• Proceedings of the Korean Reliability Society Conference
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• 2002.06a
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• pp.199-204
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• 2002

본 연구에서는 저압 증기 터빈블레이드의 안전성 확보를 위하여 작용응력 및 강도의 변동성을 고려한 확률론적 해석을 수행하였다. 정상상태에서 작용응력은 이론 및 유한요소해석에 의해서 얻을 수 있으며, 최대 von-Mises 응력은 215.4MPa이다. 회전굽힘 하중하에서의 피로한도는 응력비 R= -1에서 계단식 시험법을 이용하여 구하였으며, 이의 확률론적 특성에 가장 적합한 분포는 3 모수 와이블 분포이다. 그리고 신뢰성에 미치는 다양한 인자들의 영향은 영향계수(sensitivity factor)를 이용하여 정량적으로 평가하였다.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.26 no.1
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• pp.33-40
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• 2014

Reliability analysis of jacket type offshore wind turbine (OWT) support structure under extreme ocean environmental loads was performed. Limit state function (LSF) of OWF support structure is defined by using structural dynamic response at mud-line. Then, the dynamic response is expressed as the static response multiplied by dynamic response factor (DRF). Probabilistic distribution of DRF is found from response time history under design significant wave load. Band limited beta distribution is used for internal friction angle of ground soil. Wind load is obtained in the form of thrust force from commercial code called GH_Bladed and then, applied to tower hub as random load. In a numerical example, the response surface method (RSM) is used to express LSF of jacket type support structure for 5MW OWF. Reliability index is found using first order reliability method (FORM).

• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.926-939
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• 2022

The area of this study will cover the location-wise seismic response variation of an electrical cabinet in nuclear power point (NPP) based on classical reliability analysis. The location-based seismic ground motion (GM) selection is carried out with the help of probabilistic seismic hazard analysis using PSHRisktool, where the variation of reliability analysis can be understood from the relation between the reliability index and intensity measure. Two different approaches such as the first-order second moment method (FOSM) and Monte Carlo Simulation (MCS) are helped to evaluate and compare the reliability assessment of the cabinet. The cabinet is modeled with material uncertainty utilizing Steel01 as the material model and the fiber section modeling approach is considered to characterize the section's nonlinear reaction behavior. To verify the modal frequency, this study compares the FEM result with recorded data using Least-Squares Complex Exponential (LSCE) method from the impact hammer test. In spite of a few investigations, the main novelty of this study is to introduce the reader to check and compare the seismic reliability assessment variation in different seismic locations and for different earthquake levels. Alongside, the betterment can be found by comparing the result between two considered reliability estimation methods.

• Proceedings of the Korea Concrete Institute Conference
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• 2004.11a
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• pp.433-436
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• 2004

The safety of buildings is generally estimated by analyzing a plane frame ignoring a minor bending moment. In this paper, uncertainties of reinforced concrete shear wall subjected to a biaxial bending are considered. First, major parameters are selected from all parameters of general shear wall design to perform a reliability analysis in their practical ranges, means and standard derivations of selected design parameters for the reliability analysis are calculated by a data mining as a simulation method. The bi-section method is used to find inclined neutral axis and its limit state using MATLAB subjected to the concept on strength design method. The reliability index $\beta$ as a safety index is calculated based on AFOSM(Advanced First-Order Second Moment) method. Also, if target reliability index $\beta_T$ is decided by an engineer an amount of reinforcement can be calculated by subtracting the reliability index $\beta$ from the target reliability index $\beta_T$.

• Structural Engineering and Mechanics
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• v.45 no.5
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• pp.595-611
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• 2013

This paper aims to compare three collocation point methods associated with the odd order stochastic response surface method (SRSM) in a systematical and quantitative way. The SRSM with the Hermite polynomial chaos is briefly introduced first. Then, three collocation point methods, namely the point method, the root method and the without origin method underlying the odd order SRSMs are highlighted. Three examples are presented to demonstrate the accuracy and efficiency of the three methods. The results indicate that the condition that the Hermite polynomial information matrix evaluated at the collocation points has a full rank should be satisfied to yield reliability results with a sufficient accuracy. The point method and the without origin method are much more efficient than the root method, especially for the reliability problems involving a large number of random variables or requiring complex finite element analysis. The without origin method can also produce sufficiently accurate reliability results in comparison with the point and root methods. Therefore, the origin often used as a collocation point is not absolutely necessary. The odd order SRSMs with the point method and the without origin method are recommended for the reliability analysis due to their computational accuracy and efficiency. The order of SRSM has a significant influence on the results associated with the three collocation point methods. For normal random variables, the SRSM with an order equaling or exceeding the order of a performance function can produce reliability results with a sufficient accuracy. The order of SRSM should significantly exceed the order of the performance function involving strongly non-normal random variables.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.9 s.252
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• pp.1116-1123
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• 2006

