• Communications for Statistical Applications and Methods
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• v.29 no.4
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• pp.471-486
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• 2022

Autoregressive moving average (ARMA) models involve nonlinearity in the model coefficients because of unobserved lagged errors, which complicates the likelihood function and makes the posterior density analytically intractable. In order to overcome this problem of posterior analysis, some approximation methods have been proposed in literature. In this paper we first review the main analytic approximations proposed to approximate the posterior density of ARMA models to be analytically tractable, which include Newbold, Zellner-Reynolds, and Broemeling-Shaarawy approximations. We then use the Kullback-Leibler divergence to study the relation between these three analytic approximations and to measure the distance between their derived approximate posteriors for ARMA models. In addition, we evaluate the impact of the approximate posteriors distance in Bayesian estimates of mean and precision of the model coefficients by generating a large number of Monte Carlo simulations from the approximate posteriors. Simulation study results show that the approximate posteriors of Newbold and Zellner-Reynolds are very close to each other, and their estimates have higher precision compared to those of Broemeling-Shaarawy approximation. Same results are obtained from the application to real-world time series datasets.

• The KSFM Journal of Fluid Machinery
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• v.19 no.3
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• pp.33-36
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• 2016

The investigation on the verification of availability simulation for small-scale plant has been carried out. This study focuses on the availability variation induced by number of equipment and iteration with failure density function. The equipment classification of small-scale plant and failure type and the methodologies on Monte-Carlo simulation are established. The availability deviation with programs showed under Max. 1.7% for the case of normal function. This method could be used to availability evaluation of small-scale plant, but calibration of the failure density function is necessary for general application.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.173-173
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• 2018

본 연구는 기상-수문 분야에서 고해상도 수문기상요소를 산출하기 위해 WRF-Hydro(Weather Research and Forecasting and Model Hydrological modeling extension package) 모형을 한반도 대상으로 구축하였다. 모형은 미국 대기 연구 국립센터(NOAA)에서 개발된 커뮤니티형 고해상도 예측모델이므로 미국 등에서 활발히 활용되기 시작하였으나 아직 우리나라 적용성에 대한 연구는 많지 않다. 본 연구에서는 WRF-Hydro 모형을 한반도에 적절히 사용하기 위해 표면유출, 보수깊이, 표면거칠기와 같은 파라미터를 보정하였다. WRF-Hydro는 지역 기상모형인 WRF와 연계하여 coupled WRF/WRF-Hydro 모형을 구동하였으며, 고해상도 유출값을 얻기 위해 미국 지질조사국(USGS)에서 제공한 HydroSHEDS(Hydrological data and map based on SHuttle Elevation Derivatives at multiple Scales)를 이용하였다. 본 연구에서는 관측된 유출값을 Markov Chain Monte Carlo(MCMC) 방법을 활용하여 모형값과 비교하여 파라미터 보정을 수행하였으며, 파라미터 보정된 WRF/WRF-Hydro를 활용해 한반도 과거 홍수 및 가뭄 사상을 모의하여 결과를 분석하였다.

• Structural Engineering and Mechanics
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• v.80 no.6
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• pp.677-688
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• 2021

The building design codes and standards in many countries usually are either fully or partially adopted from the international codes. However, regional conditions like the quality of construction industry and different statistical parameters of load and resistance have essential roles in the code calibration of building design codes. This paper presents a probabilistic approach to assess the reliability level of adopted national building codes by simulating design situations and considering all load combinations. The impact of the uncertainty of wind and earthquake loads, which are entirely regional condition dependent and have a high degree of uncertainty, are quantified. In this study, the design situation is modeled by generating thousands of numbers for load effect ratios, and the reliability level of steel elements for all load combinations and different load ratios is established and compared to the target reliability. This approach is applied to the Iranian structural steel code as a case study. The results indicate that the Iranian structural steel code lacks safety in some load combinations, such as gravity and earthquake load combinations, and is conservative for other load combinations. The present procedure can be applied to the assessment of the reliability level of other national codes.

• Nuclear Engineering and Technology
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• v.39 no.2
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• pp.133-142
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• 2007

The Electric Power Research Institute (EPRI) demonstrated a method for monitoring the performance of instrument channels in Topical Report (TR) 104965, 'On-Line Monitoring of Instrument Channel Performance.' This paper presents the results of several models originally developed by EPRI to monitor three nuclear plant sensor sets: Pressurizer Level, Reactor Protection System (RPS) Loop A, and Reactor Coolant System (RCS) Loop A Steam Generator (SG) Level. The sensor sets investigated include one redundant sensor model and two non-redundant sensor models. Each model employs an Auto-Associative Kernel Regression (AAKR) model architecture to predict correct sensor behavior. Performance of each of the developed models is evaluated using four metrics: accuracy, auto-sensitivity, cross-sensitivity, and newly developed Error Uncertainty Limit Monitoring (EULM) detectability. The uncertainty estimate for each model is also calculated through two methods: analytic formulas and Monte Carlo estimation. The uncertainty estimates are verified by calculating confidence interval coverages to assure that 95% of the measured data fall within the confidence intervals. The model performance evaluation identified the Pressurizer Level model as acceptable for on-line monitoring (OLM) implementation. The other two models, RPS Loop A and RCS Loop A SG Level, highlight two common problems that occur in model development and evaluation, namely faulty data and poor signal selection

• Geomechanics and Engineering
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• v.24 no.3
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• pp.281-293
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• 2021

