• Title/Summary/Keyword: Population monte carlo

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Neutron clustering in Monte Carlo iterated-source calculations

  • Sutton, Thomas M.;Mittal, Anudha
    • Nuclear Engineering and Technology
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    • v.49 no.6
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    • pp.1211-1218
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    • 2017
  • Monte Carlo neutron transport codes generally use the method of successive generations to converge the fission source distribution to-and then maintain it at-the fundamental mode. Recently, a phenomenon called "clustering" has been noted, which produces fission distributions that are very far from the fundamental mode. In this study, a mathematical model of clustering in Monte Carlo has been developed. The model draws on previous work for continuous-time birth-death processes, as well as methods from the field of population genetics.

Bayesian estimation for finite population proportion under selection bias via surrogate samples

  • Choi, Seong Mi;Kim, Dal Ho
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.6
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    • pp.1543-1550
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    • 2013
  • In this paper, we study Bayesian estimation for the finite population proportion in binary data under selection bias. We use a Bayesian nonignorable selection model to accommodate the selection mechanism. We compare four possible estimators of the finite population proportions based on data analysis as well as Monte Carlo simulation. It turns out that nonignorable selection model might be useful for weekly biased samples.

A Bayesian Approach to Assessing Population Bioequivalence in a 2 ${\times}$ 2 Crossover Design

  • Oh, Hyun-Sook;Ko, Seoung-Gon
    • Proceedings of the Korean Statistical Society Conference
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    • 2002.05a
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    • pp.67-72
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    • 2002
  • A Bayesian testing procedure is proposed for assessment of bioequivalence in both mean and variance which ensures population bioequivalence under normality assumption. We derive the joint posterior distribution of the means and variances in a standard 2 ${\times}$ 2 crossover experimental design and propose a Bayesian testing procedure for bioequivalence based on a Markov chain Monte Carlo methods. The proposed method is applied to a real data set.

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Clustering and traveling waves in the Monte Carlo criticality simulation of decoupled and confined media

  • Dumonteil, Eric;Bruna, Giovanni;Malvagi, Fausto;Onillon, Anthony;Richet, Yann
    • Nuclear Engineering and Technology
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    • v.49 no.6
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    • pp.1157-1164
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    • 2017
  • The Monte Carlo criticality simulation of decoupled systems, as for instance in large reactor cores, has been a challenging issue for a long time. In particular, due to limited computer time resources, the number of neutrons simulated per generation is still many order of magnitudes below realistic statistics, even during the start-up phases of reactors. This limited number of neutrons triggers a strong clustering effect of the neutron population that affects Monte Carlo tallies. Below a certain threshold, not only is the variance affected but also the estimation of the eigenvectors. In this paper we will build a time-dependent diffusion equation that takes into account both spatial correlations and population control (fixed number of neutrons along generations). We will show that its solution obeys a traveling wave dynamic, and we will discuss the mechanism that explains this biasing of local tallies whenever leakage boundary conditions are applied to the system.

Advances for the time-dependent Monte Carlo neutron transport analysis in McCARD

  • Sang Hoon Jang;Hyung Jin Shim
    • Nuclear Engineering and Technology
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    • v.55 no.7
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    • pp.2712-2722
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    • 2023
  • For an accurate and efficient time-dependent Monte Carlo (TDMC) neutron transport analysis, several advanced methods are newly developed and implemented in the Seoul National University Monte Carlo code, McCARD. For an efficient control of the neutron population, a dynamic weight window method is devised to adjust the weight bounds of the implicit capture in the time bin-by-bin TDMC simulations. A moving geometry module is developed to model a continuous insertion or withdrawal of a control rod. Especially, the history-based batch method for the TDMC calculations is developed to predict the unbiased variance of a bin-wise mean estimate. The developed methods are verified for three-dimensional problems in the C5G7-TD benchmark, showing good agreements with results from a deterministic neutron transport analysis code, nTRACER, within the statistical uncertainty bounds. In addition, the TDMC analysis capability implemented in McCARD is demonstrated to search the optimum detector positions for the pulsed-neutron-source experiments in the Kyoto University Critical Assembly and AGN201K.

