• Title/Summary/Keyword: 확률론적 설계법

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System Reliability-Based Design Optimization Using Performance Measure Approach (성능치 접근법을 이용한 시스템 신뢰도 기반 최적설계)

  • Kang, Soo-Chang;Koh, Hyun-Moo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.30 no.3A
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    • pp.193-200
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    • 2010
  • Structural design requires simultaneously to ensure safety by considering quantitatively uncertainties in the applied loadings, material properties and fabrication error and to maximize economical efficiency. As a solution, system reliability-based design optimization (SRBDO), which takes into consideration both uncertainties and economical efficiency, has been extensively researched and numerous attempts have been done to apply it to structural design. Contrary to conventional deterministic optimization, SRBDO involves the evaluation of component and system probabilistic constraints. However, because of the complicated algorithm for calculating component reliability indices and system reliability, excessive computational time is required when the large-scale finite element analysis is involved in evaluating the probabilistic constraints. Accordingly, an algorithm for SRBDO exhibiting improved stability and efficiency needs to be developed for the large-scale problems. In this study, a more stable and efficient SRBDO based on the performance measure approach (PMA) is developed. PMA shows good performance when it is applied to reliability-based design optimization (RBDO) which has only component probabilistic constraints. However, PMA could not be applied to SRBDO because PMA only calculates the probabilistic performance measure for limit state functions and does not evaluate the reliability indices. In order to overcome these difficulties, the decoupled algorithm is proposed where RBDO based on PMA is sequentially performed with updated target component reliability indices until the calculated system reliability index approaches the target system reliability index. Through a mathematical problem and ten-bar truss problem, the proposed method shows better convergence and efficiency than other approaches.

A Case Study on Quantifying Uncertainties of Geotechnical Random Variables (지반 확률변수의 불확실성 정량화에 관한 사례연구)

  • Han, Sang-Hyun;Yea, Geu-Guwen;Kim, Hong-Yeon
    • The Journal of Engineering Geology
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    • v.22 no.1
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    • pp.15-25
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    • 2012
  • Probabilistic design methods have been used as a design standard in Korea and abroad for achieving reasonable design by considering the statistical uncertainties of soil properties. In this study, the following techniques for reflecting geotechnical uncertainty are analyzed: quantification of the uncertainties of geotechnical random variables, and consideration of economic feasibility in design by minimizing the uncertainties related to the number of samples. To quantify the uncertainties, the techniques were applied to soil properties obtained from samples collected and tested in the field. The results showed an underestimation of the standard deviation by the 3-sigma approach in comparison with calculations using data from the samples. This finding indicates that economical design is possible in terms of probability. However, when compared with the Bayesian approach, which does not consider the number of samples, variability in the 3-sigma approach is underestimated for some variables. This finding also indicates a safety issue, whereas the number of samples based on the Bayesian approach showed the lowest variance. The variance of the probability density function showed a marked decrease with increasing number of samples, to converge at a certain level when the number exceeds 25. Of note, the estimation of values is more reliable for random variables having low variability, such as soil unit weight, and can be obtained with a small number of samples.

System Reliability Analysis of Midship Sections (선체 중앙 횡단면의 시스템 신뢰성해석)

  • Y.S. Yang;Y.S. Suh
    • Journal of the Society of Naval Architects of Korea
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    • v.30 no.1
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    • pp.115-124
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    • 1993
  • A structural system reliability analysis is studied for the safety assessment of midship section. Probabilistically dominant collapse modes are generated by Element Replacement Method and Incrimental Load Method. In order to avoid generating the same modes repeatedly, it is branched at final plastic hinge. Using first and second order bound methods, system failure probability of midship section is computed and compared with deterministic load factor method to show the usefulness of the proposed method.

