• Proceedings of the Computational Structural Engineering Institute Conference
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• 2011.04a
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• pp.665-668
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• 2011

철근콘크리트 구조물은 타설 후 시간이 경과함에 따라 물리적인 요인과 화학적인 요인으로 인하여 열화가 발생한다. 열화를 고려한 구조해석에서 모든 열화 관련 변수를 고려하는 것은 비효율적이다. 따라서 구조물의 거동과 밀접한 관련이 있는 중요열화변수를 정의하는 것이 필요하다. 본 연구에서는 철근콘크리트 전단벽의 경년열화 해석시 중요변수를 고려하기 위하여 민감도해석을 수행하였다. 해석결과에 의하면 재료의 경화와 관련한 변수들이 열화와 관련한 변수들보다 지진응답이 민감하게 나타났다. 해석모델의 낮은 철근비로 인하여 콘크리트의 탈락에 의한 지진응답의 변화보다 철근의 단면손실에 의한 지진응답의 변화가 크게 나타났다. 만약 원전과 같이 철근비가 높은 전단벽에서는 철근의 단면손실도 지진응답에 대한 중요변수가 될 수 있을 것으로 사료된다.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.1130-1135
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• 2003

The need to increase the reliability of a structural system has been significantly brought in the procedure of real designs to consider, for instance, the material properties or geometric dimensions that reveal a random or incompletely known nature. Reliability based design optimization of a real system now becomes an emerging technique to achieve reliability, robustness and safety of these problems. Finite element analysis program and the reliability analysis program are necessary to evaluate the responses and the probabilities of failure of the system, respectively. Moreover, integration of these programs is required during the procedure of reliability based design optimization. It is well known that reliability based design optimization can often have so many local minima that it cannot converge to the specified probability of failure. To overcome this problem, barrier function method in reliability based design optimization is suggested. To illustrate the proposed formulation, reliability based design optimization of a bracket is performed. AMV and FORM are employed for reliability analysis and their optimization results are compared based on the accuracy and efficiency.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2004.05a
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• pp.190-197
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• 2004

In order to consider statistical properties of probability variables used in the structural analysis, the conventional approach using the safety factor based on past experience usually estimated the safety of a structure. Also, the real structures could only be analyzed with the error in estimation of loads, material characters and the dimensions of the members. But the errors should be considered systematically in the structural analysis. In this paper, we estimated the probability of failure of the pressure vessel. And also, this paper presents sensitivity values of the random variable. Finally, we show that reliability index and probability of failure can present the tolerance limit of dimension of randam variables.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.5
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• pp.575-584
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• 2014

In this study, the NREL 5 MW wind turbine tower model was optimized according to the multi-body dynamics and reliability-based design. The mathematical model was defined as a link-joint system including dynamic characteristics derived from Timoshenko's beam theory. For the optimization problem, the sensitivities to variations in the tower thicknesses and inner and outer diameters were acquired and arranged in terms of safety and efficiency according to bending stress and buckling standards. An optimal design was calculated with the advanced first-order second moment method and used to define a finite element model for validation. The finite element model was simulated by static analysis. The relationship between the multi-body dynamic and finite element method throughout the process was investigated, and the optimal model, which had high endurance despite its low mass, was determined.

• Journal of the Earthquake Engineering Society of Korea
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• v.9 no.5 s.45
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• pp.1-10
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• 2005

This study proposes a fatigue reliability evaluation procedure for steel-composite high-speed railway bridge based on dynamic analysis and investigates the effectiveness of Tuned Mass Damper(TMD) in terms of the extension of fatigue life of the bridge. For the fatigue reliability evaluation, the limit state is determined using S-N curve and linear fatigue-damage accumulation. Dynamic analyses are peformed repeatedly to consider the uncertainties of train-velocity and damping ratio of the bridge. The distribution of random variables related to fatigue damage for the intended service life is then statistically estimated from analytical results. Finally, the fatigue reliability indices are obtained by means of the Advanced First-Order Second-Moment (AFOSM) method. Through numerical simulation of a steel-composite bridge of 40m span, the effectiveness of TMD on fatigue life of the bridge is examined and the results are presented.

• Journal of the Korean Geotechnical Society
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• v.23 no.12
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• pp.61-73
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• 2007

As a part of Load and Resistance Factor Design(LRFD) code development in Korea, in this paper an intensive reliability analysis was performed to evaluate reliability levels of the two static bearing capacity methods for driven steel pipe piles adopted in Korean Standards for Structure Foundations by the representative reliability methods of First Order Reliability Method(FORM) and Monte Carlo Simulation(MCS). The resistance bias factors for the two static design methods were evaluated by comparing the representative measured bearing capacities with the design values. In determination of the representative bearing capacities of driven steel pipe piles, the 58 data sets of static load tests and soil property tests were collected and analyzed. The static bearing capacity formula and the Meyerhof method using N values were applied to the calculation of the expected design bearing capacity of the piles. The two representative reliability methods(FORM, MCS) based computer programs were developed to facilitate the reliability analysis in this study. Mean Value First Order Second Moment(MVFOSM) approach that provides a simple closed-form solution and two advanced methods of FORM and MCS were used to conduct the intensive reliability analysis using the resistance bias factor statistics obtained, and the results were then compared. In addition, a parametric study was conducted to identify the sensibility and the influence of the random variables on the reliability analysis under consideration.

• Journal of the Korean Geotechnical Society
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• v.23 no.11
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• pp.109-117
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• 2007

Uncertainty is pervasive in rock slope stability analysis due to various reasons and subsequently it may cause serious rock slope failures. Therefore, the importance of uncertainty has been recognized and subsequently the probability theory has been used to quantify the uncertainty since 1980's. However, some uncertainties, due to incomplete information, cannot be handled satisfactorily in the probability theory and the fuzzy set theory is more appropriate for those uncertainties. In this study the random variable is considered as fuzzy number and the fuzzy set theory is employed in rock slope stability analysis. However, the previous fuzzy analysis employed the approximate method, which is first order second moment method and point estimate method. Since previous studies used only the representative values from membership function to evaluate the stability of rock slope, the approximated analysis results have been obtained in previous studies. Therefore, the Monte Carlo simulation technique is utilized to evaluate the probability of failure for rock slope in the current study. This overcomes the shortcomings of previous studies, which are employed vertex method. With Monte Carlo simulation technique, more complete analysis results can be secured in the proposed method. The proposed method has been applied to the practical example. According to the analysis results, the probabilities of failure obtained from the fuzzy Monte Carlo simulation coincide with the probabilities of failure from the probabilistic analysis.