• Journal of the Korean Magnetics Society
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• v.26 no.3
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• pp.81-85
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• 2016

This paper introduces a performance integration method to predict variation characteristic of a performance function of electromagnetic machines or devices due to manufacturing tolerances. A normalized performance function space and a hybrid mean value technique are adapted to effectively predict mean and variance, which can identify probabilistic distribution of the performance function. To verify the effectiveness and accuracy of the proposed method, a mathematical problem and a loudspeaker model are tested, and numerical results are compared with those of existing methods such as Monte Carlo simulation and univariate dimension reduction method.

• New & Renewable Energy
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• v.17 no.1
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• pp.40-49
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• 2021

In this study, the optical properties, heat transfer capabilities and chemical reaction performance of a methane thermal decomposition reactor using solar heat as a heat source were numerically analyzed on the basis of the cavity shape. The optical properties were analyzed using TracePro, a Monte Carlo ray tracing-based program, and the heat transfer analysis was performed using Fluent, a CFD program. An indirect heating tubular reactor was rotated at a constant speed to prevent damage by the heat source in the solar furnace. The inside of the reactor was filled with a porous catalyst for methane decomposition, and the outside was insulated to reduce heat loss. The performance of the reactor, based on cavity shape, was calculated when solar heat was concentrated on the reactor surface and methane was supplied into the reactor in an environment with a solar irradiance of 700 W/㎡, a wind speed of 1 m/s, and an outdoor temperature of 25℃. Thus, it was confirmed that the heat loss of the full-cavity model decreased to 13% and the methane conversion rate increased by 33.5% when compared to the semi-cavity model.

• Smart Structures and Systems
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• v.14 no.5
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• pp.847-867
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• 2014

There are continuous efforts to mitigate structural losses from earthquakes and manage risk through seismic risk assessment; seismic fragility curves are widely accepted as an essential tool of such efforts. Seismic fragility curves can be classified into four groups based on how they are derived: empirical, judgmental, analytical, and hybrid. Analytical fragility curves are the most widely used and can be further categorized into two subgroups, depending on whether an analytical function or simulation method is used. Although both methods have shown decent performances for many seismic fragility problems, they often oversimplify the given problems in reliability or structural analyses owing to their built-in assumptions. In this paper, a new method is proposed for the development of seismic fragility curves. Integration with sophisticated software packages for reliability analysis (FERUM) and structural analysis (ZEUS-NL) allows the new method to obtain more accurate seismic fragility curves for less computational cost. Because the proposed method performs reliability analysis using the first-order reliability method, it provides component probabilities as well as useful byproducts and allows further fragility analysis at the system level. The new method was applied to a numerical example of a 2D frame structure, and the results were compared with those by Monte Carlo simulation. The method was found to generate seismic fragility curves more accurately and efficiently. Also, the effect of system reliability analysis on the development of seismic fragility curves was investigated using the given numerical example and its necessity was discussed.

• Structural Engineering and Mechanics
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• v.64 no.4
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• pp.413-426
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• 2017

Probabilistic methods are used in engineering where a computational model contains random variables. The proposed method under development: Direct Optimized Probabilistic Calculation (DOProC) is highly efficient in terms of computation time and solution accuracy and is mostly faster than in case of other standard probabilistic methods. The novelty of the DOProC lies in an optimized numerical integration that easily handles both correlated and statistically independent random variables and does not require any simulation or approximation technique. DOProC is demonstrated by a collection of deliberately selected simple examples (i) to illustrate the efficiency of individual optimization levels and (ii) to verify it against other highly regarded probabilistic methods (e.g., Monte Carlo). Efficiency and other benefits of the proposed method are grounded on a comparative case study carried out using both the DOProC and MC techniques. The algorithm has been implemented in mentioned software applications, and has been used effectively several times in solving probabilistic tasks and in probabilistic reliability assessment of structures. The article summarizes the principles of this method and demonstrates its basic possibilities on simple examples. The paper presents unpublished details of probabilistic computations based on this method, including a reliability assessment, which provides the user with the probability of failure affected by statistically dependent input random variables. The study also mentions the potential of the optimization procedures under development, including an analysis of their effectiveness on the example of the reliability assessment of a slender column.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.3
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• pp.59-67
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• 1993

The variations of the natural frequencies and the peak response acceleration at the top of prestressed concrete reactor building due to random variability and/or model uncertainty of structural parameters are studied. The results may be used as essential input parameters in seismic probabilistic risk assessment or seismic margin assessment of the reactor building. The sensitivity test of each structural parameter is first performed to determine the most influential parameter upon the natural frequency of structure model. Then Monte Carlo simulation technique is applied to evaluate the effect of parameter variation on the natural frequencies and the peak response acceleration. The acceleration time history is obtained by direct integration scheme. As the study results, it is found that the fundamental natural frequency and the peak response acceleration at the top of the building are most strongly affected by Young's modulus among the structural parameters, in which the value of mean plus one standard deviation obtained by probabilistic approach deviates up to about (+)12% from the result of deterministic method. Considering the uncertainty of flexural rigidity, the structural responses vary in range of (-)4%~(+)14%.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.10
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• pp.10-20
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• 2003

