• Structural Engineering and Mechanics
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• v.38 no.4
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• pp.503-516
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• 2011

Uncertainty in concrete properties, including concrete modulus of elasticity and modulus of rupture, are predicted by developing a microstructural homogenization model. The homogenization model is developed by analyzing a concrete representative volume element (RVE) using the finite element (FE) method. The concrete RVE considers concrete as a three phase composite material including: cement paste, aggregate and interfacial transition zone (ITZ). The homogenization model allows for considering two sources of variability in concrete, randomly dispersed aggregates in the concrete matrix and uncertain mechanical properties of composite phases of concrete. Using the proposed homogenization technique, the uncertainty in concrete modulus of elasticity and modulus of rupture (described by numerical cumulative probability density function) are determined. Deflection uncertainty of reinforced concrete (RC) beams, propagated from uncertainties in concrete properties, is quantified using Monte Carlo (MC) simulation. Cracked plane frame analysis is used to account for tension stiffening in concrete. Concrete homogenization enables a unique opportunity to bridge the gap between concrete materials and structural modeling, which is necessary for realistic serviceability prediction.

• Computers and Concrete
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• v.17 no.1
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• pp.87-106
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• 2016

This paper deals with the reliability analysis of design formulations derived for predicting the punching shear capacity of FRP-reinforced two-way slabs. Firstly, a new design code formulation was derived by means of gene expression programming. This formulation differs from the existing ones as the slab length (L) was introduced in the equation. Next, the proposed formulation was tested for its generalization capability by a parametric study. Then, the stochastic analyses of derived and existing formulations were performed by Monte Carlo simulation. Finally, the reliability analyses of these equations were carried out based on the results of stochastic analysis and the ultimate state function of ASCE-7 and ACI-318 (2011). The results indicate that the prediction performance of new formulation is significantly higher as compared to available design equations and its reliability index is within acceptable limits.

• Proceedings of the KIEE Conference
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• 2006.07a
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• pp.3-4
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• 2006

본 논문에서는 계통의 불확실성을 고려한 확률론적인 방법으로 전력계통의 신뢰도를 평가한다. 발전기 3 state modeling 및 부하의 정규분포 곡선으로 확률론 신뢰도 평가 모델을 가정하였다. 그리하여 Adequacy 및 계통의 전압 및 송전선제약 조건 외에도, 소신호 안정도 항목을 추가하여 보다 동적인 측면에서의 신뢰도 평가가 이루어지도록 하였다. 이러한 평가 방법의 결과에 의하여 각 평가 항목간의 비율을 비교하였으며, 이를 통한 PSS의 설치 위치 선정의 근거를 마련하였다. 모의 방법은 Monte Carlo Simulation방법을 사용하였으며, WSCC 3기 9모선과 New England 10기 39모선을 모의계통으로 하였다.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.292-297
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• 2003

A stochastic approach has been presented for superplastic deformation of Ti-6AJ-4V alloy, and probability function are used to heterogeneous phase distributions. The experimentally observed spatial correlation function are developed, and microstructural evolutions together with superplastic deformation behavior have investigated by means of the probability function. The result have shown that the probability varies approximately linearly with separation with distance, and significant deformation enhanced probability changes during the deformation. The stress-strain behavior with the evolutions of probability function can be correctly predicted by the model. The finite clement implementation using Monte Carlo simulation associated with phase re-distributions shows that better agreement with experimental data of failure strain on the test specimen.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.32A no.3
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• pp.100-109
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• 1995

A new Hydrodynamic model for the high energy tail electrons(Tail Electron Hydrodynamic Model : TEHD) is developed using the moment method. The Monte Carlo method is applied to a $n^{+}-n^{-}-n^{+}$ device to calibrate the TEHD equations. the discretization method and numerical procedures are explained. New models for the impact ionization and injection into the gate oxide using the tail electron density are proposed. The simulated results of the impact ionization rate for a $n^{+}-n^{-}-n^{+}$ device and MOSFET devices, and the gate injection experiment are shown to give good agreement with the Monte Carlo simulation and the measurements.

