• Structural Engineering and Mechanics
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• v.32 no.1
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• pp.167-178
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• 2009

Initial imperfections, such as initial deflection or remaining stress, cause deterioration of buckling strength of structures. The Koiter imperfection sensitivity law has been extended to describe the mechanism of reduction for structures. The extension is twofold: (1) a number of imperfections are considered, and (2) the second order (minor) imperfections are implemented, in addition to the first order (major) imperfections considered in the Koiter law. Yet, in reality, the variation of external loads is dominant over that of imperfection. In this research, probabilistic evaluation of buckling loads against external loads subjected to probabilistic variation is conducted by extending the concept of imperfection sensitivity. A truss arch subjected to dead and live loads is considered as a numerical example. The mechanism of probabilistic variation of buckling strength of this arch is described by the proposed method, and its reliability is evaluated.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.11 s.254
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• pp.1417-1424
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• 2006

In order to evaluate variation of fatigue life of mechanical components including engineering plastics, it is important to estimate probabilistic strain-life curves to accurately define the variation of fatigue characteristics. This paper intends to provide new assessment of P-$\varepsilon$-N (probabilistic strain-life curves) for considering the variation of fatigue characteristics in polyacetal. The fatigue strain controlled tests were conducted under constant 50% humidity and room temperature condition by a universal testing machine at strain ratio, R=0. A practical procedure is introduced to evaluate probabilistic strain-life curves. Three probabilistic distributions were used for generating P-$\varepsilon$-N curves such as normal, 2-parameter and 3-parameter Weibull. In this study, 3-parameter Weibull distribution was found to be most appropriate among assumed distributions when the probability distributions of the fatigue characteristic were examined using chi-square and Kolmogorov-Smirnov test. The more appropriate P-$\varepsilon$-N curves for these materials are generated by the proposed method considering 3-parameter Weibull distribution.

• Computers and Concrete
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• v.19 no.3
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• pp.305-313
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• 2017

A robust finite element based reinforced concrete bridge deck corrosion initiation model is applied for time-dependent probabilistic sensitivity analysis. The model is focused on uncertainties in the governing parameters that include variation of high performance concrete (HPC) diffusion coefficients, concrete cover depth, surface chloride concentration, holidays in reinforcements, coatings and critical chloride threshold level in several steel reinforcements. The corrosion initiation risk is expressed in the form of probability over intended life span of the bridge deck. Conducted study shows the time-dependent sensitivity analysis to evaluate the significance of governing parameters on chloride ingress rate, various steel reinforcement protection and the corrosion initiation likelihood. Results from this probabilistic analysis provide better insight into the effect of input parameters variation on the estimate of the corrosion initiation risk for the design of concrete structures in harsh chloride environments.

• Journal of the Korean Geotechnical Society
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• v.22 no.11
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• pp.101-111
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• 2006

Slope stability analysis is a geotechnical engineering problem characterized by many sources of uncertainty. Some of them are connected to the variability of soil properties involved in the analysis. In this paper, a numerical procedure of probabilistic analysis of slope stability is presented based on Spencer's method of slices. The deterministic analysis is extended to a probabilistic approach that accounts fur the uncertainties and spatial variation of the soil parameters. The procedure is based on the first-order reliability method to compute the Hasofer-Lind reliability index and Monte-Carlo Simulation. A probabilistic stability assessment was performed to obtain the variation of failure probability with the variation of soil parameters in homogeneous and layered slopes as an example. The examples give insight into the application of uncertainty treatment to the slope stability and show the impact of the spatial variability of soil properties on the outcome of a probabilistic assessment.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.1
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• pp.63-69
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• 2015

The primary aim of this paper is to evaluate the probabilistic fatigue crack propagation models using the residual of a random variable and to present the probabilistic model fit for the probabilistic fatigue crack growth behavior in Mg-Al-Zn alloys under maximum load conditions. The models used in this study were prepared by applying a random variable to empirical fatigue crack propagation models such as the Paris-Erdogan model, Walker model, Forman model, and modified Forman model. It was verified that the good models for describing the stochastic variation of the fatigue crack propagation behavior in Mg-Al-Zn alloys under maximum load conditions were the 'probabilistic Paris-Erdogan model' and 'probabilistic Walker model'. The influence of the maximum load conditions on the stochastic variation of fatigue crack growth is also considered.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1991.10a
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• pp.57-62
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• 1991

For the purpose of developing the method for efficiently calculating the design sensitivity and the reliability for the complicated structure such as ship structure, the probabilistic finite element method is introduced to formulate the deterministic design sensitivity analysis method and incorporated with the second moment reliability methods such as MVFOSM, AFOSM and SORM. Also, the probabilistic design sensitivity analysis needed in the reliability-based design is performed. The reliability analysis is carried out for the initial yielding failure, in which the derivative derived in the deterministic desin sensitivity is used. The present PFEM-based reliability method shows good agreement with Monte Carlo method in terms with the variance of response and the associated probability of failure even at the first or first few iteration steps. The probabilistic design sensitivity analysis evaluates explicitly the contribution of each random variable to probability of failure. Further, the reliability index variation can be easily predicted by the variation of the mean and the variance of the random variables.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.34 no.2
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• pp.41-48
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• 2018

Carbonation is one of the major detrimental factors to the reinforced concrete structures owing to penetration of atmospheric CO2 through the micro pores, thereby it reduces the durability of the concrete. The maintenance periods and cost for concrete according to the coefficient variation of different finishing materials is documented in literature. However, it is required to carry out the systematic and well planned studies. Therefore, keeping them in mind, surface repair was carried out to the carbonated concrete and the maintenance cost was calculated to measure the durability life after repair with different variable. The deterministic and probabilistic methods were applied for durability and repair cost of the concrete. In the existing deterministic model, the cost of repair materials increases significantly when the concrete structure reaches its service life. In present study using a stochastic model, the maintenance period and cost was evaluated. According to obtained results, there was no significant difference in the number of maintenance of the coefficient variation. The initial durability has a great influence on the maintenance time and cost of the structure. Unlike the deterministic model, the probabilistic cost estimating model reduces the number of maintenance to the target service life expectancy.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.7-12
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• 2003

In this paper, S(stochastic)-eigenvalue concept and its S-eigenvector for linear continuous-time systems with probabilistic uncertainties are 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 scheme is applied to the longitudinal dynamics of open-loop-unstable aircraft with possible uncertainties in aerodynamic and thrust effects as well as separate dynamic pressure.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.4
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• pp.700-707
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• 2009

The application of renewable energy in electric power systems is growing rapidly in order to make provision for the inequality of the climate, the dwindling supplies of coal, oil and natural gas and a further rise in oil prices. Solar cell generators(SCG) is one of the fastest growing renewable energy. This paper presents a methodology on probabilistic production cost simulation of a power system including SCGs. The generated power by SCGs is variable due to the random variation of solar radiation. In order to solve this problem, the SCGs is modeled as multi-state operational model in this paper. Probabilistic production cost of a power system can be calculated by proposed method considering SCGs with multi-state. The results show that the impacts of SCGs added to a power system can be analyzed in view point of production cost using the proposed method.