• 한국생산제조학회지
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• 제19권4호
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• pp.529-538
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• 2010

This paper presents a reliability-based topology optimization (RBTO) based on bidirectional evolutionary structural optimization (BESO). In design of a structure, uncertain conditions such as material property, operational load and dimensional variation should be considered. Deterministic topology optimization (DTO) is performed without considering the uncertainties related to the design variables. However, the RBTO can consider the uncertainty variables because it can deal with the probabilistic constraints. The reliability index approach (RIA) and the performance measure approach (PMA) are adopted to evaluate the probabilistic constraints in this study. In order to apply the BESO to the RBTO, sensitivity number for each element is defined as the change in the reliability index of the structure due to removal of each element. Smoothing scheme is also used to eliminate checkerboard patterns in topology optimization. The limit state indicates the margin of safety between the resistance (constraints) and the load of structures. The limit State function expresses to evaluate reliability index from finite element analysis. Numerical examples are presented to compare each optimal topology obtained from RBTO and DTO each other. It is verified that the RBTO based on BESO can be effectively performed from the results.

• 한국전산구조공학회논문집
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• 제23권1호
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• pp.37-43
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• 2010

본 논문에서는 선형 구조물에 대해 성능함수법을 이용하여 신뢰성기반 위상 최적설계 기법을 개발하였다. 구조물을 라이즈너-민들린(Ressiner-Mindlin) 판 요소로 분할하였으며, 각 요소의 재료 물성치를 설계변수로 사용하였다. 설계변수와 임의변수의 효율적인 설계민감도를 구하기 위하여 연속체 역학에 기초한 해석기법 중 보조변수법(Adjont variable method)을 사용하였다. 또한 확률론적 제약조건을 평가하기 위해서 성능함수법(Performance measure approach)을 사용하였으며 변위 제약조건을 두어 위상 최적설계 문제를 구성하였다. 이 때 재료 물성치와 하중을 불확실 변수로 고려하였으며 수치적 예제를 통하여 본 논문에서 제안한 최적설계 방법론을 기존의 결정론적 방법, 안전계수법(Safety factor approach), 최악조건법(Worst case approach) 등과 비교하여 그 타당성을 검증하였다.

• Earthquakes and Structures
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• 제1권1호
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• pp.109-127
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• 2010

This work aims at introducing structural sensitivity analysis capabilities into existing commercial finite element software codes for the purpose of mapping retrofit strategies for a broad group of structures including heritage-type buildings. More specifically, the first stage sensitivity analysis is implemented for the standard deterministic environment, followed by stochastic structural sensitivity analysis defined for the probabilistic environment in a subsequent, second phase. It is believed that this new generation of software that will be released by the industrial partner will address the needs of a rapidly developing specialty within the engineering design profession, namely commercial retrofit and rehabilitation activities. In congested urban areas, these activities are carried out in reference to a certain percentage of the contemporary building stock that can no longer be demolished to give room for new construction because of economical, historical or cultural reasons. Furthermore, such analysis tools are becoming essential in reference to a new generation of national codes that spell out in detail how retrofit strategies ought to be implemented. More specifically, our work focuses on identifying the minimum-cost intervention on a given structure undergoing retrofit. Finally, an additional factor that arises in earthquake-prone regions across the world is the random nature of seismic activity that further complicates the task of determining the dynamic overstress that is being induced in the building stock and the additional demands placed on the supporting structural system.

• 전산구조공학
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• 제4권2호
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• pp.111-117
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• 1991

구조 공학에서의 고유치 문제는 좌굴해석, 진동해석 등 여러분야에 응용되고 있다. 일반적으로 구조물의 좌굴강도 해석에 사용되는 대부분의 변수들은 불확실성을 내포하고 있으므로 확률론적 해석을 수행해야 하지만, 구조물의 좌굴 신뢰성 해석을 위한 극한상태 방정식은 확률변수의 함수로 명확히 표현되지 않으므로 확률 유한 요소법의 사용이 필요하다. 따라서 본 논문에서는 직접미분법에 의해 정식화된 확률 유한요소법을 사용하여 고유치 문제의 신뢰성 해석방법을 정식화 하고, 이를 바탕으로 좌굴 신뢰성 해석을 수행하였으며, 결과의 타당성을 검증하기 위하여 Crude Monte Carlo Method 및 이 방법의 단점을 대폭 보완한 Importance Sampling Method를 사용하였다. 본 논문에 의해 좌굴 신뢰성 해석 방법이 정립됨으로서 신뢰성에 기초한 최적 설계를 수행하는 경우, 시스템 파괴확률로서 소성 파괴확률과 더불어 좌굴 파괴확률의 고려가 가능해졌다.

• Structural Engineering and Mechanics
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• 제55권3호
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• pp.461-472
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• 2015

The existence of initial imperfections in manufacturing or assembly of double-layer space structures having hundreds or thousands of members is inevitable. Many of the imperfections, such as the initial curvature of the members and residual stresses in members, are all random in nature. In this paper, the probabilistic effect of initial curvature imperfections in the load bearing capacity of double-layer grid space structures with different types of supports have been investigated. First, for the initial curvature imperfection of each member, a random number is generated from a gamma distribution. Then, by employing the same probabilistic model, the imperfections are randomly distributed amongst the members of the structure. Afterwards, the collapse behavior and the ultimate bearing capacity of the structure are determined by using nonlinear push down analysis and this procedure is frequently repeated. Ultimately, based on the maximum values of bearing capacity acquired from the analysis of different samples, structure's reliability is obtained by using Monte Carlo simulation method. The results show the sensitivity of the collapse behavior of double-layer grid space structures to the random distribution of initial imperfections and supports type.