• Journal of the Korean Statistical Society
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• v.31 no.1
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• pp.63-75
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• 2002

Most attempts at Bayesian analysis of neural networks involve hierarchical modeling. We believe that similar results can be obtained with simpler models that require less computational effort, as long as appropriate restrictions are placed on parameters in order to ensure propriety of posterior distributions. In particular, we adopt a model first introduced by Lee (1999) that utilizes an improper prior for all parameters. Straightforward Gibbs sampling is possible, with the exception of the bias parameters, which are embedded in nonlinear sigmoidal functions. In addition to the problems posed by nonlinearity, direct sampling from the posterior distributions of the bias parameters is compounded due to the duplication of hidden nodes, which is a source of multimodality. In this regard, we focus on sampling from the marginal posterior distribution of the bias parameters with Markov chain Monte Carlo methods that combine traditional Metropolis sampling with a slice sampler described by Neal (1997, 2001). The methods are illustrated with data examples that are largely confined to the analysis of nonparametric regression models.

• International Journal of Aeronautical and Space Sciences
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• v.12 no.4
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• pp.396-402
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• 2011

Aircraft combat survivability is an essential factor in the design of combat aircrafts that operate in an enemy air defense area. The combat aircrafts will be confronted with anti-aircraft artillery and/or surface-to-air missiles (SAM) from the ground, and their survivability can be divided into two categories: susceptibility and vulnerability. This article studies the prediction of susceptibility in the case of a one-on-one engagement between the combat aircraft and a surface-based threat. The weighted score method is suggested for the prediction of susceptibility parameters, and Monte Carlo simulations are carried out to draw qualitative interpretation of the susceptibility characteristics of combat aircraft systems, such as the F-16 C/D, and the hypersonic aircraft, which is under development in the United States, versus ground threat from the SAM SA-10.

• Journal of the Semiconductor & Display Technology
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• v.6 no.3
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• pp.25-33
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• 2007

A computationally efficient and accurate Monte Carlo (MC) simulator of electron beam lithography process, which is named SCNU-EBL, has been developed for semiconductor nanometer pattern design and fabrication. The simulator is composed of a MC simulation model of electron trajectory into solid targets, an Gaussian-beam exposure simulation model, and a development simulation model of photoresist using a string model. Especially for the trajectories of incident electrons into the solid targets, the inner-shell electron scattering of an target atom and its discrete energy loss with an incident electron is efficiently modeled for multi-layer resists and heterogeneous multi-layer targets. The simulator was newly applied to the development profile simulation of ZEP520 positive photoresist for NGL(Next-Generation Lithography). The simulation of ZEP520 for electron-beam nanolithography gave a reasonable agreement with the SEM experiments of ZEP520 photoresist.

• Proceedings of the Korea Water Resources Association Conference
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• 1988.07a
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• pp.85-92
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• 1988

A model for the transient one-dimensional moisture movement in the saturated-unsaturated zone using a finite difference method is developed. Hysteresis in the soil water retention is incorporated. The model considers layered geologic formations. Monte Carlo simulation, together with the nearest neighbor model is used. Outputs of the model include pressure head, water content, and the water table elevation. Two Monte Carlo simulations of 100 realizations each are made for a 12-day simulation period with different input values. The simulation results show that the S.D. of the outputs increases with an increase in the input, the S.D. of the log K$$. The model is applied to predict a long term water table fluctuation, and the predicted water table agress well with the observed one.

• Journal of the Korean Applied Science and Technology
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• v.33 no.1
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• pp.213-223
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• 2016

The validity of landfill gas models is an important problem considering that they are frequently used for landfill-site-related policy making and energy recovery planning. In this study, the Monte Carlo method was applied to an landfill gas generation model in order to enhance conformity. Results show that the relative mean deviation between measured data and modeled results (MD) decreased from 19.8% to 11.7% after applying the uncertainty range of Intergovernmental Panel on Climate Change (IPCC) to the methane-generation potential and reaction constants. Additionally, when let reaction constant adjust derived errors from all other modeling components, such as model logic, gauging waste, and measured methane data, MD decreased to 6.6% and the disparity in total methane generation quantity to 2.1%.