature Engineering Test Reactor (HTTR) two-group cross section data for a fuel compact lattice and for a two-dimensional R-Z model have been generated for comparison purposes. For this comparison, 5.2% enriched uranium was selected. Furthermore, a simplified core configuration utilising only the selected type of fuel has been analysed with both the Monte Carlo code KENO and with the diffusion theory codes BOLD VENTURE and PANTHER. With a very detailed KENO model of this simplified core, k eff was calculated to be 1.1278±0.0005. Homogenisation of the core region was seen to increase k eff by 0.0340 which can be attributed to streaming of neutrons in the detailed model. The difference in k eff between the homogenised models of KENO and BOLD VENTURE amounts then only,Δk =0.0025. The PANTHER result for this core is k eff = 1. 1251, which is in good agreement with the KENO result. The fully loaded core configuration, with a range of enrichments, has also been analysed with both KENO and BOLD VENTURE. In this case the homogenisation was seen to increase k eff by 0.0375 (streaming effect). In BOLD VENTURE the critical state could be reached by the insertion of the control rods through adding an effective 10 B density over the insertion depth while the streaming of neutrons was accounted for by adjustment of the diffusion coefficient. The generation time and the effective fraction of delayed neutrons in the critical state have been calculated to be 1.11 ms and 0.705 %, respectively. This yields a prompt decay constant at critical of 6.9 s -1 . The analysis with PANTHER resulted in a k eff =1.1595 and a critical control rod setting of 244.5 cm compared to the detailed KENO results of: k eff = 1.1600 and 234.5 cm, again an excellent agreement. 5 refs

  5. Analysis of the HTTR with Monte-Carlo and diffusion theory. An IRI-ECN intercomparison

    Energy Technology Data Exchange (ETDEWEB)

    De Haas, J.B.M. [Nuclear Research and Consultancy Group NRG, Petten (Netherlands); Wallerbos, E.J.M. [Interfaculty Reactor Institute IRI, Delft University of Technology, Delft (Netherlands)

    2000-09-01

    In the framework of the IAEA Co-ordinated Research Program (CRP) 'Evaluation of HTGR Performance' for the start-up core physics benchmark of the High Temperature Engineering Test Reactor (HTTR) two-group cross section data for a fuel compact lattice and for a two-dimensional R-Z model have been generated for comparison purposes. For this comparison, 5.2% enriched uranium was selected. Furthermore, a simplified core configuration utilising only the selected type of fuel has been analysed with both the Monte Carlo code KENO and with the diffusion theory codes BOLD VENTURE and PANTHER. With a very detailed KENO model of this simplified core, k{sub eff} was calculated to be 1.1278{+-}0.0005. Homogenisation of the core region was seen to increase k{sub eff} by 0.0340 which can be attributed to streaming of neutrons in the detailed model. The difference in k{sub eff} between the homogenised models of KENO and BOLD VENTURE amounts then only,{delta}k =0.0025. The PANTHER result for this core is k{sub eff} = 1. 1251, which is in good agreement with the KENO result. The fully loaded core configuration, with a range of enrichments, has also been analysed with both KENO and BOLD VENTURE. In this case the homogenisation was seen to increase k{sub eff} by 0.0375 (streaming effect). In BOLD VENTURE the critical state could be reached by the insertion of the control rods through adding an effective {sup 10}B density over the insertion depth while the streaming of neutrons was accounted for by adjustment of the diffusion coefficient. The generation time and the effective fraction of delayed neutrons in the critical state have been calculated to be 1.11 ms and 0.705 %, respectively. This yields a prompt decay constant at critical of 6.9 s{sup -1}. The analysis with PANTHER resulted in a k{sub eff} =1.1595 and a critical control rod setting of 244.5 cm compared to the detailed KENO results of: k{sub eff} = 1.1600 and 234.5 cm, again an excellent agreement. 5 refs.

  6. The MC21 Monte Carlo Transport Code

    International Nuclear Information System (INIS)

    Sutton TM; Donovan TJ; Trumbull TH; Dobreff PS; Caro E; Griesheimer DP; Tyburski LJ; Carpenter DC; Joo H

    2007-01-01

    MC21 is a new Monte Carlo neutron and photon transport code currently under joint development at the Knolls Atomic Power Laboratory and the Bettis Atomic Power Laboratory. MC21 is the Monte Carlo transport kernel of the broader Common Monte Carlo Design Tool (CMCDT), which is also currently under development. The vision for CMCDT is to provide an automated, computer-aided modeling and post-processing environment integrated with a Monte Carlo solver that is optimized for reactor analysis. CMCDT represents a strategy to push the Monte Carlo method beyond its traditional role as a benchmarking tool or ''tool of last resort'' and into a dominant design role. This paper describes various aspects of the code, including the neutron physics and nuclear data treatments, the geometry representation, and the tally and depletion capabilities

  7. Variational Monte Carlo Technique

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 19; Issue 8. Variational Monte Carlo Technique: Ground State Energies of Quantum Mechanical Systems. Sukanta Deb. General Article Volume 19 Issue 8 August 2014 pp 713-739 ...

  8. Monte Carlo analysis of the Neutron Standards Laboratory of the CIEMAT; Analisis Monte Carlo del Laboratorio de Patrones Neutronicos del CIEMAT

    Energy Technology Data Exchange (ETDEWEB)

    Vega C, H. R. [Universidad Autonoma de Zacatecas, Unidad Academica de Estudios Nucleares, Cipres No. 10, Fracc. La Penuela, 98068 Zacatecas (Mexico); Mendez V, R. [Centro de Investigaciones Energeticas, Medioambientales y Tecnologicas, Av. Complutense 40, 28040 Madrid (Spain); Guzman G, K. A., E-mail: fermineutron@yahoo.com [Universidad Politecnica de Madrid, Departamento de Ingenieria Nuclear, C. Jose Gutierrez Abascal 2, 28006 Madrid (Spain)

    2014-10-15

    By means of Monte Carlo methods was characterized the neutrons field produced by calibration sources in the Neutron Standards Laboratory of the Centro de Investigaciones Energeticas, Medioambientales y Tecnologicas (CIEMAT). The laboratory has two neutron calibration sources: {sup 241}AmBe and {sup 252}Cf which are stored in a water pool and are placed on the calibration bench using controlled systems at distance. To characterize the neutrons field was built a three-dimensional model of the room where it was included the stainless steel bench, the irradiation table and the storage pool. The sources model included double encapsulated of steel, as cladding. With the purpose of determining the effect that produces the presence of the different components of the room, during the characterization the neutrons spectra, the total flow and the rapidity of environmental equivalent dose to 100 cm of the source were considered. The presence of the walls, floor and ceiling of the room is causing the most modification in the spectra and the integral values of the flow and the rapidity of environmental equivalent dose. (Author)

  9. Statistical analysis for discrimination of prompt gamma ray peak induced by high energy neutron: Monte Carlo simulation study

    International Nuclear Information System (INIS)

    Do-Kun Yoon; Joo-Young Jung; Tae Suk Suh; Seong-Min Han

    2015-01-01

    The purpose of this research is a statistical analysis for discrimination of prompt gamma ray peak induced by the 14.1 MeV neutron particles from spectra using Monte Carlo simulation. For the simulation, the information of 18 detector materials was used to simulate spectra by the neutron capture reaction. The discrimination of nine prompt gamma ray peaks from the simulation of each detector material was performed. We presented the several comparison indexes of energy resolution performance depending on the detector material using the simulation and statistics for the prompt gamma activation analysis. (author)

  10. Probabilistic physics-of-failure models for component reliabilities using Monte Carlo simulation and Weibull analysis: a parametric study

    International Nuclear Information System (INIS)

    Hall, P.L.; Strutt, J.E.

    2003-01-01

    In reliability engineering, component failures are generally classified in one of three ways: (1) early life failures; (2) failures having random onset times; and (3) late life or 'wear out' failures. When the time-distribution of failures of a population of components is analysed in terms of a Weibull distribution, these failure types may be associated with shape parameters β having values 1 respectively. Early life failures are frequently attributed to poor design (e.g. poor materials selection) or problems associated with manufacturing or assembly processes. We describe a methodology for the implementation of physics-of-failure models of component lifetimes in the presence of parameter and model uncertainties. This treats uncertain parameters as random variables described by some appropriate statistical distribution, which may be sampled using Monte Carlo methods. The number of simulations required depends upon the desired accuracy of the predicted lifetime. Provided that the number of sampled variables is relatively small, an accuracy of 1-2% can be obtained using typically 1000 simulations. The resulting collection of times-to-failure are then sorted into ascending order and fitted to a Weibull distribution to obtain a shape factor β and a characteristic life-time η. Examples are given of the results obtained using three different models: (1) the Eyring-Peck (EP) model for corrosion of printed circuit boards; (2) a power-law corrosion growth (PCG) model which represents the progressive deterioration of oil and gas pipelines; and (3) a random shock-loading model of mechanical failure. It is shown that for any specific model the values of the Weibull shape parameters obtained may be strongly dependent on the degree of uncertainty of the underlying input parameters. Both the EP and PCG models can yield a wide range of values of β, from β>1, characteristic of wear-out behaviour, to β<1, characteristic of early-life failure, depending on the degree of

  11. Monte Carlo - Advances and Challenges

    International Nuclear Information System (INIS)

    Brown, Forrest B.; Mosteller, Russell D.; Martin, William R.

    2008-01-01

    Abstract only, full text follows: With ever-faster computers and mature Monte Carlo production codes, there has been tremendous growth in the application of Monte Carlo methods to the analysis of reactor physics and reactor systems. In the past, Monte Carlo methods were used primarily for calculating k eff of a critical system. More recently, Monte Carlo methods have been increasingly used for determining reactor power distributions and many design parameters, such as β eff , l eff , τ, reactivity coefficients, Doppler defect, dominance ratio, etc. These advanced applications of Monte Carlo methods are now becoming common, not just feasible, but bring new challenges to both developers and users: Convergence of 3D power distributions must be assured; confidence interval bias must be eliminated; iterated fission probabilities are required, rather than single-generation probabilities; temperature effects including Doppler and feedback must be represented; isotopic depletion and fission product buildup must be modeled. This workshop focuses on recent advances in Monte Carlo methods and their application to reactor physics problems, and on the resulting challenges faced by code developers and users. The workshop is partly tutorial, partly a review of the current state-of-the-art, and partly a discussion of future work that is needed. It should benefit both novice and expert Monte Carlo developers and users. In each of the topic areas, we provide an overview of needs, perspective on past and current methods, a review of recent work, and discussion of further research and capabilities that are required. Electronic copies of all workshop presentations and material will be available. The workshop is structured as 2 morning and 2 afternoon segments: - Criticality Calculations I - convergence diagnostics, acceleration methods, confidence intervals, and the iterated fission probability, - Criticality Calculations II - reactor kinetics parameters, dominance ratio, temperature

  12. Application of direct simulation Monte Carlo method for analysis of AVLIS evaporation process

    International Nuclear Information System (INIS)

    Nishimura, Akihiko

    1995-01-01

    The computation code of the direct simulation Monte Carlo (DSMC) method was developed in order to analyze the atomic vapor evaporation in atomic vapor laser isotope separation (AVLIS). The atomic excitation temperatures of gadolinium atom were calculated for the model with five low lying states. Calculation results were compared with the experiments obtained by laser absorption spectroscopy. Two types of DSMC simulations which were different in inelastic collision procedure were carried out. It was concluded that the energy transfer was forbidden unless the total energy of the colliding atoms exceeds a threshold value. (author)

  13. A reliability analysis framework with Monte Carlo simulation for weld structure of crane's beam

    Science.gov (United States)

    Wang, Kefei; Xu, Hongwei; Qu, Fuzheng; Wang, Xin; Shi, Yanjun

    2018-04-01

    The reliability of the crane product in engineering is the core competitiveness of the product. This paper used Monte Carlo method analyzed the reliability of the weld metal structure of the bridge crane whose limit state function is mathematical expression. Then we obtained the minimum reliable welding feet height value for the welds between cover plate and web plate on main beam in different coefficients of variation. This paper provides a new idea and reference for the growth of the inherent reliability of crane.

  14. Variance analysis of the Monte-Carlo perturbation source method in inhomogeneous linear particle transport problems

    International Nuclear Information System (INIS)

    Noack, K.

    1982-01-01

    The perturbation source method may be a powerful Monte-Carlo means to calculate small effects in a particle field. In a preceding paper we have formulated this methos in inhomogeneous linear particle transport problems describing the particle fields by solutions of Fredholm integral equations and have derived formulae for the second moment of the difference event point estimator. In the present paper we analyse the general structure of its variance, point out the variance peculiarities, discuss the dependence on certain transport games and on generation procedures of the auxiliary particles and draw conclusions to improve this method

  15. Analysis of skin tissues spatial fluorescence distribution by the Monte Carlo simulation

    International Nuclear Information System (INIS)

    Churmakov, D Y; Meglinski, I V; Piletsky, S A; Greenhalgh, D A

    2003-01-01

    A novel Monte Carlo technique of simulation of spatial fluorescence distribution within the human skin is presented. The computational model of skin takes into account the spatial distribution of fluorophores, which would arise due to the structure of collagen fibres, compared to the epidermis and stratum corneum where the distribution of fluorophores is assumed to be homogeneous. The results of simulation suggest that distribution of auto-fluorescence is significantly suppressed in the near-infrared spectral region, whereas the spatial distribution of fluorescence sources within a sensor layer embedded in the epidermis is localized at an 'effective' depth

  16. Analysis of skin tissues spatial fluorescence distribution by the Monte Carlo simulation

    Energy Technology Data Exchange (ETDEWEB)

    Churmakov, D Y [School of Engineering, Cranfield University, Cranfield, MK43 0AL (United Kingdom); Meglinski, I V [School of Engineering, Cranfield University, Cranfield, MK43 0AL (United Kingdom); Piletsky, S A [Institute of BioScience and Technology, Cranfield University, Silsoe, MK45 4DT (United Kingdom); Greenhalgh, D A [School of Engineering, Cranfield University, Cranfield, MK43 0AL (United Kingdom)

    2003-07-21

    A novel Monte Carlo technique of simulation of spatial fluorescence distribution within the human skin is presented. The computational model of skin takes into account the spatial distribution of fluorophores, which would arise due to the structure of collagen fibres, compared to the epidermis and stratum corneum where the distribution of fluorophores is assumed to be homogeneous. The results of simulation suggest that distribution of auto-fluorescence is significantly suppressed in the near-infrared spectral region, whereas the spatial distribution of fluorescence sources within a sensor layer embedded in the epidermis is localized at an 'effective' depth.

  17. Analysis of skin tissues spatial fluorescence distribution by the Monte Carlo simulation

    Science.gov (United States)

    Y Churmakov, D.; Meglinski, I. V.; Piletsky, S. A.; Greenhalgh, D. A.

    2003-07-01

    A novel Monte Carlo technique of simulation of spatial fluorescence distribution within the human skin is presented. The computational model of skin takes into account the spatial distribution of fluorophores, which would arise due to the structure of collagen fibres, compared to the epidermis and stratum corneum where the distribution of fluorophores is assumed to be homogeneous. The results of simulation suggest that distribution of auto-fluorescence is significantly suppressed in the near-infrared spectral region, whereas the spatial distribution of fluorescence sources within a sensor layer embedded in the epidermis is localized at an `effective' depth.

  18. Analysis of aerial survey data on Florida manatee using Markov chain Monte Carlo.

    Science.gov (United States)

    Craig, B A; Newton, M A; Garrott, R A; Reynolds, J E; Wilcox, J R

    1997-06-01

    We assess population trends of the Atlantic coast population of Florida manatee, Trichechus manatus latirostris, by reanalyzing aerial survey data collected between 1982 and 1992. To do so, we develop an explicit biological model that accounts for the method by which the manatees are counted, the mammals' movement between surveys, and the behavior of the population total over time. Bayesian inference, enabled by Markov chain Monte Carlo, is used to combine the survey data with the biological model. We compute marginal posterior distributions for all model parameters and predictive distributions for future counts. Several conclusions, such as a decreasing population growth rate and low sighting probabilities, are consistent across different prior specifications.

  19. Damage flux analysis. Solid state detector and Monte-Carlo calculation

    International Nuclear Information System (INIS)

    Genthon, J.P.; Nimal, J.C.; Vergnaud, T.

    1975-09-01

    The change of resistivity induced by radiation in materials is particularly suitable for the measurement of equivalent damage fluxes, when it is used at low fluence for calibration of more classical activation reactions used at high fluences. A graphite and a tungsten detector are briefly described and results obtained in a good number of European reactors are given. The polykinetic three dimensional Monte-Carlo code Tripoli is used for calculation of damage fluxes. Comparison with above measurements shows a good agreement and confirms the use of the EURATOM damaging function for graphite [fr

  20. A Newton-based Jacobian-free approach for neutronic-Monte Carlo/thermal-hydraulic static coupled analysis

    International Nuclear Information System (INIS)

    Mylonakis, Antonios G.; Varvayanni, M.; Catsaros, N.

    2017-01-01

    Highlights: •A Newton-based Jacobian-free Monte Carlo/thermal-hydraulic coupling approach is introduced. •OpenMC is coupled with COBRA-EN with a Newton-based approach. •The introduced coupling approach is tested in numerical experiments. •The performance of the new approach is compared with the traditional “serial” coupling approach. -- Abstract: In the field of nuclear reactor analysis, multi-physics calculations that account for the bonded nature of the neutronic and thermal-hydraulic phenomena are of major importance for both reactor safety and design. So far in the context of Monte-Carlo neutronic analysis a kind of “serial” algorithm has been mainly used for coupling with thermal-hydraulics. The main motivation of this work is the interest for an algorithm that could maintain the distinct treatment of the involved fields within a tight coupling context that could be translated into higher convergence rates and more stable behaviour. This work investigates the possibility of replacing the usually used “serial” iteration with an approximate Newton algorithm. The selected algorithm, called Approximate Block Newton, is actually a version of the Jacobian-free Newton Krylov method suitably modified for coupling mono-disciplinary solvers. Within this Newton scheme the linearised system is solved with a Krylov solver in order to avoid the creation of the Jacobian matrix. A coupling algorithm between Monte-Carlo neutronics and thermal-hydraulics based on the above-mentioned methodology is developed and its performance is analysed. More specifically, OpenMC, a Monte-Carlo neutronics code and COBRA-EN, a thermal-hydraulics code for sub-channel and core analysis, are merged in a coupling scheme using the Approximate Block Newton method aiming to examine the performance of this scheme and compare with that of the “traditional” serial iterative scheme. First results show a clear improvement of the convergence especially in problems where significant

  1. Validation and verification of the ORNL Monte Carlo codes for nuclear safety analysis

    International Nuclear Information System (INIS)

    Emmett, M.B.

    1993-01-01

    The process of ensuring the quality of computer codes can be very time consuming and expensive. The Oak Ridge National Laboratory (ORNL) Monte Carlo codes all predate the existence of quality assurance (QA) standards and configuration control. The number of person-years and the amount of money spent on code development make it impossible to adhere strictly to all the current requirements. At ORNL, the Nuclear Engineering Applications Section of the Computing Applications Division is responsible for the development, maintenance, and application of the Monte Carlo codes MORSE and KENO. The KENO code is used for doing criticality analyses; the MORSE code, which has two official versions, CGA and SGC, is used for radiation transport analyses. Because KENO and MORSE were very thoroughly checked out over the many years of extensive use both in the United States and in the international community, the existing codes were open-quotes baselined.close quotes This means that the versions existing at the time the original configuration plan is written are considered to be validated and verified code systems based on the established experience with them

  2. Analysis and modeling of localized heat generation by tumor-targeted nanoparticles (Monte Carlo methods)

    Science.gov (United States)

    Sanattalab, Ehsan; SalmanOgli, Ahmad; Piskin, Erhan

    2016-04-01

    We investigated the tumor-targeted nanoparticles that influence heat generation. We suppose that all nanoparticles are fully functionalized and can find the target using active targeting methods. Unlike the commonly used methods, such as chemotherapy and radiotherapy, the treatment procedure proposed in this study is purely noninvasive, which is considered to be a significant merit. It is found that the localized heat generation due to targeted nanoparticles is significantly higher than other areas. By engineering the optical properties of nanoparticles, including scattering, absorption coefficients, and asymmetry factor (cosine scattering angle), the heat generated in the tumor's area reaches to such critical state that can burn the targeted tumor. The amount of heat generated by inserting smart agents, due to the surface Plasmon resonance, will be remarkably high. The light-matter interactions and trajectory of incident photon upon targeted tissues are simulated by MIE theory and Monte Carlo method, respectively. Monte Carlo method is a statistical one by which we can accurately probe the photon trajectories into a simulation area.

  3. Perturbation based Monte Carlo criticality search in density, enrichment and concentration

    International Nuclear Information System (INIS)

    Li, Zeguang; Wang, Kan; Deng, Jingkang

    2015-01-01

    Highlights: • A new perturbation based Monte Carlo criticality search method is proposed. • The method could get accurate results with only one individual criticality run. • The method is used to solve density, enrichment and concentration search problems. • Results show the feasibility and good performances of this method. • The relationship between results’ accuracy and perturbation order is discussed. - Abstract: Criticality search is a very important aspect in reactor physics analysis. Due to the advantages of Monte Carlo method and the development of computer technologies, Monte Carlo criticality search is becoming more and more necessary and feasible. Existing Monte Carlo criticality search methods need large amount of individual criticality runs and may have unstable results because of the uncertainties of criticality results. In this paper, a new perturbation based Monte Carlo criticality search method is proposed and discussed. This method only needs one individual criticality calculation with perturbation tallies to estimate k eff changing function using initial k eff and differential coefficients results, and solves polynomial equations to get the criticality search results. The new perturbation based Monte Carlo criticality search method is implemented in the Monte Carlo code RMC, and criticality search problems in density, enrichment and concentration are taken out. Results show that this method is quite inspiring in accuracy and efficiency, and has advantages compared with other criticality search methods

  4. Oxygen distribution in tumors: A qualitative analysis and modeling study providing a novel Monte Carlo approach

    International Nuclear Information System (INIS)

    Lagerlöf, Jakob H.; Kindblom, Jon; Bernhardt, Peter

    2014-01-01

    Purpose: To construct a Monte Carlo (MC)-based simulation model for analyzing the dependence of tumor oxygen distribution on different variables related to tumor vasculature [blood velocity, vessel-to-vessel proximity (vessel proximity), and inflowing oxygen partial pressure (pO 2 )]. Methods: A voxel-based tissue model containing parallel capillaries with square cross-sections (sides of 10 μm) was constructed. Green's function was used for diffusion calculations and Michaelis-Menten's kinetics to manage oxygen consumption. The model was tuned to approximately reproduce the oxygenational status of a renal carcinoma; the depth oxygenation curves (DOC) were fitted with an analytical expression to facilitate rapid MC simulations of tumor oxygen distribution. DOCs were simulated with three variables at three settings each (blood velocity, vessel proximity, and inflowing pO 2 ), which resulted in 27 combinations of conditions. To create a model that simulated variable oxygen distributions, the oxygen tension at a specific point was randomly sampled with trilinear interpolation in the dataset from the first simulation. Six correlations between blood velocity, vessel proximity, and inflowing pO 2 were hypothesized. Variable models with correlated parameters were compared to each other and to a nonvariable, DOC-based model to evaluate the differences in simulated oxygen distributions and tumor radiosensitivities for different tumor sizes. Results: For tumors with radii ranging from 5 to 30 mm, the nonvariable DOC model tended to generate normal or log-normal oxygen distributions, with a cut-off at zero. The pO 2 distributions simulated with the six-variable DOC models were quite different from the distributions generated with the nonvariable DOC model; in the former case the variable models simulated oxygen distributions that were more similar to in vivo results found in the literature. For larger tumors, the oxygen distributions became truncated in the lower

  5. Monte Carlo codes and Monte Carlo simulator program

    International Nuclear Information System (INIS)

    Higuchi, Kenji; Asai, Kiyoshi; Suganuma, Masayuki.

    1990-03-01

    Four typical Monte Carlo codes KENO-IV, MORSE, MCNP and VIM have been vectorized on VP-100 at Computing Center, JAERI. The problems in vector processing of Monte Carlo codes on vector processors have become clear through the work. As the result, it is recognized that these are difficulties to obtain good performance in vector processing of Monte Carlo codes. A Monte Carlo computing machine, which processes the Monte Carlo codes with high performances is being developed at our Computing Center since 1987. The concept of Monte Carlo computing machine and its performance have been investigated and estimated by using a software simulator. In this report the problems in vectorization of Monte Carlo codes, Monte Carlo pipelines proposed to mitigate these difficulties and the results of the performance estimation of the Monte Carlo computing machine by the simulator are described. (author)

  6. Monte Carlo simulation of expert judgments on human errors in chemical analysis--a case study of ICP-MS.

    Science.gov (United States)

    Kuselman, Ilya; Pennecchi, Francesca; Epstein, Malka; Fajgelj, Ales; Ellison, Stephen L R

    2014-12-01

    Monte Carlo simulation of expert judgments on human errors in a chemical analysis was used for determination of distributions of the error quantification scores (scores of likelihood and severity, and scores of effectiveness of a laboratory quality system in prevention of the errors). The simulation was based on modeling of an expert behavior: confident, reasonably doubting and irresolute expert judgments were taken into account by means of different probability mass functions (pmfs). As a case study, 36 scenarios of human errors which may occur in elemental analysis of geological samples by ICP-MS were examined. Characteristics of the score distributions for three pmfs of an expert behavior were compared. Variability of the scores, as standard deviation of the simulated score values from the distribution mean, was used for assessment of the score robustness. A range of the score values, calculated directly from elicited data and simulated by a Monte Carlo method for different pmfs, was also discussed from the robustness point of view. It was shown that robustness of the scores, obtained in the case study, can be assessed as satisfactory for the quality risk management and improvement of a laboratory quality system against human errors. Copyright © 2014 Elsevier B.V. All rights reserved.