In this study, the effective properties were numerically calculated for laminated plain weave textile composites with arbitrary s tacking orientation angles. A single-field macroelement with modified sub-domain integration was used in the analysis to reduce computer resource requirement while efficiently accounting for the internal microstructure. A sample calculation procedure based on the Monte Carlo method was employed to consider the random shift between the layers. Results showed that a significant deviation occurred when the orientation angles were near 0 deg for extensional modulus and Poisson's ratio and 45 deg for the shear modulus. It was also found that the average properties calculated by the 2-layer numerical specimen had large differences compared to the CLT results, which indicated that a caution must be needed when designig of thin plain weave composite structures.

• Advances in aircraft and spacecraft science
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• v.3 no.4
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• pp.471-502
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• 2016

This paper presents the dynamic instability analysis of un-damped elastically supported piezoelectric functionally graded (FG) beams subjected to in-plane static and dynamic periodic thermomechanical loadings with uncertain system properties. The elastic foundation model is assumed as one parameter Pasternak foundation with Winkler cubic nonlinearity. The piezoelectric FG beam is subjected to non-uniform temperature distribution with temperature dependent material properties. The Young's modulus and Poison's ratio of ceramic, metal and piezoelectric, density of respective ceramic and metal, volume fraction exponent and foundation parameters are taken as uncertain system properties. The basic nonlinear formulation of the beam is based on higher order shear deformation theory (HSDT) with von-Karman strain kinematics. The governing deterministic static and dynamic random instability equation and regions is solved by Bolotin's approach with Newmark's time integration method combined with first order perturbation technique (FOPT). Typical numerical results in terms of the mean and standard deviation of dynamic instability analysis are presented to examine the effect of slenderness ratios, volume fraction exponents, foundation parameters, amplitude ratios, temperature increments and position of piezoelectric layers by changing the random system properties. The correctness of the present stochastic model is examined by comparing the results with direct Monte Caro simulation (MCS).

• Nuclear Engineering and Technology
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• v.50 no.5
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• pp.673-682
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• 2018

One of the most widely used methods to estimate core damage during a nuclear power plant accident is containment radiation measurement. The evolution of severe accidents is extremely complex, leading to uncertainty in the containment dose rate (CDR). Therefore, it is difficult to accurately determine core damage. This study proposes to conduct uncertainty analysis of CDR for core damage assessment. First, based on source term estimation, the Monte Carlo (MC) and point-kernel integration methods were used to estimate the probability density function of the CDR under different extents of core damage in accident scenarios with late containment failure. Second, the results were verified by comparing the results of both methods. The point-kernel integration method results were more dispersed than the MC results, and the MC method was used for both quantitative and qualitative analyses. Quantitative analysis indicated a linear relationship, rather than the expected proportional relationship, between the CDR and core damage fraction. The CDR distribution obeyed a logarithmic normal distribution in accidents with a small break in containment, but not in accidents with a large break in containment. A possible application of our analysis is a real-time core damage estimation program based on the CDR.

• Journal of applied mathematics & informatics
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• v.17 no.1_2_3
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• pp.615-622
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• 2005

In this paper, we discuss the average case errors of some numerical quadratures, namely Trapezoidal and Simpson's, in the numerical integration problem. Our integrands are r-fold Wiener functions from the interval [0,1] and only at finite number of points the function values are evaluated. We study average case errors of these quadratures theoretically and then compare it with our practical (a posteriori) researches. Monte-Carlo simulation is used to perform these empirical researches. Finally we empirically compute the error bounds of studied quadratures for the higher degrees of Wiener functions.

• Communications for Statistical Applications and Methods
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• v.19 no.3
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• pp.495-500
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• 2012

We consider a Bayesian test of independence in a two-way contingency table that has some zero cells. To do this, we take a three-stage hierarchical Bayesian model under each hypothesis. For prior, we use Dirichlet density to model the marginal cell and each cell probabilities. Our method does not require complicated computation such as a Metropolis-Hastings algorithm to draw samples from each posterior density of parameters. We draw samples using a Gibbs sampler with a grid method. For complicated posterior formulas, we apply the Monte-Carlo integration and the sampling important resampling algorithm. We compare the values of the Bayes factor with the results of a chi-square test and the likelihood ratio test.