• Nuclear Engineering and Technology
• /
• 제55권9호
• /
• pp.3450-3463
• /
• 2023

In the two-step analysis of Pebble-Bed type High-Temperature Gas-Cooled Reactor (PB-HTGR), the lattice physics calculation for the generation of homogenized cross-sections is based on the fuel pebble. However, the randomly-dispersed fuel particles in the fuel pebble introduce double heterogeneity and randomness. Compared to the deterministic method, the Monte Carlo method which is flexible in geometry modeling provides a high-fidelity treatment. Therefore, the Monte Carlo code NECP-MCX is extended in this study to perform the lattice physics calculation of the PB-HTGR. Firstly, the capability for the simulation of randomly-dispersed media, using the explicit modeling approach, is developed in NECP-MCX. Secondly, the capability for the generation of the homogenized cross-section is also developed in NECP-MCX. Finally, simplified PB-HTGR problems are calculated by a two-step neutronics analysis tool based on Monte Carlo homogenization. For the pebble beds mixed by fuel pebble and graphite pebble, the bias is less than 100 pcm when compared to the high-fidelity model, and the bias is increased to 269 pcm for pebble bed mixed by depleted fuel pebble. Numerical results show that the Monte Carlo lattice physics calculation for the two-step analysis of PB-HTGR is feasible.

• 한국농공학회지
• /
• 제18권4호
• /
• pp.4232-4241
• /
• 1976

This study was carried out to clarify the stochastic characteristics of monthly rainfalls and to select a proper model for generating the sequential monthly rainfall amounts. The results abtained are as follows: 1. Log-Normal distribution function is the best fit theoretical distribution function to the empirical distribution of monthly rainfall amounts. 2. Seasonal and random components are found to exist in the time series of monthly rainfall amounts and non-stationarity is shown from the correlograms. 3. The Monte Carlo model shows a tendency to underestimate the mean values and standard deviations of monthly rainfall amounts. 4. The 1st order Markov model reproduces means, standard deviations, and coefficient of skewness with an error of ten percent or less. 5. A correlogram derived from the data generated by 1st order Markov model shows the charaterstics of historical data exactly. 6. It is concluded that the 1st order Markov model is superior to the Monte Carlo model in their reproducing ability of stochastic properties of monthly rainfall amounts.

• ETRI Journal
• /
• 제27권4호
• /
• pp.377-384
• /
• 2005

We investigate near-infrared light (NIR) propagation in a model of an adult head using an extensive Monte Carlo (MC) simulation. The adult head model is a four-layered slab which consists of a surface layer, a cerebrospinal fluid layer, a gray-matter layer, and a white-matter layer. We study the effects of a refractive index mismatch on the model, calculating the intensity of detected light, mean flight time, and partial mean flight time of each layer for various refractive indices of the cerebrospinal fluid layer as functions of source-detector spacing. The Monte Carlo simulation shows that the refractive index mismatch presents very rich results including rapidly decaying intensity of detected light and a peak and cross-over in the partial mean flight time with source-detector spacing. We also investigate spatial sensitivity profiles at various source-detector spacings, discussing the index mismatch effect on the model.

• Structural Engineering and Mechanics
• /
• 제71권4호
• /
• pp.329-339
• /
• 2019

Assessment of failure probability, especially for a complex structure, requires a considerable number of calls to the numerical model. Reliability methods have been developed to decrease the computational time. In this approach, the original numerical model is replaced by a surrogate model which is usually explicit and much faster to evaluate. The current paper proposed an efficient reliability method based on Monte Carlo simulation (MCS) and multi-gene genetic programming (MGGP) as a robust variant of genetic programming (GP). GP has been applied in different fields; however, its application to structural reliability has not been tested. The current study investigated the performance of MGGP as a surrogate model in structural reliability problems and compares it with other surrogate models. An adaptive Metropolis algorithm is utilized to obtain the training data with which to build the MGGP model. The failure probability is estimated by combining MCS and MGGP. The efficiency and accuracy of the proposed method were investigated with the help of five numerical examples.

• 대한환경공학회지
• /
• 제31권4호
• /
• pp.300-307
• /
• 2009

차수막이 설치되어 있지 않은 매립장에서 하부 지반으로 누출된 침출수의 이동을 고려하였다. 일련의 Monte-Carlo 시뮬레이션의 결과를 검토하여 지반의 수리지질학적, 화학적 불균질성이 침출수 이동에 미치는 영향을 분석하였다. 본 연구에서는 (1) 수리전도도(K)와 분배계수($K_d$)가 균질, (2) 수리전도도만 불균질, (3) 수리전도도와 분배계수가 모두 불균질 경우 등 3단계의 공간 변동성이 있는 가상 매립지 시스템을 시뮬레이션하였다. 포화 유동 모델과 오염물 이동 모델을 이용하여 지구통계학적 입력 인자들로부터 생성된 역상관관계의 랜덤 수리전도도-분배계수 장 내 침출수 이동을 평가하였다. 100회의 Monte-Carlo 시뮬레이션으로부터 얻은 결과에 대하여 평균, 표준편차, 변이계수와 같은 점기반 통계치들을 계산하였다. 통계치 결과에 따르면 매립 지반의 수리전도도와 분배계수의 불균질성은 침출수 농도를 제어하는 주요한 인자로서 수리전도도와 분배계수의 복합 불균질성을 반영함에 따라 오염물 이동의 변동성이 증가하였다. 또한 오염원과 감시정간의 거리가 커질수록 각 실현 간 침출수 농도의 변동성이 증가하였다.

