• Earthquakes and Structures
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• v.12 no.5
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• pp.569-581
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• 2017

The Monte Carlo Simulation (MCS) based seismic fragility analysis (SFA) approach allows defining more realistic relationship between failure probability and seismic intensity. However, the approach requires simulating large number of nonlinear dynamic analyses of structure for reliable estimate of fragility. It makes the approach computationally challenging. The response surface method (RSM) based metamodeling approach which replaces computationally involve complex mechanical model of a structure is found to be a viable alternative in this regard. An adaptive moving least squares method (MLSM) based RSM in the MCS framework is explored in the present study for efficient SFA of existing structures. In doing so, the repetition of seismic intensity for complete generation of fragility curve is avoided by including this as one of the predictors in the response estimate model. The proposed procedure is elucidated by considering a non-linear SDOF system and an existing reinforced concrete frame considered to be located in the Guwahati City of the Northeast region of India. The fragility results are obtained by the usual least squares based and the proposed MLSM based RSM and compared with that of obtained by the direct MCS technique to study the effectiveness of the proposed approach.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.19 no.4
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• pp.447-457
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• 2021

Graphite Isotope Ratio Method (GIRM) can be used to estimate plutonium production in a graphite-moderated reactor. This study presents verification results for the GIRM combined with a 3-D polynomial regression function to estimate cumulative plutonium production in a graphite-moderated reactor. Using the 3-D Monte-Carlo method, verification was done by comparing the cumulative plutonium production with the GIRM. The GIRM can estimate plutonium production for specific sampling points using a function that is based on an isotope ratio of impurity elements. In this study, the ¹⁰B/¹¹B isotope ratio was chosen and calculated for sampling points. Then, 3-D polynomial regression was used to derive a function that represents a whole core cumulative plutonium production map. To verify the accuracy of the GIRM with polynomial regression, the reference value of plutonium production was calculated using a Monte-Carlo code, MCS, up to 4250 days of depletion. Moreover, the amount of plutonium produced in certain axial layers and fuel pins at 1250, 2250, and 3250 days of depletion was obtained and used for additional verification. As a result, the difference in the total cumulative plutonium production based on the MCS and GIRM results was found below 3.1% with regard to the root mean square (RMS) error.

• Nuclear Engineering and Technology
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• v.54 no.7
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• pp.2625-2634
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• 2022

Discretization errors are extremely challenging conundrums of discrete ordinates calculations for radiation transport problems with void regions. In previous work, we have presented a multi-collision source method (MCS) to overcome discretization errors, but the efficiency needs to be improved. This paper proposes a goal-oriented algorithm for the MCS method to adaptively determine the partitioning of the geometry and dynamically change the angular quadrature in remaining iterations. The importance factor based on the adjoint transport calculation obtains the response function to get a problem-dependent, goal-oriented spatial decomposition. The difference in the scalar fluxes from one high-order quadrature set to a lower one provides the error estimation as a driving force behind the dynamic quadrature. The goal-oriented algorithm allows optimizing by using ray-tracing technology or high-order quadrature sets in the first few iterations and arranging the integration order of the remaining iterations from high to low. The algorithm has been implemented in the 3D transport code ARES and was tested on the Kobayashi benchmarks. The numerical results show a reduction in computation time on these problems for the same desired level of accuracy as compared to the standard ARES code, and it has clear advantages over the traditional MCS method in solving radiation transport problems with reflective boundary conditions.

• Journal of Microbiology and Biotechnology
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• v.28 no.4
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• pp.510-519
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• 2018

Synbiotics are a combination of probiotics and prebiotics, which lead to synergistic benefits in host welfare. Probiotics have been used as an alternative to antibiotics. Among the probiotics, Pediococcus acidilactici (PA) has shown excellent antimicrobial activity against Salmonella Gallinarum (SG) as a major poultry pathogen and has improved the production performances of animals. Inulin is widely used as a prebiotic for the improvement of animal health and growth. The main aim of this study was to investigate the antimicrobial activity of inulin nanoparticle (IN)-internalized PA encapsulated into alginate/chitosan/alginate (ACA) microcapsules (MCs) for future in vivo application. The prepared phthalyl INs (PINs) were characterized by DLS and FE-SEM. The contents of phthal groups in the PINs were estimated by $^1H-NMR$ measurement as 25.1 mol.-%. The sizes of the PINs measured by DLS were approximately 203 nm. Internalization into PA was confirmed by confocal microscopy and flow cytometry. The antimicrobial activity of PIN-internalized probiotics encapsulated into ACA MCs was measured by coculture antimicrobial assays on SG. PIN-internalized probiotics had a higher antimicrobial ability than that of ACA MCs loaded with PA/inulin or PA. Interestingly, when PINs were treated with PA and encapsulated into ACA MCs, as a natural antimicrobial peptide, pediocin was produced much more in the culture medium compared with other groups with inulin-loaded ACA MCs and PA encapsulated into ACA MCs.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.2
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• pp.61-74
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• 2012