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The Reliability-Based Probabilistic Structural Analysis for the Composite Tail Plane Structures (복합재 미익 구조의 신뢰성 기반 확률론적 구조해석)

  • Lee, Seok-Je;Kim, In-Gul
    • Journal of the Korea Institute of Military Science and Technology
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    • v.15 no.1
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    • pp.93-100
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    • 2012
  • In this paper, the deterministic optimal design for the tail plane made of composite materials is conducted under the deterministic loading condition and compared with that of the metallic materials. Next, the reliability analysis with five random variables such as loading and material properties of unidirectional prepreg is conducted to examine the probability of failure for the deterministic optimal design results. The MATLAB programing is used for reliability analysis combined with FEA S/W(COMSOL) for structural analysis. The laminated composite is assumed to the equivalent orthotropic material using classical laminated plate theory. The response surface methodology and importance sampling technique are adopted to reduce computational cost with satisfying the accuracy in reliability analysis. As a result, structural weight of composite materials is lighter than that of metals in deterministic optimal design. However, the probability of failure for the deterministic optimal design of the tail plane structures is too high to be neglected. The sensitivity of each variable is also estimated using probabilistic sensitivity analysis to figure out which variables are sensitive to failure. The computational cost is considerably reduced when response surface methodology and importance sampling technique are used. The study of the computationally inexpensive method for reliability-based design optimization will be necessary in further work.

A Stochastic Control for Nonlinear Systems under Random Disturbance Based on a Fluid Motion (유체운동에 의한 불규칙 가진을 받는 비선형계의 확률제어)

  • Oh, Soo-Young;Kim, Yong-Kwan;Cho, Lae-Kyoung;Choi, Young-Seob;Heo, Hoon
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2001.05a
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    • pp.892-896
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    • 2001
  • Investigation is performed on the stability of nonlinear system under turbulent fluid motion modelled as white noise random process, which is a preliminary result in the course of research on the characteristic and nonlinear control of the stochastic system. Adopted physical model is beam-type structure with tip-mass and main base mass. The governing equation is derived via F-P-K approach in stochastic sense. By means of Gaussian Closure method infinite dynamic moment equations due to system nonlinearity is closed to finite one. At the best of authors' knowledge, it is the first trial to design nonlinear controller by using of sliding mode technique in stochastic domain and control performance and effect in stochastic domain is studied.

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반응표면법과 Monte Carlo 모사를 이용한 불확실한 변동의 강건설계를 위한 확률적 민감도의 제안

  • 백석흠;이경영;조석수;주원식
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2004.05a
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    • pp.89-89
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    • 2004
  • 결정적인 알고리즘과 입력정보의 사용은 평가된 해석과 실제 시스템 값과의 차이로 잘못된 결론을 이끌지도 모른다. 실제 시스템은 대부분 각각의 입력 매개변수들(input parameters)과 관계된 넓은 공차 영역(tolerance band)을 가지고 있어서 입력정보로 하나의 단일한 값을 할당하는 것이 어렵다. 단일 입력에 대한 한가지 해는 변동의 이해 없이 제한된 값이라는 것을 인식할 필요가 있는데 대개 결정론적 설계는 형상과 관련된 치수변동, 항복강도나 부재의 밀도, 탄성계수와 같은 재료 물성치의 불확실성(uncertainty)과 시스템에 작용하는 하중의 변동 등을 직접 고려하지 않고 설계를 수행하기 때문에 수용할 수 있는 오차의 범위 안에서 시스템의 응답을 정확히 평가하기가 쉽지 않았다.(중략)

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Stochastic Fatigue Crack Propagation, SFCP (확률론적 피로균열진전)

  • 윤장호
    • Bulletin of the Society of Naval Architects of Korea
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    • v.30 no.3
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    • pp.23-27
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    • 1993
  • 현재까지 SFCP 해석법은 기초단계에 있으며, 아직도 정립된 방법이 없는 것이 사실이다. 따라서, 이 분야에는 많은 개선을 필요로 하고 있다. 이와 같은 개선은 이론적인 연구뿐만이 아니라, 실험적인 연구가 바탕이 되어야 라며, 동시에SFCP에 영향을 주는 초기균열의 변동성, 하중의 변동성 등을 정확한 모델링 방법에 대한 연구가 병행되어야 한다. 그리고 더 나아가서 실제 구 조물에서 피로파괴에 영향을 주는 중요한 요소인 잔류응력, 부식 등의 고려하는 방법에 관한 연구가 수행 되어져야 할 것이다. 또한, 지금까지의 연구가 주로 구조부재에 하나의 균열이 존 재한다는 가정을 내포하고 있는데, 실구조물에 적용하기 위해서는 여러개의 균열이 동시에 존 재하는 경우에 대한 연구와 균열이 성장하면서 합체(coalescence)하는 경우에 대한 연구도 수행 되어야 한다. 이와 같은 연구가 꾸준히 진행되어 소기의 성과를 거둠으로써, 구조물의 피로파괴 확률을 정확하게 추정할 수 있을 것이며, 이에 따라 합리적인 설계가 가능해질 것이다.