• 한국지하수토양환경학회지:지하수토양환경
• /
• 제11권5호
• /
• pp.1-8
• /
• 2006

본 연구에서는 매립장에서 하부 지반으로 누출된 침출수의 이동에 흡착 불균질성이 미치는 영향을 평가하고자 하였다. 이를 위하여 차수막이 설치되어 있지 않은 매립장을 대상으로 일련의 Monte-Carlo 시뮬레이션을 수행하고 그 결과를 검토하였다. 균질한 지층에서 강불균질 지층에 이르는 다양한 불균질도를 가진 랜덤 분배계수 장에 대하여 포화 유동 모델과 오염물 이동 모델을 연결시켜 침출수의 이동을 계산하였다. 100회에 걸쳐 수행된 Monte-Carlo 시뮬레이션의 결과치로부터 얻은 평균, 표준편차, 변이계수와 같은 점기반 통계치들을 이용하여 화학적 불균질도의 영향을 평가하였다. 통계치 결과에 따르면 매립지반의 분배계수 분포가 지반 내 침출수 농도를 결정하는데 매우 중요한 인자로 나타났다. 균질 흡착의 경우와 비교할 때 불균질 분배계수 장에서는 실현 간 침출수 농도 분포의 변동성이 나타났다. 분배계수 장의 분산 및 오염원과 감시정 간의 이동 시간이 커질수록 농도의 변동성이 증가하였다. 이러한 결과는 화학적 변동성이 큰 지반 내에서의 침출수 이동을 예측할 때 단일 분배계수 값을 사용하면 상당한 오차를 유발할 수 있음을 나타낸다.

• 한국소음진동공학회논문집
• /
• 제23권6호
• /
• pp.553-562
• /
• 2013

Vehicle vibrations arise from engine and road surface excitations. The engine mount system of a passenger car sustains the engine weight and insulates the excitation force from the engine system. The dynamic properties of viscoelastic material used for the vehicle engine mounts have large variation due to environmental factors such as environmental temperature and humidity etc. The present study aims to investigate the variability of dynamic characteristics in rubber engine mounts considering both environmental temperature change and material model errors/uncertainty. The engine mounts for a passenger car were modeled using finite element method. Then, the dynamic stiffness variability of the engine mounts were estimated using Monte Carlo simulation method. In order to estimate the variations in the storage and loss moduli of the viscoelastic materials, the material properties of the synthetic rubber were expressed as a fractional-derivative model. Next, in order to simulate the uncertainty propagation of the dynamic stiffness for the engine mounts due to the storage and loss moduli variations, the Monte Carlo simulation was used. The Monte Carlo simulation results showed large variation of the engine-mount stiffness along frequency axis.

• Bulletin of the Korean Chemical Society
• /
• 제33권3호
• /
• pp.901-905
• /
• 2012

In this study, we investigated the pure geometrical effect of porous materials in gas adsorption using the grand canonical Monte Carlo simulations of primitive gas-pore models with various pore geometries such as planar, cylindrical, and random pore geometries. Although the model does not possess atomistic level details of porous materials, our simulation results provided many insightful information in the effect of pore geometry on the adsorption behavior of gas molecules. First, the surface curvature of porous materials plays a significant role in the amount of adsorbed gas molecules: the concave surface such as in cylindrical pores induces more attraction between gas molecules and pore, which results in the enhanced gas adsorption. On the contrary, the convex surface of random pores gives the opposite effect. Second, this geometrical effect shows a nonmonotonic dependence on the gas-pore interaction strength and length. Third, as the external gas pressure is increased, the change in the gas adsorption due to pore geometry is reduced. Finally, the pore geometry also affects the collision dynamics of gas molecules. Since our model is based on primitive description of fluid molecules, our conclusion can be applied to any fluidic systems including reactant-electrode systems.

• 대한기계학회논문집A
• /
• 제26권11호
• /
• pp.2421-2428
• /
• 2002

In this study, the failure probability of the degraded LP turbine blade steel was performed using the Monte Carlo simulation to apply variation of applied stress and strength. For this purpose, applied stress under the service condition of steady state was obtained by theoretical stress analysis and the maximum Von-Mises stress was 219MPa. The fatigue strength under rotating-bending load was evaluated by the staircase method. Furthermore, 3-parameter Weibull distribution was found to be most appropriate among assumed distributions when the probabilistic distributions of tensile and fatigue strength were determined by the proposed analysis. The failure probability with various loading conditions was derived from the strength-stress interference model and the characteristic factor of safety was also estimated.

• International Journal of Aeronautical and Space Sciences
• /
• 제8권2호
• /
• pp.126-131
• /
• 2007

In this paper, Monte Carlo Simulation (MCS) method was used as an uncertainty assessment tool for air flow, net thrust measurement. Uuncertainty sources of the net thrust measurement were analyzed, and the probability distribution characteristics of each source were discussed. Detailed MCS methodology was described including the effect of the number of simulation. Compared to the conventional sensitivity coefficient method, the MCS method has advantage in the uncertainty assessment. The MCS is comparatively simple, convenient and accurate, especially for complex or nonlinear measurement modeling equations. The uncertainty assessment result by MCS was compared with that of the conventional sensitivity coefficient method, and each method gave different result. The uncertainties in the net thrust measurement by the MCS and the conventional sensitivity coefficient method were 0.906% and 1.209%, respectively. It was concluded that the first order Taylor expansion in the conventional sensitivity coefficient method and the nonlinearity of model equation caused the difference. It was noted that the uncertainty assessment method should be selected carefully according to the mathematical characteristics of the model equation of the measurement.