  7. Asymptotic analysis of the spatial discretization of radiation absorption and re-emission in Implicit Monte Carlo

    International Nuclear Information System (INIS)

    Densmore, Jeffery D.

    2011-01-01

    We perform an asymptotic analysis of the spatial discretization of radiation absorption and re-emission in Implicit Monte Carlo (IMC), a Monte Carlo technique for simulating nonlinear radiative transfer. Specifically, we examine the approximation of absorption and re-emission by a spatially continuous artificial-scattering process and either a piecewise-constant or piecewise-linear emission source within each spatial cell. We consider three asymptotic scalings representing (i) a time step that resolves the mean-free time, (ii) a Courant limit on the time-step size, and (iii) a fixed time step that does not depend on any asymptotic scaling. For the piecewise-constant approximation, we show that only the third scaling results in a valid discretization of the proper diffusion equation, which implies that IMC may generate inaccurate solutions with optically large spatial cells if time steps are refined. However, we also demonstrate that, for a certain class of problems, the piecewise-linear approximation yields an appropriate discretized diffusion equation under all three scalings. We therefore expect IMC to produce accurate solutions for a wider range of time-step sizes when the piecewise-linear instead of piecewise-constant discretization is employed. We demonstrate the validity of our analysis with a set of numerical examples.

  8. Monte Carlo analysis of the effects of penetrations on the performance of a tokamak fusion reactor

    International Nuclear Information System (INIS)

    Santoro, R.T.; Tang, J.S.; Alsmiller, R.G. Jr.; Barnes, J.M.

    1977-01-01

    Adjoint Monte Carlo calculations have been carried out to estimate the nuclear heating and radiation damage in the toroidal field (TF) coils adjacent to a 28 x 68 cm 2 rectangular neutral beam injector duct that passes through the blanket and shield of a D-T burning Tokamak reactor. The plasma region, blanket, shield, and TF coils were represented in cylindrical geometry using the same dimensions and compositions as those of the Experimental Power Reactor. The radiation transport was accomplished using coupled 35-group neutron, 21-group gamma-ray cross sections and the nuclear heating and radiation damage were obtained using the latest available response functions. The presence of the neutral beam injector duct leads to increases in the nuclear heating rates in the TF coils ranging from a factor of 3 to a factor of 196 greater than in the fully shielded coils depending on the location. Substantial increases in the radation damage were also noted

  9. Nonlinear Stochastic stability analysis of Wind Turbine Wings by Monte Carlo Simulations

    DEFF Research Database (Denmark)

    Larsen, Jesper Winther; Iwankiewiczb, R.; Nielsen, Søren R.K.

    2007-01-01

    and inertial contributions. A reduced two-degrees-of-freedom modal expansion is used specifying the modal coordinate of the fundamental blade and edgewise fixed base eigenmodes of the beam. The rotating beam is subjected to harmonic and narrow-banded support point motion from the nacelle displacement...... under narrow-banded excitation, and it is shown that the qualitative behaviour of the strange attractor is very similar for the periodic and almost periodic responses, whereas the strange attractor for the chaotic case loses structure as the excitation becomes narrow-banded. Furthermore......, the characteristic behaviour of the strange attractor is shown to be identifiable by the so-called information dimension. Due to the complexity of the coupled nonlinear structural system all analyses are carried out via Monte Carlo simulations....

  10. Monte Carlo analysis of TRX lattices with ENDF/B version 3 data

    International Nuclear Information System (INIS)

    Hardy, J. Jr.

    1975-01-01

    Four TRX water-moderated lattices of slightly enriched uranium rods have been reanalyzed with consistent ENDF/B Version 3 data by means of the full-range Monte Carlo program RECAP. The following measured lattice parameters were studied: ratio of epithermal-to-thermal 238 U capture, ratio of epithermal-to-thermal 235 U fissions, ration of 238 U captures to 235 U fissions, ratio of 238 U fissions to 235 U fissions, and multiplication factor. In addition to the base calculations, some studies were done to find sensitivity of the TRX lattice parameters to selected variations of cross section data. Finally, additional experimental evidence is afforded by effective 238 U capture integrals for isolated rods. Shielded capture integrals were calculated for 238 U metal and oxide rods. These are compared with other measurements

  11. Optimization of a pinhole collimator in a SPECT scintillating fiber detector system: a Monte Carlo analysis

    International Nuclear Information System (INIS)

    Hademenos, G.J.

    1994-01-01

    Monte Carlo simulations were used to optimize the dimensions of a lead pinhole collimator in a photon emission computed tomography (SPECT) system consisting of a line of equally spaced Tc-99m point sources and a plastic scintillating fiber detector. The optimization was performed by evaluating the spatial resolution and scanner sensitivity for each source distribution location and collimator parameter variation. An optimal spatial resolution of 0.43 cm FWHM was observed for a source distribution positioned 2.0 cm from the collimated scintillating fiber detection system with a pinhole radius of 1.0 mm and a collimator thickness of 3.0 cm for a 10,000 emission photon simulation. The optimal sensitivity occurred for a source distance of 2.0 cm, a radius of 3.0 mm and a thickness of 3.0 cm. (author)

  12. Analysis of QUADOS problem on TLD-ALBEDO personal dosemeter responses using discrete ordinates and Monte Carlo methods

    International Nuclear Information System (INIS)

    Kodeli, I.; Tanner, R.

    2005-01-01

    In the scope of QUADOS, a Concerted Action of the European Commission, eight calculational problems were prepared in order to evaluate the use of computational codes for dosimetry in radiation protection and medical physics, and to disseminate 'good practice' throughout the radiation dosimetry community. This paper focuses on the analysis of the P4 problem on the 'TLD-albedo dosemeter: neutron and/or photon response of a four-element TL-dosemeter mounted on a standard ISO slab phantom'. Altogether 17 solutions were received from the participants, 14 of those transported neutrons and 15 photons. Most participants (16 out of 17) used Monte Carlo methods. These calculations are time-consuming, requiring several days of CPU time to perform the whole set of calculations and achieve good statistical precision. The possibility of using deterministic discrete ordinates codes as an alternative to Monte Carlo was therefore investigated and is presented here. In particular the capacity of the adjoint mode calculations is shown. (authors)

  13. Monte carlo simulation for soot dynamics

    KAUST Repository

    Zhou, Kun

    2012-01-01

    A new Monte Carlo method termed Comb-like frame Monte Carlo is developed to simulate the soot dynamics. Detailed stochastic error analysis is provided. Comb-like frame Monte Carlo is coupled with the gas phase solver Chemkin II to simulate soot formation in a 1-D premixed burner stabilized flame. The simulated soot number density, volume fraction, and particle size distribution all agree well with the measurement available in literature. The origin of the bimodal distribution of particle size distribution is revealed with quantitative proof.

  14. Uncertainty evaluation of the kerma in the air, related to the active volume in the ionization chamber of concentric cylinders, by Monte Carlo simulation; Avaliacao de incerteza no kerma no ar, em relacao ao volume ativo da camara de ionizacao de cilindros concentricos, por simulacao de Monte Carlo

    Energy Technology Data Exchange (ETDEWEB)

    Lo Bianco, A.S.; Oliveira, H.P.S.; Peixoto, J.G.P., E-mail: abianco@ird.gov.b [Instituto de Radioprotecao e Dosimetria (IRD/CNEN-RJ), Rio de Janeiro, RJ (Brazil). Lab. Nacional de Metrologia das Radiacoes Ionizantes (LNMRI)

    2009-07-01

    To implant the primary standard of the magnitude kerma in the air for X-ray between 10 - 50 keV, the National Metrology Laboratory of Ionizing Radiations (LNMRI) must evaluate all the uncertainties of measurement related with Victtoren chamber. So, it was evaluated the uncertainty of the kerma in the air consequent of the inaccuracy in the active volume of the chamber using the calculation of Monte Carlo as a tool through the Penelope software

  15. Monte Carlo analysis of experiments on the reactivity temperature coefficient for UO2 and MOX light water moderated lattices

    International Nuclear Information System (INIS)

    Erradi, L.; Chetaine, A.; Chakir, E.; Kharchaf, A.; Elbardouni, T.; Elkhoukhi, T.

    2005-01-01

    In a previous work, we have analysed the main French experiments available on the reactivity temperature coefficient (RTC): CREOLE and MISTRAL experiments. In these experiments, the RTC has been measured in both UO 2 and UO 2 -PuO 2 PWR type lattices. Our calculations, using APOLLO2 code with CEA93 library based on JEF2.2 evaluation, have shown that the calculation error in UO 2 lattices is less than 1 pcm/C degrees which is considered as the target accuracy. On the other hand the calculation error in the MOX lattices is more significant in both low and high temperature ranges: an average error of -2 ± 0.5 pcm/C degrees is observed in low temperatures and an error of +3 ± 2 pcm/C degrees is obtained for temperatures higher than 250 C degrees. In the present work, we analysed additional experimental benchmarks on the RTC of UO 2 and MOX light water moderated lattices. To analyze these benchmarks and with the aim of minimizing uncertainties related to modelling of the experimental set up, we chose the Monte Carlo method which has the advantage of taking into account in the most exact manner the geometry of the experimental configurations. This analysis shows for the UO 2 lattices, a maximum experiment-calculation deviation of about 0,7 pcm/C degrees, which is below the target accuracy for this type of lattices. For the KAMINI experiment, which relates to the measurement of the RTC in a light water moderated lattice using U-233 as fuel our analysis shows that the ENDF/B6 library gives the best result, with an experiment-calculation deviation of the order of -0,16 pcm/C degrees. The analysis of the benchmarks using MOX fuel made it possible to highlight a discrepancy between experiment and calculation on the RTC of about -0.7 pcm/C degrees (for a range of temperatures going from 20 to 248 C degrees) and -1,2 pcm/C degrees (for a range of temperatures going from 20 to 80 C degrees). This result, in particular the tendency which has the error to decrease when the

  16. Investigation of Reduction of the Uncertainty of Monte Carlo Dose Calculations in Oncor® Clinical Linear Accelerator Simulation Using the DBS Variance Reduction Technique in Monte Carlo Code BEAMnrc

    Directory of Open Access Journals (Sweden)

    Amin Asadi

    2017-10-01

    Full Text Available Purpose: To study the benefits of Directional Bremsstrahlung Splitting (DBS dose variance reduction technique in BEAMnrc Monte Carlo (MC code for Oncor® linac at 6MV and 18MV energies. Materials and Method: A MC model of Oncor® linac was built using BEAMnrc MC Code and verified by the measured data for 6MV and 18MV energies of various field sizes. Then Oncor® machine was modeled running DBS technique, and the efficiency of total fluence and spatial fluence for electron and photon, the efficiency of dose variance reduction of MC calculations for PDD on the central beam axis and lateral dose profile across the nominal field was measured and compared. Result: With applying DBS technique, the total fluence of electron and photon increased in turn 626.8 (6MV and 983.4 (6MV, and 285.6 (18MV and 737.8 (18MV, the spatial fluence of electron and photon improved in turn 308.6±1.35% (6MV and 480.38±0.43% (6MV, and 153±0.9% (18MV and 462.6±0.27% (18MV. Moreover, by running DBS technique, the efficiency of dose variance reduction for PDD MC dose calculations before maximum dose point and after dose maximum point enhanced 187.8±0.68% (6MV and 184.6±0.65% (6MV, 156±0.43% (18MV and 153±0.37% (18MV, respectively, and the efficiency of MC calculations for lateral dose profile remarkably on the central beam axis and across the treatment field raised in turn 197±0.66% (6MV and 214.6±0.73% (6MV, 175±0.36% (18MV and 181.4±0.45% (18MV. Conclusion: Applying dose variance reduction technique of DBS for modeling Oncor® linac with using BEAMnrc MC Code surprisingly improved the fluence of electron and photon, and it therefore enhanced the efficiency of dose variance reduction for MC calculations. As a result, running DBS in different kinds of MC simulation Codes might be beneficent in reducing the uncertainty of MC calculations. 

  17. A criticality safety analysis code using a vectorized Monte Carlo method on the HITAC S-810 supercomputer

    International Nuclear Information System (INIS)

    Morimoto, Y.; Maruyama, H.

    1987-01-01

    A vectorized Monte Carlo criticality safety analysis code has been developed on the vector supercomputer HITAC S-810. In this code, a multi-particle tracking algorithm was adopted for effective utilization of the vector processor. A flight analysis with pseudo-scattering was developed to reduce the computational time needed for flight analysis, which represents the bulk of computational time. This new algorithm realized a speed-up of factor 1.5 over the conventional flight analysis. The code also adopted the multigroup cross section constants library of the Bodarenko type with 190 groups, with 132 groups being for fast and epithermal regions and 58 groups being for the thermal region. Evaluation work showed that this code reproduce the experimental results to an accuracy of about 1 % for the effective neutron multiplication factor. (author)

  18. Estimate of the melanin content in human hairs by the inverse Monte-Carlo method using a system for digital image analysis

    International Nuclear Information System (INIS)

    Bashkatov, A N; Genina, Elina A; Kochubei, V I; Tuchin, Valerii V

    2006-01-01

    Based on the digital image analysis and inverse Monte-Carlo method, the proximate analysis method is deve-loped and the optical properties of hairs of different types are estimated in three spectral ranges corresponding to three colour components. The scattering and absorption properties of hairs are separated for the first time by using the inverse Monte-Carlo method. The content of different types of melanin in hairs is estimated from the absorption coefficient. It is shown that the dominating type of melanin in dark hairs is eumelanin, whereas in light hairs pheomelanin dominates. (special issue devoted to multiple radiation scattering in random media)

  19. Markov Chain Monte Carlo

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 7; Issue 3. Markov Chain Monte Carlo - Examples. Arnab Chakraborty. General Article Volume 7 Issue 3 March 2002 pp 25-34. Fulltext. Click here to view fulltext PDF. Permanent link: https://www.ias.ac.in/article/fulltext/reso/007/03/0025-0034. Keywords.

  20. Monte Carlo and Quasi-Monte Carlo Sampling

    CERN Document Server

    Lemieux, Christiane

    2009-01-01

    Presents essential tools for using quasi-Monte Carlo sampling in practice. This book focuses on issues related to Monte Carlo methods - uniform and non-uniform random number generation, variance reduction techniques. It covers several aspects of quasi-Monte Carlo methods.

  1. Monte Carlo analysis of thermal transpiration effects in capacitance diaphragm gauges with helicoidal baffle system

    International Nuclear Information System (INIS)

    Vargas, M; Stefanov, S; Wüest, M

    2012-01-01

    The Capacitance Diaphragm Gauge (CDG) is one of the most widely used vacuum gauges in low and middle vacuum ranges. This device consists basically of a very thin ceramic or metal diaphragm which forms one of the electrodes of a cap acitor. The pressure is determined by measuring the variation in the capacitance due to the deflection of the diaphragm caused by the pressure difference established across the membrane. In order to minimize zero drift, some CDGs are operated keeping the sensor at a higher temperature. This difference in the temperature between the sensor and the vacuum chamber makes the behaviour of the gauge non-linear due to thermal transpiration effects. This effect becomes more significant when we move from the transitional flow to the free molecular regime. Besides, CDGs may incorporate different baffle systems to avoid the condensation on the membrane or its contamination. In this work, the thermal transpiration effect on the behaviour of a rarefied gas and on the measurements in a CDG with a helicoidal baffle system is investigated by using the Direct Simulation Monte Carlo method (DSMC). The study covers the behaviour of the system under the whole range of rarefaction, from the continuum up to the free molecular limit and the results are compared with empirical results. Moreover, the influence of the boundary conditions on the thermal transpiration effects is investigated by using Maxwell boundary conditions.

  2. Analysis of inconsistent source sampling in monte carlo weight-window variance reduction methods

    Directory of Open Access Journals (Sweden)

    David P. Griesheimer

    2017-09-01

    Full Text Available The application of Monte Carlo (MC to large-scale fixed-source problems has recently become possible with new hybrid methods that automate generation of parameters for variance reduction techniques. Two common variance reduction techniques, weight windows and source biasing, have been automated and popularized by the consistent adjoint-driven importance sampling (CADIS method. This method uses the adjoint solution from an inexpensive deterministic calculation to define a consistent set of weight windows and source particles for a subsequent MC calculation. One of the motivations for source consistency is to avoid the splitting or rouletting of particles at birth, which requires computational resources. However, it is not always possible or desirable to implement such consistency, which results in inconsistent source biasing. This paper develops an original framework that mathematically expresses the coupling of the weight window and source biasing techniques, allowing the authors to explore the impact of inconsistent source sampling on the variance of MC results. A numerical experiment supports this new framework and suggests that certain classes of problems may be relatively insensitive to inconsistent source sampling schemes with moderate levels of splitting and rouletting.

  3. JMCT Monte Carlo simulation analysis of full core PWR Pin-By-Pin and shielding

    International Nuclear Information System (INIS)

    Deng, L.; Li, G.; Zhang, B.; Shangguan, D.; Ma, Y.; Hu, Z.; Fu, Y.; Li, R.; Hu, X.; Cheng, T.; Shi, D.

    2015-01-01

    This paper describes the application of the JMCT Monte Carlo code to the simulation of Kord Smith Challenge H-M model, BEAVRS model and Chinese SG-III model. For H-M model, the 6.3624 millions tally regions and the 98.3 billion neutron histories do. The detailed pin flux and energy deposition densities obtain. 95% regions have less 1% standard deviation. For BEAVRS model, firstly, we performed the neutron transport calculation of 398 axial planes in the Hot Zero Power (HZP) status. Almost the same results with MC21 and OpenMC results are achieved. The detailed pin-power density distribution and standard deviation are shown. Then, we performed the calculation of ten depletion steps in 30 axial plane cases. The depletion regions exceed 1.5 million and 12,000 processors uses. Finally, the Chinese SG-III laser model is simulated. The neutron and photon flux distributions are given, respectively. The results show that the JMCT code well suits for extremely large reactor and shielding simulation. (author)

  4. Comparative analysis of a fusion reactor blanket in cylindrical and toroidal geometry using Monte Carlo

    International Nuclear Information System (INIS)

    Chapin, D.L.

    1976-03-01

    Differences in neutron fluxes and nuclear reaction rates in a noncircular fusion reactor blanket when analyzed in cylindrical and toroidal geometry are studied using Monte Carlo. The investigation consists of three phases--a one-dimensional calculation using a circular approximation to a hexagonal shaped blanket; a two-dimensional calculation of a hexagonal blanket in an infinite cylinder; and a three-dimensional calculation of the blanket in tori of aspect ratios 3 and 5. The total blanket reaction rate in the two-dimensional model is found to be in good agreement with the circular model. The toroidal calculations reveal large variations in reaction rates at different blanket locations as compared to the hexagonal cylinder model, although the total reaction rate is nearly the same for both models. It is shown that the local perturbations in the toroidal blanket are due mainly to volumetric effects, and can be predicted by modifying the results of the infinite cylinder calculation by simple volume factors dependent on the blanket location and the torus major radius

  5. Mathematical modeling, analysis and Markov Chain Monte Carlo simulation of Ebola epidemics

    Science.gov (United States)

    Tulu, Thomas Wetere; Tian, Boping; Wu, Zunyou

    Ebola virus infection is a severe infectious disease with the highest case fatality rate which become the global public health treat now. What makes the disease the worst of all is no specific effective treatment available, its dynamics is not much researched and understood. In this article a new mathematical model incorporating both vaccination and quarantine to study the dynamics of Ebola epidemic has been developed and comprehensively analyzed. The existence as well as uniqueness of the solution to the model is also verified and the basic reproduction number is calculated. Besides, stability conditions are also checked and finally simulation is done using both Euler method and one of the top ten most influential algorithm known as Markov Chain Monte Carlo (MCMC) method. Different rates of vaccination to predict the effect of vaccination on the infected individual over time and that of quarantine are discussed. The results show that quarantine and vaccination are very effective ways to control Ebola epidemic. From our study it was also seen that there is less possibility of an individual for getting Ebola virus for the second time if they survived his/her first infection. Last but not least real data has been fitted to the model, showing that it can used to predict the dynamic of Ebola epidemic.

  6. Economic analysis using Monte Carlo simulation on Xs reservoir Badak field east Kalimantan

    International Nuclear Information System (INIS)

    Nuraeni, S.; Sugiatmo, Prasetyawan O.J.

    1997-01-01

    Badak field, located in the delta of mahakam river, in east kalimantan, is a gas producer. the field was found in 1972 by VICO. Badak field is the main gas supplier to bontang LNG and gas is exported to japan, south korea and taiwan, as well as utilized for the main feed to the east kalimantan fertilizer plant. To provide the gas demand, field development as well as exploration wells are continued. on these exploration wells, gas in place determination, gas production rate as well as economic evaluation play on important role. the effect of altering gas production rate to net present value and also the effect of altering discounted factor to the rate of return curve using monte carlo simulation is presented on this paper. based on the simulation results it is obtained that the upper limit of the initial gas in place is 1.82 BSCF, the lower limit is 0.27 BSCF and the most likely million US $ with a rate of return ranges from - 30 to 33.5 percent

  7. Scaling analysis and instantons for thermally assisted tunneling and quantum Monte Carlo simulations

    Science.gov (United States)

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

    2017-01-01

    We develop an instantonic calculus to derive an analytical expression for the thermally assisted tunneling decay rate of a metastable state in a fully connected quantum spin model. The tunneling decay problem can be mapped onto the Kramers escape problem of a classical random dynamical field. This dynamical field is simulated efficiently by path-integral quantum Monte Carlo (QMC). We show analytically that the exponential scaling with the number of spins of the thermally assisted quantum tunneling rate and the escape rate of the QMC process are identical. We relate this effect to the existence of a dominant instantonic tunneling path. The instanton trajectory is described by nonlinear dynamical mean-field theory equations for a single-site magnetization vector, which we solve exactly. Finally, we derive scaling relations for the "spiky" barrier shape when the spin tunneling and QMC rates scale polynomially with the number of spins N while a purely classical over-the-barrier activation rate scales exponentially with N .

  8. Monte Carlo analysis of the Neutron Standards Laboratory of the CIEMAT

    International Nuclear Information System (INIS)

    Vega C, H. R.; Mendez V, R.; Guzman G, K. A.

    2014-10-01

    By means of Monte Carlo methods was characterized the neutrons field produced by calibration sources in the Neutron Standards Laboratory of the Centro de Investigaciones Energeticas, Medioambientales y Tecnologicas (CIEMAT). The laboratory has two neutron calibration sources: 241 AmBe and 252 Cf which are stored in a water pool and are placed on the calibration bench using controlled systems at distance. To characterize the neutrons field was built a three-dimensional model of the room where it was included the stainless steel bench, the irradiation table and the storage pool. The sources model included double encapsulated of steel, as cladding. With the purpose of determining the effect that produces the presence of the different components of the room, during the characterization the neutrons spectra, the total flow and the rapidity of environmental equivalent dose to 100 cm of the source were considered. The presence of the walls, floor and ceiling of the room is causing the most modification in the spectra and the integral values of the flow and the rapidity of environmental equivalent dose. (Author)

  9. Spatio-temporal spike train analysis for large scale networks using the maximum entropy principle and Monte Carlo method

    International Nuclear Information System (INIS)

    Nasser, Hassan; Cessac, Bruno; Marre, Olivier

    2013-01-01

    Understanding the dynamics of neural networks is a major challenge in experimental neuroscience. For that purpose, a modelling of the recorded activity that reproduces the main statistics of the data is required. In the first part, we present a review on recent results dealing with spike train statistics analysis using maximum entropy models (MaxEnt). Most of these studies have focused on modelling synchronous spike patterns, leaving aside the temporal dynamics of the neural activity. However, the maximum entropy principle can be generalized to the temporal case, leading to Markovian models where memory effects and time correlations in the dynamics are properly taken into account. In the second part, we present a new method based on Monte Carlo sampling which is suited for the fitting of large-scale spatio-temporal MaxEnt models. The formalism and the tools presented here will be essential to fit MaxEnt spatio-temporal models to large neural ensembles. (paper)

  10. A Monte Carlo study comparing PIV, ULS and DWLS in the estimation of dichotomous confirmatory factor analysis.

    Science.gov (United States)

    Nestler, Steffen

    2013-02-01

    We conducted a Monte Carlo study to investigate the performance of the polychoric instrumental variable estimator (PIV) in comparison to unweighted least squares (ULS) and diagonally weighted least squares (DWLS) in the estimation of a confirmatory factor analysis model with dichotomous indicators. The simulation involved 144 conditions (1,000 replications per condition) that were defined by a combination of (a) two types of latent factor models, (b) four sample sizes (100, 250, 500, 1,000), (c) three factor loadings (low, moderate, strong), (d) three levels of non-normality (normal, moderately, and extremely non-normal), and (e) whether the factor model was correctly specified or misspecified. The results showed that when the model was correctly specified, PIV produced estimates that were as accurate as ULS and DWLS. Furthermore, the simulation showed that PIV was more robust to structural misspecifications than ULS and DWLS. © 2012 The British Psychological Society.

