• Journal of Mechanical Science and Technology
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• v.18 no.6
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• pp.933-945
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• 2004

In this paper, S (stochastic)-eigenvalue concept and its S-eigenvector for linear continuous-time systems with probabilistic uncertainties is proposed. The proposed concept is concerned with the perturbation of eigenvalues due to the probabilistic variable parameters in the dynamic model of a plant. S-eigenstructure assignment scheme via the Sylvester equation approach based on the S-eigenvalue concept is also proposed. The proposed design schemes are illustrated by numerical examples, and applied to the longitudinal dynamics of open-loop-unstable aircraft with possible uncertainties in aerodynamic and thrust effects as well as separate dynamic pressure. These results explicitly characterize how S-eigenvalues in the complex plane may impose stability on S-eigenstructure assignment.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.05a
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• pp.753-758
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• 2004

This study is to suggest a probabilistic design determining configurations of slider air bearings with the dimensional manufacturing tolerances of the ABS. The probabilistic design problem is formulated to minimize the variation in flying height from a target value while satisfying the desired probabilities keeping the pitch and roll angles within suitable range. The proposed approach first solves the deterministic optimization problem. Then, beginning with this solution, the RBDO is continued with the probabilistic constraints affected by the random variables with a fixed standard deviation in normal distribution. The RBDO results are directly compared with the values of the initial design and the results of the deterministic optimization, respectively. The reliability analyses are performed by the descriptive sampling (DS) to show the effectiveness and accuracy of the proposed approach. It is demonstrated that the proposed RBDO approach can efficiently obtain an optimum solution satisfying all the desired probabilistic constraints.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.8
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• pp.695-701
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• 2004

This study is to suggest a Probabilistic design determining configurations of slider air bearings with the dimensional manufacturing tolerances of the ABS. The probabilistic design problem is formulated to minimize the variation in flying height from a target value while satisfying the desired probabilities keeping the pitch and roll angles within a suitable range. The proposed approach first selves the deterministic optimization problem. Then, beginning with this solution, the RBDO is continued with the probabilistic constraints affected by the random variables with a fixed standard deviation in normal distribution. The RBDO results are directly compared with the values of the initial design and the results of the deterministic optimization, respectively. The reliability analyses are performed by the descriptive sampling (DS) to show the effectiveness and accuracy of the proposed approach. It is demonstrated that the Proposed RBDO approach can efficiently obtain an optimum solution satisfying all the desired probabilistic constraints.

• Journal of Aerospace System Engineering
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• v.7 no.4
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• pp.1-11
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• 2013

In this study, probabilistic reliability analysis was conducted for hybrid rocket performance using Monte-Carlo Simulation. For the accuracy, reliability analysis was performed with experimental data. To simplify the analysis process, the oxidizer was supplied with constant pressure, so that pressure variation with time can be eliminated. And time-space averaged regression rate model was used. The regression rate is obtained with a series of experiments. For reliability analysis of thrust, constant exponent of regression rate is assumed that has probabilistic character. So, the efficiency of characteristic velocity has also probabilistic values. As a results, probability distribution of the thrust is obtained by Monte-Carlo simulation using random samples of the input parameter and validated under the 95% confidence level.

• Journal of the Society of Naval Architects of Korea
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• v.41 no.3
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• pp.49-59
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• 2004

The paper describes the preliminary ship design method using deterministic approach and probabilistic approach. In deterministic approach, there are computational aspects to applying not only the integration concurrently of principal dimension decisions and hull form variations but also hydrostatic coefficients that applied to optimization iterative process. Therefore, this paper developed that actual design concept at the preliminary ship design more than sequential design which separated in principal dimension decisions and hull form variations. Furthermore, a probabilistic approach at the preliminary ship design is applied to efficiently solve design information uncertainty that compared to deterministic approach.