• 대한기계학회논문집
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• 제14권1호
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• pp.138-144
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• 1990

본 연구에서는 피로크랙 진전수명에 대하여 대단히 중요한 초기 크랙 길이 분 포 및 타 파라마터의 크랙 진전수명에 미치는 영향을 폭넓게 논함과 동시에 또 이러한 영향을 손쉽게 예측할 수 있는 실용적 근사식을 제시하는 것이다.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2003년도 제2차 연례학술대회 발표논문집
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• pp.7-16
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• 2003

In this paper, we propose a probabilistic framework to predict the interaction probability of proteins. The notion of domain combination and domain combination pair is newly introduced and the prediction model in the framework takes domain combination pair as a basic unit of protein interactions to overcome the limitations of the conventional domain pair based prediction systems. The framework largely consists of prediction preparation and service stages. In the prediction preparation stage, two appearance pro-bability matrices, which hold information on appearance frequencies of domain combination pairs in the interacting and non-interacting sets of protein pairs, are constructed. Based on the appearance probability matrix, a probability equation is devised. The equation maps a protein pair to a real number in the range of 0 to 1. Two distributions of interacting and non-interacting set of protein pairs are obtained using the equation. In the prediction service stage, the interaction probability of a protein pair is predicted using the distributions and the equation. The validity of the prediction model is evaluated fur the interacting set of protein pairs in Yeast organism and artificially generated non-interacting set of protein pairs. When 80% of the set of interacting protein pairs in DIP database are used as foaming set of interacting protein pairs, very high sensitivity(86%) and specificity(56%) are achieved within our framework.

• 한국지진공학회논문집
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• 제2권3호
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• pp.83-86
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• 1998

The results from the Individual Plant Examination of External Event of Yonggwyang nuclear power plants, unit 3 & 4, in Korea have shown that the high degree of diversities of the experts' opinions on seismicity and attenuation models is su, pp.sed to be generic cause of uncertainty of APEs(annual exceedance probability) in the PAHA(probabilistic seismic hazard analysis). This study investigated the sensitivity of the focal depth, which is one of the most uncertain seismicity parameters in Korea, Significant differences in resultant values of annual exceedance probabilities and much more symmetrical shape of the resultant PDFs(probability density functions), in case of consideration of focal depth, are found. These two results suggest that, even for the same seismic input data set including the seismicity models and ground motion attenuation models, to consider focal depth additionally for probabilistic seismic hazard analysis evaluation makes significant influence on the distributions of uncertainties and probabilities of exceedance per year for the whole ranges of seismic hazard levels. These facts suggest that it is necessary to derive focal depth parameter more effectively from the historical and instrumental documents on earthquake phenomena in Koran Peninsula for the future study of PSHA.

• Nuclear Engineering and Technology
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• 제33권5호
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• pp.468-482
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• 2001

As a process of Direct Containment Heating (DCH) issue resolution for Korean Standard Nuclear Power Plants (KSNPs), a containment load/strength assessment with two different approaches, the probabilistic and the deterministic, was performed with all plant-specific and phenomena-specific data. In case of the probabilistic approach, the framework developed to support the Zion DCH study, Two-Cell Equilibrium (TCE) coupled with Latin Hypercubic Sampling (LHS), provided a very efficient tool to resolve DCH issue. In case of the deterministic approach, the evaluation methodology using the sophisticated mechanistic computer code, CONTAIN 2.0 was developed, based on findings from DCH-related experiments or analyses. For three bounding scenarios designated as Scenarios V, Va, and VI, the calculation results of TCE/LHS and CONTAIN 2.0 with the conservatism or typical estimation for uncertain parameters, showed that the containment failure resulted from DCH loads was not likely to occur. To verify that these two approaches might be conservative , the containment loads resulting from typical high-pressure accident scenarios (SBO and SBLOCA) for KSNPs were also predicted. The CONTAIN 2.0 calculations with boundary and initial conditions from the MAAP4 predictions, including the sensitivity calculations for DCH phenomenological parameters, have confirmed that the predicted containment pressure and temperature were much below those from these two approaches, and, therefore, DCH issue for KSNPS might be not a problem.

• BMB Reports
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• 제37권6호
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• pp.648-656
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• 2004

This paper deals with the development of a predictive probabilistic model, a composite dependency-reflecting model (CDRM), which was designed to detect core promoter regions and transcription start sites (TSS) in vertebrate genomic DNA sequences, an issue of some importance for genome annotation. The model actually represents a combination of first-, second-, third- and much higher order or long-range dependencies obtained using the expanded maximal dependency decomposition (EMDD) procedure, which iteratively decomposes data sets into subsets on the basis of dependency degree and patterns inherent in the target promoter region to be modeled. In addition, decomposed subsets are modeled by using a first-order Markov model, allowing the predictive model to reflect dependency between adjacent positions explicitly. In this way, the CDRM allows for potentially complex dependencies between positions in the core promoter region. Such complex dependencies may be closely related to the biological and structural contexts since promoter elements are present in various combinations separated by various distances in the sequence. Thus, CDRM may be appropriate for recognizing core promoter regions and TSSs in vertebrate genomic contig. To demonstrate the effectiveness of our algorithm, we tested it using standardized data and real core promoters, and compared it with some current representative promoter-finding algorithms. The developed algorithm showed better accuracy in terms of specificity and sensitivity than the promoter-finding ones used in performance comparison.