  11. Neutronic design and performance analysis of Korean ITER TBM by Monte Carlo method

    International Nuclear Information System (INIS)

    Kim, Chang Hyo; Han, Beom Seok; Park, Ho Jin

    2006-01-01

    The objective of this project is to develop a neutronic design of the Korean TBM(Test Blanket Module) which will be installed in ITER(International Thermonuclear Experimental Reactor). This project is intended to analyze a neutronic design and nuclear performances of the Korean ITER TBM through the transport calculation of MCCARD. In detail, we will conduct numerical experiments for developing the neutronic design of the Korean ITER TBM and improving the nuclear performances. The results of the numerical experiments produced in this project will be utilized for a design optimization of the Korean ITER TBM. In this project, we proposed the neutronic methodologies for analyzing the nuclear characteristics of the fusion blanket. In order to investigate the behavior of neutrons and photons in the fusion blanket, Monte Carlo transport calculation was conducted with MCCARD. In addition, to optimize the neutronic performances of the fusion blanket, we introduced the design concept using a graphite reflector and a Pb multiplier. Through various numerical experiments, it was verified that these design concepts can be utilized efficiently to improve neutronic performances and resolve many drawbacks. The graphite-reflected HCML blanket can provide the neutronic performances far better than the non-reflected blanket, and a slightly-enriched Li breeder can satisfy the tritium self-sufficiency. The HCSB blanket design concept with a graphite reflector and a Pb multiplier was proposed. According to results of the neutronic analyses, the graphite-reflected HCSB blanket with a Pb multiplier can provide the neutronic performances comparable with those of the conventional HCSB blanket

  12. Monte Carlo techniques for analyzing deep-penetration problems

    International Nuclear Information System (INIS)

    Cramer, S.N.; Gonnord, J.; Hendricks, J.S.

    1986-01-01

    Current methods and difficulties in Monte Carlo deep-penetration calculations are reviewed, including statistical uncertainty and recent adjoint optimization of splitting, Russian roulette, and exponential transformation biasing. Other aspects of the random walk and estimation processes are covered, including the relatively new DXANG angular biasing technique. Specific items summarized are albedo scattering, Monte Carlo coupling techniques with discrete ordinates and other methods, adjoint solutions, and multigroup Monte Carlo. The topic of code-generated biasing parameters is presented, including the creation of adjoint importance functions from forward calculations. Finally, current and future work in the area of computer learning and artificial intelligence is discussed in connection with Monte Carlo applications

  13. Bayesian Monte Carlo method

    International Nuclear Information System (INIS)

    Rajabalinejad, M.

    2010-01-01

    To reduce cost of Monte Carlo (MC) simulations for time-consuming processes, Bayesian Monte Carlo (BMC) is introduced in this paper. The BMC method reduces number of realizations in MC according to the desired accuracy level. BMC also provides a possibility of considering more priors. In other words, different priors can be integrated into one model by using BMC to further reduce cost of simulations. This study suggests speeding up the simulation process by considering the logical dependence of neighboring points as prior information. This information is used in the BMC method to produce a predictive tool through the simulation process. The general methodology and algorithm of BMC method are presented in this paper. The BMC method is applied to the simplified break water model as well as the finite element model of 17th Street Canal in New Orleans, and the results are compared with the MC and Dynamic Bounds methods.

  14. Monte Carlo principles and applications

    Energy Technology Data Exchange (ETDEWEB)

    Raeside, D E [Oklahoma Univ., Oklahoma City (USA). Health Sciences Center

    1976-03-01

    The principles underlying the use of Monte Carlo methods are explained, for readers who may not be familiar with the approach. The generation of random numbers is discussed, and the connection between Monte Carlo methods and random numbers is indicated. Outlines of two well established Monte Carlo sampling techniques are given, together with examples illustrating their use. The general techniques for improving the efficiency of Monte Carlo calculations are considered. The literature relevant to the applications of Monte Carlo calculations in medical physics is reviewed.

  15. Contributon Monte Carlo

    International Nuclear Information System (INIS)

    Dubi, A.; Gerstl, S.A.W.

    1979-05-01

    The contributon Monte Carlo method is based on a new recipe to calculate target responses by means of volume integral of the contributon current in a region between the source and the detector. A comprehensive description of the method, its implementation in the general-purpose MCNP code, and results of the method for realistic nonhomogeneous, energy-dependent problems are presented. 23 figures, 10 tables

  16. Fundamentals of Monte Carlo

    International Nuclear Information System (INIS)

    Wollaber, Allan Benton

    2016-01-01

    This is a powerpoint presentation which serves as lecture material for the Parallel Computing summer school. It goes over the fundamentals of the Monte Carlo calculation method. The material is presented according to the following outline: Introduction (background, a simple example: estimating @@), Why does this even work? (The Law of Large Numbers, The Central Limit Theorem), How to sample (inverse transform sampling, rejection), and An example from particle transport.

  17. Microcanonical Monte Carlo

    International Nuclear Information System (INIS)

    Creutz, M.

    1986-01-01

    The author discusses a recently developed algorithm for simulating statistical systems. The procedure interpolates between molecular dynamics methods and canonical Monte Carlo. The primary advantages are extremely fast simulations of discrete systems such as the Ising model and a relative insensitivity to random number quality. A variation of the algorithm gives rise to a deterministic dynamics for Ising spins. This model may be useful for high speed simulation of non-equilibrium phenomena

  18. Fundamentals of Monte Carlo

    Energy Technology Data Exchange (ETDEWEB)

    Wollaber, Allan Benton [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-06-16

    This is a powerpoint presentation which serves as lecture material for the Parallel Computing summer school. It goes over the fundamentals of the Monte Carlo calculation method. The material is presented according to the following outline: Introduction (background, a simple example: estimating π), Why does this even work? (The Law of Large Numbers, The Central Limit Theorem), How to sample (inverse transform sampling, rejection), and An example from particle transport.

  19. Monte Carlo alpha calculation

    Energy Technology Data Exchange (ETDEWEB)

    Brockway, D.; Soran, P.; Whalen, P.

    1985-01-01

    A Monte Carlo algorithm to efficiently calculate static alpha eigenvalues, N = ne/sup ..cap alpha..t/, for supercritical systems has been developed and tested. A direct Monte Carlo approach to calculating a static alpha is to simply follow the buildup in time of neutrons in a supercritical system and evaluate the logarithmic derivative of the neutron population with respect to time. This procedure is expensive, and the solution is very noisy and almost useless for a system near critical. The modified approach is to convert the time-dependent problem to a static ..cap alpha../sup -/eigenvalue problem and regress ..cap alpha.. on solutions of a/sup -/ k/sup -/eigenvalue problem. In practice, this procedure is much more efficient than the direct calculation, and produces much more accurate results. Because the Monte Carlo codes are intrinsically three-dimensional and use elaborate continuous-energy cross sections, this technique is now used as a standard for evaluating other calculational techniques in odd geometries or with group cross sections.

  20. Monte Carlo analysis of helium production in the ITER shielding blanket module

    International Nuclear Information System (INIS)

    Sato, S.

    1999-01-01

    In order to examine the shielding performances of the inboard blanket module in the international thermonuclear experimental reactor (ITER), shielding calculations have been carried out using a three-dimensional Monte Carlo method. The impact of radiation streaming through the front access holes and gaps between adjacent blanket modules on the helium gas production in the branch pipe weld locations and back plate have been estimated. The three-dimensional model represents an 18 sector of the overall torus region and includes the vacuum vessel, inboard blanket and back plate, plasma region, and outboard reflecting medium. And it includes the 1 m high inboard mid-plane module and the 20 mm wide gaps between adjacent modules. From the calculated results for the reference design, it has been found that the helium production at the plug of the branch pipe is four to five times higher than the design goal of 1 appm for a neutron fluence of 0.9 MW a m -2 at the inboard mid-plane first wall. Also, it has been found that the helium production at the back plate behind the horizontal gap is about three times higher than the design goal. In the reference design, the stainless steel (SS):H 2 O composition in the blanket module is 80:20%. Shielding calculations also have been carried out for the SS:H 2 O composition of 70:30, 60:40, 50:50 and 40:60%. From the evaluated results for their design, it has been found that the dependence of helium production on the SS:H 2 170 mm will reduce helium production to satisfy the design goal and not have a significant impact on weight limitations imposed by remote maintenance handling limitations. Also based on the calculated results, about 200 mm thick shields such as a key structure in the vertical gap are suggested to be installed in the horizontal gap as well to reduce the helium production at the back plate and to satisfy the design goal. (orig.)

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

    International Nuclear Information System (INIS)

    Sun, Yi; Yang, Xiaofeng; Wang, Qi

    2014-01-01

    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

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

    Science.gov (United States)

    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

  3. Quantifying geological uncertainty in metamorphic phase equilibria modelling; a Monte Carlo assessment and implications for tectonic interpretations

    Directory of Open Access Journals (Sweden)

    Richard M. Palin

    2016-07-01

    Full Text Available Pseudosection modelling is rapidly becoming an essential part of a petrologist's toolkit and often forms the basis of interpreting the tectonothermal evolution of a rock sample, outcrop, or geological region. Of the several factors that can affect the accuracy and precision of such calculated phase diagrams, “geological” uncertainty related to natural petrographic variation at the hand sample- and/or thin section-scale is rarely considered. Such uncertainty influences the sample's bulk composition, which is the primary control on its equilibrium phase relationships and thus the interpreted pressure–temperature (P–T conditions of formation. Two case study examples—a garnet–cordierite granofels and a garnet–staurolite–kyanite schist—are used to compare the relative importance that geological uncertainty has on bulk compositions determined via (1 X-ray fluorescence (XRF or (2 point counting techniques. We show that only minor mineralogical variation at the thin-section scale propagates through the phase equilibria modelling procedure and affects the absolute P–T conditions at which key assemblages are stable. Absolute displacements of equilibria can approach ±1 kbar for only a moderate degree of modal proportion uncertainty, thus being essentially similar to the magnitudes reported for analytical uncertainties in conventional thermobarometry. Bulk compositions determined from multiple thin sections of a heterogeneous garnet–staurolite–kyanite schist show a wide range in major-element oxides, owing to notable variation in mineral proportions. Pseudosections constructed for individual point count-derived bulks accurately reproduce this variability on a case-by-case basis, though averaged proportions do not correlate with those calculated at equivalent peak P–T conditions for a whole-rock XRF-derived bulk composition. The main discrepancies relate to varying proportions of matrix phases (primarily mica relative to

  4. Monte Carlo analysis of experiments on the reactivity temperature coefficient for UO2 and MOX light water moderated lattices

    International Nuclear Information System (INIS)

    Chakir, E.; Erradi, L.; Bardouni, T El.; Khoukhi, T El.; Boukhal, H.; Meroun, O.; Bakkari, B El

    2007-01-01

    Full text: In a previous work, we have analysed the main french experiments available on the reactivity temperature coefficient (RTC) : CREAOLE and Mistral experiments. In these experiments, the RTC has been measured in both UO2 and UO2-PuO2 PWR type lattices. Our calculations, using APPOLO2 code with CEA93 library based on JEF2.2 evaluation, have shown that the calculation error in UO2 lattices is less than 1 pcm/Deg C which is considered as the target accuracy. On the other hand the calculation error in the MOX lattices is more significant in both low and high temperature ranges : an average error of -2 ± 0.5 pcm/Deg C is observed in low temperatures and an error of +3±2 pcm/Deg C is obtained for temperature higher than 250Deg C. In the present work, we analysed additional experimental benchmarks on the RTC of UO2 and MOX light water moderated lattices. To analyze these benchmarks and with the aim of minimizing uncertainties related to modelling of the experimental set up, we chose the Monte Carlo Method which has the advantage of taking into account in the most exact manner the geometry of the experimental configurations. Thus we have used the code MCNP5, for its recognized power and its availability. This analysis shows for the UO2 lattices, an average experiment-calculation deviation of about 0,5 pcm/Deg C, which is largely below the target accuracy for this type of lattices, that we estimate at approximately 1 pcm/Deg C. For the KAMINI experiment, which relates to the measurement of the RTC in light water moderated lattice using U-233 as fuel our analysis shows that the Endf/B6 library gives the best result, with an experiment -calculation deviation of the order of -0,16 pcm/Deg C. The analysis of the benchmarks using MOX fuel made it possible to highlight a discrepancy between experiment and calculation on the RTC of about -0.7pcm/Deg C ( for a range of temperature going from 20 to 248 Deg C) and -1.2 pcm/Deg C ( for a range of temperature going from 20 to

  5. Coupling Monte Carlo simulations with thermal analysis for correcting microdosimetric spectra from a novel micro-calorimeter

    Science.gov (United States)

    Fathi, K.; Galer, S.; Kirkby, K. J.; Palmans, H.; Nisbet, A.

    2017-11-01

    The high uncertainty in the Relative Biological Effectiveness (RBE) values of particle therapy beam, which are used in combination with the quantity absorbed dose in radiotherapy, together with the increase in the number of particle therapy centres worldwide necessitate a better understating of the biological effect of such modalities. The present novel study is part of performance testing and development of a micro-calorimeter based on Superconducting QUantum Interference Devices (SQUIDs). Unlike other microdosimetric detectors that are used for investigating the energy distribution, this detector provides a direct measurement of energy deposition at the micrometre scale, that can be used to improve our understanding of biological effects in particle therapy application, radiation protection and environmental dosimetry. Temperature rises of less than 1μK are detectable and when combined with the low specific heat capacity of the absorber at cryogenic temperature, extremely high energy deposition sensitivity of approximately 0.4 eV can be achieved. The detector consists of 3 layers: tissue equivalent (TE) absorber, superconducting (SC) absorber and silicon substrate. Ideally all energy would be absorbed in the TE absorber and heat rise in the superconducting layer would arise due to heat conduction from the TE layer. However, in practice direct particle absorption occurs in all 3 layers and must be corrected for. To investigate the thermal behaviour within the detector, and quantify any possible correction, particle tracks were simulated employing Geant4 (v9.6) Monte Carlo simulations. The track information was then passed to the COMSOL Multiphysics (Finite Element Method) software. The 3D heat transfer within each layer was then evaluated in a time-dependent model. For a statistically reliable outcome, the simulations had to be repeated for a large number of particles. An automated system has been developed that couples Geant4 Monte Carlo output to COMSOL for

  6. Assessment of uncertainties in the lung activity measurement of low-energy photon emitters using Monte Carlo simulation of ICRP male thorax voxel phantom.

    Science.gov (United States)

    Nadar, M Y; Akar, D K; Rao, D D; Kulkarni, M S; Pradeepkumar, K S

    2015-12-01

    Assessment of intake due to long-lived actinides by inhalation pathway is carried out by lung monitoring of the radiation workers inside totally shielded steel room using sensitive detection systems such as Phoswich and an array of HPGe detectors. In this paper, uncertainties in the lung activity estimation due to positional errors, chest wall thickness (CWT) and detector background variation are evaluated. First, calibration factors (CFs) of Phoswich and an array of three HPGe detectors are estimated by incorporating ICRP male thorax voxel phantom and detectors in Monte Carlo code 'FLUKA'. CFs are estimated for the uniform source distribution in lungs of the phantom for various photon energies. The variation in the CFs for positional errors of ±0.5, 1 and 1.5 cm in horizontal and vertical direction along the chest are studied. The positional errors are also evaluated by resizing the voxel phantom. Combined uncertainties are estimated at different energies using the uncertainties due to CWT, detector positioning, detector background variation of an uncontaminated adult person and counting statistics in the form of scattering factors (SFs). SFs are found to decrease with increase in energy. With HPGe array, highest SF of 1.84 is found at 18 keV. It reduces to 1.36 at 238 keV. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  7. The Monte Carlo method for shielding calculations analysis by MORSE code of a streaming case in the CAORSO BWR power reactor shielding (Italy)

    International Nuclear Information System (INIS)

    Zitouni, Y.

    1987-04-01

    In the field of shielding, the requirement of radiation transport calculations in severe conditions, characterized by irreducible three-dimensional geometries has increased the use of the Monte Carlo method. The latter has proved to be the only rigorous and appropriate calculational method in such conditions. However, further efforts at optimization are still necessary to render the technique practically efficient, despite recent improvements in the Monte Carlo codes, the progress made in the field of computers and the availability of accurate nuclear data. Moreover, the personal experience acquired in the field and the control of sophisticated calculation procedures are of the utmost importance. The aim of the work which has been carried out is the gathering of all the necessary elements and features that would lead to an efficient utilization of the Monte Carlo method used in connection with shielding problems. The study of the general aspects of the method and the exploitation techniques of the MORSE code, which has proved to be one of the most comprehensive of the Monte Carlo codes, lead to a successful analysis of an actual case. In fact, the severe conditions and difficulties met have been overcome using such a stochastic simulation code. Finally, a critical comparison between calculated and high-accuracy experimental results has allowed the final confirmation of the methodology used by us

  8. Reconstruction of Monte Carlo replicas from Hessian parton distributions

    Energy Technology Data Exchange (ETDEWEB)

    Hou, Tie-Jiun [Department of Physics, Southern Methodist University,Dallas, TX 75275-0181 (United States); Gao, Jun [INPAC, Shanghai Key Laboratory for Particle Physics and Cosmology,Department of Physics and Astronomy, Shanghai Jiao-Tong University, Shanghai 200240 (China); High Energy Physics Division, Argonne National Laboratory,Argonne, Illinois, 60439 (United States); Huston, Joey [Department of Physics and Astronomy, Michigan State University,East Lansing, MI 48824 (United States); Nadolsky, Pavel [Department of Physics, Southern Methodist University,Dallas, TX 75275-0181 (United States); Schmidt, Carl; Stump, Daniel [Department of Physics and Astronomy, Michigan State University,East Lansing, MI 48824 (United States); Wang, Bo-Ting; Xie, Ke Ping [Department of Physics, Southern Methodist University,Dallas, TX 75275-0181 (United States); Dulat, Sayipjamal [Department of Physics and Astronomy, Michigan State University,East Lansing, MI 48824 (United States); School of Physics Science and Technology, Xinjiang University,Urumqi, Xinjiang 830046 (China); Center for Theoretical Physics, Xinjiang University,Urumqi, Xinjiang 830046 (China); Pumplin, Jon; Yuan, C.P. [Department of Physics and Astronomy, Michigan State University,East Lansing, MI 48824 (United States)

    2017-03-20

    We explore connections between two common methods for quantifying the uncertainty in parton distribution functions (PDFs), based on the Hessian error matrix and Monte-Carlo sampling. CT14 parton distributions in the Hessian representation are converted into Monte-Carlo replicas by a numerical method that reproduces important properties of CT14 Hessian PDFs: the asymmetry of CT14 uncertainties and positivity of individual parton distributions. The ensembles of CT14 Monte-Carlo replicas constructed this way at NNLO and NLO are suitable for various collider applications, such as cross section reweighting. Master formulas for computation of asymmetric standard deviations in the Monte-Carlo representation are derived. A correction is proposed to address a bias in asymmetric uncertainties introduced by the Taylor series approximation. A numerical program is made available for conversion of Hessian PDFs into Monte-Carlo replicas according to normal, log-normal, and Watt-Thorne sampling procedures.

  9. Analysis of the TRIGA Mark-II benchmark IEU-COMP-THERM-003 with Monte Carlo code MVP

    International Nuclear Information System (INIS)

    Mahmood, Mohammad Sayem; Nagaya, Yasunobu; Mori, Takamasa

    2004-03-01

    The benchmark experiments of the TRIGA Mark-II reactor in the ICSBEP handbook have been analyzed with the Monte Carlo code MVP using the cross section libraries based on JENDL-3.3, JENDL-3.2 and ENDF/B-VI.8. The MCNP calculations have been also performed with the ENDF/B-VI.6 library for comparison between the MVP and MCNP results. For both cores labeled 132 and 133, which have different core configurations, the ratio of the calculated to the experimental results (C/E) for k eff obtained by the MVP code is 0.999 for JENDL-3.3, 1.003 for JENDL-3.2, and 0.998 for ENDF/B-VI.8. For the MCNP code, the C/E values are 0.998 for both Core 132 and 133. All the calculated results agree with the reference values within the experimental uncertainties. The results obtained by MVP with ENDF/B-VI.8 and MCNP with ENDF/B-VI.6 differ only by 0.02% for Core 132, and by 0.01% for Core 133. (author)

  10. Analysis of the dead layer of a detector of germanium with code ultrapure Monte Carlo SWORD-GEANT; Analisis del dead layer de un detector de germanio ultrapuro con el codigo de Monte Carlo SWORDS-GEANT

    Energy Technology Data Exchange (ETDEWEB)

    Gallardo, S.; Querol, A.; Ortiz, J.; Rodenas, J.; Verdu, G.

    2014-07-01

    In this paper the use of Monte Carlo code SWORD-GEANT is proposed to simulate an ultra pure germanium detector High Purity Germanium detector (HPGe) detector ORTEC specifically GMX40P4, coaxial geometry. (Author)

  11. Reflections on early Monte Carlo calculations

    International Nuclear Information System (INIS)

    Spanier, J.

    1992-01-01

    Monte Carlo methods for solving various particle transport problems developed in parallel with the evolution of increasingly sophisticated computer programs implementing diffusion theory and low-order moments calculations. In these early years, Monte Carlo calculations and high-order approximations to the transport equation were seen as too expensive to use routinely for nuclear design but served as invaluable aids and supplements to design with less expensive tools. The earliest Monte Carlo programs were quite literal; i.e., neutron and other particle random walk histories were simulated by sampling from the probability laws inherent in the physical system without distoration. Use of such analogue sampling schemes resulted in a good deal of time being spent in examining the possibility of lowering the statistical uncertainties in the sample estimates by replacing simple, and intuitively obvious, random variables by those with identical means but lower variances

  12. Monte Carlo simulation of Markov unreliability models

    International Nuclear Information System (INIS)

    Lewis, E.E.; Boehm, F.

    1984-01-01

    A Monte Carlo method is formulated for the evaluation of the unrealibility of complex systems with known component failure and repair rates. The formulation is in terms of a Markov process allowing dependences between components to be modeled and computational efficiencies to be achieved in the Monte Carlo simulation. Two variance reduction techniques, forced transition and failure biasing, are employed to increase computational efficiency of the random walk procedure. For an example problem these result in improved computational efficiency by more than three orders of magnitudes over analog Monte Carlo. The method is generalized to treat problems with distributed failure and repair rate data, and a batching technique is introduced and shown to result in substantial increases in computational efficiency for an example problem. A method for separating the variance due to the data uncertainty from that due to the finite number of random walks is presented. (orig.)

  13. SPQR: a Monte Carlo reactor kinetics code

    International Nuclear Information System (INIS)

    Cramer, S.N.; Dodds, H.L.

    1980-02-01

    The SPQR Monte Carlo code has been developed to analyze fast reactor core accident problems where conventional methods are considered inadequate. The code is based on the adiabatic approximation of the quasi-static method. This initial version contains no automatic material motion or feedback. An existing Monte Carlo code is used to calculate the shape functions and the integral quantities needed in the kinetics module. Several sample problems have been devised and analyzed. Due to the large statistical uncertainty associated with the calculation of reactivity in accident simulations, the results, especially at later times, differ greatly from deterministic methods. It was also found that in large uncoupled systems, the Monte Carlo method has difficulty in handling asymmetric perturbations

  14. Monte Carlo reliability analysis of tophat stiffened composite plate structures under out of plane loading

    International Nuclear Information System (INIS)

    Sobey, A.J.; Blake, J.I.R.; Shenoi, R.A.

    2013-01-01

    Composite materials are often utilised for their high strength to weight ratio, excellent corrosion resistance, etc. but are also characterised by variabilities and uncertainties in their mechanical properties owing to the material make-up, process and fabrication techniques. It is essential that modelling techniques continue to be developed to take account of these variabilities and uncertainties and as more complicated structures are developed it is important to have rapid assessment methods to determine the reliability of these structures. Grillage analysis methods have been previously used for assessment of tophat stiffened composite structures using simple failure criteria. As new criteria are introduced, such as by the World Wide Failure Exercise, the response of more complex topologies must be introduced. This paper therefore assesses the reliability of composite grillages using Navier grillage method incorporating up to date failure criteria. An example, taken from boatbuilding, is used to show the results of using these more complex assessment methods showing that it is of high importance to use the correct assessment criteria.