Uncertainties in geomechanical input parameters which mainly related to inappropriate data acquisition and estimation due to lack of sufficient calibration information, have led wellbore instability not yet to be fully understood or addressed. This paper demonstrates a workflow of employing Quantitative Risk Assessment technique, considering these uncertainties in terms of rock properties, pore pressure and in-situ stresses to makes it possible to survey not just the likelihood of accomplishing a desired level of wellbore stability at a specific mud pressure, but also the influence of the uncertainty in each input parameter on the wellbore stability. This probabilistic methodology in conjunction with Monte Carlo numerical modeling techniques was applied to a case study of a well. The response surfaces analysis provides a measure of the effects of uncertainties in each input parameter on the predicted mud pressure from three widely used failure criteria, thereby provides a key measurement for data acquisition in the future wells to reduce the uncertainty. The results pointed out that the mud pressure is tremendously sensitive to UCS and SHmax which emphasize the significance of reliable determinations of these two parameters for safe drilling. On the other hand, the predicted safe mud window from Mogi-Coulomb is the widest while the Hoek-Brown is the narrowest and comparing the anticipated collapse failures from the failure criteria and breakouts observations from caliper data, indicates that Hoek-Brown overestimate the minimum mud weight to avoid breakouts while Mogi-Coulomb criterion give better forecast according to real observations.

• Communications for Statistical Applications and Methods
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• v.25 no.2
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• pp.131-157
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• 2018

We propose a robust event date model to estimate the date of a target event by a combination of individual dates obtained from archaeological artifacts assumed to be contemporaneous. These dates are affected by errors of different types: laboratory and calibration curve errors, irreducible errors related to contaminations, and taphonomic disturbances, hence the possible presence of outliers. Modeling based on a hierarchical Bayesian statistical approach provides a simple way to automatically penalize outlying data without having to remove them from the dataset. Prior information on individual irreducible errors is introduced using a uniform shrinkage density with minimal assumptions about Bayesian parameters. We show that the event date model is more robust than models implemented in BCal or OxCal, although it generally yields less precise credibility intervals. The model is extended in the case of stratigraphic sequences that involve several events with temporal order constraints (relative dating), or with duration, hiatus constraints. Calculations are based on Markov chain Monte Carlo (MCMC) numerical techniques and can be performed using ChronoModel software which is freeware, open source and cross-platform. Features of the software are presented in Vibet et al. (ChronoModel v1.5 user's manual, 2016). We finally compare our prior on event dates implemented in the ChronoModel with the prior in BCal and OxCal which involves supplementary parameters defined as boundaries to phases or sequences.

• Journal of Environmental Science International
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• v.13 no.2
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• pp.175-180
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• 2004

A prompt gamma-ray neutron activation (PGNA) system was simulated by the Monte Carlo N-Particle transport code (MCNP-4A) to estimate the level at which the scattered photon fluence rate, the absolute efficiency of the HPGe-detector, the volume of the concrete sample and the $^{35}$ /Cl(n, ${\gamma}$) reaction rate in this sample contribute to the count rate in the NaCl concentration measurement. The n- ${\gamma}$ fluence rates at the ST-2 beam tube exit of the HANARO reactor were used as input data, and the GAMMA-X type HPGe detector was modeled to tally 1.1649 MeV ${\gamma}$ -rays emitted from the $^{35}$ Cl(n, ${\gamma}$) reaction in the concrete sample. For three cylindrical concrete samples of 13.8, 46.8 and 157.1 ㎤ volumes, respectively, the relations between the NaCl weight fractions of 0.1, 1, 2 and 5 % in each of the concrete samples and the 1.1 649 MeV pulses created in the HPGe detector model were studied. As a result, it was found that the count rate at the same NaCl concentration nearly depends on the volume of the samples in a simulated condition of the same NaCl concentration samples, and that the linearities of the NaCl concentration calibration curves were reasonable in the narrow range of the NaCl weight fraction.

• Journal of Radiation Protection and Research
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• v.37 no.3
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• pp.146-148
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• 2012

The use of GEANT4 simulation toolkit has increased in the radiation medical field for the design of treatment system and the calibration or validation of treatment plans. Moreover, it is used especially on calculating dose simulation using medical data for radiation therapy. However, using internal visualization tool of GEANT4 detector constructions on expressing dose result has deficiencies because it cannot display isodose line. No one has attempted to use this code to a real patient's data. Therefore, to complement this problem, using the result of gMocren that is a three-dimensional volume-visualizing tool, we tried to display a simulated dose distribution and isodose line on medical image. In addition, we have compared cross-validation on the result of gMocren and GEANT4 simulation with commercial radiation treatment planning system. We have extracted the analyzed data of dose distribution, using real patient's medical image data with a program based on Monte Carlo simulation and visualization tool for radiation isodose mapping.

• Journal of the Korean Geotechnical Society
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• v.30 no.8
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• pp.5-11
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• 2014

The objective of this paper is to develop a rational reliability analysis procedure for the LRFD design provisions of bridge substructures. A bridge abutments is considered in this study. The reliability analysis is applied to determine the relationship between the major design parameters for bridge abutment and reliability index. The considered load components include dead load, vertical and horizontal earth pressure, earth surcharge, and vehicle live load. Several limit states are considered: foundation bearing capacity, sliding, and overturning. The analysis results show that the most important parameter in the reliability analysis is the effective stress friction angle of the soil. The reliability indices are calculated using Monte Carlo simulations for a selected bridge abutment. The results of the sensitivity analysis indicate that reliability index is most sensitive with regard to resistance factor and horizontal earth pressure factor.