• Journal of the Korean Geotechnical Society
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• v.23 no.4
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• pp.125-132
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• 2007

The oedometer, radial CRS and Rowe cell tests, composite discharge capacity tests and smear effect tests are carried out to estimate the parameters for the reliability-based design of vertical drain method. Also the sensitivity analysis, the probabilistic and deterministic solutions of radial consolidation theory are presented. The result of probabilistic analysis was compared to that of deterministic analysis using the tested and estimated parameters. The results indicated that the drain spacing in the deterministic method is larger than that in the probabilistic method because the former does not consider the uncertainties in the geotechnical property. The divergence of two methods is dependent on the probability of achieving target degree of consolidation by a given time and the coefficient of variation (COV) of the coefficient of horizontal consolidation ($c_h$).

• Journal of The Korean Society of Agricultural Engineers
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• v.49 no.6
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• pp.93-101
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• 2007

In general, geotechnical properties have many uncertain aspects, thus probabilistic analysis have been used to consider these aspects. It is, however, quite difficult to select an appropriate target probability for a certain structure or construction process. In this study, minimum expected cost design method based on probabilistic analysis is suggested for design of vertical drains generally used to accelerate consolidation in soft clayey soils. A sensitivity analysis is performed to select the most important uncertain parameters for the design of vertical drains. Monte Carlo simulation is used in sensitivity analysis and probabilistic analysis. Total expected cost, defined as the sum of initial cost and expected additive cost, varies widely with variation of input parameters used in design of vertical drain systems. And probability of failure to get the minimum total expected cost varies under the different design conditions. A minimum value of total expected cost is suggested as a design value in this study. The proposed design concept is applicable to unit construction process because this approach is to consider the uncertainties using probabilistic analysis and uncertainties of geotechnical properties.

• Geomechanics and Engineering
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• v.23 no.1
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• pp.15-30
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• 2020

The probabilistic bearing capacity of a strip footing placed on the edge of a purely cohesive reinforced soil slope is computed by combining lower bound finite element limit analysis technique with random field method and Monte Carlo simulation technique. To simulate actual field condition, anisotropic random field model of undrained soil shear strength is generated by using the Cholesky-Decomposition method. With the inclusion of a single layer of reinforcement, dimensionless bearing capacity factor, N always increases in both deterministic and probabilistic analysis. As the coefficient of variation of the undrained soil shear strength increases, the mean N value in both unreinforced and reinforced slopes reduces for particular values of correlation length in horizontal and vertical directions. For smaller correlation lengths, the mean N value of unreinforced and reinforced slopes is always lower than the deterministic solutions. However, with the increment in the correlation lengths, this difference reduces and at a higher correlation length, both the deterministic and probabilistic mean values become almost equal. Providing reinforcement under footing subjected to eccentric load is found to be an efficient solution. However, both the deterministic and probabilistic bearing capacity for unreinforced and reinforced slopes reduces with the consideration of loading eccentricity.

• Journal of the Earthquake Engineering Society of Korea
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• v.18 no.2
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• pp.73-78
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• 2014

In this paper, the stochastic 1D site response analysis method using Monte Carlo simulation and considering thespatial variation of shear wave velocity profile isproposed. To consider thespatial variation of shear wave velocity profile for 1D site response analysis, the proposed method generates random shear wave velocity profiles representing the target site, and Monte Carlo simulation is used to calculate theprobability distribution of the site response analysis results such as thepeak ground acceleration. Through the field application, The applicability of the proposed method is verified through field application.

• The Journal of Engineering Geology
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• v.21 no.3
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• pp.247-257
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• 2011

In this study the infinite slope model, one of the physical landslide models has been suggested to evaluate the susceptibility of the landslide. However, applying the infinite slope model in regional study area can be difficult or impossible because of the difficulties in obtaining and processing of large spatial data sets. With limited site investigation data, uncertainties were inevitably involved with. Therefore, the probabilistic analysis method such as Monte Carlo simulation and the GIS based infinite slope stability model have been used to evaluate the probability of failure. The proposed approach has been applied to practical example. The study area in Boeun area been selected since the area has been experienced tremendous amount of landslide occurrence. The geometric characteristics of the slope and the mechanical properties of soils like to friction angle and cohesion were obtained. In addition, coefficient of variation (COV) values in the uncertain parameters were varied from 10% to 30% in order to evaluate the effect of the uncertainty. The analysis results showed that the probabilistic analysis method can reduce the effect of uncertainty involved in input parameters.