  15. PICA, Photon-Induced Medium-Range Nuclear Cascade Analysis by Monte-Carlo

    International Nuclear Information System (INIS)

    2001-01-01

    1 - Description of program or function: PIC calculates the results of nuclear reactions caused by the collision of medium-energy photons with nuclei. The photon energy range in which the calculations are applicable is 30 4 are possible. The program PIC can accommodate incident monoenergetic photons as well as thin-target Bremsstrahlung spectra, thin-target Bremsstrahlung difference spectra and thick-target Bremsstrahlung spectra. For the last type of spectra the user must furnish the photon spectral data. PIC writes a history tape containing data on the properties of the particles (protons, neutrons, or pions) escaping from the nucleus. The data consists of the types of escaping particles and their energies and angles of emission. MECCAN utilizes the data on the PIC history tape to calculate cross sections such as the nonelastic cross section or the doubly differential cross section for energy-angle correlated distributions. EVAP then carries the nuclear reaction through an additional phase, that of evaporation, and calculates the energy spectra of particles (protons, neutrons, deuterons, tritons, 3 He, and alpha particles) 'boiled off' from the nucleus after the cascade has stopped, evaporation particle multiplicities, and evaporation residual nuclei (radio-chemical) cross sections. 2 - Method of solution: The interaction of high-energy photons with nuclei is described by using the intranuclear cascade and evaporation models. Monte Carlo methods are employed to provide a detailed description of each interaction. The initial interaction of the photon with the nucleus is obtained from the quasi-deuteron model of Levinger, that is, photon absorption by a neutron-proton pair moving within the nucleus or from one of the four pion-nucleon states formed in the photon-nucleon interaction. The effect of secondary nucleon-nucleus and/or pion-nucleus interactions following the photon absorption is accounted for by utilizing the intranuclear-cascade concept of high

  16. Using Static Percentiles of AE9/AP9 to Approximate Dynamic Monte Carlo Runs for Radiation Analysis of Spiral Transfer Orbits

    Science.gov (United States)

    Kwan, Betty P.; O'Brien, T. Paul

    2015-06-01

    The Aerospace Corporation performed a study to determine whether static percentiles of AE9/AP9 can be used to approximate dynamic Monte Carlo runs for radiation analysis of spiral transfer orbits. Solar panel degradation is a major concern for solar-electric propulsion because solar-electric propulsion depends on the power output of the solar panel. Different spiral trajectories have different radiation environments that could lead to solar panel degradation. Because the spiral transfer orbits only last weeks to months, an average environment does not adequately address the possible transient enhancements of the radiation environment that must be accounted for in optimizing the transfer orbit trajectory. Therefore, to optimize the trajectory, an ensemble of Monte Carlo simulations of AE9/AP9 would normally be run for every spiral trajectory to determine the 95th percentile radiation environment. To avoid performing lengthy Monte Carlo dynamic simulations for every candidate spiral trajectory in the optimization, we found a static percentile that would be an accurate representation of the full Monte Carlo simulation for a representative set of spiral trajectories. For 3 LEO to GEO and 1 LEO to MEO trajectories, a static 90th percentile AP9 is a good approximation of the 95th percentile fluence with dynamics for 4-10 MeV protons, and a static 80th percentile AE9 is a good approximation of the 95th percentile fluence with dynamics for 0.5-2 MeV electrons. While the specific percentiles chosen cannot necessarily be used in general for other orbit trade studies, the concept of determining a static percentile as a quick approximation to a full Monte Carlo ensemble of simulations can likely be applied to other orbit trade studies. We expect the static percentile to depend on the region of space traversed, the mission duration, and the radiation effect considered.

  17. Monte Carlo perturbation theory in neutron transport calculations

    International Nuclear Information System (INIS)

    Hall, M.C.G.

    1980-01-01

    The need to obtain sensitivities in complicated geometrical configurations has resulted in the development of Monte Carlo sensitivity estimation. A new method has been developed to calculate energy-dependent sensitivities of any number of responses in a single Monte Carlo calculation with a very small time penalty. This estimation typically increases the tracking time per source particle by about 30%. The method of estimation is explained. Sensitivities obtained are compared with those calculated by discrete ordinates methods. Further theoretical developments, such as second-order perturbation theory and application to k/sub eff/ calculations, are discussed. The application of the method to uncertainty analysis and to the analysis of benchmark experiments is illustrated. 5 figures

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

    Science.gov (United States)

    Núñez, M; Robie, T; Vlachos, D G

    2017-10-28

    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).

  19. Uncertainty propagation using the Monte Carlo method in the measurement of airborne particle size distribution with a scanning mobility particle sizer

    Science.gov (United States)

    Coquelin, L.; Le Brusquet, L.; Fischer, N.; Gensdarmes, F.; Motzkus, C.; Mace, T.; Fleury, G.

    2018-05-01

    A scanning mobility particle sizer (SMPS) is a high resolution nanoparticle sizing system that is widely used as the standard method to measure airborne particle size distributions (PSD) in the size range 1 nm–1 μm. This paper addresses the problem to assess the uncertainty associated with PSD when a differential mobility analyzer (DMA) operates under scanning mode. The sources of uncertainty are described and then modeled either through experiments or knowledge extracted from the literature. Special care is brought to model the physics and to account for competing theories. Indeed, it appears that the modeling errors resulting from approximations of the physics can largely affect the final estimate of this indirect measurement, especially for quantities that are not measured during day-to-day experiments. The Monte Carlo method is used to compute the uncertainty associated with PSD. The method is tested against real data sets that are monosize polystyrene latex spheres (PSL) with nominal diameters of 100 nm, 200 nm and 450 nm. The median diameters and associated standard uncertainty of the aerosol particles are estimated as 101.22 nm  ±  0.18 nm, 204.39 nm  ±  1.71 nm and 443.87 nm  ±  1.52 nm with the new approach. Other statistical parameters, such as the mean diameter, the mode and the geometric mean and associated standard uncertainty, are also computed. These results are then compared with the results obtained by SMPS embedded software.

  20. Monte Carlo applications to radiation shielding problems

    International Nuclear Information System (INIS)

    Subbaiah, K.V.

    2009-01-01

    transport in complex geometries is straightforward, while even the simplest finite geometries (e.g., thin foils) are very difficult to be dealt with by the transport equation. The main drawback of the Monte Carlo method lies in its random nature: all the results are affected by statistical uncertainties, which can be reduced at the expense of increasing the sampled population, and, hence, the computation time. Under special circumstances, the statistical uncertainties may be lowered by using variance-reduction techniques. Monte Carlo methods tend to be used when it is infeasible or impossible to compute an exact result with a deterministic algorithm. The term Monte Carlo was coined in the 1940s by physicists working on nuclear weapon projects in the Los Alamos National Laboratory

  1. Evaluation of CANDU6 PCR (power coefficient of reactivity) with a 3-D whole-core Monte Carlo Analysis

    International Nuclear Information System (INIS)

    Motalab, Mohammad Abdul; Kim, Woosong; Kim, Yonghee

    2015-01-01

    Highlights: • The PCR of the CANDU6 reactor is slightly negative at low power, e.g. <80% P. • Doppler broadening of scattering resonances improves noticeably the FTC and make the PCR more negative or less positive in CANDU6. • The elevated inlet coolant condition can worsen significantly the PCR of CANDU6. • Improved design tools are needed for the safety evaluation of CANDU6 reactor. - Abstract: The power coefficient of reactivity (PCR) is a very important parameter for inherent safety and stability of nuclear reactors. The combined effect of a relatively less negative fuel temperature coefficient and a positive coolant temperature coefficient make the CANDU6 (CANada Deuterium Uranium) PCR very close to zero. In the original CANDU6 design, the PCR was calculated to be clearly negative. However, the latest physics design tools predict that the PCR is slightly positive for a wide operational range of reactor power. It is upon this contradictory observation that the CANDU6 PCR is re-evaluated in this work. In our previous study, the CANDU6 PCR was evaluated through a standard lattice analysis at mid-burnup and was found to be negative at low power. In this paper, the study was extended to a detailed 3-D CANDU6 whole-core model using the Monte Carlo code Serpent2. The Doppler broadening rejection correction (DBRC) method was implemented in the Serpent2 code in order to take into account thermal motion of the heavy uranium nucleus in the neutron-U scattering reactions. Time-average equilibrium core was considered for the evaluation of the representative PCR of CANDU6. Two thermal hydraulic models were considered in this work: one at design condition and the other at operating condition. Bundle-wise distributions of the coolant properties are modeled and the bundle-wise fuel temperature is also considered in this study. The evaluated nuclear data library ENDF/B-VII.0 was used throughout this Serpent2 evaluation. In these Monte Carlo calculations, a large number

  2. Solution weighting for the SAND-II Monte Carlo code

    International Nuclear Information System (INIS)

    Oster, C.A.; McElroy, W.N.; Simons, R.L.; Lippincott, E.P.; Odette, G.R.

    1976-01-01

    Modifications to the SAND-II Error Analysis Monte Carlo code to include solution weighting based on input data uncertainties have been made and are discussed together with background information on the SAND-II algorithm. The new procedure permits input data having smaller uncertainties to have a greater influence on the solution spectrum than do the data having larger uncertainties. The results of an indepth study to find a practical procedure and the first results of its application to three important Interlaboratory LMFBR Reaction Rate (ILRR) program benchmark spectra (CFRMF, ΣΣ, and 235 U fission) are discussed

  3. Monte Carlo simulation of parameter confidence intervals for non-linear regression analysis of biological data using Microsoft Excel.

    Science.gov (United States)

    Lambert, Ronald J W; Mytilinaios, Ioannis; Maitland, Luke; Brown, Angus M

    2012-08-01

    This study describes a method to obtain parameter confidence intervals from the fitting of non-linear functions to experimental data, using the SOLVER and Analysis ToolPaK Add-In of the Microsoft Excel spreadsheet. Previously we have shown that Excel can fit complex multiple functions to biological data, obtaining values equivalent to those returned by more specialized statistical or mathematical software. However, a disadvantage of using the Excel method was the inability to return confidence intervals for the computed parameters or the correlations between them. Using a simple Monte-Carlo procedure within the Excel spreadsheet (without recourse to programming), SOLVER can provide parameter estimates (up to 200 at a time) for multiple 'virtual' data sets, from which the required confidence intervals and correlation coefficients can be obtained. The general utility of the method is exemplified by applying it to the analysis of the growth of Listeria monocytogenes, the growth inhibition of Pseudomonas aeruginosa by chlorhexidine and the further analysis of the electrophysiological data from the compound action potential of the rodent optic nerve. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  4. Bayesian uncertainty quantification for flows in heterogeneous porous media using reversible jump Markov chain Monte Carlo methods

    KAUST Repository

    Mondal, A.; Efendiev, Y.; Mallick, B.; Datta-Gupta, A.

    2010-01-01

    . Within each channel, the permeability is assumed to have a lognormal distribution. Uncertainty quantification in history matching is carried out hierarchically by constructing geologic facies boundaries as well as permeability fields within each facies

  5. Successful vectorization - reactor physics Monte Carlo code

    International Nuclear Information System (INIS)

    Martin, W.R.

    1989-01-01

    Most particle transport Monte Carlo codes in use today are based on the ''history-based'' algorithm, wherein one particle history at a time is simulated. Unfortunately, the ''history-based'' approach (present in all Monte Carlo codes until recent years) is inherently scalar and cannot be vectorized. In particular, the history-based algorithm cannot take advantage of vector architectures, which characterize the largest and fastest computers at the current time, vector supercomputers such as the Cray X/MP or IBM 3090/600. However, substantial progress has been made in recent years in developing and implementing a vectorized Monte Carlo algorithm. This algorithm follows portions of many particle histories at the same time and forms the basis for all successful vectorized Monte Carlo codes that are in use today. This paper describes the basic vectorized algorithm along with descriptions of several variations that have been developed by different researchers for specific applications. These applications have been mainly in the areas of neutron transport in nuclear reactor and shielding analysis and photon transport in fusion plasmas. The relative merits of the various approach schemes will be discussed and the present status of known vectorization efforts will be summarized along with available timing results, including results from the successful vectorization of 3-D general geometry, continuous energy Monte Carlo. (orig.)

  6. Applications of the Monte Carlo method in radiation protection

    International Nuclear Information System (INIS)

    Kulkarni, R.N.; Prasad, M.A.

    1999-01-01

    This paper gives a brief introduction to the application of the Monte Carlo method in radiation protection. It may be noted that an exhaustive review has not been attempted. The special advantage of the Monte Carlo method has been first brought out. The fundamentals of the Monte Carlo method have next been explained in brief, with special reference to two applications in radiation protection. Some sample current applications have been reported in the end in brief as examples. They are, medical radiation physics, microdosimetry, calculations of thermoluminescence intensity and probabilistic safety analysis. The limitations of the Monte Carlo method have also been mentioned in passing. (author)

  7. Analysis of pumping performances in one-stage turbomolecular pump by 3D direct simulation Monte Carlo calculation

    International Nuclear Information System (INIS)

    Sheng Wang; Hisashi Ninokata

    2005-01-01

    The turbomolecular pump (TMP) has been applied in many fields for producing high and ultrahigh vacuum. It works mainly in conditions of free molecular and transitional flow where the mathematical model is the Boltzmann equation. In this paper, direct simulation Monte Carlo (DSMC) method is applied to simulate the one-stage TMP with a 3D analysis in a rotating reference frame. Considering the Coriolis and centrifugal accelerations, the equations about the molecular velocities and position are deduced. The VSS model and NTC collision schemes are used to calculate the intermolecular collisions. The diffuse reflection is employed on the molecular reflection from the surfaces of boundary. The transmission probabilities of gas flow in two opposite flow direction, the relationship between the mass flow rate and the pressure difference, the pumping performances including the maximum compression ratio on different outlet pressures in free molecular flow and transitional flow and the maximum pumping efficiency on different blade angles are calculated. The transmission probabilities are applied to analyze the relationship between the outlet pressure and the maximum pressure ratio. The numerical results show good quantitative agreement with the existing experiment data. (authors)

  8. Analysis of the neutrons dispersion in a semi-infinite medium based in transport theory and the Monte Carlo method

    International Nuclear Information System (INIS)

    Arreola V, G.; Vazquez R, R.; Guzman A, J. R.

    2012-10-01

    In this work a comparative analysis of the results for the neutrons dispersion in a not multiplicative semi-infinite medium is presented. One of the frontiers of this medium is located in the origin of coordinates, where a neutrons source in beam form, i.e., μο=1 is also. The neutrons dispersion is studied on the statistical method of Monte Carlo and through the unidimensional transport theory and for an energy group. The application of transport theory gives a semi-analytic solution for this problem while the statistical solution for the flow was obtained applying the MCNPX code. The dispersion in light water and heavy water was studied. A first remarkable result is that both methods locate the maximum of the neutrons distribution to less than two mean free trajectories of transport for heavy water, while for the light water is less than ten mean free trajectories of transport; the differences between both methods is major for the light water case. A second remarkable result is that the tendency of both distributions is similar in small mean free trajectories, while in big mean free trajectories the transport theory spreads to an asymptote value and the solution in base statistical method spreads to zero. The existence of a neutron current of low energy and toward the source is demonstrated, in contrary sense to the neutron current of high energy coming from the own source. (Author)

  9. Monte Carlo design study of a moderated {sup 252}Cf source for in vivo neutron activation analysis of aluminium

    Energy Technology Data Exchange (ETDEWEB)

    Lewis, D.G.; Natto, S.S.A.; Evans, C.J. [Swansea In Vivo Analysis and Cancer Research Group, Department of Physics, University of Wales, Swansea (United Kingdom); Ryde, S.J.S. [Swansea In Vivo Analysis and Cancer Research Group, Department of Medical Physics and Clinical Engineering, Singleton Hospital, Swansea (United Kingdom)

    1997-04-01

    The Monte Carlo computer code MCNP has been used to design a moderated 2{sup 52}Cf neutron source for in vivo neutron activation analysis of aluminium (Al) in the bones of the hand. The clinical motivation is the need to monitor l body burden in subjects with renal dysfunction, at risk of Al toxicity. The design involves the source positioned on the central axis at one end of a cylindrical deuterium oxide moderator. The moderator is surrounded by a graphite reflector, with the hand inserted at the end of the moderator opposing the source. For a 1 mg {sup 252}Cf source, 15 cm long x 20 cm radius moderator and 20 cm thick reflector, the estimated minimum detection limit is .5 mg Al for a 20 min irradiation, with an equivalent dose of 16.5 mSv to the hand. Increasing the moderator length and/or introducing a fast neutron filter (for example silicon) further reduces interference from fast-neutron-induced reactions on phosphorus in bone, at the expense of decreased fluence of the thermal neutrons which activate Al. Increased source strengths may be necessary to compensate for this decreased thermal fluence, or allow measurements to be made within an acceptable time limit for the comfort of the patient. (author)

  10. Statistics of Monte Carlo methods used in radiation transport calculation

    International Nuclear Information System (INIS)

    Datta, D.

    2009-01-01

    Radiation transport calculation can be carried out by using either deterministic or statistical methods. Radiation transport calculation based on statistical methods is basic theme of the Monte Carlo methods. The aim of this lecture is to describe the fundamental statistics required to build the foundations of Monte Carlo technique for radiation transport calculation. Lecture note is organized in the following way. Section (1) will describe the introduction of Basic Monte Carlo and its classification towards the respective field. Section (2) will describe the random sampling methods, a key component of Monte Carlo radiation transport calculation, Section (3) will provide the statistical uncertainty of Monte Carlo estimates, Section (4) will describe in brief the importance of variance reduction techniques while sampling particles such as photon, or neutron in the process of radiation transport

  11. Monte Carlo simulation of neutron scattering instruments

    International Nuclear Information System (INIS)

    Seeger, P.A.

    1995-01-01

    A library of Monte Carlo subroutines has been developed for the purpose of design of neutron scattering instruments. Using small-angle scattering as an example, the philosophy and structure of the library are described and the programs are used to compare instruments at continuous wave (CW) and long-pulse spallation source (LPSS) neutron facilities. The Monte Carlo results give a count-rate gain of a factor between 2 and 4 using time-of-flight analysis. This is comparable to scaling arguments based on the ratio of wavelength bandwidth to resolution width

  12. Hazardous waste transportation risk assessment: Benefits of a combined deterministic and probabilistic Monte Carlo approach in expressing risk uncertainty

    International Nuclear Information System (INIS)

    Policastro, A.J.; Lazaro, M.A.; Cowen, M.A.; Hartmann, H.M.; Dunn, W.E.; Brown, D.F.

    1995-01-01

    This paper presents a combined deterministic and probabilistic methodology for modeling hazardous waste transportation risk and expressing the uncertainty in that risk. Both the deterministic and probabilistic methodologies are aimed at providing tools useful in the evaluation of alternative management scenarios for US Department of Energy (DOE) hazardous waste treatment, storage, and disposal (TSD). The probabilistic methodology can be used to provide perspective on and quantify uncertainties in deterministic predictions. The methodology developed has been applied to 63 DOE shipments made in fiscal year 1992, which contained poison by inhalation chemicals that represent an inhalation risk to the public. Models have been applied to simulate shipment routes, truck accident rates, chemical spill probabilities, spill/release rates, dispersion, population exposure, and health consequences. The simulation presented in this paper is specific to trucks traveling from DOE sites to their commercial TSD facilities, but the methodology is more general. Health consequences are presented as the number of people with potentially life-threatening health effects. Probabilistic distributions were developed (based on actual item data) for accident release amounts, time of day and season of the accident, and meteorological conditions

  13. Transmutation approximations for the application of hybrid Monte Carlo/deterministic neutron transport to shutdown dose rate analysis

    International Nuclear Information System (INIS)

    Biondo, Elliott D.; Wilson, Paul P. H.

    2017-01-01

    In fusion energy systems (FES) neutrons born from burning plasma activate system components. The photon dose rate after shutdown from resulting radionuclides must be quantified. This shutdown dose rate (SDR) is calculated by coupling neutron transport, activation analysis, and photon transport. The size, complexity, and attenuating configuration of FES motivate the use of hybrid Monte Carlo (MC)/deterministic neutron transport. The Multi-Step Consistent Adjoint Driven Importance Sampling (MS-CADIS) method can be used to optimize MC neutron transport for coupled multiphysics problems, including SDR analysis, using deterministic estimates of adjoint flux distributions. When used for SDR analysis, MS-CADIS requires the formulation of an adjoint neutron source that approximates the transmutation process. In this work, transmutation approximations are used to derive a solution for this adjoint neutron source. It is shown that these approximations are reasonably met for typical FES neutron spectra and materials over a range of irradiation scenarios. When these approximations are met, the Groupwise Transmutation (GT)-CADIS method, proposed here, can be used effectively. GT-CADIS is an implementation of the MS-CADIS method for SDR analysis that uses a series of single-energy-group irradiations to calculate the adjoint neutron source. For a simple SDR problem, GT-CADIS provides speedups of 200 100 relative to global variance reduction with the Forward-Weighted (FW)-CADIS method and 9 _± 5 • _1_0_"_4 relative to analog. As a result, this work shows that GT-CADIS is broadly applicable to FES problems and will significantly reduce the computational resources necessary for SDR analysis.

  14. Monte Carlo Methods in Physics

    International Nuclear Information System (INIS)

    Santoso, B.

    1997-01-01

    Method of Monte Carlo integration is reviewed briefly and some of its applications in physics are explained. A numerical experiment on random generators used in the monte Carlo techniques is carried out to show the behavior of the randomness of various methods in generating them. To account for the weight function involved in the Monte Carlo, the metropolis method is used. From the results of the experiment, one can see that there is no regular patterns of the numbers generated, showing that the program generators are reasonably good, while the experimental results, shows a statistical distribution obeying statistical distribution law. Further some applications of the Monte Carlo methods in physics are given. The choice of physical problems are such that the models have available solutions either in exact or approximate values, in which comparisons can be mode, with the calculations using the Monte Carlo method. Comparison show that for the models to be considered, good agreement have been obtained

  15. Monte Carlo Study of the abBA Experiment: Detector Response and Physics Analysis.

    Science.gov (United States)

    Frlež, E

    2005-01-01

    The abBA collaboration proposes to conduct a comprehensive program of precise measurements of neutron β-decay coefficients a (the correlation between the neutrino momentum and the decay electron momentum), b (the electron energy spectral distortion term), A (the correlation between the neutron spin and the decay electron momentum), and B (the correlation between the neutron spin and the decay neutrino momentum) at a cold neutron beam facility. We have used a GEANT4-based code to simulate the propagation of decay electrons and protons in the electromagnetic spectrometer and study the energy and timing response of a pair of Silicon detectors. We used these results to examine systematic effects and find the uncertainties with which the physics parameters a, b, A, and B can be extracted from an over-determined experimental data set.

  16. A Monte Carlo approach to combating delayed completion of ...

    African Journals Online (AJOL)

    The objective of this paper is to unveil the relevance of Monte Carlo critical path analysis in resolving problem of delays in scheduled completion of development projects. Commencing with deterministic network scheduling, Monte Carlo critical path analysis was advanced by assigning probability distributions to task times.

  17. Dynamic analysis of once-through and closed fuel cycle economics using Monte Carlo simulation

    Energy Technology Data Exchange (ETDEWEB)

    Choi, Sungyeol, E-mail: csy@kaeri.re.kr; Lee, Hyo Jik, E-mail: hyojik@kaeri.re.kr; Ko, Won Il, E-mail: nwiko@kaeri.re.kr

    2014-10-01

    Highlights: • Dynamic behavior of system costs, both reactor and fuel cycle costs, is analyzed. • Relative economics of once-through and closed fuel cycles is explored. • Probabilistic approaches are adopted for levelized electricity generation costs. • Main cost drivers for cost gaps between once-through and closed cycles are identified. - Abstract: Although no consensus about the best approach to manage spent fuels has been achieved, economics is one of the major criteria for assessing and selecting acceptable management options. This study compares the reactor and fuel cycle costs of the closed system associated with sodium-cooled fast reactors and pyroprocessing versus the once-through system. We specifically investigated the fuel cycle transition cases of the Republic of Korea from 2013 to 2100. The results revealed that the closed system (34.00 mills/kWh as a mean value) could be more expensive than the once-through system (32.75 mills/kWh). In contrast, the once-through fuel cycle costs (8.31 mills/kWh), excluding reactor costs, were projected to be greater than the closed fuel cycle costs (7.77 mills/kWh) because of the increased costs of interim storage estimated by the Korean government and the limited contribution of backend fuel cycle components to the discounted costs. The capital cost of sodium-cooled fast reactor is the largest component contributing to the cost gap between the two systems. Among fuel cycle components, pyroprocessing has the largest uncertainty contribution to the cost gap. We also calculated the breakeven unit costs of SFR capital cost and PWR spent fuel pyroprocessing cost.

  18. The Dynamic Monte Carlo Method for Transient Analysis of Nuclear Reactors

    NARCIS (Netherlands)

    Sjenitzer, B.L.

    2013-01-01

    In this thesis a new method for the analysis of power transients in a nuclear reactor is developed, which is more accurate than the present state-of-the-art methods. Transient analysis is important tool when designing nuclear reactors, since they predict the behaviour of a reactor during changing

  19. Studies of Monte Carlo Modelling of Jets at ATLAS

    CERN Document Server

    Kar, Deepak; The ATLAS collaboration

    2017-01-01

    The predictions of different Monte Carlo generators for QCD jet production, both in multijets and for jets produced in association with other objects, are presented. Recent improvements in showering Monte Carlos provide new tools for assessing systematic uncertainties associated with these jets.  Studies of the dependence of physical observables on the choice of shower tune parameters and new prescriptions for assessing systematic uncertainties associated with the choice of shower model and tune are presented.

  20. Efficiency and accuracy of Monte Carlo (importance) sampling

    NARCIS (Netherlands)

    Waarts, P.H.

