• Proceedings of the KSME Conference
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• 2001.11a
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• pp.155-160
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• 2001

This paper describes a probabilistic fracture mechanics (PFM) analysis based on Monte Carlo (MC) simulation. In the analysis of CANDU pressure tube, it is necessary to perform the PFM analyses based on statistical consideration of flaw generation time. A depth and an aspect ratio of initial semi-elliptical surface crack, a fracture toughness value, delayed hydride cracking (DHC) velocity, and flaw generation time are assumed to be probabilistic variables. In all the analyses, degradation of fracture toughness due to neutron irradiation is considered. Also, the failure criteria considered are plastic collapse, unstable fracture and crack penetration. For the crack growth by DHC, the failure probability was evaluated in due consideration of flaw generation time.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.766-767
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• 2015

전자기 관련 제품에서 제작공차에 의한 성능변동의 확률론적 분포특성을 효율적으로 예측하기 위해 성능 모멘트 적분법을 도입하였다. 제안된 기법을 검증하기 위해 간단한 수학예제와 스피커 모델의 폴피스 사이 공극의 평균자속 밀도에 대한 확률론적 분포특성 예측을 수행하고, 이를 기존 확률론적 분포특성 예측 기법과 비교하였다. 또한 몬테카를로 수치모사법을 이용하여 도출된 성능의 확률론적 분포특성 예측 값을 재계산 후 비교함으로써 제안된 기법의 정밀도를 검증하였다.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.785-790
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• 2008

Vibration of a non-linear system under random parametric excitations was evaluated by probablistic methods. The non-linear characteristic terms of a system were quasi-linearized and excitation terms were remained as they were given. An analytical method where the square mean of error was minimized was ysed. An alternative method was an energy method where the damping energy and rstoring energy of the linearized system were equalized to those of the original non-linear system. The numerical results were compared with those obtained by Monte Carlo simulation. The comparison showed the results obtained by Monte Carlo simulation located between those by the analytical method and those by the energy method.

• Ocean and Polar Research
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• v.25 no.spc3
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• pp.347-351
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• 2003

A new approach to reliability analysis of rubble mound breakwater using neural network is proposed. At first, a neural network model which can estimate the stability number of any breakwaters for some design conditions is trained. Then, the neural network model is integrated with Monte Carlo simulation technique in order to calculate probability of failure for the breakwater. The proposed technique is compared with conventional approach using empirical formula.

• Proceedings of the KSME Conference
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• 2001.06a
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• pp.459-464
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• 2001

For major nuclear power plant components periodic inspections and integrity assessments are needed for the safety. But many flaws are undetectable due to sampling inspection. Probabilistic integrity assessment is applied to take into consideration of uncertainty and variance of input parameters arise due to material properties, applied load and undetectable flaws. This paper describes a Probabilistic Fracture Mechanics(PFM) analysis based on Monte Carlo(MC) algorithms. Taking important parameters as probabilistic variables such as fracture toughness, crack growth rate and flaw shape, failure probability of major nuclear power plant components is archived as a results of MC simulation. For the verification of these analysis, a comparison study of the PFM analysis using other commercial code, mathematical method is carried out and a good agreement was observed between those results.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.21 no.3
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• pp.209-215
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• 2009

A new load surface method for reliability of caisson type breakwater was proposed. Linear functions for horizontal wave force and uplift force were estimated by using water level and wave height then they were applied to the reliability analysis of breakwater using first order reliability method(FORM). In the numerical example, sliding and overturning failure probability of caisson type breakwater were analyzed by using load surface and they were compared with those by Monte Carlo simulation.

• Journal of the Korean Society for Railway
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• v.7 no.4
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• pp.302-306
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• 2004

Many long railway tunnels without emergency evacuation system or ventilation system are under construction or in-use in Korea. In the case of tunnel-fire, many fatalities are occur in current condition. Current safety level is estimated in this study, for the efficient investment on safety. But so many uncertainties in major input parameters make the safety estimation difficult. In this study, probabilistic techniques are applied for the consideration of uncertainties in major input parameters. As results of this study, accident scenarios and survival ratio under tunnel fire accident are determined for various conditions.

• Economic and Environmental Geology
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• v.53 no.3
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• pp.245-258
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• 2020

In this study, a data-driven response surface method using the results acquired from the numerical simulation is developed to evaluate the potential storage capacity of groundwater due to the construction of a groundwater dam. The hydraulic conductivities of alluvium and basement rock, depth and slope of the channel are considered as the natural conditions of the location for groundwater dam construction. In particular, the probability models of the hydraulic conductivities and the various types of geometry of the channel are considered to ensure the reliability of the numerical simulation and the generality of the developed estimation model. As the results of multiple simulations, it can be seen that the hydraulic conductivity of basement rock and the depth of the channel greatly influence to the groundwater storage capacity. In contrast, the slope of the channel along the groundwater flow direction shows a relatively lower impact on the storage capacity. Based on the considered natural conditions and the corresponding numerical simulation results, the storage capacity estimation model is developed applying an artificial neural network as the nonlinear regression model for training. The developed estimation model shows a high correlation coefficient (>0.9) between the simulated and the estimated storage amount. This result indicates the superiority of the developed model in evaluating the storage capacity of the potential location for groundwater dam construction without the numerical simulation. Therefore, a more objective and efficient comparison for the storage capacity between the different potential locations can be possibly made based on the developed estimation model. In line with this, the proposed method can be an effective tool to assess the optimal location of groundwater dam construction across Korea.

• Journal of radiological science and technology
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• v.40 no.4
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• pp.605-611
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• 2017

The structure of the actual detector was computed using the code of the PENELOPE. Using the standard mixed sources (450, 1,000 ml), compare the effectiveness of each energy according to various densities and height of the PENELOPE computer simulation, and calculate the effectiveness of the various environmental specimens and apply them to various environmental specimens to determine the lower limit. The values obtained by the obtained value were obtained by applying the obtained efficiency to the actual environmental specimens and obtaining the lower limit values. The density correction factor is 1.155 g of the density correction factor of $0.4g/cm^3$ (59.54keV), 1.153 (661 keV), $1.06g/cm^3$ 1.064 (1,836.04keV), 1.03, and 1.033. It was confirmed that the radioactivity concentration of environmental samples decreased as the amount of specimen was measured increases, and the MDA value decreased as time measured increases.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.13 no.4
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• pp.295-300
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• 2015

The precise determination of the activity for each radionuclide in environmental samples requires the self-absorption correction factor. In this research, we derived the self-absorption correction factor for three p-type high purity germanium detectors using the Monte Carlo code MCNPX. These detectors have different characteristics such as crystal diameter, height and size of the core. We compared the calculated full-energy peak efficiency with the experimental value using a standard sample with $1g/m^3$ density and verified the modeling. We simulated the dependency of the full-energy peak efficiency on the 0.3, 0.6, 0.9, 1.0, 1.2 and $1.5g/m^3$ samples and obtained the corresponding self-absorption correction factor. The self-absorption correction factors calculated for the three detectors differ by less than 1% over most of the energy range and sample densities considered. This indicates that the self-absorption correction factors are independent of the crystal characteristics of HPGe detector.