ASSESSING POPULATION BIOEQUIVALENCE IN A $2{\times}2$ CROSSOVER DESIGN WITH CARRYOVER EFFECT IN A BAYESIAN PERSPECTIVE

  • Oh Hyun-Sook
    • Journal of the Korean Statistical Society
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    • v.35 no.3
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    • pp.239-250
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    • 2006
  • A $2{\times}2$ crossover design including carryover effect is considered for assessment of population bioequivalence of two drug formulations in a Bayesian framework. In classical analysis, it is complex to deal with the carryover effect since the estimate of the drug effect is biased in the presence of a carryover effect. The proposed method in this article uses uninformative priors and vague proper priors for objectiveness of priors and the posterior probability distribution of the parameters of interest is derived with given priors. The posterior probabilities of the hypotheses for assessing population bioequivalence are evaluated based on a Markov chain Monte Carlo simulation method. An example with real data set is given for illustration.

A BAYESIAN METHOD FOR FINDING MINIMUM GENERALIZED VARIANCE AMONG K MULTIVARIATE NORMAL POPULATIONS

  • Kim, Hea-Jung
    • Journal of the Korean Statistical Society
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    • v.32 no.4
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    • pp.411-423
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    • 2003
  • In this paper we develop a method for calculating a probability that a particular generalized variance is the smallest of all the K multivariate normal generalized variances. The method gives a way of comparing K multivariate populations in terms of their dispersion or spread, because the generalized variance is a scalar measure of the overall multivariate scatter. Fully parametric frequentist approach for the probability is intractable and thus a Bayesian method is pursued using a variant of weighted Monte Carlo (WMC) sampling based approach. Necessary theory involved in the method and computation is provided.

On Estimation of HPD Interval for the Generalized Variance Using a Weighted Monte Carlo Method

  • Kim, Hea-Jung
    • Communications for Statistical Applications and Methods
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    • v.9 no.2
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    • pp.305-313
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    • 2002
  • Regarding to inference about a scalar measure of internal scatter of Ρ-variate normal population, this paper considers an interval estimation of the generalized variance, │$\Sigma$│. Due to complicate sampling distribution, fully parametric frequentist approach for the interval estimation is not available and thus Bayesian method is pursued to calculate the highest probability density (HPD) interval for the generalized variance. It is seen that the marginal posterior distribution of the generalized variance is intractable, and hence a weighted Monte Carlo method, a variant of Chen and Shao (1999) method, is developed to calculate the HPD interval of the generalized variance. Necessary theories involved in the method and computation are provided. Finally, a simulation study is given to illustrate and examine the proposed method.

Dynamic Monte Carlo transient analysis for the Organization for Economic Co-operation and Development Nuclear Energy Agency (OECD/NEA) C5G7-TD benchmark

  • Shaukat, Nadeem;Ryu, Min;Shim, Hyung Jin
    • Nuclear Engineering and Technology
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    • v.49 no.5
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    • pp.920-927
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    • 2017
  • 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.

Calculation of kinetic parameters βeff and L with modified open source Monte Carlo code OpenMC(TD)

  • Romero-Barrientos, J.;Dami, J.I. Marquez;Molina F.;Zambra, M.;Aguilera, P.;Lopez-Usquiano, F.;Parra, B.;Ruiz, A.
    • Nuclear Engineering and Technology
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    • v.54 no.3
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    • pp.811-816
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    • 2022
  • This work presents the methodology used to expand the capabilities of the Monte Carlo code OpenMC for the calculation of reactor kinetic parameters: effective delayed neutron fraction βeff and neutron generation time L. The modified code, OpenMC(Time-Dependent) or OpenMC(TD), was then used to calculate the effective delayed neutron fraction by using the prompt method, while the neutron generation time was estimated using the pulsed method, fitting Λ to the decay of the neutron population. OpenMC(TD) is intended to serve as an alternative for the estimation of kinetic parameters when licensed codes are not available. The results obtained are compared to experimental data and MCNP calculated values for 18 benchmark configurations.