    2003-01-01

    Monte Carlo Analysis is often regarded as the most simple and accurate reliability method. Be-sides it is the most transparent method. The only problem is the accuracy in correlation with the efficiency. Monte Carlo gets less efficient or less accurate when very low probabilities are to be computed

  1. An Analysis of Spherical Particles Distribution Randomly Packed in a Medium for the Monte Carlo Implicit Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Jae Yong; Kim, Song Hyun; Shin, Chang Ho; Kim, Jong Kyung [Hanyang Univ., Seoul (Korea, Republic of)

    2014-05-15

    In this study, as a preliminary study to develop an implicit method having high accuracy, the distribution characteristics of spherical particles were evaluated by using explicit modeling techniques in various volume packing fractions. This study was performed to evaluate implicitly simulated distribution of randomly packed spheres in a medium. At first, an explicit modeling method to simulate random packed spheres in a hexahedron medium was proposed. The distributed characteristics of l{sub p} and r{sub p}, which are used in the particle position sampling, was estimated. It is analyzed that the use of the direct exponential distribution, which is generally used in the implicit modeling, can cause the distribution bias of the spheres. It is expected that the findings in this study can be utilized for improving the accuracy in using the implicit method. Spherical particles, which are randomly distributed in medium, are utilized for the radiation shields, fusion reactor blanket, fuels of VHTR reactors. Due to the difficulty on the simulation of the stochastic distribution, Monte Carlo (MC) method has been mainly considered as the tool for the analysis of the particle transport. For the MC modeling of the spherical particles, three methods are known; repeated structure, explicit modeling, and implicit modeling. Implicit method (called as the track length sampling method) is a modeling method that is the sampling based modeling technique of each spherical geometry (or track length of the sphere) during the MC simulation. Implicit modeling method has advantages in high computational efficiency and user convenience. However, it is noted that the implicit method has lower modeling accuracy in various finite mediums.

  2. Simulation of variation of apparent resistivity in resistivity surveys using finite difference modelling with Monte Carlo analysis

    Science.gov (United States)

    Aguirre, E. E.; Karchewski, B.

    2017-12-01

    DC resistivity surveying is a geophysical method that quantifies the electrical properties of the subsurface of the earth by applying a source current between two electrodes and measuring potential differences between electrodes at known distances from the source. Analytical solutions for a homogeneous half-space and simple subsurface models are well known, as the former is used to define the concept of apparent resistivity. However, in situ properties are heterogeneous meaning that simple analytical models are only an approximation, and ignoring such heterogeneity can lead to misinterpretation of survey results costing time and money. The present study examines the extent to which random variations in electrical properties (i.e. electrical conductivity) affect potential difference readings and therefore apparent resistivities, relative to an assumed homogeneous subsurface model. We simulate the DC resistivity survey using a Finite Difference (FD) approximation of an appropriate simplification of Maxwell's equations implemented in Matlab. Electrical resistivity values at each node in the simulation were defined as random variables with a given mean and variance, and are assumed to follow a log-normal distribution. The Monte Carlo analysis for a given variance of electrical resistivity was performed until the mean and variance in potential difference measured at the surface converged. Finally, we used the simulation results to examine the relationship between variance in resistivity and variation in surface potential difference (or apparent resistivity) relative to a homogeneous half-space model. For relatively low values of standard deviation in the material properties (<10% of mean), we observed a linear correlation between variance of resistivity and variance in apparent resistivity.

  3. Analysis of Various Multi-Objective Optimization Evolutionary Algorithms for Monte Carlo Treatment Planning System

    CERN Document Server

    Tydrichova, Magdalena

    2017-01-01

    In this project, various available multi-objective optimization evolutionary algorithms were compared considering their performance and distribution of solutions. The main goal was to select the most suitable algorithms for applications in cancer hadron therapy planning. For our purposes, a complex testing and analysis software was developed. Also, many conclusions and hypothesis have been done for the further research.

  4. Monte Carlo Algorithms for a Bayesian Analysis of the Cosmic Microwave Background

    Science.gov (United States)

    Jewell, Jeffrey B.; Eriksen, H. K.; ODwyer, I. J.; Wandelt, B. D.; Gorski, K.; Knox, L.; Chu, M.

    2006-01-01

    A viewgraph presentation on the review of Bayesian approach to Cosmic Microwave Background (CMB) analysis, numerical implementation with Gibbs sampling, a summary of application to WMAP I and work in progress with generalizations to polarization, foregrounds, asymmetric beams, and 1/f noise is given.

  5. Adaptive Markov Chain Monte Carlo

    KAUST Repository

    Jadoon, Khan

    2016-08-08

    A substantial interpretation of electromagnetic induction (EMI) measurements requires quantifying optimal model parameters and uncertainty of a nonlinear inverse problem. For this purpose, an adaptive Bayesian Markov chain Monte Carlo (MCMC) algorithm is used to assess multi-orientation and multi-offset EMI measurements in an agriculture field with non-saline and saline soil. In the MCMC simulations, posterior distribution was computed using Bayes rule. The electromagnetic forward model based on the full solution of Maxwell\\'s equations was used to simulate the apparent electrical conductivity measured with the configurations of EMI instrument, the CMD mini-Explorer. The model parameters and uncertainty for the three-layered earth model are investigated by using synthetic data. Our results show that in the scenario of non-saline soil, the parameters of layer thickness are not well estimated as compared to layers electrical conductivity because layer thicknesses in the model exhibits a low sensitivity to the EMI measurements, and is hence difficult to resolve. Application of the proposed MCMC based inversion to the field measurements in a drip irrigation system demonstrate that the parameters of the model can be well estimated for the saline soil as compared to the non-saline soil, and provide useful insight about parameter uncertainty for the assessment of the model outputs.

  6. Monte Carlo simulation of experiments

    International Nuclear Information System (INIS)

    Opat, G.I.

    1977-07-01

    An outline of the technique of computer simulation of particle physics experiments by the Monte Carlo method is presented. Useful special purpose subprograms are listed and described. At each stage the discussion is made concrete by direct reference to the programs SIMUL8 and its variant MONTE-PION, written to assist in the analysis of the radiative decay experiments μ + → e + ν sub(e) antiνγ and π + → e + ν sub(e)γ, respectively. These experiments were based on the use of two large sodium iodide crystals, TINA and MINA, as e and γ detectors. Instructions for the use of SIMUL8 and MONTE-PION are given. (author)

  7. Atomistic Monte Carlo simulation of lipid membranes

    DEFF Research Database (Denmark)

    Wüstner, Daniel; Sklenar, Heinz

    2014-01-01

    Biological membranes are complex assemblies of many different molecules of which analysis demands a variety of experimental and computational approaches. In this article, we explain challenges and advantages of atomistic Monte Carlo (MC) simulation of lipid membranes. We provide an introduction...... of local-move MC methods in combination with molecular dynamics simulations, for example, for studying multi-component lipid membranes containing cholesterol....

  8. Monte Carlo studies of ZEPLIN III

    CERN Document Server

    Dawson, J; Davidge, D C R; Gillespie, J R; Howard, A S; Jones, W G; Joshi, M; Lebedenko, V N; Sumner, T J; Quenby, J J

    2002-01-01

    A Monte Carlo simulation of a two-phase xenon dark matter detector, ZEPLIN III, has been achieved. Results from the analysis of a simulated data set are presented, showing primary and secondary signal distributions from low energy gamma ray events.

  9. Dynamic bounds coupled with Monte Carlo simulations

    NARCIS (Netherlands)

    Rajabali Nejad, Mohammadreza; Meester, L.E.; van Gelder, P.H.A.J.M.; Vrijling, J.K.

    2011-01-01

    For the reliability analysis of engineering structures a variety of methods is known, of which Monte Carlo (MC) simulation is widely considered to be among the most robust and most generally applicable. To reduce simulation cost of the MC method, variance reduction methods are applied. This paper

  10. Benchmark Analysis Of The High Temperature Gas Cooled Reactors Using Monte Carlo Technique

    International Nuclear Information System (INIS)

    Nguyen Kien Cuong; Huda, M.Q.

    2008-01-01

    Information about several past and present experimental and prototypical facilities based on High Temperature Gas-Cooled Reactor (HTGR) concepts have been examined to assess the potential of these facilities for use in this benchmarking effort. Both reactors and critical facilities applicable to pebble-bed type cores have been considered. Two facilities - HTR-PROTEUS of Switzerland and HTR-10 of China and one conceptual design from Germany - HTR-PAP20 - appear to have the greatest potential for use in benchmarking the codes. This study presents the benchmark analysis of these reactors technologies by using MCNP4C2 and MVP/GMVP Codes to support the evaluation and future development of HTGRs. The ultimate objective of this work is to identify and develop new capabilities needed to support Generation IV initiative. (author)

  11. Monte Carlo neutronics analysis of the ANS reactor three-element core design

    International Nuclear Information System (INIS)

    Wemple, C.A.

    1995-01-01

    The advanced neutron source (ANS) is a world-class research reactor and experimental center for neutron research, currently being designed at the Oak Ridge National Laboratory (ORNL). The reactor consists of a 330-MW(fission) highly enriched uranium core, which is cooled, moderated, and reflected with heavy water. It was designed to be the preeminent ultrahigh neutron flux reactor in the world, with facilities for research programs in biology, materials science, chemistry, fundamental and nuclear physics, and analytical chemistry. Irradiation facilities are provided for a variety of isotope production capabilities, as well as materials irradiation. This paper summarizes the neutronics efforts at the Idaho National Engineering Laboratory in support of the development and analysis of the three-element core for the advanced conceptual design phase

  12. Monte Carlo analysis of the slightly enriched uranium-D2O critical experiment LTRIIA (AWBA Development Program)

    International Nuclear Information System (INIS)

    Hardy, J. Jr.; Shore, J.M.

    1981-11-01

    The Savannah River Laboratory LTRIIA slightly-enriched uranium-D 2 O critical experiment was analyzed with ENDF/B-IV data and the RCP01 Monte Carlo program, which modeled the entire assembly in explicit detail. The integral parameters delta 25 and delta 28 showed good agreement with experiment. However, calculated K/sub eff/ was 2 to 3% low, due primarily to an overprediction of U238 capture. This is consistent with results obtained in similar analyses of the H 2 O-moderated TRX critical experiments. In comparisons with the VIM and MCNP2 Monte Carlo programs, good agreement was observed for calculated reeaction rates in the B 2 =0 cell

  13. Lectures on Monte Carlo methods

    CERN Document Server

    Madras, Neal

    2001-01-01

    Monte Carlo methods form an experimental branch of mathematics that employs simulations driven by random number generators. These methods are often used when others fail, since they are much less sensitive to the "curse of dimensionality", which plagues deterministic methods in problems with a large number of variables. Monte Carlo methods are used in many fields: mathematics, statistics, physics, chemistry, finance, computer science, and biology, for instance. This book is an introduction to Monte Carlo methods for anyone who would like to use these methods to study various kinds of mathemati

  14. Time-domain induced polarization - an analysis of Cole-Cole parameter resolution and correlation using Markov Chain Monte Carlo inversion

    Science.gov (United States)

    Madsen, Line Meldgaard; Fiandaca, Gianluca; Auken, Esben; Christiansen, Anders Vest

    2017-12-01

    The application of time-domain induced polarization (TDIP) is increasing with advances in acquisition techniques, data processing and spectral inversion schemes. An inversion of TDIP data for the spectral Cole-Cole parameters is a non-linear problem, but by applying a 1-D Markov Chain Monte Carlo (MCMC) inversion algorithm, a full non-linear uncertainty analysis of the parameters and the parameter correlations can be accessed. This is essential to understand to what degree the spectral Cole-Cole parameters can be resolved from TDIP data. MCMC inversions of synthetic TDIP data, which show bell-shaped probability distributions with a single maximum, show that the Cole-Cole parameters can be resolved from TDIP data if an acquisition range above two decades in time is applied. Linear correlations between the Cole-Cole parameters are observed and by decreasing the acquisitions ranges, the correlations increase and become non-linear. It is further investigated how waveform and parameter values influence the resolution of the Cole-Cole parameters. A limiting factor is the value of the frequency exponent, C. As C decreases, the resolution of all the Cole-Cole parameters decreases and the results become increasingly non-linear. While the values of the time constant, τ, must be in the acquisition range to resolve the parameters well, the choice between a 50 per cent and a 100 per cent duty cycle for the current injection does not have an influence on the parameter resolution. The limits of resolution and linearity are also studied in a comparison between the MCMC and a linearized gradient-based inversion approach. The two methods are consistent for resolved models, but the linearized approach tends to underestimate the uncertainties for poorly resolved parameters due to the corresponding non-linear features. Finally, an MCMC inversion of 1-D field data verifies that spectral Cole-Cole parameters can also be resolved from TD field measurements.

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

    Directory of Open Access Journals (Sweden)

    Hui-Jun Guo

    2014-09-01

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

  16. Computer system for Monte Carlo experimentation

    International Nuclear Information System (INIS)

    Grier, D.A.

    1986-01-01

    A new computer system for Monte Carlo Experimentation is presented. The new system speeds and simplifies the process of coding and preparing a Monte Carlo Experiment; it also encourages the proper design of Monte Carlo Experiments, and the careful analysis of the experimental results. A new functional language is the core of this system. Monte Carlo Experiments, and their experimental designs, are programmed in this new language; those programs are compiled into Fortran output. The Fortran output is then compiled and executed. The experimental results are analyzed with a standard statistics package such as Si, Isp, or Minitab or with a user-supplied program. Both the experimental results and the experimental design may be directly loaded into the workspace of those packages. The new functional language frees programmers from many of the details of programming an experiment. Experimental designs such as factorial, fractional factorial, or latin square are easily described by the control structures and expressions of the language. Specific mathematical modes are generated by the routines of the language

  17. Biases in Monte Carlo eigenvalue calculations

    Energy Technology Data Exchange (ETDEWEB)

    Gelbard, E.M.

    1992-12-01

    The Monte Carlo method has been used for many years to analyze the neutronics of nuclear reactors. In fact, as the power of computers has increased the importance of Monte Carlo in neutronics has also increased, until today this method plays a central role in reactor analysis and design. Monte Carlo is used in neutronics for two somewhat different purposes, i.e., (a) to compute the distribution of neutrons in a given medium when the neutron source-density is specified, and (b) to compute the neutron distribution in a self-sustaining chain reaction, in which case the source is determined as the eigenvector of a certain linear operator. In (b), then, the source is not given, but must be computed. In the first case (the ``fixed-source`` case) the Monte Carlo calculation is unbiased. That is to say that, if the calculation is repeated (``replicated``) over and over, with independent random number sequences for each replica, then averages over all replicas will approach the correct neutron distribution as the number of replicas goes to infinity. Unfortunately, the computation is not unbiased in the second case, which we discuss here.

  18. Biases in Monte Carlo eigenvalue calculations

    Energy Technology Data Exchange (ETDEWEB)

    Gelbard, E.M.

    1992-01-01

    The Monte Carlo method has been used for many years to analyze the neutronics of nuclear reactors. In fact, as the power of computers has increased the importance of Monte Carlo in neutronics has also increased, until today this method plays a central role in reactor analysis and design. Monte Carlo is used in neutronics for two somewhat different purposes, i.e., (a) to compute the distribution of neutrons in a given medium when the neutron source-density is specified, and (b) to compute the neutron distribution in a self-sustaining chain reaction, in which case the source is determined as the eigenvector of a certain linear operator. In (b), then, the source is not given, but must be computed. In the first case (the fixed-source'' case) the Monte Carlo calculation is unbiased. That is to say that, if the calculation is repeated ( replicated'') over and over, with independent random number sequences for each replica, then averages over all replicas will approach the correct neutron distribution as the number of replicas goes to infinity. Unfortunately, the computation is not unbiased in the second case, which we discuss here.

  19. Dynamic bounds coupled with Monte Carlo simulations

    Energy Technology Data Exchange (ETDEWEB)

    Rajabalinejad, M., E-mail: M.Rajabalinejad@tudelft.n [Faculty of Civil Engineering, Delft University of Technology, Delft (Netherlands); Meester, L.E. [Delft Institute of Applied Mathematics, Delft University of Technology, Delft (Netherlands); Gelder, P.H.A.J.M. van; Vrijling, J.K. [Faculty of Civil Engineering, Delft University of Technology, Delft (Netherlands)

    2011-02-15

    For the reliability analysis of engineering structures a variety of methods is known, of which Monte Carlo (MC) simulation is widely considered to be among the most robust and most generally applicable. To reduce simulation cost of the MC method, variance reduction methods are applied. This paper describes a method to reduce the simulation cost even further, while retaining the accuracy of Monte Carlo, by taking into account widely present monotonicity. For models exhibiting monotonic (decreasing or increasing) behavior, dynamic bounds (DB) are defined, which in a coupled Monte Carlo simulation are updated dynamically, resulting in a failure probability estimate, as well as a strict (non-probabilistic) upper and lower bounds. Accurate results are obtained at a much lower cost than an equivalent ordinary Monte Carlo simulation. In a two-dimensional and a four-dimensional numerical example, the cost reduction factors are 130 and 9, respectively, where the relative error is smaller than 5%. At higher accuracy levels, this factor increases, though this effect is expected to be smaller with increasing dimension. To show the application of DB method to real world problems, it is applied to a complex finite element model of a flood wall in New Orleans.

  20. Biases in Monte Carlo eigenvalue calculations

    International Nuclear Information System (INIS)

    Gelbard, E.M.

    1992-01-01

    The Monte Carlo method has been used for many years to analyze the neutronics of nuclear reactors. In fact, as the power of computers has increased the importance of Monte Carlo in neutronics has also increased, until today this method plays a central role in reactor analysis and design. Monte Carlo is used in neutronics for two somewhat different purposes, i.e., (a) to compute the distribution of neutrons in a given medium when the neutron source-density is specified, and (b) to compute the neutron distribution in a self-sustaining chain reaction, in which case the source is determined as the eigenvector of a certain linear operator. In (b), then, the source is not given, but must be computed. In the first case (the ''fixed-source'' case) the Monte Carlo calculation is unbiased. That is to say that, if the calculation is repeated (''replicated'') over and over, with independent random number sequences for each replica, then averages over all replicas will approach the correct neutron distribution as the number of replicas goes to infinity. Unfortunately, the computation is not unbiased in the second case, which we discuss here

  1. Advanced Multilevel Monte Carlo Methods

    KAUST Repository

    Jasra, Ajay; Law, Kody; Suciu, Carina

    2017-01-01

    This article reviews the application of advanced Monte Carlo techniques in the context of Multilevel Monte Carlo (MLMC). MLMC is a strategy employed to compute expectations which can be biased in some sense, for instance, by using the discretization of a associated probability law. The MLMC approach works with a hierarchy of biased approximations which become progressively more accurate and more expensive. Using a telescoping representation of the most accurate approximation, the method is able to reduce the computational cost for a given level of error versus i.i.d. sampling from this latter approximation. All of these ideas originated for cases where exact sampling from couples in the hierarchy is possible. This article considers the case where such exact sampling is not currently possible. We consider Markov chain Monte Carlo and sequential Monte Carlo methods which have been introduced in the literature and we describe different strategies which facilitate the application of MLMC within these methods.

  2. Advanced Multilevel Monte Carlo Methods

    KAUST Repository

    Jasra, Ajay

    2017-04-24

    This article reviews the application of advanced Monte Carlo techniques in the context of Multilevel Monte Carlo (MLMC). MLMC is a strategy employed to compute expectations which can be biased in some sense, for instance, by using the discretization of a associated probability law. The MLMC approach works with a hierarchy of biased approximations which become progressively more accurate and more expensive. Using a telescoping representation of the most accurate approximation, the method is able to reduce the computational cost for a given level of error versus i.i.d. sampling from this latter approximation. All of these ideas originated for cases where exact sampling from couples in the hierarchy is possible. This article considers the case where such exact sampling is not currently possible. We consider Markov chain Monte Carlo and sequential Monte Carlo methods which have been introduced in the literature and we describe different strategies which facilitate the application of MLMC within these methods.

  3. Monte Carlo simulation for IRRMA

    International Nuclear Information System (INIS)

    Gardner, R.P.; Liu Lianyan

    2000-01-01

    Monte Carlo simulation is fast becoming a standard approach for many radiation applications that were previously treated almost entirely by experimental techniques. This is certainly true for Industrial Radiation and Radioisotope Measurement Applications - IRRMA. The reasons for this include: (1) the increased cost and inadequacy of experimentation for design and interpretation purposes; (2) the availability of low cost, large memory, and fast personal computers; and (3) the general availability of general purpose Monte Carlo codes that are increasingly user-friendly, efficient, and accurate. This paper discusses the history and present status of Monte Carlo simulation for IRRMA including the general purpose (GP) and specific purpose (SP) Monte Carlo codes and future needs - primarily from the experience of the authors

  4. Present status and future prospects of neutronics Monte Carlo

    International Nuclear Information System (INIS)

    Gelbard, E.M.

    1990-01-01

    It is fair to say that the Monte Carlo method, over the last decade, has grown steadily more important as a neutronics computational tool. Apparently this has happened for assorted reasons. Thus, for example, as the power of computers has increased, the cost of the method has dropped, steadily becoming less and less of an obstacle to its use. In addition, more and more sophisticated input processors have now made it feasible to model extremely complicated systems routinely with really remarkable fidelity. Finally, as we demand greater and greater precision in reactor calculations, Monte Carlo is often found to be the only method accurate enough for use in benchmarking. Cross section uncertainties are now almost the only inherent limitations in our Monte Carlo capabilities. For this reason Monte Carlo has come to occupy a special position, interposed between experiment and other computational techniques. More and more often deterministic methods are tested by comparison with Monte Carlo, and cross sections are tested by comparing Monte Carlo with experiment. In this way one can distinguish very clearly between errors due to flaws in our numerical methods, and those due to deficiencies in cross section files. The special role of Monte Carlo as a benchmarking tool, often the only available benchmarking tool, makes it crucially important that this method should be polished to perfection. Problems relating to Eigenvalue calculations, variance reduction and the use of advanced computers are reviewed in this paper. (author)

  5. Behavioral Analysis of Visitors to a Medical Institution’s Website Using Markov Chain Monte Carlo Methods

    Science.gov (United States)

    Tani, Yuji

    2016-01-01

    Background Consistent with the “attention, interest, desire, memory, action” (AIDMA) model of consumer behavior, patients collect information about available medical institutions using the Internet to select information for their particular needs. Studies of consumer behavior may be found in areas other than medical institution websites. Such research uses Web access logs for visitor search behavior. At this time, research applying the patient searching behavior model to medical institution website visitors is lacking. Objective We have developed a hospital website search behavior model using a Bayesian approach to clarify the behavior of medical institution website visitors and determine the probability of their visits, classified by search keyword. Methods We used the website data access log of a clinic of internal medicine and gastroenterology in the Sapporo suburbs, collecting data from January 1 through June 31, 2011. The contents of the 6 website pages included the following: home, news, content introduction for medical examinations, mammography screening, holiday person-on-duty information, and other. The search keywords we identified as best expressing website visitor needs were listed as the top 4 headings from the access log: clinic name, clinic name + regional name, clinic name + medical examination, and mammography screening. Using the search keywords as the explaining variable, we built a binomial probit model that allows inspection of the contents of each purpose variable. Using this model, we determined a beta value and generated a posterior distribution. We performed the simulation using Markov Chain Monte Carlo methods with a noninformation prior distribution for this model and determined the visit probability classified by keyword for each category. Results In the case of the keyword “clinic name,” the visit probability to the website, repeated visit to the website, and contents page for medical examination was positive. In the case of the

  6. Monte Carlo theory and practice

    International Nuclear Information System (INIS)

    James, F.

    1987-01-01

    Historically, the first large-scale calculations to make use of the Monte Carlo method were studies of neutron scattering and absorption, random processes for which it is quite natural to employ random numbers. Such calculations, a subset of Monte Carlo calculations, are known as direct simulation, since the 'hypothetical population' of the narrower definition above corresponds directly to the real population being studied. The Monte Carlo method may be applied wherever it is possible to establish equivalence between the desired result and the expected behaviour of a stochastic system. The problem to be solved may already be of a probabilistic or statistical nature, in which case its Monte Carlo formulation will usually be a straightforward simulation, or it may be of a deterministic or analytic nature, in which case an appropriate Monte Carlo formulation may require some imagination and may appear contrived or artificial. In any case, the suitability of the method chosen will depend on its mathematical properties and not on its superficial resemblance to the problem to be solved. The authors show how Monte Carlo techniques may be compared with other methods of solution of the same physical problem

  7. Coevolution Based Adaptive Monte Carlo Localization (CEAMCL

    Directory of Open Access Journals (Sweden)

    Luo Ronghua

    2008-11-01

    Full Text Available An adaptive Monte Carlo localization algorithm based on coevolution mechanism of ecological species is proposed. Samples are clustered into species, each of which represents a hypothesis of the robot's pose. Since the coevolution between the species ensures that the multiple distinct hypotheses can be tracked stably, the problem of premature convergence when using MCL in highly symmetric environments can be solved. And the sample size can be adjusted adaptively over time according to the uncertainty of the robot's pose by using the population growth model. In addition, by using the crossover and mutation operators in evolutionary computation, intra-species evolution can drive the samples move towards the regions where the desired posterior density is large. So a small size of samples can represent the desired density well enough to make precise localization. The new algorithm is termed coevolution based adaptive Monte Carlo localization (CEAMCL. Experiments have been carried out to prove the efficiency of the new localization algorithm.

  8. A Monte Carlo Method for the Analysis of Gamma Radiation Transport from Distributed Sources in Laminated Shields

    International Nuclear Information System (INIS)

    Leimdoerfer, M.