In this study, the effective method for reliability estimation is proposed using tow-staged kriging metamodel and genetic algorithm. Kriging metamodel can be determined by appropriate sampling range and the number of sampling points. The first kriging metamodel is made based on the proposed sampling points. The advanced f'=rst order reliability method is applied to the first kriging metamodel to determine the reliability and most probable failure point(MPFP) approximately. Then, the second kriging metamodel is constructed using additional sampling points near the MPFP. These points are selected using genetic algorithm that have the maximum mean squared error. The Monte-Carlo simulation is applied to the second kriging metamodel to estimate the reliability. The proposed method is applied to numerical examples and the results are almost equal to the reference reliability.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.3
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• pp.18-25
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• 2005

Existing methods have performed the reliability analysis using nonlinear optimization techniques. This is mainly due to the fact that they directly apply Multidisciplinary Design Optimization(MDO) frameworks to the reliability analysis formulation. Accordingly, the reliability analysis and the Multidisciplinary Analysis(MDA) are tightly coupled in a single optimizer, which hampers utilizing the recursive and function-approximation based reliability analysis methods such as the Advanced First Order Reliability Method(AFORM). In order to utilize the efficient reliability analysis method under multidisciplinary analysis systems, we propose a new strategy named Sequential Approach on Reliability Analysis under Multidisciplinary analysis systems(SARAM). In this approach, the reliability analysis and the MDA are decomposed and arranged in a sequential manner, making a recursive loop. The efficiency of the SARAM method was verified using three illustrative examples taken from the literatures. Compared with existing methods, it showed the least number of subsystem analyses over other methods while maintaining accuracy.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.28 no.2
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• pp.92-100
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• 2016

Reliability analysis of tripod support structure for offshore wind turbine was performed. Extreme distribution function of peak response due to wind and wave loads was estimated by applying peak over threshold(POT) method. Then, stress based limit state function was defined by using maximum stress of support structure which was obtained by multiplying beam stress and concentration factor. The reliability analysis result was compared when maximum stress was calculated from shell element. Reliability index was evaluated using first order reliability method(FORM).

• Smart Structures and Systems
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• v.7 no.4
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• pp.263-274
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• 2011

A reliability-based slope stability assessment method considering fluctuations in the monitored matric suction was proposed for real-time identification of slope risk. The assessment model was based on the limit equilibrium model for infinite slope failure. The first-order reliability method (FORM) was adopted to calculate the probability of slope failure, and results of the model were compared with Monte-Carlo Simulation (MCS) results to validate the accuracy and efficiency of the model. The analysis shows that a model based on Advanced First-Order Reliability Method (AFORM) generates results that are in relatively good agreement with those of the MCS, using a relatively small number of function calls. The contribution of random variables to the slope reliability index was also examined using sensitivity analysis. The results of sensitivity analysis indicate that the effective cohesion c' is a significant variable at low values of mean matric suction, whereas matric suction ($u_a-u_w$) is the most influential factor at high mean suction values. Finally, the reliability indices of an unsaturated model soil slope, which was monitored by a wireless matric suction measurement system, were illustrated as 2D images using the suggested probabilistic model.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1991.04a
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• pp.34-42
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• 1991

This study is directed for the development of an efficient system-level Importance Sampling Technique for system reliability analysis of bridge structures Many methods have been proposed for structural reliability assessment purposes, such as the First-order Second-Moment Method, the Advanced Second-Moment Method, Computer Simulation, etc. The Importance Sampling Technique can be employed to obtain accurate estimates of the required probability with reasonable computation effort. Based on the observation and the results of application, it nay be concluded that Importance Sampling Method is a very effective tool for the system reliability analysis.