• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.6
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• pp.1043-1050
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• 2010

This paper examined the probabilistic load analysis for the tailplane during pitching maneuvering in the conceptual aircraft design phase. The flight load analysis based on the probabilistic distribution of design variables are compared with the results of the deterministic analysis. Two forms of variable distribution are used in this paper. One is standard normal distribution, the other distribution is calculated from the results of short-period longitudinal equation of aircraft motion. The influence of the distribution parameter on the probabilistic load analysis was investigated and the significant design variables that have an impact on the mean and variance of probabilistic load were identified. The comparison indicates that probabilistic load analysis provides more reliable probabilistic load distribution for the structural design than the traditional deterministic analysis.

• Geomechanics and Engineering
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• v.6 no.6
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• pp.545-560
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• 2014

For slope stability analysis, an alternative to the classical limit equilibrium method (LEM) of slices is the shear strength reduction method (SRM), which can be integrated into finite element analysis or finite difference analysis. Recently, probabilistic analysis of earth slopes has been very attractive because it is capable to take the soil uncertainty into account. However, the SRM is less commonly extended to probabilistic framework compared to a variety of probabilistic LEM analysis of earth slopes. To overcome some limitations that hinder the development of probabilistic SRM stability analysis, a new procedure based on recursive algorithm FORM with sensitivity analysis in the space of original variables is proposed. It can be used to deal with correlated non-normal variables subjected to implicit limit state surface. Using the proposed approach, a probabilistic finite element analysis of the stability of an existing earth dam is carried out in this paper.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.03a
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• pp.707-714
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• 2009

The design response spectrum generally used in Korea is decided by the site coefficients determined by deterministic methodology, while it is based on probabilistic seismic hazard analysis. The design response spectrum has to be made using probabilistic method which includes uncertainties of ground motions and ground properties for coincide with probabilistic methodology of seismic hazard analysis. In this study probabilistic site coefficients were developed, which were defined by the results of site response analysis using a set of ground motion that was compatible with present seismic hazard map. The design response spectrum defined by probabilistic seismic coefficients resulted in lower spectrum in long period area and larger spectrum in short period area. Also, the maximum spectral accelerations in site class D and site class E were lower than one in site class C while in the previous design response spectrum the maximum spectral acceleration increased from site class A to E.

• Smart Structures and Systems
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• v.10 no.2
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• pp.89-110
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• 2012

This study was intended to efficiently perform the probabilistic optimal safety assessment of steel cable-stayed bridges (SCS bridges) using stochastic finite element analysis (SFEA) and expected life-cycle cost (LCC) concept. To that end, advanced probabilistic finite element algorithm (APFEA) which enables to execute the static and dynamic SFEA considering aleatory uncertainties contained in random variable was developed. APFEA is the useful analytical means enabling to conduct the reliability assessment (RA) in a systematic way by considering the result of SFEA based on linearity and nonlinearity of before or after introducing initial tensile force. The appropriateness of APFEA was verified in such a way of comparing the result of SFEA and that of Monte Carlo Simulation (MCS). The probabilistic method was set taking into account of analytical parameters. The dynamic response characteristic by probabilistic method was evaluated using ASFEA, and RA was carried out using analysis results, thereby quantitatively calculating the probabilistic safety. The optimal design was determined based on the expected LCC according to the results of SFEA and RA of alternative designs. Moreover, given the potential epistemic uncertainty contained in safety index, failure probability and minimum LCC, the sensitivity analysis was conducted and as a result, a critical distribution phase was illustrated using a cumulative-percentile.

• Geomechanics and Engineering
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• v.24 no.4
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• pp.399-406
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• 2021

It is a key issue in the tunnel design to evaluate the stability of the excavation face. Two efficient analytical models in the context of the limit equilibrium method (LEM) and the limit analysis method (LAM) are used to carry out the deterministic calculations of the safety factor. The safety factor obtained by these two models agrees well with that provided by the numerical modelling by FLAC 3D, but consuming less time. A simple probabilistic approach based on the Mote-Carlo Simulation technique which can quickly calculate the probability distribution of the safety factor was used to perform the probabilistic analysis on the tunnel face stability. Both the cumulative probabilistic distribution and the probability density function in terms of the safety factor were obtained. The obtained results show the effectiveness of this probabilistic approach in the tunnel design.

• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.3
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• pp.75-84
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• 2013

The seepage quantity analysis of reservoir embankment is very important for assessment of embankment safety. However, the conventional analysis does not consider uncertainty of soil properties. Permeability is known that the coefficient of variation is larger than other soil properties and seepage quantity is highly dependent on the permeability of embankment. Therefore, probabilistic analysis should be carried out for seepage analysis. To designers, however, the probabilistic analysis is not an easy task. In this paper, the method that can be performed probabilistic analysis easily and efficiently through the numerical analysis based commercial program is proposed. Stochastic response surface method is used for approximate the limit state function and when estimating the coefficients, the moving least squares method is applied in order to reduce local error. The probabilistic analysis is performed by LHC-MCS through the response surface. This method was applied to two type (homogeneous, core zone) earth dams and permeability of embankment body and core are considered as random variables. As a result, seepage quantity was predicted effectively by response surface and probabilistic analysis could be successfully implemented.

• Magazine of the Korean Society of Agricultural Engineers
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• v.32 no.E
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• pp.59-66
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• 1990

Abstract The formulation of the probabilistic finite element method was briefly reviewed. The method was implemented into a computer program for frame analysis which has the same analogy as finite element analysis. Another program for Monte Carlo simulation of finite element analysis was written. Two sample structures were assumed and analized. The characteristics of the second moment statistics obtained by the probabilistic finite element method was examined through numerical studies. The applicability and limitation of the method were also evaluated in comparison with the data generated by Monte Carlo simulation.

• Proceedings of the Korea Concrete Institute Conference
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• 2006.05b
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• pp.181-184
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• 2006

Traditional durability analysis is not possible to provide a controlled durability and long-term performance of concrete structures. Recently, research works have shown that probabilistic approach based on the theory of structural reliability, would be very valuable for durability analysis. In this study, the probabilistic durability analysis based on a Monte Carlo Simulation was carried out using sample data selected from detailed field investigation. The probabilistic properties of some design variables, such as diffusion coefficients of concrete and surface chloride concentration, were newly determined using some experimental data. By applying a probabilistic durability analysis to an integral structural design, the durability performance of concrete structures would be remarkably improved.

• Journal of The Korean Society of Agricultural Engineers
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• v.56 no.1
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• pp.11-20
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• 2014

Many classification studies for the community of densely-connected nodes are limited to the comprehensive analysis for detecting the communities in probabilistic networks with nodes and edge of the probabilistic distribution because of the difficulties of the probabilistic operation. This study aims to use convolution method for operating nodes and edge of probabilistic distribution. For the probabilistic hierarchy network with nodes and edges of the probabilistic distribution, the model of this study detects the communities of nodes to make the new probabilistic distribution with two distribution. The results of our model was verified through comparing with Monte-carlo Simulation and other community-detecting methods.

• Journal of KIISE
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• v.41 no.9
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• pp.642-651
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• 2014

This paper proposes three probabilistic models for syllable-based Korean morphological analysis, and presents the performance of proposed probabilistic models. Probabilities for the models are acquired from POS-tagged corpus. The result of 10-fold cross-validation experiments shows that 98.3% answer inclusion rate is achieved when trained with Sejong POS-tagged corpus of 10 million eojeols. In our models, POS tags are assigned to each syllable before spelling recovery and morpheme generation, which enables more efficient morphological analysis than the previous probabilistic models where spelling recovery is performed at the first stage. This efficiency gains the speed-up of morphological analysis. Experiments show that morphological analysis is performed at the rate of 147K eojeols per second, which is almost 174 times faster than the previous probabilistic models for Korean morphology.