• 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.

• Steel and Composite Structures
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• v.9 no.6
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• pp.499-518
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• 2009

The present paper investigates the stochastic seismic responses of steel structure systems with Partially Restrained (PR) connections by using Perturbation based Stochastic Finite Element (PSFEM) method. A stiffness matrix formulation of steel systems with PR connections and PSFEM and MCS formulations of structural systems are given. Based on the formulations, a computer program in FORTRAN language has been developed, and stochastic seismic analyses of steel frame and bridge systems have been performed for different types of connections. The connection parameters, material and geometrical properties are assumed to be random variables in the analyses. The Kocaeli earthquake occurred in 1999 is considered as a ground motion. The connection parameters, material and geometrical properties are considered to be random variables. The efficiency and accuracy of the proposed SFEM algorithm are validated by comparison with results of Monte Carlo simulation (MCS) method.

• Journal of Magnetics
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• v.19 no.3
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• pp.266-272
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• 2014

In this paper, we suggest reliability as a metric to evaluate the robustness of a design for the optimal design of electromagnetic devices, with respect to constraints under the uncertainties in design variables. For fast numerical efficiency, we applied the sensitivity-assisted Monte Carlo simulation (S-MCS) method to perform reliability calculation. Furthermore, we incorporated the S-MCS with single-objective and multi-objective particle swarm optimization algorithms to achieve reliability-based optimal designs, undertaking probabilistic constraint and multi-objective optimization approaches, respectively. We validated the performance of the developed optimization algorithms through application to the optimal design of a superconducting magnetic energy storage system.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.683-686
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• 2008

Flood damage has been increased due to the abnormal climate and extreme rainfall. So, quantitative and qualitative hydrologic data should be improved in oder to enhance accuracy of hydrologic forecast. However, research regarding hydrologic data have not been thorough enough. Therefore, in this study, monte carlo simulation was applied to rainfall runoff model to improve the reliability of runoff analysis and risk analysis. Rainfall-Stage-Discharge curve was developed as a consequence of MCS and it is possible to get correct rating curve for high water level.

• Journal of Internet Computing and Services
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• v.25 no.2
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• pp.93-99
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• 2024

In this paper, we derive the Partial Differential Bond Price Equation (PDBPE) by using Ito's Lemma to determine the pricing of bond on term-structure of interest rate (TSIR) model with jump. From PDBPE, the Maclaurin series (MS) and the moment-generating function (MGF) for the exponential function are used to obtain a numerical solution (NS) of the bond prices. And an algorithm for determining bond prices using Monte Carlo Simulation (MCS) techniques is proposed, and the pricing of bond is determined through the simulation process. Comparing the results of the implementation of the above two pricing methods, the relative error (RE) is obtained, which means the ratio of NS and MCS. From the results, we can confirm that the RE is less than around 2.2%, which means that the pricing of bond can be predicted very accurately using the proposed algorithms as well as numerical analysis. Moreover, it was confirmed that the bond price obtained using the MS has a relatively smaller error than the pricing of bond obtained by using the MGF.

• Journal of Korea Water Resources Association
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• v.33 no.1
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• pp.15-30
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• 2000

This study is to develop the applied method of reliability analysis to present risk - initial water level relationship in the small reservoir. To determine the reliability, the grasping of uncertainty sources is prerequisited and performance function is formulated. Reliability analysis method is a statistical method and the basic procedure of risk evaluation for overtopping of reservoir is as follows. 1. Define the risk criterion and performance function for the overtopping. 2. Determine the uncertainties of all the variables in the performance function. 3. Perform the risk analysis with suitable risk calculation method. Reliability analysis method such as Monte Carlo simulation(MCS) method and mean value first order second moment(MVFOSM) method are used to calculate the risk for reservoir. Finally, risk - initial water level relationship is established according to return period and it is useful for reservoir operation and safety assessment.ssment.

• Journal of Aerospace System Engineering
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• v.12 no.3
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• pp.53-57
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• 2018

The Monte Carlo simulation (MCS) method and the Guide to the Expression of Uncertainty in Measurement (GUM) are the most widely used approaches for uncertainty estimation. In this paper, MCS and GUM were used to estimate the confidence of MOI measurement equipment developed in-house. According to the results, the GUM estimated uncertainty was slightly underestimated compared to the MCS method. This difference is due to the approximation used by GUM. MOI uncertainties estimated by both methods were less than 1% of the estimate, which shows the high measurement reliability of the developed MOI measurement system.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.14 no.2
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• pp.169-174
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• 2001

The electron transport coefficients(the electron drift velocity, W, and the longitudinal and transverse diffusion coefficient, D$_{L}$ and D$_{T}$) in SiH$_4$-Ar mixtures containing 0.5% and 5.0% monosilane were calculated over the E/N range from 0.01 to 300 Td and over the gas pressure range 0.5, 1.0 and 1.5 Torr by the time-of-flight(TOF) method of the Boltzmann equation(BE.) and Monte-Carlo simulation(MCS). The electron energy distribution function in each SiH$_4$-Ar mixtures at E/N=10 Td and L=0.2 cm, which in equilibrium region in the mean electron enregy were compared.red.

• 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.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.55 no.2
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• pp.57-61
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• 2006

This paper calculates and gives the analysis of mean energy in pure $SiH_4,\;Ar-SiH_4$ mixture gases ($SiH_4-0.5[%],\;5[%]$) over the range of $E/N =0.01{\sim}300[Td]$, p = 0.1, 1, 5.0 [Torr] by Monte Carlo the Backward prolongation method of the Boltzmann equation using computer simulation without using expensive equipment. The results have been obtained by using the electron collision cross sections by TOF, PT, SST sampling, compared with the experimental data determined by the other author. It also proved the reliability of the electron collision cross sections and shows the practical values of computer simulation. The calculations of electron swarm parameters require the knowledge of several collision cross-sections of electron beam. Thus, published momentum transfer, ionization, vibration, attachment, electronic excitation, and dissociation cross-sections of electrons for $SiH_4$ and Ar, were used. The differences of the transport coefficients of electrons in $SiH_4$, mixtures of $SiH_4$ and Ar, have been explained by the deduced energy distribution functions for electrons and the complete collision cross-sections for electrons. A two-term approximation of the Boltzmann equation analysis and Monte Carlo simulation have been used to study electron transport coefficients.