• Computers and Concrete
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• v.13 no.5
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• pp.659-677
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• 2014

A Bayesian response surface updating procedure is applied in order to update the parameters of the covariance function of a random field for concrete properties based on a limited number of available measurements. Formulas as well as a numerical algorithm are presented in order to update the parameters of response surfaces using Markov Chain Monte Carlo simulations. The parameters of the covariance function are often based on some kind of expert judgment due the lack of sufficient measurement data. However, a Bayesian updating technique enables to estimate the parameters of the covariance function more rigorously and with less ambiguity. Prior information can be incorporated in the form of vague or informative priors. The proposed estimation procedure is evaluated through numerical simulations and compared to the commonly used least square method.

• Bulletin of the Korean Chemical Society
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• v.17 no.3
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• pp.209-211
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• 1996

• Bulletin of the Korean Chemical Society
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• v.21 no.3
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• pp.361-363
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• 2000

• Bulletin of the Korean Chemical Society
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• v.33 no.3
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• pp.971-974
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• 2012

The facilitated diffusion effect on protein-DNA binding is studied. A rigorous theoretical approach is presented to deal with the coupling between one-dimensional and three-dimensional diffusive motions. For a simplified model, the present approach can provide numerically exact results, which are confirmed by the lattice-based Monte Carlo simulations.

• Bulletin of the Korean Chemical Society
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• v.28 no.10
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• pp.1811-1814
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• 2007

• Journal of the Korean Statistical Society
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• v.23 no.2
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• pp.445-461
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• 1994

This paper deals with the problem of obtaining some Bayes estimators and Bayesian credible regions of a reliability function for the Rayleigh distribution. Using several priors for a reliability function some Bayes estimators and Bayes credible sets are proposed and studied under squared error loss and Harris loss. Also the performances and behaviors of the proposed Bayes estimators are examined via Monte Carlo simulations and some numericla examples are given.

• Nuclear Engineering and Technology
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• v.55 no.10
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• pp.3639-3647
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• 2023

This paper defines a 3D full core neutronics benchmark which is based on the NuScale small modular reactor (SMR) concept. The paper provides a detailed description of the NuScale-like core, a list of expected outputs, and a reference solution to the benchmark exercises obtained with the Monte Carlo code Serpent. The benchmark was developed in the framework of the Euratom McSAFER project and can be used for verification of computational chains dedicated to 3D full-core neutronics simulations of water cooled SMRs. The paper is supplemented with a digital data set to ease the modeling process.

• Geomechanics and Engineering
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• v.3 no.3
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• pp.169-188
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• 2011

Response of buried flexible pipe-soil system is studied, through numerical analysis, with respect to deflection and buckling in a spatially varying soil media. In numerical modeling procedure, soil parameters are modeled as two-dimensional non-Gaussian homogeneous random field using Cholesky decomposition technique. Numerical analysis is performed using random field theory combined with finite difference numerical code FLAC 5.0 (2D). Monte Carlo simulations are performed to obtain the statistics, i.e., mean and variance of deflection and circumferential (buckling) stresses of buried flexible pipe-soil system in a spatially varying soil media. Results are compared and discussed in the light of available analytical solutions as well as conventional numerical procedures in which soil parameters are considered as uniformly constant. The statistical information obtained from Monte Carlo simulations is further utilized for the reliability analysis of buried flexible pipe-soil system with respect to deflection and buckling. The results of the reliability analysis clearly demonstrate the influence of extent of variation and spatial correlation structure of soil parameters on the performance assessment of buried flexible pipe-soil systems, which is not well captured in conventional procedures.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.8
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• pp.574-581
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• 2019

This paper investigates the effects of thrust misalignments and offsets of the lateral center of gravity of a space launch vehicle on its guidance performance. Sensitivity analysis and Monte Carlo simulations are applied to analyze their effects by computing changes in orbit injection errors when including the error sources. To compensate their effects, the attitude controller including an integrator additionally and the Steering Misalignment Correction (SMC) routine of the Saturn V are considered, and then Monte Carlo simulations are performed to evaluate their performances.

• Journal of the Korea Computer Graphics Society
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• v.30 no.2
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• pp.1-9
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• 2024

In this paper, we propose a new method to visualize different vector field patterns from density data. We use moving least squares (MLS), which is used in physics-based simulations and geometric processing. However, typical MLS does not take into account the nature of density, as it is interpolated to a higher order through vector-based constraints. In this paper, we design an algorithm that incorporates Monte Carlo-based weights into the MLS to efficiently account for the density characteristics implicit in the input data, allowing the algorithm to represent different forms of white noise. As a result, we experimentally demonstrate detailed vector fields that are difficult to represent using existing techniques such as naive MLS and divergence-constrained MLS.