    1964-02-01

    A description is given of a method for calculating the penetration and energy deposition of gamma radiation, based on Monte Carlo techniques. The essential feature is the application of the exponential transformation to promote the transport of penetrating quanta and to balance the steep spatial variations of the source distributions which appear in secondary gamma emission problems. The estimated statistical errors in a number of sample problems, involving concrete shields with thicknesses up to 500 cm, are shown to be quite favorable, even at relatively short computing times. A practical reactor shielding problem is also shown and the predictions compared with measurements

  9. Variance analysis of the Monte Carlo perturbation source method in inhomogeneous linear particle transport problems. Derivation of formulae

    International Nuclear Information System (INIS)

    Noack, K.

    1981-01-01

    The perturbation source method is used in the Monte Carlo method in calculating small effects in a particle field. It offers primising possibilities for introducing positive correlation between subtracting estimates even in the cases where other methods fail, in the case of geometrical variations of a given arrangement. The perturbation source method is formulated on the basis of integral equations for the particle fields. The formulae for the second moment of the difference of events are derived. Explicity a certain class of transport games and different procedures for generating the so-called perturbation particles are considered [ru

  10. A Monte Carlo Method for the Analysis of Gamma Radiation Transport from Distributed Sources in Laminated Shields

    Energy Technology Data Exchange (ETDEWEB)

    Leimdoerfer, M

    1964-02-15

    A description is given of a method for calculating the penetration and energy deposition of gamma radiation, based on Monte Carlo techniques. The essential feature is the application of the exponential transformation to promote the transport of penetrating quanta and to balance the steep spatial variations of the source distributions which appear in secondary gamma emission problems. The estimated statistical errors in a number of sample problems, involving concrete shields with thicknesses up to 500 cm, are shown to be quite favorable, even at relatively short computing times. A practical reactor shielding problem is also shown and the predictions compared with measurements.

  11. Neutronic analysis for conversion of the Ghana Research Reactor-1 facility using Monte Carlo methods and UO{sub 2} LEU fuel

    Energy Technology Data Exchange (ETDEWEB)

    Anim-Sampong, S.; Akaho, E.H.K.; Maakuu, B.T.; Gbadago, J.K. [Ghana Research Reactor-1 Centre, Dept. of Nuclear Engineering and Materials Science, National Nuclear Research Institute, Ghana Atomic Energy Commission, Legon, Accra (Ghana); Andam, A. [Kwame Nkrumah Univ. of Science and Technology, Dept. of Physics (Ghana); Liaw, J.J.R.; Matos, J.E. [Argonne National Lab., RERTR Programme, Div. of Nuclear Engineering (United States)

    2007-07-01

    Monte Carlo particle transport methods and software (MCNP) have been applied to the modelling, simulation and neutronic analysis for the conversion of the HEU-fuelled (high enrichment uranium) core of the Ghana Research Reactor-1 (GHARR-1) facility. The results show that the MCNP model of the GHARR-1 facility, which is a commercial version of the Miniature Neutron Source Reactor (MNSR) is good as the simulated neutronic and other reactor physics parameters agree with very well with experimental and zero power results. Three UO{sub 2} LEU (low enrichment uranium) fuels with different enrichments (12.6% and 19.75%), core configurations, core loadings were utilized in the conversion studies. The nuclear criticality and kinetic parameters obtained from the Monte Carlo simulation and neutronic analysis using three UO{sub 2} LEU fuels are in close agreement with results obtained for the reference 90.2% U-Al HEU core. The neutron flux variation in the core, fission chamber and irradiation channels for the LEU UO{sub 2} fuels show the same trend as the HEU core as presented in the paper. The Monte Carlo model confirms a reduction (8% max) in the peak neutron fluxes simulated in the irradiation channels which are utilized for experimental and commercial activities. However, the reductions or 'losses' in the flux levels neither affects the criticality safety, reactor operations and safety nor utilization of the reactor. Employing careful core loading optimization techniques and fuel loadings and enrichment, it is possible to eliminate the apparent reductions or 'losses' in the neutron fluxes as suggested in this paper. Concerning neutronics, it can be concluded that all the 3 LEU fuels qualify as LEU candidates for core conversion of the GHARR-1 facility.

  12. Monte Carlo techniques for analyzing deep penetration problems

    International Nuclear Information System (INIS)

    Cramer, S.N.; Gonnord, J.; Hendricks, J.S.

    1985-01-01

    A review of current methods and difficulties in Monte Carlo deep-penetration calculations is presented. Statistical uncertainty is discussed, and recent adjoint optimization of splitting, Russian roulette, and exponential transformation biasing is reviewed. Other aspects of the random walk and estimation processes are covered, including the relatively new DXANG angular biasing technique. Specific items summarized are albedo scattering, Monte Carlo coupling techniques with discrete ordinates and other methods, adjoint solutions, and multi-group Monte Carlo. The topic of code-generated biasing parameters is presented, including the creation of adjoint importance functions from forward calculations. Finally, current and future work in the area of computer learning and artificial intelligence is discussed in connection with Monte Carlo applications

  13. Monte Carlo techniques for analyzing deep penetration problems

    International Nuclear Information System (INIS)

    Cramer, S.N.; Gonnord, J.; Hendricks, J.S.

    1985-01-01

    A review of current methods and difficulties in Monte Carlo deep-penetration calculations is presented. Statistical uncertainty is discussed, and recent adjoint optimization of splitting, Russian roulette, and exponential transformation biasing is reviewed. Other aspects of the random walk and estimation processes are covered, including the relatively new DXANG angular biasing technique. Specific items summarized are albedo scattering, Monte Carlo coupling techniques with discrete ordinates and other methods, adjoint solutions, and multi-group Monte Carlo. The topic of code-generated biasing parameters is presented, including the creation of adjoint importance functions from forward calculations. Finally, current and future work in the area of computer learning and artificial intelligence is discussed in connection with Monte Carlo applications. 29 refs

  14. Application of Monte-Carlo method in definition of key categories of most radioactive polluted soil

    International Nuclear Information System (INIS)

    Mahmudov, H.M.; Valibeyova, G.; Jafarov, Y.D.; Musaeva, Sh.Z.

    2006-01-01

    Full text: The principle of analysis by Monte Carlo method consists of a choice of random variables of coefficients of an exposition doze capacities of radiation and data on activity within the boundaries of their individual density of frequency distribution upon corresponding sizes of exposition doses capacities. This procedure repeats for many times using computer and results of each round of calculations create universal density of frequency distribution of exposition doses capacities. The analysis using Monte Carlo method can be carried out at the level of radiation polluted soil categories. The analysis by Monte Carlo method is useful for realization of sensitivity analysis of measured capacity amount of an exposition dose in order to define the major factors causing uncertainty in reports. Reception of such conceptions can be valuable for definition of key categories of radiation polluted soil and establishment of priorities to use resources for enhancement of the report. Relative uncertainty of radiation polluted soil categories determined with the help of the analysis by Monte Carlo method in case of their availability can be applied using more significant divergence between average value and a confidential limit in case when borders of a confidential interval are asymmetric. It is important to determine key categories of radiation polluted soil to establish priorities to use reports of resources available for preparation and to prepare possible estimations for the most significant categories of sources. Usage of the notion u ncertainty i n reports also allows to set threshold value for a key category of sources, if it is necessary, for exact reflection of 90 percent uncertainty in reports. According to radiation safety norms level of radiation background exceeding 33 mkR/hour is considered dangerous. By calculated Monte Carlo method much more dangerous sites and sites frequently imposed to disposals and utilization were chosen from analyzed samples of

  15. Application of Monte-Carlo method in definition of key categories of most radioactive polluted soil

    Energy Technology Data Exchange (ETDEWEB)

    Mahmudov, H M; Valibeyova, G; Jafarov, Y D; Musaeva, Sh Z [Institute of Radiation Problems, Azerbaijan National Academy of Sciences, Baku (Azerbaijan)

    2006-11-15

    Full text: The principle of analysis by Monte Carlo method consists of a choice of random variables of coefficients of an exposition doze capacities of radiation and data on activity within the boundaries of their individual density of frequency distribution upon corresponding sizes of exposition doses capacities. This procedure repeats for many times using computer and results of each round of calculations create universal density of frequency distribution of exposition doses capacities. The analysis using Monte Carlo method can be carried out at the level of radiation polluted soil categories. The analysis by Monte Carlo method is useful for realization of sensitivity analysis of measured capacity amount of an exposition dose in order to define the major factors causing uncertainty in reports. Reception of such conceptions can be valuable for definition of key categories of radiation polluted soil and establishment of priorities to use resources for enhancement of the report. Relative uncertainty of radiation polluted soil categories determined with the help of the analysis by Monte Carlo method in case of their availability can be applied using more significant divergence between average value and a confidential limit in case when borders of a confidential interval are asymmetric. It is important to determine key categories of radiation polluted soil to establish priorities to use reports of resources available for preparation and to prepare possible estimations for the most significant categories of sources. Usage of the notion {sup u}ncertainty{sup i}n reports also allows to set threshold value for a key category of sources, if it is necessary, for exact reflection of 90 percent uncertainty in reports. According to radiation safety norms level of radiation background exceeding 33 mkR/hour is considered dangerous. By calted Monte Carlo method much more dangerous sites and sites frequently imposed to disposals and utilization were chosen from analyzed samples of

  16. Measurement of dose rates and Monte Carlo analysis of neutrons in a spent-fuel shipping vessel

    International Nuclear Information System (INIS)

    Ueki, K.; Namito, Y.; Fuse, T.

    1986-01-01

    On-board experiments were carried out in a spent-fuel shipping vessel, the Pacific Swan, in which 13 casks of TN-12A and Excellox 3 were loaded in five holds, and neutron and gamma-ray dose rates were measured on the hatch covers of the holds. Before shipping those casks, dose rates were also measured on the cask surfaces, one by one, to eliminate radiation from other casks. The Monte Carlo coupling technique was employed successfully to analyze the measured neutron dose rate distributions in the spent-fuel shipping vessel. Through this study, the Monte Carlo coupling code system, MORSE-CG/CASK-VESSEL, on which the MORSE-CG code was based, was established. The agreement between the measured and the calculated neutron dose rates on the TN-12A cask surface was quite satisfactory. The calculated neutron dose rates agreed with the measured values within a factor of 1.5 on the hold 3 hatch cover and within a factor of 2 on the hold 5 hatch cover in which the concrete shield was fixed in the Pacific Swan

  17. Diagrammatic Monte Carlo approach for diagrammatic extensions of dynamical mean-field theory: Convergence analysis of the dual fermion technique

    Science.gov (United States)

    Gukelberger, Jan; Kozik, Evgeny; Hafermann, Hartmut

    2017-07-01

    The dual fermion approach provides a formally exact prescription for calculating properties of a correlated electron system in terms of a diagrammatic expansion around dynamical mean-field theory (DMFT). Most practical implementations, however, neglect higher-order interaction vertices beyond two-particle scattering in the dual effective action and further truncate the diagrammatic expansion in the two-particle scattering vertex to a leading-order or ladder-type approximation. In this work, we compute the dual fermion expansion for the two-dimensional Hubbard model including all diagram topologies with two-particle interactions to high orders by means of a stochastic diagrammatic Monte Carlo algorithm. We benchmark the obtained self-energy against numerically exact diagrammatic determinant Monte Carlo simulations to systematically assess convergence of the dual fermion series and the validity of these approximations. We observe that, from high temperatures down to the vicinity of the DMFT Néel transition, the dual fermion series converges very quickly to the exact solution in the whole range of Hubbard interactions considered (4 ≤U /t ≤12 ), implying that contributions from higher-order vertices are small. As the temperature is lowered further, we observe slower series convergence, convergence to incorrect solutions, and ultimately divergence. This happens in a regime where magnetic correlations become significant. We find, however, that the self-consistent particle-hole ladder approximation yields reasonable and often even highly accurate results in this regime.

  18. Implications of Monte Carlo Statistical Errors in Criticality Safety Assessments

    International Nuclear Information System (INIS)

    Pevey, Ronald E.

    2005-01-01

    Most criticality safety calculations are performed using Monte Carlo techniques because of Monte Carlo's ability to handle complex three-dimensional geometries. For Monte Carlo calculations, the more histories sampled, the lower the standard deviation of the resulting estimates. The common intuition is, therefore, that the more histories, the better; as a result, analysts tend to run Monte Carlo analyses as long as possible (or at least to a minimum acceptable uncertainty). For Monte Carlo criticality safety analyses, however, the optimization situation is complicated by the fact that procedures usually require that an extra margin of safety be added because of the statistical uncertainty of the Monte Carlo calculations. This additional safety margin affects the impact of the choice of the calculational standard deviation, both on production and on safety. This paper shows that, under the assumptions of normally distributed benchmarking calculational errors and exact compliance with the upper subcritical limit (USL), the standard deviation that optimizes production is zero, but there is a non-zero value of the calculational standard deviation that minimizes the risk of inadvertently labeling a supercritical configuration as subcritical. Furthermore, this value is shown to be a simple function of the typical benchmarking step outcomes--the bias, the standard deviation of the bias, the upper subcritical limit, and the number of standard deviations added to calculated k-effectives before comparison to the USL

  19. Multilevel sequential Monte Carlo samplers

    KAUST Repository

    Beskos, Alexandros; Jasra, Ajay; Law, Kody; Tempone, Raul; Zhou, Yan

    2016-01-01

    In this article we consider 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 which depend on the step-size level . hL. 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 discretization levels . ∞>h0>h1⋯>hL. In many practical problems of interest, one cannot achieve an i.i.d. sampling of the associated sequence and a sequential Monte Carlo (SMC) version of the MLMC method is introduced to deal with this problem. 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. That is, relative to exact sampling and Monte Carlo for the distribution at the finest level . hL. The approach is numerically illustrated on a Bayesian inverse problem. © 2016 Elsevier B.V.

  20. Multilevel sequential Monte Carlo samplers

    KAUST Repository

    Beskos, Alexandros

    2016-08-29

    In this article we consider 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 which depend on the step-size level . hL. 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 discretization levels . ∞>h0>h1⋯>hL. In many practical problems of interest, one cannot achieve an i.i.d. sampling of the associated sequence and a sequential Monte Carlo (SMC) version of the MLMC method is introduced to deal with this problem. 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. That is, relative to exact sampling and Monte Carlo for the distribution at the finest level . hL. The approach is numerically illustrated on a Bayesian inverse problem. © 2016 Elsevier B.V.

  1. Monte Carlo criticality analysis of simple geometries containing tungsten-rhenium alloys engrained with uranium dioxide and uranium mononitride

    International Nuclear Information System (INIS)

    Webb, Jonathan A.; Charit, Indrajit

    2011-01-01

    geometries were also computationally submerged in a neutronically infinite medium of fresh water to determine the effects of rhenium addition on criticality accidents due to water submersion. The Monte Carlo analysis demonstrated that rhenium addition of up to 30 at.% can reduce the excess reactivity due to water submersion by up to $5.07 for UO 2 fueled cylinders, $3.87 for UO 2 fueled spheres and approximately $3.00 for UN fueled spheres and cylinders.

  2. Strategije drevesnega preiskovanja Monte Carlo

    OpenAIRE

    VODOPIVEC, TOM

    2018-01-01

    Po preboju pri igri go so metode drevesnega preiskovanja Monte Carlo (ang. Monte Carlo tree search – MCTS) sprožile bliskovit napredek agentov za igranje iger: raziskovalna skupnost je od takrat razvila veliko variant in izboljšav algoritma MCTS ter s tem zagotovila napredek umetne inteligence ne samo pri igrah, ampak tudi v številnih drugih domenah. Čeprav metode MCTS združujejo splošnost naključnega vzorčenja z natančnostjo drevesnega preiskovanja, imajo lahko v praksi težave s počasno konv...

  3. Application of monte-carlo method in definition of key categories of most radioactive polluted soil

    Energy Technology Data Exchange (ETDEWEB)

    Mahmudov, H M; Valibeyova, G; Jafarov, Y D; Musaeva, Sh Z [Institute of Radiation Problems, Azerbaijan National Academy of Sciences, Baku (Azerbaijan); others, and

    2006-10-15

    Full text: The principle of analysis by Monte Carlo method consists of a choice of random variables of coefficients of an exposition doze capasites of radiation and data on activity within the boundaries of their individual density of frequency distribution of exposition doses capacities.The analysis using Monte Carlo method is useful for realization of sensitivity analysis of measured capacity amount of an exposition dose in order to define the major factors causing uncertainly in reports.Reception of such conceptions can be valuable for definition of key categories of radiation polluted soil and establishment of priorities to use resources for enhancement of the report.Relative uncertainly of radiation polluted soil categories determined with the help of the analysis by Monte Carlo method in case of their availability can be applied using more significant divergence between average value and a confidential limit in case when borders of resources available for preparation and to prepare possible estimations for the most significant categories of sources.Usage of the notion {sup u}ncertainty{sup i}n reports also allows to set threshold value for a key category of sources, if it necessary, for exact reflection of 90 per cent uncertainty in reports.According to radiation safety norms level of radiation backgrounds exceeding 33 mkR/hour is considered dangerous.By calculated Monte Carlo method much more dangerous sites and sites frequently imposed to disposals and utilization were chosen from analyzed samples of polluted soil.

  4. Application of monte-carlo method in definition of key categories of most radioactive polluted soil

    International Nuclear Information System (INIS)

    Mahmudov, H.M; Valibeyova, G.; Jafarov, Y.D; Musaeva, Sh.Z

    2006-01-01

    Full text: The principle of analysis by Monte Carlo method consists of a choice of random variables of coefficients of an exposition doze capasites of radiation and data on activity within the boundaries of their individual density of frequency distribution of exposition doses capacities.The analysis using Monte Carlo method is useful for realization of sensitivity analysis of measured capacity amount of an exposition dose in order to define the major factors causing uncertainly in reports.Reception of such conceptions can be valuable for definition of key categories of radiation polluted soil and establishment of priorities to use resources for enhancement of the report.Relative uncertainly of radiation polluted soil categories determined with the help of the analysis by Monte Carlo method in case of their availability can be applied using more significant divergence between average value and a confidential limit in case when borders of resources available for preparation and to prepare possible estimations for the most significant categories of sources.Usage of the notion u ncertainty i n reports also allows to set threshold value for a key category of sources, if it necessary, for exact reflection of 90 per cent uncertainty in reports.According to radiation safety norms level of radiation backgrounds exceeding 33 mkR/hour is considered dangerous.By calculated Monte Carlo method much more dangerous sites and sites frequently imposed to disposals and utilization were chosen from analyzed samples of polluted soil.

  5. Autocorrelations in hybrid Monte Carlo simulations

    International Nuclear Information System (INIS)

    Schaefer, Stefan; Virotta, Francesco

    2010-11-01

    Simulations of QCD suffer from severe critical slowing down towards the continuum limit. This problem is known to be prominent in the topological charge, however, all observables are affected to various degree by these slow modes in the Monte Carlo evolution. We investigate the slowing down in high statistics simulations and propose a new error analysis method, which gives a realistic estimate of the contribution of the slow modes to the errors. (orig.)

  6. Theoretical simulation and analysis of large size BMP-LSC by 3D Monte Carlo ray tracing model

    International Nuclear Information System (INIS)

    Zhang Feng; Zhang Ning-Ning; Yan Sen; Song Sun; Jun Bao; Chen Gao; Zhang Yi

    2017-01-01

    Luminescent solar concentrators (LSC) can reduce the area of solar cells by collecting light from a large area and concentrating the captured light onto relatively small area photovoltaic (PV) cells, and thereby reducing the cost of PV electricity generation. LSCs with bottom-facing cells (BMP-LSC) can collect both direct light and indirect light, so further improving the efficiency of the PV cells. However, it is hard to analyze the effect of each parameter by experiment because there are too many parameters involved in the BMP-LSC. In this paper, all the physical processes of the light transmission and collection in the BMP-LSC were analyzed. A three-dimensional Monte Carlo ray tracing program was developed to study the transmission of photons in the LSC. A larger-size LSC was simulated, and the effects of dye concentration, the LSC thickness, the cell area, and the cell distance were systematically analyzed. (paper)

  7. Analysis of the uranium price predicted to 24 months, implementing neural networks and the Monte Carlo method like predictive tools

    International Nuclear Information System (INIS)

    Esquivel E, J.; Ramirez S, J. R.; Palacios H, J. C.

    2011-11-01

    The present work shows predicted prices of the uranium, using a neural network. The importance of predicting financial indexes of an energy resource, in this case, allows establishing budgetary measures, as well as the costs of the resource to medium period. The uranium is part of the main energy generating fuels and as such, its price rebounds in the financial analyses, due to this is appealed to predictive methods to obtain an outline referent to the financial behaviour that will have in a certain time. In this study, two methodologies are used for the prediction of the uranium price: the Monte Carlo method and the neural networks. These methods allow predicting the indexes of monthly costs, for a two years period, starting from the second bimonthly of 2011. For the prediction the uranium costs are used, registered from the year 2005. (Author)

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

    Science.gov (United States)

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

    2018-06-01

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

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

    Directory of Open Access Journals (Sweden)

    Hu Xiaojing

    2018-01-01

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

  10. An analysis of exposure dose on hands of radiation workers using a Monte Carlo simulation in nuclear medicine

    Energy Technology Data Exchange (ETDEWEB)

    Jang, Dong Gun [Dept. of Nuclear Medicine, Dongnam Institute of Radiological and Medical Sciences Cancer Center, Pusan (Korea, Republic of); Kang, SeSik; Kim, Jung Hoon; KIm, Chang Soo [Dept. of Radiological Science, College of Health Sciences, Catholic University, Pusan (Korea, Republic of)

    2015-12-15

    Workers in nuclear medicine have performed various tasks such as production, distribution, preparation and injection of radioisotope. This process could cause high radiation exposure to workers’ hand. The purpose of this study was to investigate shielding effect for r-rays of 140 and 511 keV by using Monte-Carlo simulation. As a result, it was effective, regardless of lead thickness for radiation shielding in 140 keV r-ray. However, it was effective in shielding material with thickness of more than only 1.1 mm in 511 keV r-ray. And also it doesn’t effective in less than 1.1 mm due to secondary scatter ray and exposure dose was rather increased. Consequently, energy of radionuclide and thickness of shielding materials should be considered to reduce radiation exposure.

  11. An Analysis on the Calculation Efficiency of the Responses Caused by the Biased Adjoint Fluxes in Hybrid Monte Carlo Simulation

    International Nuclear Information System (INIS)

    Khuat, Quang Huy; Kim, Song Hyun; Kim, Do Hyun; Shin, Chang Ho

    2015-01-01

    This technique is known as Consistent Adjoint Driven Importance Sampling (CADIS) method and it is implemented in SCALE code system. In the CADIS method, adjoint transport equation has to be solved to determine deterministic importance functions. Using the CADIS method, a problem was noted that the biased adjoint flux estimated by deterministic methods can affect the calculation efficiency and error. The biases of adjoint function are caused by the methodology, calculation strategy, tolerance of result calculated by the deterministic method and inaccurate multi-group cross section libraries. In this paper, a study to analyze the influence of the biased adjoint functions into Monte Carlo computational efficiency is pursued. In this study, a method to estimate the calculation efficiency was proposed for applying the biased adjoint fluxes in the CADIS approach. For a benchmark problem, the responses and FOMs using SCALE code system were evaluated as applying the adjoint fluxes. The results show that the biased adjoint fluxes significantly affects the calculation efficiencies

  12. Development and Application of MCNP5 and KENO-VI Monte Carlo Models for the Atucha-2 PHWR Analysis

    Directory of Open Access Journals (Sweden)

    M. Pecchia

    2011-01-01

    Full Text Available The geometrical complexity and the peculiarities of Atucha-2 PHWR require the adoption of advanced Monte Carlo codes for performing realistic neutronic simulations. Core models of Atucha-2 PHWR were developed using both MCNP5 and KENO-VI codes. The developed models were applied for calculating reactor criticality states at beginning of life, reactor cell constants, and control rods volumes. The last two applications were relevant for performing successive three dimensional neutron kinetic analyses since it was necessary to correctly evaluate the effect of each oblique control rod in each cell discretizing the reactor. These corrective factors were then applied to the cell cross sections calculated by the two-dimensional deterministic lattice physics code HELIOS. These results were implemented in the RELAP-3D model to perform safety analyses for the licensing process.

  13. Development of phased mission analysis program with Monte Carlo method. Improvement of the variance reduction technique with biasing towards top event

    International Nuclear Information System (INIS)

    Yang Jinan; Mihara, Takatsugu

    1998-12-01

    This report presents a variance reduction technique to estimate the reliability and availability of highly complex systems during phased mission time using the Monte Carlo simulation. In this study, we introduced the variance reduction technique with a concept of distance between the present system state and the cut set configurations. Using this technique, it becomes possible to bias the transition from the operating states to the failed states of components towards the closest cut set. Therefore a component failure can drive the system towards a cut set configuration more effectively. JNC developed the PHAMMON (Phased Mission Analysis Program with Monte Carlo Method) code which involved the two kinds of variance reduction techniques: (1) forced transition, and (2) failure biasing. However, these techniques did not guarantee an effective reduction in variance. For further improvement, a variance reduction technique incorporating the distance concept was introduced to the PHAMMON code and the numerical calculation was carried out for the different design cases of decay heat removal system in a large fast breeder reactor. Our results indicate that the technique addition of this incorporating distance concept is an effective means of further reducing the variance. (author)

  14. Converging stereotactic radiotherapy using kilovoltage X-rays: experimental irradiation of normal rabbit lung and dose-volume analysis with Monte Carlo simulation.