In this paper, we propose a illumination-robust face recognition system using MCS-LBP and 2D-PCA algorithm. A binary pattern transform which has been used in the field of the face recognition and facial expression, has a characteristic of robust to illumination. Thus, this paper propose MCS-LBP which is more robust to illumination than previous LBP, and face recognition system fusing 2D-PCA algorithm. The performance evaluation of proposed system was performed by using various binary pattern images and well-known face recognition features such as PCA, LDA, 2D-PCA and ULBP histogram of gabor images. In the process of performance evaluation, we used a YaleB face database, an extended YaleB face database, and a CMU-PIE face database that are constructed under varying lighting condition, and the proposed system which consists of MCS-LBP image and 2D-PCA feature show the best recognition accuracy.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2004.05a
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• pp.281-284
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• 2004

Mean energy of electrons in $SF_6-Ar$ Mixtures Gas used by MCS-BEq algorithm has been analysed over the E/N range $30{\sim}300[Td]$ by a two term Boltzmann equation and by a Monte Carlo Simulation using a set of electron cross sections determined by other authors, experimentally the electron swarm parameters for 0.2[%] and 0.5[%] $SF_6-Ar$, 0.1[%] and 5.0[%], $SF_6-Ar$ mixtures were measured by time-of-flight(TOF) method. The transport Coefficients for electrons in (100[%])$SF_6$. (100[%])Ar, (0.2[%])$SF_6-Ar$ and (0.5[%]) $SF_6-Ar$, (5.0[%]) $SF_6-Ar$, (0.1[%])$SF_6-Ar$ mixtures were measured by time-of-flight method, and the electron energy distribution function and the parameters of the velocity and the diffusion were determined by the variation of the collision cross-sections with energy. The results obtained from Boltzmann equation method and Monte Carlo simulation have been compared with present and previously obtained data and respective set of electron collision cross sections of the molecules.

• Structural Engineering and Mechanics
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• v.11 no.4
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• pp.373-392
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• 2001

The main idea behind the paper is to present two alternative methods of homogenization of the heat conduction problem in composite materials, where the heat conductivity coefficients are assumed to be random variables. These two methods are the Monte-Carlo simulation (MCS) technique and the second order perturbation second probabilistic moment method, with its computational implementation known as the Stochastic Finite Element Method (SFEM). From the mathematical point of view, the deterministic homogenization method, being extended to probabilistic spaces, is based on the effective modules approach. Numerical results obtained in the paper allow to compare MCS against the SFEM and, on the other hand, to verify the sensitivity of effective heat conductivity probabilistic moments to the reinforcement ratio. These computational studies are provided in the range of up to fourth order probabilistic moments of effective conductivity coefficient and compared with probabilistic characteristics of the Voigt-Reuss bounds.

• Proceedings of the KIEE Conference
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• 2000.07e
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• pp.17-21
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• 2000

A Study on the electron energy distribution function in $SF_6+Ar$ mixtures gas used by MCS-BE algorithm, the electron swam parameters in the 0.5% and 0.2% $SF_6+Ar$ mixtures are measured by time of flight method over the E/N(Td) range from 30 to 300(Td). A two-term approximation of the Boltzmann equation analysis and Monte Carlo simulation have been also used to study electron transport coefficients. The electron energy distribution function has been analysed in $SF_6$ gas and $SF_6+Ar$ mixtures at E/N : 200(Td) for a case of the equilibrium region in the mean electron energy. The measured results and the calculated results have been compared each other.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 1999.05a
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• pp.696-699
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• 1999

The electron transport coefficients in $SF_6+N_2$ gas is analysed in range of E/N values from 100~900(Td) by a Monte Carlo simulation and Boltzmann method, using a set of electron collision cross sections determined by the authors. The result of the Monte Carlo simulation such as electron drift velocity, ionization and electron attachment coefficients, longitudinal and transverse diffusion coefficients in nearly agreement with the respective experimental and theoretical for a range of E/N.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.62 no.1
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• pp.18-22
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• 2013

This paper describes the information for quantitative simulation of weakly ionized plasma. We must grasp the meaning of the plasma state condition to utilize engineering application and to understand materials of plasma state. Using quantitative simulations of weakly ionized plasma, we can analyze gas characteristic. In this paper, the electron transport characteristic in $CH_4$ has been analysed over the E/N range 0.1~300[Td], at the 300[$_{\circ}\;K$] by the two term approximation Boltzmann equation method and Monte Carlo Simulation. Boltzmann equation method has also been used to predict swarm parameter using the same cross sections as input. The behavior of electron has been calculated to give swarm parameter for the electron energy distribution function has been analysed in $CH_4$ at E/N=10, 100 for a case of the equilibrium region in the mean energy. A set of electron collision cross section has been assembled and used in Monte Carlo simulation to predict values of swarm parameters. The result of Boltzmann equation and Monte Carlo Simulation has been compared with experimental data by Ohmori, Lucas and Carter. The swarm parameter from the swarm study are expected to sever as a critical test of current theories of low energy scattering by atoms and molecules.