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Probabilistic Displacement Analysis Using Stochastic Finite Element Method (확률유한요소법을 이용한 확률적 변위분석)

  • 나상민;문현구
    • Tunnel and Underground Space
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    • v.13 no.5
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    • pp.397-402
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    • 2003
  • Generally it is likely that rock mass properties are expressed not by a mean value but by values with variation due to its characteristic uncertainty. This characteristic is one of the most important parts for the design of undergound structures, but yet to be fully examined. Stochastic finite element method (SFEM) is contrary to deterministic finite element method in its concept as the former has been developed in order to take the randomness of structural systems into account. Using SFEM, the response variability of structural system can be obtained and it leads probabilistic stability of structure to be analyzed. In this study, displacement response variability of circular opening with hydrostatic stress field are analyzed in terms of rock mass properties having a certain mean and a standard deviation using the SFEM. The analyzed response variability shows that the necessity of probabilistic stability analysis of underground structures using reliable mean value and standard deviation of deformation modulus.

Optimum Structural Design of Tankers Using Multi-objective Optimization Technique (다목적함수 최적화기법을 이용한 유조선의 최적구조설계)

  • 신상훈;장창두;송하철
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.15 no.4
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    • pp.591-598
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    • 2002
  • In the ship structural design, the material cost of hull weight and the overall cost of construction processes should be minimized considering safety and reliability. In the past, minimum weight design has been mainly focused on reducing material cost and increasing dead weight reflect the interests of a ship's owner. But, in the past experience, the minimum weight design has been inevitably lead to increasing the construction cost. Therefore, it is necessary that the designer of ship structure should consider both structural weight and construction cost. In this point of view, multi-objective optimization technique is proposed to design the ship structure in this study. According to the proposed algorithm, the results of optimization were compared to the structural design of actual VLCC(Very Large Crude Oil Carrier). Objective functions were weight cost and construction cost of VLCC, and ES(Evolution Strategies), one of the stochastic search methods, was used as an optimization solver. For the scantlings of members and the estimations of objectives, classification rule was adopted for the longitudinal members, and the direct calculation method, GSDM(Generalized Slope Deflection Method), lot the transverse members. To choose the most economical design point among the results of Pareto optimal set, RFR(Required Freight Rate) was evaluated for each Pareto point, and compared to actual ship.

Expansion of Sensitivity Analysis for Statistical Moments and Probability Constraints to Non-Normal Variables (비정규 분포에 대한 통계적 모멘트와 확률 제한조건의 민감도 해석)

  • Huh, Jae-Sung;Kwak, Byung-Man
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.34 no.11
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    • pp.1691-1696
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    • 2010
  • The efforts of reflecting the system's uncertainties in design step have been made and robust optimization or reliabilitybased design optimization are examples of the most famous methodologies. The statistical moments of a performance function and the constraints corresponding to probability conditions are involved in the formulation of these methodologies. Therefore, it is essential to effectively and accurately calculate them. The sensitivities of these methodologies have to be determined when nonlinear programming is utilized during the optimization process. The sensitivity of statistical moments and probability constraints is expressed in the integral form and limited to the normal random variable; we aim to expand the sensitivity formulation to nonnormal variables. Additional functional calculation will not be required when statistical moments and failure or satisfaction probabilities are already obtained at a design point. On the other hand, the accuracy of the sensitivity results could be worse than that of the moments because the target function is expressed as a product of the performance function and the explicit functions derived from probability density functions.