    Science.gov (United States)

    Kawase, Takatsugu; Kunieda, Etsuo; Deloar, Hossain M; Tsunoo, Takanori; Seki, Satoshi; Oku, Yohei; Saitoh, Hidetoshi; Saito, Kimiaki; Ogawa, Eileen N; Ishizaka, Akitoshi; Kameyama, Kaori; Kubo, Atsushi

    2009-10-01

    To validate the feasibility of developing a radiotherapy unit with kilovoltage X-rays through actual irradiation of live rabbit lungs, and to explore the practical issues anticipated in future clinical application to humans through Monte Carlo dose simulation. A converging stereotactic irradiation unit was developed, consisting of a modified diagnostic computed tomography (CT) scanner. A tiny cylindrical volume in 13 normal rabbit lungs was individually irradiated with single fractional absorbed doses of 15, 30, 45, and 60 Gy. Observational CT scanning of the whole lung was performed every 2 weeks for 30 weeks after irradiation. After 30 weeks, histopathologic specimens of the lungs were examined. Dose distribution was simulated using the Monte Carlo method, and dose-volume histograms were calculated according to the data. A trial estimation of the effect of respiratory movement on dose distribution was made. A localized hypodense change and subsequent reticular opacity around the planning target volume (PTV) were observed in CT images of rabbit lungs. Dose-volume histograms of the PTVs and organs at risk showed a focused dose distribution to the target and sufficient dose lowering in the organs at risk. Our estimate of the dose distribution, taking respiratory movement into account, revealed dose reduction in the PTV. A converging stereotactic irradiation unit using kilovoltage X-rays was able to generate a focused radiobiologic reaction in rabbit lungs. Dose-volume histogram analysis and estimated sagittal dose distribution, considering respiratory movement, clarified the characteristics of the irradiation received from this type of unit.

  15. Is Monte Carlo embarrassingly parallel?

    Energy Technology Data Exchange (ETDEWEB)

    Hoogenboom, J. E. [Delft Univ. of Technology, Mekelweg 15, 2629 JB Delft (Netherlands); Delft Nuclear Consultancy, IJsselzoom 2, 2902 LB Capelle aan den IJssel (Netherlands)

    2012-07-01

    Monte Carlo is often stated as being embarrassingly parallel. However, running a Monte Carlo calculation, especially a reactor criticality calculation, in parallel using tens of processors shows a serious limitation in speedup and the execution time may even increase beyond a certain number of processors. In this paper the main causes of the loss of efficiency when using many processors are analyzed using a simple Monte Carlo program for criticality. The basic mechanism for parallel execution is MPI. One of the bottlenecks turn out to be the rendez-vous points in the parallel calculation used for synchronization and exchange of data between processors. This happens at least at the end of each cycle for fission source generation in order to collect the full fission source distribution for the next cycle and to estimate the effective multiplication factor, which is not only part of the requested results, but also input to the next cycle for population control. Basic improvements to overcome this limitation are suggested and tested. Also other time losses in the parallel calculation are identified. Moreover, the threading mechanism, which allows the parallel execution of tasks based on shared memory using OpenMP, is analyzed in detail. Recommendations are given to get the maximum efficiency out of a parallel Monte Carlo calculation. (authors)

  16. Is Monte Carlo embarrassingly parallel?

    International Nuclear Information System (INIS)

    Hoogenboom, J. E.

    2012-01-01

    Monte Carlo is often stated as being embarrassingly parallel. However, running a Monte Carlo calculation, especially a reactor criticality calculation, in parallel using tens of processors shows a serious limitation in speedup and the execution time may even increase beyond a certain number of processors. In this paper the main causes of the loss of efficiency when using many processors are analyzed using a simple Monte Carlo program for criticality. The basic mechanism for parallel execution is MPI. One of the bottlenecks turn out to be the rendez-vous points in the parallel calculation used for synchronization and exchange of data between processors. This happens at least at the end of each cycle for fission source generation in order to collect the full fission source distribution for the next cycle and to estimate the effective multiplication factor, which is not only part of the requested results, but also input to the next cycle for population control. Basic improvements to overcome this limitation are suggested and tested. Also other time losses in the parallel calculation are identified. Moreover, the threading mechanism, which allows the parallel execution of tasks based on shared memory using OpenMP, is analyzed in detail. Recommendations are given to get the maximum efficiency out of a parallel Monte Carlo calculation. (authors)

  17. Exact Monte Carlo for molecules

    International Nuclear Information System (INIS)

    Lester, W.A. Jr.; Reynolds, P.J.

    1985-03-01

    A brief summary of the fixed-node quantum Monte Carlo method is presented. Results obtained for binding energies, the classical barrier height for H + H 2 , and the singlet-triplet splitting in methylene are presented and discussed. 17 refs

  18. Theoretical analysis of nuclear reactors (Phase III), I-V, Part V, Establishment of Monte Carlo method for solving the integral transport equation

    International Nuclear Information System (INIS)

    Pop-Jordanov, J.

    1963-02-01

    General mathematical Monte Carlo approach is described with the elements which enable solution of specific problems (verification was done by estimation of a simple integral). Special attention was devoted to systematic presentation which demanded explanation of fundamental topics of statistics and probability. This demands a procedure for modelling the stochastic process i.e. Monte Carlo method [sr

  19. Combinatorial geometry domain decomposition strategies for Monte Carlo simulations

    Energy Technology Data Exchange (ETDEWEB)

    Li, G.; Zhang, B.; Deng, L.; Mo, Z.; Liu, Z.; Shangguan, D.; Ma, Y.; Li, S.; Hu, Z. [Institute of Applied Physics and Computational Mathematics, Beijing, 100094 (China)

    2013-07-01

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

  20. Combinatorial geometry domain decomposition strategies for Monte Carlo simulations

    International Nuclear Information System (INIS)

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

    2013-01-01

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

  1. Modeling the Health Effects of Expanding e-Cigarette Sales in the United States and United Kingdom: A Monte Carlo Analysis.

    Science.gov (United States)

    Kalkhoran, Sara; Glantz, Stanton A

    2015-10-01

    The prevalence of electronic cigarette (e-cigarette) use is increasing. Population health effects will depend on cigarette smoking behaviors, levels of dual use with conventional cigarettes, and e-cigarette toxicity. To evaluate potential health effects of various scenarios of increasing promotion and use of e-cigarettes. A base case model was developed using data on actual cigarette and e-cigarette use patterns that quantifies transitions from an initial state of no cigarette or e-cigarette use to 1 of 5 final states: never use of cigarettes or e-cigarettes, cigarette use, e-cigarette use, dual use of cigarettes and e-cigarettes, or quit. Seven scenarios were created that cover a range of use patterns, depending on how the e-cigarette market might develop, as well as a range of possible long-term health effects of e-cigarette use. Scenarios for changes from the base case were evaluated using Monte Carlo simulations. Separate sets of base case model parameters were evaluated for the US and UK populations. We assigned unitless health "costs" for each final state on a scale of 0 to 100. Population health "costs" were compared with the base case (status quo) assuming e-cigarette use health "costs" from 1% to 50% as dangerous as conventional cigarette use health costs. Compared with the base case, a harm reduction scenario in which e-cigarette use increases only among smokers who are interested in quitting with more quit attempts and no increased initiation of e-cigarette use among nonsmokers, and another scenario in which e-cigarettes are taken up only by youth who would have smoked conventional cigarettes, had population-level health benefits regardless of e-cigarette health costs in both the United States and United Kingdom. Conversely, scenarios in which e-cigarette promotion leads to renormalization of cigarette smoking or e-cigarettes are used primarily by youth who never would have smoked showed net health harms across all e-cigarette health costs. In other

  2. (U) Introduction to Monte Carlo Methods

    Energy Technology Data Exchange (ETDEWEB)

    Hungerford, Aimee L. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    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.

  3. Energy dispersive X-ray fluorescence spectroscopy/Monte Carlo simulation approach for the non-destructive analysis of corrosion patina-bearing alloys in archaeological bronzes: The case of the bowl from the Fareleira 3 site (Vidigueira, South Portugal)

    Energy Technology Data Exchange (ETDEWEB)

    Bottaini, C. [Hercules Laboratory, University of Évora, Palacio do Vimioso, Largo Marquês de Marialva 8, 7000-809 Évora (Portugal); Mirão, J. [Hercules Laboratory, University of Évora, Palacio do Vimioso, Largo Marquês de Marialva 8, 7000-809 Évora (Portugal); Évora Geophysics Centre, Rua Romão Ramalho 59, 7000 Évora (Portugal); Figuereido, M. [Archaeologist — Monte da Capelinha, Apartado 54, 7005, São Miguel de Machede, Évora (Portugal); Candeias, A. [Hercules Laboratory, University of Évora, Palacio do Vimioso, Largo Marquês de Marialva 8, 7000-809 Évora (Portugal); Évora Chemistry Centre, Rua Romão Ramalho 59, 7000 Évora (Portugal); Brunetti, A. [Department of Political Science and Communication, University of Sassari, Via Piandanna 2, 07100 Sassari (Italy); Schiavon, N., E-mail: schiavon@uevora.pt [Hercules Laboratory, University of Évora, Palacio do Vimioso, Largo Marquês de Marialva 8, 7000-809 Évora (Portugal); Évora Geophysics Centre, Rua Romão Ramalho 59, 7000 Évora (Portugal)

    2015-01-01

    Energy dispersive X-ray fluorescence (EDXRF) is a well-known technique for non-destructive and in situ analysis of archaeological artifacts both in terms of the qualitative and quantitative elemental composition because of its rapidity and non-destructiveness. In this study EDXRF and realistic Monte Carlo simulation using the X-ray Monte Carlo (XRMC) code package have been combined to characterize a Cu-based bowl from the Iron Age burial from Fareleira 3 (Southern Portugal). The artifact displays a multilayered structure made up of three distinct layers: a) alloy substrate; b) green oxidized corrosion patina; and c) brownish carbonate soil-derived crust. To assess the reliability of Monte Carlo simulation in reproducing the composition of the bulk metal of the objects without recurring to potentially damaging patina's and crust's removal, portable EDXRF analysis was performed on cleaned and patina/crust coated areas of the artifact. Patina has been characterized by micro X-ray Diffractometry (μXRD) and Back-Scattered Scanning Electron Microscopy + Energy Dispersive Spectroscopy (BSEM + EDS). Results indicate that the EDXRF/Monte Carlo protocol is well suited when a two-layered model is considered, whereas in areas where the patina + crust surface coating is too thick, X-rays from the alloy substrate are not able to exit the sample. - Highlights: • EDXRF/Monte Carlo simulation is used to characterize an archeological alloy. • EDXRF analysis was performed on cleaned and patina coated areas of the artifact. • EDXRF/Montes Carlo protocol is well suited when a two-layered model is considered. • When the patina is too thick, X-rays from substrate are unable to exit the sample.

  4. Dynamic Monte Carlo transient analysis for the Organization for Economic Co-operation and Development Nuclear Energy Agency (OECD/NEA) C5G7-TD benchmark

    Energy Technology Data Exchange (ETDEWEB)

    Shaukat, Nadeem; Ryu, Min; Shim, Hyung Jin [Seoul National University, Seoul (Korea, Republic of)

    2017-08-15

    With ever-advancing computer technology, the Monte Carlo (MC) neutron transport calculation is expanding its application area to nuclear reactor transient analysis. Dynamic MC (DMC) neutron tracking for transient analysis requires efficient algorithms for delayed neutron generation, neutron population control, and initial condition modeling. In this paper, a new MC steady-state simulation method based on time-dependent MC neutron tracking is proposed for steady-state initial condition modeling; during this process, prompt neutron sources and delayed neutron precursors for the DMC transient simulation can easily be sampled. The DMC method, including the proposed time-dependent DMC steady-state simulation method, has been implemented in McCARD and applied for two-dimensional core kinetics problems in the time-dependent neutron transport benchmark C5G7-TD. The McCARD DMC calculation results show good agreement with results of a deterministic transport analysis code, nTRACER.

  5. A dual resolution measurement based Monte Carlo simulation technique for detailed dose analysis of small volume organs in the skull base region

    International Nuclear Information System (INIS)

    Yeh, Chi-Yuan; Tung, Chuan-Jung; Chao, Tsi-Chain; Lin, Mu-Han; Lee, Chung-Chi

    2014-01-01

    The purpose of this study was to examine dose distribution of a skull base tumor and surrounding critical structures in response to high dose intensity-modulated radiosurgery (IMRS) with Monte Carlo (MC) simulation using a dual resolution sandwich phantom. The measurement-based Monte Carlo (MBMC) method (Lin et al., 2009) was adopted for the study. The major components of the MBMC technique involve (1) the BEAMnrc code for beam transport through the treatment head of a Varian 21EX linear accelerator, (2) the DOSXYZnrc code for patient dose simulation and (3) an EPID-measured efficiency map which describes non-uniform fluence distribution of the IMRS treatment beam. For the simulated case, five isocentric 6 MV photon beams were designed to deliver a total dose of 1200 cGy in two fractions to the skull base tumor. A sandwich phantom for the MBMC simulation was created based on the patient's CT scan of a skull base tumor [gross tumor volume (GTV)=8.4 cm 3 ] near the right 8th cranial nerve. The phantom, consisted of a 1.2-cm thick skull base region, had a voxel resolution of 0.05×0.05×0.1 cm 3 and was sandwiched in between 0.05×0.05×0.3 cm 3 slices of a head phantom. A coarser 0.2×0.2×0.3 cm 3 single resolution (SR) phantom was also created for comparison with the sandwich phantom. A particle history of 3×10 8 for each beam was used for simulations of both the SR and the sandwich phantoms to achieve a statistical uncertainty of <2%. Our study showed that the planning target volume (PTV) receiving at least 95% of the prescribed dose (VPTV95) was 96.9%, 96.7% and 99.9% for the TPS, SR, and sandwich phantom, respectively. The maximum and mean doses to large organs such as the PTV, brain stem, and parotid gland for the TPS, SR and sandwich MC simulations did not show any significant difference; however, significant dose differences were observed for very small structures like the right 8th cranial nerve, right cochlea, right malleus and right semicircular

  6. Monte Carlo design of a system for the detection of explosive materials and analysis of the dose

    International Nuclear Information System (INIS)

    Hernandez A, P. L.; Medina C, D.; Rodriguez I, J. L.; Salas L, M. A.; Vega C, H. R.

    2015-10-01

    The problems associated with insecurity and terrorism have forced to designing systems for detecting nuclear materials, drugs and explosives that are installed on roads, ports and airports. Organic materials are composed of C, H, O and N; similarly the explosive materials are manufactured which can be distinguished by the concentration of these elements. Its elemental composition, particularly the concentration of hydrogen and oxygen, allow distinguish them from other organic substances. When these materials are irradiated with neutrons nuclear reactions (n, γ) are produced, where the emitted photons are ready gamma rays whose energy is characteristic of each element and its abundance allows estimating their concentration. The aim of this study was designed using Monte Carlo methods a system with neutron source, gamma rays detector and moderator able to distinguish the presence of Rdx and urea. In design were used as moderators: paraffin, light water, polyethylene and graphite; as detectors were used HPGe and the NaI(Tl). The design that showed the best performance was the moderator of light water and HPGe, with a source of 241 AmBe. For this design, the values of ambient dose equivalent around the system were calculated. (Author)

  7. Theoretical simulation and analysis of large size BMP-LSC by 3D Monte Carlo ray tracing model

    Institute of Scientific and Technical Information of China (English)

    Feng Zhang; Ning-Ning Zhang; Yi Zhang; Sen Yan; Song Sun; Jun Bao; Chen Gao

    2017-01-01

    Luminescent solar concentrators (LSC) can reduce the area of solar cells by collecting light from a large area and concentrating the captured light onto relatively small area photovoltaic (PV) cells,and thereby reducing the cost of PV electricity generation.LSCs with bottom-facing cells (BMP-LSC) can collect both direct light and indirect light,so further improving the efficiency of the PV cells.However,it is hard to analyze the effect of each parameter by experiment because there are too many parameters involved in the BMP-LSC.In this paper,all the physical processes of the light transmission and collection in the BMP-LSC were analyzed.A three-dimensional Monte Carlo ray tracing program was developed to study the transmission of photons in the LSC.A larger-size LSC was simulated,and the effects of dye concentration,the LSC thickness,the cell area,and the cell distance were systematically analyzed.

  8. DS86 neutron dose. Monte Carlo analysis for depth profile of {sup 152}Eu activity in a large stone sample

    Energy Technology Data Exchange (ETDEWEB)

    Endo, Satoru; Hoshi, Masaharu; Takada, Jun [Hiroshima Univ. (Japan). Research Inst. for Radiation Biology and Medicine; Iwatani, Kazuo; Oka, Takamitsu; Shizuma, Kiyoshi; Imanaka, Tetsuji; Fujita, Shoichiro; Hasai, Hiromi

    1999-06-01

    The depth profile of {sup 152}Eu activity induced in a large granite stone pillar by Hiroshima atomic bomb neutrons was calculated by a Monte Carlo N-Particle Transport Code (MCNP). The pillar was on the Motoyasu Bridge, located at a distance of 132 m (WSW) from the hypocenter. It was a square column with a horizontal sectional size of 82.5 cm x 82.5 cm and height of 179 cm. Twenty-one cells from the north to south surface at the central height of the column were specified for the calculation and {sup 152}Eu activities for each cell were calculated. The incident neutron spectrum was assumed to be the angular fluence data of the Dosimetry System 1986 (DS86). The angular dependence of the spectrum was taken into account by dividing the whole solid angle into twenty-six directions. The calculated depth profile of specific activity did not agree with the measured profile. A discrepancy was found in the absolute values at each depth with a mean multiplication factor of 0.58 and also in the shape of the relative profile. The results indicated that a reassessment of the neutron energy spectrum in DS86 is required for correct dose estimation. (author)

  9. Monte Carlo analysis of the effects of a blanket-shield penetration on the performance of a tokamak fusion reactor

    International Nuclear Information System (INIS)

    Santoro, R.T.; Tang, J.S.; Alsmiller, R.G. Jr.; Barnes, J.M.

    1977-05-01

    Adjoint Monte Carlo calculations have been carried out using the three-dimensional radiation transport code, MORSE, to estimate the nuclear heating and radiation damage in the toroidal field (TF) coils adjacent to a 28 x 68 cm 2 rectangular neutral beam injector duct that passes through the blanket and shield of a D-T burning Tokamak reactor. The plasma region, blanket, shield, and TF coils were represented in cylindrical geometry using the same dimensions and compositions as those of the Experimental Power Reactor. The radiation transport was accomplished using coupled 35-group neutron, 21-group gamma-ray cross sections obtained by collapsing the DLC-37 cross-section library. Nuclear heating and radiation damage rates were estimated using the latest available nuclear response functions. The presence of the neutral beam injector duct leads to increases in the nuclear heating rates in the TF coils ranging from a factor of 3 to a factor of 196 depending on the location. Increases in the radiation damage also result in the TF coils. The atomic displacement rates increase from factors of 2 to 138 and the hydrogen and helium gas production rates increase from factors of 11 to 7600 and from 15 to 9700, respectively

  10. Reliability analysis under epistemic uncertainty

    International Nuclear Information System (INIS)

    Nannapaneni, Saideep; Mahadevan, Sankaran

    2016-01-01

    This paper proposes a probabilistic framework to include both aleatory and epistemic uncertainty within model-based reliability estimation of engineering systems for individual limit states. Epistemic uncertainty is considered due to both data and model sources. Sparse point and/or interval data regarding the input random variables leads to uncertainty regarding their distribution types, distribution parameters, and correlations; this statistical uncertainty is included in the reliability analysis through a combination of likelihood-based representation, Bayesian hypothesis testing, and Bayesian model averaging techniques. Model errors, which include numerical solution errors and model form errors, are quantified through Gaussian process models and included in the reliability analysis. The probability integral transform is used to develop an auxiliary variable approach that facilitates a single-level representation of both aleatory and epistemic uncertainty. This strategy results in an efficient single-loop implementation of Monte Carlo simulation (MCS) and FORM/SORM techniques for reliability estimation under both aleatory and epistemic uncertainty. Two engineering examples are used to demonstrate the proposed methodology. - Highlights: • Epistemic uncertainty due to data and model included in reliability analysis. • A novel FORM-based approach proposed to include aleatory and epistemic uncertainty. • A single-loop Monte Carlo approach proposed to include both types of uncertainties. • Two engineering examples used for illustration.

  11. Alternative implementations of the Monte Carlo power method

    International Nuclear Information System (INIS)

    Blomquist, R.N.; Gelbard, E.M.

    2002-01-01

    We compare nominal efficiencies, i.e. variances in power shapes for equal running time, of different versions of the Monte Carlo eigenvalue computation, as applied to criticality safety analysis calculations. The two main methods considered here are ''conventional'' Monte Carlo and the superhistory method, and both are used in criticality safety codes. Within each of these major methods, different variants are available for the main steps of the basic Monte Carlo algorithm. Thus, for example, different treatments of the fission process may vary in the extent to which they follow, in analog fashion, the details of real-world fission, or may vary in details of the methods by which they choose next-generation source sites. In general the same options are available in both the superhistory method and conventional Monte Carlo, but there seems not to have been much examination of the special properties of the two major methods and their minor variants. We find, first, that the superhistory method is just as efficient as conventional Monte Carlo and, secondly, that use of different variants of the basic algorithms may, in special cases, have a surprisingly large effect on Monte Carlo computational efficiency

  12. Isotopic depletion with Monte Carlo

    International Nuclear Information System (INIS)

    Martin, W.R.; Rathkopf, J.A.

    1996-06-01

    This work considers a method to deplete isotopes during a time- dependent Monte Carlo simulation of an evolving system. The method is based on explicitly combining a conventional estimator for the scalar flux with the analytical solutions to the isotopic depletion equations. There are no auxiliary calculations; the method is an integral part of the Monte Carlo calculation. The method eliminates negative densities and reduces the variance in the estimates for the isotope densities, compared to existing methods. Moreover, existing methods are shown to be special cases of the general method described in this work, as they can be derived by combining a high variance estimator for the scalar flux with a low-order approximation to the analytical solution to the depletion equation

  13. Monte Carlo Methods in ICF

    Science.gov (United States)

    Zimmerman, George B.

    Monte Carlo methods appropriate to simulate the transport of x-rays, neutrons, ions and electrons in Inertial Confinement Fusion targets are described and analyzed. The Implicit Monte Carlo method of x-ray transport handles symmetry within indirect drive ICF hohlraums well, but can be improved 50X in efficiency by angular biasing the x-rays towards the fuel capsule. Accurate simulation of thermonuclear burn and burn diagnostics involves detailed particle source spectra, charged particle ranges, inflight reaction kinematics, corrections for bulk and thermal Doppler effects and variance reduction to obtain adequate statistics for rare events. It is found that the effects of angular Coulomb scattering must be included in models of charged particle transport through heterogeneous materials.

  14. Monte Carlo methods in ICF

    International Nuclear Information System (INIS)

    Zimmerman, G.B.

    1997-01-01

    Monte Carlo methods appropriate to simulate the transport of x-rays, neutrons, ions and electrons in Inertial Confinement Fusion targets are described and analyzed. The Implicit Monte Carlo method of x-ray transport handles symmetry within indirect drive ICF hohlraums well, but can be improved 50X in efficiency by angular biasing the x-rays towards the fuel capsule. Accurate simulation of thermonuclear burn and burn diagnostics involves detailed particle source spectra, charged particle ranges, inflight reaction kinematics, corrections for bulk and thermal Doppler effects and variance reduction to obtain adequate statistics for rare events. It is found that the effects of angular Coulomb scattering must be included in models of charged particle transport through heterogeneous materials. copyright 1997 American Institute of Physics

  15. Monte Carlo methods in ICF

    International Nuclear Information System (INIS)

    Zimmerman, George B.

    1997-01-01

    Monte Carlo methods appropriate to simulate the transport of x-rays, neutrons, ions and electrons in Inertial Confinement Fusion targets are described and analyzed. The Implicit Monte Carlo method of x-ray transport handles symmetry within indirect drive ICF hohlraums well, but can be improved 50X in efficiency by angular biasing the x-rays towards the fuel capsule. Accurate simulation of thermonuclear burn and burn diagnostics involves detailed particle source spectra, charged particle ranges, inflight reaction kinematics, corrections for bulk and thermal Doppler effects and variance reduction to obtain adequate statistics for rare events. It is found that the effects of angular Coulomb scattering must be included in models of charged particle transport through heterogeneous materials

  16. Shell model Monte Carlo methods

    International Nuclear Information System (INIS)

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

    1997-01-01

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

  17. A contribution Monte Carlo method

    International Nuclear Information System (INIS)

    Aboughantous, C.H.

    1994-01-01

    A Contribution Monte Carlo method is developed and successfully applied to a sample deep-penetration shielding problem. The random walk is simulated in most of its parts as in conventional Monte Carlo methods. The probability density functions (pdf's) are expressed in terms of spherical harmonics and are continuous functions in direction cosine and azimuthal angle variables as well as in position coordinates; the energy is discretized in the multigroup approximation. The transport pdf is an unusual exponential kernel strongly dependent on the incident and emergent directions and energies and on the position of the collision site. The method produces the same results obtained with the deterministic method with a very small standard deviation, with as little as 1,000 Contribution particles in both analog and nonabsorption biasing modes and with only a few minutes CPU time

  18. Shell model Monte Carlo methods

    International Nuclear Information System (INIS)

    Koonin, S.E.

    1996-01-01

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

  19. Combined FDTD-Monte Carlo analysis and a novel design for ZnO scintillator rods in polycarbonate membrane for X-ray imaging

    Energy Technology Data Exchange (ETDEWEB)

    Mohammadian-Behbahani, Mohammad-Reza [Department of Energy Engineering and Physics, Amir-Kabir University of Technology (Tehran Polytechnic), Tehran (Iran, Islamic Republic of); School of Particles and Accelerators, Institute for Research in Fundamental Sciences (IPM), Tehran (Iran, Islamic Republic of); Saramad, Shahyar, E-mail: ssaramad@aut.ac.ir [Department of Energy Engineering and Physics, Amir-Kabir University of Technology (Tehran Polytechnic), Tehran (Iran, Islamic Republic of); School of Particles and Accelerators, Institute for Research in Fundamental Sciences (IPM), Tehran (Iran, Islamic Republic of); Mohammadi, Mohammad [Department of Electrical Engineering, Amir-Kabir University of Technology (Tehran Polytechnic), Tehran (Iran, Islamic Republic of); School of Particles and Accelerators, Institute for Research in Fundamental Sciences (IPM), Tehran (Iran, Islamic Republic of)

    2017-05-01

    A combination of Finite Difference Time Domain (FDTD) and Monte Carlo (MC) methods is proposed for simulation and analysis of ZnO microscintillators grown in polycarbonate membrane. A planar 10 keV X-ray source irradiating the detector is simulated by MC method, which provides the amount of absorbed X-ray energy in the assembly. The transport of generated UV scintillation light and its propagation in the detector was studied by the FDTD method. Detector responses to different probable scintillation sites and under different energies of X-ray source from 10 to 25 keV are reported. Finally, the tapered geometry for the scintillators is proposed, which shows enhanced spatial resolution in comparison to cylindrical geometry for imaging applications.

  20. Combined FDTD-Monte Carlo analysis and a novel design for ZnO scintillator rods in polycarbonate membrane for X-ray imaging

    International Nuclear Information System (INIS)

    Mohammadian-Behbahani, Mohammad-Reza; Saramad, Shahyar; Mohammadi, Mohammad

    2017-01-01

    A combination of Finite Difference Time Domain (FDTD) and Monte Carlo (MC) methods is proposed for simulation and analysis of ZnO microscintillators grown in polycarbonate membrane. A planar 10 keV X-ray source irradiating the detector is simulated by MC method, which provides the amount of absorbed X-ray energy in the assembly. The transport of generated UV scintillation light and its propagation in the detector was studied by the FDTD method. Detector responses to different probable scintillation sites and under different energies of X-ray source from 10 to 25 keV are reported. Finally, the tapered geometry for the scintillators is proposed, which shows enhanced spatial resolution in comparison to cylindrical geometry for imaging applications.

  1. Parallel Monte Carlo reactor neutronics

    International Nuclear Information System (INIS)

    Blomquist, R.N.; Brown, F.B.

    1994-01-01

    The issues affecting implementation of parallel algorithms for large-scale engineering Monte Carlo neutron transport simulations are discussed. For nuclear reactor calculations, these include load balancing, recoding effort, reproducibility, domain decomposition techniques, I/O minimization, and strategies for different parallel architectures. Two codes were parallelized and tested for performance. The architectures employed include SIMD, MIMD-distributed memory, and workstation network with uneven interactive load. Speedups linear with the number of nodes were achieved

  2. Elements of Monte Carlo techniques

    International Nuclear Information System (INIS)

    Nagarajan, P.S.

    2000-01-01

    The Monte Carlo method is essentially mimicking the real world physical processes at the microscopic level. With the incredible increase in computing speeds and ever decreasing computing costs, there is widespread use of the method for practical problems. The method is used in calculating algorithm-generated sequences known as pseudo random sequence (prs)., probability density function (pdf), test for randomness, extension to multidimensional integration etc

  3. Adaptive Multilevel Monte Carlo Simulation

    KAUST Repository

    Hoel, H

    2011-08-23

    This work generalizes a multilevel forward Euler Monte Carlo method introduced in Michael B. Giles. (Michael Giles. Oper. Res. 56(3):607–617, 2008.) for the approximation of expected values depending on the solution to an Itô stochastic differential equation. The work (Michael Giles. Oper. Res. 56(3):607– 617, 2008.) proposed and analyzed a forward Euler multilevelMonte Carlo method based on a hierarchy of uniform time discretizations and control variates to reduce the computational effort required by a standard, single level, Forward Euler Monte Carlo method. This work introduces an adaptive hierarchy of non uniform time discretizations, generated by an adaptive algorithmintroduced in (AnnaDzougoutov et al. Raùl Tempone. Adaptive Monte Carlo algorithms for stopped diffusion. In Multiscale methods in science and engineering, volume 44 of Lect. Notes Comput. Sci. Eng., pages 59–88. Springer, Berlin, 2005; Kyoung-Sook Moon et al. Stoch. Anal. Appl. 23(3):511–558, 2005; Kyoung-Sook Moon et al. An adaptive algorithm for ordinary, stochastic and partial differential equations. In Recent advances in adaptive computation, volume 383 of Contemp. Math., pages 325–343. Amer. Math. Soc., Providence, RI, 2005.). This form of the adaptive algorithm generates stochastic, path dependent, time steps and is based on a posteriori error expansions first developed in (Anders Szepessy et al. Comm. Pure Appl. Math. 54(10):1169– 1214, 2001). Our numerical results for a stopped diffusion problem, exhibit savings in the computational cost to achieve an accuracy of ϑ(TOL),from(TOL−3), from using a single level version of the adaptive algorithm to ϑ(((TOL−1)log(TOL))2).

  4. Geometrical splitting in Monte Carlo

    International Nuclear Information System (INIS)

    Dubi, A.; Elperin, T.; Dudziak, D.J.

    1982-01-01

    A statistical model is presented by which a direct statistical approach yielded an analytic expression for the second moment, the variance ratio, and the benefit function in a model of an n surface-splitting Monte Carlo game. In addition to the insight into the dependence of the second moment on the splitting parameters the main importance of the expressions developed lies in their potential to become a basis for in-code optimization of splitting through a general algorithm. Refs

  5. Extending canonical Monte Carlo methods

    International Nuclear Information System (INIS)

    Velazquez, L; Curilef, S

    2010-01-01

    In this paper, we discuss the implications of a recently obtained equilibrium fluctuation-dissipation relation for the extension of the available Monte Carlo methods on the basis of the consideration of the Gibbs canonical ensemble to account for the existence of an anomalous regime with negative heat capacities C α with α≈0.2 for the particular case of the 2D ten-state Potts model

  6. WE-H-BRA-08: A Monte Carlo Cell Nucleus Model for Assessing Cell Survival Probability Based On Particle Track Structure Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Lee, B [Northwestern Memorial Hospital, Chicago, IL (United States); Georgia Institute of Technology, Atlanta, GA (Georgia); Wang, C [Georgia Institute of Technology, Atlanta, GA (Georgia)

    2016-06-15

    Purpose: To correlate the damage produced by particles of different types and qualities to cell survival on the basis of nanodosimetric analysis and advanced DNA structures in the cell nucleus. Methods: A Monte Carlo code was developed to simulate subnuclear DNA chromatin fibers (CFs) of 30nm utilizing a mean-free-path approach common to radiation transport. The cell nucleus was modeled as a spherical region containing 6000 chromatin-dense domains (CDs) of 400nm diameter, with additional CFs modeled in a sparser interchromatin region. The Geant4-DNA code was utilized to produce a particle track database representing various particles at different energies and dose quantities. These tracks were used to stochastically position the DNA structures based on their mean free path to interaction with CFs. Excitation and ionization events intersecting CFs were analyzed using the DBSCAN clustering algorithm for assessment of the likelihood of producing DSBs. Simulated DSBs were then assessed based on their proximity to one another for a probability of inducing cell death. Results: Variations in energy deposition to chromatin fibers match expectations based on differences in particle track structure. The quality of damage to CFs based on different particle types indicate more severe damage by high-LET radiation than low-LET radiation of identical particles. In addition, the model indicates more severe damage by protons than of alpha particles of same LET, which is consistent with differences in their track structure. Cell survival curves have been produced showing the L-Q behavior of sparsely ionizing radiation. Conclusion: Initial results indicate the feasibility of producing cell survival curves based on the Monte Carlo cell nucleus method. Accurate correlation between simulated DNA damage to cell survival on the basis of nanodosimetric analysis can provide insight into the biological responses to various radiation types. Current efforts are directed at producing cell

  7. Non statistical Monte-Carlo

    International Nuclear Information System (INIS)

    Mercier, B.

    1985-04-01

    We have shown that the transport equation can be solved with particles, like the Monte-Carlo method, but without random numbers. In the Monte-Carlo method, particles are created from the source, and are followed from collision to collision until either they are absorbed or they leave the spatial domain. In our method, particles are created from the original source, with a variable weight taking into account both collision and absorption. These particles are followed until they leave the spatial domain, and we use them to determine a first collision source. Another set of particles is then created from this first collision source, and tracked to determine a second collision source, and so on. This process introduces an approximation which does not exist in the Monte-Carlo method. However, we have analyzed the effect of this approximation, and shown that it can be limited. Our method is deterministic, gives reproducible results. Furthermore, when extra accuracy is needed in some region, it is easier to get more particles to go there. It has the same kind of applications: rather problems where streaming is dominant than collision dominated problems

  8. BREM5 electroweak Monte Carlo

    International Nuclear Information System (INIS)

    Kennedy, D.C. II.

    1987-01-01

    This is an update on the progress of the BREMMUS Monte Carlo simulator, particularly in its current incarnation, BREM5. The present report is intended only as a follow-up to the Mark II/Granlibakken proceedings, and those proceedings should be consulted for a complete description of the capabilities and goals of the BREMMUS program. The new BREM5 program improves on the previous version of BREMMUS, BREM2, in a number of important ways. In BREM2, the internal loop (oblique) corrections were not treated in consistent fashion, a deficiency that led to renormalization scheme-dependence; i.e., physical results, such as cross sections, were dependent on the method used to eliminate infinities from the theory. Of course, this problem cannot be tolerated in a Monte Carlo designed for experimental use. BREM5 incorporates a new way of treating the oblique corrections, as explained in the Granlibakken proceedings, that guarantees renormalization scheme-independence and dramatically simplifies the organization and calculation of radiative corrections. This technique is to be presented in full detail in a forthcoming paper. BREM5 is, at this point, the only Monte Carlo to contain the entire set of one-loop corrections to electroweak four-fermion processes and renormalization scheme-independence. 3 figures

  9. Uncertainty analysis guide

    International Nuclear Information System (INIS)

    Andres, T.H.

    2002-05-01

    This guide applies to the estimation of uncertainty in quantities calculated by scientific, analysis and design computer programs that fall within the scope of AECL's software quality assurance (SQA) manual. The guide weaves together rational approaches from the SQA manual and three other diverse sources: (a) the CSAU (Code Scaling, Applicability, and Uncertainty) evaluation methodology; (b) the ISO Guide,for the Expression of Uncertainty in Measurement; and (c) the SVA (Systems Variability Analysis) method of risk analysis. This report describes the manner by which random and systematic uncertainties in calculated quantities can be estimated and expressed. Random uncertainty in model output can be attributed to uncertainties of inputs. The propagation of these uncertainties through a computer model can be represented in a variety of ways, including exact calculations, series approximations and Monte Carlo methods. Systematic uncertainties emerge from the development of the computer model itself, through simplifications and conservatisms, for example. These must be estimated and combined with random uncertainties to determine the combined uncertainty in a model output. This report also addresses the method by which uncertainties should be employed in code validation, in order to determine whether experiments and simulations agree, and whether or not a code satisfies the required tolerance for its application. (author)

  10. Uncertainty analysis guide

    Energy Technology Data Exchange (ETDEWEB)

    Andres, T.H

    2002-05-01

    This guide applies to the estimation of uncertainty in quantities calculated by scientific, analysis and design computer programs that fall within the scope of AECL's software quality assurance (SQA) manual. The guide weaves together rational approaches from the SQA manual and three other diverse sources: (a) the CSAU (Code Scaling, Applicability, and Uncertainty) evaluation methodology; (b) the ISO Guide,for the Expression of Uncertainty in Measurement; and (c) the SVA (Systems Variability Analysis) method of risk analysis. This report describes the manner by which random and systematic uncertainties in calculated quantities can be estimated and expressed. Random uncertainty in model output can be attributed to uncertainties of inputs. The propagation of these uncertainties through a computer model can be represented in a variety of ways, including exact calculations, series approximations and Monte Carlo methods. Systematic uncertainties emerge from the development of the computer model itself, through simplifications and conservatisms, for example. These must be estimated and combined with random uncertainties to determine the combined uncertainty in a model output. This report also addresses the method by which uncertainties should be employed in code validation, in order to determine whether experiments and simulations agree, and whether or not a code satisfies the required tolerance for its application. (author)

  11. Monte Carlo design of a system for the detection of explosive materials and analysis of the dose; Diseno Monte Carlo de un sistema para la deteccion de materiales explosivos y analisis de la dosis

    Energy Technology Data Exchange (ETDEWEB)

    Hernandez A, P. L.; Medina C, D.; Rodriguez I, J. L.; Salas L, M. A.; Vega C, H. R., E-mail: pabloyae_2@hotmail.com [Universidad Autonoma de Zacatecas, Unidad Academica de Estudios Nucleares, Cipres No. 10, Fracc. La Penuela, 98068 Zacatecas, Zac. (Mexico)

    2015-10-15

    The problems associated with insecurity and terrorism have forced to designing systems for detecting nuclear materials, drugs and explosives that are installed on roads, ports and airports. Organic materials are composed of C, H, O and N; similarly the explosive materials are manufactured which can be distinguished by the concentration of these elements. Its elemental composition, particularly the concentration of hydrogen and oxygen, allow distinguish them from other organic substances. When these materials are irradiated with neutrons nuclear reactions (n, γ) are produced, where the emitted photons are ready gamma rays whose energy is characteristic of each element and its abundance allows estimating their concentration. The aim of this study was designed using Monte Carlo methods a system with neutron source, gamma rays detector and moderator able to distinguish the presence of Rdx and urea. In design were used as moderators: paraffin, light water, polyethylene and graphite; as detectors were used HPGe and the NaI(Tl). The design that showed the best performance was the moderator of light water and HPGe, with a source of {sup 241}AmBe. For this design, the values of ambient dose equivalent around the system were calculated. (Author)

  12. Converging Stereotactic Radiotherapy Using Kilovoltage X-Rays: Experimental Irradiation of Normal Rabbit Lung and Dose-Volume Analysis With Monte Carlo Simulation

    International Nuclear Information System (INIS)

    Kawase, Takatsugu; Kunieda, Etsuo; Deloar, Hossain M.; Tsunoo, Takanori; Seki, Satoshi; Oku, Yohei; Saitoh, Hidetoshi; Saito, Kimiaki; Ogawa, Eileen N.; Ishizaka, Akitoshi; Kameyama, Kaori; Kubo, Atsushi

    2009-01-01

    Purpose: To validate the feasibility of developing a radiotherapy unit with kilovoltage X-rays through actual irradiation of live rabbit lungs, and to explore the practical issues anticipated in future clinical application to humans through Monte Carlo dose simulation. Methods and Materials: A converging stereotactic irradiation unit was developed, consisting of a modified diagnostic computed tomography (CT) scanner. A tiny cylindrical volume in 13 normal rabbit lungs was individually irradiated with single fractional absorbed doses of 15, 30, 45, and 60 Gy. Observational CT scanning of the whole lung was performed every 2 weeks for 30 weeks after irradiation. After 30 weeks, histopathologic specimens of the lungs were examined. Dose distribution was simulated using the Monte Carlo method, and dose-volume histograms were calculated according to the data. A trial estimation of the effect of respiratory movement on dose distribution was made. Results: A localized hypodense change and subsequent reticular opacity around the planning target volume (PTV) were observed in CT images of rabbit lungs. Dose-volume histograms of the PTVs and organs at risk showed a focused dose distribution to the target and sufficient dose lowering in the organs at risk. Our estimate of the dose distribution, taking respiratory movement into account, revealed dose reduction in the PTV. Conclusions: A converging stereotactic irradiation unit using kilovoltage X-rays was able to generate a focused radiobiologic reaction in rabbit lungs. Dose-volume histogram analysis and estimated sagittal dose distribution, considering respiratory movement, clarified the characteristics of the irradiation received from this type of unit.

  13. A method based on Monte Carlo simulations and voxelized anatomical atlases to evaluate and correct uncertainties on radiotracer accumulation quantitation in beta microprobe studies in the rat brain

    Science.gov (United States)

    Pain, F.; Dhenain, M.; Gurden, H.; Routier, A. L.; Lefebvre, F.; Mastrippolito, R.; Lanièce, P.

    2008-10-01

    The β-microprobe is a simple and versatile technique complementary to small animal positron emission tomography (PET). It relies on local measurements of the concentration of positron-labeled molecules. So far, it has been successfully used in anesthetized rats for pharmacokinetics experiments and for the study of brain energetic metabolism. However, the ability of the technique to provide accurate quantitative measurements using 18F, 11C and 15O tracers is likely to suffer from the contribution of 511 keV gamma rays background to the signal and from the contribution of positrons from brain loci surrounding the locus of interest. The aim of the present paper is to provide a method of evaluating several parameters, which are supposed to affect the quantification of recordings performed in vivo with this methodology. We have developed realistic voxelized phantoms of the rat whole body and brain, and used them as input geometries for Monte Carlo simulations of previous β-microprobe reports. In the context of realistic experiments (binding of 11C-Raclopride to D2 dopaminergic receptors in the striatum; local glucose metabolic rate measurement with 18F-FDG and H2O15 blood flow measurements in the somatosensory cortex), we have calculated the detection efficiencies and corresponding contribution of 511 keV gammas from peripheral organs accumulation. We confirmed that the 511 keV gammas background does not impair quantification. To evaluate the contribution of positrons from adjacent structures, we have developed β-Assistant, a program based on a rat brain voxelized atlas and matrices of local detection efficiencies calculated by Monte Carlo simulations for several probe geometries. This program was used to calculate the 'apparent sensitivity' of the probe for each brain structure included in the detection volume. For a given localization of a probe within the brain, this allows us to quantify the different sources of beta signal. Finally, since stereotaxic accuracy is

  14. Analysis of the ITER computational shielding benchmark with the Monte Carlo TRIPOLI-4{sup ®} neutron gamma coupled calculations

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Yi-Kang, E-mail: yi-kang.lee@cea.fr

    2016-11-01

    Highlights: • Verification and validation of TRIPOLI-4 radiation transport calculations for ITER shielding benchmark. • Evaluation of CEA-V5.1.1 and FENDL-3.0 nuclear data libraries on D–T fusion neutron continuous energy transport calculations. • Advances in nuclear analyses for nuclear heating and radiation damage in iron. • This work also demonstrates that the “safety factors” concept is necessary in the nuclear analyses of ITER. - Abstract: With the growing interest in using the continuous-energy TRIPOLI-4{sup ®} Monte Carlo radiation transport code for ITER applications, a key issue that arises is whether or not the released TRIPOLI-4 code and its associated nuclear data libraries are verified and validated for the D–T fusion neutronics calculations. Previous published benchmark results of TRIPOLI-4 code on the ITER related activities have concentrated on the first wall loading, the reactor dosimetry, the nuclear heating, and the tritium breeding ratio. To enhance the TRIPOLI-4 verification and validation on neutron-gamma coupled calculations for fusion device application, the computational ITER shielding benchmark of M. E. Sawan was performed in this work by using the 2013 released TRIPOLI-4.9S code and the associated CEA-V5.1.1 data library. First wall, blanket, vacuum vessel and toroidal field magnet of the inboard and outboard components were fully modelled in this 1-D toroidal cylindrical benchmark. The 14.1 MeV source neutrons were sampled from a uniform isotropic distribution in the plasma zone. Nuclear responses including neutron and gamma fluxes, nuclear heating, and material damage indicator were benchmarked against previous published results. The capabilities of the TRIPOLI-4 code on the evaluation of above physics parameters were presented. The nuclear data library from the new FENDL-3.0 evaluation was also benchmarked against the CEA-V5.1.1 results for the neutron transport calculations. The results show that both data libraries

  15. Analysis of the ITER computational shielding benchmark with the Monte Carlo TRIPOLI-4® neutron gamma coupled calculations

    International Nuclear Information System (INIS)

    Lee, Yi-Kang

    2016-01-01

    Highlights: • Verification and validation of TRIPOLI-4 radiation transport calculations for ITER shielding benchmark. • Evaluation of CEA-V5.1.1 and FENDL-3.0 nuclear data libraries on D–T fusion neutron continuous energy transport calculations. • Advances in nuclear analyses for nuclear heating and radiation damage in iron. • This work also demonstrates that the “safety factors” concept is necessary in the nuclear analyses of ITER. - Abstract: With the growing interest in using the continuous-energy TRIPOLI-4 ® Monte Carlo radiation transport code for ITER applications, a key issue that arises is whether or not the released TRIPOLI-4 code and its associated nuclear data libraries are verified and validated for the D–T fusion neutronics calculations. Previous published benchmark results of TRIPOLI-4 code on the ITER related activities have concentrated on the first wall loading, the reactor dosimetry, the nuclear heating, and the tritium breeding ratio. To enhance the TRIPOLI-4 verification and validation on neutron-gamma coupled calculations for fusion device application, the computational ITER shielding benchmark of M. E. Sawan was performed in this work by using the 2013 released TRIPOLI-4.9S code and the associated CEA-V5.1.1 data library. First wall, blanket, vacuum vessel and toroidal field magnet of the inboard and outboard components were fully modelled in this 1-D toroidal cylindrical benchmark. The 14.1 MeV source neutrons were sampled from a uniform isotropic distribution in the plasma zone. Nuclear responses including neutron and gamma fluxes, nuclear heating, and material damage indicator were benchmarked against previous published results. The capabilities of the TRIPOLI-4 code on the evaluation of above physics parameters were presented. The nuclear data library from the new FENDL-3.0 evaluation was also benchmarked against the CEA-V5.1.1 results for the neutron transport calculations. The results show that both data libraries can be

  16. Monte Carlo Simulation of an American Option

    Directory of Open Access Journals (Sweden)

    Gikiri Thuo

    2007-04-01

    Full Text Available We implement gradient estimation techniques for sensitivity analysis of option pricing which can be efficiently employed in Monte Carlo simulation. Using these techniques we can simultaneously obtain an estimate of the option value together with the estimates of sensitivities of the option value to various parameters of the model. After deriving the gradient estimates we incorporate them in an iterative stochastic approximation algorithm for pricing an option with early exercise features. We illustrate the procedure using an example of an American call option with a single dividend that is analytically tractable. In particular we incorporate estimates for the gradient with respect to the early exercise threshold level.

  17. Atomistic Monte Carlo simulation of lipid membranes

    DEFF Research Database (Denmark)

    Wüstner, Daniel; Sklenar, Heinz

    2014-01-01

    Biological membranes are complex assemblies of many different molecules of which analysis demands a variety of experimental and computational approaches. In this article, we explain challenges and advantages of atomistic Monte Carlo (MC) simulation of lipid membranes. We provide an introduction...... into the various move sets that are implemented in current MC methods for efficient conformational sampling of lipids and other molecules. In the second part, we demonstrate for a concrete example, how an atomistic local-move set can be implemented for MC simulations of phospholipid monomers and bilayer patches...

  18. Monte Carlo 2000 Conference : Advanced Monte Carlo for Radiation Physics, Particle Transport Simulation and Applications

    CERN Document Server

    Baräo, Fernando; Nakagawa, Masayuki; Távora, Luis; Vaz, Pedro

    2001-01-01

    This book focusses on the state of the art of Monte Carlo methods in radiation physics and particle transport simulation and applications, the latter involving in particular, the use and development of electron--gamma, neutron--gamma and hadronic codes. Besides the basic theory and the methods employed, special attention is paid to algorithm development for modeling, and the analysis of experiments and measurements in a variety of fields ranging from particle to medical physics.

  19. MUSiC - A general search for deviations from Monte Carlo predictions in CMS

    Energy Technology Data Exchange (ETDEWEB)

    Biallass, Philipp A, E-mail: biallass@cern.c [Physics Institute IIIA, RWTH Aachen, Physikzentrum, 52056 Aachen (Germany)

    2009-06-01

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

  20. MUSIC -- An Automated Scan for Deviations between Data and Monte Carlo Simulation

    CERN Document Server

    CMS Collaboration

    2008-01-01

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

  1. MUSiC A General Search for Deviations from Monte Carlo Predictions in CMS

    CERN Document Server

    Biallass, Philipp

    2009-01-01

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

  2. MUSiC - A general search for deviations from Monte Carlo predictions in CMS

    International Nuclear Information System (INIS)

    Biallass, Philipp A

    2009-01-01

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